CN113125046B - Thermal resistance degradation detection method based on cross calibration technology - Google Patents
Thermal resistance degradation detection method based on cross calibration technology Download PDFInfo
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Abstract
A thermal resistance degradation detection method based on a cross calibration technology relates to the degradation detection field of thermal resistance, and comprises the following steps: and step S01, the computing platform receives the first temperature data of all the thermal resistors acquired by the data acquisition system, and invokes the accuracy criterion delta H and the linearity degradation criterion delta T stored in the computing platform. Step S02, the computing platform calculates and obtains second temperature data based on the first temperature data of all the thermal resistors. Step S03, the computing platform retrieves third temperature data stored in the computing platform, and obtains fourth temperature data through a cross calibration method according to the second temperature data. And S04, obtaining the real average temperature of the pipeline to be detected at each temperature platform. And step S05, detecting the thermal resistor with degraded precision. Step S06, detecting the thermal resistance with linear degradation. The invention has the advantages that the degradation detection is accurate by using the cross calibration technology, the thermal resistor can be detected without being removed, and the pollution and the influence caused by the disassembly and assembly work are reduced.
Description
Technical Field
The invention relates to the field of degradation detection of thermal resistors, in particular to a thermal resistor degradation detection method based on a cross calibration technology.
Background
The control system and safety system of a nuclear power plant mainly rely on thermal resistors arranged in the main circuit to achieve the measurement of the reactor coolant temperature. These temperatures are used for control and protection of the reactor. The performance of these thermal resistors directly affects the safe and stable operation of the nuclear power plant. The measurement accuracy of these thermal resistors is particularly important for nuclear power plants. With the operation of nuclear power plants, thermal resistors are subjected to high temperature and irradiation for a long time, which makes measurement accuracy and reliability challenging, so that the performance of these thermal resistors is particularly necessary to detect.
The conventional detection technology is to take the thermal resistor installed in the main loop pipeline as a detected thermal resistor, remove the thermal resistor from the main loop pipeline, use the thermal resistor with higher precision level as a standard source, and compare and analyze the measured value of the detected thermal resistor with the standard source to judge whether the performance of the thermal resistor is degraded. The method is widely applied to the field of performance detection of thermal resistors, and has the advantages of mature detection technology and high reliability. For the thermal resistor of the main loop of the nuclear power station, the method has the problems that the thermal resistor is arranged in a main loop pipeline, and the environmental radiation dose is large; the assay devices used to assay these thermal resistors are extremely susceptible to contamination; disassembly and installation also tend to introduce installation problems, causing measurement inaccuracies.
For example, the invention patent application publication number CN112146788A, publication date 2020, 12, 29, entitled thermal resistance assay system and method, discloses a thermal resistance assay system and method, the method comprising: when a target thermal resistor with finished wiring is put on a first placing frame in the transfer mechanism, a first lifting table in the transfer mechanism is controlled to ascend; when the first lifting platform ascends to a set first height, a first rotating platform and a first rotating arm in the transfer mechanism are controlled to cooperatively move so as to enable the target thermal resistor to be close to the first constant temperature tank through the first placing frame arranged on the first rotating arm; inserting the target thermal resistor into the first constant temperature tank through the transfer mechanism for thermal resistance verification; when the target thermal resistor is determined to finish the thermal resistor verification process in the first constant temperature tank, the transfer mechanism drives the target thermal resistor to move so as to transfer the target thermal resistor from the first constant temperature tank to a cleaning tank for cleaning; and when the target thermal resistor is determined to be cleaned, the transfer mechanism drives the target thermal resistor to move so as to transfer the target thermal resistor from the cleaning tank to the second constant temperature tank for thermal resistor verification. The invention improves the problem of lower efficiency of the existing thermal resistor verification, but is not suitable for thermal resistors of nuclear power plants and is easy to pollute the verification system during cleaning.
Disclosure of Invention
The invention solves the problems that in the prior art, the thermal resistor is detached and detected to easily pollute the verification equipment, the detachment and the installation are easy to introduce the installation problem, and the measurement is inaccurate.
In order to achieve the above object, the present invention is realized by the following technical scheme:
a method of thermal resistance degradation detection based on cross calibration techniques, the method comprising:
step S01, the computing platform receives the first temperature data of all the thermal resistors acquired by the data acquisition system and retrieves the accuracy criteria stored in the computing platformΔH. Linearity degradation criterionΔT is a T; the first temperature data are temperature data of the thermal resistor at a plurality of moments under a plurality of temperature platforms of the pipeline to be detected;
step S02, the computing platform calculates and obtains second temperature data based on the first temperature data of all the thermal resistors, wherein the second temperature data is that each temperature platform meets the precision criterionΔMean temperature data of the desuperheat fluctuation deviation of the thermal resistor of H；
Step S03, the computing platform retrieves third temperature data stored in the computing platform, and obtains fourth temperature data through a cross calibration method according to the second temperature data; the third temperature data is the initial temperatures of a plurality of thermal resistors of the pipeline to be detected and a plurality of adjacent pipelines under a plurality of temperature platforms; the fourth temperature data is the true average temperature of each temperature platform of the pipeline to be detected；
Step S04, the computing platform computes a thermal resistance difference value between the second temperature data and the fourth temperature data, and the absolute value of the thermal resistance difference value is compared with a precision criterionΔH, comparing, if the absolute value of the thermal resistance difference value under each temperature platform is larger than the accuracy criterionΔH, degrading the thermal resistance precision corresponding to the difference value;
step S05, the computing platform carries out least square fitting processing on the fourth temperature data to obtain a fitting curve under each temperature platform; then calculating a fitting difference between the thermal resistance difference and the fitting curve, and determining the absolute value of the fitting difference and the linearity degradation criterionΔT is compared, if the absolute value of the fitting difference is greater than the linearity degradation criterionΔAnd T, degrading the linearity of the thermal resistor corresponding to the fitting difference value.
The invention removes the influence of process temperature fluctuation and ensures the detection accuracy. The degradation of thermal resistance is judged by designing a cross calibration method, and the temperature of other pipelines is introduced to correct the pipeline temperature so as to enlarge a cross calibration sample, so that the deviation of a detection result is small, and the accuracy is high. And the thermal resistor is not required to be detached for detection, so that the possibility of pollution to the verification equipment is avoided, and the problems of installation caused by detachment and installation and inaccuracy of measurement are also avoided. The performance of the thermal resistor is judged by analyzing the precision and the linearity of the thermal resistor, potential degradation of the thermal resistor is identified in advance, and misoperation of a control system and a safety system caused by degradation of the performance of the thermal resistor is avoided, so that the accuracy and reliability of the measurement of the temperature of a detected loop are ensured, and the system is safe and economical to operate.
Preferably, the method further comprises step S00, before all the thermal resistors are installed on the pipeline to be detected, the computing platform computes the deviation value of the initial temperature and the standard temperature of each thermal resistor under a plurality of temperature platforms, and determines the precision criterion of the thermal resistor according to the deviation valueΔH. Linearity degradation criterionΔT, then the initial temperature of each thermal resistor and the precision criterion of the thermal resistor under a plurality of temperature platforms are determinedΔH. Linearity degradation criterionΔT is stored within the computing platform.
Therefore, initial data are convenient to offset deviation when whether the thermal resistance is degraded or not is detected later, and the accuracy of the data is ensured.
Preferably, step S02 specifically includes:
step S21, the computing platform processes the first temperature data of all the thermal resistors through an iterative algorithm, eliminates the thermal resistors which do not meet the precision criterion delta H, and leaves the thermal resistors which meet the precision criterion delta H;
step S22, the computing platform calculates the average value of the first temperature data of the thermal resistor meeting the precision criterion delta H through the first temperature data of the thermal resistor meeting the precision criterion delta H;
step S23, the computing platform respectively carries out least square fitting on the average value of the first temperature data of the thermal resistor meeting the precision criterion delta H to obtain a fitted curve, and respectively calculates the difference between the average value of the first temperature data of the thermal resistor meeting the precision criterion delta H and the fitted curve to obtain a temperature fluctuation deviation value at each moment under each temperature platform;
step S24, calculating the difference value of the first temperature data of the thermal resistor meeting the precision criterion delta H and the temperature fluctuation deviation at each moment under each temperature platform by the calculation platform to obtain the temperature data of the desynchronization deviation of the thermal resistor meeting the precision criterion delta H at each moment; and averaging the temperature data of the thermal resistor with the fluctuation deviation removed and meeting the precision criterion delta H at each moment to obtain second temperature data.
Therefore, the thermal resistor which obviously does not meet the precision criterion is removed through an iterative algorithm, the influence of the thermal resistor which obviously does not meet the precision criterion on the determination of the real average temperature of the platform is avoided, and the judgment accuracy is improved.
Preferably, step S02 specifically includes:
step S21, the computing platform processes the first temperature data of all the thermal resistors through an iterative algorithm, eliminates the thermal resistors which do not meet the precision criterion delta H, and leaves the thermal resistors which meet the precision criterion delta H;
step S22, calculating the average value of the thermal resistors meeting the precision criterion delta H at each moment under each temperature platform by the computing platform according to the first temperature data of the thermal resistors meeting the precision criterion delta H;
step S23, the computing platform respectively carries out least square fitting on the average value of the thermal resistance meeting the precision criterion delta H at each moment under each temperature platform to obtain a fitted curve, and respectively calculates the difference between the average value of the thermal resistance meeting the precision criterion delta H at each moment under each temperature platform and the fitted curve to obtain a temperature fluctuation deviation value at each moment under each temperature platform;
step S24, calculating the temperature data of the thermal resistor meeting the precision criterion delta H at each moment under each temperature platform and the difference value of the temperature fluctuation deviation at each moment under each temperature platform by the calculation platform to obtain the temperature data of the thermal resistor meeting the precision criterion delta H at each moment; and averaging the temperature data of the thermal resistor with the fluctuation deviation removed and meeting the precision criterion delta H at each moment to obtain second temperature data.
The influence of process temperature fluctuation is removed, the detection accuracy is guaranteed, and the mode of executing the fitting of the least square method to obtain the fitting curve is calculated faster.
Preferably, step S21 specifically includes:
step S211, calculating the average temperature value of each thermal resistor under each temperature platform by the computing platform according to the first temperature data of all the thermal resistors;
step S212, calculating the average temperature value of all the thermal resistors under each temperature platform by the calculating platform through the average temperature value of each thermal resistor under each temperature platform;
step S213, the computing platform calculates the difference between the average temperature value of each thermal resistor and the average temperature value of all thermal resistors under each temperature platform to obtain the relative deviation value of each thermal resistor;
step S214, the computing platform compares the absolute value of the relative deviation value of each thermal resistor under each temperature platform with the precision criterion delta H, if the absolute value of the relative deviation value of the thermal resistor is larger than the precision criterion delta H, the corresponding thermal resistor is removed, and the computing platform returns to step S212 to calculate the average temperature value of all the thermal resistors under each temperature platform after the corresponding thermal resistor is removed; otherwise, the thermal resistor meeting the precision criterion delta H is stored in the computing platform.
The computing platform receives the temperature data of all the thermal resistors at a plurality of moments under a plurality of temperature platforms to judge, and eliminates the thermal resistors which obviously do not meet the precision criterion through an iterative algorithm, so that the influence of the thermal resistors which obviously do not meet the precision criterion on the real average temperature determination of the platform is avoided, and the judgment accuracy is improved.
Preferably, the step S03 specifically includes:
step S31, the computing platform acquires second temperature data and invokes third temperature data stored in the computing platform; averaging the second temperature data to obtain an average temperature value；
Step S32, the computing platform calculates the actual temperature of each pipeline through the third temperature data; subtracting the actual temperature of the adjacent pipelines from the actual temperature of the pipeline to be detected to obtain initial temperature difference between the pipeline to be detected and the adjacent pipelines;
step S33, the computing platform finally calculates the value of the average temperature through the initial temperature difference between the pipeline to be detected and a plurality of adjacent pipelinesThe fourth temperature data is calculated from the average value of (a).
The degradation of thermal resistance is judged by designing a cross calibration method, and the temperature of other pipelines is introduced to correct the pipeline temperature so as to enlarge a cross calibration sample, so that the deviation of a detection result is small, and the accuracy is high.
Preferably, the step S04 further includes, if the plurality of temperature platforms are each greater than 180 degrees high Wen Pingtai, comparing the absolute value of the thermal resistance difference value with the precision criterion Δh by the computing platform, and if the absolute value of the thermal resistance difference value under each temperature platform is greater than the precision criterion Δh and the absolute value of the thermal resistance difference value increases with increasing temperature of the temperature platform, the thermal resistance corresponding to the absolute value of the difference value is degraded in precision.
Preferably, the step S05 of performing least square fitting processing on the fourth temperature data by the computing platform to obtain a fitting curve under each temperature platform specifically includes: and the computing platform respectively takes the fourth temperature data as an x axis and the thermal resistance difference value as a y axis to carry out least square fitting processing to obtain a fitting curve under each temperature platform.
Preferably, the method further comprises step S06, and the computing platform does not satisfy the accuracy criterion according to step S21ΔThe maintenance strategy is obtained by the thermal resistance of H, the thermal resistance of degradation of precision in step S04, and the degradation type of the thermal resistance of linear degradation in step S05.
Different degradation types correspond to different repair strategies so that accuracy is maintained after repair.
Preferably, step S06 further includes the computing platform tabulating the numbers and maintenance strategies of the thermal resistors in step S21 that do not meet the accuracy criterion Δh, the numbers and maintenance strategies of the thermal resistors in step S04 that are degraded in accuracy, and the numbers and maintenance strategies of the thermal resistors in step S05 that are degraded in linearity, and storing the tabulated numbers and maintenance strategies in the computing platform.
Therefore, the situation of the thermal resistor can be clearly and intuitively known, and maintenance can be performed according to the table in the later period.
Preferably, step S05 further includes: the computing platform will not meet the accuracy criterion in step S21ΔH, the precision of step S04, and the linear degree of step S05 are added together to obtain a dropAnd comparing the number of stages with the total number of the thermal resistors in the pipeline to be detected, and returning to the step S01 if the number of damages occupies more than 50% of the total number of the thermal resistors in the pipeline to be detected.
Thus, the condition that the large-scale thermal resistance judgment is degraded due to the problems of data acquisition and the like is avoided.
The invention has the advantages that:
(1) The computing platform receives the temperature data of all the thermal resistors at a plurality of moments under a plurality of temperature platforms to judge, and eliminates the thermal resistors which obviously do not meet the precision criterion through an iterative algorithm, so that the influence of the thermal resistors which obviously do not meet the precision criterion on the real average temperature determination of the platform is avoided, and the judgment accuracy is improved.
(2) The invention removes the influence of process temperature fluctuation and ensures the detection accuracy.
(3) The invention designs a cross calibration method to judge the degradation of the thermal resistor, and introduces the temperature of other pipelines to correct the pipeline temperature so as to enlarge the cross calibration sample, so that the deviation of the detection result is small and the accuracy is high.
(4) The thermal resistor of the invention does not need to be disassembled for detection, thereby avoiding the possibility of polluting the verification equipment, and avoiding the installation problems caused by disassembly and installation and the problem of inaccurate measurement.
(5) According to the invention, the performance of the thermal resistor is judged by analyzing the precision and the linearity of the thermal resistor, the potential degradation of the thermal resistor is identified in advance, and the misoperation of a control system and a safety system caused by the degradation of the thermal resistor is avoided, so that the accuracy and the reliability of the temperature measurement of a detected loop are ensured, and the system is safe and economical to operate.
Drawings
FIG. 1 is a flow chart of a thermal resistance degradation detection method based on a cross calibration technique according to the present invention.
Detailed Description
The following are specific embodiments of the present invention and the technical solutions of the present invention will be further described with reference to the accompanying drawings, but the present invention is not limited to these embodiments.
A thermal resistance degradation detection method based on a cross calibration technology is applied to a main loop of a nuclear power plant, wherein the main loop comprises two loops, and each loop comprises a steam generator, two main pumps, a hot section pipeline and two cold section pipelines. The main circuit hot leg line HL1 is shown and the cold leg lines are shown as CL1A, CL1B, respectively. Therein HL1 designed 7-pin double-pin thermal resistors, totaling 14 pins, which measured the temperature from the core to the steam generator. CL1A, CL1B designs 8 probes in total of 4 double probes, and measures the temperature of the steam generator returned to the reactor core after heat exchange. The tested line of this embodiment is HL1.
The method comprises the following steps:
step S00, before installing all the thermal resistors on the pipeline to be detected, the computing platform calculates the deviation value of the initial temperature of each thermal resistor and the temperature platform under a plurality of temperature platforms (such as 0 ℃,100 ℃,125 ℃,180 ℃, 235 ℃,285 ℃) and determines the precision criterion of the thermal resistor according to the deviation valueΔH. Linearity degradation criterionΔT, then the initial temperature of each thermal resistor and the precision criterion of the thermal resistor under a plurality of temperature platforms are determinedΔH. Linearity degradation criterionΔT is stored within the computing platform.
Step S01, the computing platform receives the first temperature data of all the thermal resistors acquired by the data acquisition system and retrieves the accuracy criteria stored in the computing platformΔH. Linearity degradation criterionΔT. The first temperature data are temperature data of the thermal resistor at m moments under a plurality of temperature platforms of the pipeline to be detected.
Step S02, the computing platform calculates and obtains second temperature data based on the first temperature data of all the thermal resistors, wherein the second temperature data is that each temperature platform meets the precision criterionΔMean temperature data of the desuperheat fluctuation deviation of the thermal resistor of H。
The method specifically comprises the following steps: in step S21, the computing platform processes the first temperature data of all the thermal resistors through an iterative algorithm, eliminates the thermal resistors which do not meet the precision criterion delta H, and leaves the thermal resistors which meet the precision criterion delta H.
The step S21 specifically includes: step S211, the computing platform calculates the average temperature value of each thermal resistor under each temperature platform according to the first temperature data of all thermal resistors。
Step S212, the computing platform calculates the average temperature value of each thermal resistor through each temperature platformCalculating the average temperature value of all the thermal resistors at each temperature plateau +.>。
Step S213, the calculation platform calculates the average temperature value of each thermal resistor under each temperature platformAverage temperature value with all thermal resistors +.>Obtain the relative deviation value +.>. The specific formula is->。
Step S214, the computing platform calculates the absolute value of the relative deviation value of each thermal resistor under each temperature platformComparing with the accuracy criterion DeltaH, if the absolute value of the relative deviation value of the thermal resistor is +.>If the temperature value is larger than the precision criterion delta H, removing the corresponding thermal resistor and returning to the step S212 to calculate the average temperature value of all the thermal resistors in each temperature platform after the corresponding thermal resistor is removed; otherwise, the thermal resistor meeting the precision criterion delta H is stored in the computing platform.
Step S22, the computing platform calculates the average value of the first temperature data of the thermal resistor meeting the precision criterion delta H through the first temperature data of the thermal resistor meeting the precision criterion delta H, and records the average value as。
Step S23, calculating the average value of the first temperature data of the thermal resistors meeting the accuracy criterion DeltaH by the platformFitting by least square method to obtain fitting curves, and calculating average value +.f. of first temperature data of thermal resistor satisfying accuracy criterion DeltaH>Obtaining a temperature fluctuation deviation value of each moment under each temperature platform by the difference between the temperature fluctuation deviation value and the fitting curve;
step S24, calculating the difference value of the first temperature data of the thermal resistor meeting the precision criterion delta H and the temperature fluctuation deviation at each moment under each temperature platform by the calculation platform to obtain the temperature data of the desynchronization deviation of the thermal resistor meeting the precision criterion delta H at each moment; and averaging the deswelling deviation temperature data of the thermal resistor meeting the accuracy criterion delta H at each moment to obtain second temperature data, namely。
Step S03, the computing platform acquires third temperature data stored in the computing platform, and fourth temperature data is acquired through a cross calibration method according to the second temperature data. The third temperature data is a plurality of thermoelectric devices of the pipeline to be detected and a plurality of adjacent pipelines under a plurality of temperature platformsInitial temperature of the resistor. The fourth temperature data is the true average temperature of each temperature platform of the pipeline to be detected。
The third temperature data is obtained by the step S00, the step S01 and the step S21 for the pipeline to be detected and the adjacent pipelines by the computing platform. This improves the accuracy of the initial temperature.
Specifically: step S31, the computing platform obtains the initial temperature of each thermal resistor of the pipeline HL1 to be detected under the plurality of temperature platforms at the initial stage of the power plant operationThe initial temperature of each thermal resistor of the adjacent pipeline CL1A under a plurality of temperature platforms +.>The initial temperature of each thermal resistor of the adjacent pipeline CL1B is +.>And second temperature data. Averaging the second temperature data to obtain an average temperature value +.> 。
Step S32, the computing platform calculates the initial temperature of each thermal resistor under a plurality of temperature platforms through the pipeline HL1 to be detected in the initial stage of the operation of the power plantThe initial temperature of each thermal resistor of the adjacent pipeline CL1A under a plurality of temperature platforms +.>The initial temperature of each thermal resistor of the adjacent pipeline CL1B is +.>The actual temperature of each conduit is calculated. Expressed as:
wherein, the liquid crystal display device comprises a liquid crystal display device,
-the actual temperature of HL1 piping at the initial stage of power plant operation;
-the measured average value of each thermal resistance temperature of HL1 pipeline at the initial stage of power plant operation;
-the initial stage of operation of the power plant, the measurement value of the ith thermal resistance of the HL1 pipeline;
-actual temperature of CL1A piping at initial stage of power plant operation;
-the measured average value of the temperature of each thermal resistor of the CL1A pipeline at the initial stage of operation of the power plant;
-the initial stage of operation of the power plant, the measurement value of the ith thermal resistance of the CL1A pipeline;
-actual temperature of CL1B piping at initial stage of power plant operation;
-the measured average value of the temperature of each thermal resistor of the CL1B pipeline at the initial stage of operation of the power plant;
-the initial stage of operation of the power plant, the measurement value of the ith thermal resistance of the CL1B pipeline;
n-for calculating HL1Is a thermal resistance number of (a);
n1-for calculating CL1AIs a thermal resistance number of (a);
n2-used for calculating CL1BIs used for the heat resistance of the semiconductor device.
And subtracting the actual temperature of the adjacent two pipelines CL1A and CL1B from the actual temperature of the pipeline HL1 to be detected to obtain the initial temperature difference between the pipeline HL1 to be detected and the pipelines CL1A and CL 1B. The method comprises the following steps:
wherein, the liquid crystal display device comprises a liquid crystal display device,
-initial temperature difference between HL1 and CL 1A;
-initial temperature difference between HL1 and CL 1B.
Step S33, the computing platform finally calculates the value of the average temperature through the initial temperature difference between the pipeline HL1 to be detected and the CL1A pipeline and the CL1B pipelineThe fourth temperature data, namely the true average temperature of the pipeline to be detected at each temperature platform, is calculated by the average value of (1)>. The specific formula is
Wherein, the liquid crystal display device comprises a liquid crystal display device,
-the corrected true average temperature value of HL 1;
=/>；
=/>；
=/>。
step S04, the computing platform computes a thermal resistance difference value between the second temperature data and the fourth temperature data, and the absolute value of the thermal resistance difference value is compared with a precision criterionΔH, comparing, if the absolute value of the thermal resistance difference value under each temperature platform is larger than the accuracy criterionΔAnd H, degrading the thermal resistance precision corresponding to the difference value.
Preferably, the step S04 further includes, if the plurality of temperature platforms are each greater than 180 degrees high Wen Pingtai, comparing the absolute value of the thermal resistance difference value with the precision criterion Δh by the computing platform, and if the absolute value of the thermal resistance difference value under each temperature platform is greater than the precision criterion Δh and the absolute value of the thermal resistance difference value increases with increasing temperature of the temperature platform, the thermal resistance corresponding to the absolute value of the difference value is degraded in precision.
And S05, the computing platform respectively takes the fourth temperature data as an x axis and the thermal resistance difference value as a y axis to carry out least square fitting processing, so as to obtain a fitting curve under each temperature platform. Then calculating a fitting difference between the thermal resistance difference and the fitting curve, and determining the absolute value of the fitting difference and the linearity degradation criterionΔT is compared, if the absolute value of the fitting difference is greater than the linearity degradation criterionΔAnd T, degrading the linearity of the thermal resistor corresponding to the fitting difference value.
Preferably, step S05 further comprises: the computing platform will not meet the accuracy criterion in step S21ΔH thermal resistance, thermal resistance with degraded accuracy in step S04, linear degradation in step S05And obtaining the degradation amount after adding the thermal resistances, comparing the degradation amount with the total amount of the thermal resistances in the pipeline to be detected, and returning to the step S01 if the damage amount occupies more than 50% of the total amount of the thermal resistances in the pipeline to be detected.
Step S06, the computing platform does not meet the precision criterion according to the step S21ΔThe maintenance strategy is obtained by the thermal resistance of H, the thermal resistance of degradation of precision in step S04, and the degradation type of the thermal resistance of linear degradation in step S05. Then, step S06 further includes, the computing platform tabulates the numbers and maintenance strategies of the thermal resistors in step S21 that do not meet the accuracy criterion Δh, the numbers and maintenance strategies of the thermal resistors in step S04 that are degraded in accuracy, and the numbers and maintenance strategies of the thermal resistors in step S05 that are degraded in linearity, and then stores the tabulated numbers and maintenance strategies in the computing platform.
The computing platform receives the temperature data of all the thermal resistors at a plurality of moments under a plurality of temperature platforms to judge, and eliminates the thermal resistors which obviously do not meet the precision criterion through an iterative algorithm, so that the influence of the thermal resistors which obviously do not meet the precision criterion on the real average temperature determination of the platform is avoided, and the judgment accuracy is improved. The invention removes the influence of process temperature fluctuation and ensures the detection accuracy. The degradation of thermal resistance is judged by designing a cross calibration method, and the temperature of other pipelines is introduced to correct the pipeline temperature so as to enlarge a cross calibration sample, so that the deviation of a detection result is small, and the accuracy is high. And the thermal resistor is not required to be detached for detection, so that the possibility of pollution to the verification equipment is avoided, and the problems of installation caused by detachment and installation and inaccuracy of measurement are also avoided. The performance of the thermal resistor is judged by analyzing the precision and the linearity of the thermal resistor, potential degradation of the thermal resistor is identified in advance, and misoperation of a control system and a safety system caused by degradation of the performance of the thermal resistor is avoided, so that the accuracy and reliability of the measurement of the temperature of a detected loop are ensured, and the system is safe and economical to operate.
The specific embodiments described herein are offered by way of example only to illustrate the spirit of the invention. Those skilled in the art may make various modifications or additions to the described embodiments or substitutions thereof without departing from the spirit of the invention or exceeding the scope of the invention as defined in the accompanying claims.
Claims (9)
1. A method for thermal resistance degradation detection based on a cross calibration technique, the method comprising:
step S01, the computing platform receives the first temperature data of all the thermal resistors acquired by the data acquisition system and retrieves the accuracy criteria stored in the computing platformΔH. Linearity degradation criterionΔT is a T; the first temperature data are temperature data of the thermal resistor at a plurality of moments under a plurality of temperature platforms of the pipeline to be detected;
step S02, the computing platform calculates and obtains second temperature data based on the first temperature data of all the thermal resistors, wherein the second temperature data is that each temperature platform meets the precision criterionΔMean temperature data of the desuperheat fluctuation deviation of the thermal resistor of H；
Step S03, the computing platform retrieves third temperature data stored in the computing platform, and obtains fourth temperature data through a cross calibration method according to the second temperature data; the third temperature data is the initial temperatures of a plurality of thermal resistors of the pipeline to be detected and a plurality of adjacent pipelines under a plurality of temperature platforms; the fourth temperature data is the true average temperature of each temperature platform of the pipeline to be detected；
Step S04, the computing platform computes a thermal resistance difference value between the second temperature data and the fourth temperature data, and the absolute value of the thermal resistance difference value is compared with a precision criterionΔH, comparing, if the absolute value of the thermal resistance difference value under each temperature platform is larger than the accuracy criterionΔH, degrading the thermal resistance precision corresponding to the difference value;
step S05, the computing platform carries out least square fitting processing on the fourth temperature data to obtain a fitting curve under each temperature platform; then calculate the thermal resistance differenceFitting difference between the value and the fitted curve, and comparing the absolute value of the fitting difference with linearity degradation criterionΔT is compared, if the absolute value of the fitting difference is greater than the linearity degradation criterionΔT, the linearity of the thermal resistor corresponding to the fitting difference value is degraded;
the step S03 specifically includes:
step S31, the computing platform acquires second temperature data and invokes third temperature data stored in the computing platform; averaging the second temperature data to obtain an average temperature value；
Step S32, the computing platform calculates the actual temperature of each pipeline through the third temperature data; subtracting the actual temperature of the adjacent pipelines from the actual temperature of the pipeline to be detected to obtain initial temperature difference between the pipeline to be detected and the adjacent pipelines;
step S33, the computing platform finally calculates the value of the average temperature through the initial temperature difference between the pipeline to be detected and a plurality of adjacent pipelinesThe fourth temperature data is calculated from the average value of (a).
2. The method for detecting degradation of thermal resistor based on cross calibration technique according to claim 1, wherein the method further comprises step S00, before all thermal resistors are installed on the pipeline to be detected, the calculating platform calculates the deviation value of the initial temperature and the standard temperature of each thermal resistor under a plurality of temperature platforms, and determines the accuracy criterion of the thermal resistor according to the deviation valueΔH. Linearity degradation criterionΔT, then the initial temperature of each thermal resistor and the precision criterion of the thermal resistor under a plurality of temperature platforms are determinedΔH. Linearity degradation criterionΔT is stored within the computing platform.
3. The method for thermal resistance degradation detection based on the cross calibration technique according to claim 1, wherein step S02 specifically comprises:
step S21, the computing platform processes the first temperature data of all the thermal resistors through an iterative algorithm, and eliminates that the accuracy criterion is not metΔH, leaving the thermal resistance satisfying the accuracy criterionΔA thermal resistance of H;
step S22, the computing platform meets the accuracy criterionΔH, calculating out first temperature data of thermal resistor meeting accuracy criterionΔAn average value of the first temperature data of the thermal resistance of H;
step S23, the computing platform respectively meets the precision criterionΔFitting the average value of the first temperature data of the thermal resistor H by a least square method to obtain a fitted curve, and respectively calculating the difference between the average value of the first temperature data of the thermal resistor meeting the accuracy criterion delta H and the fitted curve to obtain a temperature fluctuation deviation value at each moment under each temperature platform;
step S24, the computing platform calculates that the precision criterion is satisfiedΔThe difference value of the first temperature data of the thermal resistor of H and the temperature fluctuation deviation of each moment under each temperature platform is obtained, and each moment meets the precision criterionΔTemperature data of deswelling deviation of thermal resistance of H; and then each moment meets the accuracy criterionΔAnd (3) averaging the temperature data of the thermal resistor with the fluctuation deviation removed to obtain second temperature data.
4. A method for thermal resistance degradation detection based on a cross calibration technique according to claim 3, wherein step S21 specifically comprises:
step S211, calculating the average temperature value of each thermal resistor under each temperature platform by the computing platform according to the first temperature data of all the thermal resistors;
step S212, calculating the average temperature value of all the thermal resistors under each temperature platform by the calculating platform through the average temperature value of each thermal resistor under each temperature platform;
step S213, the computing platform calculates the difference between the average temperature value of each thermal resistor and the average temperature value of all thermal resistors under each temperature platform to obtain the relative deviation value of each thermal resistor;
step S214, the computing platform compares the absolute value of the relative deviation value of each thermal resistor under each temperature platform with the accuracy criterionΔH, comparing, if the absolute value of the relative deviation value of the thermal resistor is larger than the accuracy criterionΔH, eliminating the corresponding thermal resistor, and returning to the step S212 to calculate the average temperature value of all the thermal resistors under each temperature platform after eliminating the corresponding thermal resistor; otherwise, save the data meeting the accuracy criterionΔThe thermal resistance of H is within the computing platform.
5. The method of claim 1, wherein the step S04 further comprises the step of the computing platform comparing the absolute value of the thermal resistance difference with a precision criterion if the plurality of temperature platforms are each a height Wen Pingtai greater than 180 degreesΔH, comparing the absolute values of the thermal resistance differences of the temperature platforms, if the absolute values of the thermal resistance differences of the temperature platforms are larger than the accuracy criterionΔAnd H, increasing the absolute value of the thermal resistance difference value along with the increase of the temperature platform, wherein the thermal resistance corresponding to the absolute value of the difference value is degraded in precision.
6. The method for detecting thermal resistance degradation based on the cross calibration technique according to claim 1, wherein the step S05 of performing least squares fitting on the fourth temperature data by the computing platform to obtain a fitted curve under each temperature platform specifically comprises: and the computing platform respectively takes the fourth temperature data as an x axis and the thermal resistance difference value as a y axis to carry out least square fitting processing to obtain a fitting curve under each temperature platform.
7. A method of thermal resistance degradation detection based on a cross calibration technique according to claim 3, further comprising step S06, the computing platform not satisfying the accuracy criterion according to step S21ΔThe maintenance strategy is obtained by the thermal resistance of H, the thermal resistance of degradation of precision in step S04, and the degradation type of the thermal resistance of linear degradation in step S05.
8. The method for detecting degradation of thermal resistance according to claim 7, wherein step S06 further comprises the computing platform tabulating the numbers and maintenance strategies of thermal resistance in step S21 that do not satisfy the accuracy criterion Δh, the numbers and maintenance strategies of thermal resistance in step S04 that degrade, and the numbers and maintenance strategies of thermal resistance in step S05 that degrade in linear scale, and storing the tabulated numbers and maintenance strategies in the computing platform.
9. A method of thermal resistance degradation detection based on a cross-calibration technique according to claim 3, wherein step S05 further comprises: the computing platform will not meet the accuracy criterion in step S21ΔH, the thermal resistance with degraded accuracy in the step S04 and the thermal resistance with degraded linearity in the step S05 are added to obtain the degraded amount, the degraded amount is compared with the total amount of the thermal resistances in the pipeline to be detected, and if the damaged amount occupies more than 50% of the total amount of the thermal resistances in the pipeline to be detected, the step S01 is returned.
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