CN110657864A - Sensor response time measuring method - Google Patents
Sensor response time measuring method Download PDFInfo
- Publication number
- CN110657864A CN110657864A CN201910951417.9A CN201910951417A CN110657864A CN 110657864 A CN110657864 A CN 110657864A CN 201910951417 A CN201910951417 A CN 201910951417A CN 110657864 A CN110657864 A CN 110657864A
- Authority
- CN
- China
- Prior art keywords
- time
- noise signal
- sensor
- frequency domain
- domain
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01F—MEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME
- G01F25/00—Testing or calibration of apparatus for measuring volume, volume flow or liquid level or for metering by volume
- G01F25/20—Testing or calibration of apparatus for measuring volume, volume flow or liquid level or for metering by volume of apparatus for measuring liquid level
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D18/00—Testing or calibrating apparatus or arrangements provided for in groups G01D1/00 - G01D15/00
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Fluid Mechanics (AREA)
- Monitoring And Testing Of Nuclear Reactors (AREA)
Abstract
The invention relates to the technical field of sensor response time testing, in particular to a sensor response time measuring method. The method comprises the following steps: collecting a noise signal output by a sensor; analyzing the frequency domain delay of the noise signal in a frequency domain, and analyzing the time domain delay of the noise signal in a time domain; taking the maximum value of the frequency domain delay and the time domain delay as the response time of the sensor; wherein the noise signal satisfies a normal distribution. According to the technical scheme, the noise signals of the sensor are analyzed in two independent modes, namely a frequency domain analysis method and a time domain analysis method, and the final response time is determined by comparing the results of time domain response time and frequency domain response time. The actual performance of the sensor can be effectively checked regularly, potential sensor performance degradation is identified in advance, and misoperation/refusal action of the safety system caused by the sensor performance degradation is avoided, so that the accurate and reliable measurement of key parameters of the nuclear power plant is ensured, and the system is operated safely and economically.
Description
Technical Field
The invention relates to the technical field of sensor response time testing, in particular to a sensor response time measuring method.
Background
Control systems and safety systems of nuclear power plants rely primarily on process instrumentation to provide reliable information for confirming plant safety and efficiency. Therefore, there is a need to verify the performance of such instruments at predetermined intervals over the life of the plant. Therefore, it is desirable to measure the response time of sensing devices in the nuclear plant control system and safety system at predetermined time intervals.
Disclosure of Invention
The present invention provides a method for measuring the response time of a sensor to solve the above technical problems.
A sensor response time measurement method, comprising:
collecting a noise signal output by a sensor;
analyzing the frequency domain delay of the noise signal in a frequency domain, and analyzing the time domain delay of the noise signal in a time domain;
taking the maximum value of the frequency domain delay and the time domain delay as the response time of the sensor;
wherein the noise signal satisfies a normal distribution.
According to the technical scheme, the noise signals of the sensor are analyzed in two independent modes, namely a frequency domain analysis method and a time domain analysis method, and the final response time is determined by comparing the results of time domain response time and frequency domain response time. The actual performance of the sensor can be effectively checked regularly, potential sensor performance degradation is identified in advance, and misoperation/refusal action of the safety system caused by the sensor performance degradation is avoided, so that the accurate and reliable measurement of key parameters of the nuclear power plant is ensured, and the system is operated safely and economically.
Preferably, in the process of acquiring the noise signal output by the sensor, the sampling frequency is greater than 200 Hz.
Preferably, the acquiring the noise signal output by the sensor includes: firstly, the direct current component in the sensor output signal is filtered, and secondly, the irrelevant noise component in the sensor output signal is eliminated through low-pass filtering.
Preferably, in filtering out the dc component in the sensor output signal, a high pass filter or a dc offset meter is used to filter out the dc component in the sensor output signal.
Preferably, the frequency spectrum of the noise signal comprises an unattenuated portion, a turning point portion and an attenuated transition portion.
Preferably, the analyzing the frequency domain delay of the noise signal in the frequency domain includes: fourier transforming the noise signal to obtain a power spectral density curve Y (f) of the noise signal; fitting and obtaining a frequency domain transfer function H (f) based on the power spectral density curve Y (f); obtaining a frequency domain ramp response based on the frequency domain transfer function h (f); and taking the maximum time delay in a certain time period of the frequency domain slope response as the frequency domain time delay of the noise signal.
Preferably, in the fourier transform of the noise signal to obtain the power spectral density curve y (f) of the noise signal: and calculating a power density curve Y (f) of the noise signal by using a periodogram method and Fourier transform.
Preferably, in the process of fitting the frequency domain transfer function h (f) based on the power spectral density curve y (f): using fitting functionsAnd (6) fitting.
Preferably, the analyzing the time-domain delay of the noise signal in the time domain includes: calculating a power spectral density PSD using a power spectral density AR model for the noise signal; acquiring a time domain transfer function H (z) based on the calculated power spectral density PSD; obtaining a time-domain ramp response based on the time-domain transfer function h (z); and taking the maximum time delay in a certain time period of the time domain slope response as the time domain time delay of the noise signal.
Preferably, the obtaining of the time-domain transfer function h (z) based on the calculated power spectral density PSD is: power universal density based on calculationDetermining parameter p and parameter a in formulakA value of (d); based on the parameters p and akDetermining a transfer function 。
The invention has the following beneficial effects:
the noise signals of the sensor are analyzed in two independent modes, namely a frequency domain analysis method and a time domain analysis method, and the final response time is determined by comparing the results of the time domain response time and the frequency domain response time. The frequency domain analysis method and the time domain analysis method have differences, the data analysis and calculation processes are completely independent, but the power spectral densities calculated by the two methods are almost consistent, and the calculation accuracy of the frequency domain power spectral densities and the time domain power spectral densities is ensured.
Drawings
Fig. 1 is a flowchart of a method for measuring a response time of a sensor according to a first embodiment of the present invention.
Fig. 2 is a schematic diagram of a system for generating a noise signal according to a first embodiment of the present invention.
Fig. 3 is a frequency domain slope response curve according to a first embodiment of the invention.
Fig. 4 is a time-domain ramp response curve according to a first embodiment of the present invention.
Detailed Description
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. Unless otherwise defined, all terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that the conventional terms should be interpreted as having a meaning that is consistent with their meaning in the relevant art and this disclosure. The present disclosure is to be considered as an example of the invention and is not intended to limit the invention to the particular embodiments.
Noise analysis techniques monitor the response of sensors, such as level transmitters, to natural disturbances (noise) present in the water/steam system while the nuclear power plant is in operation. These fluctuations are typically produced by system currents, pump turbulence, random core heat transfer, and other naturally occurring phenomena. The noise analysis technique can also be used for response time experiments of sensors such as thermocouples, neutron detectors and the like, and the response time measurement method of the sensor is described below by taking the response time measurement method of the liquid level transmitter as an example. The noise analysis method of the invention mainly comprises the following technical points: collecting noise signals meeting normal distribution; analysis in the time domain by an Autoregressive (AR) model of power spectral density; the power spectral density is calculated in the frequency domain by Fast Fourier Transform (FFT) of the discrete signal for analysis, and the noise analysis flow is detailed in fig. 1. The following embodiment will describe the implementation of the method of the present invention in detail by taking the response time measurement method of a level transmitter as an example.
Example one
The liquid level transmitter can be equivalent to a linear system, the noise source is used as input, the liquid level transmitter generates a noise output signal, and the embodiment analyzes the noise signal output by the liquid level transmitter to obtain an equivalent transfer function model of the liquid level transmitter, so that the time delay characteristic of the transmitter is obtained.
The response time measuring method of the embodiment includes the steps of:
firstly, collecting noise signal output by sensor
The noise analysis has high requirements on signals, the liquid level transmitter can be equivalent to a low-pass filter, the frequency response of the transmitter is determined after the transmitter is installed on the site, the response time of the liquid level transmitter is related to the attenuation frequency of the liquid level transmitter, the response time is faster when the attenuation frequency is larger, and the response time is slower when the attenuation frequency is smaller. If the noise signal is a narrow-band process relative to the natural frequency of the transmitter (the frequency of the noise source is less than the natural frequency of the transmitter), the acquired signal is represented by the frequency response characteristic of the noise signal, and the frequency response of the real liquid level transmitter cannot be acquired. Only if the noise signal is a broadband process relative to the transmitter's natural frequency (the noise source frequency is greater than the transmitter natural frequency) will a true frequency response be obtained for the level transmitter. The narrow-band process can be used for evaluating the response time of the liquid level transmitter, the response time calculated by the narrow-band process is longer than the real response time of the liquid level transmitter, and as long as the response time calculated by the narrow-band process meets the requirement of safety analysis, the response time of the liquid level transmitter inevitably meets the requirement of the safety analysis, so that the noise analysis is a conservative response time testing method, and the noise signals meet the following requirements:
1) the noise signal is strong enough, and the frequency distribution bandwidth of the noise signal is wide enough. I.e. the spectrum of the noise signal is required to contain three parts, unattenuated, turning point, and attenuated transition.
2) The noise signal is a random white noise, and the amplitude probability distribution of the noise signal meets the normal distribution and cannot be monotonically increased or monotonically decreased.
3) The noise signal is a random process, and the time for acquiring the signal must be long enough during data acquisition, so that the acquired data includes all states of the random signal, i.e. the acquired signal is subjected to a respective-state experience process.
The liquid level transmitters of a three-door nuclear power 1/2 unit need to measure response time, 32 liquid level transmitters are required, the liquid level transmitters are used for measuring the liquid level of CMT, the CMT is a special safety facility, and during the normal operation of the unit, the liquid level is in a stable level, a noise source with enough strength is not available, and the frequency response of the liquid level transmitters cannot be stimulated. Fig. 2 is a schematic diagram of a system for generating a noise signal according to this embodiment. The measuring tube 1 is connected to the CMT via two isolation valves 2 in order to introduce the liquid inside the CMT into the measuring tube 1. The level transmitter of the present embodiment is mounted in the measuring tube 1 for detecting the level of liquid in the measuring tube 1. The top of the measuring pipe 1 is provided with an exhaust valve 11, and the bottom is connected with a filtering pressure reducing valve 3 through a drain valve 12. By opening the trap 12, air can be fed into the measuring tube 1 via the filter and pressure relief valve 3, which air is injected into the measuring tube 1 and causes fluctuations in the liquid level in the measuring tube, which results in noise. In this embodiment, the method for acquiring the noise signal output by the sensor based on the noise signal generating system shown in fig. 2 is as follows:
firstly, opening an isolation valve to inject liquid with 15% -20% of liquid level into a measuring pipe 1, then opening a water valve to introduce compressed air into the measuring pipe 1 to cause the liquid level in the measuring pipe 1 to fluctuate, and maintaining the fluctuation of the liquid level in the measuring pipe 1 between 35% -45% by adjusting a filtering and reducing valve 3, thereby ensuring that the signal intensity is large enough, and then starting to collect the output signal of a liquid level transmitter. The frequency of a white noise signal in the nature is generally within 100Hz, and the sampling frequency of the signal needs to satisfy the nyquist sampling theorem, that is, the sampling frequency must be greater than 2 times of the maximum frequency of the signal (i.e., 200 Hz) to avoid the signal aliasing phenomenon. The sampling frequency in this example was 2000Hz, the acquisition time was about 15 minutes, and approximately 9843040 data were acquired.
When the output signal of the liquid level transmitter is collected, firstly, the direct current component in the output signal of the transmitter needs to be filtered, and secondly, the irrelevant noise component in the output signal of the transmitter is eliminated through low-pass filtering. Specifically, a high pass filter or a dc offset meter can be used to filter out the dc component of the transmitter output signal.
Analyzing the frequency domain delay of the noise signal in the frequency domain, and analyzing the time domain delay of the noise signal in the time domain
1. Frequency domain delay of frequency domain analysis noise signal
The frequency domain analysis analyzes the noise signal based on Fourier transform, discrete Fast Fourier Transform (FFT) is carried out on the collected signal, and then the power spectral density PSD is calculated according to the FFT. There is a one-to-one correspondence between the fourier transform and the power spectral density of the discrete signal. The power spectral density analysis is based on the analysis of frequency domain signal energy, and a voltage signal acquired in the field is changed into a time domain signal along with time and is changed into a frequency domain signal after being converted through Fourier transform.
The liquid level transmitter is equivalent to a linear system, and the noise source outputs a collected voltage signal through the linear system. Assuming that a field noise source signal is x (t), an equivalent linear system transfer function of the transmitter is h (t), an output signal of the noise source is y (t), a response process of the input signal through the function is convolution operation, and a mathematical expression of the response process of the noise source through the transmitter is as follows:
wherein:
"+" operation is convolution operation;
"×" is the product operation;
t is time.
According to the convolution theorem, the product relationship of the time domain convolution in the frequency domain is as follows:
wherein:
x (f) is the Fourier transform of x (t);
h (f) is the Fourier transform of h (t);
y (f) is the Fourier transform of y (t);
f is the frequency.
In this embodiment, the frequency domain delay of the frequency domain analysis noise signal specifically includes:
A. fourier transforming the noise signal to obtain a power spectral density curve Y (f) of the noise signal. In order to improve the capability of calculating and processing data, the power spectral density curve y (f) is calculated by using fourier transform in the periodogram method in the embodiment. The collected data are divided into 30 groups, and single-side power spectral density data and distribution curves of noise data are obtained through a Fast Fourier Transform (FFT) function.
B. Fitting a frequency domain transfer function h (f) based on the power spectral density curve y (f). Establishing a proper mathematical model:
the fitting of the power spectral density curve is done using the curve fitting tool cftool based on the formula of the fitting function h (f) described above. The delay in the time domain is represented by attenuation lag in the frequency domain, and the main characteristic of the response time is represented by the turning point of the power spectral density from no attenuation to attenuation, so that the fitting effect of the low frequency band is ensured in the curve fitting process. And after the fitting is finished, obtaining a transfer function H (f) according to the characteristic parameters returned by the fitting result.
C. Obtaining a frequency domain ramp response based on the frequency domain transfer function h (f). The response time of the converter is mainly used for safety event analysis of shutdown or special functions, and under the accident condition, the parameter change is close to the slope response. A ramp response curve (as shown in fig. 3) is obtained using the unit ramp signal as an input to the transfer function, and the response time is calculated from the time difference between the ramp input and the ramp output.
D. And taking the maximum time delay in a certain time period of the frequency domain slope response as the frequency domain time delay of the noise signal. In the safety analysis report of the power plant, there is a clear requirement on the maximum allowable time of the response time. The method comprises the steps that a large delay exists at a position before the slope response of a transmitter is 0.5 second, the descending or ascending speed of the liquid level cannot be determined under an accident working condition, and if the liquid level changing speed is too high, the large delay possibly exists, so that deviation operation is carried out on the slope response and slope input on the basis of conservative consideration, and the maximum delay time of the slope response is obtained by utilizing a max function in matlab and is respectively used as the response time of a frequency domain and a time domain of the transmitter. Since the transfer function of order 2 or more than order 2 has an oscillation link (for example, the time period of 0-0.2s in fig. 3), a certain time period should include the oscillation link during the time delay of the frequency domain, so that the maximum time delay including the oscillation link can be selected during the time delay of the frequency domain. In this embodiment, since the time offset between the ramp response and the ramp input is already stable in 1.5 seconds, the maximum delay in the time period of 0-1.5S is selected as the frequency domain delay of the noise signal, and the amplitude is 0.798 in fig. 3, and the delay is 0.901S-0.798S = 0.103S.
2. Time-domain delay of time-domain analysis noise signal
And directly calculating the power spectral density of the noise signal obtained in the first step by using an AR model power spectral density function. The method specifically comprises the following steps:
A. firstly, the power spectral density AR model is adopted to calculate the power spectral densityA power spectral density curve is obtained.
B. Comparing the power spectral density calculated by the AR model with the frequency domain power spectral density Y (f), determining parameters p and a when the deviation between the two is acceptablekThe value of (c). Then based on the fitted parameters p and akDetermining a time-domain transfer function:
C. a time domain ramp response is obtained based on the frequency domain transfer function h (z). In this embodiment, the acquisition of the ramp response is obtained in two steps: first by fitting a function ofFitting is performed to obtain a step response function. Subsequently, the step response function is integrated to obtain a time-domain ramp response.
D. And taking the maximum time delay in a certain time period of the time domain slope response as the time domain time delay of the noise signal. In the safety analysis report of the power plant, there is a clear requirement on the maximum allowable time of the response time. The method comprises the steps that a large delay exists at a position before the slope response of a transmitter is 0.5 second, the descending or ascending speed of the liquid level cannot be determined under an accident working condition, and if the liquid level changing speed is too high, the large delay possibly exists, so that deviation operation is carried out on the slope response and slope input on the basis of conservative consideration, and the maximum delay time of the slope response is obtained by utilizing a max function in matlab and is respectively used as the response time of a frequency domain and a time domain of the transmitter. Since the transfer function of order 2 or more than order 2 has an oscillation link (for example, in the time period of 0-0.2s in fig. 4), when the time-domain delay is calculated, a certain time period should include the oscillation link, so that the maximum time delay including the oscillation link can be selected when the time-domain delay is calculated. In this embodiment, since the time offset between the ramp response and the ramp input is already stable in 1.5 seconds, the maximum delay in the time period of 0-1.5S is selected as the time-domain delay of the noise signal, and the amplitude is 100 in fig. 4, and the delay is 0.954S-0.854S = 0.1S.
Taking the maximum value of the frequency domain delay and the time domain delay as the response time of the sensor
The frequency domain and the time domain have difference in response time results, no matter whether the time domain and the frequency domain are based on power spectral density to perform response time calculation, the response time of the transmitter is estimated through an equivalent transfer function model of the transmitter, the calculation results of the two methods are completely independent, which result is closer to the real response time of the liquid level transmitter cannot be determined, and the larger one of the frequency domain and the time domain response time is selected based on conservative consideration.
The model of the frequency domain transfer function H (f) is Fourier transform, the model of the time domain transfer function H (Z) is Z transform, and the transfer function models are completely independent, so that the power spectral density calculation results are different. However, the power spectral densities calculated by the two modes are almost consistent, and the power spectral density calculated by the AR model verifies the power spectral density calculated by the frequency domain, so that the accuracy of calculation of the frequency domain and the time domain power spectral density is ensured.
Based on the method, the applicant calculates the result of the response time of the CMT A magnetic float liquid level transmitter by using a noise analysis algorithm according to 1400 ten thousand data acquired on site, and the result is detailed in the following table:
and (3) the response time of the instrument obtained by noise analysis is 0.2s, and the measurement result meets the requirement of the acceptance criterion.
Although embodiments of the present invention have been described, various changes or modifications may be made by one of ordinary skill in the art within the scope of the appended claims.
Claims (10)
1. A sensor response time measurement method, comprising:
collecting a noise signal output by a sensor;
analyzing the frequency domain delay of the noise signal in a frequency domain, and analyzing the time domain delay of the noise signal in a time domain;
taking the maximum value of the frequency domain delay and the time domain delay as the response time of the sensor;
wherein the noise signal satisfies a normal distribution.
2. A sensor response time measurement method according to claim 1, characterized by:
and in the process of collecting the noise signals output by the sensor, the sampling frequency is greater than 200 Hz.
3. A method of sensor response time measurement according to claim 2, wherein said acquiring a noise signal output by a sensor comprises:
firstly, the direct current component in the sensor output signal is filtered, and secondly, the irrelevant noise component in the sensor output signal is eliminated through low-pass filtering.
4. A sensor response time measurement method according to claim 3, characterized in that:
and in the step of filtering the direct-current component in the output signal of the sensor, a high-pass filter or a direct-current offset meter is adopted to filter the direct-current component in the output signal of the sensor.
5. A sensor response time measurement method according to claim 1, characterized by:
the frequency spectrum of the noise signal comprises an unattenuated portion, a turning point portion and an attenuated transition portion.
6. The method of claim 1, wherein analyzing the frequency domain delay of the noise signal in the frequency domain comprises:
fourier transforming the noise signal to obtain a power spectral density curve Y (f) of the noise signal;
fitting and obtaining a frequency domain transfer function H (f) based on the power spectral density curve Y (f);
obtaining a frequency domain ramp response based on the frequency domain transfer function h (f);
and taking the maximum time delay in a certain time period of the frequency domain slope response as the frequency domain time delay of the noise signal.
7. The method of claim 6, wherein the Fourier transforming the noise signal to obtain the power spectral density curve Y (f) of the noise signal comprises:
and calculating a power density curve Y (f) of the noise signal by using a periodogram method and Fourier transform.
9. A method of measuring sensor response time according to claim 1, wherein said analyzing the time domain delay of said noise signal in the time domain comprises:
calculating a power spectral density PSD using a power spectral density AR model for the noise signal;
acquiring a time domain transfer function H (z) based on the calculated power spectral density PSD;
obtaining a time-domain ramp response based on the time-domain transfer function h (z);
and taking the maximum time delay in a certain time period of the time domain slope response as the time domain time delay of the noise signal.
10. The method of claim 1, wherein the obtaining the time-domain transfer function h (z) based on the calculated PSD of the power spectral density is:
power universal density based on calculationDetermining parameter p and parameter a in formulakA value of (d);
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201910951417.9A CN110657864B (en) | 2019-10-08 | 2019-10-08 | Sensor response time measuring method |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201910951417.9A CN110657864B (en) | 2019-10-08 | 2019-10-08 | Sensor response time measuring method |
Publications (2)
Publication Number | Publication Date |
---|---|
CN110657864A true CN110657864A (en) | 2020-01-07 |
CN110657864B CN110657864B (en) | 2020-12-18 |
Family
ID=69040219
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201910951417.9A Active CN110657864B (en) | 2019-10-08 | 2019-10-08 | Sensor response time measuring method |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN110657864B (en) |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN113138318A (en) * | 2021-04-27 | 2021-07-20 | 山东英信计算机技术有限公司 | Phase jitter test method and system |
CN114459679A (en) * | 2021-11-08 | 2022-05-10 | 上海核工程研究设计院有限公司 | Method for measuring on-line dynamic response time of sensor |
CN114500615A (en) * | 2022-04-18 | 2022-05-13 | 深圳日晨物联科技有限公司 | Intelligent terminal based on thing allies oneself with sensing technology |
Citations (15)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP3093179B2 (en) * | 1989-01-27 | 2000-10-03 | ドルビー・ラボラトリーズ・ライセンシング・コーポレーション | Short delay encoder and decoder for high quality audio |
CN101068232A (en) * | 2007-06-12 | 2007-11-07 | 华为技术有限公司 | Method and device for getting channel time domain response, OFDM fine symbol synchronizing method and device |
CN101093403A (en) * | 2006-06-22 | 2007-12-26 | 国际商业机器公司 | Method for reducing electromagnetic interference of clock circuit and clock management circuit |
CN101141429A (en) * | 2006-09-06 | 2008-03-12 | 华为技术有限公司 | Method and device of measuring carrier interference noise ratio |
CN101266292A (en) * | 2008-05-08 | 2008-09-17 | 北京航空航天大学 | GNSS reflected signal frequency domain processing unit and method |
CA2831593A1 (en) * | 2011-03-28 | 2012-10-04 | Avl Test Systems, Inc. | Deconvolution method for emissions measurement |
US8576933B2 (en) * | 2011-06-13 | 2013-11-05 | Broadcom Corporation | Apparatus and method for selective single-carrier equalization |
CN103455028A (en) * | 2013-08-29 | 2013-12-18 | 国家电网公司 | Static testing and calibrating method for PID link of control system of wind turbine generator |
CN104902505A (en) * | 2014-03-05 | 2015-09-09 | 中国移动通信集团公司 | Method and device for interference detection, and method, device and system for interference elimination |
US9172423B1 (en) * | 2011-05-02 | 2015-10-27 | University Of Central Florida Research Foundation, Inc. | Correlator time delay extraction for wireless acoustic sensors |
CN107707324A (en) * | 2017-08-28 | 2018-02-16 | 西安电子科技大学 | A kind of acoustical signal delay time estimation method based on phase difference and maximal possibility estimation |
CN107843892A (en) * | 2017-10-31 | 2018-03-27 | 西安电子科技大学 | A kind of high-speed target Doppler velocity measurement method based on least square method |
CN109540192A (en) * | 2018-10-23 | 2019-03-29 | 北京诺亦腾科技有限公司 | A kind of the time delay measurement method, apparatus and storage medium of motion capture system |
CN109901107A (en) * | 2019-03-07 | 2019-06-18 | 西安电子科技大学 | A kind of time difference positioning method, device, computer equipment and readable storage medium storing program for executing |
KR101991844B1 (en) * | 2018-06-20 | 2019-06-21 | 국방과학연구소 | Apparatus and method for estimating time delay |
-
2019
- 2019-10-08 CN CN201910951417.9A patent/CN110657864B/en active Active
Patent Citations (15)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP3093179B2 (en) * | 1989-01-27 | 2000-10-03 | ドルビー・ラボラトリーズ・ライセンシング・コーポレーション | Short delay encoder and decoder for high quality audio |
CN101093403A (en) * | 2006-06-22 | 2007-12-26 | 国际商业机器公司 | Method for reducing electromagnetic interference of clock circuit and clock management circuit |
CN101141429A (en) * | 2006-09-06 | 2008-03-12 | 华为技术有限公司 | Method and device of measuring carrier interference noise ratio |
CN101068232A (en) * | 2007-06-12 | 2007-11-07 | 华为技术有限公司 | Method and device for getting channel time domain response, OFDM fine symbol synchronizing method and device |
CN101266292A (en) * | 2008-05-08 | 2008-09-17 | 北京航空航天大学 | GNSS reflected signal frequency domain processing unit and method |
CA2831593A1 (en) * | 2011-03-28 | 2012-10-04 | Avl Test Systems, Inc. | Deconvolution method for emissions measurement |
US9172423B1 (en) * | 2011-05-02 | 2015-10-27 | University Of Central Florida Research Foundation, Inc. | Correlator time delay extraction for wireless acoustic sensors |
US8576933B2 (en) * | 2011-06-13 | 2013-11-05 | Broadcom Corporation | Apparatus and method for selective single-carrier equalization |
CN103455028A (en) * | 2013-08-29 | 2013-12-18 | 国家电网公司 | Static testing and calibrating method for PID link of control system of wind turbine generator |
CN104902505A (en) * | 2014-03-05 | 2015-09-09 | 中国移动通信集团公司 | Method and device for interference detection, and method, device and system for interference elimination |
CN107707324A (en) * | 2017-08-28 | 2018-02-16 | 西安电子科技大学 | A kind of acoustical signal delay time estimation method based on phase difference and maximal possibility estimation |
CN107843892A (en) * | 2017-10-31 | 2018-03-27 | 西安电子科技大学 | A kind of high-speed target Doppler velocity measurement method based on least square method |
KR101991844B1 (en) * | 2018-06-20 | 2019-06-21 | 국방과학연구소 | Apparatus and method for estimating time delay |
CN109540192A (en) * | 2018-10-23 | 2019-03-29 | 北京诺亦腾科技有限公司 | A kind of the time delay measurement method, apparatus and storage medium of motion capture system |
CN109901107A (en) * | 2019-03-07 | 2019-06-18 | 西安电子科技大学 | A kind of time difference positioning method, device, computer equipment and readable storage medium storing program for executing |
Non-Patent Citations (1)
Title |
---|
符玲 等: ""基于频域动态模型的同步相量测量算法"", 《中国电机工程学报》 * |
Cited By (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN113138318A (en) * | 2021-04-27 | 2021-07-20 | 山东英信计算机技术有限公司 | Phase jitter test method and system |
CN113138318B (en) * | 2021-04-27 | 2022-05-06 | 山东英信计算机技术有限公司 | Phase jitter test method and system |
CN114459679A (en) * | 2021-11-08 | 2022-05-10 | 上海核工程研究设计院有限公司 | Method for measuring on-line dynamic response time of sensor |
CN114459679B (en) * | 2021-11-08 | 2024-09-24 | 上海核工程研究设计院股份有限公司 | Method for measuring on-line dynamic response time of sensor |
CN114500615A (en) * | 2022-04-18 | 2022-05-13 | 深圳日晨物联科技有限公司 | Intelligent terminal based on thing allies oneself with sensing technology |
Also Published As
Publication number | Publication date |
---|---|
CN110657864B (en) | 2020-12-18 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN110657864B (en) | Sensor response time measuring method | |
JP4422412B2 (en) | Flow diagnostic system | |
CN109296506B (en) | Vibration detection method, control method and device for wind turbine generator | |
CN109885854B (en) | ARMA model-based chatter boundary real-time prediction system and prediction method | |
AU2010220551A1 (en) | Method for monitoring wind turbines | |
KR100997009B1 (en) | The method for dynamic detection and on-time warning of industrial process | |
CN105043776A (en) | Aircraft engine performance monitoring and fault diagnosis method | |
CN104457643B (en) | A kind of impulse noise filter method and device of track geometry detection data | |
CN110687791B (en) | Nonlinear oscillation detection method based on improved adaptive frequency modulation modal decomposition | |
CN100456010C (en) | Method for detecting leakage of oil gas pipe based on pressure signal knee | |
CN116975544A (en) | Online power system inertia identification system and method based on ARMAX model | |
Su et al. | Chaotic dynamic characteristics of pressure fluctuation signals in hydro-turbine | |
CN116861313A (en) | Kalman filtering working condition identification method and system based on vibration energy trend | |
CN113820571B (en) | Wind power plant cable insulation on-line monitoring method and device | |
CN105203915A (en) | Diagnosis system and diagnosis method of loosening defect of power transformer winding | |
CN110991074A (en) | Method for judging validity of measurement data of displacement sensor | |
CN103928923B (en) | A kind of network stationary power quality method for early warning based on sensitivity analysis | |
CN109635430A (en) | Grid power transmission route transient signal monitoring method and system | |
CN111523231B (en) | Subsynchronous oscillation analysis method based on EEMD and Prony method | |
CN118278624A (en) | Intelligent analysis system for electric power monitoring data based on mutual inductor | |
WO2020193110A1 (en) | Detecting wind turbine performance change | |
CN110082101B (en) | Planetary gear system fault monitoring method based on input and output torque dynamics characteristics | |
CN110440138B (en) | Exhaust detection method and device for pressure measurement pipeline | |
KR101372489B1 (en) | System for monitoring low pressure turbine using smart sensor | |
CN115576189A (en) | PID control method of air inlet environment simulation system based on self-adaptive homogeneous differentiator |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |