A reliability evaluation method and system for pressure gauge calibration station based on quantitative analysis

Abstract

The present invention relates to the field of data processing technology, and specifically to a method and system for evaluating the reliability of a pressure gauge calibration bench based on quantitative analysis. Performance parameters of collected pressure gauge samples are collected through sensors, the collected data are normalized to obtain standard pressure gauge sample performance parameter data, and data quantification processing is performed in combination with set pressure gauge performance parameter influence weights to generate first pressure gauge performance test result data. At the same time, the pressure gauge sample is calibrated through a target pressure gauge calibration bench to generate second pressure gauge performance test result data. Deviation analysis is performed based on the first pressure gauge performance test result data and the second pressure gauge performance test result data, and the target pressure gauge calibration bench is evaluated based on the deviation analysis result, thereby achieving accurate evaluation of the reliability of the pressure gauge calibration bench.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a reliability evaluation method and system for a pressure gauge calibration station based on quantitative analysis. Background Art

[0002] In industrial processes and scientific research, it is important to accurately measure the pressure value of the equipment through a pressure gauge. Therefore, it is increasingly important to select a reliable pressure gauge calibration station to ensure the detection accuracy of the pressure gauge.

[0003] The Chinese invention patent with publication number CN111414692B introduces a reliability assessment method for a pressure gauge calibration station based on a Bayesian correction model, establishes a fault characteristic index system that can characterize the pressure gauge calibration station; constructs an accident tree model of the pressure gauge calibration station; establishes a BN model diagram of the pressure gauge calibration station, and directly maps the FTA model diagram into a BN model diagram through a graphic mapping method; determines the prior probability of the bottom event and the conditional probability between each layer; modifies the Bayesian model according to actual conditions; calculates the failure probability; calculates the posterior probability of the bottom event, and finds the bottom event with the maximum risk of causing failure. It can not only obtain the failure probability of the pressure gauge calibration station but also obtain the most likely risk event that causes failure when failure occurs. However, the calibration accuracy of the pressure gauge calibration station is not considered, and it is difficult to accurately determine whether the calibration result of the pressure gauge calibration station is reliable. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] In order to solve the deficiencies in the background technology, the present invention provides a method and system for evaluating the reliability of a pressure gauge calibration station based on quantitative analysis, which can accurately evaluate the reliability of the pressure gauge calibration station by analyzing the deviation between the calibration results of the pressure gauge calibration station and the actual performance test results.

[0006] (II) Technical solution

[0007] A reliability evaluation method for a pressure gauge calibration station based on quantitative analysis comprises the following steps:

[0008] S1. Collect pressure gauge samples;

[0009] S2. Collecting the pressure gauge performance parameters of the pressure gauge sample through a sensor to obtain the pressure gauge sample performance parameter data;

[0010] S3, performing data processing on the performance parameter data of the pressure gauge sample to generate first pressure gauge performance test result data;

[0011] S4, performing pressure gauge performance calibration on the pressure gauge sample through a target pressure gauge calibration station to generate second pressure gauge performance test result data;

[0012] S5, performing pressure gauge performance test result deviation analysis based on the first pressure gauge performance test result data and the second pressure gauge performance test result data to generate pressure gauge performance test result deviation data;

[0013] S6, performing a performance evaluation on the target pressure gauge calibration station based on the pressure gauge performance test result deviation data, and generating target pressure gauge calibration station performance evaluation data;

[0014] S7. Combining the pressure gauge performance test result deviation data and the target pressure gauge calibration station performance evaluation data, constructing the pressure gauge calibration station reliability evaluation result data, and pushing it to the evaluation result display platform.

[0015] The present invention collects performance parameters of collected pressure gauge samples through sensors, normalizes the collected data to obtain standard pressure gauge sample performance parameter data, and performs data quantization processing in combination with set pressure gauge performance parameter influence weights to generate first pressure gauge performance test result data. At the same time, the pressure gauge samples are calibrated through a target pressure gauge calibration station to generate second pressure gauge performance test result data, and a deviation analysis is performed based on the first pressure gauge performance test result data and the second pressure gauge performance test result data. The target pressure gauge calibration station is evaluated based on the deviation analysis results, thereby achieving an accurate evaluation of the reliability of the pressure gauge calibration station.

[0016] Preferably, the specific steps of collecting pressure gauge samples are as follows:

[0017] S11. Randomly select from the pressure gauge to be tested pressure gauges as pressure gauge samples, and obtain the pressure gauge sample set ,in, represents the first A pressure gauge, Indicates the total number of pressure gauge samples.

[0018] Preferably, the specific steps of collecting the pressure gauge performance parameters of the pressure gauge sample through the sensor to obtain the pressure gauge sample performance parameter data are as follows:

[0019] S21, set the pressure gauge performance parameter category set ,in, Indicates Performance parameters of pressure gauges: Indicates the total number of pressure gauge performance parameter categories;

[0020] S22, collecting pressure gauge performance parameters of each pressure gauge sample in the pressure gauge sample set through a sensor to obtain a pressure gauge sample performance parameter data matrix as follows:

[0021] ,

[0022] in, Indicates that the sensor The pressure gauge performance parameters are collected by sampling the pressure gauges. Performance parameter data of this type of pressure gauge.

[0023] The various performance parameters of the pressure gauge sample are collected through the sensor, and the pressure gauge sample performance parameter data is obtained to provide a data basis for subsequent operations.

[0024] Preferably, the specific steps of processing the pressure gauge sample performance parameter data to generate the first pressure gauge performance test result data are as follows:

[0025] S31, using the maximum and minimum standardization method to normalize the performance parameter data matrix of the pressure gauge sample The performance parameter data of the pressure gauge samples in the standard pressure gauge are normalized to generate the performance parameter data matrix of the standard pressure gauge samples. as follows:

[0026] ,

[0027] in, Indicates that the sensor collects The pressure gauge samples obtained The performance parameter data of the pressure gauge of the class is normalized to obtain the performance parameter data of the standard pressure gauge sample; the normalization formula is as follows:

[0028] ,

[0029] in, and Respectively represent the first and second order of all pressure gauge samples in the pressure gauge sample performance parameter data matrix Maximum and minimum values ​​in the performance parameter data of similar pressure gauges;

[0030] S32, setting the pressure gauge performance parameter influence weights corresponding to each pressure gauge performance parameter category in the pressure gauge performance parameter category set through an intelligent optimization algorithm, and generating a pressure gauge performance parameter influence weight set ,in, Indicates The weight of the influence of the performance parameters of the pressure gauge on the performance of the pressure gauge; the setting process is as follows:

[0031] S321, construct a squirrel population, set the squirrel population size to The probability of a predator existing is , the random glide distance is The sliding coefficient is , the current number of iterations is The maximum number of iterations is And the dimension of the search space for the influence weight of the pressure gauge performance parameters is ;

[0032] Randomly generate in the search space of the influence weights of pressure gauge performance parameters The pressure gauge performance parameter influence weights are grouped, and each squirrel in the squirrel population corresponds to a group of pressure gauge performance parameter influence weights. The initial position set of the squirrel population is initialized as ,in, Indicates the squirrel population The initial positions of individual squirrels;

[0033] S322, calculate the fitness function value of each squirrel individual in the squirrel population, arrange the squirrel individuals in the squirrel population from large to small according to the fitness function value, and select the squirrel individual with the highest fitness function value as the current optimal individual; the fitness function formula is as follows:

[0034] ,

[0035] in, Indicates the squirrel population The fitness function value of each squirrel, Indicates the squirrel population The influence weight of the pressure gauge performance parameters corresponding to the individual squirrels on the accuracy of the pressure gauge performance detection, Indicates the correction value;

[0036] S323, setting a fitness function threshold, placing the current best individual on the hickory tree with the best food quality, placing the squirrel individuals whose fitness function values ​​are greater than the fitness function threshold on the oak tree with the second best food quality, and finally placing the remaining squirrel individuals on ordinary trees without food;

[0037] S324. Individual squirrels in the squirrel population will forage for food by moving to trees with better food quality in the search space of the pressure gauge performance parameter influence weight. During the foraging process, the position update of individual squirrels will be as follows:

[0038] The individual squirrel on the oak tree moves to the position of the individual squirrel on the hickory tree in the pressure gauge performance parameter influence weight search space to update the position; the position update formula is as follows:

[0039] ,

[0040] in, Indicates The location of the individual squirrel on the oak tree after the location update, Indicates the current location of an individual squirrel in an oak tree, represents the position of the current optimal individual, Represents a random number uniformly distributed between (0,1);

[0041] The squirrel individuals on the ordinary tree move to the position of the squirrel individuals on the hickory tree in the pressure gauge performance parameter influence weight search space to update their position; the position update formula is as follows:

[0042] ,

[0043] in, Indicates The position of the squirrel individual on a common tree after the position update, Indicates The current position of an individual squirrel in a common tree, Represents a random number uniformly distributed between (0,1);

[0044] The squirrel individuals on the ordinary tree move to the position of the squirrel individuals on the oak tree in the pressure gauge performance parameter influence weight search space to update their position; the position update formula is as follows:

[0045] ,

[0046] in, Represents a random number uniformly distributed between (0,1);

[0047] S325, calculation of seasonal constants And seasonal change condition threshold ,like , no operation is performed and the process directly enters S326; otherwise, the squirrel individuals on the ordinary tree will update their positions by randomly moving in the pressure gauge performance parameter influence weight search space to find food;

[0048] S326, calculating the fitness function value of each squirrel individual in the squirrel population after the position is updated, and arranging the squirrel individuals in the squirrel population from large to small according to the fitness function value, and selecting the squirrel individual with the highest fitness function value as the current optimal individual;

[0049] S327, determine the current number of iterations Is it less than the maximum number of iterations? , if the current number of iterations Less than the maximum number of iterations , then the current number of iterations Add 1 and return to S323; otherwise, take the current optimal individual as the global optimal solution, and output a set of pressure gauge performance parameter influence weights corresponding to the global optimal solution as the pressure gauge performance parameter influence weight set corresponding to the pressure gauge performance parameter category set;

[0050] S33, based on the pressure gauge performance parameter influence weight set, the standard pressure gauge sample performance parameter data matrix The performance parameter data of the standard pressure gauge sample in the data are quantified to generate the first pressure gauge performance test result data set ,in, Indicates The first pressure gauge performance test result data is obtained by quantifying the performance parameter data of the standard pressure gauge samples of the pressure gauge samples, and .

[0051] The maximum and minimum standardization method is used to normalize the collected performance parameter data of the pressure gauge samples, and the collected data is scientifically processed to ensure the accuracy of the acquired data and effectively avoid errors caused by abnormal data. The squirrel search algorithm is used to accurately set the influence weights of the pressure gauge performance parameters, which provides a data basis for accurately quantifying the performance parameter data of the standard pressure gauge samples, while ensuring the accuracy and reliability of the set data, improving the speed and efficiency of the optimization process, and effectively avoiding the optimization results from falling into the local optimum.

[0052] Preferably, the specific steps of performing pressure gauge performance calibration on the pressure gauge sample by using a target pressure gauge calibration station to generate the second pressure gauge performance test result data are as follows:

[0053] S41, using the target pressure gauge calibration station to perform pressure gauge performance calibration on each pressure gauge sample in the pressure gauge sample set in turn, to generate a second pressure gauge performance test result data set ,in, Indicates that the target pressure gauge calibration station is used to check the The second pressure gauge performance test result data is obtained after the pressure gauge performance is calibrated for a pressure gauge sample.

[0054] Preferably, the specific steps of performing pressure gauge performance test result deviation analysis based on the first pressure gauge performance test result data and the second pressure gauge performance test result data to generate pressure gauge performance test result deviation data are as follows:

[0055] S51: Perform a pressure gauge performance test result deviation analysis based on the first pressure gauge performance test result data and the second pressure gauge performance test result data to generate a pressure gauge performance test result deviation data set. ,in, Indicates the target pressure gauge calibration station for the performance test result deviation data of pressure gauge samples, and .

[0056] Preferably, the performance of the target pressure gauge calibration station is evaluated based on the pressure gauge performance test result deviation data, and the specific steps of generating the target pressure gauge calibration station performance evaluation data are as follows:

[0057] S61, using a mean formula to perform average numerical measurement processing on the pressure gauge performance test result deviation data in the pressure gauge performance test result deviation data set, to generate pressure gauge performance test result deviation mean data , Indicates the total number of pressure gauge samples;

[0058] S62, setting the first deviation threshold value to And the second deviation threshold is ;

[0059] S63, the pressure gauge performance test result deviation mean data , the first deviation threshold And the second deviation threshold Perform numerical comparisons;

[0060] like , then the performance evaluation result of the target pressure gauge calibration bench is judged to be excellent;

[0061] like , then the performance evaluation result of the target pressure gauge calibration bench is judged to be good;

[0062] like , then the performance evaluation result of the target pressure gauge calibration bench is judged to be poor;

[0063] S64. Data identification is performed on the performance evaluation results of the target pressure gauge calibration station to generate performance evaluation data of the target pressure gauge calibration station .

[0064] The deviation data of the pressure gauge performance test results are averaged and measured using the mean formula, and the performance of the target pressure gauge calibration station is evaluated based on the set threshold. The comprehensive performance of the pressure gauge calibration station is scientifically evaluated to ensure the accuracy of the performance evaluation results of the pressure gauge calibration station.

[0065] Preferably, the specific steps of combining the pressure gauge performance test result deviation data and the target pressure gauge calibration station performance evaluation data to construct the pressure gauge calibration station reliability evaluation result data and push them to the evaluation result display platform are as follows:

[0066] S71, the pressure gauge performance test result deviation data set And the target pressure gauge calibration station performance evaluation data Combine data to construct the reliability evaluation result data of pressure gauge calibration station ;

[0067] S72, transmitting the reliability evaluation result data of the pressure gauge calibration station to the wireless communication network Push to the evaluation result display platform.

[0068] The present invention also discloses a pressure gauge calibration station reliability evaluation system based on quantitative analysis, including a pressure gauge sample collection module, a pressure gauge sample performance parameter acquisition module, a first pressure gauge performance test result data construction module, a second pressure gauge performance test result data construction module, a pressure gauge performance test result deviation data generation module, a target pressure gauge calibration station performance evaluation module and a pressure gauge calibration station reliability evaluation result display module;

[0069] The pressure gauge sample collection module randomly extracts samples from the pressure gauge to be tested. pressure gauges as pressure gauge samples, and obtain a pressure gauge sample set;

[0070] The pressure gauge sample performance parameter acquisition module acquires pressure gauge performance parameter data of each pressure gauge sample in the pressure gauge sample set through a sensor;

[0071] The first pressure gauge performance test result data construction module normalizes the pressure gauge sample performance parameter data by a maximum and minimum normalization method to generate standard pressure gauge sample performance parameter data, and then sets the pressure gauge performance parameter influence weight by an intelligent optimization algorithm, performs performance parameter data quantification processing on the standard pressure gauge sample performance parameter data based on the pressure gauge performance parameter influence weight, and generates the first pressure gauge performance test result data;

[0072] The second pressure gauge performance test result data construction module performs pressure gauge performance verification on each pressure gauge sample in the pressure gauge sample set in ascending order of numbers through a target pressure gauge verification station to generate second pressure gauge performance test result data;

[0073] The pressure gauge performance test result deviation data generating module performs pressure gauge performance test result deviation analysis based on the first pressure gauge performance test result data and the second pressure gauge performance test result data to generate pressure gauge performance test result deviation data;

[0074] The target pressure gauge calibration station performance evaluation module uses a mean value formula to perform average numerical measurement processing on the pressure gauge performance test result deviation data in the pressure gauge performance test result deviation data set, generates pressure gauge performance test result deviation mean data, and compares the data with the set first deviation degree threshold and second deviation degree threshold, and evaluates the performance of the target pressure gauge calibration station according to the numerical comparison result;

[0075] The pressure gauge calibration station reliability assessment result display module constructs the pressure gauge calibration station reliability assessment result data by combining the pressure gauge performance test result deviation data and the target pressure gauge calibration station performance assessment data, and pushes it to the assessment result display platform through the wireless communication network.

[0076] (III) Beneficial effects

[0077] 1. The present invention collects performance parameters of the collected pressure gauge samples through sensors, normalizes the collected data, obtains performance parameter data of standard pressure gauge samples, and performs data quantification processing in combination with the set pressure gauge performance parameter influence weights to generate first pressure gauge performance test result data, and at the same time, calibrates the pressure gauge samples through a target pressure gauge calibration station to generate second pressure gauge performance test result data, performs deviation analysis based on the first pressure gauge performance test result data and the second pressure gauge performance test result data, and evaluates the target pressure gauge calibration station based on the deviation analysis results, thereby achieving accurate evaluation of the reliability of the pressure gauge calibration station;

[0078] 2. The maximum and minimum standardization method is used to normalize the performance parameter data of the collected pressure gauge samples, and the collected data is scientifically processed to ensure the accuracy of the acquired data and effectively avoid errors caused by abnormal data;

[0079] 3. The squirrel search algorithm is used to accurately set the influence weights of the pressure gauge performance parameters, providing a data basis for accurately quantifying the performance parameter data of the standard pressure gauge samples. At the same time, the accuracy and reliability of the set data are guaranteed, the speed and efficiency of the optimization process are improved, and the optimization results are effectively prevented from falling into the local optimum.

[0080] 4. The deviation data of the pressure gauge performance test results are averaged and measured through the mean formula, and the performance of the target pressure gauge calibration station is evaluated in combination with the set threshold value. The comprehensive performance of the pressure gauge calibration station is scientifically evaluated to ensure the accuracy of the performance evaluation results of the pressure gauge calibration station. BRIEF DESCRIPTION OF THE DRAWINGS

[0081] In order to more clearly illustrate the technical solutions of the embodiments of the invention, the drawings required for describing the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the invention. For ordinary technicians in this field, they can also obtain drawings based on these drawings without paying creative work.

[0082] Figure 1 A flow chart of a method for evaluating the reliability of a pressure gauge calibration station based on quantitative analysis provided by the present invention;

[0083] Figure 2 A schematic diagram of a module of a pressure gauge calibration bench reliability evaluation system based on quantitative analysis provided by the present invention. DETAILED DESCRIPTION

[0084] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0085] In the description of the present invention, it is necessary to understand that the terms "opening", "upper", "lower", "top", "middle", "inside" and the like indicating orientation or positional relationship are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the components or elements referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore cannot be understood as limiting the invention.

[0086] Embodiment 1 is as follows:

[0087] See also Figure 1 A reliability evaluation method for a pressure gauge calibration station based on quantitative analysis includes the following steps:

[0088] S1. Collect pressure gauge samples;

[0089] S11. Randomly select from the pressure gauge to be tested pressure gauges as pressure gauge samples, and obtain the pressure gauge sample set ,in, represents the first A pressure gauge, Indicates the total number of pressure gauge samples.

[0090] S2. Collecting the pressure gauge performance parameters of the pressure gauge sample through a sensor to obtain the pressure gauge sample performance parameter data;

[0091] S21, set the pressure gauge performance parameter category set ,in, Indicates Performance parameters of pressure gauges: Indicates the total number of pressure gauge performance parameter categories;

[0092] S22, collecting pressure gauge performance parameters of each pressure gauge sample in the pressure gauge sample set through a sensor to obtain a pressure gauge sample performance parameter data matrix as follows:

[0093] ,

[0094] in, Indicates that the sensor The pressure gauge performance parameters are collected by sampling the pressure gauges. Performance parameter data of this type of pressure gauge.

[0095] S3, performing data processing on the performance parameter data of the pressure gauge sample to generate first pressure gauge performance test result data;

[0096] S31, using the maximum and minimum standardization method to normalize the performance parameter data matrix of the pressure gauge sample The performance parameter data of the pressure gauge samples in the standard pressure gauge are normalized to generate the performance parameter data matrix of the standard pressure gauge samples. as follows:

[0097] ,

[0098] in, Indicates that the sensor collects The pressure gauge samples obtained The performance parameter data of the pressure gauge of the class is normalized to obtain the performance parameter data of the standard pressure gauge sample; the normalization formula is as follows:

[0099] ,

[0100] in, and Respectively represent the first and second order of all pressure gauge samples in the pressure gauge sample performance parameter data matrix Maximum and minimum values ​​in the performance parameter data of similar pressure gauges;

[0101] S32, setting the pressure gauge performance parameter influence weights corresponding to each pressure gauge performance parameter category in the pressure gauge performance parameter category set through an intelligent optimization algorithm, and generating a pressure gauge performance parameter influence weight set ,in, Indicates The weight of the influence of the performance parameters of the pressure gauge on the performance of the pressure gauge; the setting process is as follows:

[0102] S321, construct a squirrel population, set the squirrel population size to The probability of a predator existing is , the random glide distance is The sliding coefficient is , the current number of iterations is The maximum number of iterations is And the dimension of the search space for the influence weight of the pressure gauge performance parameters is ;

[0103] Randomly generate in the search space of the influence weights of pressure gauge performance parameters The pressure gauge performance parameter influence weights are grouped, and each squirrel in the squirrel population corresponds to a group of pressure gauge performance parameter influence weights. The initial position set of the squirrel population is initialized as ,in, Indicates the squirrel population The initial positions of individual squirrels;

[0104] S322, calculate the fitness function value of each squirrel individual in the squirrel population, arrange the squirrel individuals in the squirrel population from large to small according to the fitness function value, and select the squirrel individual with the highest fitness function value as the current optimal individual; the fitness function formula is as follows:

[0105] ,

[0106] in, Indicates the squirrel population The fitness function value of each squirrel, Indicates the squirrel population The influence weight of the pressure gauge performance parameters corresponding to the individual squirrels on the accuracy of the pressure gauge performance detection, Indicates the correction value;

[0107] S323, setting a fitness function threshold, placing the current best individual on the hickory tree with the best food quality, placing the squirrel individuals whose fitness function values ​​are greater than the fitness function threshold on the oak tree with the second best food quality, and finally placing the remaining squirrel individuals on ordinary trees without food;

[0108] S324. Individual squirrels in the squirrel population will forage for food by moving to trees with better food quality in the search space of the pressure gauge performance parameter influence weight. During the foraging process, the position update of individual squirrels will be as follows:

[0109] The individual squirrel on the oak tree moves to the position of the individual squirrel on the hickory tree in the pressure gauge performance parameter influence weight search space to update the position; the position update formula is as follows:

[0110] ,

[0111] in, Indicates The location of the individual squirrel on the oak tree after the location update, Indicates the current location of an individual squirrel in an oak tree, represents the position of the current optimal individual, Represents a random number uniformly distributed between (0,1);

[0112] The squirrel individuals on the ordinary tree move to the position of the squirrel individuals on the hickory tree in the pressure gauge performance parameter influence weight search space to update their position; the position update formula is as follows:

[0113] ,

[0114] in, Indicates The position of the squirrel individual on a common tree after the position update, Indicates The current position of an individual squirrel in a common tree, Represents a random number uniformly distributed between (0,1);

[0115] The squirrel individuals on the ordinary tree move to the position of the squirrel individuals on the oak tree in the pressure gauge performance parameter influence weight search space to update their position; the position update formula is as follows:

[0116] ,

[0117] in, Represents a random number uniformly distributed between (0,1);

[0118] S325, calculation of seasonal constants And seasonal change condition threshold ,like , no operation is performed and the process directly enters S326; otherwise, the squirrel individuals on the ordinary tree will update their positions by randomly moving in the pressure gauge performance parameter influence weight search space to find food;

[0119] S326, calculating the fitness function value of each squirrel individual in the squirrel population after the position is updated, and arranging the squirrel individuals in the squirrel population from large to small according to the fitness function value, and selecting the squirrel individual with the highest fitness function value as the current optimal individual;

[0120] S327, determine the current number of iterations Is it less than the maximum number of iterations? , if the current number of iterations Less than the maximum number of iterations , then the current number of iterations Add 1 and return to S323; otherwise, take the current optimal individual as the global optimal solution, and output a set of pressure gauge performance parameter influence weights corresponding to the global optimal solution as the pressure gauge performance parameter influence weight set corresponding to the pressure gauge performance parameter category set;

[0121] S33, based on the pressure gauge performance parameter influence weight set, the standard pressure gauge sample performance parameter data matrix The performance parameter data of the standard pressure gauge sample in the data are quantified to generate the first pressure gauge performance test result data set ,in, Indicates The first pressure gauge performance test result data is obtained by quantifying the performance parameter data of the standard pressure gauge samples of the pressure gauge samples, and .

[0122] S4, performing pressure gauge performance calibration on the pressure gauge sample through a target pressure gauge calibration station to generate second pressure gauge performance test result data;

[0123] S41, using the target pressure gauge calibration station to perform pressure gauge performance calibration on each pressure gauge sample in the pressure gauge sample set in turn, to generate a second pressure gauge performance test result data set ,in, Indicates that the target pressure gauge calibration station is used to check the The second pressure gauge performance test result data is obtained after the pressure gauge performance is calibrated for a pressure gauge sample.

[0124] S5, performing pressure gauge performance test result deviation analysis based on the first pressure gauge performance test result data and the second pressure gauge performance test result data to generate pressure gauge performance test result deviation data;

[0125] S51: Perform a pressure gauge performance test result deviation analysis based on the first pressure gauge performance test result data and the second pressure gauge performance test result data to generate a pressure gauge performance test result deviation data set. ,in, Indicates the target pressure gauge calibration station for the performance test result deviation data of pressure gauge samples, and .

[0126] S6, performing a performance evaluation on the target pressure gauge calibration station based on the pressure gauge performance test result deviation data, and generating target pressure gauge calibration station performance evaluation data;

[0127] S61, using a mean formula to perform average numerical measurement processing on the pressure gauge performance test result deviation data in the pressure gauge performance test result deviation data set, to generate pressure gauge performance test result deviation mean data , Indicates the total number of pressure gauge samples;

[0128] S62, setting the first deviation threshold value to And the second deviation threshold is ;

[0129] S63, the pressure gauge performance test result deviation mean data , the first deviation threshold And the second deviation threshold Perform numerical comparisons;

[0130] like , then the performance evaluation result of the target pressure gauge calibration bench is judged to be excellent;

[0131] like , then the performance evaluation result of the target pressure gauge calibration bench is judged to be good;

[0132] like , then the performance evaluation result of the target pressure gauge calibration bench is judged to be poor;

[0133] S64. Data identification is performed on the performance evaluation results of the target pressure gauge calibration station to generate performance evaluation data of the target pressure gauge calibration station .

[0134] S7, combining the pressure gauge performance test result deviation data and the target pressure gauge calibration station performance evaluation data, constructing the pressure gauge calibration station reliability evaluation result data, and pushing it to the evaluation result display platform;

[0135] S71, the pressure gauge performance test result deviation data set And the target pressure gauge calibration station performance evaluation data Combine data to construct the reliability evaluation result data of pressure gauge calibration station ;

[0136] S72, transmitting the reliability evaluation result data of the pressure gauge calibration station to the wireless communication network Push to the evaluation result display platform.

[0137] Embodiment 2 is as follows:

[0138] See also Figure 2 , a pressure gauge calibration station reliability evaluation system based on quantitative analysis, including a pressure gauge sample collection module, a pressure gauge sample performance parameter acquisition module, a first pressure gauge performance test result data construction module, a second pressure gauge performance test result data construction module, a pressure gauge performance test result deviation data generation module, a target pressure gauge calibration station performance evaluation module and a pressure gauge calibration station reliability evaluation result display module;

[0139] The pressure gauge sample collection module randomly extracts samples from the pressure gauge to be tested. pressure gauges as pressure gauge samples, and obtain a pressure gauge sample set;

[0140] The pressure gauge sample performance parameter acquisition module acquires pressure gauge performance parameter data of each pressure gauge sample in the pressure gauge sample set through a sensor;

[0141] The first pressure gauge performance test result data construction module normalizes the pressure gauge sample performance parameter data by a maximum and minimum normalization method to generate standard pressure gauge sample performance parameter data, and then sets the pressure gauge performance parameter influence weight by an intelligent optimization algorithm, performs performance parameter data quantification processing on the standard pressure gauge sample performance parameter data based on the pressure gauge performance parameter influence weight, and generates the first pressure gauge performance test result data;

[0142] The second pressure gauge performance test result data construction module performs pressure gauge performance verification on each pressure gauge sample in the pressure gauge sample set in ascending order of numbers through a target pressure gauge verification station to generate second pressure gauge performance test result data;

[0143] The pressure gauge performance test result deviation data generating module performs pressure gauge performance test result deviation analysis based on the first pressure gauge performance test result data and the second pressure gauge performance test result data to generate pressure gauge performance test result deviation data;

[0144] The target pressure gauge calibration station performance evaluation module uses a mean value formula to perform average numerical measurement processing on the pressure gauge performance test result deviation data in the pressure gauge performance test result deviation data set, generates pressure gauge performance test result deviation mean data, and compares the data with the set first deviation degree threshold and second deviation degree threshold, and evaluates the performance of the target pressure gauge calibration station according to the numerical comparison result;

[0145] The pressure gauge calibration station reliability assessment result display module constructs the pressure gauge calibration station reliability assessment result data by combining the pressure gauge performance test result deviation data and the target pressure gauge calibration station performance assessment data, and pushes it to the assessment result display platform through the wireless communication network.

[0146] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0147] The preferred embodiments of the invention disclosed above are only used to help explain the invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the invention, so that those skilled in the art can understand and use the invention well.

Claims

1. A reliability assessment method for a pressure gauge calibration station based on quantitative analysis, characterized in that: The steps include: S1. Collecting pressure gauge samples, wherein S1 comprises the following steps: S11. Randomly select from the pressure gauge to be tested pressure gauges as pressure gauge samples, and obtain the pressure gauge sample set ,in, represents the first A pressure gauge, Indicates the total number of pressure gauge samples; S2, collecting the pressure gauge performance parameters of the pressure gauge sample through a sensor to obtain the pressure gauge sample performance parameter data, wherein S2 includes the following steps: S21, set the pressure gauge performance parameter category set ,in, Indicates Performance parameters of pressure gauges: Indicates the total number of pressure gauge performance parameter categories; S22, collecting pressure gauge performance parameters of each pressure gauge sample in the pressure gauge sample set through a sensor to obtain a pressure gauge sample performance parameter data matrix as follows: ， in, Indicates that the sensor The pressure gauge performance parameters are collected by sampling the pressure gauges. Performance parameter data of similar pressure gauges; S3, processing the performance parameter data of the pressure gauge sample to generate first pressure gauge performance test result data, wherein S3 includes the following steps: S31, using the maximum and minimum standardization method to normalize the performance parameter data matrix of the pressure gauge sample The performance parameter data of the pressure gauge samples in the standard pressure gauge are normalized to generate the performance parameter data matrix of the standard pressure gauge samples. as follows: ， in, Indicates that the sensor collects The pressure gauge samples obtained The performance parameter data of the pressure gauge of the class is normalized to obtain the performance parameter data of the standard pressure gauge sample; the normalization formula is as follows: , in, and Respectively represent the first and second order of all pressure gauge samples in the pressure gauge sample performance parameter data matrix Maximum and minimum values ​​in the performance parameter data of similar pressure gauges; S32, setting the pressure gauge performance parameter influence weights corresponding to each pressure gauge performance parameter category in the pressure gauge performance parameter category set through an intelligent optimization algorithm, and generating a pressure gauge performance parameter influence weight set ,in, Indicates The weight of the influence of the performance parameters of similar pressure gauges on the performance of pressure gauges; S321, construct a squirrel population, set the squirrel population size to The probability of a predator existing is , the random glide distance is The sliding coefficient is , the current number of iterations is The maximum number of iterations is And the dimension of the search space for the influence weight of the pressure gauge performance parameters is ; Randomly generate in the search space of the influence weights of pressure gauge performance parameters The pressure gauge performance parameter influence weights are grouped, and each squirrel in the squirrel population corresponds to a group of pressure gauge performance parameter influence weights. The initial position set of the squirrel population is initialized as ,in, Indicates the squirrel population The initial positions of individual squirrels; S322, calculating the fitness function value of each squirrel individual in the squirrel population, arranging the squirrel individuals in the squirrel population from large to small according to the fitness function value, and selecting the squirrel individual with the highest fitness function value as the current optimal individual; S323, setting a fitness function threshold, placing the current best individual on the hickory tree with the best food quality, placing the squirrel individuals whose fitness function values ​​are greater than the fitness function threshold on the oak tree with the second best food quality, and finally placing the remaining squirrel individuals on ordinary trees without food; S324. Individual squirrels in the squirrel population will forage for food by moving to trees with better food quality in the search space of the pressure gauge performance parameter influence weight. During the foraging process, the position update of individual squirrels will be as follows: The individual squirrel on the oak tree moves to the position of the individual squirrel on the hickory tree in the pressure gauge performance parameter influence weight search space to update the position; the position update formula is as follows: ， in, Indicates The location of the individual squirrel on the oak tree after the location update, Indicates the current location of the individual squirrel in the oak tree, represents the position of the current optimal individual, Represents a random number uniformly distributed between (0,1); The squirrel individuals on the ordinary tree move to the position of the squirrel individuals on the hickory tree in the pressure gauge performance parameter influence weight search space to update their position; the position update formula is as follows: ， in, Indicates The position of the squirrel individual on a common tree after the position update, Indicates The current position of an individual squirrel in a common tree, Represents a random number uniformly distributed between (0,1); The squirrel individuals on the ordinary tree move to the position of the squirrel individuals on the oak tree in the pressure gauge performance parameter influence weight search space to update their position; the position update formula is as follows: ， in, Represents a random number uniformly distributed between (0,1); S325, calculation of seasonal constants And seasonal change condition threshold ,like , no operation is performed and the process directly enters S326; otherwise, the squirrel individuals on the ordinary tree will update their positions by randomly moving in the pressure gauge performance parameter influence weight search space to find food; S326, calculating the fitness function value of each squirrel individual in the squirrel population after the position is updated, and arranging the squirrel individuals in the squirrel population from large to small according to the fitness function value, and selecting the squirrel individual with the highest fitness function value as the current optimal individual; S327, determine the current number of iterations Is it less than the maximum number of iterations? , if the current number of iterations Less than the maximum number of iterations , then the current number of iterations Add 1 and return to S323; otherwise, take the current optimal individual as the global optimal solution, and output a set of pressure gauge performance parameter influence weights corresponding to the global optimal solution as the pressure gauge performance parameter influence weight set corresponding to the pressure gauge performance parameter category set; S33, based on the pressure gauge performance parameter influence weight set, the standard pressure gauge sample performance parameter data matrix The performance parameter data of the standard pressure gauge sample in the data are quantified to generate the first pressure gauge performance test result data set ,in, Indicates The first pressure gauge performance test result data is obtained by quantifying the performance parameter data of the standard pressure gauge samples of the pressure gauge samples, and ; S4, performing pressure gauge performance calibration on the pressure gauge sample through a target pressure gauge calibration station to generate second pressure gauge performance test result data, wherein S4 includes the following steps: S41, using the target pressure gauge calibration station to perform pressure gauge performance calibration on each pressure gauge sample in the pressure gauge sample set in turn, to generate a second pressure gauge performance test result data set ,in, Indicates that the target pressure gauge calibration station is used to check the The second pressure gauge performance test result data obtained after the pressure gauge performance is verified for a pressure gauge sample; S5, performing pressure gauge performance test result deviation analysis according to the first pressure gauge performance test result data and the second pressure gauge performance test result data to generate pressure gauge performance test result deviation data, wherein S5 comprises the following steps: S51: Perform a pressure gauge performance test result deviation analysis based on the first pressure gauge performance test result data and the second pressure gauge performance test result data to generate a pressure gauge performance test result deviation data set. ,in, Indicates the target pressure gauge calibration station for the performance test result deviation data of pressure gauge samples, and ; S6, based on the pressure gauge performance test result deviation data, the target pressure gauge calibration station is subjected to performance evaluation, and target pressure gauge calibration station performance evaluation data is generated, wherein S6 comprises the following steps: S61, using a mean formula to perform average numerical measurement processing on the pressure gauge performance test result deviation data in the pressure gauge performance test result deviation data set, to generate pressure gauge performance test result deviation mean data , Indicates the total number of pressure gauge samples; S62, setting the first deviation threshold value to And the second deviation threshold is ; S63, the pressure gauge performance test result deviation mean data , the first deviation threshold And the second deviation threshold Perform numerical comparisons; like , then the performance evaluation result of the target pressure gauge calibration bench is judged to be excellent; like , then the performance evaluation result of the target pressure gauge calibration bench is judged to be good; like , then the performance evaluation result of the target pressure gauge calibration bench is judged to be poor; S64. Data identification is performed on the performance evaluation results of the target pressure gauge calibration station to generate performance evaluation data of the target pressure gauge calibration station ; S7. Combining the pressure gauge performance test result deviation data and the target pressure gauge calibration station performance evaluation data, constructing the pressure gauge calibration station reliability evaluation result data, and pushing it to the evaluation result display platform.

2. A reliability assessment method for a pressure gauge calibration station based on quantitative analysis according to claim 1, characterized in that: The S7 comprises the following steps: S71, the pressure gauge performance test result deviation data set And the target pressure gauge calibration station performance evaluation data Combine data to construct the reliability evaluation result data of pressure gauge calibration station ; S72, transmitting the reliability evaluation result data of the pressure gauge calibration station to the wireless communication network Push to the evaluation result display platform.

3. A system for implementing the reliability assessment method of a pressure gauge calibration station based on quantitative analysis as described in any one of claims 1 to 2, characterized in that: The system includes a pressure gauge sample collection module, a pressure gauge sample performance parameter collection module, a first pressure gauge performance test result data construction module, a second pressure gauge performance test result data construction module, a pressure gauge performance test result deviation data generation module, a target pressure gauge calibration station performance evaluation module and a pressure gauge calibration station reliability evaluation result display module.

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