Impact dummy chest sensing device anomaly detection method and device and electronic equipment

Abstract

The invention provides a collision dummy chest sensing device abnormity detection method and device and electronic equipment, and the method comprises the steps: obtaining first acting force data and second acting force data of the chest of a collision dummy in a vehicle safety collision test; the abnormal detection result of the chest displacement sensing device is determined based on the comparison result of the first acting force data and the second acting force data, and the first acting force data is determined based on displacement data detected by the chest displacement sensing device of the collision dummy; the second acting force data is used for representing a theoretical value of an acting force required for generating the displacement data, and the second acting force data is determined based on data detected by a detection device except the chest displacement sensing device, so that anomaly detection can be quickly and effectively carried out on the displacement sensing device which collides with the chest of the dummy; therefore, the accuracy of chest displacement test data can be effectively ensured, and the reliability of a vehicle collision safety test result is improved.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a method, device and electronic equipment for detecting abnormality of a collision dummy chest sensor device. Background Art

[0002] In recent years, with the continuous development of automobile technology, the requirements for vehicle driving safety have become higher and higher. Collision safety can effectively reduce the degree of injury to people in traffic accidents and is an important factor in improving vehicle driving safety. In order to improve the collision safety of vehicles, collision dummies are usually used to conduct collision safety development tests and collision certification tests to ensure that the vehicle meets the corresponding safety standards.

[0003] However, collision dummies usually suffer from problems such as wear and aging during multiple collision tests, especially the displacement sensor device on the collision dummy's chest, which needs to frequently withstand the tension of the seat belt and the impact force of the steering wheel during collision tests. Although relevant personnel will inspect, repair and recalibrate the collision dummy after the test, it is impossible to effectively avoid abnormalities in the displacement sensor device during the test due to personnel negligence or the long service life of the collision dummy. In addition, the displacement sensor device is usually wrapped by the simulated skin on the outside of the dummy, and the abnormality of the displacement sensor device cannot be detected from the outside of the collision dummy, making it difficult to avoid the distortion of the chest displacement test data and the impact on the reliability of the vehicle collision safety test results.

[0004] Therefore, it is necessary to provide a method for quickly and effectively detecting abnormalities in a displacement sensor device of a crash dummy's chest. Summary of the invention

[0005] To solve the above technical problems, the present application provides a method, device and electronic equipment for detecting abnormalities of a collision dummy chest sensor device, so as to solve the problem in the prior art that it is impossible to quickly and effectively detect abnormalities of a displacement sensor device on the collision dummy chest.

[0006] To achieve the above technical objectives, the present application provides the following technical solutions:

[0007] In a first aspect, an embodiment of the present specification provides a method for detecting abnormality of a crash dummy chest sensor device, comprising:

[0008] Acquire first force data and second force data of the chest of a collision dummy in a vehicle safety collision test; wherein the first force data is determined based on displacement data detected by a chest displacement sensor device of the collision dummy, and is used to characterize a theoretical value of the force required to generate the displacement data; the second force data is determined based on data detected by a target detection device, and the target detection device is a detection device other than the chest displacement sensor device;

[0009] Based on a comparison result of the first force data and the second force data, an abnormality detection result of the chest displacement sensor device is determined.

[0010] In one embodiment, determining the abnormal detection result of the chest displacement sensor device based on the comparison result of the first force data and the second force data includes:

[0011] The first force data and the second force data are respectively screened according to a target time interval to obtain first sub-data corresponding to the first force data and second sub-data corresponding to the second force data;

[0012] Based on the comparison result of the first sub-data and the second sub-data, an abnormality detection result of the chest displacement sensing device is determined.

[0013] In one embodiment, the process of determining the target time interval includes:

[0014] The target time interval is determined based on a time interval during which a theoretical value of the first force data is equal to a theoretical value of the second force data after the vehicle collides.

[0015] In one implementation, determining the abnormality detection result of the chest displacement sensor device based on the comparison result of the first sub-data and the second sub-data includes:

[0016] generating a first curve graph based on the first sub-data, and generating a second curve graph based on the second sub-data;

[0017] Based on the similarity between the first curve graph and the second curve graph, an abnormality detection result of the chest displacement sensing device is determined.

[0018] In one embodiment, determining the abnormal detection result of the chest displacement sensor device based on the similarity between the first curve graph and the second curve graph includes:

[0019] When the similarity is greater than or equal to a preset similarity threshold, it is determined that there is no abnormality in the chest displacement sensor device;

[0020] When the similarity is less than the preset similarity threshold, it is determined that the chest displacement sensor device is abnormal.

[0021] In one embodiment, the process of determining the first force data includes:

[0022] The first force data is obtained by multiplying the displacement data detected by the chest displacement sensor device with the chest stiffness data of the collision dummy.

[0023] In one embodiment, the second force data includes first target data determined based on tension data detected by a seat belt tension detection device of the vehicle, and / or second target data determined based on acceleration data detected by a chest acceleration sensor device of the collision dummy, and the second target data is used to characterize a theoretical value of the force required to generate the acceleration data.

[0024] In one implementation, the process of determining the second target data includes:

[0025] The acceleration data detected by the chest acceleration sensor device is multiplied by the chest mass data of the collision dummy to obtain the second target data.

[0026] In a second aspect, the embodiments of this specification provide a crash dummy chest sensor device abnormality detection device, comprising:

[0027] a first processing module, for obtaining first force data and second force data on the chest of a collision dummy in a vehicle safety collision test; wherein the first force data is determined based on displacement data detected by a chest displacement sensor device of the collision dummy, and is used to characterize a theoretical value of the force required to generate the displacement data; and the second force data is determined based on data detected by a target detection device, and the target detection device is a detection device other than the chest displacement sensor device;

[0028] The second processing module is used to determine the abnormal detection result of the chest displacement sensor device based on the comparison result of the first force data and the second force data.

[0029] In a third aspect, an embodiment of this specification provides an electronic device, comprising at least one processor and at least one memory, wherein the memory stores a computer program, and when the computer program is executed by the processor, the method for detecting an abnormality of a collision dummy chest sensor device as described in any one of the above items is implemented.

[0030] In a fourth aspect, an embodiment of the present specification provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method for detecting abnormality of a collision dummy chest sensor device as described in any one of the above items is implemented.

[0031] In a fifth aspect, an embodiment of the present specification provides a computer program product or a computer program, wherein the computer program product includes a computer program, and the computer program is stored in a computer-readable storage medium; the processor of the computer device reads the computer program from the computer-readable storage medium, and when the processor executes the computer program, the method for detecting an abnormality of a collision dummy chest sensor device as described in any one of the above items is implemented.

[0032] It can be seen from the above technical scheme that the embodiments of the present application provide a method, device and electronic device for detecting abnormality of a collision dummy's chest sensor device. The method obtains first force data and second force data on the chest of the collision dummy in a vehicle safety collision test, and determines the abnormal detection result of the chest displacement sensor device based on the comparison result of the first force data and the second force data, wherein the first force data is determined based on the displacement data detected by the chest displacement sensor device of the collision dummy, and is used to characterize the theoretical value of the force required to generate the displacement data, and the second force data is determined based on the data detected by a detection device other than the chest displacement sensor device. Therefore, by converting the displacement data detected by the chest displacement sensor device of the collision dummy into the first force data, and comparing the first force data with the force data of the chest of the collision dummy obtained by other means, the displacement sensor device of the collision dummy's chest can be quickly and effectively detected for abnormality, thereby effectively ensuring the accuracy of the chest displacement test data, thereby improving the reliability of the vehicle collision safety test results. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0034] Figure 1 A flowchart of a method for detecting abnormality of a crash dummy chest sensor device is provided in an embodiment of the present specification.

[0035] Figure 2 A schematic diagram for comparing a first curve graph corresponding to first force data and a second curve graph corresponding to each second force data provided in an implementation manner of this specification.

[0036] Figure 3 Another schematic diagram of comparison of a first curve graph corresponding to first force data and a second curve graph corresponding to each second force data provided for an implementation manner of this specification.

[0037] Figure 4 A schematic structural diagram of a crash dummy chest sensor device abnormality detection device provided in an embodiment of the present specification. DETAILED DESCRIPTION

[0038] Unless otherwise defined, the technical terms or scientific terms used in the embodiments of this specification shall have the common meanings understood by persons with ordinary skills in the field to which this specification belongs. The words "first", "second" and similar words used in the embodiments of this specification do not indicate any order, quantity or importance, but are only used to avoid confusion of constituent elements.

[0039] Unless the context requires otherwise, throughout the specification, "plurality" means "at least two", and "including" is interpreted as an open, inclusive meaning, that is, "including, but not limited to". In the description of the specification, the terms "one embodiment", "some embodiments", "exemplary embodiments", "examples", "specific examples" or "some examples" are intended to indicate that a particular feature, structure, material or characteristic associated with the embodiment or example is included in at least one embodiment or example of the specification. The schematic representation of the above terms does not necessarily refer to the same embodiment or example.

[0040] The following will be combined with the drawings in the embodiments of this specification to clearly and completely describe the technical solutions in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments in this specification, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this specification.

[0041] Overview

[0042] As mentioned in the background technology, in recent years, with the continuous development of automobile technology, the requirements for vehicle driving safety have become increasingly higher, and collision safety can effectively reduce the degree of injury to people in traffic accidents and is an important factor in improving vehicle driving safety. In order to improve the collision safety of vehicles, collision dummies are usually used to conduct collision safety development tests and collision certification tests to ensure that the vehicle meets the corresponding safety standards.

[0043] However, collision dummies usually experience problems such as wear and aging during multiple collision tests, especially the displacement sensor device on the chest of the collision dummy, which needs to frequently withstand the tension of the seat belt and the impact of the steering wheel during the collision test. Although relevant personnel will inspect, repair and recalibrate the collision dummy after the test, due to personnel negligence or the long service life of the collision dummy, it is impossible to effectively avoid the abnormality of the displacement sensor device during the test, and thus the data detection accuracy of the displacement sensor device during the test cannot be guaranteed. At the same time, since the displacement sensor device is usually wrapped by the simulated skin outside the dummy, the abnormality of the displacement sensor device cannot be detected outside the collision dummy, and it is impossible to determine whether the chest displacement test data collected by the displacement sensor device is distorted. Considering that the safety standards have strict standards for the chest displacement of the collision dummy, once the chest displacement test data exceeds the limit value in the safety standards, the vehicle collision test will fail; in addition, there will be a problem that the chest displacement test data meets the limit value in the safety standards, but the actual vehicle collision safety performance cannot meet the safety standards, thus the reliability of the vehicle collision safety test results cannot be guaranteed.

[0044] Among them, the insufficient reliability of vehicle collision safety test results will have extremely serious consequences. For example, when the collision safety performance of the vehicle meets the safety standards but is mistakenly judged as not meeting them, relevant personnel will need to spend more resources and energy to make corrections, and additional verification tests will be required. When the collision safety performance of the vehicle cannot meet the safety standards but is mistakenly judged as meeting them, the risk of personal injury during driving will be greatly increased.

[0045] Therefore, it is necessary to provide a method for quickly and effectively detecting abnormalities in a displacement sensor device of a crash dummy's chest.

[0046] In order to solve the problem that traditional methods cannot quickly and effectively detect abnormalities in the displacement sensor device of the collision dummy's chest, in the technical solution of the present application, the method for detecting abnormalities in the collision dummy's chest sensor device obtains first force data and second force data on the collision dummy's chest in a vehicle safety collision test, and determines the abnormal detection result of the chest displacement sensor device based on the comparison result of the first force data and the second force data, wherein the first force data is determined based on the displacement data detected by the collision dummy's chest displacement sensor device, and is used to characterize the theoretical value of the force required to generate the displacement data, and the second force data is determined based on data detected by a detection device other than the chest displacement sensor device. Therefore, by converting the displacement data detected by the collision dummy's chest displacement sensor device into the first force data, and comparing the first force data with the force data of the collision dummy's chest obtained by other means, the displacement sensor device of the collision dummy's chest can be quickly and effectively detected for abnormalities, thereby effectively ensuring the accuracy of the chest displacement test data, thereby improving the reliability of the vehicle collision safety test results.

[0047] Based on the above inventive concept, the abnormality detection method of the crash dummy chest sensor device provided in the embodiment of this specification is exemplarily described below.

[0048] Exemplary Methods

[0049] The embodiments of this specification provide a method for detecting abnormality of a crash dummy chest sensor device, such as Figure 1 As shown, including:

[0050] S101. Acquire first force data and second force data on the chest of a collision dummy in a vehicle safety collision test; wherein the first force data is determined based on displacement data detected by a chest displacement sensor device of the collision dummy, and is used to characterize a theoretical value of the force required to generate the displacement data; the second force data is determined based on data detected by a target detection device, and the target detection device is a detection device other than the chest displacement sensor device.

[0051] Specifically, the collision dummy may be a dummy used in a vehicle safety collision test. The first force data on the collision dummy's chest may be determined based on displacement data detected by a chest displacement sensor of the collision dummy in the vehicle safety collision test, and the chest displacement sensor may be disposed on the collision dummy's chest. The first force data may be used to characterize a theoretical value of the force required to generate the detected displacement data, that is, ideally, the magnitude of the force required to act on the collision dummy's chest when generating the detected displacement data.

[0052] The second force data of the chest of the crash dummy can be determined based on the data detected by the target detection device in the vehicle safety collision test, and the target detection device can be a detection device other than the chest displacement sensor device of the crash dummy. The target detection device can include a detection device other than the chest displacement sensor device arranged on the chest of the crash dummy, such as a chest acceleration sensor device, and can also include a detection device arranged on the vehicle, such as a seat belt tension detection device, and can also include a newly added detection device, such as a stress detection device arranged on the chest of the crash dummy.

[0053] The second force data can be one set of data or multiple sets of data, which can be set according to actual needs. It can be understood that when the second force data is multiple sets of data, different second force data can be determined based on data detected by different target detection devices.

[0054] During implementation, the data detected by the chest displacement sensor device and each target detection device can be obtained in real time during a vehicle safety collision test. After the vehicle safety collision test is completed, the data detected by the chest displacement sensor device and each target detection device in the vehicle safety collision test can be obtained from a data storage unit of a test equipment, etc.

[0055] S102: Determine an abnormality detection result of the chest displacement sensor device based on a comparison result of the first force data and the second force data.

[0056] Specifically, when the second force data is a group of data, the second force data can be used as target force data, and based on the comparison result between the first force data and the target force data, the abnormal detection result of the chest displacement sensor device is determined.

[0057] When the second force data is a plurality of sets of data, the abnormal detection result of the chest displacement sensor device can be determined based on the comparison result between the first force data and the target force data in the plurality of sets of second force data. The target force data can be a set of second force data with the highest credibility among the plurality of sets of second force data. For example, the comparison result between every two sets of second force data in the plurality of sets of second force data can be obtained, and the target force data can be determined based on the comparison result between each set of second force data.

[0058] Among them, when two sets of second force data are included, when the difference value of the two sets of second force data is less than or equal to the preset difference threshold, any one of the two sets of second force data can be used as the target force data. In addition, when the difference value of the two sets of second force data is greater than the preset difference threshold, it can be considered that both sets of second force data are unreliable, that is, there is no target force data. At this time, the test results of the vehicle safety collision test can be considered invalid.

[0059] When three or more sets of second force data are included, the number of similar force data for each second force data may be determined based on the comparison results between the second force data, and the second force data with the largest number of similar force data may be used as candidate force data. For any second force data, the similar force data of the second force data may include second force data whose difference value with the second force data is less than or equal to a preset difference threshold value among the second force data other than the second force data.

[0060] If the number of candidate force data is one group, the candidate force data can be used as the target force data. If the number of candidate force data is multiple groups, any candidate force data can be used as the target force data. The total difference value corresponding to each candidate force data can also be obtained, and the candidate force data with the smallest total difference value can be used as the target force data. Corresponding to any candidate force data, the total difference value corresponding to the candidate force data can be the sum of the difference values ​​between the candidate force data and the corresponding similar force data.

[0061] During implementation, in the process of determining the abnormal detection result of the chest displacement sensor device based on the comparison result of the first force data and the target force data, the difference value or the similarity of the change trend between the first force data and the target force data can be obtained, so as to determine the abnormal detection result of the chest displacement sensor device based on the comparison result of the difference value or the similarity of the change trend with the corresponding threshold.

[0062] Among them, for any two sets of force data, the difference value of the two sets of force data can be the variance, standard deviation, change trend dissimilarity (the difference between 1 and the similarity of the change trends of the two sets of force data), etc., which can be set according to actual needs.

[0063] Therefore, by converting the displacement data detected by the chest displacement sensor device of the collision dummy into first force data, and comparing the first force data with the second force data of the collision dummy's chest obtained by other means, the displacement sensor device of the collision dummy's chest can be quickly and effectively detected for abnormalities, thereby effectively ensuring the accuracy of the chest displacement test data, and further improving the reliability of the vehicle collision safety test results.

[0064] In a feasible implementation manner, determining the abnormal detection result of the chest displacement sensor device based on the comparison result of the first force data and the second force data includes:

[0065] The first force data and the second force data are respectively screened according to a target time interval to obtain first sub-data corresponding to the first force data and second sub-data corresponding to the second force data;

[0066] Based on the comparison result of the first sub-data and the second sub-data, an abnormality detection result of the chest displacement sensing device is determined.

[0067] Specifically, the target time interval may include any time interval in a vehicle safety collision test.

[0068] As a preferred implementation, the process of determining the target time interval may include:

[0069] The target time interval is determined based on a time interval during which a theoretical value of the first force data is equal to a theoretical value of the second force data after the vehicle collides.

[0070] The theoretical value of the first force data may be the actual value of the force that causes the collision dummy to produce chest displacement in the vehicle safety collision test, and the theoretical value of the second force data may be the actual value of the force corresponding to the target parameter in the vehicle safety collision test, and the target parameter is the parameter detected by the target detection device. For example, if the second force data is determined based on the tension data detected by the seat belt tension detection device, then the theoretical value of the second force data may be the actual tension of the seat belt in the vehicle safety collision test, and if the second force data is determined based on the acceleration data detected by the chest acceleration sensor of the collision dummy, then the theoretical value of the second force data may be the actual value of the force that causes the collision dummy to produce chest acceleration in the vehicle safety collision test.

[0071] In a vehicle safety collision test, after a vehicle collision, the chest of the collision dummy will be subjected to the tension of the seat belt, the impact force of the airbag and the impact force of the steering wheel, all of which will cause displacement and acceleration of the collision dummy's chest. In the early stage of a vehicle collision, the chest of the collision dummy is only subjected to the tension of the seat belt. The airbag is detonated when a first time length (e.g., 16ms) is reached after the collision, and the airbag contacts the collision dummy when a second time length (e.g., 37ms) is reached after the collision.

[0072] As a preferred embodiment, the time interval during which the chest of the collision dummy is only subjected to the tension of the seat belt can be used as the target time interval (for example, from the moment of collision to the moment before the airbag contacts the collision dummy), that is, within the target time interval, the chest of the collision dummy is only subjected to the force of a single component, thereby effectively avoiding the influence on the accuracy of the determination results of the first force data and the second force data caused by the imbalance of the force on the chest of the collision dummy caused by different components acting on the chest of the collision dummy at the same time, and thus the validity of the abnormal detection result of the chest displacement sensor device cannot be guaranteed. At the same time, by using the time interval during which the chest of the collision dummy is only subjected to the tension of the seat belt as the target time interval, the second force data can be determined based on the tension data detected by the vehicle's seat belt tension detection device, the acceleration data detected by the collision dummy's chest acceleration sensor device, and the stress data detected by the stress detection device set on the collision dummy's chest, thereby effectively increasing the number of force data that can be referenced when performing abnormal detection on the chest displacement sensor device, and thus the validity of the abnormal detection result of the chest displacement sensor device can be improved.

[0073] In implementation, the first force data may be screened according to the target time interval to obtain first sub-data corresponding to the first force data, that is, the first sub-data is determined based on the displacement data detected by the chest displacement sensor device within the target time interval.

[0074] At the same time, each second force data can be screened according to the target time interval to obtain the second sub-data corresponding to each group of second force data, that is, the second sub-data is determined based on the data detected by the corresponding target detection device within the target time interval.

[0075] Among them, in the process of determining the abnormal detection result of the chest displacement sensor device based on the comparison result of the first force data and the second force data, the abnormal detection result of the chest displacement sensor device can be determined based on the comparison result of the first sub-data and the second sub-data, thereby effectively ensuring the reliability of the abnormal detection result of the chest displacement sensor device.

[0076] In a feasible implementation manner, determining the abnormal detection result of the chest displacement sensor device based on the comparison result of the first sub-data and the second sub-data includes:

[0077] generating a first curve graph based on the first sub-data, and generating a second curve graph based on the second sub-data;

[0078] Based on the similarity between the first curve graph and the second curve graph, an abnormality detection result of the chest displacement sensing device is determined.

[0079] Specifically, the first sub-data and the second sub-data may both be continuous values. In real time, the first sub-data and the second sub-data may be sequentially input into a preset drawing tool (e.g., Python, Matlab), etc., to obtain a first curve graph corresponding to the first sub-data and a second curve graph corresponding to each second sub-data. The first sub-data and the second sub-data may also be sampled and processed respectively to obtain first sampled data corresponding to the first sub-data and second sampled data corresponding to each second sub-data, and curve fitting may be performed on the first sampled data to obtain a first curve graph, and curve fitting may be performed on the second sampled data to obtain a second curve graph.

[0080] It can be understood that before generating the first curve graph based on the first sub-data and generating the second curve graph based on the second sub-data, the first sub-data and the second sub-data can be filtered respectively to avoid the influence of factors such as noise interference in the data detection process of the chest displacement sensor device and the target detection device on the validity of the first sub-data and the second sub-data, thereby further improving the validity of the abnormal detection results of the chest displacement sensor device.

[0081] After obtaining the first curve graph and the second curve graph, the similarity between the first curve graph and the second curve graph can be obtained, and the abnormal detection result of the chest displacement sensor device can be determined based on the similarity between the first curve graph and the second curve graph. For example, the similarity between the first curve graph and the second curve graph can be automatically identified by an image recognition model such as a convolutional neural network, and the similarity between the first curve graph and the second curve graph can also be determined based on the distance information between the first curve graph and the second curve graph (such as the Euclidean distance, etc.), which can be set according to actual needs.

[0082] Among them, in the vehicle safety collision test, the data detected by different detection devices have a certain time delay. For example, after the tension of the seat belt acts on the chest of the collision dummy, the chest acceleration and chest displacement will have a certain lag relative to the tension of the seat belt. Therefore, before determining the similarity between the first curve graph and the second curve graph based on the distance information between the first curve graph and the second curve graph, the first curve graph and / or the second curve graph can also be translated so that the peak point or starting point of the first curve graph and the second curve graph are aligned, thereby effectively avoiding the influence of the time delay between the data detected by the chest displacement sensor device and the data detected by the target detection device on the accuracy of the determination result of the similarity between the first curve graph and the second curve graph, and further improving the effectiveness of the abnormal detection result of the chest displacement sensor device.

[0083] In a feasible implementation manner, determining the abnormal detection result of the chest displacement sensor device based on the similarity between the first curve graph and the second curve graph includes:

[0084] When the similarity is greater than or equal to a preset similarity threshold, it is determined that there is no abnormality in the chest displacement sensor device;

[0085] When the similarity is less than the preset similarity threshold, it is determined that the chest displacement sensor device is abnormal.

[0086] Specifically, considering that there are certain errors in the data detected by different detection devices, in implementation, a similarity threshold can be set, and the similarity between the first curve graph and the second curve graph can be compared with the similarity threshold to determine whether there is an abnormality in the displacement sensing device based on the comparison result.

[0087] For example, when the similarity is greater than or equal to the similarity threshold, it can be determined that there is no abnormality in the chest displacement sensor device. When the similarity is less than the similarity threshold, it can be determined that there is an abnormality in the chest displacement sensor device, thereby enabling rapid and effective abnormality detection of the chest displacement sensor device.

[0088] In a feasible implementation manner, the process of determining the first force data includes:

[0089] The first force data is obtained by multiplying the displacement data detected by the chest displacement sensor device with the chest stiffness data of the collision dummy.

[0090] Specifically, the chest stiffness data of the crash dummy may be preset, for example, a plurality of detection values ​​of the chest stiffness of the crash dummy may be obtained at a standard test temperature, and the chest stiffness data of the crash dummy may be determined based on the detection values. It is understandable that the chest stiffness data of the crash dummy may also be periodically updated, for example, after the crash dummy completes a specified number of crash tests, the chest stiffness data of the crash dummy is updated once, thereby effectively ensuring the validity of the first force data.

[0091] In implementation, the displacement data detected by the chest displacement sensor device may be multiplied by the chest stiffness data of the collision dummy to obtain the first force data, for example, F s =K·S, S is the displacement data detected by the chest displacement sensor of the collision dummy, K is the chest stiffness data of the collision dummy, F s The theoretical value of the force required to generate the displacement data S is obtained, so that the first force data can be determined quickly and effectively.

[0092] In a feasible implementation manner, the second force data includes first target data determined based on tension data detected by a seat belt tension detection device of the vehicle, and / or second target data determined based on acceleration data detected by a chest acceleration sensor device of the collision dummy, and the second target data is used to characterize a theoretical value of the force required to generate the acceleration data.

[0093] Specifically, the second force data may include first target data and / or second target data. The first target data may be determined based on the tension data F detected by the seat belt tension detection device of the vehicle, and the second target data may be determined based on the acceleration data detected by the chest acceleration sensor device of the collision dummy. The second target data may be used to characterize the theoretical value of the force required to generate the detected acceleration data, that is, ideally, the magnitude of the force required to act on the chest of the collision dummy when generating the detected acceleration data, so that the chest displacement sensor device of the collision dummy can be detected for abnormality based on the data detected by the existing detection devices of the vehicle and / or the collision dummy, without the need to add other detection equipment.

[0094] In which, when the second force data includes the first target data or the second target data, the abnormal detection result of the chest displacement sensor device can be determined directly based on the comparison result of the first force data and the second force data.

[0095] In the case where the second force data includes both the first target data and the second target data, the first target data can be compared with the second target data to determine whether the first target data and the second target data are consistent with each other based on the comparison result of the first target data and the second target data. For example, whether the first target data and the second target data are consistent can be determined based on the comparison result of the similarity between the second curve graph corresponding to the first target data and the second curve graph corresponding to the second target data within the target time interval and a preset similarity threshold.

[0096] If the first target data does not match the second target data, the test result of the vehicle safety collision test can be considered invalid, and the vehicle safety collision test shall be conducted again after the chest acceleration sensor device of the collision dummy and the seat belt tension detection device of the vehicle are maintained.

[0097] If the first target data matches the second target data, the abnormal detection result of the chest displacement sensor device can be determined based on the comparison result of the first force data with any one of the first target data and the second target data; the first comparison result of the first force data with the first target data and the second comparison result of the first force data with the second target data can also be obtained respectively, and when there is at least one comparison result in the first comparison result and the second comparison result indicating that there is no abnormality in the chest displacement sensor device, it is determined that there is no abnormality in the chest displacement sensor device; otherwise, it is determined that there is an abnormality in the chest displacement sensor device, thereby being able to quickly and effectively perform abnormal detection on the chest displacement sensor device without increasing the cost of the detection equipment.

[0098] In a feasible implementation manner, the process of determining the second target data includes:

[0099] The acceleration data detected by the chest acceleration sensor device is multiplied by the chest mass data of the collision dummy to obtain the second target data.

[0100] Specifically, the chest mass data of the crash dummy may be preconfigured, wherein the chest mass data of the crash dummy may be determined according to the type of the crash dummy, for example, the standard chest mass of a 50 percentile male crash dummy is 18.73 kg, and the standard chest mass of a 5 percentile female crash dummy is 12 kg.

[0101] In implementation, the acceleration data detected by the chest acceleration sensor device may be multiplied by the chest mass data of the collision dummy to obtain the second force data, for example, F a =m 胸 a, a is the acceleration data detected by the chest acceleration sensor of the collision dummy, m 胸 is the chest mass data of the collision dummy, F aThe theoretical value of the force required to generate the acceleration data a is obtained, so that the second force data can be determined quickly and effectively.

[0102] The following uses an example in which the second force data includes both the first target data and the second target data to illustrate the effect of the present application.

[0103] Among them, the first force data (F s ) in the entire collision test, the first curve corresponding to the first target data (F), and the second curve corresponding to the second target data (F a ) corresponds to the second curve graph, the airbag contacts the collision dummy 37ms after the vehicle collides, therefore, the time interval between 0 and 37ms can be used as the target time interval, so as to compare the first curve graph and the second curve graphs in the target time interval, and determine the abnormal detection result of the chest displacement sensor device based on the comparison result.

[0104] Figure 2 is a schematic diagram for comparing a first curve graph corresponding to the first force data and a second curve graph corresponding to each second force data, Figure 2 It can be seen that in the time interval between 0 and 37 ms, F s The corresponding curve graph and F a The corresponding curves are basically overlapped, and F s The corresponding curve and F a After the corresponding curve graph is shifted to the left, it can overlap with the curve graph corresponding to F, that is, F s The corresponding curve graph, F a The corresponding curve graph and the curve graph corresponding to F are highly similar, and it can be determined that there is no abnormality in the chest displacement sensor device.

[0105] Figure 3 is another comparison diagram of the first curve graph corresponding to the first force data and the second curve graph corresponding to each second force data, Figure 3 It can be seen that in the time interval between 0 and 37 ms, F s The corresponding curve graph and F a The corresponding curve graphs have poor similarity, and F s The corresponding curve and F a After the corresponding curve graph is shifted to the left, F a The corresponding curve graph can be overlapped with the curve graph corresponding to F, and F s The corresponding curve graph cannot overlap with the curve graph corresponding to F, that is, F a The corresponding curve graph is similar to the curve graph of F, while F s The corresponding curve graph and F aThe similarity between the corresponding curve graph and the curve graph corresponding to F is relatively low, and it can be determined that there is an abnormality in the chest displacement sensor device.

[0106] Thus, abnormality detection of the chest displacement sensor device can be performed quickly and effectively.

[0107] Exemplary Devices

[0108] In an exemplary embodiment of the present specification, a crash dummy chest sensor device abnormality detection device is also provided, such as Figure 4 As shown, including:

[0109] The first processing module 401 is used to obtain first force data and second force data of the chest of the collision dummy in the vehicle safety collision test; wherein the first force data is determined based on the displacement data detected by the chest displacement sensor device of the collision dummy, and is used to represent the theoretical value of the force required to generate the displacement data; the second force data is determined based on the data detected by the target detection device, and the target detection device is a detection device other than the chest displacement sensor device;

[0110] The second processing module 402 is used to determine the abnormality detection result of the chest displacement sensor device based on the comparison result of the first force data and the second force data.

[0111] In a feasible implementation manner, the second processing module 402 is specifically configured to:

[0112] The first force data and the second force data are respectively screened according to a target time interval to obtain first sub-data corresponding to the first force data and second sub-data corresponding to the second force data;

[0113] Based on the comparison result of the first sub-data and the second sub-data, an abnormality detection result of the chest displacement sensing device is determined.

[0114] In a feasible implementation manner, the second processing module 402 is further configured to:

[0115] The target time interval is determined based on a time interval during which a theoretical value of the first force data is equal to a theoretical value of the second force data after the vehicle collides.

[0116] In a feasible implementation manner, the second processing module 402 is specifically configured to:

[0117] generating a first curve graph based on the first sub-data, and generating a second curve graph based on the second sub-data;

[0118] Based on the similarity between the first curve graph and the second curve graph, an abnormality detection result of the chest displacement sensing device is determined.

[0119] In a feasible implementation manner, the second processing module 402 is specifically configured to:

[0120] When the similarity is greater than or equal to a preset similarity threshold, it is determined that there is no abnormality in the chest displacement sensor device;

[0121] When the similarity is less than the preset similarity threshold, it is determined that the chest displacement sensor device is abnormal.

[0122] In a feasible implementation manner, the first processing module 401 is specifically configured to:

[0123] The first force data is obtained by multiplying the displacement data detected by the chest displacement sensor device with the chest stiffness data of the collision dummy.

[0124] In a feasible implementation manner, the second force data includes first target data determined based on tension data detected by a seat belt tension detection device of the vehicle, and / or second target data determined based on acceleration data detected by a chest acceleration sensor device of the collision dummy, and the second target data is used to characterize a theoretical value of the force required to generate the acceleration data.

[0125] In a feasible implementation manner, the first processing module 401 is specifically configured to:

[0126] The acceleration data detected by the chest acceleration sensor device is multiplied by the chest mass data of the collision dummy to obtain the second target data.

[0127] The crash dummy chest sensor device abnormality detection device provided in this embodiment belongs to the same application concept as the crash dummy chest sensor device abnormality detection method provided in the above embodiments of this application, and can execute the crash dummy chest sensor device abnormality detection method provided in any of the above embodiments of this application, and has the corresponding functional modules and beneficial effects of executing the crash dummy chest sensor device abnormality detection method. For technical details not fully described in this embodiment, please refer to the specific processing content of the crash dummy chest sensor device abnormality detection method provided in the above embodiments of this application, and will not be repeated here.

[0128] Exemplary Devices

[0129] In an exemplary embodiment of the present specification, an electronic device is also provided, comprising at least one processor and at least one memory, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the method for detecting abnormality of a collision dummy chest sensor device as described in any of the above embodiments is implemented.

[0130] Exemplary computer program products and storage media

[0131] In addition to the above-mentioned methods and apparatus, the method for detecting abnormalities in a crash dummy chest sensor device provided in the embodiments of this specification may also be a computer program product, which includes computer program instructions, which, when executed by a processor, cause the processor to execute the steps of the method for detecting abnormalities in a crash dummy chest sensor device according to various embodiments of this specification described in the above-mentioned “Exemplary Methods” section of this specification.

[0132] The computer program product can be written in any combination of one or more programming languages ​​to write program codes for executing the operations of the embodiments of this specification, and the programming languages ​​include object-oriented programming languages, such as Java, C++, etc., and also include conventional procedural programming languages, such as "C" language or similar programming languages.

[0133] In addition, an embodiment of the present specification also provides a computer-readable storage medium on which a computer program is stored, and the computer program is executed by a processor to perform the steps of the method for detecting abnormalities in the chest sensor device of a collision dummy according to various embodiments of the present specification described in the above "Exemplary Method" section of the present specification.

[0134] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this specification can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0135] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0136] The above-mentioned embodiments only express several implementation methods of this specification, and the descriptions are relatively specific and detailed, but they cannot be understood as limiting the scope of the solutions provided by the embodiments of this specification. It should be pointed out that for ordinary technicians in this field, several modifications and improvements can be made without departing from the concept of this specification, which all belong to the protection scope of this specification. Therefore, the protection scope of the patent of this specification shall be based on the attached claims.

Claims

1. A method for detecting abnormality of a collision dummy chest sensor device, characterized in that: include: Acquire first force data and second force data of the chest of a collision dummy in a vehicle safety collision test; wherein the first force data is determined based on displacement data detected by a chest displacement sensor device of the collision dummy, and is used to characterize a theoretical value of the force required to generate the displacement data; the second force data is determined based on data detected by a target detection device, and the target detection device is a detection device other than the chest displacement sensor device; Based on a comparison result of the first force data and the second force data, an abnormality detection result of the chest displacement sensor device is determined.

2. The method according to claim 1, characterized in that Determining an abnormality detection result of the chest displacement sensor device based on a comparison result of the first force data and the second force data includes: The first force data and the second force data are respectively screened according to a target time interval to obtain first sub-data corresponding to the first force data and second sub-data corresponding to the second force data; Based on the comparison result of the first sub-data and the second sub-data, an abnormality detection result of the chest displacement sensing device is determined.

3. The method according to claim 2, characterized in that The process of determining the target time interval includes: The target time interval is determined based on a time interval during which a theoretical value of the first force data is equal to a theoretical value of the second force data after the vehicle collides.

4. The method according to claim 2, characterized in that: Determining an abnormality detection result of the chest displacement sensor device based on a comparison result of the first sub-data and the second sub-data includes: generating a first curve graph based on the first sub-data, and generating a second curve graph based on the second sub-data; Based on the similarity between the first curve graph and the second curve graph, an abnormality detection result of the chest displacement sensing device is determined.

5. The method according to claim 4, characterized in that Determining an abnormal detection result of the chest displacement sensor device based on the similarity between the first curve graph and the second curve graph includes: When the similarity is greater than or equal to a preset similarity threshold, it is determined that there is no abnormality in the chest displacement sensor device; When the similarity is less than the preset similarity threshold, it is determined that the chest displacement sensor device is abnormal.

6. The method according to claim 1, characterized in that The process of determining the first force data includes: The first force data is obtained by multiplying the displacement data detected by the chest displacement sensor device with the chest stiffness data of the collision dummy.

7. The method according to any one of claims 1 to 6, characterized in that: The second force data includes first target data determined based on tension data detected by a seat belt tension detection device of the vehicle, and / or second target data determined based on acceleration data detected by a chest acceleration sensor device of the collision dummy, wherein the second target data is used to characterize a theoretical value of the force required to generate the acceleration data.

8. The method according to claim 7, characterized in that The process of determining the second target data includes: The acceleration data detected by the chest acceleration sensor device is multiplied by the chest mass data of the collision dummy to obtain the second target data.

9. A crash dummy chest sensor device abnormality detection device, characterized in that: include: a first processing module, for obtaining first force data and second force data on the chest of a collision dummy in a vehicle safety collision test; wherein the first force data is determined based on displacement data detected by a chest displacement sensor device of the collision dummy, and is used to characterize a theoretical value of the force required to generate the displacement data; and the second force data is determined based on data detected by a target detection device, and the target detection device is a detection device other than the chest displacement sensor device; The second processing module is used to determine the abnormal detection result of the chest displacement sensor device based on the comparison result of the first force data and the second force data.

10. An electronic device, characterized in that: The method comprises at least one processor and at least one memory, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the method for detecting abnormality of a crash dummy chest sensor device according to any one of claims 1 to 8 is implemented.

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