Patent Application
20170160243
This invention generally relates to the field of structural health monitoring (“SHM”).
SHM involves the process of implementing a damage detection and characterization strategy for engineering structures. Such damages may include changes to the material and/or geometric properties of a structural system as well as changes to the boundary conditions and system connectivity, which adversely affect the structural system's performance. The monitoring process may include the observation of a system over time using periodically sampled dynamic response measurements from an array of sensors, the extraction of damage-sensitive features from these measurements, and the statistical analysis of these features to determine the current state of system health.
Currently, a SHM system includes data acquisition devices and at least one processing device, such as a computer, that is separate from the data acquisition devices. These data acquisition devices are usually mounted onto or installed near a structure to be monitored. In passive mode SHM systems, these data acquisition devices include in-situ sensors which listen to the changes continuously or periodically. In active mode SHM systems, however, these data acquisition devices include not only in-situ sensors but also actuators. The actuators use waveform generators and power amplifiers to generate actuation signals and send the actuation signals to the structure, whereas the in-situ sensors listen to the actuation signals and send back sensor signals for measurement. When the structure is normal, the sensor signals are used as the baseline data. When the structure has defects or changes, the sensor signals would be different from the baseline data. These data acquisition devices either integrate the actuator(s) and/or sensor(s) inside or connect to them externally. However, these data acquisition devices do not have the capabilities to determine the structural changes and damages independently. Active mode SHM system relies on the separate processing device(s) to perform relevant analysis and determine if the structure has experienced any change, defect, or damage. To achieve this goal, these data acquisition devices transmit the raw sensor data to the processing device(s) via a network or pre-processes the raw sensor data through some filtering or data compression process before the transmission via the network. The processing device(s) then determines the structural changes and damages based on the raw or pre-processed sensor data received from the data acquisition devices. However, the network connectivity becomes the critical point of the system. Any network glitches or failure will disrupt the monitoring of the structure. Since all sensor data, either in raw format or in pre-processed format, need to be transmitted to the processing device for analysis, the requirement for network bandwidth and processing power of the processing device grows dramatically as the number of data acquisition devices increases. This makes SHM systems difficult to scale. In addition, for a very large structure, a large number of such SHM devices are required. When each smart SHM device sends raw data to a processing device for analysis, the processing device will need to perform heavy data processing and it could take a very long time for the processing device to find the result. In time critical situations, any critical damage to the structure may not be timely detected.
The present invention discloses a smart SHM device with built-in intelligence. The device is capable of detecting events, processing sensor data, extracting features, executing analytics algorithms, and determining structural changes and damages all by itself. Such events include, but are not limited to, impacts, pressure, strains, load changes, vibrations, accelerations, decelerations, temperature changes, motions, light, humidity changes, etc. Features that may be extracted from the sensor data include, but are not limited to, frequency, energy, waveform envelope, peak points, and zero crossing points. The structural changes and damages that may be determined by the smart SHM device include, but are not limited to, cracks, delamination, deformations, corrosions, erosions, leakages, bolt loosening, movements, bending, etc.
In one embodiment of the present invention, a plurality of the smart SHM devices is connected to a remote management console through a network. The console may be a computer or a mobile computing device with necessary software deployed on it. The remote management console provides central management for those smart SHM devices, including but not limited to baseline adjustment, data acquisition setup, threshold adjustment, removing data, time clock synchronization, user management. The remote management console also systematically downloads useful analytic results or data from these devices and coordinates the collaboration and operation of these smart SHM devices.
This invention integrates data acquisition and data processing into a single smart device, which greatly simplifies the electrical wiring need, reduces the overall footprints, and improves the reliability of a SHM system. The baseline information regarding the structure when it is in healthy condition is stored locally at the SHM device. A predefined threshold is also stored locally in the SHM device. The baseline information is used to determine if the structure defects exceed the safety operation boundary. The detection of structural changes and damages is performed directly by the smart SHM device. This allows instantaneous event detection in the shortest time frame, which is especially useful at time critical situations where the decision must be made as fast as possible. Because the detection of structural changes and damages is performed locally, a smart SHM device can continuously monitor a structure to detect damage, even when network connection is not available.
The smart SHM device does not need to send all sensor data to the remote management console across the network for processing. The sensor data, extracted features, and results of structural changes and damages are transmitted to the remote management console only when requested or scheduled. This dramatically reduces the load on the network infrastructure.
In one embodiment of the present invention, the sensor data and analytic results are stored in a memory module of the smart SHM device during network down time and are sent across network when the network connection is recovered. This significantly improves overall system reliability.
The ability to distribute heavy processing at the device level significantly improves the system scalability. In one embodiment of the present invention, multiple smart SHM devices are deployed to monitor a large structure. The ability of parallel processing by these smart SHM devices provides the fastest response speed for the monitoring of the large structure. Likewise, multiple smart SHM devices can be used to monitor a very important structure to add redundancy for maximizing the reliability.
In one embodiment of the present invention, the smart SHM device provides a sleep mode for saving power, especially when the device is operated by battery power. When in sleep mode, the smart SHM device's processing unit, actuating unit, and communication unit go into sleep, leaving one or just a few sensors in monitoring mode. The sensor(s) consumes very little power to conserve energy. When an event is detected, the device wakes up and starts processing the event.
In one embodiment of the present invention, the smart SHM device is operated by battery power. This is useful in situations where external power supply is not conveniently available for the device. In another embodiment of the invention, the smart SHM device is powered by either AC or DC power from the power source on the structure or close to the structure.
In one embodiment of the present invention, the device is permanently mounted onto or close to the structure to be monitored with fixture such as screws, epoxy, metal belts, or clamps, or soldering, etc.
In one embodiment of the present invention, the device has self-diagnosis ability and sensor diagnosis ability.
The subject matter, which is regarded as the invention, is particularly pointed out and distinctly claimed in the claims at the conclusion of the specification. The foregoing and other features and also the advantages of the invention will be apparent from the following detailed description taken in conjunction with the accompanying drawings. Additionally, the leftmost digit of a reference number identifies the drawing in which the reference number first appears.
The actuating unit 101 and sensor unit 102 may include piezoelectric-based actuators and sensors or Electromagnetic Acoustic Transducer (EMAT)-based actuators and sensors, respective. In one embodiment of the invention, the actuating unit 101 and sensor unit 102 are installed inside the smart SHM device 100. During operation, the actuating unit 101 sends excitation signals across the structure and the sensor unit 102 receives the structure's response to the excitation signals. Alternatively, the actuating unit 101 and/or the sensor unit 102 may be connected externally to the smart SHM device 100 via connecters and/or cables. In this configuration, the actuating unit 101 and the sensor unit 102, or a number of these units, may be easily deployed at specific location(s) of the structure, where it would be difficult to fit the whole smart SHM device due to space restraints.
In one embodiment of the invention, the sensor unit 102 may include multiple sensors with different sensing capabilities, such as accelerometer, strain gauge sensor, motion sensor, temperature sensor, humidity sensor, pressure sensor, gyro sensor, force sensor, light sensor, audio sensor, biometrics sensor, proximity sensor, current sensor, magnetic sensor, acoustic sensor, ultrasonic sensor, GPS sensor, and others.
It should be noted that different variations of design of the actuating unit and/or the sensor unit may be achieved by combining and/or rearranging all or some of the above described embodiments and/or their components. For example, a plurality of analog sensors 301, amplifiers with filter 303, and digital sensors 331 can be combined into one sensor unit.
The processing unit 401 controls the actuating unit 405 to send out excitation signals based on predefined schedules, user commands, or events detected from the sensor unit(s) 404 and/or sensor unit(s) 406. There are many ways to implement the processing unit 401. In one embodiment, the processing unit 401 detects structural changes by comparing new data with a baseline profile. The baseline profile may be created right after the installation of the smart SHM device 400 onto the structure or any maintenance of the structure has just been finished. When the change exceeds a predefined threshold, the processing unit 401 determines that a change or damage in structure has occurred and may cause an alarm to sound and send an alert message to a remote management console.
In another embodiment, the processing unit 401 calculates structural changes based on a pre-established structure model. When the change exceeds a predefined threshold, the processing unit 401 determines that a change or damage in the structure has occurred and may cause an alarm to sound and send an alert message to a remote management console. For example, statistical models for discrimination between features from the undamaged and damaged structures are established. Statistical model development is concerned with the implementation of the algorithms to quantify the damage state of the structure.
In yet another embodiment, the processing unit 401 can estimate structural changes and damages by using extracted feature data. Because the size of the feature data is much smaller than sensor data, only a fraction of network bandwidth, computational power, and memory are required. This significantly improves the response time of the smart SHM device. Feature data includes, but is not limited to, (1) the peak values of each cycle of a waveform; (2) the maximum and minimum values of each cycle of a waveform; (3) down-sampled data from the raw data; (4) the peak values of a waveform in a given window. For example, the total waveform has 6,000 data points and one is only interested in the data points in the window of [500, 2000].
In one embodiment, adaptive method such as machine learning algorithms can be used to adjust the schedule adaptively based on the structure status. For example, when the structure reaches a critical failure threshold, more frequent scanning can be scheduled automatically.
The memory unit 408 of the smart SHM device 400 may include volatile memory such as RAM 409 and/or non-volatile memory such as flash memory 410. The flash memory 410 (or other type of non-volatile memory) saves device configurations, baseline profiles, history data, as well as software programs that perform various tasks of data processing, analytics, data transmission, process management, hardware management, etc. History data includes sensor data, extracted features and events, detected structural changes and damages. In one embodiment, the flash memory 410 maintains a database that stores the baseline profiles, history data, and new data. The database has a predefined size limit and when the database becomes full, the oldest data will be erased first to leave space for new data. In addition, these stored data may be accessed from the remote management console, which is discussed in detail below.
The communication unit 407 of the smart SHM device 400 provides connectivity to other devices. In one embodiment of the invention, an Ethernet port is included. In other embodiments, other communication interfaces may be used, including but not limited to Wi-Fi, cellular network, Zigbee, Zwave, CAN bus, I2C, SPI, RS485, RS232, USB, and others.
In one embodiment of the invention, the smart SHM device 400 has an HDMI display interface to connect to an external monitor and host USB ports to connect to a keyboard and mouse. This provides a local user interface. Furthermore, the smart SHM device may carry a LED light, a LCD screen, a keypad, and/or an alarm. A user can use the keypad to configure the smart SHM device, including the LED light, LCD screen, and/or alarm, during installation. During operation, the LED light, LCD screen, and/or alarm can indicate the status and send alarm notifications when critical condition is detected.
In one embodiment of the present invention, the smart SHM device 400 provides a sleep mode for saving power, especially when the device is operated by battery power. When in sleep mode, the smart SHM device's processing unit, actuating unit, memory unit, and communication unit go into sleep, leaving one or just a few sensors in monitoring mode. The sensor(s) consumes very little power to conserve energy. When an event is detected, the device wakes up and starts processing the event.
For example, when the smart SHM device 400 goes into the sleep mode, the processing unit 401, the actuating unit 405, the memory unit 408, and the communication unit 407 go into sleep. Only one or more sensors (e.g., a piezoelectric sensor) and a low-power circuit 411 are still operating for monitoring certain events. In one case, such an event is a strong impact to the structure. When an impact event occurs, the piezoelectric sensor converts the mechanical energy to electrical signal. The conversion does not need external power due to the property of piezoelectric. When the voltage level of the electrical signal exceeds a predefined voltage level, the low-power circuit 411 sends a wake-up call to the processing unit 401 to wake up the whole SHM device 400.
In another example, the smart SHM device 400 goes into the sleep mode and wakes up periodically controlled by an internal timer 412 that consumes very low power. The sleeping period may be specified and adjusted by users.
Although specific embodiments of the invention have been disclosed, those having ordinary skill in the art will understand that changes can be made to the specific embodiments without departing from the spirit and scope of the invention. The scope of the invention is not to be restricted, therefore, to the specific embodiments. Furthermore, it is intended that the appended claims cover any and all such applications, modifications, and embodiments within the scope of the present invention.
This application claims priority to U.S. provisional patent application Ser. No. 62/261,866, filed Dec. 2, 2015, the entire content of which is incorporated herein by reference.
| Number | Date | Country | |
|---|---|---|---|
| 62261866 | Dec 2015 | US |
