The present 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.
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.
PCT publication no. 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 online 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. This patent also relates 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.
The existing drying process does 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.
The present invention is related to 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 (PLC), relay, or wireless sensor networks. 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 for the material and determines the total moisture content of the material based on the inflection point of the material.
Other objects and advantages of the embodiments herein will become readily apparent from the following detailed description taken in conjunction with the accompanying drawings.
In the following detailed description, a reference is made to the accompanying drawings that form a part hereof, and in which the specific embodiments that may be practiced is shown by way of illustration. These 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 therefore not to be taken in a limiting sense.
In accordance with the present invention, the method uses an algorithm for accurately measuring the real-time valid dew-point value of a material and the total moisture content of the material is estimated within the determined valid dew-point value during the material drying process. The material used during the drying process can be a resin, a plastic, or the like.
Total mass of water vapor U(t) that has been forced out of the dryer at a given time t, can be obtained from the equation
U(t)=k∫0tDP(t′)*DAir(t′)*F(t′)dt′ [1]
Where DP(t′) is the dew-point at a given time t′ in the outlet, DAir(t′) is the density of air (since outlet air temperature is changing) and F(t′) is the flow rate, which remains same all the time. A linear correction factor of k is assumed because dew-point measurement is never accurate and it is to offset the inaccurate dew-point.
Then water extracted from plastic between any two given points t and t2, is given by
ΔU(t−t2)=k∫t2tDP(t′)*DAir(t′)*F(t′)dt′ [2]
To measure the moisture content of plastic as V(t), following mass conservation equation is applied denoting total mass of plastic as Mp,
Mp*{V(t)−V(t2)}=ΔU(t−t2)=k∫t2tDP(t′)*DAir(t′)*F(t′)dt′ [3]
Assuming t2=0th time or any other time from several sets of measurement of drying, k is determined from linear regression which is supposed to remain constant as it reflects dew-points calibration adjustment.
Knowing k, total amount of water in plastic material can be estimated as well as remaining water in plastic or alike material can be determined.
In an embodiment, the following algorithm is used to determine the initial moisture content of the plastic:
Since within 15-30 minutes of outlet air attaining highest and saturated temperature, plastic moisture content is expected to reduce to 50-100 parts per million (ppm), practically, we can use an equation, (assuming Td is the time to arrive at high-saturated temperature at outlet of the dryer):
Vapor content of plastic at top at any given time during material cycling:
A Controlling Module 204 is configured to transmit data across modules in the system 200 by using any of the existing data transmitting technology such as Programmable Logic Controller (PLC), relay, and wireless sensor networks and so on.
The foregoing description of the specific embodiments will so fully reveal the general nature of the embodiments herein that others can, by applying current knowledge, readily modify and/or adapt for various applications such specific embodiments without departing from the generic concept, and, 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, it will be obvious for a person skilled in the art to practice the invention with modifications. However, all such modifications are deemed to be within the scope of the claims.
This application claims priority to the U.S. Provisional Patent application No. 62/119,293 filed in the United States Patent and Trademark Office on Feb. 23, 2015, entitled “Method for Accurately Measuring Real-Time Dew-Point Value and Total Moisture Content of a Material”. The specification of the above referenced patent application is incorporated herein by reference in its entirety.
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 |
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 | 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 |
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 |
20160291552 | Pal et al. | Oct 2016 | A1 |
20160299183 | Lee | Oct 2016 | A1 |
20160313216 | Pal et al. | Oct 2016 | A1 |
20160349305 | Pal | Dec 2016 | 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 |
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 |
2648393 | Oct 2013 | EP |
WO 2005086760 | Sep 2005 | WO |
WO 2010104735 | Sep 2010 | WO |
WO 2013-0041440 | 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 2017123425 | Jul 2017 | WO |
Entry |
---|
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/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. |
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. |
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 Precursor Wear Debris in Lubrication Systems by Jack Edmonds, et al., dated May 2000, published by IEEE. |
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. |
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. |
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. |
Number | Date | Country | |
---|---|---|---|
20160245765 A1 | Aug 2016 | US |
Number | Date | Country | |
---|---|---|---|
62119293 | Feb 2015 | US |