Performance test management system for rubber fender

Abstract

The invention belongs to the technical field of rubber fender performance test, and particularly relates to a rubber fender performance test management system which comprises a server, a test item risk feedback module, a test item importance feedback module, a test supervision intensity comprehensive evaluation module, an operation matching degree detection and analysis module and a performance test evaluation early warning module. According to the invention, the risk analysis and the importance analysis are carried out on the corresponding performance test items, and the supervision intensity is judged based on the risk analysis result and the importance analysis result, so that supervision measures with the corresponding intensity are adapted when the corresponding performance test items are carried out, and safe and efficient completion of the corresponding performance test items is ensured. And matching degree analysis is carried out on corresponding performance test items and corresponding test operators, so that management personnel can carry out test personnel adjustment in time, the smooth and efficient test process is further ensured, and the accuracy of a rubber fender test result is ensured.

Description

Technical Field

[0001] The invention relates to the technical field of rubber fender performance testing, in particular to a performance testing management system for rubber fenders. Background Art

[0002] Rubber fender is a kind of anti-collision equipment, which is commonly seen in ports and docks. Rubber fender has the advantages of small reaction force, large energy absorption, easy installation, corrosion resistance, long service life, etc. There are many types of rubber fenders, and its application scenarios are wide, including solid fenders, floating fenders, filled fenders, etc. Each fender has its specific application scenario. For example, solid fenders are mainly suitable for large-scale facilities, while floating fenders are suitable for ship-to-ship, ship-to-dock, dock and other scenarios;

[0003] It is an essential link to conduct various performance tests on rubber fenders during their production process. At present, testers are often directly arranged to conduct tests on corresponding test items. The personnel arrangement is arbitrary, and it is impossible to conduct risk difficulty analysis and importance analysis on various performance test items, which is not conducive to the supervision arrangement and tester arrangement of managers during testing. In addition, it is impossible to analyze the matching degree between various performance test items and corresponding testers and provide feedback warnings. It is not only difficult to ensure the smooth and efficient testing process of rubber fenders, but also difficult to ensure the accuracy of test results;

[0004] In view of the above technical defects, a solution is now proposed. Summary of the invention

[0005] The purpose of the present invention is to provide a performance test management system for rubber fenders, which solves the problem that the prior art is unable to perform risk difficulty analysis and importance analysis on each performance test item, and is unable to analyze the matching degree between each performance test item and the corresponding tester and provide feedback warning, making it difficult to ensure the smooth and efficient progress of the rubber fender test process and the accuracy of the test results.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A performance test management system for a rubber fender comprises a server, a test item risk feedback module, a test item importance feedback module, a test supervision intensity comprehensive evaluation module, an operation matching degree detection and analysis module and a performance test evaluation and early warning module; the server collects the performance test items of the rubber fender, and marks the corresponding performance test items as analysis objects i, i={1,2,…,m}, m represents the number of performance test items and m is a natural number greater than 1; the test item risk feedback module performs risk analysis on the corresponding analysis object i, and accordingly assigns a risk determination symbol FX-1 or FX-2 to the corresponding analysis object i, and sends the risk determination symbol FX-1 or FX-2 of the corresponding analysis object i to the test supervision intensity comprehensive evaluation module via the server; the test item importance feedback module performs importance analysis on the corresponding analysis object i, and accordingly assigns an importance determination symbol ZY-1 or ZY-2 to the corresponding analysis object i, and sends the importance determination symbol ZY-1 or ZY-2 of the corresponding analysis object i to the test supervision intensity comprehensive evaluation module via the server;

[0008] The comprehensive assessment module of the test supervision intensity obtains the risk determination symbol FX-1 or FX-2 and the importance determination symbol ZY-1 or ZY-2 of the corresponding analysis object i, and generates the test high-intensity supervision signal, the test medium-intensity supervision signal or the test low-intensity supervision signal of the corresponding analysis object i through analysis; the test high-intensity supervision signal, the test medium-intensity supervision signal or the test low-intensity supervision signal of the corresponding analysis object i is sent to the test supervision terminal and the operation matching detection and analysis module via the server; the operation matching detection and analysis module is used to perform matching analysis on the corresponding performance test items and the corresponding test operators, and generate a matching qualified signal or a matching unqualified signal accordingly, and send the matching unqualified signal to the test supervision terminal via the server; the performance test assessment and early warning module is used to obtain the performance parameter data of all performance test items of the corresponding rubber fender, and generate a performance test unqualified signal or a performance test qualified signal through analysis, and send the performance test unqualified signal to the test supervision terminal via the server, and the test supervision terminal issues a corresponding early warning.

[0009] Furthermore, the specific operation process of the test project risk feedback module includes:

[0010] The number of operation steps of the analysis object i and the average operation time of each group of operation steps are obtained, and the average operation time is compared with the preset operation time threshold of the corresponding operation step. If the average operation time exceeds the corresponding preset operation time threshold, the corresponding operation step is marked as a difficult operation step. If the average operation time does not exceed the corresponding preset operation time threshold, the corresponding operation step is marked as an easy operation step. The number of difficult operation steps and the number of easy operation steps in the analysis object i are marked as PK1 and PK2 respectively, and the overall step evaluation coefficient PKi is obtained by ratio calculation through the formula PKi=PK1 / (PK2+0.864); the overall step evaluation coefficient of the analysis object i and the number of operation steps are numerically calculated to obtain the project difficulty assessment coefficient;

[0011] And obtain the number of test errors in the historical test process of the analysis object i and mark it as the operation error coefficient, and mark the number of erroneous operations in each test process as the single error frequency, and compare the single error frequency with the corresponding preset single error frequency threshold. If the single error frequency exceeds the preset single error frequency threshold, the corresponding test process is marked as a risk test, and the number of risk tests corresponding to the analysis object i and the operation error coefficient are numerically calculated to obtain the project stability assessment coefficient; the project difficulty assessment coefficient and the project stability assessment coefficient are numerically compared with the preset project difficulty assessment coefficient threshold and the preset project stability assessment coefficient threshold respectively. If both the project difficulty assessment coefficient and the project stability assessment coefficient do not exceed the corresponding preset threshold, the risk determination symbol FX-1 is assigned, and the risk determination symbol FX-2 is assigned in other cases.

[0012] Furthermore, the specific operation process of the test item importance feedback module includes:

[0013] The average total time and average test cost consumed by the analysis object i during the test process are obtained, and the average total time and average test cost consumed are numerically compared with the preset time consumption threshold and the preset cost consumption threshold, respectively. If the average total time consumed exceeds the preset time consumption threshold or the average test cost consumed exceeds the preset cost consumption threshold, an importance determination symbol ZY-2 is assigned;

[0014] If the average total time consumed and the average test cost consumed do not exceed the corresponding preset thresholds, the average total time consumed and the average test cost consumed are numerically calculated to obtain the importance assessment coefficient, and the importance assessment coefficient is numerically compared with the preset importance assessment coefficient threshold. If the importance assessment coefficient exceeds the preset importance assessment coefficient threshold, the importance judgment symbol ZY-2 is assigned; if the importance assessment coefficient does not exceed the preset importance assessment coefficient threshold, the importance judgment symbol ZY-1 is assigned.

[0015] Furthermore, the specific operation process of the comprehensive evaluation module for testing regulatory intensity is as follows:

[0016] Obtain the risk determination symbol FX-1 or FX-2 and the importance determination symbol ZY-1 or ZY-2 corresponding to the analysis object i, assign the value 1 to the risk determination symbol FX-1, assign the value 0 to the risk determination symbol FX-2, and assign the value 1 to the importance determination symbol ZY-1, and assign the value 0 to the importance determination symbol ZY-2; sum up the values ​​represented by the risk determination symbol and the importance determination symbol of the analysis object i to obtain the monitoring strength assessment value QTi. If QTi=0, a high-intensity supervision signal is generated for the test; if QTi=1, a medium-intensity supervision signal is generated for the test; if QTi=2, a low-intensity supervision signal is generated for the test.

[0017] Furthermore, the specific operation process of the operation matching detection and analysis module includes:

[0018] All test operators who perform the rubber fender performance test are obtained, and the corresponding test operators are marked as analysis targets k, where k = {1, 2, ..., g}, g represents the number of test operators and is a natural number greater than 1; the working time of the analysis target k for the rubber fender performance test and the total number of historical operations of the analysis target k for the corresponding performance test items are collected, and the number of successful completions of the corresponding performance test items and the total number of historical operations are calculated to obtain the project test success coefficient, and the working time of the analysis target k for the rubber fender performance test, the total number of historical operations of the corresponding performance test items, and the corresponding project test success coefficient are normalized to obtain the matching coefficient;

[0019] The matching coefficient of the corresponding analysis target k is numerically compared with the corresponding preset matching coefficient threshold. If the corresponding performance test item corresponds to the high-intensity supervision signal of the test, the value of the preset matching coefficient threshold is PT1. If the corresponding performance test item corresponds to the medium-intensity supervision signal of the test, the value of the preset matching coefficient threshold is PT2. If the corresponding performance test item corresponds to the low-intensity supervision signal of the test, the value of the preset matching coefficient threshold is PT3, and PT1>PT2>PT3>0; if the matching coefficient exceeds the corresponding preset matching coefficient threshold, it is judged that the analysis target k and the corresponding performance test item match normally and generate a matching qualified signal; if the matching coefficient does not exceed the corresponding preset matching coefficient threshold, it is judged that the analysis target k and the corresponding performance test item match abnormally and generate a matching unqualified signal.

[0020] Furthermore, the specific analysis process of the performance test evaluation and early warning module includes:

[0021] After testing all performance test items of the corresponding rubber fender, several groups of performance parameter data are obtained. If the performance parameter data meets the corresponding data requirements, the corresponding performance parameter data is marked as positive data. If the performance parameter data does not meet the corresponding data requirements, the corresponding performance parameter data is marked as negative data. The deviation value of the negative data compared with the corresponding data requirements is marked as a negative parameter factor. The negative parameter factor is numerically compared with the corresponding preset negative parameter factor range. If the negative parameter factor exceeds the maximum value of the corresponding preset negative parameter factor range, the corresponding negative data is marked as super-abnormal negative data. If the negative parameter factor is within the corresponding preset negative parameter factor range, the corresponding negative data is marked as medium-abnormal negative data. If the negative parameter factor does not exceed the minimum value of the corresponding preset negative parameter factor range, the corresponding negative data is marked as slightly abnormal negative data.

[0022] If there is excessive negative data in the performance parameter data of the corresponding rubber fender, a performance test failure signal is generated; if there is no excessive negative data in the performance parameter data of the corresponding rubber fender, the number of positive data, the number of medium negative data and the number of slightly negative data are obtained and marked as QE1, QE2 and QE3 respectively, and the performance evaluation coefficient QP is obtained by numerical calculation through the formula QP=(b2*QE2+b3*QE3) / (b1*QE1+0.827), b1, b2, b3 are preset proportional coefficients with values ​​greater than zero, b2>b3>b1; if QP≥QPmax, a performance test failure signal is generated, if QP<QPmax, a performance test qualified signal is generated, and QPmax is a preset judgment threshold of the performance evaluation coefficient QP, and the value of QPmax is greater than zero.

[0023] Compared with the prior art, the present invention has the following beneficial effects:

[0024] 1. In the present invention, risk analysis and importance analysis are performed on the corresponding performance test items so as to master the difficulty, risk status and importance status of all performance test items of the rubber fender, facilitate supervision of the subsequent test process, help to smoothly complete the performance test of the rubber fender, improve test efficiency and test effect and reduce test costs, and generate a high-intensity supervision signal, a medium-intensity supervision signal or a low-intensity supervision signal for the corresponding performance test items based on the risk analysis results and the importance analysis results, so as to adapt the supervision measures of the corresponding intensity when performing the corresponding performance test items, ensure the safe and efficient completion of the corresponding performance test items, help to arrange test personnel, and have a high degree of intelligence;

[0025] 2. In the present invention, by performing matching analysis between corresponding performance test items and corresponding test operators, a matching qualified signal or a matching unqualified signal is generated accordingly, so as to realize the matching degree feedback and early warning of the testers of corresponding performance test items, so that the management personnel can adjust the testers in time, thereby further ensuring the smooth and efficient progress of the test process, and further ensuring the accuracy of the test results of the rubber fender; and by obtaining the performance parameter data of all performance test items of the corresponding rubber fender, and analyzing them to evaluate the quality and performance of the rubber fender, so that the backstage management personnel can grasp the performance status of the rubber fender in time, which is helpful to timely trace the production to find the cause of the performance abnormality, and increase the test inspection of the produced rubber fender as needed to ensure the product quality of the produced rubber fender. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings;

[0027] Figure 1 This is a system block diagram of Embodiment 1 of the present invention;

[0028] Figure 2 This is a system block diagram of Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0029] 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.

[0030] Embodiment 1: Figure 1 As shown, a performance test management system for a rubber fender proposed by the present invention includes a server, a test item risk feedback module, a test item importance feedback module, a test supervision intensity comprehensive evaluation module, and an operation matching degree detection and analysis module, and the server is communicatively connected with the test item risk feedback module, the test item importance feedback module, the test supervision intensity comprehensive evaluation module, and the operation matching degree detection and analysis module;

[0031] The server collects the performance test items of the rubber fender, and marks the corresponding performance test items as analysis object i, i = {1, 2, ..., m}, m represents the number of performance test items and m is a natural number greater than 1; the test item risk feedback module performs risk analysis on the corresponding analysis object i, and assigns risk determination symbol FX-1 or FX-2 to the corresponding analysis object i accordingly, and sends the risk determination symbol FX-1 or FX-2 of the corresponding analysis object i to the test supervision intensity comprehensive evaluation module via the server, so as to grasp the difficulty of successfully completing all performance test items of the rubber fender, which is helpful to take supervision measures suitable for the corresponding performance test items, and further ensure the smooth completion of the rubber fender performance test and improve the accuracy of the test results; the specific operation process of the test item risk feedback module is as follows:

[0032] The number of operation steps of the analysis object i and the average operation time of each group of operation steps are obtained, and the average operation time is compared with the preset operation time threshold of the corresponding operation step. If the average operation time exceeds the corresponding preset operation time threshold, the corresponding operation step is marked as a difficult operation step. If the average operation time does not exceed the corresponding preset operation time threshold, the corresponding operation step is marked as an easy operation step. The number of difficult operation steps and the number of easy operation steps in the analysis object i are marked as PK1 and PK2 respectively, and the overall step evaluation coefficient PKi is obtained by ratio calculation using the formula PKi=PK1 / (PK2+0.864);

[0033] The overall evaluation coefficient PKi of the step of the analysis object i and the number of operation steps BSi are numerically calculated by the formula CKi=au1*PKi+au2*BSi to obtain the project difficulty evaluation coefficient CKi; it should be noted that BSi=PK1+PK2; wherein au1 and au2 are preset weight coefficients, au1>au2>1; and the numerical value of the project difficulty evaluation coefficient CKi is positively proportional to the overall evaluation coefficient PKi of the step and the number of operation steps BSi. The larger the numerical value of the project difficulty evaluation coefficient CKi, the greater the obstacle to the successful completion of the corresponding analysis object i, and the more supervision needs to be strengthened during the implementation of the corresponding performance test project;

[0034] And obtain the number of test errors in the historical test process of the analysis object i and mark it as the operation error coefficient, and mark the number of erroneous operations in each test process as the single error frequency, and compare the single error frequency with the corresponding preset single error frequency threshold. If the single error frequency exceeds the preset single error frequency threshold, the corresponding test process is marked as a risk test, and the number of risk tests TSi corresponding to the analysis object i and the operation error coefficient WSi are numerically calculated through the formula CWi=(ap1*TSi+ap2*WSi) / 2 to obtain the project stability assessment coefficient CWi;

[0035] Among them, ap1 and ap2 are preset weight coefficients, ap1>ap2>0; and, as can be seen from the above formula, the numerical value of the project stabilization assessment coefficient CWi is positively proportional to the number of risk tests TSi and the operation error coefficient WSi. The larger the numerical value of the project stabilization assessment coefficient CWi, the more difficult it is to complete the analysis object i smoothly, and the more supervision needs to be strengthened during the implementation of the corresponding performance test project; the project difficulty assessment coefficient CKI and the project stabilization assessment coefficient CWi are numerically compared with the preset project difficulty assessment coefficient threshold and the preset project stabilization assessment coefficient threshold, respectively. If the project difficulty assessment coefficient CKI and the project stabilization assessment coefficient CWi do not exceed the corresponding preset threshold, indicating that the corresponding performance test project is easier to complete smoothly and safely, then the risk judgment symbol FX-1 is assigned, and the risk judgment symbol FX-2 is assigned in other cases.

[0036] The test item importance feedback module will perform importance analysis on the corresponding analysis object i, and assign importance judgment symbol ZY-1 or ZY-2 to the corresponding analysis object i accordingly, and send the importance judgment symbol ZY-1 or ZY-2 of the corresponding analysis object i to the test supervision intensity comprehensive evaluation module via the server, so as to grasp the importance status of all performance test items of the rubber fender, facilitate the supervision of the subsequent test process, help to smoothly complete the performance test of the rubber fender, improve the test efficiency and test effect and reduce the test cost; the specific operation process of the test item importance feedback module is as follows:

[0037] The average total time and average test cost consumed by the analysis object i during the test process are obtained, and the average total time and average test cost consumed are numerically compared with the preset time consumption threshold and the preset cost consumption threshold, respectively. If the average total time consumed exceeds the preset time consumption threshold or the average test cost consumed exceeds the preset cost consumption threshold, it indicates that the corresponding performance test project is more important, the test process investment is larger, and the supervision needs to be strengthened during the test process, and the importance judgment symbol ZY-2 is assigned; if the average total time consumed and the average test cost consumed do not exceed the corresponding preset threshold, the average total time consumed PGi and the average test cost consumed PBi are numerically calculated through the formula ZPi=bt1*PG i+bt2*PBi to obtain the importance evaluation coefficient ZPi;

[0038] Among them, bt1 and bt2 are preset weight coefficients, bt2>bt1>1; from the above formula, it can be seen that the value of the importance assessment coefficient ZPi is positively proportional to the average total time PGi consumed and the average test cost PBi consumed. The larger the value of the importance assessment coefficient ZPi, the more important the corresponding performance test item is; the importance assessment coefficient ZPi is numerically compared with the preset importance assessment coefficient threshold. If the importance assessment coefficient ZPi exceeds the preset importance assessment coefficient threshold, it indicates that the corresponding performance test item is more important, and the importance judgment symbol ZY-2 is assigned; if the importance assessment coefficient ZPi does not exceed the preset importance assessment coefficient threshold, the importance judgment symbol ZY-1 is assigned.

[0039] The test supervision intensity comprehensive evaluation module obtains the risk determination symbol FX-1 or FX-2 and the importance determination symbol ZY-1 or ZY-2 of the corresponding analysis object i, and generates the test high-intensity supervision signal, the test medium-intensity supervision signal or the test low-intensity supervision signal of the corresponding analysis object i through analysis, so as to adapt the corresponding intensity supervision measures when carrying out the corresponding performance test items, ensure the safe and efficient completion of the corresponding performance test items, and facilitate the arrangement of test personnel, with a high degree of intelligence; the specific operation process of the test supervision intensity comprehensive evaluation module is as follows:

[0040] Obtain the risk determination symbol FX-1 or FX-2 and the importance determination symbol ZY-1 or ZY-2 of the corresponding analysis object i, assign the value 1 to the risk determination symbol FX-1, assign the value 0 to the risk determination symbol FX-2, and assign the value 1 to the importance determination symbol ZY-1, and assign the value 0 to the importance determination symbol ZY-2; sum up the values ​​represented by the risk determination symbol and the importance determination symbol of the corresponding analysis object i to obtain the supervision strength assessment value QT i, if QT i=0, it indicates that the importance and completion difficulty of the corresponding performance test item are both large, then a high-intensity supervision signal for the test is generated, if QT i=1, then a medium-intensity supervision signal for the test is generated, if QT i=2, it indicates that the importance and completion difficulty of the corresponding performance test item are both small, then a low-intensity supervision signal for the test is generated;

[0041] The high-intensity supervision signal, medium-intensity supervision signal or low-intensity supervision signal of the corresponding analysis object i is sent to the test supervision terminal and the operation matching detection and analysis module via the server; the operation matching detection and analysis module is used to perform matching analysis between the corresponding performance test items and the corresponding test operators, and generate a matching qualified signal or a matching unqualified signal accordingly, and send the matching unqualified signal to the test supervision terminal via the server to realize the matching degree feedback and early warning of the test personnel of the corresponding performance test items, so that the management personnel can adjust the test personnel in time, thereby further ensuring the smooth and efficient progress of the test process, and further ensuring the accuracy of the rubber fender test results; the specific operation process of the operation matching detection and analysis module is as follows:

[0042] All test operators who perform the rubber fender performance test are obtained, and the corresponding test operators are marked as analysis targets k, where k = {1, 2, ..., g}, g represents the number of test operators and is a natural number greater than 1; the working time of the rubber fender performance test performed by the analysis target k is collected, as well as the total number of historical operations of the corresponding performance test items performed by the analysis target k. The number of times the corresponding performance test items are successfully completed and the total number of historical operations are calculated to obtain the project test success coefficient, and the formula is used. The working time GSk of the rubber fender performance test of the analysis target k, the total number of historical operations CZk of the corresponding performance test items, and the corresponding item test success coefficient SLk are normalized and calculated to obtain the matching coefficient QHk;

[0043] Among them, es1, es2, and es3 are all preset proportional coefficients with values ​​greater than zero, and es3>es2>es1; and, the larger the value of the matching coefficient QHk, the more the corresponding analysis target k matches the corresponding performance test item, and the more the corresponding performance test item can be efficiently and smoothly completed; the matching coefficient QHk of the corresponding analysis target k is numerically compared with the corresponding preset matching coefficient threshold. If the matching coefficient QHk exceeds the corresponding preset matching coefficient threshold, it is judged that the analysis target k matches the corresponding performance test item normally and a matching qualified signal is generated. If the matching coefficient QHk does not exceed the corresponding preset matching coefficient threshold, then It is determined that the analysis target k matches the corresponding performance test item abnormally and generates a matching failure signal; it should be noted that if the corresponding performance test item corresponds to the high-intensity supervision signal of the test, the preset matching coefficient threshold value is PT1, if the corresponding performance test item corresponds to the medium-intensity supervision signal of the test, the preset matching coefficient threshold value is PT2, if the corresponding performance test item corresponds to the low-intensity supervision signal of the test, the preset matching coefficient threshold value is PT3, and PT1>PT2>PT3>0; the preset matching coefficient threshold values ​​with different values ​​for different supervision intensities are used to help ensure the accuracy of the analysis results.

[0044] Embodiment 2: Figure 2 As shown, the difference between this embodiment and embodiment 1 is that the server is connected to the performance test evaluation and early warning module in communication. When the matching degree of all performance test items of the corresponding rubber fender and the corresponding test operator is normal, various performance test operations of the rubber fender are performed. The performance test evaluation and early warning module obtains the performance parameter data of all performance test items of the corresponding rubber fender, and generates a performance test failure signal or a performance test pass signal through analysis, and sends the performance test failure signal to the test supervision terminal via the server. The test supervision terminal issues a corresponding early warning so that the backstage management personnel can timely grasp the performance status of the rubber fender. When the corresponding management personnel receive the corresponding early warning, they can timely trace the production to find the cause of the performance abnormality, and increase the test inspection of the produced rubber fender as needed, which is helpful to ensure the product quality of the produced rubber fender. The specific analysis process of the performance test evaluation and early warning module is as follows:

[0045] After testing all performance test items of the corresponding rubber fender, several groups of performance parameter data (including tensile strength data, tear strength data, compression strength data, resilience data, etc.) are obtained. If the performance parameter data meets the corresponding data requirements, the corresponding performance parameter data is marked as positive data. If the performance parameter data does not meet the corresponding data requirements, the corresponding performance parameter data is marked as negative data. The deviation value of the negative data compared with the corresponding data requirements is marked as a negative parameter factor. The negative parameter factor is numerically compared with the corresponding preset negative parameter factor range. If the negative parameter factor exceeds the maximum value of the corresponding preset negative parameter factor range, the corresponding negative data is marked as super abnormal negative data. If the negative parameter factor is within the corresponding preset negative parameter factor range, the corresponding negative data is marked as medium abnormal negative data. If the negative parameter factor does not exceed the minimum value of the corresponding preset negative parameter factor range, the corresponding negative data is marked as slightly abnormal negative data.

[0046] If there are super-abnormal negative data in the performance parameter data of the corresponding rubber fender, it indicates that the performance and quality of the corresponding rubber fender are poor, and a performance test failure signal is generated. If there are no super-abnormal negative data in the performance parameter data of the corresponding rubber fender, the number of positive data, the number of medium-abnormal negative data and the number of slightly abnormal negative data are obtained and marked as QE1, QE2 and QE3 respectively. The performance is calculated by numerical calculation using the formula QP = (b2*QE2+b3*QE3) / (b1*QE1+0.827). The performance evaluation coefficient QP, b1, b2, and b3 are preset proportional coefficients whose values ​​are greater than zero, and b2>b3>b1; it should be noted that the larger the value of the performance evaluation coefficient QP, the worse the performance of the rubber fender; the performance evaluation coefficient QP is numerically compared with QPmax (QPmax is a preset judgment threshold of the performance evaluation coefficient QP, and the value of QPmax is greater than zero), if QP≥QPmax, a performance test failure signal is generated, and if QP<QPmax, a performance test pass signal is generated.

[0047] The working principle of the present invention is as follows: when in use, a risk analysis is performed on the corresponding performance test items through the test item risk feedback module, so as to understand the difficulty of successfully completing all performance test items of the rubber fender; an importance analysis is performed on the corresponding performance test items through the test item importance feedback module, so as to understand the importance of all performance test items of the rubber fender, which is convenient for supervision of subsequent test processes, helps to successfully complete the performance test of the rubber fender, improves test efficiency and test effect, and reduces test costs; and a test supervision intensity comprehensive evaluation module generates a test high-intensity supervision signal and a test medium-intensity supervision signal for the corresponding performance test items based on the risk analysis results and the importance analysis results and through analysis. Or test low-intensity supervision signals, so as to adapt supervision measures of corresponding intensity when conducting corresponding performance test items, ensure the safe and efficient completion of corresponding performance test items, help to arrange test personnel, and have a high degree of intelligence; and through the operation matching detection and analysis module, the corresponding performance test items and the corresponding test operators are matched for analysis, and a qualified matching signal or an unqualified matching signal is generated accordingly, and the unqualified matching signal is sent to the test supervision terminal via the server, so as to realize the matching degree feedback and early warning of the test personnel of the corresponding performance test items, so that the management personnel can adjust the test personnel in time, thereby further ensuring the smooth and efficient progress of the test process, and further ensuring the accuracy of the rubber fender test results.

[0048] The above formulas are all dimensionless and numerical calculations. The formula is a formula obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formula are set by technicians in this field according to actual conditions. The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the contents of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that technicians in the relevant technical field can understand and use the present invention well. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. A performance test management system for rubber fenders, characterized in that: It includes server, test item risk feedback module, test item importance feedback module, test supervision intensity comprehensive evaluation module, operation matching degree detection and analysis module and performance test evaluation and early warning module; The server collects the performance test items of the rubber fender, and marks the corresponding performance test items as analysis objects i, where i = {1, 2, ..., m}, and m represents the number of performance test items and is a natural number greater than 1; The test item risk feedback module performs risk analysis on the corresponding analysis object i, assigns a risk determination symbol FX-1 or FX-2 to the corresponding analysis object i, and sends the risk determination symbol FX-1 or FX-2 of the corresponding analysis object i to the test supervision intensity comprehensive assessment module via the server; The test item importance feedback module performs importance analysis on the corresponding analysis object i, assigns importance determination symbol ZY-1 or ZY-2 to the corresponding analysis object i, and sends the importance determination symbol ZY-1 or ZY-2 of the corresponding analysis object i to the test supervision intensity comprehensive assessment module via the server; The test supervision intensity comprehensive assessment module obtains the risk determination symbol FX-1 or FX-2 and the importance determination symbol ZY-1 or ZY-2 corresponding to the analysis object i, and generates a test high-intensity supervision signal, a test medium-intensity supervision signal or a test low-intensity supervision signal corresponding to the analysis object i through analysis; Sending the test high-intensity supervision signal, the test medium-intensity supervision signal or the test low-intensity supervision signal corresponding to the analysis object i to the test supervision terminal and the operation matching degree detection and analysis module via the server; The operation matching degree detection and analysis module is used to perform matching degree analysis between the corresponding performance test items and the corresponding test operators, thereby generating a matching degree qualified signal or a matching degree unqualified signal, and sending the matching degree unqualified signal to the test supervision terminal via the server; The performance test evaluation and early warning module is used to obtain the performance parameter data of all performance test items of the corresponding rubber fender, and generate a performance test failure signal or a performance test pass signal through analysis, and send the performance test failure signal to the test supervision terminal via the server, and the test supervision terminal issues a corresponding early warning.

2. A performance test management system for rubber fenders according to claim 1, characterized in that: The specific operation process of the test project risk feedback module includes: The number of operation steps of the analysis object i and the average operation time of each group of operation steps are obtained, and the average operation time is numerically compared with the preset operation time threshold of the corresponding operation step. If the average operation time exceeds the corresponding preset operation time threshold, the corresponding operation step is marked as a difficult operation step. If the average operation time does not exceed the corresponding preset operation time threshold, the corresponding operation step is marked as an easy operation step. The number of difficult operation steps and the number of easy operation steps in the analysis object i are marked as PK1 and PK2 respectively, and the overall step evaluation coefficient PKi is obtained by ratio calculation through the formula PKi=PK1 / (PK2+0.864); the overall step evaluation coefficient of the analysis object i and the number of operation steps are numerically calculated to obtain the project difficulty assessment coefficient; And obtain the number of test errors in the historical test process of the analysis object i and mark it as the operation error coefficient, and mark the number of erroneous operations in each test process as the single error frequency, and compare the single error frequency with the corresponding preset single error frequency threshold. If the single error frequency exceeds the preset single error frequency threshold, the corresponding test process is marked as a risk test, and the number of risk tests corresponding to the analysis object i and the operation error coefficient are numerically calculated to obtain the project stability assessment coefficient; the project difficulty assessment coefficient and the project stability assessment coefficient are numerically compared with the preset project difficulty assessment coefficient threshold and the preset project stability assessment coefficient threshold respectively. If both the project difficulty assessment coefficient and the project stability assessment coefficient do not exceed the corresponding preset threshold, the risk determination symbol FX-1 is assigned, and the risk determination symbol FX-2 is assigned in other cases.

3. A performance test management system for rubber fenders according to claim 1, characterized in that: The specific operation process of the test item importance feedback module includes: The average total time and average test cost consumed by the analysis object i during the test process are obtained, and the average total time and average test cost consumed are numerically compared with the preset time consumption threshold and the preset cost consumption threshold, respectively. If the average total time consumed exceeds the preset time consumption threshold or the average test cost consumed exceeds the preset cost consumption threshold, an importance determination symbol ZY-2 is assigned; If the average total time consumed and the average test cost consumed do not exceed the corresponding preset thresholds, the average total time consumed and the average test cost consumed are numerically calculated to obtain the importance assessment coefficient, and the importance assessment coefficient is numerically compared with the preset importance assessment coefficient threshold. If the importance assessment coefficient exceeds the preset importance assessment coefficient threshold, the importance judgment symbol ZY-2 is assigned; if the importance assessment coefficient does not exceed the preset importance assessment coefficient threshold, the importance judgment symbol ZY-1 is assigned.

4. A performance test management system for rubber fenders according to claim 1, characterized in that: The specific operation process of the comprehensive assessment module for testing regulatory intensity is as follows: Obtain the risk determination symbol FX-1 or FX-2 and the importance determination symbol ZY-1 or ZY-2 corresponding to the analysis object i, assign the value 1 to the risk determination symbol FX-1, assign the value 0 to the risk determination symbol FX-2, and assign the value 1 to the importance determination symbol ZY-1, and assign the value 0 to the importance determination symbol ZY-2; The numerical values ​​represented by the risk judgment symbol and the importance judgment symbol of the corresponding analysis object i are summed up to obtain the supervision assessment value QTi. If QTi=0, a high-intensity supervision signal is generated; if QTi=1, a medium-intensity supervision signal is generated; if QTi=2, a low-intensity supervision signal is generated.

5. A performance test management system for rubber fenders according to claim 4, characterized in that: The specific operation process of the operation matching detection and analysis module includes: All test operators who perform the rubber fender performance test are obtained, and the corresponding test operators are marked as analysis targets k, where k = {1, 2, ..., g}, g represents the number of test operators and is a natural number greater than 1; the working time of the analysis target k for the rubber fender performance test and the total number of historical operations of the analysis target k for the corresponding performance test items are collected, and the number of successful completions of the corresponding performance test items and the total number of historical operations are calculated to obtain the project test success coefficient, and the working time of the analysis target k for the rubber fender performance test, the total number of historical operations of the corresponding performance test items, and the corresponding project test success coefficient are normalized to obtain the matching coefficient; The matching coefficient of the corresponding analysis target k is numerically compared with the corresponding preset matching coefficient threshold. If the corresponding performance test item corresponds to the high-intensity supervision signal of the test, the value of the preset matching coefficient threshold is PT1. If the corresponding performance test item corresponds to the medium-intensity supervision signal of the test, the value of the preset matching coefficient threshold is PT2. If the corresponding performance test item corresponds to the low-intensity supervision signal of the test, the value of the preset matching coefficient threshold is PT3, and PT1>PT2>PT3>0; if the matching coefficient exceeds the corresponding preset matching coefficient threshold, it is judged that the analysis target k and the corresponding performance test item match normally and generate a matching qualified signal; if the matching coefficient does not exceed the corresponding preset matching coefficient threshold, it is judged that the analysis target k and the corresponding performance test item match abnormally and generate a matching unqualified signal.

6. A performance test management system for rubber fenders according to claim 1, characterized in that: The specific analysis process of the performance test evaluation and early warning module includes: After testing all performance test items of the corresponding rubber fender, several groups of performance parameter data are obtained. If the performance parameter data meets the corresponding data requirements, the corresponding performance parameter data is marked as positive data. If the performance parameter data does not meet the corresponding data requirements, the corresponding performance parameter data is marked as negative data. The deviation value of the negative data compared with the corresponding data requirements is marked as a negative parameter factor. The negative parameter factor is numerically compared with the corresponding preset negative parameter factor range. If the negative parameter factor exceeds the maximum value of the corresponding preset negative parameter factor range, the corresponding negative data is marked as super-abnormal negative data. If the negative parameter factor is within the corresponding preset negative parameter factor range, the corresponding negative data is marked as medium-abnormal negative data. If the negative parameter factor does not exceed the minimum value of the corresponding preset negative parameter factor range, the corresponding negative data is marked as slightly abnormal negative data. If there is excessive negative data in the performance parameter data of the corresponding rubber fender, a performance test failure signal is generated; if there is no excessive negative data in the performance parameter data of the corresponding rubber fender, the number of positive data, the number of medium negative data and the number of slightly negative data are obtained and marked as QE1, QE2 and QE3 respectively, and the performance evaluation coefficient QP is obtained by numerical calculation through the formula QP=(b2*QE2+b3*QE3) / (b1*QE1+0.827), b1, b2, b3 are preset proportional coefficients with values ​​greater than zero, b2>b3>b1; if QP≥QPmax, a performance test failure signal is generated, if QP<QPmax, a performance test qualified signal is generated, and QPmax is a preset judgment threshold of the performance evaluation coefficient QP, and the value of QPmax is greater than zero.

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