Intelligent management system and method of simulation model based on multi-source data fusion

Abstract

The present invention relates to the technical field of multi-data fusion model management. Specifically, it is a simulation model intelligent management system and method based on multi-source data fusion, the system includes a data acquisition module, a data analysis module, a model supervision module and an alarm reminder module; the data acquisition module is to collect data information of the protection vehicle, local impact simulation data and historical impact data sets under actual impact scenarios; the data analysis module is to analyze the impact simulation data of the protection vehicle and the impact value between the impact resistance of different areas of the protection vehicle and the local impact simulation; the model supervision module is to analyze the overall impact resistance score of the protection vehicle and the score accuracy; the alarm reminder module is to issue an alarm reminder when the accuracy of the overall impact resistance score of the protection vehicle is lower than the preset accurate threshold. The present invention analyzes the impact simulation data of the local area and other areas, and quickly obtains the impact resistance and safety of the vehicle in different impact scenarios under limited resources.

Description

Technical Field

[0001] The present invention relates to the technical field of multi-data fusion model management, and in particular to a simulation model intelligent management system and method based on multi-source data fusion. Background Art

[0002] Multi-data fusion technology, also known as data fusion, is based on the principle of integrating data and information from different sensors, different sources, different formats, and different representations to obtain more comprehensive, accurate, and reliable information. Data fusion technology has been widely used in many fields, including multi-source image compounding, robotics and intelligent instrument systems, image analysis and understanding, target detection and tracking, automatic target recognition, etc. Multi-data fusion technology plays a vital role in the impact simulation of protective vehicles. First of all, the impact simulation of protective vehicles is a complex and critical process, which involves the performance and safety evaluation of vehicles under various extreme conditions. In order to more accurately simulate and evaluate the impact performance of protective vehicles, it is necessary to obtain and process a large amount of data, including vehicle structural data, material data, impact load data, occupant biomechanical data, etc. These data come from a wide range of sources and in various forms, including both measured data and simulated data, both static data and dynamic data. Therefore, how to effectively fuse these multi-source heterogeneous data is an important issue in the impact simulation technology of protective vehicles.

[0003] Under existing technologies, comprehensive impact simulation of protective vehicles consumes a lot of computing resources and time, which may result in high costs. Different areas of the vehicle usually have certain dependencies and correlations in design and performance, so it is difficult to gain an in-depth understanding of the impact resistance of local areas of the vehicle during comprehensive impact simulation, which is not conducive to discovering potential design defects or improvement points. Summary of the invention

[0004] The purpose of the present invention is to provide a simulation model intelligent management system and method based on multi-source data fusion to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solution: a simulation model intelligent management method based on multi-source data fusion, the simulation model intelligent management method specifically comprises the following steps:

[0006] S100, extracting data information of the protection vehicle from an existing database, constructing a model using an appropriate modeling tool based on the data information of the protection vehicle, performing local impact simulation based on the constructed frame model, and extracting local impact simulation data from the simulation model;

[0007] S200, extracting historical impact simulation data that is most similar to the data information of the protection vehicle through the simulation database, and analyzing the impact simulation data of different areas of the protection vehicle by combining the historical impact simulation data with the local impact simulation data and the data information of the protection vehicle; the impact simulation data includes key indicators such as deformation, stress distribution, and energy absorption of the frame model under impact, and the impact resistance of the protection vehicle can be directly evaluated based on these indicators;

[0008] S300. Since the simulation is performed based on different areas of the protection vehicle during the impact simulation process, it is impossible for the protection vehicle to be subjected to only one fixed area or one type of impact in actual situations. Therefore, it is necessary to analyze the overall impact resistance score of the protection vehicle based on the impact simulation data of different areas of the protection vehicle. It is very important to analyze the impact resistance of the protection vehicle because one of the main design goals of the protection vehicle is to ensure that personnel injury and equipment damage can be minimized in the event of a collision or accidental impact. This ability is directly related to the safety protection performance of the protection vehicle and is the key to whether it can effectively protect workers and equipment in various potentially dangerous environments. For example, during road construction and traffic maintenance, the protection vehicle can provide important safety protection, reduce accidental risks, and improve work efficiency. For example, anti-collision buffer vehicles can be used to improve safety and efficiency in road construction and traffic maintenance; in emergency situations, such as traffic accidents or natural disasters, the protection vehicle can quickly arrive at the scene to provide necessary protection and support for rescue personnel and equipment. For example, the safety anti-collision equipment rescue protection vehicle can provide various tools and equipment required for rescue work and provide effective safety guarantees on site; in some engineering projects that require special protection, such as nuclear power plant construction and bridge construction, the protection vehicle can also play an important role. They can provide additional safety protection to ensure that engineering projects can proceed smoothly.

[0009] S400: Evaluate the accuracy of the overall impact resistance performance score of the protection vehicle based on the historical impact data set and the set impact scenario parameter set, and issue an early warning when the accuracy of the overall impact resistance performance score of the protection vehicle is lower than a preset accuracy threshold.

[0010] Furthermore, the specific method of performing local impact simulation on the workshop model and extracting local impact simulation data therefrom in S100 is as follows:

[0011] S101. Extract data information of the protection vehicle from the existing database and generate a set Sj, S={Sj1, Sj2, Sj3...Sij...SIj}, where Sji represents the i-th data information of the j-th area of ​​the protection vehicle, j=1, 2, 3...J, J represents the number of areas into which the protection vehicle is divided, i=1, 2, 3...I, I represents the amount of data information of the protection vehicle, and construct a model using appropriate modeling tools based on the data information of the protection vehicle, where the data information of the protection vehicle includes detailed modeling of main parts such as the vehicle body, tires, and frame, as well as any additional components or systems that may affect the impact response; simulate the impact scenario It is proposed to define and set the impact scene parameters as sets Z, V, and C, Z={Z1, Z2, Z3...Za...ZA}, V={V1, V2, V3...Va...VA}, and C={C1, C2, C3...Ca...CA}; where Z, V, and C represent different impact types, Za represents the ath impact scene parameter under the Z type impact, Va represents the ath impact scene parameter under the V type impact, and Ca represents the ath impact scene parameter under the C type impact; a=1, 2, 3...A, where A represents the number of impact scene parameters, and the impact scene parameters include impact speed, impact angle, and impact intensity, etc.;

[0012] S102. Perform local impact simulation on the constructed frame model through simulation software. It is very important to accurately set the material properties of each component in the model, because these properties will directly affect the behavior of the model in the simulation. During the simulation, the frame model will be affected by the defined impact scenario and produce corresponding responses. The simulation software, i.e., the simulation model, will record these response data. Therefore, local impact simulation data is extracted from the simulation model. The sets generated based on the local impact simulation data are pj'z, pj'c, pj'v, j'∈{1, 2, 3...J}, respectively. The local impact simulation is to perform impact simulation on any area of ​​the frame model. Among them, pj'z, pj'c, pj 'v represents the local simulation data set under different types of impact, pj'z={pj'z1, pj'z2, pj'z3...pj'ze...pj'zE}, pj'c={pj'c1, pj'c2, pj'c3...pj'ce...pj'cE}, pj'v={pj'v1, pj'v2, pj'v3...pj've...pj'vE}, e=1, 2, 3...E, E represents the amount of local simulation data, where the impact simulation data includes key indicators such as deformation, stress distribution, and energy absorption of the frame model under impact. According to these indicators, the impact resistance of the protective vehicle can be directly evaluated.

[0013] Furthermore, the specific method of analyzing the impact simulation data of different areas of the protection vehicle in S200 is as follows:

[0014] S201. Extract the historical vehicle data information set Un from the existing database, where Un represents the data information set of the nth historical vehicle in the existing database, n=1, 2, 3...N, and N represents the number of the extracted historical vehicle data information sets. Since the historical vehicle data information sets in the existing database correspond one-to-one to the historical impact simulation data in the simulation database, the similarity between the protection vehicle data information set and the historical vehicle data information set in the existing database is calculated based on the impact simulation comparison table: Un→{Pnz, Pnc, Pnv}, through the formula: ln=|Un∩S| / |Un∪S|, where ln represents the similarity between the protection vehicle data information set and the nth historical vehicle data information set in the existing database. The similarity of the historical vehicle data information set, the absolute value of the set is expressed as the number of subsets in the set, and the historical impact simulation data {Pn'z, Pn'c, Pn'v}, n'∈{1, 2, 3...N}, are selected according to the historical vehicle data information set with the highest similarity according to the impact simulation comparison table; wherein Pnz represents the impact simulation data set under the Z type impact corresponding to the data information set of the nth historical vehicle in the existing database, Pnc represents the impact simulation data set under the C type impact corresponding to the data information set of the nth historical vehicle in the existing database, and Pnv represents the impact simulation data set under the V type impact corresponding to the data information set of the nth historical vehicle in the existing database;

[0015] S202. Extract the impact resistance score yj'i corresponding to the data information of the protection vehicle for local impact simulation and the impact resistance score yji corresponding to the data information of each area of ​​the protection vehicle based on the data information of the protection vehicle, wherein yj'i represents the impact resistance score corresponding to the i-th data information of the j'th area of ​​the protection vehicle, and yji represents the impact resistance score corresponding to the i-th data information of the j-th area of ​​the protection vehicle; wherein the impact resistance score corresponding to the data information of the protection vehicle is represented by a specific numerical value, and the numerical value is judged based on the impact resistance obtained by the training model. When the material, thickness and strength of the protection vehicle in different areas are different, the corresponding impact resistance is also different; when the impact resistance is stronger, the numerical value of the corresponding data in different areas is higher; according to the formula: pjz=(∑I i=1yji / ∑I i=1yj'i)*pj'z, pjc=(∑I i=1yji / ∑I i=1yj'i)*pj'c, pjv=(∑I i=1yji / ∑I i=1yj'i)*pj'v, the impact simulation data sets of different areas of the protection vehicle under different types of impact simulation are calculated respectively, pjz represents the impact simulation data set of the jth area of ​​the protection vehicle under the Z type impact simulation, pjc represents the impact simulation data set of the jth area of ​​the protection vehicle under the C type impact simulation, and pjv represents the impact simulation data set of the jth area of ​​the protection vehicle under the V type impact simulation;

[0016] S203. Generate an impact simulation data set of the protection vehicle {Pz, Pc, Pv} based on the impact simulation data sets of different areas of the protection vehicle under different types of impact simulations, wherein Pz represents the impact simulation data set of the protection vehicle under Z type impact, Pz represents the impact simulation data set of the protection vehicle under C type impact, Pv represents the impact simulation data set of the protection vehicle under V type impact, Pz={p1z, p2z, p3z...pjz...pJz}, Pc={p1c, p2c, p3c...pjc...pJc}, Pv={p1v, p2v, p3v...pjv...pJv}.

[0017] Furthermore, the specific method of analyzing the overall impact resistance score of the protection vehicle based on the impact simulation data of different areas of the protection vehicle in S300 is as follows:

[0018] S301. According to the impact simulation data sets of different areas of the protection vehicle under different types of impact simulations, determine the correlation between different areas under local impact simulation: {pj'z, pj'c, pj'v}→{pjz, pjc, pjv}=Rj, where Rj represents the impact value of the jth area under local impact simulation. Since j'∈{1, 2, 3...J}, when j' and j values ​​coincide, {pj'z, pj'c, pj'v}→{pj'z, pj'c, pj'v} does not exist, that is, Rj'=0. , when the impact value is larger, it means that the impact resistance score of the area affected by the local impact simulation is smaller; the correlation relationship is the proportion of the deformation and stress distribution of any area under the impact simulation to other areas. When the area involved is larger, the impact value is larger, and the impact resistance of other areas will be reduced or unchanged accordingly due to the proportion of the deformation and stress distribution of any area under the impact simulation; when any area of ​​the protective vehicle is impacted, the deformation and stress distribution generated may affect the impact resistance of other areas of the protective vehicle;

[0019] S302, constructing an overall impact resistance performance analysis model according to the correlation between different regions under impact simulation and the impact resistance performance scores yji corresponding to the data information of each region of the protection vehicle:

[0020] Y=∑J j=1[(∑I i=1yji)*(1-Rj)]

[0021] The overall impact resistance score of the protection vehicle is calculated, where Y represents the overall impact resistance score of the protection vehicle.

[0022] Furthermore, the specific method for evaluating the accuracy of the overall impact resistance score of the protection vehicle in S400 is as follows: historical impact data sets under actual impact scenarios are obtained, namely Zh, Ch and Vh, where Zh, Ch and Vh represent historical impact data sets of Z, C and V type impacts under actual impact scenarios, respectively, through the formula:

[0023] lz=|Zh∩Z| / |Zh∪Z|, lc=|Ch∩C| / |Ch∪C|, lv=|Vh∩V| / |Vh∪V|

[0024] L=lz+lc+lv

[0025] The accuracy of the overall impact resistance performance score of the protection vehicle is calculated; where lz, lc and lv represent the similarity values ​​of the historical impact data set and the set impact scenario parameter set under Z, C and V type impacts respectively, and L represents the accuracy of the overall impact resistance performance score of the protection vehicle, L∈[0,3]; when the accuracy L of the overall impact resistance performance score of the protection vehicle is lower than the preset accuracy threshold L', an alarm is issued, and the overall impact resistance performance score of the protection vehicle is analyzed.

[0026] A simulation model intelligent management system based on multi-source data fusion, the simulation model intelligent management system includes a data acquisition module, a data analysis module, a model supervision module and an alarm reminder module; the output end of the data acquisition module is connected to the input end of the data analysis module, the output end of the data analysis module is connected to the input end of the model supervision module, and the output end of the model supervision module is connected to the input end of the alarm reminder module; the data acquisition module is used to collect data information of the protection vehicle, local impact simulation data and historical impact data sets under actual impact scenarios; the data analysis module is used to analyze the impact simulation data of the protection vehicle and the impact value between the impact resistance of different areas of the protection vehicle and the local impact simulation; the model supervision module analyzes the overall impact resistance performance score of the protection vehicle and the score accuracy; the alarm reminder module is used to issue an alarm reminder when the accuracy of the overall impact resistance performance score of the protection vehicle is lower than a preset accuracy threshold.

[0027] Furthermore, the data acquisition module includes a protection vehicle data information acquisition unit, a local impact simulation data acquisition unit and a historical impact data set acquisition unit; the protection vehicle data information acquisition unit extracts the data information of the protection vehicle from an existing database; the local impact simulation data acquisition unit performs local impact simulation on the constructed frame model through simulation software, and extracts local impact simulation data from the simulation model; the historical impact data set acquisition unit selects the historical impact simulation data corresponding to the historical vehicle data information set with the highest similarity based on the impact simulation comparison table.

[0028] Furthermore, the data analysis module includes an impact simulation data analysis unit and a regional impact influence value analysis unit; the impact simulation data analysis unit analyzes the impact simulation data sets of different regions of the protection vehicle under different types of impact simulations; the regional impact influence value analysis unit analyzes the influence value between the impact resistance of different regions of the protection vehicle and the local impact simulation.

[0029] Furthermore, the model supervision module includes an overall impact resistance performance score analysis unit and an overall impact resistance performance score accuracy analysis unit; the overall impact resistance performance score analysis unit is for the overall impact resistance performance score of the protection vehicle; the overall impact resistance performance score accuracy analysis unit is for judging the accuracy of the overall impact resistance performance score of the protection vehicle.

[0030] Furthermore, the warning reminder module includes a warning decision unit and an impact scenario parameter reset unit; the warning decision unit is to issue an alarm reminder when the accuracy of the overall impact resistance performance score of the protection vehicle is lower than a preset accuracy threshold; the impact scenario parameter reset unit is to reset the impact scenario parameters and re-simulate when the terminal receives the alarm reminder.

[0031] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: after performing impact simulation on a local area of ​​the protected vehicle, the present invention uses historical data information to analyze the simulation data of other areas, thereby saving computing costs and time; and different areas of the vehicle usually have certain dependencies and correlations in design and performance. Based on the analysis of the impact simulation data of the local area and the impact simulation data of other areas, potential problems in the vehicle design can be quickly identified and improved; and the impact resistance and safety of the vehicle in different impact scenarios can be quickly analyzed with limited resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0033] Figure 1 It is a structural schematic diagram of the simulation model intelligent management system based on multi-source data fusion of the present invention. DETAILED DESCRIPTION

[0034] 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.

[0035] See also Figure 1 The present invention provides a technical solution: a simulation model intelligent management method based on multi-source data fusion, the simulation model intelligent management method specifically comprises the following steps:

[0036] S100, extracting data information of the protection vehicle from an existing database, constructing a model based on the data information of the protection vehicle using appropriate modeling tools, such as CATIA, SolidWorks, etc., performing local impact simulation based on the constructed frame model, and extracting local impact simulation data from the simulation model;

[0037] S200, extracting historical impact simulation data that is most similar to the data information of the protection vehicle through the simulation database, and analyzing the impact simulation data of different areas of the protection vehicle by combining the historical impact simulation data with the local impact simulation data and the data information of the protection vehicle; the impact simulation data includes key indicators such as deformation, stress distribution, and energy absorption of the frame model under impact, and the impact resistance of the protection vehicle can be directly evaluated based on these indicators;

[0038] S300. Since the simulation is performed based on different areas of the protection vehicle during the impact simulation, it is impossible for the protection vehicle to be subjected to only one fixed area or one type of impact in actual situations. Therefore, it is necessary to analyze the overall impact resistance performance score of the protection vehicle based on the impact simulation data of different areas of the protection vehicle.

[0039] S400: Evaluate the accuracy of the overall impact resistance performance score of the protection vehicle based on the historical impact data set and the set impact scenario parameter set, and issue an early warning when the accuracy of the overall impact resistance performance score of the protection vehicle is lower than a preset accuracy threshold.

[0040] Furthermore, the specific method of performing local impact simulation on the workshop model and extracting local impact simulation data therefrom in S100 is as follows:

[0041] S101. Extract the data information of the protection vehicle from the existing database and generate a set Sj, S={Sj1, Sj2, Sj3...Sij...SIj}, where Sji represents the i-th data information of the j-th area of ​​the protection vehicle, j=1, 2, 3...J, J represents the number of areas into which the protection vehicle is divided, i=1, 2, 3...I, I represents the amount of data information of the protection vehicle, and construct a model based on the data information of the protection vehicle using appropriate modeling tools such as CATIA, SolidWorks, etc., where the data information of the protection vehicle includes detailed modeling of main parts such as the body, tires, frame, and any additional components or systems that may affect the impact response; perform impact modeling on the impact scenario. Simulation definition, setting the impact scenario parameters as sets Z, V, C, Z={Z1, Z2, Z3...Za...ZA}, V={V1, V2, V3...Va...VA}, C={C1, C2, C3...Ca...CA}; where Z, V, C represent different impact types, such as side impact, frontal impact, and top impact; Za represents the ath impact scenario parameter under Z type impact, Va represents the ath impact scenario parameter under V type impact, and Ca represents the ath impact scenario parameter under C type impact; a=1, 2, 3...A, A represents the number of impact scenario parameters, and the impact scenario parameters include impact velocity, impact angle, and impact intensity, etc.;

[0042] S102. Perform local impact simulation on the constructed frame model through simulation software (such as ANSYS, LS-DYNA, etc.). It is very important to accurately set the material properties of each component in the model, because these properties will directly affect the behavior of the model in the simulation; for example, the material, thickness, strength, etc. of the body and frame will affect the anti-impact performance; in the simulation process, the vehicle model will be affected by the defined impact scenario and produce corresponding responses, and the simulation software, i.e., the simulation model, will record these response data, so the local impact simulation data is extracted from the simulation model, and the sets generated based on the local impact simulation data are pj'z, pj'c, pj'v, j'∈{1, 2, 3...J}, where the local impact simulation is any one of the frame models. impact simulation is performed in different areas; pj'z, pj'c, and pj'v represent the local simulation data sets under different types of impacts, pj'z={pj'z1, pj'z2, pj'z3...pj'ze...pj'zE}, pj'c={pj'c1, pj'c2, pj'c3...pj'ce...pj'cE}, pj'v={pj'v1, pj'v2, pj'v3...pj've...pj'vE}, e=1, 2, 3...E, E represents the amount of local simulation data, and the impact simulation data includes key indicators such as deformation, stress distribution, and energy absorption of the frame model under impact. According to these indicators, the impact resistance of the protective vehicle can be directly evaluated.

[0043] Furthermore, the specific method of analyzing the impact simulation data of different areas of the protection vehicle in S200 is as follows:

[0044] S201. Extract the historical vehicle data information set Un from the existing database, where Un represents the data information set of the nth historical vehicle in the existing database, n=1, 2, 3...N, and N represents the number of the extracted historical vehicle data information sets. Since the historical vehicle data information sets in the existing database correspond one-to-one to the historical impact simulation data in the simulation database, the similarity between the protection vehicle data information set and the historical vehicle data information set in the existing database is calculated based on the impact simulation comparison table: Un→{Pnz, Pnc, Pnv}, through the formula: ln=|Un∩S| / |Un∪S|, where ln represents the similarity between the protection vehicle data information set and the nth historical vehicle data information set in the existing database. The similarity of the historical vehicle data information set, the absolute value of the set is expressed as the number of subsets in the set, and the historical impact simulation data {Pn'z, Pn'c, Pn'v}, n'∈{1, 2, 3...N}, are selected according to the historical vehicle data information set with the highest similarity according to the impact simulation comparison table; wherein Pnz represents the impact simulation data set under the Z type impact corresponding to the data information set of the nth historical vehicle in the existing database, Pnc represents the impact simulation data set under the C type impact corresponding to the data information set of the nth historical vehicle in the existing database, and Pnv represents the impact simulation data set under the V type impact corresponding to the data information set of the nth historical vehicle in the existing database;

[0045] S202. Extract the impact resistance score yj'i corresponding to the data information of the protection vehicle for local impact simulation and the impact resistance score yji corresponding to the data information of each area of ​​the protection vehicle based on the data information of the protection vehicle, wherein yj'i represents the impact resistance score corresponding to the i-th data information of the j'th area of ​​the protection vehicle, and yji represents the impact resistance score corresponding to the i-th data information of the j-th area of ​​the protection vehicle; wherein the impact resistance score corresponding to the data information of the protection vehicle is represented by a specific numerical value, and the numerical value is judged based on the impact resistance obtained by the training model. When the material, thickness and strength of the protection vehicle in different areas are different, the corresponding impact resistance is also different; when the impact resistance is stronger, the numerical value of the corresponding data in different areas is higher; according to the formula: pjz=(∑I i=1yji / ∑I i=1yj'i)*pj'z, pjc=(∑I i=1yji / ∑I i=1yj'i)*pj'c, pjv=(∑I i=1yji / ∑I i=1yj'i)*pj'v, the impact simulation data sets of different areas of the protection vehicle under different types of impact simulation are calculated respectively, pjz represents the impact simulation data set of the jth area of ​​the protection vehicle under the Z type impact simulation, pjc represents the impact simulation data set of the jth area of ​​the protection vehicle under the C type impact simulation, and pjv represents the impact simulation data set of the jth area of ​​the protection vehicle under the V type impact simulation;

[0046] S203. Generate an impact simulation data set of the protection vehicle {Pz, Pc, Pv} based on the impact simulation data sets of different areas of the protection vehicle under different types of impact simulations, wherein Pz represents the impact simulation data set of the protection vehicle under Z type impact, Pz represents the impact simulation data set of the protection vehicle under C type impact, Pv represents the impact simulation data set of the protection vehicle under V type impact, Pz={p1z, p2z, p3z...pjz...pJz}, Pc={p1c, p2c, p3c...pjc...pJc}, Pv={p1v, p2v, p3v...pjv...pJv}.

[0047] Furthermore, the specific method of analyzing the overall impact resistance score of the protection vehicle based on the impact simulation data of different areas of the protection vehicle in S300 is as follows:

[0048] S301. According to the impact simulation data sets of different areas of the protection vehicle under different types of impact simulations, determine the correlation between different areas under local impact simulation: {pj'z, pj'c, pj'v}→{pjz, pjc, pjv}=Rj, where Rj represents the impact value of the j-th area under local impact simulation. Since j'∈{1, 2, 3...J}, {pj'z, pj'c, pj'v}→{pj'z, pj'c, pj'v} does not exist, that is, Rj'=0. The larger the impact value, the smaller the impact resistance score of the area affected by the local impact simulation. The correlation is any The deformation and stress distribution of any area under impact simulation involves the proportion of other areas. The larger the area of ​​other areas involved, the greater the impact value. The impact resistance of other areas will be reduced or unchanged accordingly due to the proportion of the deformation and stress distribution of any area under impact simulation. When any area of ​​the protection vehicle is impacted, the deformation and stress distribution may affect the impact resistance of other areas of the protection vehicle, such as the anti-collision guardrail and roll cage of the protection vehicle. These devices exist to provide additional protection and reduce the degree of damage in the event of an accident. If they are damaged or fail, the impact resistance of the entire protection vehicle may be reduced.

[0049] S302, constructing an overall impact resistance performance analysis model according to the correlation between different regions under impact simulation and the impact resistance performance scores yji corresponding to the data information of each region of the protection vehicle:

[0050] Y=∑J j=1[(∑I i=1yji)*(1-Rj)]

[0051] The overall impact resistance score of the protection vehicle is calculated, where Y represents the overall impact resistance score of the protection vehicle.

[0052] Furthermore, the specific method for evaluating the accuracy of the overall impact resistance score of the protection vehicle in S400 is as follows: historical impact data sets under actual impact scenarios are obtained, namely Zh, Ch and Vh, where Zh, Ch and Vh represent historical impact data sets of Z, C and V type impacts under actual impact scenarios, respectively, through the formula:

[0053] lz=|Zh∩Z| / |Zh∪Z|, lc=|Ch∩C| / |Ch∪C|, lv=|Vh∩V| / |Vh∪V|

[0054] L=lz+lc+lv

[0055] The accuracy of the overall impact resistance performance score of the protection vehicle is calculated; where lz, lc and lv represent the similarity values ​​of the historical impact data set and the set impact scenario parameter set under Z, C and V type impacts respectively, and L represents the accuracy of the overall impact resistance performance score of the protection vehicle, L∈[0,3]; when the accuracy L of the overall impact resistance performance score of the protection vehicle is lower than the preset accuracy threshold L', an alarm is issued, and the overall impact resistance performance score of the protection vehicle is analyzed.

[0056] A simulation model intelligent management system based on multi-source data fusion, the simulation model intelligent management system includes a data acquisition module, a data analysis module, a model supervision module and an alarm reminder module; the output end of the data acquisition module is connected to the input end of the data analysis module, the output end of the data analysis module is connected to the input end of the model supervision module, and the output end of the model supervision module is connected to the input end of the alarm reminder module; the data acquisition module is used to collect data information of the protection vehicle, local impact simulation data and historical impact data sets under actual impact scenarios; the data analysis module is used to analyze the impact simulation data of the protection vehicle and the impact value between the impact resistance of different areas of the protection vehicle and the local impact simulation; the model supervision module analyzes the overall impact resistance performance score of the protection vehicle and the score accuracy; the alarm reminder module is used to issue an alarm reminder when the accuracy of the overall impact resistance performance score of the protection vehicle is lower than a preset accuracy threshold.

[0057] Furthermore, the data acquisition module includes a protection vehicle data information acquisition unit, a local impact simulation data acquisition unit and a historical impact data set acquisition unit; the protection vehicle data information acquisition unit extracts the data information of the protection vehicle from an existing database; the local impact simulation data acquisition unit performs local impact simulation on the constructed frame model through simulation software (such as ANSYS, LS-DYNA, etc.), and extracts local impact simulation data from the simulation model; the historical impact data set acquisition unit selects the historical impact simulation data corresponding to the historical vehicle data information set with the highest similarity based on the impact simulation comparison table.

[0058] Furthermore, the data analysis module includes an impact simulation data analysis unit and a regional impact influence value analysis unit; the impact simulation data analysis unit analyzes the impact simulation data sets of different regions of the protection vehicle under different types of impact simulations; the regional impact influence value analysis unit analyzes the influence value between the impact resistance of different regions of the protection vehicle and the local impact simulation.

[0059] Furthermore, the model supervision module includes an overall impact resistance performance score analysis unit and an overall impact resistance performance score accuracy analysis unit; the overall impact resistance performance score analysis unit is for the overall impact resistance performance score of the protection vehicle; the overall impact resistance performance score accuracy analysis unit is for judging the accuracy of the overall impact resistance performance score of the protection vehicle.

[0060] Furthermore, the warning reminder module includes a warning decision unit and an impact scenario parameter reset unit; the warning decision unit is to issue an alarm reminder when the accuracy of the overall impact resistance performance score of the protection vehicle is lower than a preset accuracy threshold; the impact scenario parameter reset unit is to reset the impact scenario parameters and re-simulate when the terminal receives the alarm reminder.

[0061] In this embodiment:

[0062] According to the impact simulation data sets of different areas of the protection vehicle under different types of impact simulation, the correlation relationship of different areas under local impact simulation is determined: {pj'z, pj'c, pj'v}→{pjz, pjc, pjv}=Rj={0.7, 0.1, 0.15...};

[0063] According to the correlation between different areas under impact simulation and the impact resistance scores yji={20, 15, 37...} corresponding to the data information of each area of ​​the protection vehicle, the overall impact resistance performance analysis model is constructed:

[0064] Y=∑J j=1[(∑I i=1yji)*(1-Rj)]=76

[0065] The overall impact resistance score of the protection vehicle is calculated, where Y represents the overall impact resistance score of the protection vehicle.

[0066] The historical shock data sets obtained under the actual shock scenario are Zh, Ch and Vh, where Zh, Ch and Vh represent the historical shock data sets of Z, C and V type shocks under the actual shock scenario, respectively. The formula is:

[0067] lz=|Zh∩Z| / |Zh∪Z|=0.4, lc=|Ch∩C| / |Ch∪C|=0.15, lv=|Vh∩V| / |Vh∪V|=0.23

[0068] L=lz+lc+lv=0.78

[0069] The calculated accuracy of the overall impact resistance performance score of the protection vehicle is L=0.78, which is lower than the preset accuracy threshold L'=2.5, and an alarm is issued, and the overall impact resistance performance score of the protection vehicle is analyzed.

[0070] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0071] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. The intelligent management method of simulation model based on multi-source data fusion is characterized by: The simulation model intelligent management method specifically comprises the following steps: S100, extracting data information of a protection vehicle from an existing database, constructing a model based on the data information of the protection vehicle, performing local impact simulation based on the constructed frame model, and extracting local impact simulation data from the simulation model; S200, extracting historical impact simulation data that is most similar to the data information of the protection vehicle through the simulation database, and analyzing the impact simulation data of different areas of the protection vehicle by combining the historical impact simulation data with the local impact simulation data and the data information of the protection vehicle; S300, analyzing the overall impact resistance score of the protection vehicle based on the impact simulation data of different areas of the protection vehicle; S400, evaluating the accuracy of the overall impact resistance performance score of the protection vehicle based on the historical impact data set and the set impact scenario parameter set, and issuing an early warning when the accuracy of the overall impact resistance performance score of the protection vehicle is lower than a preset accuracy threshold; The specific method of performing local impact simulation on the workshop model and extracting local impact simulation data therefrom in S100 is as follows: S101. Extract the data information of the protection vehicle from the existing database and generate a set Sj, S={Sj1, Sj2, Sj3...Sij...SIj}, where Sji represents the i-th data information of the j-th area of ​​the protection vehicle, j=1, 2, 3...J, J represents the number of areas into which the protection vehicle is divided, i=1, 2, 3...I, I represents the amount of data information of the protection vehicle, simulate and define the impact scenario, and set the impact scenario parameters to be the set Z, V, C, Z={Z 1, Z2, Z3...Za...ZA}, V={V1, V2, V3...Va...VA}, C={C1, C2, C3...Ca...CA}; where Z, V, C represent different impact types, Za represents the ath impact scenario parameter under Z type impact, Va represents the ath impact scenario parameter under V type impact, and Ca represents the ath impact scenario parameter under C type impact; a=1, 2, 3...A, A represents the number of impact scenario parameters; S102, perform local impact simulation on the constructed frame model through simulation software, extract local impact simulation data from the simulation model, and generate sets pj'z, pj'c, pj'v according to the local impact simulation data, j'∈{1, 2, 3...J}; wherein pj'z, pj'c, pj'v respectively represent local simulation data sets under different types of impact, pj'z={pj'z1, pj'z2, pj'z3...pj'ze...pj'zE}, pj'c={pj'c1, pj'c2, pj'c3...pj'ce...pj'cE}, pj'v={pj'v1, pj'v2, pj'v3...pj've...pj'vE}, e=1, 2, 3...E, E represents the amount of local simulation data; The specific method of analyzing the impact simulation data of different areas of the protection vehicle in S200 is as follows: S201. Extract a historical vehicle data information set Un from an existing database, where Un represents the nth historical vehicle data information set in the existing database, n=1, 2, 3...N, where N represents the number of historical vehicle data information sets extracted, and calculate the similarity between the protection vehicle data information set and the historical vehicle data information set in the existing database through the formula: ln=|Un∩S| / |Un∪S|, where ln represents the similarity between the protection vehicle data information set and the nth historical vehicle data information set in the existing database, and select the historical vehicle data information set with the highest similarity according to the impact simulation comparison table. Impact simulation data {Pn'z, Pn'c, Pn'v}, n'∈{1, 2, 3...N}; wherein Pnz represents the impact simulation data set corresponding to the data information set of the nth historical vehicle in the existing database under the Z type impact, Pnc represents the impact simulation data set corresponding to the data information set of the nth historical vehicle in the existing database under the C type impact, and Pnv represents the impact simulation data set corresponding to the data information set of the nth historical vehicle in the existing database under the V type impact; Pn'z, Pn'c, Pn'v refer to the historical impact simulation data under the Z, C, and V type impacts, respectively, selected according to the historical vehicle data information set with the highest similarity according to the impact simulation comparison table; S202. Extract the impact resistance score yj'i corresponding to the data information of the protection vehicle for local impact simulation and the impact resistance score yji corresponding to the data information of each area of ​​the protection vehicle based on the data information of the protection vehicle, wherein yj'i represents the impact resistance score corresponding to the i-th data information of the j'th area of ​​the protection vehicle, and yji represents the impact resistance score corresponding to the i-th data information of the j'th area of ​​the protection vehicle; according to the formula: pjz=(∑I i=1yji / ∑I i=1yj'i)*pj'z, pjc=(∑I i=1yji / ∑I i=1yj'i)*pj'c, pjv=(∑I i=1yji / ∑I i=1yj'i)*pj'v, the impact simulation data sets of different areas of the protection vehicle under different types of impact simulation are calculated respectively, pjz represents the impact simulation data set of the jth area of ​​the protection vehicle under the Z type impact simulation, pjc represents the impact simulation data set of the jth area of ​​the protection vehicle under the C type impact simulation, and pjv represents the impact simulation data set of the jth area of ​​the protection vehicle under the V type impact simulation; S203. Generate an impact simulation data set of the protection vehicle {Pz, Pc, Pv} based on the impact simulation data sets of different areas of the protection vehicle under different types of impact simulations, wherein Pz represents the impact simulation data set of the protection vehicle under Z type impact, Pz represents the impact simulation data set of the protection vehicle under C type impact, Pv represents the impact simulation data set of the protection vehicle under V type impact, Pz={p1z, p2z, p3z...pjz...pJz}, Pc={p1c, p2c, p3c...pjc...pJc}, Pv={p1v, p2v, p3v...pjv...pJv}.

2. The simulation model intelligent management method based on multi-source data fusion according to claim 1 is characterized in that: The specific method of analyzing the overall impact resistance score of the protection vehicle based on the impact simulation data of different areas of the protection vehicle in S300 is as follows: S301, determining the correlation between different regions under local impact simulation according to the impact simulation data sets of different regions of the protection vehicle under different types of impact simulation: {pj'z, pj'c, pj'v}→{pjz, pjc, pjv}=Rj, where Rj represents the impact value of the jth region under local impact simulation; S302, constructing an overall impact resistance performance analysis model according to the correlation between different regions under impact simulation and the impact resistance performance scores yji corresponding to the data information of each region of the protection vehicle: Y=∑J j=1[(∑I i=1yji)*(1-Rj)] The overall impact resistance score of the protection vehicle is calculated, where Y represents the overall impact resistance score of the protection vehicle.

3. The simulation model intelligent management method based on multi-source data fusion according to claim 2 is characterized in that: The specific method for evaluating the accuracy of the overall impact resistance performance score of the protection vehicle in S400 is as follows: the historical impact data sets under the actual impact scenario are obtained, namely Zh, Ch and Vh, where Zh, Ch and Vh represent the historical impact data sets of Z, C and V type impacts under the actual impact scenario, respectively, through the formula: lz=|Zh∩Z| / |Zh∪Z|, lc=|Ch∩C| / |Ch∪C|, lv=|Vh∩V| / |Vh∪V| L=lz+lc+lv The accuracy of the overall impact resistance performance score of the protection vehicle is calculated; wherein lz, lc and lv represent the similarity values ​​of the historical impact data set and the set impact scenario parameter set under Z, C and V type impacts respectively, and L represents the accuracy of the overall impact resistance performance score of the protection vehicle; when the accuracy L of the overall impact resistance performance score of the protection vehicle is lower than the preset accuracy threshold L', an alarm is issued.

4. A simulation model intelligent management system based on multi-source data fusion, using the simulation model intelligent management method based on multi-source data fusion as claimed in claim 1, characterized in that: The simulation model intelligent management system includes a data acquisition module, a data analysis module, a model supervision module and an alarm reminder module; the output end of the data acquisition module is connected to the input end of the data analysis module, the output end of the data analysis module is connected to the input end of the model supervision module, and the output end of the model supervision module is connected to the input end of the alarm reminder module; the data acquisition module is used to collect data information of the protection vehicle, local impact simulation data and historical impact data sets under actual impact scenarios; the data analysis module is used to analyze the impact simulation data of the protection vehicle and the impact value between the impact resistance of different areas of the protection vehicle and the local impact simulation; the model supervision module analyzes the overall impact resistance performance score of the protection vehicle and the score accuracy; the alarm reminder module is used to issue an alarm reminder when the accuracy of the overall impact resistance performance score of the protection vehicle is lower than a preset accuracy threshold.

5. The simulation model intelligent management system based on multi-source data fusion according to claim 4 is characterized in that: The data acquisition module includes a protection vehicle data information acquisition unit, a local impact simulation data acquisition unit and a historical impact data set acquisition unit; the protection vehicle data information acquisition unit extracts the data information of the protection vehicle from an existing database; the local impact simulation data acquisition unit performs local impact simulation on the constructed frame model through simulation software, and extracts local impact simulation data from the simulation model; the historical impact data set acquisition unit selects the historical impact simulation data corresponding to the historical vehicle data information set with the highest similarity based on the impact simulation comparison table.

6. The simulation model intelligent management system based on multi-source data fusion according to claim 5 is characterized in that: The data analysis module includes an impact simulation data analysis unit and a regional impact impact value analysis unit; the impact simulation data analysis unit analyzes the impact simulation data sets of different areas of the protection vehicle under different types of impact simulations; the regional impact impact value analysis unit analyzes the impact value between the impact resistance of different areas of the protection vehicle and the local impact simulation.

7. The simulation model intelligent management system based on multi-source data fusion according to claim 6 is characterized by: The model supervision module includes an overall impact resistance performance score analysis unit and an overall impact resistance performance score accuracy analysis unit; the overall impact resistance performance score analysis unit is used to score the overall impact resistance performance of the protection vehicle; the overall impact resistance performance score accuracy analysis unit is used to judge the accuracy of the overall impact resistance performance score of the protection vehicle.

8. The simulation model intelligent management system based on multi-source data fusion according to claim 7 is characterized in that: The warning module includes a warning decision unit and an impact scenario parameter reset unit; the warning decision unit is used to issue a warning when the accuracy of the overall impact resistance performance score of the protection vehicle is lower than a preset accuracy threshold; The impact scenario parameter resetting unit resets the impact scenario parameters and re-simulates when the terminal receives an alarm reminder.

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