A ship system semi-physical simulation test simulation method and system, and electronic equipment

Abstract

The present invention proposes a simulation method and system for semi-physical simulation test of ship system, which uses a simulation model in a virtual simulation environment combined with test equipment in a hardware test environment on the semi-physical simulation test platform of the ship system to build a simulation test platform for processing ship system simulation data, so as to complete working condition tests of different test equipment and different scenarios. Through the ship system simulation data processing method of the present invention, on-site test data acquisition and system design and verification are carried out, and it is possible to quickly switch between the simulation environment and the test environment, compare the correctness of the verification test of the simulation data, and find out the difference between the pure virtual simulation and the actual test; when some test equipment of the intelligent manufacturing service platform is not present, simulation replacement can be performed in the simulation environment, which can ensure the integrity and comprehensive progress of the simulation data test.

Description

Technical Field

[0001] The present application relates to the technical field of high-end equipment manufacturing and intelligent manufacturing equipment industries, and in particular to a semi-physical simulation test method and system for ship systems, and electronic equipment. Background Art

[0002] High-end equipment manufacturing, also known as advanced equipment manufacturing, refers to the industry that produces and manufactures high-tech, high-value-added advanced industrial facilities and equipment. High-end equipment mainly includes high-tech and high-value-added equipment required for the transformation and upgrading of traditional industries and the development of strategic emerging industries. Intelligent manufacturing equipment refers to manufacturing equipment with perception, analysis, reasoning, decision-making, and control functions. It is an integration and deep fusion of advanced manufacturing technology, information technology, and intelligent technology. At present, ship systems are important applications of high-end equipment manufacturing and intelligent manufacturing equipment industries. The design verification test and interface joint debugging test of the semi-physical simulation test method of the ship system have the characteristics of many participating equipment, long test cycle, and cumbersome test subjects. Due to the significant shortening of the delivery cycle of ship products and the significant improvement of technical indicators, the previous model of conducting concentrated tests after all participating equipment arrives on site can no longer meet the current development needs. The use of system virtual simulation and other means also has the problem of lack of test data correction such as data applied to shipbuilding industry manufacturing, resulting in low accuracy of simulation results. There is an urgent need to develop a simulation test simulation system that can not only support pure virtual simulation, but also connect to the test equipment at any time, and carry out semi-physical / physical tests through a semi-physical test system. In this way, test verification can be carried out in advance when all test equipment are not on site, thereby improving the processing efficiency of test data and effectively enhancing the intelligent manufacturing capabilities. Summary of the invention

[0003] In order to meet the simulation requirements of a semi-physical simulation test of a ship system, the present invention provides a simulation method for a semi-physical simulation test of a ship system, the method comprising the following steps:

[0004] S1, starting a simulation test platform, identifying a test device connected to a signal switching module of the simulation test platform, and determining a simulation model to be imported according to the connected test device and a test device list, wherein the test device list includes identifiers of all test devices to be tested;

[0005] S2, importing the simulation model to be imported into the simulation test platform, checking the hardware system connection according to the connection relationship between the signal switching module and the test equipment, and configuring the simulation environment;

[0006] S3, importing the test case into the simulation test platform, and collecting the test result data of the simulation test platform in real time;

[0007] S4, extracting two groups of test result data from the test result data according to the connection relationship, and performing data alignment, data matching and data analysis on the two groups of test result data to optimize and adjust the parameters of the simulation model, wherein the two groups of test result data correspond to the connection state of the signal switching module for any one of the test devices and the import state of its simulation model.

[0008] As a possible implementation manner, the determining the simulation model to be imported according to the connected test equipment and the test equipment list further includes:

[0009] The simulation test platform obtains a first identification set of all test equipment connected to the signal switching module, matches the first identification set with the test equipment list to obtain a second identification set of the test equipment that is not connected to the signal switching module among all the test equipment to be tested, and uses the simulation model corresponding to the test equipment corresponding to the second identification set as the simulation model to be imported.

[0010] As a possible implementation manner, checking the hardware system connection according to the connection relationship between the signal switching module and the test equipment further includes:

[0011] The hardware system connection is checked according to the connection relationship between the signal switching module and the test equipment to determine whether the hardware system connection needs to be configured; if so, the flexible wiring module is run to flexibly configure the connection between the control system and the actuator.

[0012] As a possible implementation manner, extracting two groups of test result data from the test result data according to the connection relationship specifically includes:

[0013] The test result data of any one of the test devices and the simulation test platform being in a connected state for a preset time period is taken as the first group of test result data, and the test result data of the test device and the simulation test platform being in a disconnected state for the preset time period is taken as the second group of test result data, wherein the simulation test platform has imported the simulation model corresponding to the test device within the preset time period when the test device and the simulation test platform are in a disconnected state, and the connection status of other test devices and the simulation test platform and the import status of other simulation models of the simulation test platform remain unchanged within the preset time period.

[0014] As a possible implementation manner, extracting two groups of test result data from the test result data according to the connection relationship specifically includes:

[0015] According to each simulation model imported by the simulation test platform and the time step of the corresponding test equipment sampling, a timestamp is added to the test result data collected at each sampling point;

[0016] When the test device and the simulation test platform are connected, sampling point data with timestamps added of the preset time length is extracted according to the time step as a first set of test result data of the test device;

[0017] When the simulation model corresponding to the test equipment has been imported into the simulation test platform, sampling point data with timestamps added of the preset time length are extracted according to the time step as a second group of test result data corresponding to the simulation model.

[0018] As a possible implementation, data alignment and data matching are performed on the two groups of test result data, specifically including:

[0019] Determine the start time and end time of the first group of test result data and the second group of test result data;

[0020] According to the time range of the first group of test result data and the second group of test result data, selecting the same time period for interception;

[0021] The same time step and sampling frequency are maintained so that the first group of test result data and the second group of test result data have the same time resolution.

[0022] As a possible implementation manner, the preset duration is the duration of a sampling period, and further includes:

[0023] Acquire the first set of test result data and the second set of test result data of the preset time period;

[0024] Calculate the mean of all the test result data of any sampling point in the sampling period of the first group of test result data, and take the set of test result data of the sampling point with the smallest error with the mean in the sampling period as the first group of test result data;

[0025] Calculate the mean of all the test result data of any sampling point in the sampling period of the second set of test result data, and take the set of test result data of the sampling point with the smallest error with the mean in the sampling period as the second set of test result data.

[0026] Optimizing and adjusting the parameters of the simulation model specifically includes:

[0027] Assume there are N sets, and initialize each set at time k = 0;

[0028] predict:

[0029] in, Identifies the state analysis value of the i-th set at time k, represents the predicted value of the state at time k+1, M k,k+1 represents the state change relationship from time k to time k+1, ω i,k Represents the model error, and its mean is 0. The covariance matrix is ​​Q k Normal distribution of

[0030] renew:

[0031]

[0032]

[0033]

[0034]

[0035]

[0036] in, is the state analysis value of the i-th set at time k+1, K k+1 is the gain matrix, is the observation matrix at time k+1, H k+1 is the observation operator at time k+1, v i,k is the observation error, and its mean is 0. The covariance matrix is ​​Q k Gaussian distribution, is the mean of all the analyzed values ​​of the set, is the mean of all predicted values ​​of the set, is the prediction error variance matrix, R k is the observation field error covariance matrix.

[0037] As another embodiment, the present invention provides a semi-physical simulation test system for a ship system, the system comprising the following modules:

[0038] Signal simulation module for implementing actuator simulation, signal conditioning, signal aggregation and distribution, signal exchange and clock synchronization functions;

[0039] Flexible interface module for switching between system test environment and simulation environment, fault simulation injection, disconnection test, and test data bypass collection;

[0040] A test operation environment module for providing an operation environment for the test control host, simulation model, tester integrated software, and test system data;

[0041] The ship system simulation industrial data processing system based on the Internet intelligent manufacturing service platform executes the ship system semi-physical simulation test simulation method as described above.

[0042] As another embodiment, the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned semi-physical simulation test method for a ship system when executing the program.

[0043] The present invention proposes that the present invention provides a simulation method and system for semi-physical simulation test of a ship system, and a simulation test simulation platform system is built by using a simulation model in a virtual simulation environment combined with test equipment in a hardware test environment, so as to complete the working condition test of different test equipment and different scenes. Through the simulation test simulation platform system of the present invention, on-site test data acquisition and system design and verification can be carried out, and the simulation environment and the test environment can be quickly switched to compare and verify the correctness of the test; at the same time, the difference between the pure virtual simulation and the actual test can be found according to the comparative test; when some test equipment is not on site, simulation substitution can be performed in the simulation environment, which can ensure the integrity and comprehensive progress of the test. When there are doubts about some data in the test, the data information collected by bypass isolation can be used for verification; it has the function of digital analog information fault injection, and can test some test functions of the test equipment, the robustness of the ship system control strategy, etc. By switching between full digital simulation and semi-physical simulation, not only can the accuracy of the simulation model be improved, design verification can be carried out in advance, but also joint debugging tests can be carried out in advance, greatly shortening the test cycle. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is a schematic diagram of a flow chart of a simulation method for a semi-physical simulation test of a ship system provided by the present invention;

[0045] Figure 2 It is a semi-physical simulation test simulation device of a ship system of the present invention and a system principle diagram;

[0046] Figure 3 It is a schematic diagram of the control algorithm model development process of the present invention;

[0047] Figure 4 It is a schematic diagram of the data comparison and analysis process of the present invention;

[0048] Figure 5 It is a flow chart of the operation of the comprehensive test operation software of the present invention;

[0049] Figure 6 It is a schematic diagram of the operation flow of the comprehensive software of the tester of the present invention;

[0050] Figure 7 It is a schematic diagram of the system configuration software operation flow of the present invention;

[0051] Figure 8 It is a schematic diagram of the operation flow of the host computer software of the simulation system of the present invention;

[0052] Fig. 9 It is a schematic diagram of the execution flow of the tester operation management software of the present invention;

[0053] Fig.10 It is a schematic diagram of the operation flow of the fault injection software of the present invention. DETAILED DESCRIPTION

[0054] The embodiments of the present invention are further described below with reference to the accompanying drawings.

[0055] like Figure 1 As shown, in some embodiments, the present invention provides a method for simulating a semi-physical simulation test of a ship system, the method comprising the following steps:

[0056] S1, start the simulation test platform, identify the test equipment connected to the signal switching module of the simulation test platform, and determine the simulation model to be imported according to the connected test equipment and the test equipment list, wherein the test equipment list includes all the test equipment identifiers to be tested; it should be noted that the simulation test platform of the present invention can be as follows Figure 2The structure of the simulation platform for ship system simulation test shown. In the present invention, the switching function between the test environment based on the test equipment and the simulation environment based on the simulation model is mainly realized by the signal switching module, and the switching between the simulation signal and the real sensor signal is controlled by software or model. Exemplarily, the signal switching module includes CAN signal switching, analog signal switching, digital DI / O signal switching and signal switching lower computer software, which can realize the remote automatic switching of the channel hard wire of 12 CAN signals, the remote automatic switching of the channel hard wire of 32 analog signals, and the remote automatic switching of the channel hard wire of 64 digital DI / O signals. The switching function of the signal switching module / unit can be realized by relays. The analog signal, CAN signal, and digital DI / O signal are all two-wire signals. At least two relays are required to switch such signals. Preferably, one double-pole double-throw relay is selected, and the two relays can be operated simultaneously during switching. Preferably, the simulation model of the present invention is used to realize the function of the corresponding test equipment in a virtual way, so as to realize the simulation test of the test equipment in advance when the test equipment is not present, so as to ensure the integrity and comprehensive progress of the platform test; further, the test equipment of the present invention and its corresponding simulation model can have multiple, and in the current test cycle or in all test cycles, the identification of all test equipment that may participate in the test constitutes a test equipment list; the test equipment list can be stored in the memory behind the simulation test platform. After starting the simulation test platform, the test equipment connected to the signal switching module of the simulation test platform can be identified by the simulation test platform or its connected signal switching module, for example, by sending a handshake signal for identification, which is not repeated here; then, the simulation model to be imported is determined according to the connected test equipment and the test equipment list. For example, the test equipment list includes a device identification list [A, B, C, D], and the device identification of the test equipment connected to the signal switching module of the simulation test platform is identified as B, D by the simulation test platform or its connected signal switching module. Then, all simulation models corresponding to the identification of the test equipment A, C except the identification of the connected test equipment (for example, simulation model identification a, c) are used as simulation models to be imported.

[0057] S2, import the simulation model to be imported into the simulation test platform, check the hardware system connection according to the connection relationship between the signal switching module and the test equipment, and configure the simulation environment; it should be noted that after the tester comprehensive software is started, the signal switching unit and the flexible wiring unit need to be controlled and managed in the system configuration management software to configure the system; after the system configuration is completed, run the simulation system host software, and configure the simulation environment through the human-computer interface, including building a simulation system environment, importing simulation models, adding signal drivers, adding data monitoring modules, and adding online parameter adjustment modules; after completing the simulation environment configuration, match the model-IO interface through the tester operation management software, add test cases, test processes, equipment status display, etc., and deploy the code to the simulation simulator, and control the operation process; after the system is running normally, the fault injection unit can be controlled by the fault injection software, and the test data is collected and filtered by the test data acquisition software, and transmitted to the system response analysis software for display. When the simulation system host computer software is running, the simulation environment is built through the human-machine interface, such as adding a simulation simulator, and a third-party simulation model is added through the model import module, that is, the simulation model to be imported is imported into the simulation test platform; then the corresponding IO signal driver module is added, and data monitoring and parameters that need to be adjusted in real time are added according to display and control needs, and displayed on the human-machine interface. In addition, when the system configuration management software is running, the control system is connected to the real device or simulation system in the signal switching module according to the test requirements. After the switching is completed, the hardware system connection is checked. If the hardware system connection needs to be configured, the flexible wiring module is run to flexibly configure the connection between the control system and the actuator.

[0058] S3, import the test case into the simulation test platform, and collect the test result data of the simulation test platform in real time; it should be noted that the present invention realizes the import of test cases and other functions through the tester operation management software, and the tester operation management software is mainly used to realize the tester static interface logic matching, multiple sets of tester operation timing verification, test case editing and design functions, tester test process management functions, tester operation key parameter display functions, tester equipment status monitoring functions and inter-system communication protocol customization functions. In addition, the real-time collection of the test result data of the simulation test platform can be realized by data acquisition software, and can also be realized by the functional module of test data bypass collection, which is not limited here.

[0059] S4, extracting two groups of test result data from the test result data according to the connection relationship, and performing data alignment, data matching and data analysis on the two groups of test result data to optimize and adjust the parameters of the simulation model, wherein the two groups of test result data correspond to the connection state of the signal switching module for any one of the test devices and the import state of its simulation model. It should be noted that the present invention uses the control variable method to achieve the comparison of two groups of test data to determine the accuracy of the simulation model parameters. For example, the test scenario where the two groups of test data to be compared are located is that the connection method between other test equipment and their corresponding simulation models and the simulation test platform remains unchanged. For example, the current test scenario is that test equipment B and D are connected to the simulation test platform. Obviously, the simulation models corresponding to test equipment B and D have not been imported into the simulation test platform at this time, and test equipment C is not connected to the simulation test platform. Obviously, the simulation model c corresponding to test equipment C has been imported into the simulation test platform at this time; in the current test scenario, the two groups of test result data consisting of the first group of test result data collected when test equipment A is connected to the simulation test platform and the second group of test result data collected when test equipment A is not connected to the simulation test platform and the simulation model corresponding to test equipment A has been imported into the simulation test platform are used as objects of comparison and verification, so as to ensure the accuracy of the verification results.

[0060] As a possible implementation manner, the determining the simulation model to be imported according to the connected test equipment and the test equipment list further includes:

[0061] The simulation test platform obtains a first identification set of all test equipment connected to the signal switching module, matches the first identification set with the test equipment list to obtain a second identification set of test equipment that is not connected to the signal switching module among all test equipment to be tested, and uses the simulation model corresponding to the test equipment corresponding to the second identification set as the simulation model to be imported. For example, the test equipment list consisting of all test equipment to be tested in the current test cycle includes a device identification list [A, B, C, D]. The device identifications of the test equipment connected to the signal switching module of the simulation test platform are identified as A and C by the simulation test platform or the signal switching module connected to it, that is, the first identification set is [A, C]. Then, the first identification set [A, C] is matched with the test equipment list [A, B, C, D] to obtain a second identification set of test equipment that is not connected to the signal switching module among all test equipment to be tested, that is, [B, D]. The simulation model corresponding to the test equipment B and D corresponding to the second identification set [B, D] is used as the simulation model to be imported, thereby realizing the identification of the test equipment and the import of the simulation model.

[0062] As a possible implementation manner, checking the hardware system connection according to the connection relationship between the signal switching module and the test equipment further includes:

[0063] According to the connection relationship between the signal switching module and the test equipment, the hardware system connection is checked to determine whether the hardware system connection needs to be configured; if so, the flexible wiring module is run to flexibly configure the connection between the control system and the actuator. It should be noted that the present invention realizes the flexible configuration of the connection between the control system and the actuator by controlling the flexible wiring unit.

[0064] As a possible implementation manner, extracting two groups of test result data from the test result data according to the connection relationship specifically includes:

[0065] The test result data of any one of the test devices and the simulation test platform being in a connected state for a preset time period is taken as the first group of test result data, and the test result data of the test device and the simulation test platform being in a disconnected state for the preset time period is taken as the second group of test result data, wherein the simulation test platform has imported the simulation model corresponding to the test device within the preset time period when the test device and the simulation test platform are in a disconnected state, and the connection status of other test devices and the simulation test platform and the import status of other simulation models of the simulation test platform remain unchanged within the preset time period. It should be noted that the present invention realizes the periodic comparison of two sets of test data by combining the control variable method with the test periodicity to further improve the accuracy of the simulation model parameters. For example, the test scene where the two sets of test data to be compared are located is that the connection mode between other test equipment and their corresponding simulation models and the simulation test platform remains unchanged. For example, the current test scene is that the test equipment B and D are connected to the simulation test platform. Obviously, the simulation models corresponding to the test equipment B and D are not imported into the simulation test platform at this time, and the test equipment C is not connected to the simulation test platform. Obviously, the simulation model corresponding to the test equipment C has been imported into the simulation test platform at this time; in the current test scene, the preset time length (for example The test result data within one or more test sub-cycles) is taken as the first group of test data, the test sub-cycle is a sub-cycle in the test cycle required to complete all test equipment, and the test of one of the test equipment or its corresponding simulation model is completed through one or more of the test sub-cycles, and the first group of test result data of the test sub-cycle M is collected when the test equipment A is in a connected state with the simulation test platform, and the second group of test result data of the test sub-cycle N is collected when the test equipment A is not connected to the simulation test platform but the simulation model corresponding to the test equipment A has been imported into the simulation test platform. The two groups of test result data are used as objects of comparison and verification, so as to ensure the accuracy of the verification result. Among them, the test sub-cycle M and the test sub-cycle N can not only have the same time length, but also have the same signal periodicity properties, for example, the start time and end time of the cycle, the hardware environment and software environment where the cycle is located, wherein the software environment refers to the same software type and version of the test.

[0066] As a possible implementation manner, extracting two groups of test result data from the test result data according to the connection relationship specifically includes:

[0067] According to the time step of sampling of each simulation model imported by the simulation test platform and its corresponding test equipment, a timestamp is added to the test result data collected at each sampling point; it should be noted that, in order to improve the accuracy of test data comparison, the present invention also considers the time step of sampling, that is, the time frequency of sampling data acquisition, on the basis of considering the periodicity of sampling, and adds a timestamp to the test result data collected at each sampling point; thus, according to the time step of sampling of each simulation model imported by the simulation test platform and its corresponding test equipment, a timestamp is added to the test result data collected at each sampling point, so that the sampling data of each sampling point is identified by the timestamp to achieve point-to-point comparison of the sampling data. In order to improve the efficiency and utilization of data sampling, preferably, the present invention can use the shortest time step in the sampling step of all test equipment and its simulation model, that is, the maximum sampling frequency to perform sampling across multiple sub-periods including all sampling periods, that is, the sampling frequency is the highest, and the sampling duration is the sampling duration covering all sub-periods and the entire test period to perform sampling of test data, so that there is no need to consider the different sampling steps of different test equipment and its simulation model and adjust the sampling frequency in different sub-periods respectively, thereby improving the convenience and efficiency of data sampling.

[0068] When the test equipment and the simulation test platform are in a connected state, the sampling point data with the preset time stamp is extracted according to the time step as the first group of test result data of the test equipment; it should be noted that in order to meet the different requirements of different test equipment and its simulation model for the sampling step of test data, that is, the sampling frequency, the present invention extracts the sampling data that meets the sampling step, that is, the sampling frequency of the current test equipment and its simulation model from the test data with the highest sampling frequency and the sampling time covering all sub-cycles and the entire test cycle, and compares them. Specifically, when the test equipment and the simulation test platform are in a connected state, the sampling point data with the preset time stamp is extracted according to the time step as the first group of test result data of any current test equipment to be detected. Similarly, when the simulation test platform has imported the simulation model corresponding to the test equipment, the sampling point data with the preset time stamp is extracted according to the time step as the second group of test result data corresponding to any current simulation model to be detected, wherein the current simulation model corresponds to the test equipment. Therefore, the test data with the highest sampling frequency and the sampling time covering all sub-cycles and the entire test cycle is used as the source data of the sampling data acquired by all the equipment to be tested and their simulation models, so that the sampling data of the corresponding sampling period and sampling frequency are extracted according to actual needs as the first group of test result data and the second group of test result data, respectively, thereby avoiding the inconvenience caused by repeatedly adjusting the sampling period and sampling frequency to meet the test requirements of different test equipment and their simulation models, and improving the efficiency of acquiring sampling data.

[0069] As a possible implementation, data alignment and data matching are performed on the two groups of test result data, specifically including:

[0070] Determine the start time and end time of the first group of test result data and the second group of test result data; it should be noted that, since the test process of the test platform may be periodic, for example, the test starts at 8 am during the day shift and ends at 8 pm, or the night shift test is conducted from 8 pm to 8 am. Obviously, although the test duration of the day shift test and the night shift test is the same, both are 12 hours, the servers occupied by the test platform in the night shift test state are often running under a lower load, while the servers occupied by the test platform in the day shift test state are often running under a higher load. These different load states occupying server hardware and software resources will cause differences in test performance and deviations in test result data. To this end, the present invention extracts the test data in order to eliminate the differences in test results caused by the load state of the above test platform. An alignment strategy is adopted. Specifically, it is necessary to first determine the start time and end time of the first group of test result data and the second group of test result data, that is, the time period range for sampling data extraction, and then, according to the time range of the first group of test result data and the second group of test result data, select the same time period for interception, for example, the intercepted data are all from 9 am to 12 pm, or from 12 pm to 3 am; finally, maintain the same time step and sampling frequency, so that the first group of test result data and the second group of test result data have the same time resolution, for example, the sampling frequency is 20 times within 1s, so that the sampling data is intercepted or extracted within the above time period to meet the periodicity requirements of the sampling data, avoid periodic deviations, and improve the sampling accuracy of the sampling data and the accuracy of the test results.

[0071] As a possible implementation manner, the preset duration is the duration of a sampling period, and further includes:

[0072] Acquire the first group of test result data and the second group of test result data of the preset time length; it should be noted that, in addition to the aforementioned periodic deviation, random deviation may also occur. For this reason, the sampling mean method of the present invention is used to acquire the sampling data. Specifically, calculate the mean of the test result data of any sampling point within the sampling period of all the first group of test result data of the current test equipment or its simulation model. For example, 3 groups of the first group of test result data are obtained, namely [a1, a2, a3...an], [b1, b2, b3...bn], and [c1, c2, c3...cn], and the mean of the test result data of any sampling point within the sampling period is calculated as [(a1+b1+c1) / 3, (a2+b2+c2) / 3, (a3+b3+ c3) / 3...(an+bn+cn) / 3], and the set of test result data of the sampling points with the smallest error to the mean value within the sampling period is taken as the first set of test result data. For example, b1 is the closest to (a1+b1+c1) / 3 among a1, b1, and c1. Similarly, a2 is the closest to (a2+b2+c2) / 3 among a2, b2, and c2. c3 is the closest to (a3+b3+c3) / 3 among a3, b3, and c3. cn is the closest to (an+bn+cn) / 3 among an, bn, and cn. The above-mentioned sampling data closest to the corresponding mean value is taken as the sampling data, and constitutes the first set of test result data, namely (b1, a2, c3...cn). Similarly, the mean of the test result data of all the second set of test result data of any sampling point within the sampling period is calculated, and the set of test result data of the sampling points with the smallest error to the mean value within the sampling period is taken as the second set of test result data.Specifically, the mean of the test result data of any sampling point in the sampling period of all the second groups of test result data of the current test device or its simulation model is calculated. For example, 4 groups of the second groups of test result data are obtained, namely [A1, A2, A3...An], [B1, B2, B3...Bn], [C1, C2, C3...Cn], and [D1, D2, D3...Dn], and the mean of the test result data of any sampling point in the sampling period is calculated as [(A1+B1+C1+D1) / 4, (A2+B2+C2+D2) / 4, (A3+B3+C3+D3 ) / 4...(An+Bn+Cn+Dn) / 4], and the set of test result data of the sampling points with the smallest error to the mean value within the sampling period is taken as the first set of test result data. For example, among A1, B1, C1, and D1, A1 is the closest to [(A1+B1+C1+D1) / 4. Similarly, among A2, B2, C2, and D2, D2 is the closest to (A2+B2+C2+D2) / 4. Among A3, B3, C3, and D3, C3 is the closest to (A3+B3+C3+D3) / 4. Among An, Bn, Cn, and Dn, Bn is the closest to (An+Bn+Cn+Dn) / 4. The above-mentioned sampling data closest to the corresponding mean value is taken as sampling data, and constitutes the second set of test result data, namely (A1, D2, C3...Bn). Thus, the first set of test result data (b1, a2, c3...cn) and the second set of test result data (A1, D2, C3...Bn) are used as two sets of test data to be compared, thereby avoiding the problem of low accuracy of test data comparison caused by random errors. In addition, the number of sets of the first set of test result data obtained can be the same as the number of sets of the second set of test result data obtained.

[0073] As a preferred implementation, optimizing and adjusting the parameters of the simulation model specifically includes:

[0074] Assume there are N sets, and initialize each set at time k = 0;

[0075] predict:

[0076] in, Identifies the state analysis value of the i-th set at time k, represents the predicted value of the state at time k+1, M k,k+1 represents the state change relationship from time k to time k+1, ω i,k Represents the model error, and its mean is 0. The covariance matrix is ​​Q k Normal distribution of

[0077] renew:

[0078]

[0079]

[0080]

[0081]

[0082]

[0083] in, is the state analysis value of the i-th set at time k+1, K k+1 is the gain matrix, is the observation matrix at time k+1, H k+1 is the observation operator at time k+1, v i,k is the observation error, and its mean is 0. The covariance matrix is ​​Q k Gaussian distribution, is the mean of all the analyzed values ​​of the set, is the mean of all predicted values ​​of the set, is the prediction error variance matrix, R k is the observation field error covariance matrix. The optimization and adjustment of the parameters of the simulation model is implemented by the control algorithm. The control algorithm model composed of the control algorithm can realize the automatic optimization calculation of the parameters of the simulation model, further improving the simulation efficiency, accuracy and prediction ability.

[0084] In some embodiments, the present invention provides a ship system semi-physical simulation test simulation system, combined with Figure 2The ship system simulation test simulation device and system schematic diagram shown are mainly composed of signal simulation facilities, flexible interface system and comprehensive simulation test operation environment. The signal simulation facility consists of the tester control and simulation simulator hardware facilities, signal conditioning unit, signal adaptation unit, comprehensive signal network and clock synchronization unit, which mainly realizes the real-time and IO interface drive of the signal simulation model, the conditioning of analog signals and DI / O signals, and the aggregation and distribution of signals. The flexible interface system consists of digital-analog signal switching and management system, fault simulation injection cabinet, test disconnection test equipment, and test data bypass acquisition unit, which mainly realizes the switching between the system test environment and the simulation environment, fault simulation injection, disconnection test, and test data bypass acquisition. The comprehensive test operation environment consists of the test control host, simulation model, tester comprehensive software, and test system data processing components. The control algorithm model in the simulation model runs on the local control device, the actuator simulation model in the simulation model runs in the real-time simulator, and the tester comprehensive software and test system data processing components run in each test control host. The simulation model is mainly used for the simulation and control of the actuators in the simulation system, including the actuator simulation model and the control algorithm model; the comprehensive software of the tester includes the system configuration management software, the simulation system host computer software, the fault injection host computer software, the data acquisition software, the system response data analysis software, and the tester operation management software; the test system data processing software is mainly used for comparative analysis of test data. When all the mode switching units are switched to one end of the signal simulation facility, this test simulation device and system support full digital simulation functions. The signal simulation facility runs the control station model, the local control model and the system model respectively. These models are uniformly controlled and managed through the comprehensive test operation environment. The signal simulation devices can be connected through Ethernet or through a real physical signal interface. When using a real physical interface connection, test data bypass collection, flexible wiring signal switching and fault injection testing through a fault injection unit can be performed.

[0085] The system includes the following modules: a signal simulation module for realizing simulation of actuators, signal conditioning, signal aggregation and distribution, signal exchange and clock synchronization functions; a flexible interface module for realizing switching between system test environment and simulation environment, fault simulation injection, line break test, and test data bypass collection functions; a test operation environment module for providing an operating environment for the test control host, simulation model, tester integrated software, and test system data; the ship system simulation test simulation system executes the ship system simulation test simulation method as described above.

[0086] In some embodiments, the present invention provides a ship system semi-physical simulation test simulation system, which specifically includes the following subsystems / units, specifically including signal simulation facilities, flexible interface systems, and comprehensive test operation environments. The ship system semi-physical simulation test simulation system is used to run the above-mentioned ship system semi-physical simulation test simulation method,

[0087] The specific implementation methods and methods are as follows:

[0088] 1. Signal simulation facilities: Signal simulation facilities mainly include tester control and simulation simulator hardware facilities, signal conditioning units, signal adaptation units, integrated signal network and clock synchronization units. Tester control and simulation simulator hardware facilities mainly realize the real-time and IO interface driving functions of signal simulation models, support online simulation verification of control software and system software in the model, support data acquisition and analysis software and various board drivers, support signal simulation project management, graphical establishment of signal simulation environment, signal simulation data generation, signal simulation case design and execution, protocol visualization configuration, signal data acquisition and analysis, data record generation and other functions. The signal conditioning unit is mainly a signal conditioning chassis, which has built-in analog quantity conditioning boards and digital quantity conditioning boards. The analog quantity conditioning board mainly realizes the functions of 4-20mA current conversion to voltage and voltage conversion to voltage. The digital quantity conditioning board mainly realizes the conditioning and isolation functions of digital quantity DIO, and realizes the conditioning function of 0-24V and TTL level conversion. The signal adaptation unit mainly realizes the wiring harness adaptation function of the aggregation and distribution of all ship product equipment signals. The integrated signal network and clock synchronization unit includes an integrated signal network and a clock synchronization unit, and mainly realizes signal exchange and clock synchronization functions.

[0089] 2. Flexible interface system: The flexible interface system is mainly composed of a signal switching unit, a fault injection unit, a test line break test device, and a bypass acquisition unit. It mainly realizes the functions of switching between the system test environment and the simulation environment, fault simulation injection, line break test, and test data bypass acquisition.

[0090] (1) Signal switching unit: The switching function between the test environment and the simulation environment is mainly realized by the signal switching unit, which controls the switching between the simulation signal and the real sensor signal through software or model control. The signal switching unit includes CAN signal switching, analog signal switching, digital DI / O signal switching and signal switching lower computer software, which can realize the hard-wired remote automatic switching of 12 CAN signal channels, the hard-wired remote automatic switching of 32 analog signal channels, and the hard-wired remote automatic switching of 64 digital DI / O signal channels. The switching function of the signal switching unit is planned to be realized by relays. The analog signal, CAN signal, and digital DI / O signal are all two-wire signals. At least two relays are required to switch such signals. In this scheme, a double-pole double-throw relay is selected, and the two relays can be operated simultaneously during switching.

[0091] (2) Fault injection unit: The fault injection unit can implement the fault injection function of the physical layer, electrical layer or protocol layer for analog signals, DI / O signals, CAN bus signals, RS422 / 485 signals through models or fault injection software. The fault injection unit consists of a fault injection control device and a fault injection box.

[0092] (3) Wire break test equipment: The rear panel of the wire break test equipment is equipped with input and output plugs. The input plug reorders the signal according to the fault-normal line sequence and is used to connect the fault injection unit. The output plug is used to connect the signal switching unit. The front panel of the wire break test equipment is a terminal block. The signal connection and disconnection are achieved by plugging and unplugging the terminal block. At the same time, the terminal block supports manual fault injection, such as voltage signal injection, current signal injection, etc.

[0093] (4) Bypass acquisition unit: The bypass acquisition unit is mainly used for bypass acquisition of sensor data. It consists of a signal separation box, a signal conditioning box, and a bypass acquisition industrial control computer. The bypass acquisition industrial control computer has built-in analog data acquisition equipment, DI / O data acquisition equipment, and CAN bus signal acquisition equipment. The signal separation box mainly realizes the isolation, distribution, and one-to-two functions of all signals. The signal separation box can isolate the input and output signals of the control device and convert the signals from one to two. One signal is transmitted to the bypass acquisition industrial control computer through the signal conditioning box, and the other signal enters the controlled device or simulation facility through the fault injection unit, disconnection test equipment, and signal switching unit.

[0094] 3. Comprehensive test operation environment: The comprehensive test operation environment consists of a test control host, a simulation model, a tester integrated software, and a test system data processing component. The control algorithm model in the simulation model runs on the local control device, the actuator simulation model in the simulation model runs in the real-time simulator, and the tester integrated software and test system data processing components run in each test control host. The simulation model, tester integrated software, and test system data processing component are customized and developed based on a mature framework. The simulation model is mainly used for the simulation and control of the actuator in the simulation system. The tester integrated software is mainly used for simulation system control and monitoring, system configuration management, fault injection equipment management, fault process configuration and monitoring, data collection, system response data analysis, operation management, etc. The test system data processing component is mainly used to provide a human-computer interaction interface for the system data center, including data management, data chart analysis, data statistics, report generation, report management, organizational structure management, role permissions, message reminders, and system log management, etc., and is used for comparative analysis of test data and simulation data.

[0095] (1) Simulation model: The simulation model is mainly used for the simulation and control of the actuator in the simulation system, including the actuator simulation model and the control algorithm model. The actuator simulation model runs in the real-time simulator, and the control algorithm model runs in the local control device.

[0096] ① Actuator simulation model: The actuator model is developed based on the hydraulic model library. The model library includes typical pump source models, actuator models, pressure control valve models, flow control valve models, reversing valve models, pipeline models, joint models, boundary models and hydraulic auxiliary device models, which can quickly perform auxiliary analysis such as design, improvement and optimization of the hydraulic system.

[0097] ② Control algorithm model: The control algorithm model is customized and developed based on each test condition. The control algorithm model runs in each local control device and is developed based on C language or Matlab / Simulink. The control algorithm model is compiled to generate an executable file, and the control algorithm model can be configured in each local control device through the simulation system host computer software. Figure 3 In the control algorithm model development process shown in the figure, the control station control algorithm converts the main control instructions from the tester integrated software into control instructions for each local control device through the control station control algorithm. After receiving the control instructions, each local control device converts them into logical instructions of the actuator through the control algorithm and outputs them, so as to control the actuators such as pumps, flow valves, and switch valves in the simulation simulator. After each actuator is actuated, the simulation simulator uploads the actuator status quantity, and the local control device control algorithm reads the feedback signals such as flow and pressure sent back by the simulation simulator, compares them with the control instructions, and controls until the control instructions are completed.

[0098] (2) Test system data processing component: The test system data processing component is mainly used for comparative analysis of test data and simulation data, and provides a human-computer interaction interface for the test system data processing center. The test system data processing component can achieve system troubleshooting and system optimization through data comparative analysis. The test data comparative analysis module supports reading stored information, and supports analysis and comparison of fault information, data, curve display, etc. In order to improve the model operation efficiency and intuitive comparison results, the data comparison is carried out in the test control host. The test control host selects the data source to be compared and compares it, and presents the comparison results to the user through the test system processing component. The process is as follows: Figure 4 The data comparison and analysis flow chart is shown in the figure. The data comparison method is based on the user's settings. The comparison data supports equal, greater than, less than, greater than or equal to, less than or equal to, within the range, and outside the range. The user can set the comparison method for each signal segment. After receiving the semi-physical signal data and simulation model data, the test management host automatically analyzes the data content and compares according to the user-set mode. The comparison results will be stored in a .txt file together with the source data.

[0099] Real-time comparative analysis of test-simulation data: In the process of virtual-real interaction, it is necessary to continuously compare the experimental data with the simulation data to achieve virtual-real control and real-real control. In the process of data comparison, the following steps need to be performed: Real-time comparative analysis steps:

[0100] The first step is data alignment: including time alignment. Time alignment refers to aligning the experimental data and simulation data in time so that they have the same time step and sampling frequency. The following are some specific methods and steps to achieve time alignment: First, realize timestamp synchronization. By adding timestamps in experiments and simulations, the experimental data and simulation data have the same starting point and step. The timestamp can be generated by the clock of the computer system, and the clock of the experimental and simulation systems can be synchronized. The specific steps are as follows: Add a timestamp to each data sampling point. The timestamp can be generated by the clock of the computer system. During the simulation process, according to the time step of the simulation model, add a timestamp to each simulation data point. Match and align the timestamps of the experimental data and simulation data so that they have the same time step and sampling frequency. Secondly, realize time interpolation. If there is a difference in the time step of the experimental data and simulation data, the interpolation method can be used to adjust the data. Interpolation methods include linear interpolation, polynomial interpolation, spline interpolation, etc. Interpolation can make the experimental data and simulation data have the same time step. The specific steps are as follows: According to the sampling frequency and time step of the experimental data, calculate the time point that needs to be interpolated; use the interpolation method to calculate the data value of the interpolation point according to the known time points and corresponding data values ​​of the experimental data; align the data value of the interpolation point with the simulation data so that the two have the same time step and sampling frequency; time interception: if there is a difference in the time range of the experimental data and the simulation data, you can intercept the time period for comparative analysis. Ensure that the time range of the experimental data and the simulation data is consistent in order to perform accurate comparative analysis. The specific steps are as follows: determine the start and end time of the experimental data and the simulation data; select the same time period for interception according to the time range of the experimental data and the simulation data; keep the same time step and sampling frequency so that the experimental data and the simulation data have the same time resolution.

[0101] The second step is data matching. Data matching refers to matching data based on the common features of experimental data and simulation data, such as state variables, input and output signals, etc., to ensure the consistency of data for comparative analysis. The following methods can be used for data matching: 1. Feature extraction: Extract relevant features from experimental data and simulation data. By extracting the same features, experimental data and simulation data can be matched. The specific steps are as follows: Through signal processing methods, perform preprocessing operations such as filtering and denoising on experimental data and simulation data. Extract the features of experimental data and simulation data, including peak values, spectrum distribution, envelope curves, etc. Compare features and match data according to standards such as similarity or thresholds. 2. Data pattern matching: Match data by comparing the data patterns of experimental data and simulation data, including periodic trends, noise characteristics, etc. One or more methods such as autocorrelation function, correlation coefficient, spectrum analysis, etc. can be used for data pattern matching. The specific steps are as follows: Based on the pattern features of experimental data and simulation data, such as period, trend, noise, etc., calculate relevant statistics or frequency domain analysis indicators. Compare the statistics of experimental data and simulation data, such as correlation coefficient, spectrum characteristics, etc., to judge the similarity between data. Based on criteria such as similarity or threshold, determine whether the experimental data and simulation data match. 3. Data alignment algorithm: Use data alignment algorithm to achieve the matching of experimental data and simulation data. Algorithms include dynamic time warping (DTW), least squares fitting, etc., which can find the best data match through optimization algorithms. The specific steps are as follows: Based on the characteristics of experimental data and simulation data, such as waveform shape, frequency distribution, etc., calculate the similarity index. Use data alignment algorithm, such as dynamic time warping (DTW), to find the best data match through optimization algorithm.

[0102] The third step is statistical analysis and evaluation: including statistical indicators. Statistical indicators are used to evaluate the consistency and similarity between experimental data and simulation data. Statistical indicators include mean, variance, standard deviation, correlation coefficient, etc. By calculating these statistical indicators, the degree of difference between experimental data and simulation data can be quantified, and the accuracy and reliability of the model can be further evaluated. Error analysis is the process of comparing the errors of experimental data and simulation data, analyzing the sources of errors and influencing factors. By analyzing the errors, the deficiencies of the model can be found, and the model can be improved and optimized. Error analysis methods include root mean square error (RMSE), mean absolute error (MAE), residual analysis, etc. Confidence interval analysis is a method of evaluating the accuracy and confidence of a simulation model by calculating confidence intervals. The confidence interval is a quantitative description of the uncertainty of model parameters or prediction results. By calculating the confidence interval, the upper and lower bounds of the model parameters or prediction results can be obtained, thereby evaluating the reliability of the model.

[0103] The fourth step is optimization and adjustment. First, adjust the model parameters. In the process of comparative analysis, if it is found that there are large differences between the experimental data and the simulation data, it is possible to consider adjusting the parameters of the simulation model. By adjusting the model parameters, the accuracy and predictive ability of the model can be improved. The method for adjusting the model parameters can be selected according to the specific simulation model and data characteristics, and the method includes the least square method, genetic algorithm, particle swarm optimization algorithm, etc. Secondly, error correction is performed. In the comparative analysis, if it is found that there are systematic errors or deviations between the experimental data and the simulation data, it is possible to consider correcting the model. By adjusting the structure and algorithm of the model, the errors and deviations in the model can be corrected, and the fit between the model and the actual system can be improved. The correction method includes the correction coefficient method, the correction factor method, the model structure adjustment, etc. The specific optimization and adjustment algorithm is as follows: based on the Kalman filter algorithm, combined with the ensemble forecast, the problem of difficult estimation and forecasting of the background error solution equation matrix in practical applications is solved, and it can be used for data assimilation of nonlinear systems. The specific method of optimizing and adjusting the parameters of the simulation model is as described in the above embodiment, and will not be repeated here.

[0104] (3) Tester integrated software: The tester integrated software includes system configuration management software, simulation system host computer software, fault injection host computer software, data acquisition software, system response data analysis software, and tester operation management software. The tester integrated software is mainly used for system configuration management, simulation system control and monitoring, operation management, fault injection equipment management and fault process configuration and monitoring, data acquisition, system response data analysis, etc.

[0105] ①Tester integrated software operation process: Figure 5 As shown, before the tester comprehensive software is run, the simulation model needs to be compiled to generate executable code, and the system configuration management software in the tester comprehensive software is opened to control and manage the signal switching unit and the flexible wiring unit, and configure the system; after the system configuration is completed, the simulation system host software is run, and the simulation environment is configured through the human-computer interface, including building a simulation system environment, importing simulation models, adding signal drivers, adding data monitoring modules, and adding online parameter adjustment modules; after completing the simulation environment configuration, the model-IO interface is matched through the tester operation management software, test cases, test processes, equipment status displays, etc. are added, and the code is deployed to the simulation simulator, and the operation process is controlled; after the system is running normally, the fault injection unit can be controlled by the fault injection software, and the test data is collected and filtered by the test data acquisition software, and transmitted to the system response analysis software for display or analyzed by the experimental system data processing component.

[0106] ②System configuration management software: such as Figure 7The system configuration software operation process shown in the figure is that the system configuration management software mainly manages the signal switching unit and the flexible wiring unit in the flexible interface system in a unified manner. The system configuration management software realizes the switching between the control system and the simulation system, and the control system and the real device by controlling the signal switching unit; and realizes the flexible configuration of the connection between the control system and the actuator by controlling the flexible wiring unit. The signal switching module of the system configuration management software sends the signal switching command and transmits it to the signal switching unit through TCP / IP. After receiving the command, the relay in the signal switching unit starts the action to realize the switching of the signal between the control system and the simulation system, and the control system and the real device. When the system configuration management software is running, the control system is connected to the real device or simulation system in the signal switching module according to the test requirements. After the switching is completed, the hardware system connection is checked. If the hardware system connection needs to be configured, the flexible wiring module is run to flexibly configure the connection between the control system and the actuator. The system configuration management software supports saving the configuration information as a configuration file, and can also load the existing configuration file to realize the fast loading of hardware information for software simulation calls.

[0107] ③Simulation system host computer software: such as Figure 8 As shown in the figure, the host computer software of the simulation system is the core of the comprehensive software development and management of the tester. It can control and manage large and complex semi-physical test systems and control the distributed computing of model codes. The host computer software of the simulation system has an interactive interface, which displays all the required functions of the comprehensive test operation environment, realizes configuration and management functions, and interacts with the operation data. When the host computer software of the simulation system is running, the simulation environment is built through the human-machine interface, such as adding simulation simulators, etc., and third-party simulation models are added through the model import module, and the corresponding IO signal driver module is added. According to the display and control needs, data monitoring and parameters that need to be adjusted in real time are added, and displayed on the human-machine interface.

[0108] ④Tester operation management software: such as Fig. 9 As shown, the tester operation management software is mainly used to realize the tester static interface logic matching, multiple tester operation timing verification, test case editing and design functions, tester test process management functions, tester operation key parameter display functions, tester equipment status monitoring functions and inter-system communication protocol customization functions. The tester operation management software supports the customization of communication protocols and multiple tester operation timing verification. Through static interface logic matching, the model interface is associated with the IO channel or communication protocol interface to form test cases, add test processes, design test steps and logic, add equipment status monitoring and key parameter display, and download the entire project. The process control module controls the main processes of the model such as start, pause, run and reset, and displays and monitors the equipment status monitoring and key parameters.

[0109] ⑤Fault injection into host computer software: Fig.10 As shown in the figure, the fault injection host computer software has the unified management function of fault injection equipment, and can configure the fault process and monitor the fault information. The fault injection host computer software includes physical layer and electrical layer fault injection, protocol layer fault injection, and model function fault injection. When the fault injection host computer software is running, the fault injection type is selected through the button, the corresponding fault injection page is opened, the channel that needs fault injection is selected for fault injection, and the fault status is monitored.

[0110] As another embodiment, the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the ship system simulation test method as described above when executing the program.

[0111] It will be appreciated by those skilled in the art that the present invention includes devices for performing one or more of the operations described in the present application. These devices may be specially designed and manufactured for the desired purpose, or may include known devices in general-purpose computers. These devices have computer programs stored therein, which are selectively activated or reconstructed. Such computer programs may be stored in a device (e.g., computer) readable medium or in any type of medium suitable for storing electronic instructions and coupled to a bus, respectively, the computer readable medium including but not limited to any type of disk (including floppy disk, hard disk, optical disk, CD-ROM, and magneto-optical disk), ROM (Read-Only Memory), RAM (Random Access Memory), EPROM (Erasable Programmable Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory), flash memory, magnetic card. That is, the readable medium includes any medium that stores or transmits information in a readable form by a device (e.g., computer).

[0112] Those skilled in the art will appreciate that each block in these structure diagrams and / or block diagrams and / or flow charts and combinations of blocks in these structure diagrams and / or block diagrams and / or flow charts can be implemented using computer program instructions. Those skilled in the art will appreciate that these computer program instructions can be provided to a general-purpose computer, a professional computer, or a processor of other programmable data processing methods to implement, thereby executing the scheme specified in the block or multiple blocks of the structure diagram and / or block diagram and / or flow chart disclosed in the present invention through the processor of the computer or other programmable data processing method.

[0113] Those skilled in the art will appreciate that the various operations, methods, steps, measures, and schemes discussed in the present invention may be alternated, modified, combined, or deleted. Further, other steps, measures, and schemes in the various operations, methods, and schemes discussed in the present invention may also be alternated, modified, rearranged, decomposed, combined, or deleted. Further, the steps, measures, and schemes in the prior art that are similar to those disclosed in the present invention may also be alternated, modified, rearranged, decomposed, combined, or deleted.

[0114] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for semi-physical simulation test of a ship system, characterized in that: The method comprises the following steps: S1, starting a simulation test platform, identifying a test device connected to a signal switching module of the simulation test platform, and determining a simulation model to be imported according to the connected test device and a test device list, wherein the test device list includes identifiers of all test devices to be tested; S2, importing the simulation model to be imported into the simulation test platform, checking the hardware system connection according to the connection relationship between the signal switching module and the test equipment, and configuring the simulation environment; S3, importing the test case into the simulation test platform, and collecting data from the simulation test platform in real time as test result data; S4, extracting two groups of test result data from the test result data according to the connection relationship, and performing data alignment, data matching and data analysis on the two groups of test result data to optimize and adjust the parameters of the simulation model, wherein the two groups of test result data correspond to the connection state of the signal switching module for any one of the test devices and the import state of its simulation model; Extracting two groups of test result data from the test result data according to the connection relationship specifically includes: The test result data of any one of the test devices being in a connected state with the simulation test platform for a preset time period is taken as the first group of test result data, and the test result data of the test device being in a disconnected state with the simulation test platform for the preset time period is taken as the second group of test result data, wherein the simulation test platform has imported the simulation model corresponding to the test device within the preset time period when the test device and the simulation test platform are in a disconnected state, and the connection status of other test devices with the simulation test platform and the import status of other simulation models of the simulation test platform remain unchanged within the preset time period; Extracting two groups of test result data from the test result data according to the connection relationship specifically includes: According to each simulation model imported by the simulation test platform and the time step of the corresponding test equipment sampling, a timestamp is added to the test result data collected at each sampling point; When the test device and the simulation test platform are connected, sampling point data with timestamps added of the preset time length is extracted according to the time step as a first set of test result data of the test device; In a state where the simulation model corresponding to the test equipment has been imported into the simulation test platform, sampling point data with timestamps added of the preset time length is extracted according to the time step as a second set of test result data corresponding to the simulation model; Optimizing and adjusting the parameters of the simulation model specifically includes: Assume there are N sets, and initialize each set at time k = 0; predict: in, Identifies the state analysis value of the i-th set at time k, represents the predicted value of the state at time k+1, M k,k+1 represents the state change relationship from time k to time k+1, ω i,k Represents the model error, and its mean is 0. The covariance matrix is ​​Q k Normal distribution of renew: in, is the state analysis value of the i-th set at time k+1, K k+1 is the gain matrix, is the observation matrix at time k+1, H k+1 is the observation operator at time k+1, v i,k is the observation error, and its mean is 0. The covariance matrix is ​​Q k Gaussian distribution, is the mean of all the analyzed values ​​of the set, is the mean of all the predicted values ​​of the set, is the prediction error variance matrix, R k is the observation field error covariance matrix.

2. The method according to claim 1, characterized in that: The step of determining the simulation model to be imported according to the connected test equipment and the test equipment list further includes: The simulation test platform obtains a first identification set of all test equipment connected to the signal switching module, matches the first identification set with the test equipment list to obtain a second identification set of the test equipment that is not connected to the signal switching module among all the test equipment to be tested, and uses the simulation model corresponding to the test equipment corresponding to the second identification set as the simulation model to be imported.

3. The method according to claim 2, characterized in that Checking the hardware system connection according to the connection relationship between the signal switching module and the test equipment also includes: The hardware system connection is checked according to the connection relationship between the signal switching module and the test equipment to determine whether the hardware system connection needs to be configured; if so, the flexible wiring module is run to flexibly configure the connection between the control system and the actuator.

4. The method according to claim 1, characterized in that: The two groups of test result data are aligned and matched, specifically including: Determine the start time and end time of the first group of test result data and the second group of test result data; According to the time range of the first group of test result data and the second group of test result data, selecting the same time period for interception; The same time step and sampling frequency are maintained so that the first group of test result data and the second group of test result data have the same time resolution.

5. The method according to claim 1, characterized in that The preset duration is the duration of a sampling period, and also includes: Acquire the first set of test result data and the second set of test result data of the preset time period; Calculate the mean of all the test result data of any sampling point in the sampling period of the first group of test result data, and take the set of test result data of the sampling point with the smallest error with the mean in the sampling period as the first group of test result data; Calculate the mean of all the test result data of any sampling point in the sampling period of the second set of test result data, and take the set of test result data of the sampling point with the smallest error with the mean in the sampling period as the second set of test result data.

6. A ship system semi-physical simulation test system, characterized in that: The system includes the following modules: Signal simulation module for implementing actuator simulation, signal conditioning, signal aggregation and distribution, signal exchange and clock synchronization functions; Flexible interface module for switching between system test environment and simulation environment, fault simulation injection, disconnection test, and test data bypass collection; A test operation environment module for providing an operation environment for the test control host, simulation model, tester integrated software, and test system data; The ship system simulation test simulation system executes a ship system semi-physical simulation test simulation method as described in any one of claims 1-5.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the method according to any one of claims 1 to 5 is implemented.

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