Vehicle health state data batch processing method based on specified threshold value

Abstract

The invention belongs to the technical field of vehicle health management and big data, particularly relates to a vehicle health state data batch processing method based on a specified threshold value, and provides a vehicle health state data batch processing method in the form of a data batch processing standard process and a data processing parameter table. For different vehicle types, a'vehicle state parameter group name table ', a'specified threshold range table' and a'state parameter group sampling time interval table 'only need to be modified according to the health state parameter characteristics of the vehicle types without understanding a data processing flow and reading a data processing code, so that decoupling of a data processing standard flow and code and data processing parameters is realized, and the data processing efficiency is improved. In addition, research and development personnel can be helped to analyze a data change rule before and after an abnormal value appears by reserving data before and after the abnormal value of the state parameter appears for 10 seconds, and the method has the advantages of increasing data processing speed, improving data quality, improving research and development efficiency and the like.

Description

Technical Field

[0001] The present invention belongs to the technical field of vehicle health management and big data, and particularly relates to a method for batch processing of vehicle health status data based on a specified threshold. Background Art

[0002] With the continuous improvement of vehicle reliability requirements, the importance of vehicle health management has been continuously enhanced. With the continuous deepening of vehicle informatization, the characteristics of big data have become more and more obvious. Generally speaking, vehicle health status data shows characteristics such as a large volume of original data, a low density of valid data, and many data characteristic parameters. In detail, vehicle health status data reflects typical multi-source characteristics: the data comes from multiple subsystems of multiple vehicle units of multiple vehicle models. Through the above analysis, it can be seen that if the original data is directly used, problems such as data being unable to be found, understood, or used well are likely to occur. The data processing method based on a specified threshold can screen out the data outside the specified threshold range, which is convenient for R & D personnel to quickly lock the problem data and improve the R & D efficiency.

[0003] Vehicle health status data is generally stored and managed in multiple state parameter groups, such as the engine state parameter group, the chassis state parameter group, etc. Each state parameter group contains multiple state parameters. For example, the engine state parameter group contains engine speed, engine intake air temperature, engine intake air pressure, etc. At present, the data processing method of vehicle health status data based on a specified threshold is mainly that R & D personnel formulate a data processing process for a single vehicle model according to their own data processing habits and write corresponding data processing codes in the data processing software. When the vehicle model changes, R & D personnel need to re-formulate the data processing process and write codes, or understand the existing data processing codes of a certain vehicle model and modify them on this basis. There is a lack of a standard data processing process applicable to all vehicle models. Therefore, it is difficult to use the data processing software for rapid batch processing of data, resulting in low work efficiency, high cost, and poor effect. There is an urgent need to develop a general method for batch processing of vehicle health status data based on a specified threshold, so as to improve the data analysis efficiency and fully release the data value. Summary of the Invention

[0004] (1) Technical Problems to be Solved

[0005] The technical problem to be solved by the present invention is as follows: How to solve the problem that the existing vehicle health status data processing method based on a specified threshold mainly involves R & D personnel formulating a data processing process for a single vehicle model according to their own data processing habits and writing corresponding data processing codes in the data processing software. When the vehicle model changes, R & D personnel need to re-formulate the data processing process and write codes, or understand the existing data processing codes of a certain vehicle model and modify them on this basis. There is a lack of a standard data processing process applicable to all vehicle models, so it is difficult to use the data processing software for rapid batch processing of data, resulting in low work efficiency, high costs, and poor effects.

[0006] (II) Technical Solution

[0007] To solve the above technical problem, the present invention provides a method for batch processing vehicle health status data based on a specified threshold. The method includes the following steps:

[0008] Step 1: Read the values of each status parameter in each vehicle status parameter group and save them as a status parameter value table;

[0009] Step 2: Read the vehicle status parameter group name table, and read the corresponding status parameter value table according to the names and the number of parameters of each status parameter group in the vehicle status parameter group name table;

[0010] Step 3: Read the specified threshold range table, and save the row numbers where the values in the status parameter value table are not within the specified threshold range in the outlier row number table;

[0011] Step 4: Find all the parameters without row number records in the outlier row number table, and delete all the values of these parameters in the status parameter value table;

[0012] Step 5: Read the status parameter group sampling time interval table, and calculate the sampling points c of the status parameter group in a 10s duration according to the sampling time interval Δt i of the status parameter group by formula (1). If the number of sampling points is not an integer, round it to an integer; i

[0013]

[0014] Step 6: Determine the minimum value p imin and the maximum value p imax of all the row numbers in the outlier row number table;

[0015] Step 7: Calculate the minimum number of rows h imin and the maximum number of rows h imax that the parameter values should retain after the status parameter value table undergoes data processing based on the specified threshold according to formula (2) and formula (3);

[0016] himin = p imin - c i (2);

[0017] h imax = p imax + c i (3);

[0018] Step 8: After deleting all rows in the status parameter value table with column deletion where the number of rows is less than the minimum number of rows to be retained for the parameter values described in Step 7 and all rows where the number of rows is greater than the maximum number of rows to be retained for the parameter values described in Step 7, a status parameter value table generated after batch processing of vehicle health status data based on a specified threshold is obtained;

[0019] Step 9: Repeat Steps 2 to 8 for each status parameter group of the vehicle to obtain m status parameter value tables generated after batch processing of the status parameter value tables of n status parameter groups of the vehicle based on a specified threshold;

[0020] Step 10: When the vehicle model changes, according to the health status parameter characteristics of the changed vehicle model, modify the vehicle status parameter group name table in Step 2, the specified threshold range table in Step 3, and the status parameter group sampling time interval table in Step 4, and repeat Steps 1 to 9 to complete the batch processing of vehicle health status data based on a specified threshold when the vehicle model changes.

[0021] Among them, in the above Step 1, a status parameter group represents all status parameters included in a vehicle health status monitoring unit; and, the sampling times of all status parameters in a status parameter group are the same;

[0022] The specific implementation of the above Step 1 is as follows:

[0023] All status parameter values of the i-th status parameter group among the n status parameter groups of the vehicle are saved as an independent status parameter value table P i , P i The first column of is the sampling time.

[0024] Among them, the specific implementation of the above Step 2 is as follows:

[0025] Read the vehicle status parameter group name table M, and according to the name Name of the i-th status parameter group and the number of its status parameters Num in the vehicle status parameter group name table i and its number of status parameters Num i Read the corresponding status parameter value table.

[0026] Among them, in the said step 3, the line numbers where the values of all state parameters not within the specified threshold range in a state parameter group are saved as an independent outlier line number table. If the outlier line number table is an empty table, steps 4 to 8 are not implemented, and step 9 is directly implemented;

[0027] Among them, the specific implementation of the said step 3 is as follows:

[0028] g ij is the value of the i-th row and j-th column in the specified threshold range table G, representing the specified threshold range of the j-th state parameter in the i-th state parameter group. Using data processing software, the state parameter value table P i the line numbers where the values of the j-th state parameter p ij not within the specified threshold range g ij are saved in the outlier line number table E i .

[0029] Among them, the specific implementation of the said step 4 is as follows:

[0030] Find all the parameters without line number records in the outlier line number table E i , and delete all the values of these parameters in the state parameter value table P i to obtain the column-deleted state parameter value table Q i .

[0031] Among them, the specific implementation of the said step 5 is as follows:

[0032] The i-th parameter Δt in the state parameter group sampling time interval table T i is the sampling time interval of the i-th state parameter group. The sampling point number c of the i-th state parameter group in a 10s duration is calculated by formula (1) i . If c i is not an integer, it is rounded to an integer.

[0033] Among them, the specific implementation of the said step 7 is as follows:

[0034] Calculate the minimum line number h i and the maximum line number h imin that the parameter values should be retained after data processing based on the specified threshold for the state parameter value table P imax . If h imin < 1, then let h imin = 1. r imax is the maximum line number of the state parameter value table P i . If h imax > r imax , then let h imax = r imax .

[0035] Among them, the specific implementation of step 8 is as follows:

[0036] Delete all rows in the state parameter value table Q i with the number of rows less than h imin and greater than h imax to obtain table W i , where W i is the state parameter value table P of the i-th state parameter group i which is the state parameter value table generated after batch processing of data based on a specified threshold.

[0037] Among them, the specific implementation of step 9 is as follows:

[0038] Use data processing software to repeat steps 2 to 8 for each state parameter group of the vehicle to obtain the state parameter value tables {P1, P2,..., P k ,..., P n} of n state parameter groups of the vehicle, and generate m state parameter value tables {W1, W2,..., W u ,..., W m} after batch processing of data based on a specified threshold, where m ≤ n. When m < n, it means that the state parameter values of (n - m) state parameter groups among the n state parameter groups of the vehicle are all within the specified threshold range.

[0039] (III) Beneficial effects

[0040] In order to solve the following problems existing in the prior art:

[0041] The vehicle health status data processing method based on a specified threshold mainly involves R & D personnel formulating a data processing process for a single vehicle model according to their own data processing habits and writing corresponding data processing codes in the data processing software. When the vehicle model changes, R & D personnel need to re-formulate the data processing process and write codes, or understand the existing data processing codes of a certain vehicle model and modify them on this basis. There is a lack of a standard data processing process applicable to all vehicle models, so it is difficult to perform rapid batch processing of data using data processing software, resulting in low work efficiency, high costs, and poor effects.

[0042] The present invention provides a method for batch processing of vehicle health status data based on a specified threshold. It uses a data acquisition device to read and save the values of each status parameter in each group of vehicle status parameters, reads the corresponding status parameter value table according to the name and number of parameters in the vehicle status parameter group name table, saves the row numbers where the values in the status parameter value table are not within the specified threshold range in the outlier row number table, finds all the parameters without row records in the outlier row number table, deletes all the values of these parameters in the status parameter value table, calculates the number of sampling points of the status parameter group in a 10s duration according to the sampling time interval of the status parameter group, determines the minimum and maximum values of all the row numbers in the outlier row number table, calculates the minimum and maximum row numbers that the parameter values should retain after data processing of the status parameter value table based on the specified threshold, and deletes the rows in the status parameter value table with column deletion where the number of rows is less than the minimum row number that the parameter values should retain and all the rows where the number of rows is greater than the maximum row number that the parameter values should retain, to obtain the status parameter value table generated after batch processing of the vehicle health status data based on the specified threshold.

[0043] The present invention proposes a method for batch processing of vehicle health status data in the form of "standard data batch processing process" plus "data processing parameter table". For different vehicle models, only the "vehicle status parameter group name table", "specified threshold range table" and "status parameter group sampling time interval table" need to be modified according to the health status parameter characteristics of the vehicle model, without the need to understand the data processing process and read the data processing code, realizing the decoupling of the data processing standard process and code from the data processing parameters. In addition, by retaining the data 10s before and after the occurrence of status parameter outliers, it can help R & D personnel analyze the data change rules before and after the occurrence of outliers. The present invention has advantages such as accelerating the data processing speed, improving the data quality, and enhancing the R & D efficiency. Brief Description of the Drawings

[0044] Figure 1 It is a flowchart of the method for batch processing of vehicle health status data based on a specified threshold according to the present invention. Detailed Embodiment

[0045] To make the objectives, content, and advantages of the present invention clearer, the following further describes the detailed embodiments of the present invention in conjunction with the drawings and embodiments.

[0046] The implementation process of the present invention is as Figure 1As shown in the figure, the design idea is described as follows: The present invention uses a data acquisition device to read and save the values of each state parameter in each vehicle state parameter group, reads the corresponding state parameter value table according to the name and number of parameters of the state parameter groups in the vehicle state parameter group name table, saves the row numbers where the values in the state parameter value table are not within the specified threshold range in the outlier row number table, finds all the parameters without row records in the outlier row number table, deletes all the values of these parameters in the state parameter value table, calculates the number of sampling points of the state parameter group in a 10s duration according to the sampling time interval of the state parameter group, determines the minimum and maximum values of all row numbers in the outlier row number table, calculates the minimum and maximum row numbers that the parameter values should retain after data processing of the state parameter value table based on the specified threshold, and deletes the rows in the state parameter value table with column deletion where the number of rows is less than the minimum row number that the parameter values should retain and all the rows where the number of rows is greater than the maximum row number that the parameter values should retain, to obtain the state parameter value table generated after batch processing of the vehicle health status data based on the specified threshold.

[0047] The present invention proposes a method for batch processing of vehicle health status data in the form of "standard process for batch data processing" plus "data processing parameter table". For different vehicle models, only the "vehicle state parameter group name table", "specified threshold range table", and "state parameter group sampling time interval table" need to be modified according to the health status parameter characteristics of the vehicle model, without the need to understand the data processing process and read the data processing code, realizing the decoupling of the data processing process and code from the data processing parameters. In addition, by retaining the data 10s before and after the occurrence of state parameter outliers, it can help R & D personnel analyze the data change rules before and after the occurrence of outliers. The present invention has advantages such as accelerating the data processing speed, improving the data quality, and enhancing the R & D efficiency.

[0048] The present invention includes:

[0049] Step 1: Use a data acquisition device to read the values of each state parameter in each vehicle state parameter group and save them as a state parameter value table;

[0050] Among them, in the said Step 1, the data acquisition device is preferably a vehicle health status data acquisition device;

[0051] Among them, in the said Step 1, a state parameter group represents all the state parameters included in a vehicle health status monitoring unit;

[0052] Among them, in the said Step 1, all the state parameters in a state parameter group have the same sampling time.

[0053] Among them, the specific implementation steps of the said Step 1 are as follows:

[0054] All the state parameter values of the i-th state parameter group among the n vehicle state parameter groups are saved as an independent state parameter value table Pi , P i The first column of i is the sampling time.

[0055] Step 2: Use data processing software to read the vehicle status parameter group name table, and read the corresponding status parameter value table according to the names and the number of parameters of each status parameter group in the vehicle status parameter group name table.

[0056] Among them, in the said Step 2, the data processing software is preferably MATLAB, PyCharm, or R language;

[0057] Among them, the specific implementation steps of the said Step 2 are as follows:

[0058] Use data processing software to read the vehicle status parameter group name table M, and read the corresponding status parameter value table according to the name Name i of the i-th status parameter group and its number of status parameters Num i in the vehicle status parameter group name table.

[0059] Step 3: Use data processing software to read the specified threshold range table G, and save the row numbers of the values in the status parameter value table that are not within the specified threshold range in the outlier row number table;

[0060] Among them, in the said Step 3, the data processing software is preferably MATLAB, PyCharm, or R language;

[0061] Among them, in the said Step 3, the specified threshold range is determined by the vehicle model;

[0062] Among them, in the said Step 3, the row numbers of all the status parameter values in a status parameter group that are not within the specified threshold range are saved as an independent outlier row number table. If the outlier row number table is an empty table, Steps 4 to 8 are not implemented, and Step 9 is directly implemented;

[0063] Among them, the specific implementation steps of the said Step 3 are as follows:

[0064] g ij is the value in the i-th row and j-th column of the specified threshold range table G, representing the specified threshold range of the j-th status parameter in the i-th status parameter group. Use data processing software to process the status parameter value table P i to save the row numbers of the values of the j-th status parameter p ij in P that are not within the specified threshold range g ij in the outlier row number table E i .

[0065] Step 4: Use data processing software to find all the parameters in the outlier row number table that have no row records, and delete all the values of these parameters in the status parameter value table;

[0066] Among them, in the said step 4, the data processing software is preferably MATLAB, PyCharm, or R language;

[0067] Among them, the specific implementation steps of the said step 4 are as follows:

[0068] Use the data processing software to find out the outlier row number table E i All the parameters without row number records in it, and delete all the values of these parameters in the status parameter value table P i to obtain the column-deleted status parameter value table Q i .

[0069] Step 5: Use the data processing software to read the sampling time interval table T of the status parameter group, and calculate the number of sampling points of the status parameter group in a 10s duration according to the sampling time interval of the status parameter group by formula (1). If the number of sampling points is not an integer, round it to an integer.

[0070]

[0071] Among them, in the said step 5, the data processing software is preferably MATLAB, PyCharm, or R language;

[0072] Among them, in the said step 5, the sampling time interval of the status parameter group is determined by the vehicle model.

[0073] Among them, the specific implementation steps of the said step 5 are as follows:

[0074] The i-th parameter Δt in the sampling time interval table T of the status parameter group i is the sampling time interval of the i-th status parameter group, and the number of sampling points c of the i-th status parameter group in a 10s duration is calculated by formula (1) i , if c i is not an integer, round it to an integer.

[0075] Step 6: Use the data processing software to determine the minimum value and the maximum value of all row numbers in the outlier row number table;

[0076] Among them, in the said step 6, the data processing software is preferably MATLAB, PyCharm, or R language;

[0077] Among them, the specific implementation steps of the said step 6 are as follows:

[0078] Use the data processing software to determine the outlier row number table E i The minimum value p of all row numbers in it imin and the maximum value p imax .

[0079] Step 7: Using data processing software, calculate the minimum and maximum number of rows of parameter values to be retained after data processing based on a specified threshold according to Equations (2) and (3) to obtain a table of state parameter values.

[0080] h imin = p imin - c i (2)

[0081] h imax = p imax + c i (3)

[0082] Wherein, in the said Step 7, the data processing software is preferably MATLAB, PyCharm, or R language.

[0083] The specific implementation steps of the said Step 7 are as follows:

[0084] Using data processing software, calculate the state parameter value table P according to Equations (2) and (3) i The minimum number of rows h of parameter values to be retained after data processing based on a specified threshold imin and the maximum number of rows h imax . If h imin < 1, then set h imin = 1. Let r imax be the maximum number of rows of the state parameter value table P i . If h imax > r imax , then set h imax = r imax .

[0085] Step 8: After using data processing software to delete all rows with the number of rows less than the minimum number of rows of parameter values to be retained in Step 7 and all rows with the number of rows greater than the maximum number of rows of parameter values to be retained in Step 7 from the state parameter value table with columns deleted, obtain the state parameter value table generated after batch processing of vehicle health state data based on a specified threshold.

[0086] Wherein, in the said Step 8, the data processing software is preferably MATLAB, PyCharm, or R language.

[0087] The specific implementation steps of the said Step 8 are as follows:

[0088] Using data processing software to delete all rows with the number of rows less than h i and all rows with the number of rows greater than h imin from the state parameter value table Q imax with columns deleted to obtain table W i . W i is the state parameter value table P of the i-th state parameter group. iA table of state parameter values generated after batch processing of data based on a specified threshold.

[0089] Step 9: Use data processing software to repeat Steps 2 to 8 for each state parameter group of the vehicle, and obtain m tables of state parameter values generated after batch processing of the tables of state parameter values of n state parameter groups of the vehicle based on a specified threshold.

[0090] Among them, in the said Step 9, the data processing software is preferably MATLAB, PyCharm, or R language.

[0091] Among them, the specific implementation steps of the said Step 9 are as follows:

[0092] Use data processing software to repeat Steps 2 to 8 for each state parameter group of the vehicle, and obtain the table of state parameter values {P1, P2, …, P k , … P n} of n state parameter groups of the vehicle, and m tables of state parameter values {W1, W2, …, W u , … W m} generated after batch processing of the data based on a specified threshold, where m ≤ n. When m < n, it means that the state parameter values of (n - m) state parameter groups among the n state parameter groups of the vehicle are all within the specified threshold range.

[0093] Step 10: When the vehicle model changes, according to the characteristics of the health state parameters of the changed vehicle model, modify the table of vehicle state parameter group names in Step 2, the table of specified threshold ranges in Step 3, and the table of state parameter group sampling time intervals in Step 4, and repeat Steps 1 to 9 to complete the batch processing of vehicle health state data based on a specified threshold when the vehicle model changes.

[0094] Example 1

[0095] To solve the above technical problems, this example provides a method for batch processing of vehicle health state data based on a specified threshold, and the method includes the following steps:

[0096] Step 1: Use a vehicle health state data acquisition device to read the state parameter values of 3 state parameter groups of the vehicle and save them as a table of state parameter values. Among them, the first state parameter group is the vehicle chassis state parameter group, and its table of state parameter values P1 is shown in Table 1; the second state parameter group is the vehicle transmission state parameter group, and its table of state parameter values P2 is shown in Table 2; the third state parameter group is the vehicle engine state parameter group, and its table of state parameter values P3 is shown in Table 3.

[0097] Step 2: Use data processing software to read the vehicle status parameter group name table M, and read the status parameter value tables P1, P2, and P3 in Step 1 according to the names and the number of parameters of the three status parameter groups in the vehicle status parameter group name table. In MATLAB, the readtable function can be used to read the vehicle status parameter group name table and the status parameter value tables in Step 1.

[0098] Step 3: Use data processing software to read the specified threshold range of each status parameter in the specified threshold range table G shown in Table 5, and save the row numbers of the status parameter values that are not within the specified threshold range in the three status parameter value tables in Step 2 as independent outlier row number tables respectively. Table 6 is the outlier row number table E1 of the vehicle chassis status parameter group, and Table 7 is the outlier row number table E2 of the vehicle transmission status parameter group. Since all the status parameter values in the vehicle engine status parameter group are within the specified threshold range, there is no outlier row number table for the vehicle engine status parameter group. In MATLAB, the readtable function can be used to read the specified threshold range table, and the find function can be used to find the row numbers of the status parameter values that are not within the specified threshold range in the status parameter value table.

[0099] Step 4: Use data processing software to find the parameters without row records in the outlier row number tables E1 and E2 respectively, and delete all the values of these parameters in the corresponding status parameter value tables P1 and P2 to obtain the column-reduced status parameter value tables Q1 and Q2, as shown in Table 8 and Table 9. In MATLAB, the isempty function can be used to find the parameters without row records in the outlier row number table.

[0100] Step 5: Use data processing software to read the status parameter group sampling time interval table T shown in Table 10. According to the sampling time intervals of each status parameter group, it is calculated by Equation (1) that the number of sampling points of the vehicle chassis status parameter group in a 10s duration is 10, and the number of sampling points of the vehicle transmission status parameter group in a 10s duration is 5. In MATLAB, the readtable function can be used to read the status parameter group sampling time interval table.

[0101] Step 6: Use data processing software to determine that the minimum number of rows of the outlier row number table E1 of the vehicle chassis status parameter group is p 1min = 3, and the maximum number of rows is p 1max = 35. The minimum number of rows of the outlier row number table E2 of the vehicle transmission status parameter group is p 2min = 12, and the maximum number of rows is p 2max = 27. In MATLAB, the min function can be used to determine the minimum number of rows, and the max function can be used to determine the maximum number of rows.

[0102] Step 7: Using data processing software, calculate the vehicle chassis state parameter value table P1 according to Equation (2) and Equation (3). After data processing based on the specified threshold, the minimum number of rows of parameter values to be retained is h 1min = 1, and the maximum number of rows is h 1max = 45. After data processing based on the specified threshold for the vehicle transmission state parameter value table P2, the minimum number of rows of parameter values to be retained is h 2min = 7, and the maximum number of rows is h 2max = 32.

[0103] Step 8: Using data processing software, after deleting all rows with less than 1 and greater than 45 rows in the state parameter value table Q1 with columns deleted, obtain the state parameter value table W1 generated after batch data processing of the state parameter value table P1 of the vehicle chassis state parameter group based on the specified threshold, as shown in Table 11. After deleting all rows with less than 7 and greater than 32 rows in the state parameter value table Q2 with columns deleted, obtain the state parameter value table W2 generated after batch data processing of the state parameter value table P2 of the vehicle transmission state parameter group based on the specified threshold, as shown in Table 12. In MATLAB, the writematrix function can be used to output the state parameter value table generated after batch data processing of the state parameter value table based on the specified threshold as a table file in formats such as xls and txt.

[0104] Step 9: Using data processing software, repeat Steps 2 to 7 for each state parameter group of the vehicle to obtain two state parameter value tables {W1, W2} generated after batch data processing of the state parameter value tables {P1, P2, P3} of the three state parameter groups of the vehicle based on the specified threshold. The state parameter values of one state parameter group are all within the specified threshold range.

[0105] Step 10: When the vehicle model changes, according to the health state parameter characteristics of the changed vehicle model, modify the vehicle state parameter group name table in Step 2, the specified threshold range table in Step 3, and the state parameter group sampling time interval table in Step 4, and repeat Steps 1 to 9 to complete the batch processing of vehicle health state data based on the specified threshold after the vehicle model change.

[0106] The present invention has advantages such as accelerating data processing speed, improving data quality, and enhancing R & D efficiency. It proposes a method for batch processing of vehicle health status data in the form of "standard process for batch data processing" plus "data processing parameter table". For different vehicle models, it only needs to modify the "vehicle status parameter group name table", "specified threshold range table", and "status parameter group sampling time interval table" according to the health status parameter characteristics of the vehicle model, without the need to understand the data processing process and read the data processing code, achieving the decoupling of the data processing standard process and code from the data processing parameters. Additionally, by retaining the data 10 seconds before and after the occurrence of status parameter outliers, it can help R & D personnel analyze the data change rules before and after the occurrence of outliers.

[0107] Table 1 Vehicle Chassis Status Parameter Group Status Parameter Value Table P1

[0108]

[0109]

[0110]

[0111] Table 2 Vehicle Transmission Status Parameter Group Status Parameter Value Table P2

[0112]

[0113]

[0114] Table 3 Vehicle Engine Status Parameter Group Status Parameter Value Table P3

[0115]

[0116]

[0117] Table 4 Vehicle Status Parameter Group Name Table M

[0118] Status parameter group name Number of status parameters Vehicle chassis status parameter group 5 Vehicle transmission status parameter group 6 Vehicle engine status parameter group 5

[0119] Table 5 Specified Threshold Range Table G

[0120]

[0121] Table 6 Vehicle Chassis Status Parameter Group Outlier Row Number Table E1

[0122] Chassis power distribution self-check status Air compressor exhaust pressure Mpa Chassis controller input voltage V 6 6 3 25 27 33 35

[0123] Table 7 Vehicle Transmission Status Parameter Group Outlier Row Number Table E2

[0124] Vortex speed 12 23 26 27

[0125] Table 8 Table Q1 of State Parameter Values after Deleting Columns of Vehicle Chassis State Parameter Group

[0126]

[0127]

[0128]

[0129]

[0130] Table 9 Table Q2 of State Parameter Values after Deleting Columns of Vehicle Transmission State Parameter Group

[0131]

[0132]

[0133] Table 10 Table T of Sampling Time Intervals of State Parameter Groups

[0134]

[0135] Table 11 Table W1 of State Parameter Values after Batch Processing of Vehicle Chassis State Parameter Group Based on Specified Thresholds

[0136]

[0137]

[0138] Table 12 Table W2 of State Parameter Values after Batch Processing of Vehicle Transmission State Parameter Group Based on Specified Thresholds

[0139]

[0140]

[0141] The above are only the preferred embodiments of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the technical principle of the present invention, several improvements and modifications can be made, and these improvements and modifications should also be regarded as the protection scope of the present invention.

Claims

1. A method for batch processing of vehicle health status data based on a specified threshold, characterized in that, The method includes the following steps: Step 1: Read the values of each state parameter in each state parameter group of the vehicle and save them as a state parameter value table; Step 2: Read the vehicle state parameter group name table, and read the corresponding state parameter value table according to the names and the number of parameters of each state parameter group in the vehicle state parameter group name table; Step 3: Read the specified threshold range table, and save the row numbers of the values in the state parameter value table that are not within the specified threshold range in the outlier row number table; Step 4: Find all the parameters without row records in the outlier row number table, and delete all the values of these parameters in the state parameter value table; Step 5: Read the sampling time interval table of the status parameter group, and according to the sampling time interval Δt of the status parameter group i , calculate the number of sampling points c of the status parameter group in a 10s duration according to Equation (1) i , and if the number of sampling points is not an integer, round it to an integer; Step 6: Determine the minimum value p of all the row numbers in the outlier row number table imin and the maximum value p imax ; Step 7: After the state parameter value table calculated according to Equation (2) and Equation (3) undergoes data processing based on a specified threshold, the minimum number of rows h and the maximum number of rows h that the parameter values should retain imin ; imax ; h imin = p imin - c i (2); h imax = p imax + c i (3); Step 8: After deleting the rows in the state parameter value table with column deletion where all the row numbers are less than the minimum number of rows that the parameter values should retain as described in Step 7 and all the row numbers are greater than the maximum number of rows that the parameter values should retain as described in Step 7, a state parameter value table generated after batch processing of the vehicle health status data based on the specified threshold is obtained; Step 9: Repeat Steps 2 to 8 for each state parameter group of the vehicle to obtain m state parameter value tables generated after batch processing of the state parameter value tables of n state parameter groups of the vehicle based on the specified threshold; Step 10: When the vehicle model changes, according to the health status parameter characteristics of the changed vehicle model, modify the vehicle state parameter group name table in Step 2, the specified threshold range table in Step 3, and the state parameter group sampling time interval table in Step 4, and repeat Steps 1 to 9 to complete the batch processing of the vehicle health status data based on the specified threshold when the vehicle model changes.

2. The method for batch processing of vehicle health status data based on a specified threshold as claimed in claim 1, wherein In Step 1, a state parameter group represents all the state parameters included in a vehicle health status monitoring unit; moreover, the sampling times of all the state parameters in a state parameter group are the same; The specific implementation of Step 1 is as follows: All state parameter values of the $i$-th state parameter group among the $n$ state parameter groups of the vehicle are saved as an independent state parameter value table $P$. i , $P$ i The first column of which is the sampling time.

3. The method for batch processing of vehicle health status data based on a specified threshold as claimed in claim 2, wherein The specific implementation of Step 2 is as follows: Read the vehicle status parameter group name table M, and according to the name Name of the i-th status parameter group in the vehicle status parameter group name table i and its number of status parameters Num i Read the corresponding status parameter value table.

4. The method for batch processing of vehicle health status data based on a specified threshold according to claim 3, characterized in that, In Step 3, the row numbers of the values of all the state parameters in a state parameter group that are not within the specified threshold range are saved as an independent outlier row number table. If the outlier row number table is an empty table, Steps 4 to 8 are not implemented, and Step 9 is directly implemented; Among them, the specific implementation of Step 3 is as follows: g ij It represents the value of the j-th column in the i-th row of the specified threshold range table G, indicating the specified threshold range of the j-th state parameter in the i-th state parameter group. Using data processing software, the state parameter value table P i the j-th state parameter p ij whose value is not within the specified threshold range g ij in the number of rows where the values are located is saved in the outlier row number table E i .

5. The method for batch processing of vehicle health status data based on a specified threshold as described in claim 4, wherein The specific implementation of Step 4 is as follows: Find the table E of the number of rows of outliers i All the parameters without row numbers in it, and delete all the values of these parameters in the status parameter value table P i to obtain the status parameter value table Q with columns deleted i .

6. The method for batch processing of vehicle health status data based on a specified threshold according to claim 5, wherein The specific implementation of Step 5 is as follows: The i-th parameter Δt in the state parameter group sampling time interval table T i is the sampling time interval of the i-th state parameter group, and the number of sampling points c of the i-th state parameter group in a 10s duration is calculated by Equation (1). i , if c i is not an integer, it is rounded to an integer.

7. The method for batch processing of vehicle health status data based on a specified threshold according to claim 6, characterized in that, The specific implementation of Step 7 is as follows: The state parameter value table P is calculated according to equations (2) and (3). i The minimum number of rows h that the parameter values should retain after data processing based on a specified threshold imin and the maximum number of rows h imax If h imin < 1, then set h imin = 1, r imax is the maximum number of rows of the state parameter value table P i If h imax > r imax then set h imax = r imax .

8. The method for batch processing of vehicle health status data based on a specified threshold according to claim 7, wherein The specific implementation of Step 8 is as follows: The state parameter value table Q with columns deleted i in which all rows with a number of rows less than h imin and rows with a number of rows greater than h imax are deleted to obtain table W i , W i is the state parameter value table P of the i-th state parameter group i which is the state parameter value table generated after batch processing of data based on a specified threshold value 9. The method for batch processing of vehicle health status data based on a specified threshold as claimed in claim 8, wherein The specific implementation of Step 9 is as follows: Repeat steps 2 to 8 for each set of vehicle state parameters using the data processing software to obtain a table of state parameter values {P1, P2, …, P k , …, P n} for n sets of vehicle state parameters. After batch processing of the data based on a specified threshold, m tables of state parameter values {W1, W2, …, W u , …, W m} are generated, where m ≤ n. When m < n, it means that the state parameter values of (n - m) sets of vehicle state parameters are all within the specified threshold range.

10. The method for batch processing of vehicle health status data based on a specified threshold as claimed in claim 9, wherein, The method has the advantages of accelerating the data processing speed, improving the data quality, and enhancing the R & D efficiency.

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