Active engine hood data processing method and device

Abstract

The invention relates to the field of automobile part testing, and discloses an active engine hood data processing method and device, and the method comprises the steps: obtaining whole vehicle message data and pedestrian protection sensing data in parallel; and the whole vehicle message data and the pedestrian protection sensing data are transmitted to a processing terminal, so that the processing terminal diagnoses the whole vehicle message data and the pedestrian protection sensing data according to the engine hood data abnormity rule, and a diagnosis result is obtained. According to the invention, the vehicle message data and the pedestrian protection sensing data are acquired in a parallel mode, so that the acquisition efficiency of the test data is greatly improved; the whole vehicle message data and the pedestrian protection sensing data are rapidly diagnosed through the engine hood data abnormity rule, the test efficiency is greatly improved, and compared with manual identification, the error rate is greatly reduced.

Description

Technical Field

[0001] The invention relates to the field of automobile component testing, and in particular to an active hood data processing method and device. Background Art

[0002] With the growth of car ownership and the increase of urban population density, the importance of pedestrian safety in road traffic has become increasingly prominent. Among existing automobile safety technologies, active pop-up hoods are important devices for protecting pedestrians. However, in the development and calibration process of active hoods, it is necessary to consider a variety of working conditions and misuse scenarios, such as small animals, trash cans, bicycles, etc., while also taking into account factors such as temperature and vehicle speed, resulting in a large calibration matrix and numerous data collection times. The existing data collection method is not only inefficient, but also unable to identify anomalies and causes in real time during the test process, requiring manual offline analysis, which seriously affects the test progress and vehicle project development.

[0003] Therefore, an efficient active hood data processing method is urgently needed to improve the test efficiency and safety of the active pop-up hood. Summary of the invention

[0004] Based on this, it is necessary to provide an active hood data processing method and device to address the above technical problems, so as to improve the test efficiency and safety of the active pop-up hood.

[0005] A method for processing active mask data, comprising: Acquire vehicle message data and pedestrian protection sensor data in parallel; The whole vehicle message data and the pedestrian protection sensor data are transmitted to a processing terminal, so that the processing terminal diagnoses the whole vehicle message data and the pedestrian protection sensor data according to the abnormal rules of the mask data to obtain a diagnosis result.

[0006] Optionally, the hair mask data anomaly rule includes a first hair mask data anomaly rule; The processing terminal diagnoses the vehicle message data and the pedestrian protection sensor data according to the mask data abnormality rule to obtain a diagnosis result, including: Generate a dependent variable-independent variable curve according to the vehicle message data and the pedestrian protection sensor data; Determine whether the vehicle message data and the pedestrian protection sensor data are empty, and whether the dependent variable in the dependent variable-independent variable curve is continuously zero according to the first mask data abnormality rule; If the vehicle message data and the pedestrian protection sensor data are empty, or the dependent variable in the dependent variable-independent variable curve is continuously zero, a first diagnostic result is generated; the first diagnostic result includes data abnormalities of the collection device, sensor abnormalities, or trigger switch abnormalities.

[0007] Optionally, the hair mask data anomaly rule includes a second hair mask data anomaly rule; The processing terminal diagnoses the vehicle message data and the pedestrian protection sensor data according to the mask data abnormality rule to obtain a diagnosis result, including: Determining the vehicle operating condition according to the vehicle message data; extracting acceleration and / or pressure values ​​from the pedestrian protection sensor data; Determining whether the positive and negative directions of the acceleration and / or pressure values ​​are consistent with the vehicle operating conditions according to the second hood data abnormality rule; If the positive and negative directions of the acceleration and / or pressure values ​​are inconsistent with the vehicle operating conditions, a second diagnostic result is generated; the second diagnostic result includes a sensor installation error or a sensor abnormality.

[0008] Optionally, the hair mask data anomaly rule includes a third hair mask data anomaly rule; The processing terminal diagnoses the vehicle message data and the pedestrian protection sensor data according to the mask data abnormality rule to obtain a diagnosis result, including: Generate a dependent variable-independent variable curve according to the vehicle message data and the pedestrian protection sensor data; Determining whether the initial value of the dependent variable in the dependent variable-independent variable curve is zero according to the third mask data abnormality rule; If the initial value of the dependent variable in the dependent variable-independent variable curve is not zero, a third diagnostic result is generated; the third diagnostic result includes a trigger switch abnormality or a data acquisition setting error.

[0009] Optionally, the hair mask data anomaly rule includes a fourth hair mask data anomaly rule; The processing terminal diagnoses the vehicle message data and the pedestrian protection sensor data according to the mask data abnormality rule to obtain a diagnosis result, including: generating a dependent variable-independent variable curve according to the vehicle message data and the pedestrian protection sensor data; determining a vehicle operating condition according to the vehicle message data; Processing the vehicle operating condition and the dependent variable-independent variable curve according to the fourth hood data abnormality rule; If the vehicle operating condition is a low-speed condition or a lightweight condition, and the dependent variable-independent variable curve shows a curve clipping wave, a fourth diagnostic result is generated, and the fourth diagnostic result includes data abnormality of the acquisition device or sensor abnormality.

[0010] Optionally, the hair mask data anomaly rule includes a fifth hair mask data anomaly rule; The processing terminal diagnoses the vehicle message data and the pedestrian protection sensor data according to the mask data abnormality rule to obtain a diagnosis result, including: generating a dependent variable-independent variable curve according to the vehicle message data and the pedestrian protection sensor data; determining a vehicle operating condition according to the vehicle message data; Processing the vehicle operating condition and the dependent variable-independent variable curve according to the fifth hood data abnormality rule; If the vehicle operating condition is a high-speed condition or a heavyweight condition, and the dependent variable in the first half of the dependent variable-independent variable curve is less than the first preset threshold, a fifth diagnostic result is generated, and the fifth diagnostic result includes data abnormality of the acquisition device or sensor abnormality.

[0011] Optionally, the hair mask data anomaly rule includes a sixth hair mask data anomaly rule; The processing terminal diagnoses the vehicle message data and the pedestrian protection sensor data according to the mask data abnormality rule to obtain a diagnosis result, including: Generate a dependent variable-independent variable curve according to the vehicle message data and the pedestrian protection sensor data; Processing the vehicle operating condition and the dependent variable-independent variable curve according to the sixth hood data abnormality rule; If the dependent variable in the second half of the dependent variable-independent variable curve has an abnormal peak or is lower than the second preset threshold, a sixth diagnostic result is generated, and the sixth diagnostic result includes data abnormality of the acquisition device, sensor abnormality, sensor detachment or connection harness detachment.

[0012] Optionally, the hair mask data anomaly rule includes a seventh hair mask data anomaly rule; The processing terminal diagnoses the vehicle message data and the pedestrian protection sensor data according to the mask data abnormality rule to obtain a diagnosis result, including: generating a dependent variable-independent variable curve according to the vehicle message data and the pedestrian protection sensor data; determining the vehicle operating condition according to the vehicle message data; extracting acceleration from the pedestrian protection sensor data; Processing the vehicle operating condition, the dependent variable-independent variable curve and the acceleration according to the seventh hood data abnormality rule; If the acceleration does not match the whole vehicle operating condition, and the dependent variable-independent variable curve does not match the whole vehicle operating condition, a seventh diagnostic result is generated, and the seventh diagnostic result includes an error in the channel setting of the acquisition device and an error in the sensor position.

[0013] An active hood data processing device, comprising: A collection device for acquiring vehicle message data and pedestrian protection sensor data in parallel; The processing terminal is used to obtain the whole vehicle message data and the pedestrian protection sensor data from the collection device; diagnose the whole vehicle message data and the pedestrian protection sensor data according to the abnormal rules of the mask data to obtain the diagnosis result.

[0014] Optionally, the acquisition device includes a bus receiver, a PSI transceiver, and a sensor connected to the PSI transceiver; the bus receiver is connected to the vehicle bus; The acquisition device acquires the pedestrian protection sensing data from the sensor via the PSI transceiver; The acquisition device obtains the whole vehicle message data from the vehicle bus through the bus receiver.

[0015] The above-mentioned active hood data processing method and device adopt a parallel method to obtain the whole vehicle message data and pedestrian protection sensor data, which greatly improves the efficiency of obtaining test data; the whole vehicle message data and pedestrian protection sensor data are quickly diagnosed through the hood data anomaly rules, which greatly improves the test efficiency. Compared with manual identification, the error rate is greatly reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0017] Figure 1 It is a flowchart of a method for processing active mask data in one embodiment of the present invention; Figure 2 It is a structural schematic diagram of an active mask data processing device in one embodiment of the present invention; Figure 3 It is a structural schematic diagram of a collection device in one embodiment of the present invention. DETAILED DESCRIPTION

[0018] 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 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.

[0019] In one embodiment, if Figure 1 As shown, a method for processing active mask data is provided, comprising the following steps: S10, acquiring vehicle message data and pedestrian protection sensor data in parallel; S20, transmitting the whole vehicle message data and the pedestrian protection sensor data to a processing terminal, so that the processing terminal diagnoses the whole vehicle message data and the pedestrian protection sensor data according to a mask data abnormality rule to obtain a diagnosis result.

[0020] It is understandable that the active hood data processing method provided in this embodiment is used to improve the test efficiency and safety of the active pop-up hood. The active hood data processing method includes two stages, namely, a data collection stage, namely step S10, and a data processing stage, namely step S20.

[0021] During the data collection phase, the vehicle is powered on, and then the collection device is powered. At this time, the collection device can send and receive vehicle message data through the vehicle bus. Vehicle message data refers to data information transmitted through the CAN bus in the internal network of the car. Target objects such as the legs of pedestrian protection dummies, simulated small animals, and trash cans are guided by the traction system to hit the front bumper position of the vehicle, triggering the strip switch. The I / O signal generated by the strip switch is transmitted to the collection device as a signal mark to start recording the test data. At this time, the vehicle message data and pedestrian protection sensor data after the start of the active pop-up hood test are obtained in parallel through the collection device. Pedestrian protection sensor data refers to the data collected by each sensor connected to the collection device, including but not limited to the pressure value collected by the pedestrian protection collision sensor and the pressure value collected by the pedestrian protection pressure hose.

[0022] In the data processing stage, that is, after the active pop-up hood test is completed, the vehicle message data and pedestrian protection sensor data can be transmitted to the processing terminal by wire or wireless means. The processing terminal can be a desktop computer, a laptop computer or other computer equipment. After receiving the vehicle message data and pedestrian protection sensor data, the processing device aligns the data time axis of each sensor channel with the zero moment of collision (i.e., the moment when the strip switch generates an I / O signal), and deletes the data that exceeds the predetermined time length, which is irrelevant to the test. The predetermined time length can be set according to actual needs, such as 500ms. Then, the processing terminal diagnoses the processed vehicle message data and pedestrian protection sensor data according to the hood data anomaly rule to obtain the diagnosis result. The hood data anomaly rule is a rule based on the summary of historical tests, which can timely diagnose the abnormal situation of the test and generate the diagnosis result, greatly improving the test efficiency of the active pop-up hood test, and greatly reducing the error rate compared with manual identification.

[0023] This embodiment adopts a parallel method to obtain the whole vehicle message data and pedestrian protection sensor data, which greatly improves the efficiency of obtaining test data; the whole vehicle message data and pedestrian protection sensor data are quickly diagnosed by issuing mask data anomaly rules, which greatly improves the test efficiency. Compared with manual identification, the error rate is greatly reduced.

[0024] Optionally, the hair mask data anomaly rule includes a first hair mask data anomaly rule; In step S20, the processing terminal diagnoses the vehicle message data and the pedestrian protection sensor data according to the mask data abnormality rule to obtain a diagnosis result, including: S2011, generating a dependent variable-independent variable curve according to the vehicle message data and the pedestrian protection sensor data; S2012, judging whether the vehicle message data and the pedestrian protection sensor data are empty according to the first mask data abnormality rule, and whether the dependent variable in the dependent variable-independent variable curve is continuously zero; S2013. If the vehicle message data and the pedestrian protection sensor data are empty, or the dependent variable in the dependent variable-independent variable curve is continuously zero, a first diagnostic result is generated; the first diagnostic result includes data abnormality of the collection device, sensor abnormality or trigger switch abnormality.

[0025] Understandably, a dependent variable-independent variable curve, such as an acceleration-time curve or a pressure value-time curve, can be generated based on the vehicle message data and pedestrian protection sensor data. According to the first hood data abnormality rule, whether the vehicle message data and pedestrian protection sensor data are empty, and whether the dependent variable in the dependent variable-independent variable curve is continuously zero, is diagnosed. If there is data missing in the vehicle message data and pedestrian protection sensor data, the vehicle message data and pedestrian protection sensor data are determined to be empty, and the first diagnostic result is generated at the same time; or, if the dependent variable in the dependent variable-independent variable curve is continuously zero, the first diagnostic result is generated. Only when the vehicle message data and pedestrian protection sensor data are not empty, and the dependent variable in the dependent variable-independent variable curve is not continuously zero, the first diagnostic result is not generated. The first diagnostic result includes data abnormality of the acquisition device, sensor abnormality or trigger switch abnormality. Here, the trigger switch abnormality refers to the strip switch trigger abnormality.

[0026] This embodiment performs a rapid diagnosis on the vehicle message data and pedestrian protection sensor data according to the first hood data abnormality rule, and can generate a first diagnosis result to evaluate whether the active pop-up hood test is wrong.

[0027] Optionally, the hair mask data anomaly rule includes a second hair mask data anomaly rule; In step S20, the processing terminal diagnoses the vehicle message data and the pedestrian protection sensor data according to the mask data abnormality rule to obtain a diagnosis result, including: S2021. Determine the vehicle operating condition according to the vehicle message data; S2022, extracting acceleration and / or pressure values ​​from the pedestrian protection sensor data; S2023, judging whether the positive and negative directions of the acceleration and / or pressure values ​​are consistent with the vehicle operating conditions according to the second hood data abnormality rule; S2024. If the positive and negative directions of the acceleration and / or pressure values ​​do not match the vehicle operating conditions, a second diagnostic result is generated; the second diagnostic result includes a sensor installation error or a sensor abnormality.

[0028] Understandably, the vehicle operating condition, such as high-speed operating condition, low-speed operating condition, etc., can be determined based on the vehicle message data. The acceleration and / or pressure value is extracted from the pedestrian protection sensor data. According to the second hood data abnormality rule, it is determined whether the positive and negative directions of the acceleration and / or pressure values ​​are consistent with the vehicle operating condition. If they are consistent, the second diagnostic result is not generated. If they are not consistent, the second diagnostic result is generated. The second diagnostic result includes a sensor installation error or a sensor abnormality. For example, a sensor installation error may be a reverse wiring connection.

[0029] This embodiment performs a rapid diagnosis on the vehicle message data and pedestrian protection sensor data according to the second hood data abnormality rule, and can generate a second diagnosis result to evaluate whether the active pop-up hood test is wrong.

[0030] Optionally, the hair mask data anomaly rule includes a third hair mask data anomaly rule; In step S20, the processing terminal diagnoses the vehicle message data and the pedestrian protection sensor data according to the mask data abnormality rule to obtain a diagnosis result, including: S2031, generating a dependent variable-independent variable curve according to the vehicle message data and the pedestrian protection sensor data; S2032, judging whether the initial value of the dependent variable in the dependent variable-independent variable curve is zero according to the third mask data abnormality rule; S2033. If the initial value of the dependent variable in the dependent variable-independent variable curve is not zero, a third diagnostic result is generated; the third diagnostic result includes a trigger switch abnormality or a data acquisition setting error.

[0031] Understandably, a dependent variable-independent variable curve, such as an acceleration-time curve, or a pressure value-time curve, can be generated based on the vehicle message data and pedestrian protection sensor data. According to the third hood data abnormality rule, it is determined whether the initial value of the dependent variable in the dependent variable-independent variable curve is zero. If it is zero, it means that the initial value of the dependent variable is normal; if it is not zero, it means that the initial value of the dependent variable is abnormal, and a third diagnostic result is generated at the same time. The third diagnostic result includes a trigger switch abnormality or a data acquisition setting error. In some examples, the vertical coordinate of the dependent variable-independent variable curve may not start at 0 due to a data acquisition setting error.

[0032] This embodiment performs a rapid diagnosis on the vehicle message data and pedestrian protection sensor data according to the third hood data abnormality rule, and can generate a third diagnosis result to evaluate whether the active pop-up hood test is wrong.

[0033] Optionally, the hair mask data anomaly rule includes a fourth hair mask data anomaly rule; In step S20, the processing terminal diagnoses the vehicle message data and the pedestrian protection sensor data according to the mask data abnormality rule to obtain a diagnosis result, including: S2041, generating a dependent variable-independent variable curve according to the vehicle message data and the pedestrian protection sensor data; determining a vehicle operating condition according to the vehicle message data; S2042, processing the vehicle operating condition and the dependent variable-independent variable curve according to the fourth hood data abnormality rule; S2043. If the vehicle operating condition is a low-speed condition or a lightweight condition, and the dependent variable-independent variable curve shows a curve clipping wave, a fourth diagnostic result is generated, and the fourth diagnostic result includes data abnormality of the acquisition device or sensor abnormality.

[0034] Understandably, a dependent variable-independent variable curve, such as an acceleration-time curve, or a pressure value-time curve, can be generated based on the vehicle message data and pedestrian protection sensor data. The vehicle operating condition, such as high-speed operating condition, low-speed operating condition, etc., can be determined based on the vehicle message data. The vehicle operating condition and the dependent variable-independent variable curve are diagnosed according to the fourth hood data abnormality rule. If the vehicle operating condition is a low-speed condition or a lightweight condition, and the dependent variable-independent variable curve has a curve clipping, a fourth diagnostic result is generated. Otherwise, the fourth diagnostic result is not generated. The fourth diagnostic result includes data abnormalities of the acquisition device or sensor abnormalities. When a curve clipping occurs, it means that the dependent variable exceeds the range of the sensor.

[0035] This embodiment performs a rapid diagnosis on the vehicle message data and pedestrian protection sensor data according to the fourth hood data abnormality rule, and can generate a fourth diagnosis result to evaluate whether the active pop-up hood test is wrong.

[0036] Optionally, the hair mask data anomaly rule includes a fifth hair mask data anomaly rule; In step S20, the processing terminal diagnoses the vehicle message data and the pedestrian protection sensor data according to the mask data abnormality rule to obtain a diagnosis result, including: S2051, generating a dependent variable-independent variable curve according to the vehicle message data and the pedestrian protection sensor data; determining a vehicle operating condition according to the vehicle message data; S2052, processing the vehicle operating condition and the dependent variable-independent variable curve according to the fifth hood data abnormality rule; S2053. If the vehicle operating condition is a high-speed condition or a heavyweight condition, and the dependent variable in the first half of the dependent variable-independent variable curve is less than a first preset threshold, a fifth diagnostic result is generated, and the fifth diagnostic result includes data abnormality of the acquisition device or sensor abnormality.

[0037] Understandably, a dependent variable-independent variable curve, such as an acceleration-time curve, or a pressure value-time curve, can be generated based on the vehicle message data and pedestrian protection sensor data. The vehicle operating condition, such as high-speed operating condition, low-speed operating condition, etc., can be determined based on the vehicle message data. The vehicle operating condition and the dependent variable-independent variable curve are diagnosed according to the fifth hood data anomaly rule. If the vehicle operating condition is a high-speed condition or a heavyweight condition, and the dependent variable in the first half of the dependent variable-independent variable curve is less than the first preset threshold, then the fifth diagnostic result is generated. Otherwise, the fifth diagnostic result is not generated. The fifth diagnostic result includes data anomalies of the acquisition device or sensor anomalies. The first preset threshold can be set according to actual needs. The dependent variable in the first half of the dependent variable-independent variable curve is less than the first preset threshold, indicating that the value of the dependent variable is too low.

[0038] This embodiment performs a rapid diagnosis on the vehicle message data and pedestrian protection sensor data according to the fifth hood data abnormality rule, and can generate a fifth diagnosis result to evaluate whether the active pop-up hood test is wrong.

[0039] Optionally, the hair mask data anomaly rule includes a sixth hair mask data anomaly rule; In step S20, the processing terminal diagnoses the vehicle message data and the pedestrian protection sensor data according to the mask data abnormality rule to obtain a diagnosis result, including: S2061, generating a dependent variable-independent variable curve according to the vehicle message data and the pedestrian protection sensor data; determining a vehicle operating condition according to the vehicle message data; S2062, processing the vehicle operating condition and the dependent variable-independent variable curve according to the sixth hood data abnormality rule; S2063. If the dependent variable in the second half of the dependent variable-independent variable curve has an abnormal peak or is lower than the second preset threshold, a sixth diagnostic result is generated, and the sixth diagnostic result includes data abnormality of the acquisition device, sensor abnormality, sensor detachment, or connection harness detachment.

[0040] Understandably, a dependent variable-independent variable curve, such as an acceleration-time curve or a pressure value-time curve, can be generated based on the vehicle message data and pedestrian protection sensor data. The vehicle operating condition, such as high-speed operating condition, low-speed operating condition, etc., can be determined based on the vehicle message data. The vehicle operating condition and the dependent variable-independent variable curve are diagnosed according to the sixth hood data abnormality rule. If the vehicle operating condition is a high-speed operating condition or a heavyweight operating condition, and the dependent variable in the second half of the dependent variable-independent variable curve is less than the second preset threshold, then the sixth diagnostic result is generated. Otherwise, the sixth diagnostic result is not generated. The sixth diagnostic result includes data abnormality of the acquisition device, sensor abnormality, sensor detachment, or connection harness detachment. The second preset threshold can be set according to actual needs. The dependent variable in the second half of the dependent variable-independent variable curve is less than the second preset threshold, indicating that the data of the acquisition device is abnormal, the sensor is abnormal, or the connection harness is detached due to impact.

[0041] This embodiment performs a rapid diagnosis on the vehicle message data and pedestrian protection sensor data according to the sixth hood data abnormality rule, and can generate a sixth diagnosis result to evaluate whether the active pop-up hood test is wrong.

[0042] Optionally, the hair mask data anomaly rule includes a seventh hair mask data anomaly rule; In step S20, the processing terminal diagnoses the vehicle message data and the pedestrian protection sensor data according to the mask data abnormality rule to obtain a diagnosis result, including: S2071, generating a dependent variable-independent variable curve according to the vehicle message data and the pedestrian protection sensor data; determining the vehicle operating condition according to the vehicle message data; extracting acceleration from the pedestrian protection sensor data; S2072, processing the vehicle operating condition, the dependent variable-independent variable curve and the acceleration according to the seventh hood data abnormality rule; S2073. If the acceleration does not match the whole vehicle operating condition, and the dependent variable-independent variable curve does not match the whole vehicle operating condition, a seventh diagnostic result is generated, and the seventh diagnostic result includes an error in the channel setting of the acquisition device and an error in the sensor position.

[0043] A dependent variable-independent variable curve, such as an acceleration-time curve or a pressure value-time curve, can be generated based on the vehicle message data and pedestrian protection sensor data. Acceleration is extracted from the pedestrian protection sensor data. The vehicle operating condition, such as high-speed operating condition, low-speed operating condition, etc., can be determined based on the vehicle message data. The vehicle operating condition, dependent variable-independent variable curve and acceleration are diagnosed according to the seventh hood data anomaly rule. If the acceleration does not match the vehicle operating condition, or the dependent variable-independent variable curve does not match the vehicle operating condition, the seventh diagnostic result is generated. Otherwise, the seventh diagnostic result is not generated. The seventh diagnostic result includes an error in the channel setting of the acquisition device and an error in the sensor position.

[0044] This embodiment performs a rapid diagnosis on the vehicle message data and pedestrian protection sensor data according to the seventh hood data abnormality rule, and can generate a seventh diagnosis result to evaluate whether the active pop-up hood test is wrong.

[0045] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0046] In one embodiment, an active mask data processing device is provided, and the active mask data processing device corresponds to the active mask data processing method in the above embodiment. Figure 2 As shown, the active mask data processing device includes: The collection device 10 is used to obtain vehicle message data and pedestrian protection sensor data in parallel; The processing terminal 20 is used to obtain the whole vehicle message data and the pedestrian protection sensor data from the collection device 10; diagnose the whole vehicle message data and the pedestrian protection sensor data according to the abnormal rules of the mask data to obtain a diagnosis result.

[0047] Understandably, the collection device 10 can be set in the vehicle to obtain the whole vehicle message data and pedestrian protection sensor data in parallel. The processing terminal 20 can be a desktop computer, a laptop computer or other computer equipment, which is used to obtain the whole vehicle message data and the pedestrian protection sensor data from the collection device 10 after the active pop-up hood test; diagnose the whole vehicle message data and pedestrian protection sensor data according to the hood data abnormality rules to obtain the diagnosis result. The collection device 10 and the processing terminal 20 can be connected in a wired or wireless manner.

[0048] Alternatively, if Figure 3 As shown, the acquisition device 10 includes a bus receiver 04, a PSI transceiver, and a sensor connected to the PSI transceiver; the bus receiver 04 is connected to the vehicle bus; The acquisition device 10 acquires the pedestrian protection sensing data from the sensor via the PSI transceiver; The acquisition device 10 acquires the vehicle message data from the vehicle bus via the bus receiver 04 .

[0049] Understandably, the collection device 10 is provided with a bus receiver 04, which is connected to the vehicle bus and is used to receive vehicle message data. The collection device 10 is also provided with a PSI transceiver, which is connected to the sensor and is used to receive and send the sensor data. In an example, the PSI transceiver includes a PSI transceiver 01 and a PSI transceiver 02.

[0050] In one example, the collection device 10 also includes a connector 03, a power management chip 06, an MCU 08, a wireless transmission module 07, a base plate 05 and a housing 09. The connector 03 is used to connect various sensors, such as collision sensors and pedestrian protection pressure hoses. The power management chip 06 is used to power the various components of the collection device 10. The MCU 08 is used to process and store vehicle message data and pedestrian protection sensor data. The wireless transmission module 07 is used to transmit vehicle message data and pedestrian protection sensor data. The base plate 05 is used to install and fix the collection device 10 in the front cabin. The housing 09 is used to protect the internal circuit of the collection device 10.

[0051] For the specific definition of the active hood data processing device, please refer to the definition of the active hood data processing method above, which will not be repeated here. Each module in the above-mentioned active hood data processing device can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0052] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A method for processing active mask data, characterized in that: include: Acquire vehicle message data and pedestrian protection sensor data in parallel; The whole vehicle message data and the pedestrian protection sensor data are transmitted to a processing terminal, so that the processing terminal diagnoses the whole vehicle message data and the pedestrian protection sensor data according to the abnormal rules of the mask data to obtain a diagnosis result.

2. The active mask data processing method according to claim 1, characterized in that: The hair mask data anomaly rule includes a first hair mask data anomaly rule; The processing terminal diagnoses the vehicle message data and the pedestrian protection sensor data according to the mask data abnormality rule to obtain a diagnosis result, including: Generate a dependent variable-independent variable curve according to the vehicle message data and the pedestrian protection sensor data; Determine whether the vehicle message data and the pedestrian protection sensor data are empty, and whether the dependent variable in the dependent variable-independent variable curve is continuously zero according to the first mask data abnormality rule; If the vehicle message data and the pedestrian protection sensor data are empty, or the dependent variable in the dependent variable-independent variable curve is continuously zero, a first diagnostic result is generated; the first diagnostic result includes data abnormalities of the collection device, sensor abnormalities, or trigger switch abnormalities.

3. The active mask data processing method according to claim 1, characterized in that: The hair mask data anomaly rule includes a second hair mask data anomaly rule; The processing terminal diagnoses the vehicle message data and the pedestrian protection sensor data according to the mask data abnormality rule to obtain a diagnosis result, including: Determining the vehicle operating condition according to the vehicle message data; extracting acceleration and / or pressure values ​​from the pedestrian protection sensor data; Determining whether the positive and negative directions of the acceleration and / or pressure values ​​are consistent with the vehicle operating conditions according to the second hood data abnormality rule; If the positive and negative directions of the acceleration and / or pressure values ​​are inconsistent with the vehicle operating conditions, a second diagnostic result is generated; the second diagnostic result includes a sensor installation error or a sensor abnormality.

4. The active mask data processing method according to claim 1, characterized in that: The hair mask data anomaly rule includes a third hair mask data anomaly rule; The processing terminal diagnoses the vehicle message data and the pedestrian protection sensor data according to the mask data abnormality rule to obtain a diagnosis result, including: Generate a dependent variable-independent variable curve according to the vehicle message data and the pedestrian protection sensor data; Determining whether the initial value of the dependent variable in the dependent variable-independent variable curve is zero according to the third mask data abnormality rule; If the initial value of the dependent variable in the dependent variable-independent variable curve is not zero, a third diagnostic result is generated; the third diagnostic result includes a trigger switch abnormality or a data acquisition setting error.

5. The active mask data processing method according to claim 1, characterized in that: The hair mask data anomaly rule includes a fourth hair mask data anomaly rule; The processing terminal diagnoses the vehicle message data and the pedestrian protection sensor data according to the mask data abnormality rule to obtain a diagnosis result, including: generating a dependent variable-independent variable curve according to the vehicle message data and the pedestrian protection sensor data; determining a vehicle operating condition according to the vehicle message data; Processing the vehicle operating condition and the dependent variable-independent variable curve according to the fourth hood data abnormality rule; If the vehicle operating condition is a low-speed condition or a lightweight condition, and the dependent variable-independent variable curve shows a curve clipping wave, a fourth diagnostic result is generated, and the fourth diagnostic result includes data abnormality of the acquisition device or sensor abnormality.

6. The active mask data processing method according to claim 1, characterized in that: The hair mask data anomaly rule includes a fifth hair mask data anomaly rule; The processing terminal diagnoses the vehicle message data and the pedestrian protection sensor data according to the mask data abnormality rule to obtain a diagnosis result, including: generating a dependent variable-independent variable curve according to the vehicle message data and the pedestrian protection sensor data; determining a vehicle operating condition according to the vehicle message data; Processing the vehicle operating condition and the dependent variable-independent variable curve according to the fifth hood data abnormality rule; If the vehicle operating condition is a high-speed condition or a heavyweight condition, and the dependent variable in the first half of the dependent variable-independent variable curve is less than the first preset threshold, a fifth diagnostic result is generated, and the fifth diagnostic result includes data abnormality of the acquisition device or sensor abnormality.

7. The active mask data processing method according to claim 1, characterized in that: The hair mask data anomaly rule includes a sixth hair mask data anomaly rule; The processing terminal diagnoses the vehicle message data and the pedestrian protection sensor data according to the mask data abnormality rule to obtain a diagnosis result, including: generating a dependent variable-independent variable curve according to the vehicle message data and the pedestrian protection sensor data; determining a vehicle operating condition according to the vehicle message data; Processing the vehicle operating condition and the dependent variable-independent variable curve according to the sixth hood data abnormality rule; If the dependent variable in the second half of the dependent variable-independent variable curve has an abnormal peak or is lower than the second preset threshold, a sixth diagnostic result is generated, and the sixth diagnostic result includes data abnormality of the acquisition device, sensor abnormality, sensor detachment or connection harness detachment.

8. The active mask data processing method according to claim 1, characterized in that: The hair mask data anomaly rule includes a seventh hair mask data anomaly rule; The processing terminal diagnoses the vehicle message data and the pedestrian protection sensor data according to the mask data abnormality rule to obtain a diagnosis result, including: generating a dependent variable-independent variable curve according to the vehicle message data and the pedestrian protection sensor data; determining the vehicle operating condition according to the vehicle message data; extracting acceleration from the pedestrian protection sensor data; Processing the vehicle operating condition, the dependent variable-independent variable curve and the acceleration according to the seventh hood data abnormality rule; If the acceleration does not match the whole vehicle operating condition, and the dependent variable-independent variable curve does not match the whole vehicle operating condition, a seventh diagnostic result is generated, and the seventh diagnostic result includes an error in the channel setting of the acquisition device and an error in the sensor position.

9. An active mask data processing device, characterized in that: include: A collection device for acquiring vehicle message data and pedestrian protection sensor data in parallel; A processing terminal, used for acquiring the vehicle message data and the pedestrian protection sensor data from the collection device; The vehicle message data and the pedestrian protection sensor data are diagnosed according to the abnormal rules of the mask data to obtain a diagnosis result.

10. The active mask data processing device according to claim 9, characterized in that: The acquisition device includes a bus receiver, a PSI transceiver, and a sensor connected to the PSI transceiver; the bus receiver is connected to the vehicle bus; The acquisition device acquires the pedestrian protection sensing data from the sensor via the PSI transceiver; The acquisition device obtains the whole vehicle message data from the vehicle bus through the bus receiver.

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