Inspection data analysis system and method based on smart valve handheld inspection terminal

Abstract

The present invention discloses an inspection data analysis system and method based on a smart valve handheld inspection terminal, which specifically relates to the field of data analysis technology, including an inspection terminal data upload module, an inspection data processing center and a data module; the inspection data processing center includes an inspection data preprocessing module, an inspection data storage module, an inspection data analysis module, and an abnormal inspection data identification module; through the abnormal inspection data identification module, an ARIMA model is used to predict relevant data at future time points, and a valve comprehensive risk index is calculated, and the valve comprehensive risk index and a pre-set valve comprehensive risk index threshold are judged and compared. When the valve has a higher risk, an alarm is issued, and according to the alarm information, a corresponding maintenance plan is predicted through a decision tree model, so as to timely discover valve risks and take corresponding maintenance measures, thereby improving the reliability and safety of the valve.

Description

Technical Field

[0001] The present invention relates to the field of data analysis technology, and more specifically, to an inspection data analysis system and method based on a smart valve handheld inspection terminal. Background Art

[0002] The smart valve handheld inspection terminal is a tool specifically used to collect and record the operating conditions of valves and other equipment. It mainly works in an information-based manner and is suitable for inspection operations in the fields and scenarios of electricity, petrochemicals, water supply, railways, forests, and properties.

[0003] The smart valve handheld inspection terminal abandons the traditional manual inspection recording mode. It receives inspection tasks, records inspection routes and inspection conditions through the smart valve handheld inspection terminal. The voice intercom function of the smart valve handheld inspection terminal can communicate with the inspection center. Once an emergency occurs, it can quickly feedback and respond to it, reducing the losses caused by accidents. It not only improves the inspection quality and efficiency, but also standardizes the inspection operation behavior and standards, and informatizes the inspection data, greatly simplifying the complicated inspection process in the past.

[0004] The existing inspection data analysis system lacks the ability to effectively process and analyze data. The data processing process is cumbersome and inefficient. It mainly focuses on the analysis and statistics of historical data and lacks the ability of real-time monitoring and early warning. As a result, it is unable to detect equipment anomalies and failures in a timely manner, and unable to take appropriate measures to repair or prevent them. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, the present invention provides an inspection data analysis system and method based on a smart valve handheld inspection terminal. Through the inspection terminal data upload module, the smart valve handheld inspection terminal is used to collect the operation data and working condition data of the valve in real time, thereby improving the efficiency and accuracy of data collection; the inspection data analysis module is used to divide the data in the database into periods, and the data of each period is statistically analyzed to calculate the real-time quality evaluation index of the valve. The operating status of the valve is judged according to the real-time quality evaluation index of the valve. When there is a safety hazard in the operation of the valve, the abnormal inspection data identification module is started to provide a scientific basis for the maintenance and management of the valve; through the abnormal inspection data identification module, the data in the database is divided into periods, and the data of each period is statistically analyzed to calculate the real-time quality evaluation index of the valve. The real-time quality evaluation index of the valve is used to determine the operating status of the valve. When there is a safety hazard in the operation of the valve, the abnormal inspection data identification module is started to provide a scientific basis for the maintenance and management of the valve; The ARIMA model predicts relevant data at future time points, calculates the comprehensive risk index of the valve, and compares the comprehensive risk index of the valve with the pre-set comprehensive risk index threshold of the valve. When the valve is at a higher risk, an alarm is issued. According to the alarm information, the corresponding maintenance plan is predicted through the decision tree model, so as to timely discover the valve risk and take corresponding maintenance measures to improve the reliability and safety of the valve; through the data display module, the alarm information and the corresponding maintenance plan are displayed on the smart valve handheld inspection terminal, and the inspection personnel are reminded by sound and vibration that there are new alarm information and maintenance plans that need to be processed, thereby improving the work efficiency of the inspection personnel to solve the problems raised in the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solution: an inspection data analysis system based on a smart valve handheld inspection terminal, comprising:

[0007] Inspection terminal data upload module, inspection data processing center and data display module; the inspection data processing center includes inspection data preprocessing module, inspection data storage module, inspection data analysis module, and abnormal inspection data identification module;

[0008] Inspection terminal data upload module: used to collect valve operation data and working condition data in real time through the smart valve handheld inspection terminal, and upload it to the inspection data preprocessing module;

[0009] Inspection data preprocessing module: used to receive data uploaded from the smart valve handheld inspection terminal and preprocess the data, including data cleaning, denoising and missing value processing;

[0010] Inspection data storage module: used to store pre-processed data into the database;

[0011] The inspection data analysis module includes an inspection data processing unit and a valve operation status judgment unit; the inspection data processing unit is used to divide the data in the database into periods, perform statistical analysis on the data of each period, and calculate the reliability coefficient, response speed, flow efficiency, and load efficiency corresponding to the valve in each period; the valve operation status judgment unit is used to calculate the real-time quality evaluation index of the valve, judge the operation status of the valve according to the real-time quality evaluation index of the valve, and start the abnormal inspection data identification module when there is a safety hazard in the operation of the valve;

[0012] The abnormal inspection data identification module includes an abnormal inspection data alarm unit and an abnormal inspection data response unit. The abnormal inspection data alarm unit is used to calculate the valve comprehensive risk index, detect the valve risk according to the valve comprehensive risk index and issue an alarm; the abnormal inspection data response unit is used to generate a maintenance plan according to the alarm information and transmit it to the data display module;

[0013] Data display module: used to display the alarm information and corresponding maintenance plan on the smart valve handheld inspection terminal, and remind the inspection personnel through sound and vibration that there are new alarm information and maintenance plans that need to be handled.

[0014] In a preferred embodiment, the specific processing process of the inspection data processing unit is:

[0015] A1. Divide the valve operation data and working condition data in the database according to the period, recorded as xi, i=1, 2, 3...N; where xi represents the valve operation data and working condition data in the i-th period;

[0016] A2. Calculate the opening and closing frequency of the valve Pa , Average failure frequency Pb , Average maintenance frequency Pc , average running time PTa , average running speed PTb , average workload PTc , and the average workload PTd ;

[0017] A3. Calculate the reliability coefficient of the valve Xk , Response speed Sx , Traffic efficiency La , and load efficiency Lb .

[0018] In a preferred embodiment, the switching frequency Pa The calculation formula is: ,in zaj Indicates j The number of times the valve is opened per day, zbj Indicatesj Number of valve closings per day, Zj Indicates j Number of valve operations per day, n Indicates the amount of time;

[0019] The mean failure frequency Pb The calculation formula is: ,in gaj Indicates j Number of valve failures per day, Zj Indicates j Number of valve operations per day, n Indicates the amount of time;

[0020] The average maintenance frequency Pc The calculation formula is: ,in waj Indicates j Maintenance times of valves per day, Zj Indicates j Number of valve operations per day, n Indicates the amount of time;

[0021] The average running time PTa The calculation formula is: ,in taj Indicates j The running time of the valve is n Indicates the amount of time;

[0022] The average running speed PTb The calculation formula is: ,in tbj Indicates j The operating speed of the valve, n Indicates the amount of time;

[0023] The average workload PTc The calculation formula is: ,in tcj Indicates j The working load of the valve is n Indicates the amount of time;

[0024] The average working flow PTd The calculation formula is: ,in tdj Indicates j The working flow of the valve is n Indicates the amount of time.

[0025] In a preferred embodiment, the reliability coefficient Xk The calculation formula is: ,in Pa Indicates the opening and closing frequency of the valve, PTa Indicates the average operating time of the valve, Pb represents the average failure frequency of the valve, Pc Indicates the average maintenance frequency of the valve, β 1. β 2 represents the proportional coefficient of each item;

[0026] The response speed Sx The calculation formula is: ,in Pa Indicates the opening and closing frequency of the valve, PTb Indicates the average running speed;

[0027] The flow efficiency La The calculation formula is: , where K represents the opening of the valve, PTd Indicates the average working flow of the valve;

[0028] The load efficiency Lb The calculation formula is: ,in PTb Indicates the average operating speed of the valve, PTc Indicates the average working load of the valve.

[0029] In a preferred embodiment, the specific processing method of the valve operation status judgment unit is:

[0030] Based on the obtained valve reliability coefficient Xk , Response speed Sx , Traffic efficiency La , and load efficiency Lb , calculate the real-time quality assessment index of the valve Sz ;

[0031] Real-time quality assessment index of the valve Sz The calculation formula is:

[0032] ,in ω 1. ω 2. ω 3. ω 4 represent the proportional coefficients of each item;

[0033] When the valve's real-time quality assessment index Sz Does not exceed the preset value σ 1, indicating that the valve is operating normally and has passed the inspection; when the real-time quality assessment index of the valve is Sz Exceeding the preset value σ2, it indicates that the valve is operating abnormally and needs to be replaced or repaired immediately; when the real-time quality assessment index of the valve Sz In the preset value σ 1 and default value σ 2, it indicates that there are potential safety hazards in valve operation and the abnormal inspection data identification module is started.

[0034] In a preferred embodiment, the specific processing process of the abnormal inspection data alarm unit is:

[0035] B1. Reliability coefficient of valves in each cycle based on ARIMA model Xk , Response speed Sx , Traffic efficiency La , and load efficiency Lb Analyze and predict the reliability coefficient of the valve for each future cycle Xk 〃 , Response speed Sx 〃 , Traffic efficiency La 〃 , and load efficiency Lb 〃 ;

[0036] B2. According to the reliability coefficient of the valve in each future cycle Xk 〃 , Response speed Sx 〃 , Traffic efficiency La 〃 , and load efficiency Lb 〃 , calculate the stability coefficient of the valve Wx , the rate of change of response speed Lxb and efficiency stability index Lcx ;

[0037] B3. According to the stability coefficient of the valve Wx , the rate of change of response speed Lxb and efficiency stability index Lcx , calculate the valve comprehensive risk index Q, , where λ represents the adjustment factor;

[0038] B4. Compare the valve comprehensive risk index Q with the pre-set valve comprehensive risk index threshold Q threshold. If Q ≥ Q threshold, it means that the valve has a high risk and needs to take corresponding measures to reduce the risk. Otherwise, it means that the valve has a low risk and continues to monitor or take regular maintenance measures.

[0039] B5. The high risk of valves is transmitted as alarm information to the abnormal inspection data response unit.

[0040] In a preferred embodiment, the stability coefficient Wx The calculation formula is: ,in N 〃 represents the number of future cycles, Xki 〃 represents the reliability coefficient of the valve in the future i-th cycle, JXk 〃 Indicates the average reliability coefficient of the valve in the future;

[0041] The rate of change of the response speed Lxb The calculation formula is: ,in N 〃 represents the number of future cycles, Sx 〃 i represents the response speed of the valve in the future i-th cycle, Sx 〃 i+1 Indicates the future of valve i+ Response speed of 1 cycle;

[0042] The efficiency stability index Lcx The calculation formula is:

[0043] ,in N 〃 represents the number of future cycles, Lai 〃 represents the flow efficiency of the valve in the future i-th cycle, Lbi 〃 represents the load efficiency of the valve in the future i-th cycle, JLa 〃 Indicates the average flow efficiency of the valve in the future, JLb 〃 Indicates the average load efficiency of the valve in the future, γ 1. γ 2 represents the proportionality coefficient of each item.

[0044] In a preferred embodiment, the specific processing process of the abnormal inspection data response unit is as follows:

[0045] C1. Receive and record the alarm information of valves with high risk from the abnormal inspection data alarm unit; the alarm information includes the stability coefficient of the valve Wx , the rate of change of response speed Lxb and efficiency stability index Lcx Specific data;

[0046] C2. Based on the decision tree model, the corresponding maintenance plan is predicted according to the input valve stability coefficient, response speed change rate and efficiency stability index;

[0047] C3. Transmit the alarm information and the corresponding maintenance plan to the data display module.

[0048] To achieve the above object, the present invention provides the following technical solution: a method for analyzing inspection data based on a smart valve handheld inspection terminal, comprising the following steps:

[0049] Step S1: Collect the operation data and working condition data of the valve in real time through the smart valve handheld inspection terminal;

[0050] Step S2, preprocessing the operation data and working condition data of the valve;

[0051] Step S3, storing the preprocessed data in a database;

[0052] Step S4, divide the data in the database into periods, perform statistical analysis on the data of each period, calculate the real-time quality evaluation index of the valve, judge the operating status of the valve according to the real-time quality evaluation index of the valve, and start the abnormal inspection data identification module when there is a safety hazard in the operation of the valve;

[0053] Step S5, calculating the comprehensive risk index of the valve, detecting the valve risk according to the comprehensive risk index of the valve, and issuing an alarm, and generating a maintenance plan according to the alarm information;

[0054] Step S6: Display the alarm information and the corresponding maintenance plan on the smart valve handheld inspection terminal to remind the inspection personnel to handle it.

[0055] Technical effects and advantages of the present invention:

[0056] The present invention uses a smart valve handheld inspection terminal through an inspection terminal data upload module to collect valve operation data and working condition data in real time, thereby improving the efficiency and accuracy of data collection; pre-processes the data through an inspection data pre-processing module and an inspection data storage module, and stores the data in a database; divides the data in the database into periods through an inspection data analysis module, performs statistical analysis on the data of each period, calculates the real-time quality evaluation index of the valve, and judges the operating status of the valve according to the real-time quality evaluation index of the valve. When there is a safety hazard in the operation of the valve, the abnormal inspection data identification module is started to provide a scientific basis for the maintenance and management of the valve; through the abnormal inspection data identification module, the ARIMA model is used to predict the relevant data at future time points, and the comprehensive risk index of the valve is calculated. The valve comprehensive risk index is judged and compared with the pre-set valve comprehensive risk index threshold. When the valve is at a higher risk, an alarm is issued. According to the alarm information, the corresponding maintenance plan is predicted through the decision tree model, so as to timely discover the valve risk and take corresponding maintenance measures to improve the reliability and safety of the valve; through the data display module, the alarm information and the corresponding maintenance plan are displayed on the smart valve handheld inspection terminal, and the inspection personnel are reminded by sound and vibration that there are new alarm information and maintenance plans that need to be processed, thereby improving the work efficiency of the inspection personnel; in summary, the present invention can monitor the valve operating status in real time and perform data analysis, has practical application value, greatly improves the efficiency and quality of valve inspection work, reduces maintenance costs, and ensures the stability of production operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 It is the overall structural block diagram of the present invention.

[0058] Figure 2 It is a flow chart of the steps and methods of the present invention. DETAILED DESCRIPTION

[0059] 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.

[0060] The present invention provides Figure 1 - Figure 2 The inspection data analysis system and method based on the smart valve handheld inspection terminal shown in the figure include an inspection terminal data upload module, an inspection data processing center and a data display module; the inspection data processing center includes an inspection data preprocessing module, an inspection data storage module, an inspection data analysis module, and an abnormal inspection data identification module;

[0061] The inspection terminal data upload module is used to collect the operation data and working condition data of the valve in real time through the smart valve handheld inspection terminal, and upload it to the inspection data preprocessing module; the operation data includes the number of times the valve is opened, the number of times the valve is closed, the number of times the valve is operated, the number of times the valve fails, the number of times the valve is maintained, the valve opening, the operation time of the valve, and the operation speed of the valve; the working condition data includes the workload of the valve and the working flow of the valve; the number of times the valve is opened and closed refers to the number of times the valve is turned from the closed state to the open state, or from the open state to the closed state in actual operation; the number of times the valve is operated refers to the total number of times the valve is opened, closed, adjusted, and maintained;

[0062] The inspection data preprocessing module is used to receive data uploaded from the smart valve handheld inspection terminal and preprocess the data, including data cleaning, denoising and missing value processing, to ensure the quality and reliability of the data; the data cleaning, denoising and missing value processing belong to the existing technical means, so this embodiment does not make a specific description;

[0063] The inspection data storage module is used to store the pre-processed data in a database for subsequent data processing and analysis;

[0064] The inspection data analysis module includes an inspection data processing unit and a valve operation status judgment unit; the inspection data processing unit is used to divide the data in the database into periods, perform statistical analysis on the data of each period, and calculate the reliability coefficient, response speed, flow efficiency, and load efficiency corresponding to the valve in each period; the valve operation status judgment unit is used to calculate the real-time quality evaluation index of the valve, judge the operation status of the valve according to the real-time quality evaluation index of the valve, and start the abnormal inspection data identification module when there is a safety hazard in the operation of the valve;

[0065] It should be specifically explained in this embodiment that the specific processing process of the inspection data processing unit is as follows:

[0066] A1. The operation data and working condition data of the valve in the database are divided according to the cycle, which is recorded as xi, i=1, 2, 3...N; wherein xi represents the operation data and working condition data of the valve in the i-th cycle; the cycle in the division according to the cycle specifically refers to a period of time, such as one day, one week or one month;

[0067] A2. Calculate the opening and closing frequency of the valve Pa , Average failure frequency Pb , Average maintenance frequency Pc , average running time PTa , average running speed PTb , average workloadPTc , and the average workload PTd ;

[0068] The switching frequency Pa The calculation formula is: ,in zaj Indicates j The number of times the valve is opened per day, zbj Indicates j Number of valve closings per day, Zj Indicates j Number of valve operations per day, n Indicates the amount of time;

[0069] The mean failure frequency Pb The calculation formula is: ,in gaj Indicates j Number of valve failures per day, Zj Indicates j Number of valve operations per day, n Indicates the amount of time;

[0070] The average maintenance frequency Pc The calculation formula is: ,in waj Indicates j Maintenance times of valves per day, Zj Indicates j Number of valve operations per day, n Indicates the amount of time;

[0071] The average running time PTa The calculation formula is: ,in taj Indicates j The running time of the valve is n Indicates the amount of time;

[0072] The average running speed PTb The calculation formula is: ,in tbj Indicates j The operating speed of the valve, n Indicates the amount of time;

[0073] The average workload PTc The calculation formula is: ,in tcj Indicates j The working load of the valve is n Indicates the amount of time;

[0074] The average working flow PTdThe calculation formula is: ,in tdj Indicates j The working flow of the valve is n Indicates the amount of time;

[0075] A3. Calculate the reliability coefficient of the valve Xk , Response speed Sx , Traffic efficiency La , and load efficiency Lb ;

[0076] The reliability coefficient Xk The calculation formula is: ,in Pa Indicates the opening and closing frequency of the valve, PTa Indicates the average operating time of the valve, Pb represents the average failure frequency of the valve, Pc Indicates the average maintenance frequency of the valve, β 1. β 2 respectively represent the proportional coefficients of each item. The size of the proportional coefficient is to quantify each parameter to obtain a specific value, which is convenient for subsequent comparison. The size of the proportional coefficient can be determined as long as it does not affect the proportional relationship between the parameter and the quantified value. The larger the reliability coefficient, the better the reliability and maintainability of the valve.

[0077] The response speed Sx The calculation formula is: ,in Pa Indicates the opening and closing frequency of the valve, PTb Indicates the average running speed;

[0078] The flow efficiency La The calculation formula is: , where K represents the opening of the valve, PTd Indicates the average working flow of the valve;

[0079] The load efficiency Lb The calculation formula is: ,in PTb Indicates the average operating speed of the valve, PTc Indicates the average working load of the valve;

[0080] It should be specifically explained in this implementation that the specific processing method of the valve operation status judgment unit is:

[0081] Based on the obtained valve reliability coefficient Xk , Response speed Sx , Traffic efficiency La , and load efficiency Lb, calculate the real-time quality assessment index of the valve Sz ;

[0082] Real-time quality assessment index of the valve Sz The calculation formula is:

[0083] ,in ω 1. ω 2. ω 3. ω 4 represent the proportional coefficients of each item respectively. The size of the proportional coefficient is to quantify each parameter to obtain a specific value for subsequent comparison. The size of the proportional coefficient can be determined as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0084] When the valve's real-time quality assessment index Sz Does not exceed the preset value σ 1, indicating that the valve is operating normally and has passed the inspection; when the real-time quality assessment index of the valve is Sz Exceeding the preset value σ 2, it indicates that the valve is operating abnormally and needs to be replaced or repaired immediately; when the real-time quality assessment index of the valve Sz In the preset value σ 1 and default value σ 2, it indicates that there is a safety hazard in the valve operation, and the abnormal inspection data identification module is started; the preset value σ 1 and default value σ 2 can be set according to specific circumstances, and this embodiment does not specifically limit the specific data;

[0085] The abnormal inspection data identification module includes an abnormal inspection data alarm unit and an abnormal inspection data response unit. The abnormal inspection data alarm unit is used to calculate the valve comprehensive risk index, detect the valve risk according to the valve comprehensive risk index and issue an alarm to timely discover potential faults and problems; the abnormal inspection data response unit is used to generate a maintenance plan according to the alarm information and transmit it to the data display module;

[0086] It should be specifically explained in this implementation that the specific processing process of the abnormal inspection data alarm unit is as follows:

[0087] B1. Reliability coefficient of valves in each cycle based on ARIMA model Xk , Response speed Sx , Traffic efficiency La , and load efficiency Lb Analyze and predict the reliability coefficient of the valve for each future cycle Xk 〃 , Response speed Sx 〃 , Traffic efficiencyLa 〃 , and load efficiency Lb 〃 ; The prediction process of the ARIMA model belongs to the existing technical means, so this embodiment does not make a specific description;

[0088] B2. According to the reliability coefficient of the valve in each future cycle Xk 〃 , Response speed Sx 〃 , Traffic efficiency La 〃 , and load efficiency Lb 〃 , calculate the stability coefficient of the valve Wx , the rate of change of response speed Lxb and efficiency stability index Lcx ; The stability coefficient refers to the change of the reliability coefficient of the valve, which is used to measure the reliability stability of the valve; the change rate of the response speed is used to measure the change of the response speed of the valve; the efficiency stability index is used to measure the stability of the valve operation efficiency;

[0089] The stability factor Wx The calculation formula is: ,in N 〃 represents the number of future cycles, Xki 〃 represents the reliability coefficient of the valve in the future i-th cycle, JXk 〃 Indicates the average reliability coefficient of the valve in the future; specifically, the "future" here refers to the future from the current time. N 〃 cycle, therefore, the stability coefficient is a prediction and evaluation of the stability of the valve in the future;

[0090] The rate of change of the response speed Lxb The calculation formula is: ,in N 〃 represents the number of future cycles, Sx 〃 i represents the response speed of the valve in the future i-th cycle, Sx 〃 i+1 Indicates the future of valve i+ 1 cycle response speed; specifically, the "future" here refers to the time from the current time to the future. N 〃cycle, therefore, the change rate of the response speed is a prediction and evaluation of the change of the valve response speed in the future period of time;

[0091] The efficiency stability index Lcx The calculation formula is:

[0092] ,in N 〃 represents the number of future cycles, Lai 〃 represents the flow efficiency of the valve in the future i-th cycle, Lbi 〃 represents the load efficiency of the valve in the future i-th cycle, JLa 〃 Indicates the average flow efficiency of the valve in the future, JLb 〃 Indicates the average load efficiency of the valve in the future, γ 1. γ 2 represents the proportional coefficient of each item. The size of the proportional coefficient is to quantify each parameter to obtain a specific value for subsequent comparison. The size of the proportional coefficient can be whatever as long as it does not affect the proportional relationship between the parameter and the quantized value. Specifically, the "future" here refers to the future from the current time. N 〃 cycle, therefore, the efficiency stability index is a prediction and evaluation of the stability of valve operating efficiency in the future period of time;

[0093] B3. According to the stability coefficient of the valve Wx , the rate of change of response speed Lxb and efficiency stability index Lcx , calculate the valve comprehensive risk index Q, , where λ represents the adjustment factor, which is used to adjust the risk index. The specific value depends on the specific application scenario and requirements. For example, if it is believed that the valve stability coefficient, the change rate of the response speed and the efficiency stability index have different influences on the comprehensive risk, the value of λ can be assigned according to their relative importance. A common practice is to set λ to a constant less than 1 so that the risk index ranges from 0 to 1.

[0094] B4. Compare and judge the valve comprehensive risk index Q with the pre-set valve comprehensive risk index threshold Q threshold. If Q ≥ Q threshold, it means that the valve has a high risk and needs to take corresponding measures to reduce the risk. Otherwise, it means that the valve has a low risk and continues to monitor or take routine maintenance measures. The pre-set valve comprehensive risk index threshold Q threshold can be set according to the specific situation, and this embodiment does not specifically limit the specific data.

[0095] B5. Transmit the high risk of valves as alarm information to the abnormal inspection data response unit;

[0096] It should be specifically explained in this implementation that the specific processing process of the abnormal inspection data response unit is as follows:

[0097] C1. Receive and record the alarm information of valves with high risk from the abnormal inspection data alarm unit; the alarm information includes the stability coefficient of the valve Wx , the rate of change of response speed Lxb and efficiency stability index Lcx Specific data;

[0098] C2. Based on the input valve stability coefficient, response speed change rate and efficiency stability index, a corresponding maintenance plan is predicted based on the decision tree model; the prediction process of the decision tree model belongs to the existing technical means, so this embodiment does not make a specific description; the maintenance plan refers to a specific maintenance operation, a suggestion for replacing parts, or a recommended time point for regular maintenance;

[0099] C3, transmitting the alarm information and the corresponding maintenance plan to the data display module;

[0100] The data display module is used to display the alarm information and the corresponding maintenance plan on the smart valve handheld inspection terminal, and remind the inspection personnel through sound and vibration that there are new alarm information and maintenance plans that need to be processed;

[0101] In this embodiment, it should be specifically explained that the inspection data analysis method based on the smart valve handheld inspection terminal includes the following steps:

[0102] Step S1: Collect the operation data and working condition data of the valve in real time through the smart valve handheld inspection terminal;

[0103] Step S2, preprocessing the operation data and working condition data of the valve;

[0104] Step S3, storing the preprocessed data in a database;

[0105] Step S4, divide the data in the database into periods, perform statistical analysis on the data of each period, calculate the real-time quality evaluation index of the valve, judge the operating status of the valve according to the real-time quality evaluation index of the valve, and start the abnormal inspection data identification module when there is a safety hazard in the operation of the valve;

[0106] Step S5, calculating the comprehensive risk index of the valve, detecting the valve risk according to the comprehensive risk index of the valve, and issuing an alarm, and generating a maintenance plan according to the alarm information;

[0107] Step S6: Display the alarm information and the corresponding maintenance plan on the smart valve handheld inspection terminal to remind the inspection personnel to handle it.

[0108] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

[0109] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. Inspection data analysis system based on smart valve handheld inspection terminal, characterized by: include: Inspection terminal data upload module, inspection data processing center and data display module; The inspection data processing center includes an inspection data preprocessing module, an inspection data storage module, an inspection data analysis module, and an abnormal inspection data identification module; Inspection terminal data upload module: used to collect valve operation data and working condition data in real time through the smart valve handheld inspection terminal, and upload it to the inspection data preprocessing module; Inspection data preprocessing module: used to receive data uploaded from the smart valve handheld inspection terminal and preprocess the data, including data cleaning, denoising and missing value processing; Inspection data storage module: used to store pre-processed data into the database; The inspection data analysis module includes an inspection data processing unit and a valve operation status judgment unit; the inspection data processing unit is used to divide the data in the database into periods, perform statistical analysis on the data of each period, and calculate the reliability coefficient, response speed, flow efficiency, and load efficiency corresponding to the valve in each period; the valve operation status judgment unit is used to calculate the real-time quality evaluation index of the valve, and judge the operation status of the valve according to the real-time quality evaluation index of the valve. When there is a safety hazard in the operation of the valve, the abnormal inspection data identification module is started; The specific processing process of the inspection data processing unit is as follows: A1. Divide the valve operation data and working condition data in the database according to the period, recorded as xi, i=1, 2, 3...N; where xi represents the valve operation data and working condition data in the i-th period; A2. Calculate the valve opening and closing frequency Pa, average failure frequency Pb, average maintenance frequency Pc, average operating time PTa, average operating speed PTb, average workload PTc, and average operating flow rate PTd; A3. Calculate the valve's reliability coefficient Xk, response speed Sx, flow efficiency La, and load efficiency Lb; The specific processing method of the valve operation status judgment unit is: Based on the obtained valve reliability coefficient Xk, response speed Sx, flow efficiency La, and load efficiency Lb, calculate the valve's real-time quality evaluation index Sz; The calculation formula of the real-time quality evaluation index Sz of the valve is: , where ω1, ω2, ω3, and ω4 represent the proportional coefficients of each item respectively; When the real-time quality evaluation index Sz of the valve does not exceed the preset value σ1, it indicates that the valve is operating normally and the inspection has passed; when the real-time quality evaluation index Sz of the valve exceeds the preset value σ2, it indicates that the valve is operating abnormally and needs to be replaced or repaired immediately; when the real-time quality evaluation index Sz of the valve is between the preset value σ1 and the preset value σ2, it indicates that there are safety hazards in the operation of the valve and the abnormal inspection data identification module is started; The abnormal inspection data identification module includes an abnormal inspection data alarm unit and an abnormal inspection data response unit. The abnormal inspection data alarm unit is used to calculate the valve comprehensive risk index, detect the valve risk according to the valve comprehensive risk index and issue an alarm; the abnormal inspection data response unit is used to generate a maintenance plan according to the alarm information and transmit it to the data display module; The specific processing process of the abnormal inspection data alarm unit is as follows: B1. Based on the ARIMA model, the reliability coefficient Xk, response speed Sx, flow efficiency La, and load efficiency Lb of the valve in each cycle are analyzed to predict the reliability coefficient Xk of the valve in each cycle in the future. 〃 , Response speed Sx 〃 , flow efficiency La 〃 , and load efficiency Lb 〃 ; B2. According to the reliability coefficient Xk of the valve in each future cycle 〃 , Response speed Sx 〃 , flow efficiency La 〃 , and load efficiency Lb 〃 , calculate the valve stability coefficient Wx, response speed change rate Lxb and efficiency stability index Lcx; B3. Calculate the valve comprehensive risk index Q based on the valve stability coefficient Wx, response speed change rate Lxb and efficiency stability index Lcx. , where λ represents the adjustment factor; B4. Compare the valve comprehensive risk index Q with the pre-set valve comprehensive risk index threshold Q threshold. If Q ≥ Q threshold, it means that the valve has a high risk and needs to take corresponding measures to reduce the risk. Otherwise, it means that the valve has a low risk and continues to monitor or take regular maintenance measures. B5. Transmit the high risk of valves as alarm information to the abnormal inspection data response unit; The specific processing process of the abnormal inspection data response unit is as follows: C1. Receive and record the alarm information of valves with high risk transmitted by the abnormal inspection data alarm unit; the alarm information includes the specific data of the valve stability coefficient Wx, the change rate of response speed Lxb and the efficiency stability index Lcx; C2. Based on the decision tree model, the corresponding maintenance plan is predicted according to the input valve stability coefficient, response speed change rate and efficiency stability index; C3, transmitting the alarm information and the corresponding maintenance plan to the data display module; Data display module: used to display the alarm information and corresponding maintenance plan on the smart valve handheld inspection terminal, and remind the inspection personnel through sound and vibration that there are new alarm information and maintenance plans that need to be handled.

2. The inspection data analysis system based on the smart valve handheld inspection terminal according to claim 1 is characterized in that: The calculation formula of the opening and closing frequency Pa is: , where zaj represents the number of times the valve is opened on the jth day, zbj represents the number of times the valve is closed on the jth day, Zj represents the number of times the valve is operated on the jth day, and n represents the amount of time; The calculation formula of the average fault frequency Pb is: , where gaj represents the number of valve failures on the jth day, Zj represents the number of valve operations on the jth day, and n represents the amount of time; The calculation formula of the average maintenance frequency Pc is: , where waj represents the number of valve maintenance on the jth day, Zj represents the number of valve operations on the jth day, and n represents the amount of time; The calculation formula of the average running time PTa is: , where taj represents the operation time of the valve on the jth day, and n represents the number of times; The calculation formula of the average running speed PTb is: , where tbj represents the operating speed of the valve on the jth day, and n represents the amount of time; The calculation formula of the average workload PTc is: , where tcj represents the workload of the valve on the jth day, and n represents the number of hours; The calculation formula of the average working flow PTd is: , where tdj represents the working flow of the valve on the jth day, and n represents the amount of time.

3. The inspection data analysis system based on the smart valve handheld inspection terminal according to claim 1 is characterized in that: The calculation formula of the reliability coefficient Xk is: , where Pa represents the opening and closing frequency of the valve, PTa represents the average operating time of the valve, Pb represents the average failure frequency of the valve, Pc represents the average maintenance frequency of the valve, and β1 and β2 represent the proportional coefficients of each item respectively; The calculation formula of the response speed Sx is: , where Pa represents the opening and closing frequency of the valve, and PTb represents the average operating speed; The calculation formula of the flow efficiency La is: , where K represents the valve opening, and PTd represents the average working flow of the valve; The calculation formula of the load efficiency Lb is: , where PTb represents the average operating speed of the valve and PTc represents the average working load of the valve.

4. The inspection data analysis system based on the smart valve handheld inspection terminal according to claim 1 is characterized in that: The calculation formula of the stability coefficient Wx is: , where N 〃 Indicates the number of future cycles, Xki 〃 Represents the reliability coefficient of the valve in the future i-th cycle, JXk 〃 Indicates the average reliability coefficient of the valve in the future; The calculation formula of the change rate Lxb of the response speed is: , where N 〃 Indicates the number of future cycles, Sx 〃 i Indicates the response speed of the valve in the future i-th cycle, Sx 〃 i+1 Indicates the response speed of the valve in the future i+1th cycle; The calculation formula of the efficiency stability index Lcx is: , where N 〃 Indicates the number of future cycles, Lai 〃 Indicates the flow efficiency of the valve in the future i-th cycle, Lbi 〃 Indicates the load efficiency of the valve in the future i-th cycle, JLa 〃 Indicates the average flow efficiency of the valve in the future, JLb 〃 It represents the average load efficiency of the valve in the future, and γ1 and γ2 represent the proportional coefficients of each item.

5. A method for analyzing inspection data based on a handheld inspection terminal for smart valves, the method being used to implement the inspection data analysis system based on a handheld inspection terminal for smart valves as described in any one of claims 1 to 4 above, characterized in that: The following steps are involved: Step S1: Collect the operation data and working condition data of the valve in real time through the smart valve handheld inspection terminal; Step S2, preprocessing the operation data and working condition data of the valve; Step S3, storing the preprocessed data in a database; Step S4, divide the data in the database into periods, perform statistical analysis on the data of each period, calculate the real-time quality evaluation index of the valve, judge the operating status of the valve according to the real-time quality evaluation index of the valve, and start the abnormal inspection data identification module when there is a safety hazard in the operation of the valve; Step S5, calculating the comprehensive risk index of the valve, detecting the valve risk according to the comprehensive risk index of the valve, and issuing an alarm, and generating a maintenance plan according to the alarm information; Step S6: Display the alarm information and the corresponding maintenance plan on the smart valve handheld inspection terminal to remind the inspection personnel to handle it; A1. Divide the valve operation data and working condition data in the database according to the cycle, recorded as xi, i=1, 2, 3...N; wherein xi represents the valve operation data and working condition data in the i-th cycle; the cycle in the division according to the cycle specifically refers to a period of time, such as one day, one week or one month; A2. Calculate the valve opening and closing frequency Pa, average failure frequency Pb, average maintenance frequency Pc, average operating time PTa, average operating speed PTb, average workload PTc, and average working flow PTd; A3. Calculate the valve's reliability coefficient Xk, response speed Sx, flow efficiency La, and load efficiency Lb; Based on the obtained valve reliability coefficient Xk, response speed Sx, flow efficiency La, and load efficiency Lb, the real-time quality evaluation index Sz of the valve is calculated; the calculation formula of the real-time quality evaluation index Sz of the valve is: , where ω1, ω2, ω3, and ω4 represent the proportional coefficients of each item respectively; when the real-time quality evaluation index Sz of the valve does not exceed the preset value σ1, it indicates that the valve is operating normally and the inspection has passed; when the real-time quality evaluation index Sz of the valve exceeds the preset value σ2, it indicates that the valve is operating abnormally and needs to be replaced or repaired immediately; when the real-time quality evaluation index Sz of the valve is between the preset value σ1 and the preset value σ2, it indicates that there are safety hazards in the operation of the valve and the abnormal inspection data identification module is started; B1. Based on the ARIMA model, the reliability coefficient Xk, response speed Sx, flow efficiency La, and load efficiency Lb of the valve in each cycle are analyzed to predict the reliability coefficient Xk of the valve in each cycle in the future. 〃 , Response speed Sx 〃 , flow efficiency La 〃 , and load efficiency Lb 〃 ; B2. According to the reliability coefficient Xk of the valve in each future cycle 〃 , Response speed Sx 〃 , flow efficiency La 〃 , and load efficiency Lb 〃 , calculate the valve stability coefficient Wx, response speed change rate Lxb and efficiency stability index Lcx; B3. Calculate the valve comprehensive risk index Q based on the valve stability coefficient Wx, response speed change rate Lxb and efficiency stability index Lcx. , where λ represents the adjustment factor; B4. Compare the valve comprehensive risk index Q with the pre-set valve comprehensive risk index threshold Q threshold. If Q ≥ Q threshold, it means that the valve has a high risk and needs to take corresponding measures to reduce the risk. Otherwise, it means that the valve has a low risk and continues to monitor or take regular maintenance measures. B5. Transmit the high risk of valves as alarm information to the abnormal inspection data response unit; C1. Receive and record the alarm information of valves with high risk transmitted by the abnormal inspection data alarm unit; the alarm information includes the specific data of the valve stability coefficient Wx, the change rate of response speed Lxb and the efficiency stability index Lcx; C2. Based on the decision tree model, the corresponding maintenance plan is predicted according to the input valve stability coefficient, response speed change rate and efficiency stability index; C3. Transmit the alarm information and the corresponding maintenance plan to the data display module.

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