Methods for measuring real-time dew-point value and total moisture content of material to be molded or extruded

Information

  • Patent Grant
  • 10969356
  • Patent Number
    10,969,356
  • Date Filed
    Friday, September 6, 2019
    4 years ago
  • Date Issued
    Tuesday, April 6, 2021
    3 years ago
Abstract
A method for accurately measuring the real-time valid dew-point value of a material and determining the total moisture content of the material by using an algorithm during the material drying process. The algorithm estimates the valid dew-point value of the material and the total moisture content of the material by analyzing sensor data received on a server. The algorithm determines a valid dew-point value by estimating an inflection point of the moisture content versus time friction/curve for the material, and the total moisture content of the material is determined within the valid dew-point value.
Description
FIELD OF INVENTION

This invention relates generally to a method of accurately measuring real-time dew-point value and total moisture content of a material. More specifically, it relates to accurately measuring the real-time valid dew-point value and estimating the total moisture content of the material within the valid dew-point value using an algorithm during a material drying process.


GENERAL BACKGROUND

Currently, the existing material drying processes adopt various mechanisms to determine the real-time dew-point value of a material and to estimate the total moisture content of the material. However, these processes do not provide an accurate real-time dew-point estimate as the dew-point of the material may vary over a period during the material drying process. Further, the existing drying process does not allow the system to provide a valid dew-point value within which the system must be capable of estimating the total moisture content of the material.


The existing drying processes do not allow a system to provide a valid dew-point value within which the system must be capable of estimating the total moisture content of the material. Hence, there is a need for a system that provides an accurate real-time valid dew-point value within which the moisture content of the material can be determined during the material drying process.


DESCRIPTION OF THE PRIOR ART

PCT publication WO2013093942 discloses a method and a device for moisture determination and control using real-time measurement of the material moisture content at an inlet and outlet of the drying process, such as in a drying hopper. Here, the drying process is controlled by anticipating the drying load based on the moisture content of the incoming material to be dried.


CN 103399486 discloses a temperature optical energy-saving control method for a plastic dryer. The method adopts a predictive control strategy based on multi-model switching to identify dynamic characteristics of air temperature of the plastic dryer and establish a switching system model of an object under each typical working condition. An optical target function with constraint is established by utilizing a switching rule and a mixed neural network is formed by neural networks for processing a continuous variable and a discrete binary variable together.


U.S. Pat. No. 8,433,443 B2 relates to a method for on line monitoring of polymerization reaction in a fluid bed reactor to generate data indicative of imminent occurrence of a discontinuity event (such as sheeting). The method further relates to optional control of the reaction to prevent the occurrence of the discontinuity event.


CN 201672991 relates to a dry and wet bulb temperature acquisition device performing functions of dry and wet bulb temperature acquisition, wireless data receiving and transmitting, and dry and wet bulb temperature display.


U.S. Pat. No. 8,021,462 B2 relates to a dehumidification plant for granular materials having varying physicochemical characteristics, with energy consumption less than that of the dehumidification process, and to a process for regenerating at least one process tower in a granular material dehumidification plant.


EP 2186613 B1 relates to a high efficiency system for dehumidifying and/or drying plastic material. The system enables electronic process control of hopper parameters monitored through sensors and devices.


U.S. Pat. No. 6,289,606 B2 relates to an apparatus and a method for controlling moisture content of a particulate material in a hopper. The apparatus comprises a dew-point sensor to output a signal based on the sensed moisture content of the material and a control circuitry to cause the selector to operate based on output signal.


SUMMARY OF THE INVENTION

This invention provides a system and method for accurately measuring the real-time dew-point value of a material based on which the total moisture content of the material is determined. The method comprises of acquiring data from temperature sensors and dew-point sensors that are positioned at dryer outlets while performing the material drying process. The method receives the sensed data at a server from the sensors by using any of the existing data transmitting technologies such as programmable logic controller, a relay, or a wireless sensor network. Further, the method estimates the initial moisture content of the material before the drying process begins and estimates the total moisture content of the material at any instance during the drying process. The method measures a valid dew-point of the material by determining an inflection point of the moisture content as a function of time curve for the material and determines the total moisture content of the material based on that determined inflection point for the moisture versus time curve/function for the material. The material is preferably granular plastic resin; however the method is not limited to the granular plastic resin but has applicability to other materials that require drying or accurate determination of moisture content.


Other objects and advantages of the embodiments herein will become readily apparent from the following detailed description taken in conjunction with the accompanying drawings.





DESCRIPTION OF THE DRAWINGS


FIG. 1 illustrates a system used in a material drying process according to the invention.



FIG. 2 illustrates the system components required for accurately measuring the real-time valid dew-point value of a material based on which the total moisture content of the material is determined according to the invention.



FIG. 3a and FIG. 3b illustrates a graphical representation of the dew-point measure for different materials according to the invention.





DETAILED DESCRIPTION OF THE INVENTION

In the following detailed description, reference is made to the accompanying drawings that form a part hereof, and specific embodiments that may be practiced are shown by way of illustration. The embodiments are described in sufficient detail to enable those skilled in the art to practice the embodiments and it is to be understood that the logical, mechanical and other changes may be made without departing from the scope of the embodiments. The following detailed description is not to be taken in a limiting sense.


In accordance with the invention, the method uses an algorithm for accurately measuring the real-time valid dew-point value of a material. Total moisture content of the material is estimated within the determined valid dew-point value during the material drying process. The material used for the drying process can be a resin, a plastic, or the like.



FIG. 1 illustrates a system used in the material drying process. The system 100 comprises a unit 101 used as a material dryer by blowing dry air into unit 101 and a hopper 102 used to maintain the moisture level of the material. Temperature and dew-point sensors 103 are fixed at the unit outlet for acquiring data from the hopper 102 to determine the temperature and the real-time valid dew-point value of the material. Sensor data acquired from the hopper 102 is sent to a server 104 for estimating initial moisture content of the material before starting the drying process. System 100 determines the moisture content of the material, being dried by the drying process, using an algorithm.


A valid dew-point value 105 for the material inside the dryer unit 101 is determined by using an algorithm. An inflection point of the material moisture level as a function of time curve is determined for the material. Total moisture content of the material is determined based on the inflection point of the moisture as a function of time curve as estimated for the material by using the algorithm. The real-time valid dew-point value of the material is determined and is transmitted to hopper 102 for determining total moisture content of the material within the valid dew-point value by using the algorithm which provides the determination of the inflection point of the moisture content versus time curve for the material of interest.



FIG. 2 illustrates a system 200 for accurately measuring the real-time valid dew-point value of a material based on which the total moisture content of the material is determined. The system 200 includes a sensor module 201 to sense temperature and dew-point data of the material in the hopper 102, a data acquisition module 202 to acquire the sensed data in server 104 for processing the acquired data, and an analyzer module 203 which estimates the valid dew-point of the material and total moisture content of the material by executing an algorithm. The algorithm determines the valid dew-point value of the material as follows: Total mass of water vapor U(t) that has been forced out of the dryer at a given time t, is obtained from the equation

U(t)=k∫0tDP({acute over (t)})*DAir({acute over (t)})*F({acute over (t)})d{acute over (t)}  [1]

where DP({acute over (t)}) is the dew-point at a given time {acute over (t)} in the outlet, DAir({acute over (t)}) is the density of air (since outlet air temperature is changing) and F({acute over (t)}) is the flow rate, which remains constant all the time. A linear correction factor of k is assumed because dew-point measurement is never accurate and is used to offset the inaccurate dew-point.


Then, water vapor extracted from the material between any two given times t and t2, is given by

ΔU(t−t2)=k∫t2tDP({acute over (t)})*DAir({acute over (t)})*F({acute over (t)})d{acute over (t)}  [2]

To determine the moisture content of the material as V(t), following mass conservation equation is applied, denoting total mass of material as Mp,

Mp*{V(t)−V(t2)}=ΔU(t−t2)=k∫t2tDP({acute over (t)})*DAir({acute over (t)})*F({acute over (t)})d{acute over (t)}  [3]

Assuming t2=0th time or any other time from several sets of measurement of drying, k is determined from linear regression, which should remain constant as it reflects dew-point calibration adjustment.


Knowing k, the total amount of water in the material can be determined.


In one practice of the invention, the following algorithm is used to determine the initial moisture content of the material of interest:










V


(
0
)


=


(

k
Mp

)





0






DP


(

t
'

)






**


D
Air



(

t
'

)



*

F


(

t
'

)



d


t
'








[
4
]








Since within 15-30 minutes of the outlet air attaining highest and saturated temperature, material moisture content is expected to reduce to 50-100 parts per million (ppm), the following modification of equation [4] is used to approximate the residual moisture content, (assuming Td is the time to arrive at high-saturated temperature at outlet of the dryer):










V


(
0
)





(

k
Mp

)





0

1.5
*
Td






DP


(

t
'

)






**


D
Air



(

t
'

)



*

F


(

t
'

)



d


t
'








[
5
]








Moisture vapor content of material at top at any given time during material cycling is determined using equation 6:











V


(
t
)





V


(
0
)


-


(

k
Mp

)





0
t





DP


(

t
'

)






**


D
Air



(

t
'

)



*

F


(

t
'

)



d


t
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]




[
6
]








A control module 204 to transmits data across modules in system 200 using any existing data transmitting technology such as a programmable logic controller, a relay, a wireless sensor network and the like.



FIG. 3a and FIG. 3b are a graphical representation of the dew-point measurement for different materials. As depicted in FIG. 3a, as temperature of drying air is increased for nylon, the moisture content/dew-point value for nylon is decreasing during the drying process. Further, as the temperature of the drying air is increased during the drying process the valid dew-point decreases. As depicted in FIG. 3b, as the drying air is blown into the dryer unit 101, over a period the valid dew-point value of the material eventually decreases.


The method transmits the estimated valid dew-point value to hopper 102 within which the total moisture content of the material can be determined by the algorithm. For example, the curve for one material depicts a dew-point of 2000 ppm and the curve for the other material depicts a dew-point of 770 ppm, which have decreased over a period of time during the material drying process. The algorithm determines the total moisture content of the material within the valid dew-point value estimated for the material.


The foregoing description of the specific embodiments fully reveals the embodiments that others can, by applying current knowledge, readily modify and/or adapt these embodiments for various applications without departing from the generic concept. Therefore, such adaptations and modifications should and are intended to be comprehended within the meaning and range of equivalents of the disclosed embodiments. It is to be understood that the phraseology or terminology employed herein is for the purpose of description and not of limitation. Therefore, while the embodiments herein have been described in terms of preferred embodiments, those skilled in the art will recognize that the embodiments herein can be practiced with modification within the spirit and scope of the appended claims. Although the embodiments herein are described with various specific embodiments, a person skilled in the art will practice the invention with modifications. However, all such modifications are deemed to be within the scope of the claims.

Claims
  • 1. A method for measuring real-time dew-point value of a granular resin material and determining total moisture content of said material in the course of drying said material preparatory to molding or extruding said material into finished plastic parts comprising: a) acquiring data from temperature and dew-point sensors positioned at in a sole drying air outlet of a hopper having said material therein;b) transmitting the acquired data, using a programmable logic controller, a relay, or a wireless sensor network, to a server;c) estimating initial moisture content of said material before the drying process begins by executing the
  • 2. Ancillary to a dryer having a hopper for hot air drying of granular resin material preparatory to molding or extrusion, a system for measuring real-time dew-point of granular polymeric resin material to be molded or extruded into finished plastic products once the material is sufficiently dry, and determining total moisture content of said material comprising: a) a server;b) a temperature sensor for sensing temperature of drying air exiting the hopper;c) a dew-point sensor for sensing dew point of drying air entering the hopper;d) a communication system using a programmable logic controller, a relay, or a network of wireless sensors, for providing data from the sensors to the server;e) the server comprising an analyzer module for i) estimating initial moisture content of said material by executing the algorithm
  • 3. A method of fabricating plastic parts by molding or extrusion from granular polymeric resin material, comprising: a) loading a hopper with granular resin material to be molded into finished plastic articles;b) drying the granular resin material to sufficient dryness that the material can be molded or extruded into finished plastic articles without bubbles of moisture forming in the article during the molding or extrusion process, comprising: i) introducing drying air into the hopper for passage through the granular resin material contained therein and escape from the hopper via a drying air outlet;ii) positioning a temperature sensor at the drying air outlet to sense temperature of drying air exiting the hopper;iii) positioning a dew point sensor at the drying air outlet to sense dew point of drying air exiting the hopper;iv) acquiring data from temperature and dew-point sensors positioned in a sole drying air outlet of a hopper having said material therein;v) estimating initial moisture content of said material before the drying process begins by executing the
CROSS-REFERENCE TO RELATED PATENT APPLICATIONS

This patent application is a 35 USC 120 division of pending U.S. patent application Ser. No. 15/049,098, entitled “Method for Accurately Measuring Real-Time Dew Point Value and Total Moisture Content of a Material”, filed 21 Feb. 2016 and published as United States patent publication 2016/0245765 A1 on 25 Aug. 2016. This application claims the priority of the '098 application under 35 USC 120. The '098 application claimed the priority of U.S. Provisional Patent application Ser. No. 62/119,293 filed Feb. 23, 2015, entitled “Method for Accurately Measuring Real-Time Dew-Point Value and Total Moisture Content of a Material”. This patent application claims the benefit of the priority of the '293 application through the '098 application; the priority is claimed under 35 USC 120.

US Referenced Citations (114)
Number Name Date Kind
4023940 Shultz May 1977 A
4131011 Ling Dec 1978 A
5150289 Badavas Sep 1992 A
5487225 Downie Jan 1996 A
5610339 Haseley et al. Mar 1997 A
5825338 Salmon et al. Oct 1998 A
5995561 Yamasaki et al. Nov 1999 A
6289606 Gillette et al. Sep 2001 B2
6405108 Patel et al. Jun 2002 B1
7406399 Furem et al. Jul 2008 B2
7882394 Hosek et al. Feb 2011 B2
7938935 MacHattie et al. May 2011 B2
8021462 Moretto Sep 2011 B2
8094034 Patel et al. Jan 2012 B2
8112381 Yuan et al. Feb 2012 B2
8126574 Discenzo et al. Feb 2012 B2
8150340 Albsmeier et al. Apr 2012 B2
8334784 Patel et al. Dec 2012 B2
8390299 Laepple et al. Mar 2013 B2
8405940 Schweitzer, III et al. Mar 2013 B2
8421475 Thiim Apr 2013 B2
8433443 Hagerty et al. Apr 2013 B2
8560368 Maity et al. Oct 2013 B1
8571904 Guru et al. Oct 2013 B2
8726535 Garrido et al. May 2014 B2
8868242 Loutfi Oct 2014 B2
8920078 Woolever Dec 2014 B2
9052216 Kamel et al. Jun 2015 B2
9062536 Fischer Jun 2015 B2
9250275 Patel et al. Feb 2016 B2
9781243 Huang Oct 2017 B1
10041844 Brady Aug 2018 B1
20010038345 Satoh et al. Nov 2001 A1
20020143421 Wetzer Oct 2002 A1
20040102924 Jarrell May 2004 A1
20040176926 Edie Sep 2004 A1
20040199573 Schwarz et al. Oct 2004 A1
20050222794 Baird et al. Oct 2005 A1
20060137105 Hong Jun 2006 A1
20060168195 Maturana et al. Jul 2006 A1
20060208169 Breed et al. Sep 2006 A1
20060276949 Beck et al. Dec 2006 A1
20070100518 Cooper May 2007 A1
20070185685 Lannes et al. Aug 2007 A1
20070193056 Switalski Aug 2007 A1
20080103732 Stoupis May 2008 A1
20080109185 Cheung et al. May 2008 A1
20080289045 Fryer Nov 2008 A1
20090024359 Bibelhausen et al. Jan 2009 A1
20090043518 Roh et al. Feb 2009 A1
20090119243 Yuan et al. May 2009 A1
20100023307 Lee Jan 2010 A1
20100169030 Parlos Jul 2010 A1
20100199352 Hill et al. Aug 2010 A1
20100295692 Bjorn Nov 2010 A1
20110016199 De Carlo et al. Jan 2011 A1
20110131398 Chaturvedi et al. Jun 2011 A1
20110137697 Yedatore et al. Jun 2011 A1
20110216805 Fernando et al. Sep 2011 A1
20110307220 Lacaille Dec 2011 A1
20120045068 Kim et al. Feb 2012 A1
20120166142 Maeda et al. Jun 2012 A1
20120209569 Becourt et al. Aug 2012 A1
20120213098 Sun Aug 2012 A1
20120271576 Kamel Oct 2012 A1
20120290104 Holt et al. Nov 2012 A1
20120330499 Scheid et al. Dec 2012 A1
20120330614 Kar Dec 2012 A1
20130102284 Storozuk Apr 2013 A1
20130119047 Driussi May 2013 A1
20130170417 Thomas et al. Jul 2013 A1
20130173178 Poczka et al. Jul 2013 A1
20130201316 Binder et al. Aug 2013 A1
20130268469 Sharma et al. Oct 2013 A1
20130287060 Langdoc et al. Oct 2013 A1
20130304677 Gupta et al. Nov 2013 A1
20130318022 Yadav et al. Nov 2013 A1
20140129164 Gorbold May 2014 A1
20140132418 Lill May 2014 A1
20140163416 Shuck Jun 2014 A1
20140186215 Shinta Jul 2014 A1
20140207394 Madden Jul 2014 A1
20140223767 Arno Aug 2014 A1
20140244836 Goel et al. Aug 2014 A1
20140262130 Yenni Sep 2014 A1
20140309805 Ricci Oct 2014 A1
20140314284 Movellan et al. Oct 2014 A1
20140335480 Asenjo et al. Nov 2014 A1
20140336791 Asenjo et al. Nov 2014 A1
20140337429 Asenjo et al. Nov 2014 A1
20150026044 Refaeli Jan 2015 A1
20150039250 Rank Feb 2015 A1
20150094914 Abreu Apr 2015 A1
20150139817 Kowalski May 2015 A1
20150181313 Murphy Jun 2015 A1
20150185251 Heydron et al. Jul 2015 A1
20150233856 Samuilov Aug 2015 A1
20150261215 Blevins Sep 2015 A1
20160086285 Peters et al. Mar 2016 A1
20160147205 Kaufman May 2016 A1
20160189440 Cattone Jun 2016 A1
20160209831 Pal Jul 2016 A1
20160245279 Pal et al. Aug 2016 A1
20160245686 Pal et al. Aug 2016 A1
20160245765 Pal Aug 2016 A1
20160291552 Pal et al. Oct 2016 A1
20160299183 Lee Oct 2016 A1
20160313216 Pal et al. Oct 2016 A1
20160349305 Pal Dec 2016 A1
20170032281 Hsu Feb 2017 A1
20170060574 Malladi et al. Mar 2017 A1
20170061608 Kim et al. Mar 2017 A1
20170163444 McLaughlin et al. Jun 2017 A1
20170201585 Doraiswamy et al. Jul 2017 A1
Foreign Referenced Citations (23)
Number Date Country
201672991 Dec 2010 CN
102539911 Jul 2012 CN
103399486 Nov 2013 CN
203362223 Dec 2013 CN
203588054 May 2014 CN
104036614 Sep 2014 CN
1836576 Feb 2012 EP
2186613 May 2013 EP
2648393 Oct 2013 EP
WO 2005086760 Sep 2005 WO
WO 2010104735 Sep 2010 WO
WO 2013040855 Mar 2013 WO
WO 2013-041440 Mar 2013 WO
WO 2013093942 Jun 2013 WO
WO 2014044906 Mar 2014 WO
WO 2014085648 Jun 2014 WO
WO 2014089567 Jun 2014 WO
WO 2014117245 Aug 2014 WO
WO 2015022036 Feb 2015 WO
WO 2016137848 Sep 2016 WO
WO 2016137848 Sep 2016 WO
WO 2017-1234525 Jul 2017 WO
WO 2017123425 Jul 2017 WO
Non-Patent Literature Citations (27)
Entry
International Search Report and Written Opinion for PCT Application No. PCT/US16/18820; dated Aug. 4, 2016.
International Search Report and Written Opinion for PCT Application No. PCT/US15/066547; dated Mar. 17, 2016.
Sensors Drive Mobile IoT; Wong, William; Jan. 26, 2015; Electronic Design.
International Search Report and Written Opinion for PCT Application No. PCT/US16/028724; dated Aug. 22, 2016.
International Search Report and Written Opinion for PCT Application No. PCT/US16/18831; dated Aug. 12, 2016.
Fault Detection in Kerman Combined Cycle Power Plant Boilers by Means of Support Vector Machine Classifier Algorithms and PCA by M. Berahman, et al., 3rd International Conference on Control, Instrumentation, and Automation (ICCIA 2013), Dec. 28-30, 2013, Tehran, Iran.
Fault Monitoring and Diagnosis of Induction Machines Based on Harmonic Wavelet Transform and Wavelet neural Network by Qianjin Guo, et al., dated Sep. 2008, published at the Fourth International Conference on Natural Computation.
Fault Diagnosis Method Study in Roller Bearing Based on Wavelet Transform and Stacked Auto-encoder, by Junbo Tan, et al., dated Feb. 2015, published by IEEE.
A Diagnostic Expert System Embedded in a Portable Vibration Analysis Instrument by Dr. Robert Milne, et al., dated May 13, 1991, published at IEE Colloquium on Intelligent Instrumentation.
Detection of Precursor Wear Debris in Lubrication Systems by Jack Edmonds, et al., dated May 2000, published by IEEE.
Fault Diagnosis of Bearing Based on Fuzzy Support Vector Machine, by Haodong Ma, et al., dated Jan. 2015, published by IEEE.
Investigation of the Mechanical Faults Classification using Support Vector Machine Approach by Zhiqiang Jiang, et al., dated Aug. 2010, 2010 Second International Conference on Intelligent Human-Machine Systems and Cybernetics.
Impact Characterization of Multiple-Points-Defect on Machine Fault Diagnosis by Muhammad F. Yaqub, et al., 8th IEEE International Conference on Automation Science and Engineering, Aug. 20-24, 2012, Seoul, Korea.
Detection of Generalized-Roughness Bearing Fault by Spectral-Kurtosis Energy of Vibration or Current Signals by Fabio Immovilli, et al., IEEE Transations on Industrial Electronics, vol. 56, No. 11, Nov. 2009.
Intrinsic Mode Function Determination of Faulty Rolling Element Bearing Based on Kurtosis by Wei Kang, et al., Proceeding of the 2015 IEEE International Conference on Information and Automation, Lijiang, China, Aug. 2015.
Condition Monitoring and Fault Diagnosis of Rolling Element Bearings Based on Wavelet Energy Entropy and SOM by Shuai Shi, et al., dated Aug. 2012, published by IEEE.
Continuous Hidden Markov Model Based Gear Fault Diagnosis and Incipient Fault Detection by Jian-She Kang, et al., dated Jun. 2011, published by Institute of Electrical and Electronics Engineers (IEEE).
Study on Fault Diagnosis of Gear with Spall using Ferrography and Vibration Analysis by Wei Feng, et al., published in Aug. 2009 at the International Conference on Measuring Technology and Mechatronics Automation.
International Search Report and Written Opinion for PCT Application No. PCT/US2016/067814; dated Apr. 6, 2017.
International Search Report and Written Opinion for PCT Application No. PCT/US2016/067546; dated Apr. 11, 2017.
Krishnamurthy, S. et al. (2008) Automation of Facility Management Processes Using Machine-to-Machine Technologies. In: Floerkemeier C., Langheinrich M., Fleisch E., Mattern F., Sarma S.E. (eds) The Internet of Things. Lecture Notes in Computer Science, vol. 4952. DOI:10.1007/978-3-540-78731-0_5 (Year: 2008).
Holler, J. et al. (2014). “From Machine-to-machine to the Internet of Things: Introduction to a New Age of Intelligence.” Chapters 2, 4, 5, 7, 10, 12. Academic Press. DOI:10.1016/B978-0-12-407684-6.00002-4 (Year: 2014).
Azure IoT Edge open for developers to build for the intelligent edge, George, Sam; Azure Internet of Things; Nov. 15, 2017.
Predix Edge Technology Product Brief, General Electric, 2017.
http://ieeexplore.ieee.org/document/8089336/ Future Edge Cloud and Edge Computing for Internet of Things Applications—Janali Pan et al.
Challenges and Solutions of Protecting Variable Speed Drive Motors; Aversa, et al.; Feb. 11, 2013; Presented at the 2013 Texas A&M Conference for Protective Relay Engineers.
Dec. 21, 2018 Non-Final Office Action against Applicant's co-pending U.S. Appl. No. 14/833,111.
Related Publications (1)
Number Date Country
20190391096 A1 Dec 2019 US
Provisional Applications (1)
Number Date Country
62119293 Feb 2015 US
Divisions (1)
Number Date Country
Parent 15049098 Feb 2016 US
Child 16562500 US