CN110907015B - Liquid level monitoring method based on RFID (radio frequency identification) in indoor environment - Google Patents

Liquid level monitoring method based on RFID (radio frequency identification) in indoor environment Download PDF

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CN110907015B
CN110907015B CN201910822196.5A CN201910822196A CN110907015B CN 110907015 B CN110907015 B CN 110907015B CN 201910822196 A CN201910822196 A CN 201910822196A CN 110907015 B CN110907015 B CN 110907015B
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liquid level
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肖甫
顾冰
周剑
黄海平
徐松
刘海猛
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Nanjing University of Posts and Telecommunications
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01F—MEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME
    • G01F23/00—Indicating or measuring liquid level or level of fluent solid material, e.g. indicating in terms of volume or indicating by means of an alarm
    • G01F23/22—Indicating or measuring liquid level or level of fluent solid material, e.g. indicating in terms of volume or indicating by means of an alarm by measuring physical variables, other than linear dimensions, pressure or weight, dependent on the level to be measured, e.g. by difference of heat transfer of steam or water
    • G01F23/28—Indicating or measuring liquid level or level of fluent solid material, e.g. indicating in terms of volume or indicating by means of an alarm by measuring physical variables, other than linear dimensions, pressure or weight, dependent on the level to be measured, e.g. by difference of heat transfer of steam or water by measuring the variations of parameters of electromagnetic or acoustic waves applied directly to the liquid or fluent solid material
    • G01F23/284—Electromagnetic waves

Abstract

The invention provides a liquid level monitoring method based on RFID in an indoor environment, which adopts signal data of an acquired RFID label as a judgment standard of a liquid level state, comprises a training stage and a real-time monitoring stage, obtains a threshold value corresponding to a liquid level height state in the training stage, and then realizes the monitoring of a region where the real-time liquid level in a water tank to be detected is located in the real-time monitoring stage; compared with the traditional water level identification meter which can only statically identify the height, the liquid level monitoring method based on the RFID in the indoor environment can identify the area where the liquid level is located in real time by comparing the RSSI value acquired in real time with the threshold value in the rising process of the liquid level, and is simple, convenient, feasible and reliable in monitoring.

Description

Liquid level monitoring method based on RFID (radio frequency identification) in indoor environment
Technical Field
The invention relates to a liquid level monitoring method based on RFID in an indoor environment.
Background
Liquid storage tanks have a wide range of uses in modern life, for example, industrial liquid oil tanks, production water storage tanks, solar water heater water storage equipment and the like, all of which require storage of liquid. The rational utilization water resource has very important meaning, meanwhile, to liquid level measurement's precision and real-time nature, can directly influence the complete realization of storage box function and the rational utilization of water resource.
The early water tank only utilizes the storage space, and the water use, water level monitoring and other aspects are still manually carried out, so that the method is low in efficiency and very inconvenient. From the analysis of the manual monitoring technology, the following problems mainly exist: firstly, the recording mode is mainly manual recording, and the workload of data recording in the later period is large; secondly, the real-time performance and accuracy of acquisition, transmission and processing of water level information are poor, and the requirements of modern hydrology cannot be met. A series of self-recording water level meters have appeared later, which can be roughly classified into three categories as to the way they sense water level: float type, pressure type water gauge. Although the workload is greatly reduced, the equipment is greatly influenced by the environment, has large error, is most importantly expensive, and is not suitable for popularization.
The above-mentioned problems are problems that should be considered and solved in the liquid level monitoring process in an indoor environment.
Disclosure of Invention
The invention aims to provide a liquid level monitoring method based on RFID in an indoor environment, which solves the problems of low efficiency, large error, inconvenient monitoring and high cost in the prior art.
The technical solution of the invention is as follows:
a liquid level monitoring method based on RFID in an indoor environment adopts signal data of an acquired RFID label as a judgment standard of a liquid level state, comprises a training stage and a real-time monitoring stage, a threshold value corresponding to a liquid level height state is obtained in the training stage, and then the monitoring of a region where the real-time liquid level in a water tank to be detected is located is realized in the real-time monitoring stage; comprises the following steps of (a) carrying out,
s1, attaching the RFID tag to the outer wall of the water tank to be tested, respectively arranging the RFID tag and the RFID reader on two sides of the water tank to be tested, then injecting water into the empty water tank to be tested until the water is full in the training stage, and collecting signal data obtained by the RFID reader in the water injection process, wherein the signal data comprises a signal strength value, namely an RSSI value;
s2, preprocessing the RSSI value acquired in the step S1 to obtain a preprocessed RSSI oscillogram;
s3, according to a liquid level monitoring algorithm, extracting signal characteristics of the data preprocessed in the step S2, and accordingly obtaining a threshold value corresponding to the liquid level height state;
and S4, in the real-time monitoring stage, the RFID reader collects the RSSI value in real time, and compares the RSSI value collected in real time with the threshold value obtained in the step S3 to obtain the area where the real-time liquid level in the water tank to be detected is located.
Optionally, in step S2, the RSSI value collected in step S1 is preprocessed, specifically,
s21, carrying out median filtering processing on the collected original RSSI values, eliminating isolated noise points, setting a sliding window, then sorting data in the sliding window, selecting a middle value to replace the original value, and then outputting the median filtering as follows:
ri＝Med(xi)
where Med () is a one-dimensional median filter function, riIs the median filtered RSSI value, xiIs the RSSI value of the ith sample point;
s22, carrying out abnormal value elimination on the RSSI value processed in the step S21 by an algorithm based on local weighted linear regression, traversing N sampling points, calculating the distance between each sampling point and the point t to be predicted, namely the weight of the contribution error of each sampling point, and giving higher weight to the point near the sampling point i by using a Gaussian kernel, wherein the corresponding weight of the Gaussian kernel is as follows:
Figure BDA0002185685430000021
wherein, ω isiIs a weight matrix with N elements and only diagonal elements, t is the time value of the point to be predicted, t isiIs the time of the ith sample point, λ is the wavelength parameter, λ controls the rate at which the weight decreases, and point tiThe closer to t, ωiThe greater the value of (A);
obtaining a kernel function matrix W composed of N points to be measured as:
Figure BDA0002185685430000022
wherein, ω isiIs the weight value at the ith sample point;
using least squares pair (t)i，ri) And i is 1,2, …, N, calculating the sum of squares of residuals, and obtaining an optimal regression coefficient theta:
θ＝(XTWX)-1XTWY
wherein X is (t)1,t2…,tN) Is a vector of time values of N sampling points, T is a matrix transposition symbol, and Y is (r)1,r2…,rN) The RSSI values corresponding to the N sampling points form a vector; then, the obtained optimal regression coefficient is substituted into the following formula to obtain an estimated value of each sampling point:
x′i＝θTti
wherein, x'iThe RSSI value of the ith sampling point after the local weighted linear regression is obtained;
and further obtaining a preprocessed RSSI waveform image with abnormal values removed.
Optionally, in step 3, according to a liquid level monitoring algorithm, signal features are extracted from the data preprocessed in step S2, so as to obtain a threshold corresponding to the liquid level height state, specifically,
s31, introducing a slope, and obtaining a final threshold value with an expression as follows:
Figure BDA0002185685430000031
in the formula (f)iIs the characteristic value of the ith sample point,
Figure BDA0002185685430000032
x′i、x′i+1the RSSI value, t, of the ith and (i + 1) th sampling point after the local weighted linear regressioni、ti+1Is the time value, k, corresponding to the ith and the (i + 1) th sampling pointsiThe slope of the ith sampling point;
s32, according to the preprocessed RSSI waveform diagram obtained in step S2, using a valley point in the obtained RSSI waveform diagram as a point B, using a maximum RSSI value in the acquisition time after the occurrence of the valley point as a point S, and obtaining a threshold value at the point S and a threshold value at the point B as:
Figure BDA0002185685430000033
wherein k isS、x′SSlope and RSSI value, k, corresponding to the starting point respectivelyB、x′BRespectively corresponding to the slope and RSSI value of the trough;
s33, the threshold f obtained in the step S32S、fBAs the change threshold value of liquid level state respectively, specifically be, divide into three liquid level state with the liquid level state of the water tank that awaits measuring, do respectively: a normal ascending area, a safety buffer area and an overflow warning area, wherein the threshold value fSAs the liquid level state change threshold value of the normal ascending region and the safety buffer region, the threshold value fBAs the liquid level state change threshold value of the safety buffer area and the overflow warning area.
Optionally, in step S4, the RSSI value acquired in real time is compared with the threshold value obtained in step S3, so as to obtain the area where the real-time liquid level in the water tank to be tested is located, specifically,
when f is>fSWhen the water level is in the normal rising area; when f isB＜f≤fSWhen the water level is in the safe buffer area; when f is less than or equal to fBAnd the water level is in an overflow warning area, wherein f is an RSSI value acquired in real time.
The invention has the beneficial effects that:
according to the liquid level monitoring method based on the RFID in the indoor environment, the wireless radio frequency signals are used as liquid level monitoring evaluation factors, and can be obtained from RFID equipment, so that the whole system is simple, convenient and feasible, and has good simplicity.
The liquid level monitoring method based on the RFID in the indoor environment adopts the RFID technology, the RSSI value is extracted from the liquid level monitoring method, an algorithm for local weighted regression is adopted to remove abnormal values, the RSSI value with robustness is obtained, meanwhile, the slope characteristics are combined, more accurate and reliable data are obtained, the monitoring reliability is guaranteed, the liquid level monitoring method based on the RFID in the indoor environment can be suitable for liquid level detection in various containers, and the liquid level monitoring method based on the RFID has better adaptability.
Compared with the traditional water level identification meter which can only identify the height statically, the liquid level monitoring method based on the RFID in the indoor environment can identify the area where the liquid level is located in real time by comparing the RSSI value acquired in real time with the threshold value in the rising process of the liquid level.
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FIG. 1 is a schematic flow diagram of a method for RFID-based liquid level monitoring in an indoor environment according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of an embodiment RFID tag deployment;
FIG. 3 is an RSSI waveform diagram of the normal rise region, the safety buffer region and the overflow warning region in the embodiment;
FIG. 4 is a schematic diagram illustrating a normal ascending area, a safety buffer area, and an overflow guarding area on a water tank to be tested in the embodiment;
wherein: 1-RFID label, 2-water tank to be tested, 3-RFID reader and 4-antenna.
Detailed Description
Preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
Examples
A liquid level monitoring method based on RFID in an indoor environment adopts signal data of an acquired RFID label as a judgment standard of a liquid level state, comprises a training stage and a real-time monitoring stage, a threshold value corresponding to a liquid level height state is obtained in the training stage, and then the monitoring of a region where the real-time liquid level in a water tank to be detected is located is realized in the real-time monitoring stage; as shown in fig. 1, includes the following steps,
s1, pasting the RFID tag on the outer wall of the water tank to be detected, for example, pasting the RFID tag at a position 10cm away from the top end of the water tank to be detected, setting the position according to the capacity of the specific water tank, as shown in fig. 2, respectively setting the RFID tag and the RFID reader at two sides of the water tank to be detected, and fixing the antenna of the RFID reader to be right opposite to the RFID tag, so that the RFID reader can penetrate through the water tank to be detected to detect the RFID tag. Then, in a training stage, filling water into an empty water tank to be detected until the water tank is full, and collecting Signal data obtained by an RFID reader in the water filling process, wherein the Signal data comprises a Signal Strength value (Received Signal Strength Indication) which is an RSSI value;
s2, preprocessing the RSSI value acquired in the step S1 to eliminate abnormal values, so that the acquired RSSI value is more representative, and a preprocessed RSSI oscillogram is obtained; in particular to a method for preparing a high-performance nano-silver alloy,
s21, carrying out median filtering processing on the collected original RSSI values, eliminating isolated noise points, setting a sliding window, then sorting data in the sliding window, selecting a middle value to replace the original value, and then outputting the median filtering as follows:
ri＝Med(xi)
where Med () is a one-dimensional median filter function, riIs the median filtered RSSI value, xiIs the RSSI value of the ith sample point;
s22, considering that the RSSI values have the characteristics of roughness and poor time stability, removing abnormal values of the RSSI values processed in the step S21 by using a local weighted linear regression-based algorithm, traversing N sampling points, calculating the distance between each sampling point and a point t to be predicted, namely the distance between each sampling point and the point t to be predicted, wherein the distance is the weight of a contribution error of each sampling point, and a Gaussian kernel is used for endowing a point near a sampling point i with higher weight, and the corresponding weight of the Gaussian kernel is as follows:
Figure BDA0002185685430000051
wherein, ω isiIs a weight matrix with N elements and only diagonal elements, t is the time value of the point to be predicted, t isiIs the time of the ith sample point, λ is the wavelength parameter, λ controls the rate at which the weight decreases, and point tiThe closer to t, ωiThe greater the value of (A);
obtaining a kernel function matrix W composed of N points to be measured as:
Figure BDA0002185685430000052
wherein, ω isiIs the weight value at the ith sample point;
using least squares pair (t)i，ri) And i is 1,2, …, N, calculating the sum of squares of residuals, and obtaining an optimal regression coefficient theta:
θ＝(XTWX)-1XTWY
wherein X is (t)1,t2…,tN) Is N samplesThe time values of the points form a vector, T is the transpose sign of the matrix, and Y is (r)1,r2…,rN) The RSSI values corresponding to the N sampling points form a vector; then, the obtained optimal regression coefficient is substituted into the following formula to obtain an estimated value of each sampling point:
x′i＝θTti
wherein, x'iThe RSSI value of the ith sampling point after the local weighted linear regression is obtained;
and further obtaining a preprocessed RSSI waveform image with abnormal values removed.
S3, according to a liquid level monitoring algorithm, extracting signal characteristics of the data preprocessed in the step S2, and accordingly obtaining a threshold value corresponding to the liquid level height state; in particular to a method for preparing a high-performance nano-silver alloy,
s31, introducing a slope, and obtaining a final threshold value with an expression as follows:
Figure BDA0002185685430000061
in the formula (f)iIs the characteristic value of the ith sample point,
Figure BDA0002185685430000062
x′i、x′i+1the RSSI value, t, of the ith and (i + 1) th sampling point after the local weighted linear regressioni、ti+1Is the time value, k, corresponding to the ith and the (i + 1) th sampling pointsiThe slope of the ith sampling point;
s32, according to the preprocessed RSSI waveform obtained in step S2, as shown in fig. 3, the valley point in the obtained RSSI waveform is taken as the B point, the maximum RSSI value in the acquisition time after the occurrence of the valley point is taken as the S point, and the threshold values of the S point and the B point are respectively determined as:
Figure BDA0002185685430000063
wherein k isS、x′SSlope and RSSI value, k, corresponding to the starting point respectivelyB、x′BRespectively corresponding to the slope and RSSI value of the trough;
s33, the threshold f obtained in the step S32S、fBAs the change threshold value of liquid level state respectively, specifically be, divide into three liquid level state with the liquid level state of the water tank that awaits measuring, do respectively: a normal ascending area, a safety buffer area and an overflow warning area, wherein the threshold value fSAs the liquid level state change threshold value of the normal ascending region and the safety buffer region, the threshold value fBAs the liquid level state change threshold value of the safety buffer area and the overflow warning area.
And S4, in the real-time monitoring stage, the RFID reader collects the RSSI value in real time, and compares the RSSI value collected in real time with the threshold value obtained in the step S3 to obtain the area where the real-time liquid level in the water tank to be detected is located. In particular to a method for preparing a high-performance nano-silver alloy,
when f is>fSWhen the water level is in the normal rising area; when f isB＜f≤fSWhen the water level is in the safe buffer area; when f is less than or equal to fBAnd the water level is in an overflow warning area, wherein f is an RSSI value acquired in real time.
According to the liquid level monitoring method based on the RFID, different liquid level states are obtained by utilizing the shielding effect of the rising liquid level on the RFID signals. When the liquid level rises, the line-of-sight link between the RFID tag and the antenna of the RFID reader will be blocked, as shown in fig. 2. The different liquid level states can be distinguished by identifying critical characteristic values during successive liquid level rises, as in fig. 3. Preprocessing the acquired signal data; extracting signal characteristics from the preprocessed data according to a liquid level monitoring algorithm so as to obtain a threshold value corresponding to the liquid level height state; and finally, comparing the RSSI value acquired in real time with a threshold value, and identifying the area where the liquid level is located. The embodiment method is simple, convenient and feasible, and reliable in monitoring, thereby being convenient for realizing more efficient utilization and storage of liquid
The liquid level monitoring method based on the RFID adopts a non-contact sensing technology, does not need to contact water, realizes high sensing by carrying out feature extraction on the reflected signal of the passive RFID label, can be applied to liquid level monitoring of household or industrial water tanks, and achieves the aim of safe water supply. The method of the embodiment utilizes the multipath effect generated by the liquid level to the RSSI value in the radio frequency identification technology in the rising process, the RSSI value is changed regularly due to the change of the liquid level, and the RSSI value is changed due to the fact that the multipath effects of the water levels in different height states are different. According to the method, the RFID signal data are used as the liquid level state judgment standard when the liquid level rises, the area where the liquid level is located can be identified in the rising process, and therefore the liquid can be more efficiently utilized and stored.
According to the liquid level monitoring method based on the RFID in the indoor environment, the wireless radio frequency signals are used as liquid level monitoring evaluation factors, and can be obtained from RFID equipment, so that the whole system is simple, convenient and feasible.
According to the liquid level monitoring method based on the RFID in the indoor environment, the RFID technology is adopted, the RSSI value is extracted from the RSSI value, the algorithm for local weighted regression is adopted to remove abnormal values, the RSSI value with robustness is obtained, meanwhile, the slope characteristics are combined, more accurate and reliable data are obtained, the monitoring reliability is guaranteed, and the liquid level monitoring method based on the RFID in the indoor environment can be suitable for liquid level detection in various containers.
Compared with the traditional water level identification meter which can only statically identify the height, the liquid level monitoring method based on the RFID in the indoor environment can identify the area where the liquid level is located in real time by comparing the RSSI value acquired in real time with the threshold value in the rising process of the liquid level.

Claims (3)

1. A liquid level monitoring method based on RFID in an indoor environment is characterized in that: acquiring signal data of an RFID (radio frequency identification) label as a judgment standard of a liquid level state, wherein the judgment standard comprises a training stage and a real-time monitoring stage, a threshold corresponding to the liquid level height state is obtained in the training stage, and then the monitoring of the region where the real-time liquid level in the water tank to be detected is located is realized in the real-time monitoring stage; comprises the following steps of (a) carrying out,
s1, attaching the RFID tag to the outer wall of the water tank to be tested, respectively arranging the RFID tag and the RFID reader on two sides of the water tank to be tested, then injecting water into the empty water tank to be tested until the water is full in the training stage, and collecting signal data obtained by the RFID reader in the water injection process, wherein the signal data comprises a signal strength value, namely an RSSI value;
s2, preprocessing the RSSI value acquired in the step S1 to obtain a preprocessed RSSI oscillogram;
s3, according to a liquid level monitoring algorithm, extracting signal characteristics of the data preprocessed in the step S2, and accordingly obtaining a threshold value corresponding to the liquid level height state; in particular to a method for preparing a high-performance nano-silver alloy,
s31, introducing a slope, and obtaining a final threshold value with an expression as follows:
Figure FDA0002873335140000011
in the formula (f)iIs the characteristic value of the ith sample point,
Figure FDA0002873335140000012
x′i、x′i+1the RSSI value, t, of the ith and (i + 1) th sampling point after the local weighted linear regressioni、ti+1Is the time value, k, corresponding to the ith and the (i + 1) th sampling pointsiThe slope of the ith sampling point;
s32, according to the preprocessed RSSI waveform diagram obtained in step S2, using a valley point in the obtained RSSI waveform diagram as a point B, using a maximum RSSI value in the acquisition time after the occurrence of the valley point as a point S, and obtaining a threshold value at the point S and a threshold value at the point B as:
Figure FDA0002873335140000013
wherein k isS、x′SSlope and RSSI value, k, corresponding to the starting point respectivelyB、x′BRespectively corresponding to the slope and RSSI value of the trough;
s33, the threshold f obtained in the step S32S、fBAs the change threshold value of liquid level state respectively, specifically be, divide into three liquid level state with the liquid level state of the water tank that awaits measuring, do respectively: a normal ascending area, a safety buffer area and an overflow warning area, wherein the threshold value fSAs the liquid level state change threshold value of the normal ascending region and the safety buffer region, the threshold value fBAs a safety buffer and overflowA liquid level state change threshold value of the alert zone;
and S4, in the real-time monitoring stage, the RFID reader collects the RSSI value in real time, and compares the RSSI value collected in real time with the threshold value obtained in the step S3 to obtain the area where the real-time liquid level in the water tank to be detected is located.
2. The RFID-based liquid level monitoring method in an indoor environment of claim 1, wherein: in step S2, the RSSI value collected in step S1 is preprocessed, specifically,
s21, carrying out median filtering processing on the collected original RSSI values, eliminating isolated noise points, setting a sliding window, then sorting data in the sliding window, selecting a middle value to replace the original value, and then outputting the median filtering as follows:
ri＝Med(xi)
where Med () is a one-dimensional median filter function, riIs the median filtered RSSI value, xiIs the RSSI value of the ith sample point;
s22, carrying out abnormal value elimination on the RSSI value processed in the step S21 by an algorithm based on local weighted linear regression, traversing N sampling points, and endowing each point near the point to be detected with a certain weight by using a Gaussian kernel, wherein the corresponding weight of the Gaussian kernel is as follows:
Figure FDA0002873335140000021
wherein, ω isiIs the weight value at the ith sampling point, t is the time value corresponding to the point to be predicted, tiIs the time value of the ith sample point, λ is the wavelength parameter, λ controls the rate at which the weight decreases, and t is the pointiThe closer to t, ωiThe greater the value of (A);
obtaining a kernel function matrix W composed of N points to be measured as:
Figure FDA0002873335140000022
wherein, ω isiIs the weight value at the ith sample point;
using least squares pair (t)i，ri) And i is 1,2, …, N, calculating the sum of squares of residuals, and obtaining an optimal regression coefficient theta:
θ＝(XTWX)-1XTWY
wherein X is (t)1,t2…,tN) Is a vector of time values of N sampling points, T is a matrix transposition symbol, and Y is (r)1,r2…,rN) The RSSI values corresponding to the N sampling points form a vector; then, the obtained optimal regression coefficient is substituted into the following formula to obtain an estimated value of each sampling point:
x′i＝θTti
wherein, x'iThe RSSI value of the ith sampling point after the local weighted linear regression is obtained;
and further obtaining a preprocessed RSSI waveform image with abnormal values removed.
3. The RFID-based liquid level monitoring method in an indoor environment of claim 1, wherein: in step S4, the RSSI value collected in real time is compared with the threshold value obtained in step S3 to obtain the area where the real-time liquid level in the water tank to be measured is located, specifically,
when f is>fSWhen the water level is in the normal rising area; when f isB<f≤fSWhen the water level is in the safe buffer area; when f is less than or equal to fBAnd the water level is in an overflow warning area, wherein f is an RSSI value acquired in real time.
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Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102506963A (en) * 2011-11-14 2012-06-20 苏州佳世达电通有限公司 Capacity sensing device
CN102750576A (en) * 2012-06-01 2012-10-24 北京物资学院 Radio frequency identification device (RFID) label with level-detecting device, RFID system with level-detecting device and level detection method
US8933789B1 (en) * 2012-07-13 2015-01-13 The United States of America as represented by the Administrator of the National Aeronauties and Space Administration Systems and methods for RFID-enabled information collection
CN105389975A (en) * 2015-12-11 2016-03-09 北京航空航天大学 Chauffeured car scheduling method and apparatus
CN106382969A (en) * 2016-09-05 2017-02-08 南京大学 Container liquid height detection system based on radio frequency identification (RFID) technique and working method thereof
CN107425257A (en) * 2017-08-29 2017-12-01 厦门致联科技有限公司 A kind of integrated liquid level detection device based on RFID
CN108804758A (en) * 2018-05-01 2018-11-13 南京信息工程大学 The law study method of Rare Earth Mine tail Rare Earth Element Contents based on data fitting

Family Cites Families (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20070010278A1 (en) * 2005-06-21 2007-01-11 D Agostino Anthony System and method for controlling power consumption in a wireless device
CN102322920A (en) * 2011-08-24 2012-01-18 四川大学 Method for measuring existence of powdery materials in specific material position of container and implementation material level switch thereof
CN103090930B (en) * 2011-10-28 2016-08-03 上海凡宜科技电子有限公司 Radar levelmeter and signal processing method thereof
CN103455778A (en) * 2012-06-01 2013-12-18 北京物资学院 Object position measurement RFID system and object position measurement method thereof
CN202648743U (en) * 2012-07-17 2013-01-02 成都九洲电子信息系统股份有限公司 Water level monitoring system using radio-frequency communication method
CN207282694U (en) * 2017-08-29 2018-04-27 厦门致联科技有限公司 A kind of integrated liquid level detection device based on RFID

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102506963A (en) * 2011-11-14 2012-06-20 苏州佳世达电通有限公司 Capacity sensing device
CN102750576A (en) * 2012-06-01 2012-10-24 北京物资学院 Radio frequency identification device (RFID) label with level-detecting device, RFID system with level-detecting device and level detection method
US8933789B1 (en) * 2012-07-13 2015-01-13 The United States of America as represented by the Administrator of the National Aeronauties and Space Administration Systems and methods for RFID-enabled information collection
CN105389975A (en) * 2015-12-11 2016-03-09 北京航空航天大学 Chauffeured car scheduling method and apparatus
CN106382969A (en) * 2016-09-05 2017-02-08 南京大学 Container liquid height detection system based on radio frequency identification (RFID) technique and working method thereof
CN107425257A (en) * 2017-08-29 2017-12-01 厦门致联科技有限公司 A kind of integrated liquid level detection device based on RFID
CN108804758A (en) * 2018-05-01 2018-11-13 南京信息工程大学 The law study method of Rare Earth Mine tail Rare Earth Element Contents based on data fitting

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
40_T混合磁体外超导线圈迫流氦流动摩擦因子分析;胡煜涛;《中国优秀硕士学位论文全文数据库基础科学辑》;20180115;第5.3节 *

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