Automobile tire pressure data analysis method, electronic equipment and system

Abstract

The invention relates to the technical field of automobile tire pressure sensors, and discloses an automobile tire pressure data analysis method which comprises the following steps: acquiring original automobile tire pressure data and parameter configuration information corresponding to the original automobile tire pressure data; analyzing the data area data according to the configuration area data to obtain level sample point segment data; determining a period deviation range and a pulse width deviation range of the automobile tire pressure data according to the parameter configuration information; filtering the level sample point segment data according to the period deviation range and the pulse width deviation range; determining target level sample point segment data from the filtered level sample point segment data according to a sampling baud rate and a first level jump moment of each frame of data of the filtered level sample point segment data; encoding the target level sample point segment data according to the data encoding format to obtain target data; and analyzing the target data to obtain automobile tire pressure data. In this way, the efficiency and reliability of function testing of the automobile tire pressure sensor are improved.

Description

Technical Field

[0001] The embodiments of the present application relate to the technical field of automobile tire pressure sensors, and specifically to an automobile tire pressure data analysis method, electronic equipment, and system. Background Art

[0002] Tire Pressure Monitor System (TPMS) is an active safety system that uses a highly sensitive wireless sensor device fixed in the car's tire to collect data such as tire pressure and temperature while the car is driving or stationary, and transmits the data to a host computer in the cab. It displays relevant data such as tire pressure and temperature in real time in digital form, and alerts the driver with a buzzer or voice warning when any tire abnormality occurs (to prevent tire blowout).

[0003] Tire pressure sensors, a crucial component of direct tire pressure monitoring systems, monitor tire pressure and temperature in real time. When the sensor's battery runs low or is damaged by other external factors, the sensor must be replaced. The final step in the development of a replacement tire pressure sensor is testing its functional accuracy and reliability.

[0004] The existing method for testing the functional accuracy and reliability of tire pressure sensors is to evaluate the functional accuracy and reliability of the tire pressure sensor to be tested based on the vehicle tire pressure data detected by the tire pressure sensor to be tested. In this process, the tire pressure sensor to be tested sends the detected vehicle tire pressure data through a radio frequency signal, and the tester uses a vector signal analyzer to collect the radio frequency signal. The tester then manually analyzes and decodes the radio frequency signal to obtain the vehicle tire pressure data. The manual analysis and decoding method not only leads to low efficiency in the functional test of the tire pressure sensor to be tested, but also easily reduces the reliability of the functional test of the tire pressure sensor due to errors in reading and counting. In addition, due to noise interference or signal interference from other sensors, the radio frequency signal collected by the vector signal analyzer is interfered with by clutter, which reduces the accuracy of the vehicle tire pressure data read by the tester, thereby reducing the reliability of the functional test of the tire pressure sensor to be tested. Summary of the Invention

[0005] In view of the above problems, the embodiments of the present application provide a method, electronic device and system for analyzing automobile tire pressure data, which can improve the efficiency and reliability of functional testing of automobile tire pressure sensors.

[0006] According to one aspect of an embodiment of the present application, a method for analyzing automobile tire pressure data is provided, the method comprising: obtaining original automobile tire pressure data and parameter configuration information corresponding to the original automobile tire pressure data; wherein the original automobile tire pressure data comprises configuration area data and data area data, the configuration area data comprises a sampling baud rate, a number of samples, a level type, and a memory offset, and the parameter configuration information comprises a data encoding format, a data baud rate, and a data frequency deviation; parsing the data area data according to the number of samples, the level type, and the memory offset to obtain level sample segment data; determining a period deviation range and a pulse width deviation range of the automobile tire pressure data according to the data encoding format, the data baud rate, and the data frequency deviation; filtering the level sample segment data according to the period deviation range and the pulse width deviation range to obtain filtered level sample segment data; determining target level sample segment data from the filtered level sample segment data according to the sampling baud rate and the first level jump moment of each frame of data of the filtered level sample segment data; encoding the target level sample segment data according to the data encoding format to obtain target data; and analyzing the target data to obtain automobile tire pressure data.

[0007] In an optional manner, obtaining the original vehicle tire pressure data and the parameter configuration information corresponding to the original vehicle tire pressure data further includes: obtaining the original vehicle tire pressure data; determining a channel number that identifies the original vehicle tire pressure data, the channel number corresponding to the parameter configuration information of the original vehicle tire pressure data; and determining the parameter configuration information corresponding to the original vehicle tire pressure data based on the channel number.

[0008] In an optional manner, determining a period deviation range and a pulse width deviation range of automobile tire pressure data based on a data encoding format, a data baud rate, and a data frequency deviation further includes: calculating the period of the automobile tire pressure data based on the data baud rate; determining the pulse width of the automobile tire pressure data based on the data encoding format and the period of the automobile tire pressure data; determining the period deviation range of the automobile tire pressure data based on the period of the automobile tire pressure data and the data frequency deviation; determining the pulse width deviation range of the automobile tire pressure data based on the pulse width of the automobile tire pressure data and the data frequency deviation; filtering the level sample segment data based on the period deviation range and the pulse width deviation range to obtain filtered level sample segment data, further including: starting from a starting position of the level sample segment data, modifying the levels in the level sample segment data that do not meet the period deviation range or the pulse width deviation range to a low level, until the entire level sample segment data is traversed to obtain the filtered level sample segment data.

[0009] In an optional manner, determining target level sample segment data from the filtered level sample segment data according to the sampling baud rate and the first level transition moment of each frame of filtered level sample segment data further includes: calculating the duration of the target level sample segment data according to the sampling baud rate; determining the first level transition moment of each frame of filtered level sample segment data; and determining the target level sample segment data from the filtered level sample segment data according to the first level transition moment of each frame of filtered level sample segment data and the duration of the target level sample segment data.

[0010] In an optional manner, the vehicle tire pressure data includes a frame format and multiple physical quantities; analyzing the target data to obtain the vehicle tire pressure data further includes: obtaining an identifier of standard vehicle tire pressure data and multiple physical quantities; when the target data includes an identifier of the standard vehicle tire pressure data, parsing the target data to obtain a frame format and multiple physical quantities of the vehicle tire pressure data; the method also includes: determining a calculation method for each physical quantity of the vehicle tire pressure data based on each physical quantity of the standard vehicle tire pressure data and each physical quantity of the vehicle tire pressure data.

[0011] In an optional manner, the target level sample segment data is determined from the filtered level sample segment data according to the sampling baud rate and the first level jump moment of each frame of the filtered level sample segment data, further comprising: determining a plurality of target level sample segment data from the filtered level sample segment data according to the sampling baud rate and the first level jump moment of each frame of the filtered level sample segment data; wherein each frame of data corresponds to each target level sample segment data; encoding the target level sample segment data according to the data encoding format to obtain target data, further comprising: encoding the plurality of target level sample segment data according to the data encoding format to obtain a plurality of target data; the method further comprising: encoding the plurality of target level sample segment data in chronological order based on the first level jump moment of the plurality of target data The method further comprises: sequentially sorting a plurality of target data to obtain a plurality of sorted target data; when the target data includes an identifier of standard automobile tire pressure data, parsing the target data to obtain a frame format and a plurality of physical quantities of the automobile tire pressure data, and further comprising: when the sorted target data includes an identifier of standard automobile tire pressure data, sequentially parsing the sorted target data to obtain a plurality of groups of data of each automobile tire pressure data; wherein each group of data includes a frame format and a plurality of initial physical quantities, and the same initial physical quantities of the plurality of automobile tire pressure data are sorted in chronological order; obtaining a state of the test tire at the first level jump moment of each target data; verifying the frame format and the plurality of initial physical quantities of the plurality of groups of each automobile tire pressure data according to the state to obtain the frame format and the plurality of physical quantities of the plurality of automobile tire pressure data.

[0012] In an optional manner, when the sorted target data contains the identifier of standard automobile tire pressure data, the sorted target data are parsed in sequence to obtain multiple groups of frame formats and multiple initial physical quantities for each automobile tire pressure data, further including: when each sorted target data contains the identifier of standard automobile tire pressure data, field missing processing, redundant data processing and abnormal field processing are performed on the multiple sorted target data in sequence to obtain processed sorted target data; the processed sorted target data are parsed in sequence to obtain multiple groups of frame formats and multiple initial physical quantities for each automobile tire pressure data.

[0013] According to another aspect of an embodiment of the present application, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the automobile tire pressure data analysis method provided in any of the above embodiments.

[0014] According to another aspect of an embodiment of the present application, a vehicle tire pressure data analysis system is provided for analyzing vehicle tire pressure data detected by a vehicle tire pressure sensor, the system comprising a tire testing machine, a sensor controller, a standard detection sensor, a signal analyzer and the electronic device provided in the above embodiment; the electronic device is respectively communicated with the tire testing machine, the sensor controller and the signal analyzer, the sensor controller and the signal analyzer are respectively used to communicate with the vehicle tire pressure sensor to be tested, the standard detection sensor is respectively communicated with the sensor controller and the signal analyzer, and the standard detection sensor and the vehicle tire pressure sensor to be tested are placed in a test tire of the tire testing machine; wherein the electronic device is used to send a control instruction to the tire testing machine so that the tire testing machine moves according to the control instruction; the electronic device is also used to send a start instruction to the sensor controller and the signal analyzer so that the sensor controller and the signal analyzer start; the sensor controller is used to send a start instruction to the standard detection sensor to enable the sensor controller and the signal analyzer to start The sensor and the tire pressure sensor of the vehicle to be tested send a start-up instruction to start the standard detection sensor and the tire pressure sensor of the vehicle to be tested; the standard detection sensor is used to detect the first original tire pressure data of the test tire of the tire testing machine when the tire testing machine is moving, and send the first original tire pressure data to the signal analyzer; the signal analyzer is used to receive the first original tire pressure data and the second original tire pressure data sent by the tire pressure sensor of the vehicle to be tested, and send the first original tire pressure data and the second original tire pressure data to the electronic device, the second original tire pressure data being the data obtained by the tire pressure sensor of the vehicle to be tested when detecting the test tire of the tire testing machine when the tire testing machine is moving; the electronic device is also used to analyze the first original tire pressure data and the second original tire pressure data respectively to obtain the first tire pressure data and the second tire pressure data, and determine the calculation method of the physical quantity of the second tire pressure data based on the first tire pressure data.

[0015] According to another aspect of the embodiments of the present application, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the automobile tire pressure data analysis method provided by any of the above embodiments is implemented.

[0016] In an embodiment of the present application, data in the data area is parsed by the number of samples, level type, and memory offset to obtain level sample segment data. The period deviation range and pulse width deviation range of the automobile tire pressure data are determined by the data encoding format, data baud rate, and data frequency deviation. The level sample segment data can be filtered by the period deviation range and pulse width deviation range to effectively filter out interference signals of the automobile tire pressure data. The target level sample segment data is determined from the level sample segment data by sampling the baud rate and the first level jump moment of each frame of data of the level sample segment data. The target level sample segment data is encoded by the data encoding format to obtain target data. Finally, the target data is analyzed to obtain the automobile tire pressure data. Through the above method, not only can the automobile tire pressure data be visualized, the radio frequency signal of the tire pressure sensor to be tested can be quickly decoded, and the functional accuracy and reliability test efficiency of the tire pressure sensor can be improved, but also errors that occur during manual decoding can be avoided, the reliability of the automobile tire pressure data can be improved, and the reliability of the functional test of the tire pressure sensor to be tested can be improved. Furthermore, by filtering the level sample data through the period deviation range and pulse width deviation range of the automobile tire pressure data, the interference signal introduced when the vector signal analyzer collects the automobile tire pressure data sent by the tire pressure sensor to be tested can be effectively filtered out, thereby improving the accuracy of the automobile tire pressure data and thus improving the reliability of the functional test of the tire pressure sensor to be tested.

[0017] The above description is only an overview of the technical solutions of the embodiments of the present application. In order to more clearly understand the technical means of the embodiments of the present application, they can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the embodiments of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings are only used to illustrate the embodiments and are not to be considered as limiting the present application. In addition, the same reference symbols are used to represent the same components throughout the drawings. In the drawings:

[0019] Figure 1 A schematic diagram of the structure of a vehicle tire pressure data analysis system provided in an embodiment of the present application is shown;

[0020] Figure 2 A schematic diagram showing a flow chart of a method for analyzing automobile tire pressure data provided by an embodiment of the present application is shown;

[0021] Figure 3 Shown Figure 2A schematic flow chart of the sub-steps of step 170;

[0022] Figure 4 A schematic diagram showing a flow chart of a method for analyzing automobile tire pressure data provided by another embodiment of the present application is shown;

[0023] Figure 5 Shown Figure 4 Schematic diagram of the sub-step flow of step 290;

[0024] Figure 6 A schematic diagram of the structure of a vehicle tire pressure data analysis device provided in an embodiment of the present application is shown;

[0025] Figure 7 A schematic structural diagram of an electronic device provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0026] The exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application can be implemented in various forms and should not be limited to the embodiments set forth herein.

[0027] The main process for developing an alternative tire pressure sensor is as follows: 1. Collecting and analyzing data from the interaction between the vehicle's tire pressure system ECU (Electronic Control Unit) and the sensor; 2. Designing the tire pressure sensor's structure, hardware, communication protocol, and software system architecture; 3. Hardware manufacturing and software development of the tire pressure sensor; 4. Functional accuracy and reliability testing of the tire pressure sensor.

[0028] Regarding the functional accuracy and reliability testing of tire pressure sensors, the existing testing method is to place the tire pressure sensor to be tested into the test tire of a tire testing machine, and then control the inflation, deflation and rotation of the tire testing machine to simulate the working scenario of the tire pressure sensor to be tested. During the operation of the tire testing machine, the tire pressure sensor to be tested detects the car tire pressure data in the test tire. Based on the car tire pressure data detected by the tire pressure sensor to be tested, the functional accuracy and reliability of the tire pressure sensor to be tested can be evaluated.

[0029] During the functional accuracy and reliability testing of the tire pressure sensor under test, the sensor transmits the detected tire pressure data via a radio frequency signal. Testers use a vector signal analyzer to collect and save the radio frequency signal. Currently, after collecting the radio frequency signal from the tire pressure sensor under test, testers need to manually analyze and decode the radio frequency signal. For example, the tester uses an oscilloscope to display the radio frequency signal collected by the vector signal analyzer. Then, based on experience, the tester reads the data displayed on the oscilloscope to obtain tire pressure data such as frame format, pressure, temperature, and acceleration. This manual analysis and decoding method not only decodes data slowly, resulting in inefficient functional accuracy and reliability testing of the tire pressure sensor under test, but is also prone to errors in reading and counting, resulting in reduced reliability of the tire pressure sensor's functional testing. In addition, since the tire pressure sensor to be tested is connected to the vector signal analyzer via a radio frequency signal, the tire pressure sensor to be tested detects the temperature, pressure, acceleration and other vehicle tire pressure data of the test tire and sends it out via a radio frequency signal. When the vector signal analyzer collects the radio frequency signal, due to noise interference or signal interference from other sensors, the radio frequency signal collected by the vector signal analyzer is interfered with by clutter. Although a filter can be used to filter the radio frequency signal collected by the vector signal analyzer and then displayed on an oscilloscope, the filter parameters are fixed and are prone to over-filtering or under-filtering. This will still reduce the accuracy of the vehicle tire pressure data read by the tester, thereby reducing the reliability of the functional test of the tire pressure sensor to be tested.

[0030] Based on this, the present application provides a method for analyzing automobile tire pressure data. By obtaining the configuration information of a vector signal analyzer and automatically parsing the radio frequency signal of the tire pressure sensor to be tested, the level sample segment data can be obtained. The valid data related to the automobile tire pressure data can be determined from the level sample segment data through the configuration information, and by serializing the valid data, the analysis of the valid data can be realized, and visual automobile tire pressure data can be generated. This can not only quickly decode the radio frequency signal of the tire pressure sensor to be tested, thereby improving the functional accuracy and reliability testing efficiency of the tire pressure sensor to be tested, but also avoid errors that occur during manual decoding, improve the reliability of the automobile tire pressure data, and thus improve the reliability of the functional test of the tire pressure sensor to be tested. Furthermore, before determining the valid data, the level sample data is filtered according to the parameter configuration information of the tire pressure sensor to be tested, which can effectively filter out the interference signal introduced by the vector signal analyzer when collecting the automobile tire pressure data sent by the tire pressure sensor to be tested, thereby improving the accuracy of the automobile tire pressure data and thus improving the reliability of the functional test of the tire pressure sensor to be tested.

[0031] Figure 1The structure diagram of the automobile tire pressure data analysis system provided by the embodiment of the present application is shown, and the automobile tire pressure data analysis system is used to analyze the automobile tire pressure data detected by the automobile tire pressure sensor. Figure 1 As shown, the automobile tire pressure data analysis system 10 includes a tire testing machine 11, a sensor controller 12, a standard detection sensor 13, a signal analyzer 14, and an electronic device 15. The electronic device 15 is respectively connected to the tire testing machine 11, the sensor controller 12, and the signal analyzer 14. The sensor controller 12 and the signal analyzer 14 are respectively connected to the tire pressure sensor 16 of the vehicle to be tested. The standard detection sensor 13 is respectively connected to the sensor controller 12 and the signal analyzer 14. The standard detection sensor 13 and the tire pressure sensor 16 of the vehicle to be tested are placed in the test tire of the tire testing machine.

[0032] The tire testing machine 11 is a testing device that can simulate the inflation, deflation and rotation of automobile tires during actual use.

[0033] The sensor controller 12 connects to the standard detection sensor 13 via low-frequency signals and to the electronic device 15 via USB. Based on instructions sent by the electronic device 15, the sensor controller 12 controls the activation and operation of the standard detection sensor 13 and the tire pressure sensor 16 to be tested. Serving as a bridge for communication between the electronic device 15, the standard detection sensor 13, and the tire pressure sensor 16 to be tested, the sensor controller 12 converts USB signal control instructions into wireless low-frequency signal control instructions through internal protocol and algorithm conversion, completing interactive communication between the electronic device 15 and the sensors.

[0034] The standard detection sensor 13 accurately detects actual tire pressure data, including pressure, temperature, and acceleration, within the test tire. After conversion using the protocol unit and the RF signal adapter unit, it transmits a high-frequency signal through the RF antenna. This data collected by the standard detection sensor 13 serves as a benchmark for determining the pressure, temperature, and acceleration of the test tire detected by the tire pressure detection sensor 16. This helps determine whether the detection accuracy of the tire pressure detection sensor 16 meets design specifications, thereby confirming the functional accuracy and reliability of the tire pressure detection sensor 16.

[0035] Signal analyzer 14 can be connected to electronic device 15 via USB and connected to standard detection sensor 13 and tire pressure sensor 16 of the vehicle under test via low-frequency / high-frequency signals. Signal analyzer 14 collects low-frequency / high-frequency signals transmitted by standard detection sensor 13 and tire pressure sensor 16 of the vehicle under test and stores the collected low-frequency / high-frequency signals in electronic device 15 via a specified path.

[0036] The electronic device 15 can be a tablet computer, computer, server, or other device equipped with a screen. An application program (APP) is installed on the electronic device 15. By controlling buttons and input boxes on the APP's interactive interface, the electronic device 15 can control the operation of the tire tester 11, sensor controller 12, and signal analyzer 14. The APP contains multiple test cases. After running each test case, the tire tester 11 can be controlled to operate according to different control instructions, allowing the tire tester's test tires to simulate different operating scenarios of automobile tire pressures.

[0037] Specifically, the tester launches the app on electronic device 15. After the app runs the test case, electronic device 15 sends control instructions to tire tester 11, causing it to move according to the control instructions. For example, the app controls the test tire to inflate or deflate to a specified pressure or rotate at a specified speed and direction. Simultaneously, the app configures parameters for signal analyzer 14, enabling it to start and collect data. After data collection, the app saves the collected raw tire pressure data to a file.

[0038] The electronic device 15 sends a startup instruction to the sensor controller 12 and the signal analyzer 14 to start the sensor controller 12 and the signal analyzer 14 .

[0039] The sensor controller 12 sends a start instruction to the standard detection sensor 13 and the tire pressure sensor 16 of the vehicle to be tested, so as to start the standard detection sensor 13 and the tire pressure sensor 16 of the vehicle to be tested.

[0040] The standard detection sensor 13 detects first original automobile tire pressure data of the test tire of the tire testing machine 11 when the tire testing machine 11 moves, and sends the first original automobile tire pressure data to the signal analyzer.

[0041] The tire pressure sensor 16 of the vehicle to be tested detects the second original tire pressure data of the test tire of the tire testing machine 11 when the tire testing machine 11 is moving, and sends the second original tire pressure data to the signal analyzer.

[0042] The signal analyzer 14 receives the first original vehicle tire pressure data and the second original vehicle tire pressure data, and sends the first original vehicle tire pressure data and the second original vehicle tire pressure data to the electronic device 15 to be stored in a designated path of the electronic device 15 .

[0043] The APP of the electronic device 15 automatically reads the saved first original vehicle tire pressure data and the second original vehicle tire pressure data according to the test case, and analyzes the first original vehicle tire pressure data and the second original vehicle tire pressure data to obtain the first vehicle tire pressure data and the second vehicle tire pressure data, and determines the calculation method of the physical quantity of the second vehicle tire pressure data based on the first vehicle tire pressure data.

[0044] Figure 2 A flow chart of a method for analyzing tire pressure data of a vehicle provided by an embodiment of the present application is shown. Figure 1 The electronic device 15 shown in the embodiment is executed. Figure 2 As shown, the automobile tire pressure data analysis method includes the following steps:

[0045] Step 110: Obtain original vehicle tire pressure data and parameter configuration information corresponding to the original vehicle tire pressure data; wherein the original vehicle tire pressure data includes configuration area data and data area data, the configuration area data includes sampling baud rate, number of samples, level type and memory offset, and the parameter configuration information includes data encoding format, data baud rate and data frequency deviation.

[0046] In the embodiment of the present application, the original automobile tire pressure data may be the first original automobile tire pressure data detected by the standard detection sensor 13 or the second original automobile tire pressure data detected by the automobile tire pressure sensor 16 .

[0047] Configuration area data refers to the configuration information used by the signal analyzer 14 to collect radio frequency signals sent by the tire pressure sensor 16 under test. This information can be used to initially analyze the raw tire pressure data collected by the signal analyzer 14. Parameter configuration information refers to the configuration information used by the tire pressure sensor 16 under test to detect the tire pressure data within the test tire.

[0048] For example, the sampling baud rate can be set to 100000 symbols / s, the number of samples can be set to 2000, the level type can be set to high level as 1 and low level as 0, and the memory offset can be set to 64 bytes.

[0049] The data encoding format can be Manchester encoding format, differential Manchester encoding format, PWM encoding format, NZR encoding format, etc. This application uses Manchester encoding format as an example for illustration and does not constitute a limitation. The data baud rate can be set to 1000 symbols / s, and the data frequency deviation can be set to 5%.

[0050] The data in the data area may include the automobile tire pressure data detected multiple times by the tire pressure sensor to be tested and collected by the signal acquisition channel. Correspondingly, the data in the configuration area includes configuration information of the automobile tire pressure data detected multiple times.

[0051] Specifically, the signal analyzer 14 has multiple signal acquisition channels, each with a unique channel number. During the actual RF signal data acquisition process, the RF signal data transmitted by the standard detection sensor 13 or the different tire pressure sensors to be tested 16 are typically collected through different signal acquisition channels. For example, the signal analyzer 14 collects RF signal data from the standard detection sensor 13 through signal acquisition channel 1, collects RF signal data from the tire pressure sensor to be tested 16a through signal acquisition channel 2, and collects RF signal data from the tire pressure sensor to be tested 16b through signal acquisition channel 3. After the signal analyzer 14 collects RF signal data from the standard detection sensor 13 or the different tire pressure sensors to be tested 16, it can use the channel number to identify the file in which the stored RF signal data is stored, that is, to identify the file containing the original vehicle tire pressure data.

[0052] When a function test is required on a specific tire pressure sensor 16 under test, the electronic device 15 pre-stores the ID of the tire pressure sensor 16 under test, its parameter configuration information, and the channel number of the signal acquisition channel for the tire pressure sensor 16 under test. Therefore, after acquiring the raw tire pressure data, the corresponding parameter configuration information can be obtained based on the channel number of the file identifying the raw tire pressure data. This method automatically obtains the configuration information of the tire pressure sensor 16 under test, allowing the tire pressure data collected by the signal analyzer 14 to be cleaned, ensuring consistency between data detection and parameter cleaning.

[0053] Step 120: Parse the data in the data area according to the number of samples, level type, and memory offset to obtain level sample segment data.

[0054] Level sample segment data includes low-level samples and high-level samples. Typically, the parsed level sample segment data can be cached separately as continuous low-level sample segment data and continuous high-level sample segment data to save data cache space. The high bit of the continuous high-level sample segment data can be set to 1, and the high bit of the continuous low-level sample segment data can be set to 0. For example, when the level sample segment data is 0x10004000, 0x00008000, 0x10002000, and 0x00004000, it indicates 8192 continuous high-level samples and 16384 continuous low-level samples, or 4096 continuous high-level samples and 8192 continuous low-level samples.

[0055] For example, when the number of samples is 2000, the level type is 1 for high level and 0 for low level, and the memory offset is 64 bytes, assuming that each sample occupies 2 bytes, the starting position of the data area to be parsed is 64 bytes, the total length is 4000 (number of samples × number of bytes occupied by each sample) bytes, and the end position is 4064 bytes. It can be seen that it is necessary to read data within 64 to 4064 bytes, a total of 2000 samples. For the sample value of each sample point read, if the sample value is greater than the threshold, the sample point is parsed as a high level and recorded as 1. If the sample value is less than or equal to the threshold, the sample point is parsed as a low level and recorded as 0. In this way, the level sample segment data composed of high and low levels can be parsed.

[0056] Step 130: Determine the period deviation range and pulse width deviation range of the vehicle tire pressure data according to the data encoding format, data baud rate, and data frequency deviation.

[0057] Specifically, step 130 includes the following steps:

[0058] Step 131: Calculate the period of the vehicle tire pressure data according to the data baud rate.

[0059] Step 132: Determine the pulse width of the vehicle tire pressure data according to the data encoding format and the period of the vehicle tire pressure data.

[0060] Step 133: Determine a period deviation range of the vehicle tire pressure data according to the period and data frequency deviation of the vehicle tire pressure data.

[0061] Step 134: Determine the pulse width deviation range of the tire pressure data according to the pulse width and data frequency deviation of the tire pressure data.

[0062] Assuming that the data baud rate is 100,000 symbols / s, the period T of the automobile tire pressure data can be calculated as: T = 1 / data baud rate = 1 / 100,000 = 10μs. Furthermore, since the pulse width of Manchester encoding is equal to each half cycle, after determining the period T of the automobile tire pressure data, the pulse width P of the automobile tire pressure data can be calculated as: P = T / 2 = 1 / 2 = 5μs.

[0063] When the data frequency deviation is 5%, the cycle deviation range of the tire pressure data is T 差 T 差 =[10×(1-5%),10×(1+5%)]=[9.5μs,10.5μs], pulse width deviation range P 差 For: P 差 =[5×(1-5%), 5×(1+5%)]=[4.75μs, 5.25μs].

[0064] Step 140: filtering the level sample segment data according to the period deviation range and the pulse width deviation range to obtain filtered level sample segment data.

[0065] Specifically, starting from the starting position of the level sample segment data, the levels that do not meet the period deviation range or the pulse width deviation range in the level sample segment data are modified to low levels until the entire level sample segment data is traversed to obtain filtered level sample segment data.

[0066] Starting from 0μs of the level sample segment data, first determine whether the first cycle T1 of the level sample segment data meets the cycle deviation range T of the automobile tire pressure data. 差 ([9.5μs,10.5μs]); If the first cycle T1 meets the cycle deviation range T of the tire pressure data of the car 差 , then determine whether the two pulse widths P1 and P2 of the first cycle T1 meet the pulse width deviation range of the automobile tire pressure data. If the pulse width P1 or the pulse width P2 meets the pulse width deviation range of the automobile tire pressure data, then determine whether the second cycle T2 meets the cycle deviation range T of the automobile tire pressure data. 差 If the pulse width P1 or pulse width P2 does not meet the pulse width deviation range of the automobile tire pressure data, the level of the pulse width P1 or pulse width P2 is modified to a low level; if the first cycle T1 does not meet the cycle deviation range T of the automobile tire pressure data 差 , then the level of the first cycle T1 is modified to a low level, and then the second cycle T2 is judged whether it meets the cycle deviation range T of the automobile tire pressure data. 差 ...And so on, it is possible to judge in turn whether the period of the entire level sample segment data meets the period deviation range of the automobile tire pressure data, and to judge in turn whether the pulse width of the entire level sample segment data meets the pulse width deviation range of the automobile tire pressure data, so as to modify the level of the level sample segment data whose period does not meet the period deviation range of the automobile tire pressure data or whose pulse width does not meet the pulse width deviation range of the automobile tire pressure data to a low level, thereby realizing filtering of the level sample segment data.

[0067] For example, when the first cycle T1 = 10μs, T1 meets the cycle deviation range of automobile tire pressure data [9.5μs, 10.5μs]. Then, it is determined whether pulse width P1 or pulse width P2 meets the pulse width deviation range of automobile tire pressure data. When pulse width P1 = 4μs and pulse width P2 = 6μs, both pulse width P1 and pulse width P2 do not meet the pulse width deviation range of automobile tire pressure data [4.75μs, 5.25μs]. The level of the first cycle T1 is modified to a low level. When the second cycle T2 = 12.5μs, T2 does not meet the cycle deviation range of automobile tire pressure data [9.5μs, 10.5μs]. The level of the second cycle T2 is modified to a low level. When the third cycle T3 = 9.8μs, T3 meets the cycle deviation range of the automobile tire pressure data [9.5μs, 10.5μs]. When the pulse width P1 = 4.8μs and the pulse width P2 = 5μs, both the pulse width P1 and the pulse width P2 meet the pulse width deviation range of the automobile tire pressure data [4.75μs, 5.25μs].

[0068] In this way, the levels that do not meet the cycle and pulse width requirements of the tire pressure data can be filtered out, thereby filtering out the noise data other than the tire pressure data and ensuring the accuracy of subsequent decoding of the level sample segment data.

[0069] Step 150: Determine target level sample segment data from the filtered level sample segment data according to the sampling baud rate and the first level transition moment of each frame of the filtered level sample segment data.

[0070] The target level sample segment data is valid data collected by the signal analyzer, that is, the tire pressure data of the vehicle detected by the tire pressure sensor to be tested.

[0071] Specifically, step 150 includes the following steps:

[0072] Step 151: Calculate the duration of the target level sample segment data according to the sampling baud rate.

[0073] The duration of each sample point can be calculated based on the sampling baud rate. For example, when the sampling baud rate is 100000 symbols / s, the duration of each sample point t can be calculated. n = t = 1 / 100000 = 10 μs. Since the total number of samples is 2000, the duration t of the target level sample segment data can be determined. 总 is: t 总 =10×2000=20000μs=20ms.

[0074] Step 152: Determine the first level jump moment of each frame of the filtered level sample segment data.

[0075] In the level sample segment data, there is a continuous high level or low level before the first frame of data, which lasts for about 1s. The first high-low level change that meets the sampling baud rate after the continuous high level can be determined as the first frame of data. That is, the moment when the high-low level change that meets the sampling baud rate first appears is the first level jump moment of the first frame of data.

[0076] There is a continuous high or low level between each frame of data, and the duration, that is, the frame interval time, is approximately 10ms. Therefore, after the first frame of data, the first high or low level change that matches the sampling baud rate after the frame interval time can be determined as a frame of data. Correspondingly, the first time a high or low level change that matches the sampling baud rate after the frame interval time appears can be determined as the first level jump time of each frame of data.

[0077] Step 153: determining target level sample segment data from the filtered level sample segment data according to the first level jump moment of each frame of the filtered level sample segment data and the duration of the target level sample segment data.

[0078] After determining the duration of the target level sample segment data and the first level jump moment of each frame of data, the level sample segment data in the filtered level sample segment data that lasts for the duration of the target level sample segment data from the first level jump moment of each frame of data is the target level sample segment data.

[0079] For example, when the first level jump time of each frame of data is 1s and the duration of the target level sample segment data is 20ms, the level sample segment data between 1s and 1.02s in the filtered level sample segment data is the target level sample segment data.

[0080] Through steps 151 and 152, the first level jump moment of each frame of data and the duration of the target level sample segment data can be determined. Each frame of data can be determined from the filtered level sample segment data, that is, the target level sample segment data can be determined, thereby determining the valid data collected by the signal analyzer each time, and further determining the vehicle tire pressure data detected and sent by the tire pressure sensor to be tested each time.

[0081] Step 160: Encode the target level sample segment data according to the data encoding format to obtain target data.

[0082] Taking the Manchester encoding format as an example, in the target level sample segment data, a high level to low level jump represents 1, and a low level to high level jump represents 0. In this way, by encoding the target level sample segment data using the Manchester encoding format, visual target data can be obtained.

[0083] In an embodiment of the present application, the obtained target data can be identified by the channel number, the first level jump time and the data encoding format, so as to facilitate the subsequent performance evaluation of the tire pressure sensor to be tested.

[0084] Step 170: Analyze the target data to obtain the vehicle tire pressure data.

[0085] The tire pressure data obtained in the embodiment of the present application may include a frame interval, a frame format, and multiple physical quantities. The frame interval may be determined by the difference between the first level transition moments of two adjacent frames of data. The frame format may be: The multiple physical quantities may include pressure, temperature, acceleration, etc.

[0086] In this step, the obtained automobile tire pressure data may be tire pressure data detected by a standard detection sensor, or may be tire pressure data detected by a tire pressure sensor to be tested.

[0087] After analyzing the tire pressure data detected by the standard detection sensor and the tire pressure data detected by the tire pressure sensor to be tested using the automobile tire pressure data analysis method provided in the embodiment of the present application, the calculation method of each physical quantity of the tire pressure sensor to be tested can be inferred based on the tire pressure data detected by the standard detection sensor and the tire pressure data detected by the tire pressure sensor to be tested.

[0088] In this way, by comparing the frame format of the tire pressure sensor to be tested with the designed ideal frame format, and the calculation method of each physical quantity of the tire pressure sensor to be tested with the designed ideal calculation method of each physical quantity, the function of the tire pressure sensor to be tested can be tested.

[0089] In an embodiment of the present application, data in the data area is parsed by the number of samples, level type, and memory offset to obtain level sample segment data. The period deviation range and pulse width deviation range of the automobile tire pressure data are determined by the data encoding format, data baud rate, and data frequency deviation. The level sample segment data can be filtered by the period deviation range and pulse width deviation range to effectively filter out interference signals of the automobile tire pressure data. The target level sample segment data is determined from the level sample segment data by sampling the baud rate and the first level jump moment of each frame of data of the level sample segment data. The target level sample segment data is encoded by the data encoding format to obtain target data. Finally, the target data is analyzed to obtain the automobile tire pressure data. Through the above method, not only can the automobile tire pressure data be visualized, the radio frequency signal of the tire pressure sensor to be tested can be quickly decoded, and the functional accuracy and reliability test efficiency of the tire pressure sensor can be improved, but also errors that occur during manual decoding can be avoided, the reliability of the automobile tire pressure data can be improved, and the reliability of the functional test of the tire pressure sensor to be tested can be improved. Furthermore, by filtering the level sample data through the period deviation range and pulse width deviation range of the automobile tire pressure data, the interference signal introduced when the vector signal analyzer collects the automobile tire pressure data sent by the tire pressure sensor to be tested can be effectively filtered out, thereby improving the accuracy of the automobile tire pressure data and thus improving the reliability of the functional test of the tire pressure sensor to be tested.

[0090] In order to improve the accuracy of the functional test results of the tire pressure sensor to be tested, the present application also provides an implementation method, optionally, Figure 3 Shown Figure 2 As shown in the flowchart of the sub-steps of step 170, step 170 further includes the following steps:

[0091] Step 171: Obtain an identifier of the vehicle tire pressure data and multiple physical quantities of the standard vehicle tire pressure data.

[0092] The identifier of the automobile tire pressure data is the identification number of the tire pressure sensor to be tested, such as an ID. The multiple physical quantities of the standard automobile tire pressure data are the multiple physical quantities of the automobile tire pressure data detected by the standard detection sensor mentioned above.

[0093] Step 172: When the target data includes an identifier of the automobile tire pressure data, the target data is parsed to obtain a frame format and multiple physical quantities of the automobile tire pressure data.

[0094] After obtaining the target data, it is necessary to check whether the target data is the data detected by the tire pressure sensor to be tested, so as to eliminate the interference of data from other sensors and ensure the reliability of the functional test results of the tire pressure sensor to be tested.

[0095] Specifically, it is first determined whether the target data contains the identification of the automobile tire pressure data. When the target data contains the identification of the automobile tire pressure data, each field of the target data is parsed to obtain multiple physical quantities of the automobile tire pressure data, thereby obtaining the frame format of the automobile tire pressure data.

[0096] In some cases, the field representing the vehicle tire pressure data identifier in the target data may be missing bits. Therefore, when determining whether the target data contains the vehicle tire pressure data identifier, if the target data contains a field that is 90% similar to the vehicle tire pressure data identifier, the target data is considered to contain the vehicle tire pressure data identifier. For example, if the vehicle tire pressure data identifier is 1011101111 and the target data contains a field with the value 10111011*1, the target data is considered to contain the vehicle tire pressure data identifier.

[0097] Step 173: Determine a calculation method for each physical quantity of the vehicle tire pressure data according to each physical quantity of the standard vehicle tire pressure data and each physical quantity of the vehicle tire pressure data.

[0098] First, each physical quantity in the tire pressure data is determined, such as temperature, pressure, and acceleration. Then, a functional relationship is determined for each physical quantity, such as a linear relationship, a nonlinear relationship, or another form of relationship. Finally, each physical quantity in the standard tire pressure data is substituted into the functional relationship for each physical quantity in the tire pressure data to obtain the functional relationship for each physical quantity.

[0099] In this step, the tire pressure data detected by the standard detection sensor and the tire pressure sensor to be tested at the same time can be matched according to the first level jump moment of the identified target data, that is, multiple physical quantities of the standard automobile tire pressure data at the same time can be matched with each physical quantity of the automobile tire pressure data. In this way, the calculation method of each physical quantity of the automobile tire pressure data can be determined by each physical quantity of the standard automobile tire pressure data at the same time and each physical quantity of the automobile tire pressure data, thereby ensuring the accuracy of the calculation method of each physical quantity of the determined automobile tire pressure data.

[0100] By identifying and filtering target data using tire pressure data, interference from data from other sensors can be eliminated. Because tire pressure data detected by the standard test sensor can serve as a benchmark for evaluating tire pressure data detected by the tire pressure sensor under test, the calculation method for extrapolating each physical quantity of the tire pressure data from multiple physical quantities in the standard tire pressure data can improve the accuracy of the calculation method for each physical quantity in the tire pressure data, thereby increasing the reliability of the functional test results of the tire pressure sensor under test.

[0101] Figure 4 A flowchart of a method for analyzing tire pressure data of a vehicle provided by another embodiment of the present application is shown. Figure 1 The electronic device 15 shown in the embodiment is executed. Figure 4 As shown, the automobile tire pressure data analysis method includes the following steps:

[0102] Step 210: Obtain original vehicle tire pressure data and parameter configuration information corresponding to the original vehicle tire pressure data; wherein the original vehicle tire pressure data includes configuration area data and data area data, the configuration area data includes sampling baud rate, number of samples, level type and memory offset, and the parameter configuration information includes data encoding format, data baud rate and data frequency deviation.

[0103] Step 220: Parse the data in the data area according to the sampling baud rate, number of samples, level type, and memory offset to obtain level sample segment data.

[0104] Step 230: Determine the period deviation range and pulse width deviation range of the vehicle tire pressure data according to the data encoding format, data baud rate, and data frequency deviation.

[0105] Step 240: Filter the level sample segment data according to the period deviation range and the pulse width deviation range to obtain filtered level sample segment data.

[0106] Steps 210-240 can refer to Figure 2 Steps 110 to 140 are not described here in detail.

[0107] Step 250: Determine a plurality of target level sample segment data from the filtered level sample segment data according to the sampling baud rate and the first level transition moment of each frame of the filtered level sample segment data, wherein each frame of data corresponds to each target level sample segment data.

[0108] Specifically, the level sample segment data includes multiple frames of data, each frame of data representing tire pressure data detected by the tire pressure sensor under test. In the embodiment of the present application, each frame of data corresponds to each target level sample segment data, meaning that each frame of data corresponds to each target level sample segment data. Therefore, based on the sampling baud rate and the first level transition moment of each frame of filtered level sample segment data, the correspondence between each target level sample segment data can be determined from the level sample segment data.

[0109] Step 260: Encode the multiple target level sample segment data according to the data encoding format to obtain multiple target data.

[0110] By encoding each target level sample segment data in sequence, multiple target data can be obtained.

[0111] Step 270: Based on the first level transition moment of the multiple target data, sort the multiple target data in chronological order to obtain multiple sorted target data.

[0112] Step 280: Obtain the identifier and multiple physical quantities of standard automobile tire pressure data.

[0113] This step can refer to Figure 3 Step 171 is not described here any more.

[0114] Step 290: If the sorted target data includes an identifier for standard vehicle tire pressure data, the sorted target data is parsed sequentially to obtain multiple sets of data for each vehicle tire pressure data. Each set of data includes a frame format and multiple initial physical quantities. The initial physical quantities of the multiple vehicle tire pressure data that are identical are sorted in chronological order.

[0115] For each sorted target data, multiple groups of data can be parsed. For example, by parsing the sorted target data 1, 3 groups of car tire pressure data 1 can be obtained, and these 3 groups of data are at time 1; by parsing the sorted target data 2, 3 groups of car tire pressure data 2 can be obtained, and these 3 groups of data are at time 2; by parsing the sorted target data 3, 3 groups of car tire pressure data 3 can be obtained, and these 3 groups of data are at time 3.

[0116] Among them, the frame format of the first group of data of the automobile tire pressure data 1 can be: [identification of automobile tire pressure data][pressure][temperature][acceleration][check code], and the physical quantity can be: [pressure 10][temperature 40][acceleration 2.5]; the frame format of the second group of data of the automobile tire pressure data 1 can be: [identification of automobile tire pressure data][temperature][pressure][acceleration][check code], and the physical quantity can be: [temperature 41][pressure 10.5][acceleration 2.58], and the frame format of the third group of data of the automobile tire pressure data 1 can be: [identification of automobile tire pressure data][acceleration][temperature][pressure][check code], and the physical quantity can be: [acceleration 2.55][temperature 40.8][pressure 9.5].

[0117] Taking the initial physical quantity of pressure as an example, after sorting in chronological order, we can get: pressure 1, pressure 2, pressure 3 corresponding to time 1, pressure 1, pressure 2, pressure 3 corresponding to time 2, and pressure 1, pressure 2, pressure 3 corresponding to time 3.

[0118] Step 300: Obtain the state of the test tire at the first level jump moment of each target data.

[0119] State refers to whether the test tire is inflated, not inflated, or deflated; moving at a constant speed, accelerating, or decelerating; and rotating or not rotating. While controlling the tire tester's motion according to the test case, the electronic equipment also records the duration of each movement and the corresponding test tire state, enabling subsequent analysis of the vehicle's tire pressure data.

[0120] Therefore, the present application can determine the state of the test tire at the first level jump moment according to the first level jump moment of the target data.

[0121] Step 310: Verify the frame formats and multiple initial physical quantities of multiple groups of tire pressure data of each vehicle according to the state to obtain the frame formats and multiple physical quantities of multiple vehicle tire pressure data.

[0122] For example, assuming the test tire is accelerating at the moment of the first level transition of target data 1, for example, at time 1, with an acceleration of 3, we can preliminarily infer that the test tire's pressure does not exceed 20°C, the temperature does not exceed 50°C, and the acceleration does not exceed 4. Based on this, we can verify the 10 sets of tire pressure data 1. After verification, we can determine that the first, third, and fifth sets of tire pressure data 1 are the frame format and multiple physical quantities of target data 1.

[0123] After this step, each target data can obtain up to 3 sets of data for each vehicle tire pressure data.

[0124] Step 320: Determine a calculation method for each physical quantity of the vehicle tire pressure data according to each physical quantity of the standard vehicle tire pressure data and each physical quantity of the vehicle tire pressure data.

[0125] This step can refer to Figure 3 Step 173 is not described here any more.

[0126] The embodiment of the present application determines multiple target data from the level sample segment data, parses each target data to obtain multiple sets of vehicle tire pressure data, and then verifies the multiple sets of vehicle tire pressure data by testing the status of the tires, thereby improving the frame format of the vehicle tire pressure data and the accuracy of each physical quantity.

[0127] In order to improve the accuracy of multiple physical quantities of automobile tire pressure data, the present application also provides an implementation method, optionally, Figure 5 Shown Figure 4 As shown in the flowchart of the sub-steps of step 290, step 290 includes the following steps:

[0128] Step 291: When each sorted target data contains an identifier of standard automobile tire pressure data, field missing processing, redundant data processing, and abnormal field processing are sequentially performed on the plurality of sorted target data to obtain processed sorted target data.

[0129] Step 292: parse the processed and sorted target data in sequence to obtain multiple groups of frame formats and multiple initial physical quantities of each vehicle tire pressure data.

[0130] First, missing byte values are identified for multiple target data. If a bit in a byte is missing, such as the tire pressure data identifier, missing bits are processed for that byte, meaning they are padded. For example, if the tire pressure data identifier byte in target data 2 is missing, the tire pressure data identifier bytes in target data 1 and target data 3 are obtained and the missing bits are filled using the tire pressure data identifier bytes.

[0131] Then, redundant data detection is performed on multiple target data. Among multiple target data, if two target data are identical, one of the target data is deleted. Specifically, if any three of the four fields representing the tire pressure data, namely, the identifier, pressure, temperature, and acceleration, are identical in two target data, the two target data are considered identical. For example, if the identifier, pressure, and temperature fields representing the tire pressure data in target data 1 are identical to the identifier, pressure, and temperature fields representing the tire pressure data in target data 2, then target data 1 is considered identical to target data 2. In this case, either target data 1 or target data 2 can be deleted.

[0132] Finally, abnormal field detection is performed on multiple target data to identify abnormal fields in the target data. For example, if the pressure field value of target data 1 is 10, the pressure field value of target data 2 is 20, and the pressure field value of target data 3 is also 20, then it can be determined that the pressure field of target data 2 is abnormal. In this case, the pressure field of target data 2 can be deleted or modified to make it conform to the pressure distribution trend.

[0133] After processing missing fields, redundant data, and abnormal fields on multiple target data, the processed and sorted target data can be obtained. Subsequently, the processed and sorted target data can be parsed to obtain multiple sets of frame formats and multiple initial physical quantities for each vehicle tire pressure data.

[0134] By performing field missing processing, redundant data processing, and abnormal field processing on each target data, the abnormal values of the physical quantity fields in each target data can be corrected, making the physical quantities of the target data obtained by analysis more accurate.

[0135] Figure 6 FIG. 1 shows a schematic diagram of the structure of the automobile tire pressure data analysis device provided in an embodiment of the present application. Figure 6 As shown, the automobile tire pressure data analysis device 400 includes: an acquisition module 410, a parsing module 420, a first determination module 430, a filtering module 440, a second determination module 450, an encoding module 460 and an analysis module 470.

[0136] The acquisition module 410 is used to obtain the original automobile tire pressure data and the parameter configuration information corresponding to the original automobile tire pressure data; wherein the original automobile tire pressure data includes configuration area data and data area data, the configuration area data includes sampling baud rate, number of samples, level type and memory offset, and the parameter configuration information includes data encoding format, data baud rate and data frequency deviation; the parsing module 420 is used to parse the data area data according to the number of samples, level type and memory offset to obtain level sample segment data; the first determination module 430 is used to determine the automobile tire pressure data according to the data encoding format, data baud rate and data frequency deviation period deviation range and pulse width deviation range; the filtering module 440 is used to filter the level sample segment data according to the period deviation range and the pulse width deviation range to obtain filtered level sample segment data; the second determination module 450 is used to determine the target level sample segment data from the filtered level sample segment data according to the sampling baud rate and the first level jump moment of each frame of data of the filtered level sample segment data; the encoding module 460 is used to encode the target level sample segment data according to the data encoding format to obtain target data; the analysis module 470 is used to analyze the target data to obtain vehicle tire pressure data.

[0137] The automobile tire pressure data analysis device 400 provided in this embodiment is used to execute the technical solution of the automobile tire pressure data analysis method in the aforementioned method embodiment. Its implementation principle and technical effects are similar and will not be repeated here.

[0138] Figure 7 A schematic structural diagram of an electronic device provided in an embodiment of the present application is shown. The specific embodiment of the present application does not limit the specific implementation of the electronic device.

[0139] like Figure 7 As shown, the electronic device 15 may include a processor 152 and a memory 154 .

[0140] The memory 154 is used to store a computer program 156. The memory 154 may include a high-speed RAM memory, or may also include a non-volatile memory, such as at least one disk memory. The computer program 156 may include computer-executable instructions.

[0141] The processor 152 is configured to execute the computer program 156 to implement the above-mentioned embodiment of the automobile tire pressure data analysis method.

[0142] The processor 152 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application. The one or more processors included in the electronic device may be processors of the same type, such as one or more CPUs, or may be processors of different types, such as one or more CPUs and one or more ASICs.

[0143] An embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the above-mentioned embodiment of the automobile tire pressure data analysis method is implemented.

[0144] An embodiment of the present application provides a computer program that can be executed by a processor to implement the above-mentioned embodiment of the automobile tire pressure data analysis method.

[0145] An embodiment of the present application provides a computer program product, which includes a computer program. When the computer program is executed by a processor, it implements the above-mentioned embodiment of the automobile tire pressure data analysis method.

[0146] In the several embodiments provided in this application, if any function is implemented in the form of a software function module / unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, part or all of the technical solution of this application can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a personal computer, server or other electronic device) to execute all or part of the steps of the method described in each embodiment of this application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), magnetic disk or optical disk, and other media that can store computer program code.

[0147] The algorithm or demonstration provided here are not inherently relevant to any particular computer, virtual system or other equipment. Various general purpose systems can also be used together with the teachings based on this. According to the above description, it is obvious that the structure required for constructing this type of system. In addition, the present application embodiment is not directed to any specific programming language yet. It should be understood that various programming languages can be utilized to realize the content of the present application described here, and the above description of specific languages is for the purpose of disclosing the best mode of implementation of the present application.

[0148] It should be noted that the above embodiments illustrate rather than limit the present application, and that a person skilled in the art may devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between brackets should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The present application may be implemented by means of hardware comprising several different elements and by means of a suitably programmed computer. In claims that list several means, several units or modules of these means may be embodied by the same item of hardware. The use of the words first, second, and third etc. does not indicate any order. These words may be interpreted as names. The steps in the above embodiments should not be understood as limiting the order of execution unless otherwise specified.

[0149] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A method for analyzing automobile tire pressure data, characterized in that: The method comprises: Obtaining original tire pressure data and parameter configuration information corresponding to the original tire pressure data; wherein the original tire pressure data includes configuration area data and data area data, the configuration area data includes sampling baud rate, number of samples, level type and memory offset, and the parameter configuration information includes data encoding format, data baud rate and data frequency deviation; Parsing the data area data according to the number of samples, the level type and the memory offset to obtain level sample segment data; Determine a period deviation range and a pulse width deviation range of the automobile tire pressure data according to the data encoding format, the data baud rate, and the data frequency deviation; Filtering the level sample segment data according to the period deviation range and the pulse width deviation range to obtain filtered level sample segment data; Determining target level sample segment data from the filtered level sample segment data according to the sampling baud rate and the first level jump moment of each frame of data of the filtered level sample segment data; Encoding the target level sample segment data according to the data encoding format to obtain target data; The target data is analyzed to obtain automobile tire pressure data.

2. The method according to claim 1, characterized in that The obtaining of original automobile tire pressure data and parameter configuration information corresponding to the original automobile tire pressure data further includes: Get the original car tire pressure data; Determining a channel number identifying the original automobile tire pressure data, where the channel number corresponds to parameter configuration information of the original automobile tire pressure data; Parameter configuration information corresponding to the original automobile tire pressure data is determined according to the channel number.

3. The method according to claim 1, characterized in that The determining of the period deviation range and the pulse width deviation range of the automobile tire pressure data according to the data encoding format, the data baud rate, and the data frequency deviation further includes: Calculating the period of the vehicle tire pressure data according to the data baud rate; determining a pulse width of the vehicle tire pressure data according to the data encoding format and the cycle of the vehicle tire pressure data; determining a period deviation range of the vehicle tire pressure data according to the period of the vehicle tire pressure data and the data frequency deviation; determining a pulse width deviation range of the tire pressure data according to the pulse width of the tire pressure data and the data frequency deviation; The filtering of the level sample segment data according to the period deviation range and the pulse width deviation range to obtain filtered level sample segment data further includes: Starting from the starting position of the level sample segment data, the levels of the level sample segment data that do not meet the period deviation range or the pulse width deviation range are modified to low levels until the entire level sample segment data is traversed to obtain filtered level sample segment data.

4. The method according to claim 1, wherein The step of determining target level sample segment data from the filtered level sample segment data according to the sampling baud rate and the first level transition moment of each frame of data of the filtered level sample segment data further comprises: Calculate the duration of the target level sample segment data according to the sampling baud rate; Determining a first level jump moment of each frame of the filtered level sample segment data; The target level sample segment data is determined from the filtered level sample segment data according to the first level jump moment of each frame of the filtered level sample segment data and the duration of the target level sample segment data.

5. The method according to claim 1, wherein The automobile tire pressure data includes a frame format and multiple physical quantities; The analyzing the target data to obtain the automobile tire pressure data further includes: Obtain the identifier and multiple physical quantities of standard automobile tire pressure data; When the target data includes an identifier of the standard automobile tire pressure data, parsing the target data to obtain a frame format and multiple physical quantities of the automobile tire pressure data; The method further comprises: A calculation method for each physical quantity of the vehicle tire pressure data is determined according to each physical quantity of the standard vehicle tire pressure data and each physical quantity of the vehicle tire pressure data.

6. The method according to claim 5, characterized in that The step of determining target level sample segment data from the filtered level sample segment data according to the sampling baud rate and the first level transition moment of each frame of data of the filtered level sample segment data further comprises: Determining a plurality of target level sample segment data from the filtered level sample segment data according to the sampling baud rate and the first level jump moment of each frame of the filtered level sample segment data; wherein each frame of data corresponds to each target level sample segment data; The step of encoding the target level sample segment data according to the data encoding format to obtain target data further includes: Encoding the plurality of target level sample segment data according to the data encoding format to obtain a plurality of target data; The method further comprises: sorting the plurality of target data in chronological order based on first level transition moments of the plurality of target data to obtain a plurality of sorted target data; When the target data includes the identifier of the standard automobile tire pressure data, parsing the target data to obtain the frame format and multiple physical quantities of the automobile tire pressure data further includes: When the sorted target data includes the identifier of the standard vehicle tire pressure data, the sorted target data are sequentially parsed to obtain multiple sets of data for each vehicle tire pressure data; wherein each set of data includes a frame format and multiple initial physical quantities, and the same initial physical quantities of the multiple vehicle tire pressure data are sorted in chronological order; Obtaining the state of the test tire at the first level jump moment of each target data; The frame formats and initial physical quantities of multiple groups of tire pressure data of each vehicle are verified according to the state to obtain the frame formats and physical quantities of multiple tire pressure data of the vehicle.

7. The method according to claim 6, characterized in that When the sorted target data includes the identifier of the standard automobile tire pressure data, the sorted target data are sequentially parsed to obtain multiple groups of frame formats and multiple initial physical quantities of each automobile tire pressure data, further comprising: When each of the sorted target data contains the identifier of the standard automobile tire pressure data, sequentially performing field missing processing, redundant data processing, and abnormal field processing on the plurality of sorted target data to obtain processed sorted target data; The processed and sorted target data are analyzed in sequence to obtain multiple groups of frame formats and multiple initial physical quantities of each vehicle tire pressure data.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory, wherein: The processor executes the computer program to implement the automobile tire pressure data analysis method according to any one of claims 1 to 7.

9. An automobile tire pressure data analysis system for analyzing automobile tire pressure data detected by an automobile tire pressure sensor, characterized in that: The system comprises: a tire testing machine, a sensor controller, a standard detection sensor, a signal analyzer and the electronic device according to claim 8; The electronic device is respectively connected to the tire testing machine, the sensor controller and the signal analyzer for communication, the sensor controller and the signal analyzer are respectively used to communicate with the tire pressure sensor of the vehicle to be tested, the standard detection sensor is respectively connected to the sensor controller and the signal analyzer for communication, and the standard detection sensor and the tire pressure sensor of the vehicle to be tested are placed in the test tire of the tire testing machine; wherein, The electronic device is used to send a control instruction to the tire testing machine so that the tire testing machine moves according to the control instruction; The electronic device is further configured to send a startup instruction to the sensor controller and the signal analyzer to start the sensor controller and the signal analyzer; The sensor controller is used to send a start instruction to the standard detection sensor and the tire pressure sensor of the vehicle to be tested, so as to start the standard detection sensor and the tire pressure sensor of the vehicle to be tested; The standard detection sensor is used to detect the first original automobile tire pressure data of the test tire of the tire testing machine when the tire testing machine is moving, and send the first original automobile tire pressure data to the signal analyzer; The signal analyzer is configured to receive the first original vehicle tire pressure data and second original vehicle tire pressure data sent by the tire pressure sensor of the vehicle to be tested, and transmit the first original vehicle tire pressure data and the second original vehicle tire pressure data to the electronic device, wherein the second original vehicle tire pressure data is data obtained by the tire pressure sensor of the vehicle to be tested detecting a test tire of the tire testing machine when the tire testing machine is moving; The electronic device is also used to analyze the first original vehicle tire pressure data and the second original vehicle tire pressure data respectively to obtain first vehicle tire pressure data and second vehicle tire pressure data, and determine the calculation method of the physical quantity of the second vehicle tire pressure data based on the first vehicle tire pressure data.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the automobile tire pressure data analysis method according to any one of claims 1 to 7 is implemented.

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