Thermal modeling for cables transmitting data and power

Information

  • Patent Grant
  • 11519789
  • Patent Number
    11,519,789
  • Date Filed
    Wednesday, September 16, 2020
    4 years ago
  • Date Issued
    Tuesday, December 6, 2022
    2 years ago
Abstract
In one embodiment, a method includes receiving at a thermal modeling module, data from a Power Sourcing Equipment device (PSE) for cables extending from the PSE to Powered Devices (PDs), the cables configured to transmit power and data from the PSE to the PDs, calculating at the thermal modeling module, thermal characteristics for the cables based on the data, and identifying a thermal rise above a specified threshold at one of the cables. The data comprises real-time electrical data for the cables. An apparatus and logic are also disclosed herein.
Description
TECHNICAL FIELD

The present disclosure relates generally to communications networks, and more particularly, to thermal modeling for cables transmitting power and data communications.


BACKGROUND

Communications cables that are used to deliver power and data simultaneously may encounter self-heating due to a combination of currents carried in the cables, how the cables are installed (e.g., cable bundling), and what type of cables are used. Heat generation in cable bundles is an issue that can greatly affect performance and cause damage to a cable plant.





BRIEF DESCRIPTION OF THE DRAWINGS


FIG. 1 illustrates an example of a network in which embodiments described herein may be implemented.



FIG. 2 depicts an example of a network device useful in implementing embodiments described herein.



FIG. 3 is a flowchart illustrating an overview of a process for thermal modeling of cables, in accordance with one embodiment.



FIG. 4 illustrates detection of cable adjacencies, in accordance with one embodiment.



FIG. 5 illustrates detection of cable adjacencies, in accordance with another embodiment.



FIG. 6 illustrates use of a TDR (Time Domain Reflectometer) to determine cable length and health, in accordance with one embodiment.



FIG. 7 illustrates an example of a risk assessment table providing cable thermal status, in accordance with one embodiment.



FIG. 8 illustrates an example of a risk assessment table providing cable thermal status, in accordance with another embodiment.



FIG. 9 illustrates an example of a risk assessment table providing cable thermal status, in accordance with another embodiment.



FIG. 10 illustrates a graphical view providing risk assessment and cable thermal status, in accordance with one embodiment.





Corresponding reference characters indicate corresponding parts throughout the several views of the drawings.


DESCRIPTION OF EXAMPLE EMBODIMENTS
Overview

In one embodiment, a method generally comprises receiving at a thermal modeling module, data from a Power Sourcing Equipment device (PSE) for cables extending from the PSE to Powered Devices (PDs), the cables configured to transmit power and data from the PSE to the PDs, calculating at the thermal modeling module, thermal characteristics for the cables based on the data, and identifying a thermal rise above a specified threshold at one of the cables. The data comprises real-time electrical data for the cables.


In another embodiment, an apparatus generally comprises an interface for receiving data from a Power Sourcing Equipment device (PSE) for cables extending from the PSE to Powered Devices (PDs), the cables configured to transmit power and data from the PSE to the PDs, the data comprising real-time electrical data for the cables, a processor for calculating thermal characteristics for the cables based on the data and identifying a thermal rise above a specified threshold at one of the cables, and memory for storing wire gauges and associated cable temperature ratings.


In yet another embodiment, logic is encoded on one or more non-transitory computer readable media for execution and when executed by a processor operable to process data from a Power Sourcing Equipment device (PSE) for cables extending from the PSE to Powered Devices (PDs), the cables configured to transmit power and data from the PSE to the PDs, the data comprising real-time electrical data for the cables, calculate thermal characteristics for the cables based on the data, and identify a thermal rise above a specified threshold at one of the cables.


EXAMPLE EMBODIMENTS

The following description is presented to enable one of ordinary skill in the art to make and use the embodiments. Descriptions of specific embodiments and applications are provided only as examples, and various modifications will be readily apparent to those skilled in the art. The general principles described herein may be applied to other applications without departing from the scope of the embodiments. Thus, the embodiments are not to be limited to those shown, but are to be accorded the widest scope consistent with the principles and features described herein. For purpose of clarity, details relating to technical material that is known in the technical fields related to the embodiments have not been described in detail.


In systems used to simultaneously transmit power and data communications (e.g., Power over Ethernet (PoE), Power over Fiber (PoF), and the like), cable heating may degrade the reliability of the communications signals that are carried over the cables and damage the cable plant. Cable plant damage is often a direct result of thermal stress occurring in unattended or non-visible locations. In some cases, powered devices may still operate on a thermally stressed cable with uncertain operation, thereby leaving a user confused as to how to debug the system. High temperatures may also lead to higher power costs due more power dissipated in the cables. In conventional systems, visible inspection may be needed to comply with standards (e.g., NEC (National Electrical Code), IEEE (Institute of Electrical and Electronics Engineers) 802.3) and determine the operational ability of the cable plant between the power source equipment and the powered devices. Many instances of failure may be missed or ignored. As PoE standards allow for higher power transmissions, temperature concerns are expected to become more prevalent.


The embodiments described herein provide real-time thermal modeling in cables that are used to carry data and power simultaneously. Real-time measurements provide an accurate and up-to-date analysis of a cable plant health assessment. The embodiments may be used, for example, to identify power and thermal impact due to self-heating and provide alerts for possible over heat conditions. One or more embodiments may be used to limit power output based on the modeling or prevent modes that may result in unwanted cable behavior such as heat damage to the cable or other unintended consequences. As described in detail below, one or more embodiments may collect cable heating factors (e.g., current carried in cable, cable type, cable installation, etc.) and use this data to model expected temperature rises and other health assessment characteristics in the cables to determine if the cable can handle the power level and if the integrity of the data carried across the cable is at risk.


Referring now to the drawings, and first to FIG. 1, an example of a network in which embodiments described herein may be implemented is shown. The embodiments operate in the context of a data communications network including multiple network devices. The network may include any number of network devices in communication via any number of nodes (e.g., routers, switches, gateways, controllers, or other network devices), which facilitate passage of data within the network. The network devices may communicate over or be in communication with one or more networks (e.g., local area network (LAN), metropolitan area network (MAN), wide area network (WAN), virtual private network (VPN) (e.g., Ethernet virtual private network (EVPN), layer 2 virtual private network (L2VPN)), virtual local area network (VLAN), enterprise network, corporate network, data center, Internet, intranet, or any other network).


The network may be configured for Power over Ethernet (PoE), Power over Fiber (PoF), or any other power over communications cable system that is used to pass electric power along with data to allow a single cable to provide both data connectivity and electric power to network devices such as wireless access points, IP (Internet Protocol) cameras, VoIP (Voice over IP) phones, video cameras, point-of-sale devices, security access control devices, residential devices, building automation, industrial automation, and many other devices. Signals may be exchanged among communications equipment and power transmitted from power sourcing equipment to powered devices.


As shown in the simplified example of FIG. 1, the network may include a Power Sourcing Equipment device (PSE) 10 in communication with any number of Powered Devices (PDs) 12 via cables 14. The PSE may be a network device such as a switch that provides (sources) power on the cable 14. The PSE 10 may be configured to delivery power at one or more output levels (e.g., programmable PoE). The network may include any number of PSEs 10 in communication with any number of PDs 12. The PD 12 is powered by the PSE 10 and consumes energy.


The cables 14 are configured to transmit both power and data from the PSE 10 to the PDs 12. The cables 14 may be formed from any material suitable to carry both power and data (e.g., copper, fiber). The cables 14 may comprise, for example Catx cable (e.g., category 5 twisted pair (e.g., four pair) Ethernet cabling) or any other type of cable. The cables 14 may extend between the PSE 10 and PDs 12 at a distance, for example, of 10 meters, 100 meters, or any other length. The cables 14 may be arranged in any configuration. For example, the cables 14 may be bundled together in one or more groups 13 or stacked in one or more groups 15 as shown schematically in cross-section in FIG. 1. Any number of cables 14 may be bundled together. The cables 14 may have a round, flat, oval, or any other cross-sectional shape and may include any number or type of conductors (e.g., solid or stranded wires). The cables 14 may be bundled together at one location 16 while not bundled together at another location 17, for example.


The cable 14 may be rated for one or more power levels, a maximum power level, a maximum temperature, or identified according to one or more categories indicating acceptable power level usage, for example. In one example, the cables 14 correspond to a standardized wire gauge system such as AWG (American Wire Gauge). For different gauge wire, AWG provides data including diameter, area, resistance per length, ampacity (maximum amount of current a conductor can carry before sustaining immediate or progressive deterioration), and fusing current (how much current it takes to melt a wire in free air). Various other standards (e.g., NEC (National Electrical Code), UL (Underwriters Laboratories)) may be used to provide various requirements for the cable and cable system and provide temperature ratings or limits, or other information. This data may be stored in a thermal modeling system for reference in providing a cable thermal status, as described below.


As noted above, the cables 14 may encounter self-heating. For example, when power is added to twisted-pair cables, the copper conductors generate heat and temperatures rise. A thermal modeling module 18 is configured to model the thermal impact due to self-heating. In one or more embodiments, the thermal modeling module 18 is located at a network device 19, which may be located at a Network Operations Center (NOC), for example. The network device 19 may comprise, for example, a network management station, controller, computer, or any other device. The network device 19 is in communication with the PSE 10 and may also communicate with one or more PDs 12 directly or through the PSE. The thermal modeling module 18 (e.g., code, software, logic, firmware, application, client, appliance, hardware, device, element) may also be distributed across any number of network devices or operate in a cloud environment. Also, the thermal modeling module 18 or one or more components of the module may be located at the PSE 10, as shown in FIG. 1.


The PSE 10 may measure one or more variables used for thermal modeling calculations at the PSE or at the network device 19. For example, the PSE 10 may measure cable length using a TDR (Time Domain Reflectometer), output voltage at PSE, and current (e.g., for individual conductors). In one or more embodiments, the PSE 10 may also collect intelligent PD available statistics for reporting input voltage at the PD. One or more calculations may be made at the PSE 10 or at the remote network device 19 based on measurements made at the PSE.


The thermal modeling module 18 may collect data including, for example, cable AWG, real-time current carried in the conductors of the cables (nominal or maximum current), voltage (output at PSE, input at PD), cable length, cable segment length, number of PSE ports, cable proximity to other cables carrying currents that can act as localized heat sources, maximum expected ambient temperature where cables are routed, maximum temperature rating of the cable, temperature at PD, or any combination of this data or other data. Various measurements may be used to gather real-time data and user input may also be provided for one or more parameters (e.g., cable type, cable installation configuration, number of ports) if not available. The thermal modeling module 18 may use this data to determine the operational maximum power (maximum safe available power for delivery on the PSE port), thermal characteristics (real-time temperature rise in cables), overall health of an end-to-end cable 14, a bundle of those end-to-end cables, and a bundle encompassing bundles of cable bundles, and if a cable is safe for operation by the attached PD 12.


As described in detail below, the thermal modeling module 18 may calculate real-time localized heating in a cable plant and generate a cable plant risk assessment (e.g., spreadsheet, graphical image) and alarm states to minimize unsafe operation. In one or more embodiments, the thermal modeling module 18 may provide an alarm state or syslog (system log) message, as well as prevent delivery of more power than is safely determined for a particular cable. For example, the thermal modeling module 18 may warn a user of potential heating issues and power concerns that may compromise the cable plant, data integrity of the communications channel, and PD operation.


In one or more embodiments, the network device 19 may include a GUI (Graphical User Interface) 11 for receiving user input and presenting results of the thermal modeling to the user. As described below, the GUI 11 may be used to display a risk assessment table or graphical image indicating the thermal rise, health status, or other information about the cables and cable plant.


It is to be understood that the network devices and topology shown in FIG. 1 and described above are only examples and the embodiments described herein may be implemented in networks comprising different network topologies or network devices, or using different protocols or cables, without departing from the scope of the embodiments. For example, the network may comprise any number or type of network devices that facilitate passage of data over the network (e.g., routers, switches, gateways, controllers), network elements that operate as endpoints or hosts (e.g., servers, virtual machines, clients), and any number of network sites or domains in communication with any number of networks. Thus, network nodes may be used in any suitable network topology, which may include any number of servers, virtual machines, switches, routers, or other nodes interconnected to form a large and complex network, which may include cloud or fog computing. Nodes may be coupled to other nodes or networks through one or more interfaces employing any suitable wired or wireless connection, which provides a viable pathway for electronic communications.



FIG. 2 illustrates an example of a network device 20 that may be used to implement the embodiments described herein. In one embodiment, the network device 20 is a programmable machine that may be implemented in hardware, software, or any combination thereof. The network device 20 includes one or more processors 22, memory 24, network interface (port) 26, and thermal modeling module 28.


Memory 24 may be a volatile memory or non-volatile storage, which stores various applications, operating systems, modules, and data for execution and use by the processor 22. For example, components of the thermal modeling module 28 (e.g., code, logic, firmware, etc.) may be stored in the memory 24. Memory 24 may also store manually input data (e.g., wire gauges and associated cable temperature ratings, measurements, calculated data, or other data, tables, or graphs. The network device 20 may include any number of memory components.


Logic may be encoded in one or more tangible media for execution by the processor 22. For example, the processor 22 may execute codes stored in a computer-readable medium such as memory 24. The computer-readable medium may be, for example, electronic (e.g., RAM (random access memory), ROM (read-only memory), EPROM (erasable programmable read-only memory)), magnetic, optical (e.g., CD, DVD), electromagnetic, semiconductor technology, or any other suitable medium. In one example, the computer-readable medium comprises a non-transitory computer-readable medium. Logic may be used to perform one or more functions described below with respect to the flowchart of FIG. 3. The network device 20 may include any number of processors 22.


The network interface 26 may comprise any number of interfaces (linecards, ports) for receiving data or transmitting data to other devices. The interface may be, for example, an interface at the PSE 10 for transmitting power and data to the PD 12, an interface at the PSE for transmitting measurements, data, or risk assessment information to the network device 19, or an internal interface at the PSE 10 for transmitting data to the thermal modeling module 18 (FIGS. 1 and 2). The network interface 26 may include, for example, an Ethernet interface for connection to a computer or network. The interface 26 may be configured for PoE, PoF, or similar operation.


It is to be understood that the network device 20 shown in FIG. 2 and described above is only an example and that different configurations of network devices may be used. For example, the network device 20 may further include any suitable combination of hardware, software, algorithms, processors, devices, components, or elements operable to facilitate the capabilities described herein.



FIG. 3 is a flowchart illustrating an overview of a process for modeling thermal characteristics of cables used to transmit power and data, in accordance with one embodiment. At step 30, the thermal modeling module 18 receives real-time electrical data (e.g., real-time measurements of relevant parameters) from the PSE 10 (FIGS. 1 and 3). In one embodiment, data is extracted from the PSE 10, which may include data from the PDs 12. User input may be received if an intelligent PD is not available. The thermal modeling module 18 identifies cable adjacencies and characteristics (step 32). In one embodiment, the PSE 10 may use a TDR to determine the cable length at each port. The thermal modeling module 18 may use voltage, current, and cable length to determine wire gauge using a calculated resistance. If the PD 12 is not able to provide V_in (voltage at PD), the wire gauge may be provided by user input. As described below, cable adjacencies (e.g., arrangement of cables within a bundle, bundle size) may be identified by transmitting a pulse at the PSE 10 and then measuring an E field (pulsed field strength) at surrounding cables 14 to detect adjacent cables. The thermal modeling module 18 may use the wire gauge data, cable adjacencies, and current, voltage, and power data to calculate thermal characteristics for the cables (step 34). The thermal characteristics may include, for example, thermal rise, maximum power, and overall end-to-end cable health. If a thermal rise at one of the cables exceeds a specified threshold (step 36), the thermal modeling module 18 may take action to reduce the risk of unsafe operation at the cable (step 38). This may include, for example, identifying the cable in a risk assessment table, graphical image, alert, alarm, message, or other indication presented to a user, or preventing operation of the port connected to the cable. The thermal modeling module 18 may, for example, generate a table or image to indicate cable health for a selected power level and environment for a cable or bundle of cables, as well as generate alarm states (e.g., lights) and messages (e.g., syslog). The thermal rise may refer to a specific temperature, delta temperature, change in temperature (e.g., percent or increase above a baseline temperature), or a rise in temperature over a period of time.


It is to be understood that the process shown in FIG. 3 and described above is only an example and that steps may be added, removed, or combined, without departing from the scope of the embodiments.


The following provides examples for determining wire gauge, bundle size, and cable adjacencies, and presenting data and thermal modeling results to a user.


In one or more embodiments, wire gauge calculations may be made using V_out (voltage at port of PSE), V_in (voltage at PD), I_individual_cable (current of cable), and TDR_m (cable length). In one example, calculations are performed assuming no connector loss. The resistance calculations may be performed as follows:

R_individual conductor=(V_out−V_in)/I_individual conductor; and
R_mOhm/m=(R_individual_conductor/TDR_m)×1000.

R_mOhm/m may be used to determine the AWG for the conductor.


The user may enter the basic wire gauge for the assessment calculations if there is not an intelligent PD to provide V_in.



FIG. 4 illustrates an example of a PSE 40 that may be used to provide measurements for use in automatically calculating cable adjacency. In the example shown in FIG. 4, the PSE 40 includes two PHY (circuitry for physical layer functions) each having a SerDes 41 (Serializer/Deserializer), a signal receiver 44, and a signal generator 46. The PSE 40 may comprise any number of ports and corresponding components. In one embodiment, a 1 MHz (or any other frequency) pulse is transmitted by the signal generator 46. The pulse is used to automatically determine cable to cable proximity by calculating a measured field strength (E Field 48) at the receiver 44. The pulse may be used to track a cable tied to a particular port or switch within a cable bundle referenced to the transmitting port. The pulse may be used, for example within a switch or router during bring up. The 1 MHz pulse cannot be used to determine cable proximity between switches in a network or in a situation wherein a data center is running production traffic and a new switch or new cable plant is added. In this case, a packet pulse generator may be used as shown in FIG. 5.



FIG. 5 illustrates a plurality of PSEs 50a, 50b, 50c, 50d, 50e, with one or more PSEs configured as a packet pulse generator for use in automatically calculating cable adjacency and bundle size determination, in accordance with one embodiment. The PSE includes a SerDes 51, signal receiver 54 and signal generator 56, as previously described. The PSEs may communicate with one another over an Ethernet command port communications plane or over a data plane, for example. The packet pulse generator is a specific packet type (packet 55 in FIG. 5) transmitted instead of idle packets and with a higher energy content achieved by increasing the transmitted signal. The packet 55 is detected and the receiver 54 calculates the cable to cable distance based on the field strength (E Field 58). In the example shown in FIG. 5, PSE 50b generates the packet 55 and the field strength 58 is measured by PSE 50a. The packet pulse generator allows the equipment and cable plant to change over time with constant (or periodic) updates to the cable-to-cable adjacency within the data center or office environment.


In one embodiment, the packet pulse generator carries switch IP (Internet Protocol) address and port ID (identifier) so that adjacent switches in the data center can identify where the packet is sourced from and return the received calculation for each port on the switch receiving or recognizing the packet. In one example, the packet 55 includes the source equipment IP address (e.g., IP address for Ethernet console port or command control panel), source equipment definition (e.g., what kind of switching or routing equipment), source port (e.g., port number, port power capability, port speed capability), signal data definition (e.g., data packet type (FFFF0000, FF00, AA55, etc.)), and data (e.g., as many bytes as possible of the signal data definition).


The pulsing and high frequency tests described above may be used to detect cable architecture (e.g., cable bundling, cable adjacency, bundle size) and basic dielectric calculations may be used to determine cable insulation type. In one example for a 96 port switch, a source wire pulse may be transmitted on one port and the pulse field strength measured on 95 ports. This process may be repeated through 96 ports or a fewer number of ports. In another example, a pulse may be sent on only a portion of the ports until an arrangement of the cables is identified. The cable bundling may be determined by using field strength measurements to determine cable location and cable adjacency. For example, finite element analysis and a convergence algorithm may be used to determine cable-to-cable proximity. In order to detect shielded foil, the pulse strength may be increased on a closest pair to determine if a change indicates shielded or not shielded. The measured field strength will increase with a smaller factor with a shielded cable. An algorithm output may be used to determine the proximity of cables and build a table.


It is to be understood that the methods and systems described above for determining cable adjacency and bundle characteristics are only examples and that other devices or methods may be used without departing from the scope of the embodiments. Also, if bundle characteristics are known, this information may be manually input to the thermal modeling system. In one or more embodiments, both the 1 MHz pulse and packet pulse generator may be used to determine cable adjacencies. For example, the 1 MHz pulse may be used during bring up and the packet pulse generator used for periodic updates.



FIG. 6 illustrates an embodiment that may be used to determine cable length and health. In the example shown in FIG. 6, PSE 60 includes a SerDes 61, signal receiver 64, TDR (Time Domain Reflectometer) 65, and signal generator 66. The TDR 65 may be used to determine the cable length for any port, which may be used to calculate wire gauge (e.g., AWG). If the voltage at the PD 12 is known by the PSE 60, this may be used in conjunction with cable length to determine cable AWG per port, as previously described. The TDR 65 may also be used to evaluate and determine the cable segments and connection quality. When the PHY detects a cable is connected, a TDR process may be performed to determine the basic cable layout. TDR data may provide, for example, cable length and maximum loss, number of cable segments (length of cable segments and loss per segment, connector count and loss), and identification of cable anomalies. During a TDR process, a cable health assessment may be performed based on losses in the cable. The health assessment may determine the relative loss at each segment (conductor in a particular length of cable) and at each segment point (e.g., RJ45 connector or other type of connector). Using the defined wire gauge calculations, each cable segment in the entire cable length may be evaluated for maximum conductor current. Each connector may be evaluated for its ability to handle the port conductor current. The health assessment along with overall wire gauge calculations may be used to determine the maximum conductor current of an end-to-end cable. In one embodiment, transmit and receive equalization sequences or channel operating margin may be used in place of TDR.


As shown in FIGS. 7, 8, and 9, tables 70, 80, and 90 may be created from automatically generated data, manually entered data, and calculations. The table 70 shown in FIG. 7 is based on smart PDs, which are configured to measure their input port voltage. The table 80 shown in FIG. 8 is based on a Vpd calculated by the PSE. The table 90 shown in FIG. 9 is based on smart PDs and automatically gathered cable bundle information.


Referring first to FIG. 7, for each port at the PSE 10 (e.g., 1-24), the table 70 includes Vpse (V_out), Iport (I_individual_cable), Pport (power_port), Vpd (V_in), TDR (length), Cable AWG (wire gauge), Cable Temp Rating, Bundle (bundle containing cable (e.g., A, B)), Pcable (calculated power dissipated by (or in) the cable), Thermal Rise, and Cable Thermal Status. The PSE 10 measures Iport, Vpse, Pport, and TDR (to determine cable length) (FIGS. 1 and 7). The PSE 10 measures the real-time current in the cable and the real-time output voltage at the PSE. In one or more embodiments, the PD 12 measures its port voltage and sends it to the PSE 10 via Layer 2. The user may input the cable temperature rating for each AWG, and the bundle in which the cable is located. This information may be input at the GUI 11 at the network operations center device 19, for example, and stored at the thermal modeling module 18. The thermal modeling module 18 (at PSE 10 or network device 19) calculates Pcable based on a combination of Iport and Vpd. The thermal rise may be calculated based on Iport and bundle size. The thermal rise calculations may take into account, for example, cable characteristics (e.g., gauge, area, length, material, insulation type), location (e.g., cable adjacency, bundle location, bundle size), electrical characteristics (e.g., current, voltage, resistance, power), thermal properties (e.g., conductive and convective properties of cable, environment (air gaps, bundling contact, maximum expected ambient temperature at location of cable routing)), or any combination of these or other variables.


The cable thermal status is based on the calculated thermal rise and maximum temperature rating of the cable and may be represented, for example, as a color (e.g., green (safe operating condition), yellow (approaching unsafe operating condition), red (unsafe operating condition)) based on a specified limit or threshold. The threshold may be based on standard temperature limits for the cable or may be user defined. Cable health may be determined based on an expected Pcable based on Iport, Vport, and TDR as compared to Pcable calculated using Vpd.


Referring now to FIG. 8, the table 80 shows an example of a risk assessment table for a system in which the PDs are not configured to measure port voltage and provide Vpd. The Vpd column in table 80 is moved from the automatically gathered data (in table 70) to the calculated data. As previously described, the PSE 10 measures Iport, Vport, Pport, and TDR (to measure cable length). A user may input AWG of cable conductors, the cable temperature rating, and the bundle containing the cable. The thermal modeling module 18 (at PSE or other network device 19) may calculate: Vpd based on Iport, Vport, cable length, and AWG; Pcable based on combination of Iport and Vpd; and thermal rise based on Iport and bundle size. The cable thermal status is based on thermal rise and may be indicated as green, yellow, or red, as described above. The cable health cannot be determined without the help of the PD.


The table 90 in FIG. 9 illustrates an automated case in which the smart PDs provide the port voltage (Vpd) and the PSE uses a signal or packet pulse (as described above with respect to FIGS. 4 and 5) to automatically determine cable bundle configuration. In this example, data including Vpse, Iport, Pport, Vpd, TDR, Cable AWG, and Bundle information is automatically gathered. The cable power (Pcable) and resulting thermal rise are calculated. As previously described, a cable thermal status column is provided to indicate the health of the cable based on thermal rise thresholds.


It is to be understood that the tables 70, 80, and 90 shown in FIGS. 7, 8, and 9, respectively, are only examples and that different columns or data may be included or different formats used without departing from the scope of the embodiments. Also, as described above, different data may be automatically gathered or calculated based on system configuration or capability of the devices.



FIG. 10 illustrates an example of a customer risk assessment graphical image 100. In this example, an indication is provided for each cable with respect to the risk/health assessment table. As shown in FIG. 10, one cable is identified as “Health: Good, 22AGW, P_c=2.3 W, Trise=6 deg C.” and another cable is identified as “Health: max current exceeded, 24AGW, P_c=10.2 W, Trise=12 deg C.”. The graphical view 100 shown in FIG. 10 may be available on a customer screen (e.g., GUI 11 at network operations center device 19 in FIG. 1) or on an equipment display screen.


It is to be understood that the tables 70, 80, 90 shown in FIGS. 7, 8, and 9 and the graphical image 100 shown in FIG. 10 are only examples and that different data, more or less data, or any combination or presentation of data may be provided in the tables or shown in the graphical view. A GUI may allow a user to select how much information or details are presented and how they are presented (e.g., table, image). Also, the user may select to view only a portion of a cable plant, one or more cable plants, or only cables or cable plants with thermal or power issues.


In addition to (or in place of) the table 70, 80, 90 or schematic 100, the thermal modeling module 18 may transmit one or more alerts (alarm, message, syslog, etc.) when a specified threshold has been reached (e.g., thermal rise above a specified limit, maximum current or power exceeded in one or more cables). For example, the thermal modeling module 18 may determine or user input provided to define appropriate thresholds for allowable temperature rise in a cable for safe operation per port. In one example, a red cable thermal status may prevent the port from operating and a yellow cable thermal status may only allow the port to operate with user intervention. In one embodiment, the GUI may allow for a red override. The user may set the green/yellow/red threshold as appropriate for their cable plant configuration. In one embodiment, the thermal modeling module 18 may generate a flag based on worst case PD classification current. The alarm conditions may include, for example, a strict mode in which the PSE 10 monitors real-time PD currents and enforces a current limit (i.e., shuts down port when current limit is exceeded), and a non-strict mode in which the PSE monitors real-time PD currents and generates an alarm when a current limit is exceeded. The alarm and assessment information may be displayed, for example, on a system display panel or customer interface and provide an indication that attention is needed (e.g., blue attention LED (Light Emitting Diode), syslog message sent through the Ethernet control interface port to the network operations center).


As can be observed from the foregoing, the embodiments described herein may provide many advantages. For example, one or more embodiments may be used to prevent the unwanted heating of cables (e.g., individual cables, bundle of cables) in communications cables where power is delivered over the cables to a powered device. The calculations may be done at installation and continued in real-time during idle packet transfer of the communications circuit, for example. Alarm conditions, attention lights, LCD (Liquid Crystal Display), and messaging may be used to alert the end user in the event an unwanted amount of power beyond the ability of the cable and cable environment is requested by the PD. In one or more embodiments, the PSE port may automatically limit the power available for delivery based on the ability of the cable to safely deliver the required current, and thereby prevent serious damage to the cable plant, building, or user. The embodiments may be used, for example, by network engineers who manage networks with a significant deployment of PoE or PoF powered devices to provide a warning of deployment scenarios where the self-heating of cables could jeopardize the data integrity of the cables. The system may be used for long term planning in a cable plant, for example. One or more embodiments allow a network engineer to simply review the cable plant health assessment, which provides a more accurate assessment than may be provided with visual inspection and also saves a significant amount of time.


Although the method and apparatus have been described in accordance with the embodiments shown, one of ordinary skill in the art will readily recognize that there could be variations made to the embodiments without departing from the scope of the invention. Accordingly, it is intended that all matter contained in the above description and shown in the accompanying drawings shall be interpreted as illustrative and not in a limiting sense.

Claims
  • 1. A method comprising: receiving at a thermal modeling module, data from a PSE (Power Sourcing Equipment) for cables extending from the PSE to PDs (Powered Devices) and configured to transmit power and data from the PSE to the PDs;identifying cable adjacencies, the cable adjacencies including an arrangement of cables within a cable bundle and a size of the cable bundle;calculating at the thermal modeling module, thermal characteristics for the cables based on the data and said cable adjacencies; andidentifying a thermal rise above a specified threshold at one of the cables.
  • 2. The method of claim 1 wherein the data comprises voltage and current at ports of the PSE connected to the cables and wherein voltage at the PD is calculated at the thermal modeling module.
  • 3. The method of claim 1 further comprising identifying at the thermal modeling module a wire gauge of one or more of the cables based on measurements at the PSE and PD.
  • 4. The method of claim 1 wherein cable length is measured at the PSE using a time domain reflectometer.
  • 5. The method of claim 1 wherein identifying said cable adjacencies for one or more of the cables comprises detecting adjacent cables carrying current in the cable bundle and identifying a cable proximity to said adjacent cables.
  • 6. The method of claim 1 wherein identifying cable adjacencies comprises transmitting a pulse on one of the cables connected to the PSE and measuring a field strength at another one of the cables connected to a signal receiver at the PSE.
  • 7. The method of claim 1 wherein identifying cable adjacencies comprises measuring a field strength at one of the cables connected to the PSE based on a packet pulse transmitted on a cable connected to another PSE.
  • 8. The method of claim 1 further comprising limiting power output at a port of the PSE connected to the one of the cables identified as having said thermal rise above the specified threshold.
  • 9. The method of claim 1 further comprising generating a graphical image indicating a thermal status for one or more of the cables.
  • 10. The method of claim 1 further comprising generating a risk assessment table comprising the data and said thermal rise for each of the cables.
  • 11. The method of claim 4 wherein the cable length is used to calculate a wire gauge.
  • 12. Logic encoded on one or more non-transitory computer readable media for execution and when executed by a processor operable to: process data from a PSE (Power Sourcing Equipment) for cables extending from the PSE to PDs (Powered Devices), the cables configured to transmit power and data from the PSE to the PDs, the data comprising real-time electrical data for the cables;identify cable adjacencies, the cable adjacencies including an arrangement of cables within a cable bundle and a size of the cable bundle;calculate thermal characteristics for the cables based on the data and said cable adjacencies; andidentify real-time localized heating in a cable plant.
  • 13. An apparatus comprising: a memory;a network interface configured to enable network communication; anda processor, wherein the processor is configured to perform operations comprising:receiving data from a PSE (Power Sourcing Equipment) for cables extending from the PSE to PDs (Powered Devices) and configured to transmit power and data from the PSE to the PDs;identifying cable adjacencies, the cable adjacencies including an arrangement of cables within a cable bundle and a size of the cable bundle;calculating thermal characteristics for the cables based on the data and said cable adjacencies; andidentifying a thermal rise above a specified threshold at one of the cables.
  • 14. The apparatus of claim 13, wherein the data comprises voltage and current at ports of the PSE connected to the cables and wherein voltage at the PD is calculated at a thermal modeling module.
  • 15. The apparatus of claim 13, wherein the processor is configured to perform further operations comprising identifying a wire gauge of one or more of the cables based on measurements at the PSE and PD.
  • 16. The apparatus of claim 13, wherein cable length is measured at the PSE using a time domain reflectometer.
  • 17. The apparatus of claim 13, wherein the processor is further configured to perform the operation of identifying said cable adjacencies for one or more of the cables by detecting adjacent cables carrying current in the cable bundle and identifying a cable proximity to said adjacent cables.
  • 18. The apparatus of claim 13, wherein the processor is further configured to perform the operation of identifying cable adjacencies by transmitting a pulse on one of the cables connected to the PSE and measuring a field strength at another one of the cables connected to a signal receiver at the PSE.
  • 19. The apparatus of claim 13, wherein the processor is further configured to perform the operation of identifying cable adjacencies by measuring a field strength at one of the cables connected to the PSE based on a packet pulse transmitted on a cable connected to another PSE.
  • 20. The apparatus of claim 16, wherein the cable length is used to calculate a wire gauge.
STATEMENT OF RELATED APPLICATIONS

The present application is a continuation of U.S. patent application Ser. No. 15/604,344, entitled THERMAL MODELING FOR CABLES TRANSMITTING DATA AND POWER, filed on May 24, 2017, which is incorporated herein by reference in its entirety.

US Referenced Citations (234)
Number Name Date Kind
3335324 Buckeridge Aug 1967 A
3962529 Kubo Jun 1976 A
4811187 Nakajima Mar 1989 A
4997388 Dale et al. Mar 1991 A
5602387 Bowen Feb 1997 A
5652893 Ben-Meir Jul 1997 A
6008631 Johari Dec 1999 A
6220955 Posa Apr 2001 B1
6259745 Chan Jul 2001 B1
6636538 Stephens Oct 2003 B1
6685364 Brezina Feb 2004 B1
6784790 Lester Aug 2004 B1
6826368 Koren Nov 2004 B1
6855881 Khoshnood Feb 2005 B2
6860004 Hirano Mar 2005 B2
7188415 Robinson Mar 2007 B2
7325150 Lehr Jan 2008 B2
7420355 Liu Sep 2008 B2
7473849 Glew Jan 2009 B2
7490996 Sommer Feb 2009 B2
7492059 Peker Feb 2009 B2
7509505 Randall Mar 2009 B2
7566987 Black et al. Jul 2009 B2
7583703 Bowser Sep 2009 B2
7589435 Metsker Sep 2009 B2
7593747 Karam Sep 2009 B1
7603570 Schindler Oct 2009 B2
7616465 Vinciarelli Nov 2009 B1
7737704 Diab Jun 2010 B2
7813646 Furey Oct 2010 B2
7814346 Diab Oct 2010 B2
7835389 Yu Nov 2010 B2
7854634 Filipon Dec 2010 B2
7881072 DiBene Feb 2011 B2
7915761 Jones Mar 2011 B1
7921307 Karam Apr 2011 B2
7924579 Arduini Apr 2011 B2
7940787 Karam May 2011 B2
7973538 Karam Jul 2011 B2
8020043 Karam Sep 2011 B2
8035399 Diab Oct 2011 B2
8037324 Hussain Oct 2011 B2
8081589 Gilbrech Dec 2011 B1
8184525 Karam May 2012 B2
8276397 Carlson Oct 2012 B1
8279883 Diab Oct 2012 B2
8310089 Schindler Nov 2012 B2
8319627 Chan Nov 2012 B2
8344246 Lipiansky Jan 2013 B2
8345439 Goergen Jan 2013 B1
8350538 Cuk Jan 2013 B2
8358893 Sanderson Jan 2013 B1
8386820 Diab Feb 2013 B2
8638008 Baldwin et al. Jan 2014 B2
8700923 Fung Apr 2014 B2
8712324 Corbridge Apr 2014 B2
8750710 Hirt Jun 2014 B1
8768528 Millar et al. Jul 2014 B2
8781637 Eaves Jul 2014 B2
8787775 Earnshaw Jul 2014 B2
8829917 Lo Sep 2014 B1
8836228 Xu Sep 2014 B2
8842430 Hellriegel Sep 2014 B2
8849471 Daniel Sep 2014 B2
8966747 Vinciarelli Mar 2015 B2
9019895 Li Apr 2015 B2
9024473 Huff May 2015 B2
9184795 Eaves Nov 2015 B2
9189036 Ghoshal Nov 2015 B2
9189043 Vorenkamp Nov 2015 B2
9273906 Goth Mar 2016 B2
9319101 Lontka Apr 2016 B2
9321362 Woo Apr 2016 B2
9373963 Kuznelsov Jun 2016 B2
9419436 Eaves Aug 2016 B2
9484771 Braylovskiy et al. Nov 2016 B2
9510479 Vos Nov 2016 B2
9531551 Balasubramanian Dec 2016 B2
9590811 Hunter, Jr. Mar 2017 B2
9618714 Murray Apr 2017 B2
9640998 Dawson May 2017 B2
9665148 Hamdi May 2017 B2
9693244 Maruhashi Jun 2017 B2
9734940 McNutt Aug 2017 B1
9853689 Eaves Dec 2017 B2
9874930 Vavilala Jan 2018 B2
9882656 Sipes, Jr. Jan 2018 B2
9893521 Lowe Feb 2018 B2
9948198 Imai Apr 2018 B2
9979370 Xu May 2018 B2
9985600 Xu May 2018 B2
10007628 Pitigoi-Aron Jun 2018 B2
10028417 Schmidtke Jul 2018 B2
10128764 Vinciarelli Nov 2018 B1
10248178 Brooks Apr 2019 B2
10263526 Sandusky et al. Apr 2019 B2
10281513 Goergen et al. May 2019 B1
10407995 Moeny Sep 2019 B2
10439432 Eckhardt Oct 2019 B2
10541543 Eaves Jan 2020 B2
10541758 Goergen et al. Jan 2020 B2
10631443 Byers et al. Apr 2020 B2
10735105 Goergen et al. Aug 2020 B2
20010024373 Cuk Sep 2001 A1
20020126967 Panak Sep 2002 A1
20040000816 Khoshnood Jan 2004 A1
20040033076 Song Feb 2004 A1
20040043651 Bain Mar 2004 A1
20040073703 Boucher Apr 2004 A1
20040264214 Xu et al. Dec 2004 A1
20050197018 Lord Sep 2005 A1
20050268120 Schindler Dec 2005 A1
20060202109 Delcher Sep 2006 A1
20060209875 Lum Sep 2006 A1
20070103168 Batten May 2007 A1
20070143508 Linnman Jun 2007 A1
20070236853 Crawley Oct 2007 A1
20070263675 Lum Nov 2007 A1
20070284946 Robbins Dec 2007 A1
20070288125 Quaratiello Dec 2007 A1
20080004634 Farritor et al. Jan 2008 A1
20080054720 Lum et al. Mar 2008 A1
20080198635 Hussain Aug 2008 A1
20080229120 Diab Sep 2008 A1
20080310067 Diab Dec 2008 A1
20090027033 Diab Jan 2009 A1
20100052642 Diab Mar 2010 A1
20100077239 Diab Mar 2010 A1
20100117808 Karam May 2010 A1
20100171602 Kabbara Jul 2010 A1
20100190384 Lanni Jul 2010 A1
20100214708 Diab Aug 2010 A1
20100237846 Vetteth Sep 2010 A1
20100290190 Chester Nov 2010 A1
20100318819 Diab Dec 2010 A1
20110004773 Hussain Jan 2011 A1
20110007664 Diab et al. Jan 2011 A1
20110057612 Taguchi et al. Mar 2011 A1
20110083824 Rogers Apr 2011 A1
20110228578 Serpa Sep 2011 A1
20110266867 Schindler Nov 2011 A1
20110290497 Stenevik Dec 2011 A1
20120043935 Dyer et al. Feb 2012 A1
20120064745 Ottliczky Mar 2012 A1
20120170927 Huang Jul 2012 A1
20120201089 Barth Aug 2012 A1
20120231654 Conrad Sep 2012 A1
20120317426 Lee Nov 2012 A1
20120319468 Schneider Dec 2012 A1
20130077923 Weem Mar 2013 A1
20130079633 Weem Mar 2013 A1
20130103220 Eaves Apr 2013 A1
20130249292 Blackwell, Jr. Sep 2013 A1
20130272721 Van Veen Oct 2013 A1
20130329344 Tucker et al. Dec 2013 A1
20140111180 Vladan Apr 2014 A1
20140126151 Campbell et al. May 2014 A1
20140129850 Paul May 2014 A1
20140258742 Chien Sep 2014 A1
20140258813 Lusted et al. Sep 2014 A1
20140265550 Milligan Sep 2014 A1
20140372773 Heath Dec 2014 A1
20150049992 Bauco Feb 2015 A1
20150078740 Sipes, Jr. Mar 2015 A1
20150106539 Leinonen Apr 2015 A1
20150115741 Dawson Apr 2015 A1
20150207317 Radermacher et al. Jul 2015 A1
20150215001 Eaves Jul 2015 A1
20150215131 Paul Jul 2015 A1
20150333918 White, III Nov 2015 A1
20150340818 Scherer Nov 2015 A1
20160018252 Hanson Jan 2016 A1
20160020911 Sipes, Jr. Jan 2016 A1
20160064938 Balasubramanian Mar 2016 A1
20160111877 Eaves Apr 2016 A1
20160118784 Saxena Apr 2016 A1
20160133355 Glew May 2016 A1
20160134331 Eaves May 2016 A1
20160142217 Gardner May 2016 A1
20160188427 Chandrashekar et al. Jun 2016 A1
20160197600 Kuznetsov Jul 2016 A1
20160365967 Tu Jul 2016 A1
20160241148 Kizilyalli Aug 2016 A1
20160253436 Albero Sep 2016 A1
20160262288 Chainer Sep 2016 A1
20160273722 Crenshaw Sep 2016 A1
20160294500 Chawgo Oct 2016 A1
20160294568 Chawgo et al. Oct 2016 A1
20160308683 Pischl Oct 2016 A1
20160352535 Hiscock Dec 2016 A1
20170023756 Glew Jan 2017 A1
20170041152 Sheffield Feb 2017 A1
20170041153 Picard Feb 2017 A1
20170054296 Daniel Feb 2017 A1
20170110871 Foster Apr 2017 A1
20170123466 Carnevale May 2017 A1
20170146260 Ribbich May 2017 A1
20170155517 Cao Jun 2017 A1
20170164525 Chapel Jun 2017 A1
20170155518 Yang Jul 2017 A1
20170214236 Eaves Jul 2017 A1
20170229886 Eaves Aug 2017 A1
20170234738 Ross Aug 2017 A1
20170244318 Giuliano Aug 2017 A1
20170248976 Moller Aug 2017 A1
20170294966 Jia et al. Oct 2017 A1
20170325320 Wendt Nov 2017 A1
20180024964 Mao Jan 2018 A1
20180053313 Smith Feb 2018 A1
20180054083 Hick Feb 2018 A1
20180060269 Kessler Mar 2018 A1
20180088648 Otani Mar 2018 A1
20180098201 Torello Apr 2018 A1
20180102604 Keith Apr 2018 A1
20180123360 Eaves May 2018 A1
20180159430 Albert Jun 2018 A1
20180188712 MacKay Jul 2018 A1
20180191513 Hess Jul 2018 A1
20180254624 Son Sep 2018 A1
20180313886 Mlyniec Nov 2018 A1
20180340840 Bullock Nov 2018 A1
20190126764 Fuhrer May 2019 A1
20190267804 Matan Aug 2019 A1
20190272011 Goergen et al. Sep 2019 A1
20190277899 Goergen et al. Sep 2019 A1
20190277900 Goergen et al. Sep 2019 A1
20190278347 Goergen et al. Sep 2019 A1
20190280895 Mather Sep 2019 A1
20190304630 Goergen et al. Oct 2019 A1
20190312751 Goergen et al. Oct 2019 A1
20190342011 Goergen et al. Nov 2019 A1
20190363493 Sironi et al. Nov 2019 A1
20200044751 Goergen et al. Feb 2020 A1
20200153174 Curtis May 2020 A1
Foreign Referenced Citations (24)
Number Date Country
1209880 Jul 2005 CN
201689347 Dec 2010 CN
10359776 Feb 2014 CN
104698297 Jun 2015 CN
204836199 Dec 2015 CN
205544597 Aug 2016 CN
104081237 Oct 2016 CN
106165342 Nov 2016 CN
106249087 Dec 2016 CN
106465162 Feb 2017 CN
104412541 May 2019 CN
1936861 Jun 2008 EP
2120443 Nov 2009 EP
2257009 Dec 2010 EP
2432134 Mar 2012 EP
2693688 Feb 2014 EP
WO199316407 Aug 1993 WO
2006127916 Nov 2006 WO
WO2010053542 May 2010 WO
WO2017054030 Apr 2017 WO
WO2017167926 Oct 2017 WO
WO2018017544 Jan 2018 WO
WO2019023731 Feb 2019 WO
2019212759 Nov 2019 WO
Non-Patent Literature Citations (48)
Entry
Alexander C.K., “Fundamentals of Electric Circuits,” Indian Edition, Jan. 2013, 37 pages.(“Alexander”).
Cheng K.W.E., et al., “Constant Frequency, Two-Stage Quasiresonant Convertor,” Published in: IEE Proceedings B—Electric Power Applications, May 1, 1992, vol. 139, No. 03, pp. 227-237, XP000292493.
Eaves S.S., “Network Remote Powering Using Packet Energy Transfer,” Proceedings of IEEE International Conference on Telecommunications Energy (INTELEC), 2012, Scottsdale, AZ, Sep. 30-Oct. 4, 2012, IEEE 2012, Eaves IEEE, 4 pages.
Edelstein S., Updated 2016 Tesla Model S Also Gets New 75-kWhbattery Option, Jun. 19, 2016, Archived Jun. 19, 2016 by Internet Archive Wayback machine at https://web.archive.org/web/20160619001148/https://www.greencarreports.com/news/1103 782_updated-2016-tesla-model-s-also-gets-new-7 5-kwh-battery-option (“Edelstein”) 4 pages.
Extended European Search Report for European Application No. 21156406.7, dated May 10, 2021, 12 Pages.
Giovino B., “Develop the Right Power Over Ethernet System for Industrial LED Smart Lighting,” https://www.digikey.com/en/articles/develop-the-right-power-over-ethernet-system-for-industrial-led-smart-lighting?utm_adgroup=General&utm_source=google&utm_medium=cpc&utm_campaign=Dynamic%20Search_EN_RLSA&utm_term=&utm_content=General&gclid=EAlaIQobChMlrIiOzOHN9QIVQfvlCh2ZpwrHEAAYASAAEgKKt_D_BwE, Jun. 11, 2018, 7 pages.
Hall S.H., “High-Speed Digital System Design,” A Handbook of Interconnect Theory and Design Practices, Sep. 2000, 55 pages. (“Hall”).
“Heat Concerns When Powering A Power Over Ethernet (PoE) Device,” Blog, https://planetechusa.com/heat-concerns-when-powering-a-poe-device/, Apr. 21, 2020, 9 pages.
International Preliminary Report on Patentability for International Application No. PCT/US2018/032250, dated Dec. 5, 2019, 09 Pages.
International Search Report and Written Opinion for International Application No. PCT/US2018/032250, dated Jul. 20, 2018, 12 Pages.
International Standard IEC 60947-1 Edition 5.0, 2014, ISBN 978-2-8322-1798-6, Sep. 2014, 106 pages. (“IEC-60947”).
International Standard IEC 60950-1 Edition 2.2, 2013, ISBN 978-2-8322-0820-5, May 2013, Part 1, 324 pages. (“IEC-60950”).
International Standard IEC 60950-1 Edition 2.2, 2013, ISBN 978-2-8322-0820-5, May 2013, Part 2, 324 pages. (“IEC-60950”).
International Standard IEC 62368-1 Edition 2.0, 2014, ISBN 978-2-8322-1405-3, Feb. 2014, Part 1, 340 pages. (“IEC-62368”).
International Standard IEC 62368-1 Edition 2.0, 2014, ISBN 978-2-8322-1405-3, Feb. 2014, Part 2, 340 pages. (“IEC-62368”).
International Standard IEC/TS 60479-1 Edition 4.0, 2005, ISBN 2-8318-8096-3, Jul. 2005, 122 pages. (“IEC-60479”).
Jingquan C., et al., “Buck-Boost PWM Converters Having Two Independently Controlled Switches,” 32nd Annual IEEE Power Electronics Specialists Conference, PESC 2001, Conference Proceedings, Vancouver, Canada, New York, NY : IEEE., US, US, Jun. 17-21, 2001, vol. 2, pp. 736-741, DOI:10.1109/PESC.2001.954206, ISBN 978-0-7803-7067-8, XP010559317.
Lathi B.P., “Modern Digital and Analog Communication Systems,” Fourth Edition, Jan. 2009, 15 pages. (“Lathi”).
NFPA, “NFPA 70 National Electrical Code,” 2017 Edition (NEC), Aug. 2016, 881 pages.
Petition for Post Grant Review of U.S. Pat. No. 10,735,105 [Public], Filed Feb. 16, 2021, PGR 2021-00055, 132 pages.
Petition for Post Grant Review of U.S. Pat. No. 10,735,105 [Public], Filed Feb. 16, 2021, PGR 2021-00056, 116 pages.
Tuenge, et al., “PoE Lighting System Energy Reporting Study Part 1,” Feb. 2017, 66 Pages.
James, “Power Over Ethernet—The Story So Far,” HellermannTyton, Mar. 2019, 9 Pages.
Panduit, “Power Over Ethernet with Panduit Copper Cabling,” https://www.panduit.com/content/dam/panduit/en/solutions/COTB05-WW-ENG-PoECabling.pdf, Oct. 2018, 8 Pages.
“Protecting Your IP Traffic from the Heat and Noise of High-Power POE,” https://www.cablinginstall.com/sponsored/berk-tek/article/16482586/protecting-your-ip-traffic-from-the-heat-and-noise-of-highpower-poe, Mar. 28, 2017, 18 Pages.
Sedra A.S., “Microelectronic Circuits,” Oxford, Seventh Edition, Jan. 2014, 38 pages. (“Sedra”).
Stallings W., “Data and Computer Communications,” Fourth Edition, Jan. 1994, 14 pages. (“Stallings”).
Tanenbaum A.S., “Computer Networks,” Third Edition, Mar. 1996, 12 pages.(“Tanenbaum”).
Tellas R., “The Time to Prepare for 100W Power Over Ethernet is Now,” Belden Inc., Jun. 2018, 6 pages.
Microsemi, “Understanding 802.3at PoE Plus Standard Increases Available Power,” Jun. 2011, 7 pages. (“Microsemi”).
Yencheck, Thermal Modeling of Portable Power Cables, 1993.
Zhang, Machine Learning-Based Temperature Prediction for Runtime Thermal Management across System Components, Mar. 2016.
Data Center Power Equipment Thermal Guidelines and Best Practices.
Dynamic Thermal Rating of Substation Terminal Equipment by Rambabu Adapa, 2004.
Chen, Real-Time Termperature Estimation for Power MOSEFETs Conidering Thermal Aging Effects:, IEEE Trnasactions on Device and Materials Reliability, vol. 14, No. 1, Mar. 2014.
UPOE-2400G, 7 pages (Year: 2016).
Hirshmann, 8 pages, (Year: 2011).
Selecting Cables for Power over Ethernet, Hitachi Cable America Inc. Aug. 12, 2017, 7 pages (Year: 2017).
How Cable Temperature Impacts Cable Reach, Belden, Sep. 29, 2017, 2 pages (Year: 2017).
NCP1095, PoE-PD Interface Controller, IEEE 802.3bt, 17 pages, Jun. 2019 (Year: 2019).
IEEE 802.3af PoE Powered Device Controllers With Auto-Retry, Texas Instruments, Apr. 2008, 28 pages (Year: 2008).
https://www.fischerconnectors.com/us/en/products/fiberoptic.
http://www.strantech.com/products/tfoca-genx-hybrid-2x2-fiber-optic-copper-connector/.
http://www.qpcfiber.com/product/connectors/e-link-hybrid-connector/.
https://www.lumentum.com/sites/default/files/technical-library-items/poweroverfiber-tn-pv-ae_0.pdf.
“Network Remote Power Using Packet Energy Transfer”, Eaves et al., www.voltserver.com, Sep. 2012.
Product Overview, “Pluribus VirtualWire Solution”, Pluribus Networks, PN-PO-VWS-05818, https://www.pluribusnetworks.com/assets/Pluribus-VirtualWire-PO-50918.pdf, May 2018, 5 pages.
Implementation Guide, “Virtual Chassis Technology Best Practices”, Juniper Networks, 8010018-009-EN, Jan. 2016, https://wwwjuniper.net/us/en/local/pdf/implementation-guides/8010018-en.pdf, 29 pages.
Related Publications (1)
Number Date Country
20200408608 A1 Dec 2020 US
Continuations (1)
Number Date Country
Parent 15604344 May 2017 US
Child 17022685 US