CN115407747B - Data processing method and device and vehicle - Google Patents

Data processing method and device and vehicle Download PDF

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Publication number
CN115407747B
CN115407747B CN202210887100.5A CN202210887100A CN115407747B CN 115407747 B CN115407747 B CN 115407747B CN 202210887100 A CN202210887100 A CN 202210887100A CN 115407747 B CN115407747 B CN 115407747B
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simulation
signal
sampling
data
target
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CN115407747A (en
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郭笑通
李论
王仕伟
侯杰
陈志刚
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FAW Group Corp
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FAW Group Corp
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults

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  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Automation & Control Theory (AREA)
  • Electric Propulsion And Braking For Vehicles (AREA)

Abstract

The application discloses a data processing method and device and a vehicle. The method comprises the following steps: acquiring at least one initial signal data when a vehicle fails; acquiring initial signal periods in each initial signal data, determining an initial signal period with the shortest period from at least one initial signal period, and obtaining a target signal period; determining a plurality of simulation sampling moments through a target signal period, and generating a plurality of simulation signal values according to the simulation sampling moments, the signal value of each initial signal data and the signal sampling moment respectively; and respectively establishing association relations between a plurality of simulation sampling moments and a plurality of simulation signal values of each initial signal data to obtain simulation data corresponding to the faults. The application solves the problems of long time and low accuracy required by the method for manually processing the signal data in the related technology, and the failure cause cannot be accurately determined.

Description

Data processing method and device and vehicle
Technical Field
The present application relates to the field of data processing, and in particular, to a data processing method and apparatus, and a vehicle.
Background
With the development of automobile chassis electric control systems, more and more vehicles begin to carry control units of braking systems such as an electronic booster, an electronic stability control system, an integrated braking control system and the like, and signals on a vehicle CAN network CAN be acquired in real time through vehicle-mounted CAN (Controller Area Network) equipment during real-vehicle road test. Therefore, after the vehicle has faults, the fault recovery and the fault determination of the vehicle faults CAN be carried out by intercepting CAN data comprising the fault occurrence time.
The currently adopted fault reproduction and fault determination methods are as follows: after the cut CAN data is manually adjusted and analyzed, signals in the CAN data are simulated, the simulation signals are sent to a test control system, state information of a tested control unit is collected, and fault recurrence is carried out. However, the method of manually analyzing the CAN data is time-consuming and labor-consuming, and each piece of data cannot be accurately processed due to huge data volume, so that the test control system cannot accurately reproduce the fault and determine the cause of the fault.
Aiming at the problems that the method for manually processing signal data in the related art is long in time and low in accuracy, and the failure cause cannot be accurately determined, no effective solution is proposed at present.
Disclosure of Invention
The application provides a data processing method and device and a vehicle, and aims to solve the problems that in the related art, the time required by a method for manually processing signal data is long, the accuracy is low, and the failure cause cannot be accurately determined.
According to one aspect of the present application, a data processing method is provided. The method comprises the following steps: acquiring at least one initial signal data when a vehicle fails, wherein each initial signal data at least comprises an initial signal period, a plurality of signal values and a signal sampling time of each signal value; acquiring initial signal periods in each initial signal data, obtaining at least one initial signal period, determining the initial signal period with the shortest period from the at least one initial signal period, and obtaining a target signal period; determining a plurality of simulation sampling moments through a target signal period, and generating a plurality of simulation signal values of each initial signal data according to the simulation sampling moments, the signal values of each initial signal data and the signal sampling moments; and respectively establishing association relations between a plurality of simulation sampling moments and a plurality of simulation signal values of each initial signal data to obtain a plurality of groups of target simulation data, and determining the plurality of groups of target simulation data as simulation data corresponding to faults.
Optionally, determining the plurality of simulated sampling instants by the target signal period includes: acquiring the minimum signal sampling time and the maximum signal sampling time in the signal sampling time of all the initial signal data, and determining the difference value between the maximum signal sampling time and the initial information sampling time as simulation time length; dividing the target signal period by a preset proportion to reduce the target signal period to obtain a simulation signal period; and generating a plurality of simulation sampling points of each initial signal data according to the simulation signal period in the simulation time length, and simulating sampling time of each simulation sampling point.
Optionally, generating the plurality of simulated signal values of each initial signal data according to the plurality of simulated sampling moments, the signal value of each initial signal data, and the signal sampling moment, respectively, includes: respectively acquiring simulation sampling moments with shortest interval with each signal sampling moment in target initial signal data from a plurality of simulation sampling moments to obtain a plurality of first simulation sampling moments, wherein the target initial signal data is any initial signal data; setting the simulation signal value of each simulation sampling point at the first simulation sampling moment as the signal value of the corresponding signal sampling moment, and setting the simulation signal values of the rest simulation sampling points to zero to obtain a plurality of first simulation signal values, wherein the rest simulation sampling points are simulation sampling points except the simulation sampling points at the first simulation sampling moment in the plurality of simulation sampling points; the first simulation signal value of each simulation sampling point is adjusted according to the sequence from small to large at the simulation sampling moment, so that a plurality of second simulation signal values are obtained; a plurality of second simulated signal values are determined as simulated signal values of the target initial signal data.
Optionally, adjusting the first simulation signal value of each simulation sampling point in order of from small to large according to the simulation sampling time, to obtain a plurality of second simulation signal values includes: starting from the simulation sampling point with the minimum simulation sampling moment, judging whether the first simulation signal value of each simulation sampling point is larger than a second preset value or not in sequence; under the condition that the first simulation signal value of the current simulation sampling point is not a second preset value, skipping the current simulation sampling point, and judging whether the first simulation signal value of the next simulation sampling point is the second preset value or not; and under the condition that the first simulation signal value of the current simulation sampling point is a second preset value, determining the first simulation signal value of the previous simulation sampling point of the current simulation sampling point as the first simulation signal value of the current simulation sampling point until all simulation sampling points are traversed, and obtaining a plurality of second simulation signal values.
Optionally, before determining a plurality of simulation sampling instants by the target signal period and generating a plurality of simulation signal values for each initial signal data according to the plurality of simulation sampling instants, the signal value for each initial signal data and the signal sampling instant, respectively, the method further comprises: judging whether each initial signal data carries a frame loss mark or not; under the condition that the initial signal data carries a frame loss identification, determining a signal sampling moment corresponding to the frame loss identification; and determining a signal value of the signal sampling moment corresponding to the frame loss identification as a preset value.
Optionally, before determining whether each initial signal data carries a frame loss identifier, the method further includes: respectively determining time differences between adjacent sampling moments in each initial signal data to obtain a plurality of groups of time differences; calculating the frame loss rate in each initial signal data according to the following formula to obtain a plurality of frame loss rates:
Wherein epsilon i.j is the frame loss rate of the ith-1 time difference value of the jth signal, p j is the initial signal period of the jth signal, and Deltat i.j is the time difference value between the ith signal sampling time and the ith-1 signal sampling time of the jth signal; judging whether the frame loss rates are larger than a preset frame loss threshold or not; under the condition that the frame loss rate larger than the preset frame loss threshold exists in the plurality of frame loss rates, acquiring the frame loss rate larger than the preset frame loss threshold to obtain a target frame loss rate, and adding a frame loss identification in initial signal data corresponding to the target frame loss rate.
Optionally, after association relations between a plurality of simulation sampling moments and a plurality of simulation signal values of each initial signal data are respectively established, a plurality of groups of target simulation data are obtained, and the plurality of groups of target simulation data are determined to be simulation data corresponding to faults, the method further includes: judging whether initial signal data corresponding to each group of target simulation data carries a first type identifier, wherein the first type identifier represents a discrete signal; under the condition that the initial signal data corresponding to any group of target simulation data carries a first type identifier, calculating the difference value between the signal values of each group of adjacent sampling moments in the initial signal data corresponding to the target simulation data to obtain a plurality of difference values; judging whether an abnormal difference value exists in the difference values, determining adjacent sampling time groups corresponding to the abnormal difference values under the condition that the abnormal difference value exists, and determining larger signal sampling time in the adjacent sampling time groups as a first sampling time; determining the last sampling time of the first sampling time in the initial signal data corresponding to the target simulation data to obtain a second sampling time, and determining the next sampling time of the first sampling time in the initial signal data corresponding to the target simulation data to obtain a third sampling time; and determining a signal value of the second sampling moment to obtain a first signal value, and changing simulation signal values corresponding to a plurality of simulation sampling moments between the first simulation sampling moment corresponding to the first sampling moment and the first simulation sampling moment corresponding to the third sampling moment into the first signal value in the target simulation data, so as to obtain changed target simulation data.
Optionally, after association relations between a plurality of simulation sampling moments and a plurality of simulation signal values of each initial signal data are respectively established, a plurality of groups of target simulation data are obtained, and the plurality of groups of target simulation data are determined to be simulation data corresponding to faults, the method further includes: judging whether initial signal data corresponding to each group of target simulation data carries a second type identifier, wherein the second type identifier characterizes continuous signals; under the condition that the initial signal data corresponding to any group of target simulation data carries a second type identifier, determining the deviation rate between the signal values of each group of adjacent sampling moments in the initial signal data corresponding to the target simulation data to obtain a plurality of deviation rates; judging whether an abnormal deviation rate exists in the deviation rate, calculating an adjacent sampling time group corresponding to the abnormal deviation rate under the condition that the abnormal deviation rate exists, and determining a larger signal sampling time in the adjacent sampling time group as a fourth sampling time; determining the last sampling time of the fourth sampling time in the initial signal data corresponding to the target simulation data to obtain a fifth sampling time, and determining the next sampling time of the fourth sampling time in the initial signal data corresponding to the target simulation data to obtain a sixth sampling time; and determining a signal value of the fifth sampling moment to obtain a second signal value, and changing simulation signal values corresponding to a plurality of simulation sampling moments between the first simulation sampling moment corresponding to the fourth sampling moment and the first simulation sampling moment corresponding to the sixth sampling moment into the second signal value in the target simulation data, so as to obtain changed target simulation data.
According to another aspect of the present application, there is provided a data processing apparatus. The device comprises: the first acquisition unit is used for acquiring at least one initial signal data when the vehicle fails, wherein each initial signal data at least comprises an initial signal period, a plurality of signal values and a signal sampling time of each signal value; the second acquisition unit is used for acquiring initial signal periods in the initial signal data to obtain at least one initial signal period, and determining the initial signal period with the shortest period from the at least one initial signal period to obtain a target signal period; the generating unit is used for determining a plurality of simulation sampling moments through the target signal period and generating a plurality of simulation signal values of each initial signal data according to the simulation sampling moments, the signal values of each initial signal data and the signal sampling moments; the first determining unit is used for respectively establishing association relations between a plurality of simulation sampling moments and a plurality of simulation signal values of each initial signal data to obtain a plurality of groups of target simulation data, and determining the plurality of groups of target simulation data as simulation data corresponding to faults.
According to another aspect of the embodiments of the present invention, there is also provided a computer storage medium for storing a program, where the program when executed controls a device in which the computer storage medium is located to perform a data processing method.
According to another aspect of embodiments of the present invention, there is also provided an electronic device including one or more processors and a memory; the memory has stored therein computer readable instructions for execution by the processor, wherein the computer readable instructions when executed perform a data processing method.
According to the application, the following steps are adopted: acquiring at least one initial signal data when a vehicle fails, wherein each initial signal data at least comprises an initial signal period, a plurality of signal values and a signal sampling time of each signal value; acquiring initial signal periods in each initial signal data, obtaining at least one initial signal period, determining the initial signal period with the shortest period from the at least one initial signal period, and obtaining a target signal period; determining a plurality of simulation sampling moments through a target signal period, and generating a plurality of simulation signal values of each initial signal data according to the simulation sampling moments, the signal values of each initial signal data and the signal sampling moments; and respectively establishing association relations between a plurality of simulation sampling moments and a plurality of simulation signal values of each initial signal data to obtain a plurality of groups of target simulation data, and determining the plurality of groups of target simulation data as simulation data corresponding to faults. The method solves the problems that the method for manually processing the signal data in the related art has long time and low accuracy, and the failure cause cannot be accurately determined. The target signal period is determined from a plurality of initial signal data, the period and the simulation sampling time of the simulation data are determined according to the target signal period, and the simulation signal value of each simulation sampling time in the simulation data is determined according to the signal value and the signal sampling time in each initial signal data, so that the simulation data are automatically generated through the initial signal data, and the effect of rapidly and accurately generating the simulation data corresponding to the faults of the vehicle is achieved.
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The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application. In the drawings:
FIG. 1 is a flow chart of a data processing method provided according to an embodiment of the present application;
fig. 2 is a schematic diagram of a data processing apparatus according to an embodiment of the present application.
Detailed Description
It should be noted that, without conflict, the embodiments of the present application and features of the embodiments may be combined with each other. The application will be described in detail below with reference to the drawings in connection with embodiments.
In order that those skilled in the art will better understand the present application, a technical solution in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present application without making any inventive effort, shall fall within the scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present application and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate in order to describe the embodiments of the application herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
It should be noted that, related information (including, but not limited to, user equipment information, user personal information, etc.) and data (including, but not limited to, data for presentation, analyzed data, etc.) related to the present disclosure are information and data authorized by a user or sufficiently authorized by each party. For example, an interface is provided between the system and the relevant user or institution, before acquiring the relevant information, the system needs to send an acquisition request to the user or institution through the interface, and acquire the relevant information after receiving the consent information fed back by the user or institution.
It should be noted that the data processing method and apparatus and a vehicle determined by the present disclosure may be used in the field of data processing, and may also be used in any field other than the field of data processing, and the application field of the data processing method and apparatus and a vehicle determined by the present disclosure is not limited.
According to an embodiment of the present application, there is provided a data processing method.
Fig. 1 is a flowchart of a data processing method according to an embodiment of the present application. As shown in fig. 1, the method comprises the steps of:
Step S102, at least one initial signal data when the vehicle fails is obtained, wherein each initial signal data at least comprises an initial signal period, a plurality of signal values and a signal sampling time of each signal value.
Specifically, when a control unit of a brake system of a vehicle fails, CAN data of the vehicle when the vehicle fails CAN be intercepted, and the vehicle failure is reproduced through the CAN data, so that a failure cause is determined. Because the control unit of the brake system is complex, a large number of signal graphs exist in the obtained CAN data, namely the sampling time and the signal value curve of the CAN signals, so that initial signal data corresponding to each CAN data CAN be obtained from the signal graphs, and a plurality of initial signal data sets CAN be obtained, and the initial signal data sets CAN be expressed as: Wherein t i.k is a set of signal sampling moments of the 1 st to i th signal sampling points of the kth initial signal data, and V i.k is a set of signal values of the 1 st to i th signal sampling points of the kth initial signal data.
Further, an initial signal period corresponding to each initial signal data and identification information of each initial signal data may be obtained from an auxiliary file CANmatrix corresponding to the CAN data, so as to obtain an initial signal period of each initial signal data, a plurality of signal sampling moments of each initial signal data, and a signal value of each signal sampling moment.
The plurality of initial signal data sets do not include the transmission signals in the CAN data, wherein the transmission signals are signals sent by the controlled control unit. Meanwhile, the plurality of initial signal data sets also do not include a check class signal (such as a Checksum signal) and a rolling count class signal (such as a Livecounter signal), that is,Only the non-check class signal and the non-rolling count class signal in the received signal in CAN data.
Step S104, obtaining initial signal periods in the initial signal data to obtain at least one initial signal period, and determining the initial signal period with the shortest period from the at least one initial signal period to obtain a target signal period.
Specifically, the initial signal period is a signal sampling period of each CAN signal, after obtaining a plurality of initial signal data, the initial signal period of each initial signal data needs to be obtained, a period with the minimum period is obtained from the plurality of initial signal periods, a target signal period is obtained, and the target signal period is determined as a period of simulation data corresponding to each initial signal data.
For example, the signal period of the a-initial signal data may be 1s, that is, one signal value is obtained every 1s, the signal period of the B-initial signal data may be 0.1s, the signal period of the c-initial signal data may be 0.5s, and the signal period of the d-initial signal data may be 0.08s, then the target signal period is the shortest period of the 4 signal periods, that is, the target signal period may be 0.08s.
In order to facilitate calculation, the simulation data of a plurality of signals may be unified, and after the shortest period is obtained, the period may be shortened again, so as to obtain the target signal period, for example, when the shortest period is 0.1s, 0.01s may be used as the target signal period, so as to facilitate calculation and simulation.
Step S106, determining a plurality of simulation sampling moments through the target signal period, and generating a plurality of simulation signal values of each initial signal data according to the simulation sampling moments, the signal values of each initial signal data and the signal sampling moments.
For example, the simulation sampling time may be 1s, a simulation sampling point is set in each second of the simulation data, and the simulation signal value of each simulation sampling point is determined according to the signal value and the signal sampling time of the initial signal data, for example, the signal sampling time of the initial signal data a is 2s, 4s, and 6s, and the signal values are 1, 2, and 3, respectively, and the simulation signal values corresponding to 2s, 4s, and 6s in the simulation data may be 1, 2, 3,1s, 3s, and 5s may be average values of adjacent signal values, that is, 0.5, 1.5, and 2.5, so as to obtain the simulation data corresponding to the initial signal data a.
Step S108, respectively establishing association relations between a plurality of simulation sampling moments and a plurality of simulation signal values of each initial signal data to obtain a plurality of groups of target simulation data, and determining the plurality of groups of target simulation data as simulation data corresponding to faults.
Specifically, the simulation signal values are in one-to-one correspondence with the simulation sampling moments, so that a set of target simulation data can be obtained, and the vehicle abnormality is reproduced according to the plurality of target simulation data, so that the abnormality cause is obtained.
For example, multiple sets of target simulation data may be represented by a set of target simulation data, where the set of target simulation data may be: Wherein t h.k is a set of simulation sampling moments of the 1 st to h th simulation signal sampling points of the kth initial signal data, and V h.k is a set of simulation signal values of the 1 st to h th simulation signal sampling points of the kth initial signal data.
According to the data processing method provided by the embodiment of the application, at least one initial signal data when a vehicle fails is obtained, wherein each initial signal data at least comprises an initial signal period, a plurality of signal values and a signal sampling time of each signal value; acquiring initial signal periods in each initial signal data, obtaining at least one initial signal period, determining the initial signal period with the shortest period from the at least one initial signal period, and obtaining a target signal period; determining a plurality of simulation sampling moments through a target signal period, and generating a plurality of simulation signal values of each initial signal data according to the simulation sampling moments, the signal values of each initial signal data and the signal sampling moments; and respectively establishing association relations between a plurality of simulation sampling moments and a plurality of simulation signal values of each initial signal data to obtain a plurality of groups of target simulation data, and determining the plurality of groups of target simulation data as simulation data corresponding to faults. The method solves the problems that the method for manually processing the signal data in the related art has long time and low accuracy, and the failure cause cannot be accurately determined. The target signal period is determined from a plurality of initial signal data, the period and the simulation sampling time of the simulation data are determined according to the target signal period, and the simulation signal value of each simulation sampling time in the simulation data is determined according to the signal value and the signal sampling time in each initial signal data, so that the simulation data are automatically generated through the initial signal data, and the effect of rapidly and accurately generating the simulation data corresponding to the faults of the vehicle is achieved.
In order to obtain a suitable target signal period and simulation duration, optionally, in the data processing method provided by the embodiment of the present application, determining a plurality of simulation sampling moments through the target signal period includes: acquiring the minimum signal sampling time and the maximum signal sampling time in the signal sampling time of all the initial signal data, and determining the difference value between the maximum signal sampling time and the initial information sampling time as simulation time length; dividing the target signal period by a preset proportion to reduce the target signal period to obtain a simulation signal period; and generating a plurality of simulation sampling points of each initial signal data according to the simulation signal period in the simulation time length, and simulating sampling time of each simulation sampling point.
Specifically, when determining a plurality of simulation sampling moments through the target signal period, it is necessary to determine the setting amount of the simulation sampling moments, that is, the simulation duration, for example, when the target signal period is 1s, it is expected that 10 simulation sampling moments are set, and then the simulation duration may be set to 10s.
It should be noted that, since the objective of the present technical solution is to generate the target simulation data of each initial signal data and use a plurality of target simulation data to perform abnormal reproduction, in order to unify the target simulation data, it is necessary to obtain the maximum value of signal sampling moments in the plurality of initial signal data and determine the maximum value as a simulation duration, so as to ensure that all signal values in each initial signal data can be added to the simulation data, thereby ensuring the integrity of the data.
Further, when determining the target signal period of the target simulation data, in order to facilitate calculation, the simulation data of the plurality of signals may be unified at the same time, and after the shortest period is obtained, the period may be shortened again, so as to obtain the simulation signal period, for example, in the case that the shortest period is 0.1s, 0.01s may be used as the simulation signal period, so as to facilitate calculation and simulation.
After the simulation signal period and the simulation time length are obtained, a plurality of simulation sampling points of each initial signal data and simulation sampling time of each simulation sampling point can be generated in the simulation time length according to the simulation signal period.
For example, the simulation signal period may be 0.05, the simulation duration may be 0.5s, and the simulation sampling time is: 0.05, 0.1, 0.15, 0.2, 0.25, 0.3, 0.35, 0.4, 0.45, 0.5, thereby obtaining corresponding sampling points and sampling moments.
In order to accurately assign values to the simulated signal values in the simulated data, so that the simulated signal values are consistent with the corresponding initial signal data, optionally, in the data processing method provided by the embodiment of the application, generating the plurality of simulated signal values of each initial signal data according to the plurality of simulated sampling moments, the signal value of each initial signal data and the signal sampling moment includes: respectively acquiring simulation sampling moments with shortest interval with each signal sampling moment in target initial signal data from a plurality of simulation sampling moments to obtain a plurality of first simulation sampling moments, wherein the target initial signal data is any initial signal data; setting the simulation signal value of each simulation sampling point at the first simulation sampling moment as the signal value of the corresponding signal sampling moment, and setting the simulation signal values of the rest simulation sampling points to zero to obtain a plurality of first simulation signal values, wherein the rest simulation sampling points are simulation sampling points except the simulation sampling points at the first simulation sampling moment in the plurality of simulation sampling points; the first simulation signal value of each simulation sampling point is adjusted according to the sequence from small to large at the simulation sampling moment, so that a plurality of second simulation signal values are obtained; a plurality of second simulated signal values are determined as simulated signal values of the target initial signal data.
Specifically, any one initial signal data is firstly obtained, each signal sampling time in the initial signal data is determined, and the nearest simulation sampling time of each signal sampling time is determined in a plurality of simulation sampling times in the simulation data, so as to obtain a plurality of groups of simulation sampling time-signal sampling time.
For example, the a initial signal data includes 5 signal sampling moments, which are respectively: 0.1s, 0.2s, 0.3s, 0.4s and 0.5s, and the target simulation period may be 0.04s, then under the condition that the target simulation period is 0.04s, the simulation sampling time is: 0.06s, 0.12s, 0.18s, 0.24s, 0.30s, 0.36s, 0.42s, 0.48s, 0.54s, etc., where among the simulated sampling instants, the simulated sampling instant closest to each signal sampling instant is determined, that is: 0.12s, 0.18s, 0.30s, 0.42s, 0.48s.
After obtaining multiple groups of simulation sampling time-signal sampling time, according to the association relationship in the groups, the signal value of the signal sampling time can be determined as the simulation signal value of the corresponding simulation sampling time, and the simulation signal values corresponding to the rest simulation sampling time are set as 0, so that multiple first simulation signal values in the simulation data are obtained.
For example, 5 signal sampling instants included in the a-original signal data: the signal values corresponding to 0.1s, 0.2s, 0.3s, 0.4s and 0.5s are 1, 2, 3, 4 and 5 respectively, and the simulation signal values corresponding to the simulation sampling moments 0.12s, 0.18s, 0.30s, 0.42s and 0.48s are 1, 2, 3, 4 and 5 respectively according to the corresponding relation, and the simulation signal values corresponding to the rest simulation sampling moments 0.06s, 0.24s, 0.36s and 0.48s are 0 respectively, so that a plurality of first simulation signal values of the simulation data are obtained.
Further, after the first simulation signal values are obtained, the first simulation signal values of each simulation sampling point need to be adjusted according to the sequence from small to large at the simulation sampling time to obtain a plurality of second simulation signal values, and the plurality of second simulation signal values are determined to be the simulation signal values of the target initial signal data.
For example, the adjustment method may be to determine an average value of a previous non-0 simulation signal value and a next non-0 simulation signal value of a simulation sampling time at which the simulation signal value is 0 as the simulation signal value of the simulation sampling time, for example, the simulation signal value of 0.18s is 2, the simulation signal value of 0.30s is 3, and the simulation signal value of 0.24s may be 2.5. According to the above rule, the simulated signal value of the target initial signal data is determined from the first simulated signal value: 0.1, 2,0, 3, 0, 4, 5, 0 are changed to: 0.5, 1,2, 2.5, 3, 3.5, 4, 5, 2.5.
In order to obtain a more accurate second simulation signal, optionally, in the data processing method provided by the embodiment of the present application, adjusting the first simulation signal value of each simulation sampling point according to the order from small to large at the simulation sampling time, to obtain a plurality of second simulation signal values includes: starting from the simulation sampling point with the minimum simulation sampling moment, judging whether the first simulation signal value of each simulation sampling point is larger than a second preset value or not in sequence; under the condition that the first simulation signal value of the current simulation sampling point is not a second preset value, skipping the current simulation sampling point, and judging whether the first simulation signal value of the next simulation sampling point is the second preset value or not; and under the condition that the first simulation signal value of the current simulation sampling point is a second preset value, determining the first simulation signal value of the previous simulation sampling point of the current simulation sampling point as the first simulation signal value of the current simulation sampling point until all simulation sampling points are traversed, and obtaining a plurality of second simulation signal values.
Specifically, the second preset value may be 0, and from a plurality of first simulation signal values, sequentially traversing each first simulation signal value according to the sequence from the small simulation sampling time to the large simulation sampling time, and judging whether each first simulation signal value is greater than 0, and taking the previous first simulation signal value of the current first simulation signal value as the value of the current first simulation signal value if not greater than 0, that is, equal to 0; and under the condition that the value is larger than 0, skipping the current first simulation signal value, and judging the next first simulation signal value until all the first simulation signal values are traversed.
For example, the plurality of first simulated signal values may be: the first simulation signal value of 0.1s is 4, the first simulation signal value of 0.2s is 5, the first simulation signal value of 0.3s is 0, the first simulation signal value of 0.4s is 0, the first simulation signal value of 0.5s is 6, after the sequential traversal, the first simulation signal value of 0.1s is still 4, the first simulation signal value of 0.2s is still 5, the first simulation signal value of 0.2s is given to 0.3s due to the fact that the first simulation signal value of 0.3s is 0, so that the first simulation signal value of 0.3s is changed to 5, the first simulation signal value of 0.3s is given to 0.4s due to the fact that the first simulation signal value of 0.3s is already changed to 5, the first simulation signal value of 0.4s is also changed to 5, the first simulation signal value of 0.5s is still 6, and a plurality of second simulation signal values are obtained: the first simulation signal value of 0.1s is 4, the first simulation signal value of 0.2s is 5, the first simulation signal value of 0.3s is 5, the first simulation signal value of 0.4s is 5, and the first simulation signal value of 0.5s is 6.
Optionally, in the data processing method provided in the embodiment of the present application, before determining a plurality of simulation sampling moments through a target signal period, and generating a plurality of simulation signal values of each initial signal data according to the plurality of simulation sampling moments, the signal value of each initial signal data, and the signal sampling moment, the method further includes: judging whether each initial signal data carries a frame loss mark or not; under the condition that the initial signal data carries a frame loss identification, determining a signal sampling moment corresponding to the frame loss identification; and determining a signal value of the signal sampling moment corresponding to the frame loss identification as a preset value.
It should be noted that, before generating the plurality of simulation signal values of each initial signal data according to the plurality of simulation sampling moments, the signal value of each initial signal data and the signal sampling moment, the signal value in the initial signal data may be adjusted, so that the simulation data is more accurate.
Specifically, the initial signal data may further include an identifier, for example, a frame loss identifier, before generating, by using the signal value and the signal sampling time of each initial signal data, a plurality of simulation signal values of each initial signal data, whether a frame loss identifier exists in the initial signal data may be determined, and in the case that a frame loss identifier exists, it is necessary to determine the signal sampling time corresponding to the frame loss identifier, and modify the signal value of the signal sampling time to a preset value, where the preset value may be an invalid value, that is, when the simulation data is used, a frame loss phenomenon occurs at the sampling time may be determined by the invalid value.
Optionally, in the data processing method provided by the embodiment of the present application, before determining whether each initial signal data carries a frame loss identifier, the method further includes: respectively determining time differences between adjacent sampling moments in each initial signal data to obtain a plurality of groups of time differences; calculating the frame loss rate in each initial signal data according to the following formula to obtain a plurality of frame loss rates:
Wherein epsilon i.j is the frame loss rate of the ith-1 time difference value of the jth signal, p j is the initial signal period of the jth signal, and Deltat i.j is the time difference value between the ith signal sampling time and the ith-1 signal sampling time of the jth signal; judging whether the frame loss rates are larger than a preset frame loss threshold or not; under the condition that the frame loss rate larger than the preset frame loss threshold exists in the plurality of frame loss rates, acquiring the frame loss rate larger than the preset frame loss threshold to obtain a target frame loss rate, and adding a frame loss identification in initial signal data corresponding to the target frame loss rate.
Specifically, before judging whether each initial signal data carries a frame loss identifier, the frame loss identifier needs to be added to the initial signal data. The determination of the frame loss rate of each initial signal can be made by equation 1. For any initial signal data, calculating the difference value between each group of adjacent signal sampling moments through N signal sampling moments in the initial signal data to obtain N-1 difference values, namely Deltat i.j, calculating N-1 frame loss rates of the initial signal data according to the initial signal period of the initial signal data, and determining whether the frame loss rate is larger than a preset frame loss threshold value.
Under the condition that the frame loss rate larger than the preset frame loss threshold exists in the plurality of frame loss rates, acquiring the frame loss rate larger than the preset frame loss threshold, obtaining a target frame loss rate, determining a signal sampling time corresponding to the target frame loss rate, and determining the signal sampling time as a signal sampling time corresponding to a frame loss identification in the initial signal data.
Optionally, after association relations between a plurality of simulation sampling moments and a plurality of simulation signal values of each initial signal data are respectively established, a plurality of groups of target simulation data are obtained, and the plurality of groups of target simulation data are determined to be simulation data corresponding to faults, the method further includes: judging whether initial signal data corresponding to each group of target simulation data carries a first type identifier, wherein the first type identifier represents a discrete signal; under the condition that the initial signal data corresponding to any group of target simulation data carries a first type identifier, calculating the difference value between the signal values of each group of adjacent sampling moments in the initial signal data corresponding to the target simulation data to obtain a plurality of difference values; judging whether an abnormal difference value exists in the difference values, determining adjacent sampling time groups corresponding to the abnormal difference values under the condition that the abnormal difference value exists, and determining larger signal sampling time in the adjacent sampling time groups as a first sampling time; determining the last sampling time of the first sampling time in the initial signal data corresponding to the target simulation data to obtain a second sampling time, and determining the next sampling time of the first sampling time in the initial signal data corresponding to the target simulation data to obtain a third sampling time; and determining a signal value of the second sampling moment to obtain a first signal value, and changing simulation signal values corresponding to a plurality of simulation sampling moments between the first simulation sampling moment corresponding to the first sampling moment and the first simulation sampling moment corresponding to the third sampling moment into the first signal value in the target simulation data, so as to obtain changed target simulation data.
Specifically, the initial signal data may also carry a first type identifier, and the initial signal data is represented as a state signal, that is, a discrete signal, where a difference value between signal values corresponding to N signal sampling moments in the initial signal data is calculated to obtain N-1 signal value difference values, and whether an abnormal difference value exists in the N-1 signal value difference values is determined, where the abnormal difference value may be a non-0 difference value, and if the abnormal difference value exists, the adjacent signal sampling moment corresponding to the set of adjacent signal values needs to be obtained, and a larger signal sampling moment is obtained, the signal sampling moment is determined to be a first sampling moment, and a smaller signal sampling moment is determined to be a second sampling moment, and a signal value corresponding to the second sampling moment is obtained, so that a first signal value is obtained, and a plurality of simulation signal values corresponding to simulation sampling moments between the first simulation sampling moment corresponding to the first sampling moment and the third simulation sampling moment in the target simulation data are changed to complete updating of the target simulation data.
For example, when there is a non-0 difference in the a initial sample data, the sampling times corresponding to the non-zero difference are 0.5s and 0.6s, the signal value of 0.5s is 1, the signal value of 0.6s is 10, the first sampling time is 0.6s, the second sampling time is 0.5s, and the third sampling time is 0.7s, at this time, it is necessary to determine the first simulation sampling time corresponding to 0.6s, for example, 0.58s, and the first simulation sampling time corresponding to 0.7s, for example, 0.72s in the target simulation data, at this time, the simulation signal values corresponding to all simulation sampling times between 0.58s and 0.72s may be changed from 10 to 1, thereby completing the update of the target simulation data.
Optionally, after association relations between a plurality of simulation sampling moments and a plurality of simulation signal values of each initial signal data are respectively established, a plurality of groups of target simulation data are obtained, and the plurality of groups of target simulation data are determined to be simulation data corresponding to faults, the method further includes: judging whether initial signal data corresponding to each group of target simulation data carries a second type identifier, wherein the second type identifier characterizes continuous signals; under the condition that the initial signal data corresponding to any group of target simulation data carries a second type identifier, determining the deviation rate between the signal values of each group of adjacent sampling moments in the initial signal data corresponding to the target simulation data to obtain a plurality of deviation rates; judging whether an abnormal deviation rate exists in the deviation rate, calculating an adjacent sampling time group corresponding to the abnormal deviation rate under the condition that the abnormal deviation rate exists, and determining a larger signal sampling time in the adjacent sampling time group as a fourth sampling time; determining the last sampling time of the fourth sampling time in the initial signal data corresponding to the target simulation data to obtain a fifth sampling time, and determining the next sampling time of the fourth sampling time in the initial signal data corresponding to the target simulation data to obtain a sixth sampling time; and determining a signal value of the fifth sampling moment to obtain a second signal value, and changing simulation signal values corresponding to a plurality of simulation sampling moments between the first simulation sampling moment corresponding to the fourth sampling moment and the first simulation sampling moment corresponding to the sixth sampling moment into the second signal value in the target simulation data, so as to obtain changed target simulation data.
Specifically, the initial signal data may also carry a second type identifier, and the initial signal data is represented as a physical signal, that is, a continuous signal, where the signal value deviation rate between the signal values corresponding to each set of adjacent signal sampling moments is calculated through the signal values corresponding to N signal sampling moments in the initial signal data, so as to obtain N-1 signal value deviation rates, and determine whether an abnormal deviation rate exists in N-1 signal value difference values, where the abnormal deviation rate may be a signal deviation rate greater than a certain preset deviation rate, if the abnormal deviation rate exists, then adjacent signal sampling moments corresponding to the set of adjacent signal values need to be obtained, and a larger signal sampling moment needs to be obtained, and the signal sampling moment needs to be determined as a fourth sampling moment, and a smaller signal sampling moment needs to be determined as a fifth sampling moment, and a signal value corresponding to the fifth sampling moment is obtained, so as to obtain a second signal value, and update the second simulation value corresponding to the second simulation sampling moment corresponding to the fourth sampling moment and the sixth moment in the target simulation data, thereby completing the updating of the simulation data.
For example, when there is an abnormal deviation value in the B initial sample data, the sampling time corresponding to the abnormal deviation value is 0.7s and 0.8s, the signal value of 0.7s is 5, the signal value of 0.8s is 14, the fourth sampling time is 0.8s, the fifth sampling time is 0.7s, and the sixth sampling time is 0.9s, at this time, it is necessary to determine the first simulation sampling time corresponding to 0.8s, for example, 0.81s, and the first simulation sampling time corresponding to 0.9s, for example, 0.91s in the target simulation data, at this time, the simulation signal values corresponding to all simulation sampling times between 0.81s and 0.91s may be changed from 14 to 5, thereby completing the update of the target simulation data.
It should be noted that, the signal deviation rate may be calculated by the following formula 2, and the formula 2 is as follows:
wherein δ i.j is the signal deviation rate, V i.j is the signal value of the ith signal sampling time of the jth initial signal data, and V i-1.j is the signal value of the ith-1 signal sampling time of the jth initial signal data.
It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer executable instructions, and that although a logical order is illustrated in the flowcharts, in some cases the steps illustrated or described may be performed in an order other than that illustrated herein.
The embodiment of the application also provides a data processing device, and the data processing device of the embodiment of the application can be used for executing the data processing method provided by the embodiment of the application. The following describes a data processing apparatus provided in an embodiment of the present application.
Fig. 2 is a schematic diagram of a data processing apparatus according to an embodiment of the present application. As shown in fig. 2, the apparatus includes: a first acquisition unit 21, a second acquisition unit 22, a generation unit 23, a first determination unit 24.
Specifically, the first acquiring unit 21 is configured to acquire at least one initial signal data when the vehicle fails, where each initial signal data includes at least an initial signal period, a plurality of signal values, and a signal sampling time of each signal value.
The second obtaining unit 22 is configured to obtain an initial signal period in each initial signal data, obtain at least one initial signal period, and determine an initial signal period with a shortest period from the at least one initial signal period, so as to obtain a target signal period.
The generating unit 23 is configured to determine a plurality of simulation sampling moments according to the target signal period, and generate a plurality of simulation signal values of each initial signal data according to the plurality of simulation sampling moments, the signal value of each initial signal data, and the signal sampling moment, respectively.
The first determining unit 24 is configured to establish association relationships between a plurality of simulation sampling moments and a plurality of simulation signal values of each initial signal data, respectively, to obtain a plurality of sets of target simulation data, and determine the plurality of sets of target simulation data as simulation data corresponding to a fault.
The data processing device provided in the embodiment of the present application is configured to obtain, by using the first obtaining unit 21, at least one initial signal data when a vehicle fails, where each initial signal data at least includes an initial signal period, a plurality of signal values, and a signal sampling time of each signal value. The second obtaining unit 22 is configured to obtain an initial signal period in each initial signal data, obtain at least one initial signal period, and determine an initial signal period with a shortest period from the at least one initial signal period, so as to obtain a target signal period. The generating unit 23 is configured to determine a plurality of simulation sampling moments according to the target signal period, and generate a plurality of simulation signal values of each initial signal data according to the plurality of simulation sampling moments, the signal value of each initial signal data, and the signal sampling moment, respectively. The first determining unit 24 is configured to establish association relationships between a plurality of simulation sampling moments and a plurality of simulation signal values of each initial signal data, respectively, to obtain a plurality of sets of target simulation data, and determine the plurality of sets of target simulation data as simulation data corresponding to a fault. The method solves the problems that the method for manually processing the signal data in the related art has long time and low accuracy, and the failure cause cannot be accurately determined. The target signal period is determined from a plurality of initial signal data, the period and the simulation sampling time of the simulation data are determined according to the target signal period, and the simulation signal value of each simulation sampling time in the simulation data is determined according to the signal value and the signal sampling time in each initial signal data, so that the simulation data are automatically generated through the initial signal data, and the effect of rapidly and accurately generating the simulation data corresponding to the faults of the vehicle is achieved.
Optionally, in the data processing apparatus provided in the embodiment of the present application, the generating unit 23 includes: the first acquisition module is used for acquiring the minimum signal sampling time and the maximum signal sampling time in the signal sampling time of all the initial signal data, and determining the difference value between the maximum signal sampling time and the initial information sampling time as simulation duration; the reduction module is used for dividing the target signal period by a preset proportion to reduce the target signal period to obtain a simulation signal period; the generation module is used for generating a plurality of simulation sampling points of each initial signal data according to the simulation signal period and simulation sampling time of each simulation sampling point in the simulation time length.
Optionally, in the data processing apparatus provided in the embodiment of the present application, the generating unit 23 includes: the second acquisition module is used for respectively acquiring simulation sampling moments with the shortest interval with each signal sampling moment in the target initial signal data from a plurality of simulation sampling moments to obtain a plurality of first simulation sampling moments, wherein the target initial signal data is any initial signal data; the setting module is used for setting the simulation signal value of each simulation sampling point at the first simulation sampling moment to be the signal value of the corresponding signal sampling moment, and setting the simulation signal values of the rest simulation sampling points to be zero to obtain a plurality of first simulation signal values, wherein the rest simulation sampling points are simulation sampling points except the simulation sampling points at the first simulation sampling moment in the plurality of simulation sampling points; the adjusting module is used for adjusting the first simulation signal value of each simulation sampling point from small to large according to the simulation sampling time to obtain a plurality of second simulation signal values; and the determining module is used for determining a plurality of second simulation signal values as simulation signal values of the target initial signal data.
Optionally, in the data processing apparatus provided in the embodiment of the present application, the first adjustment module includes: the first judging sub-module is used for sequentially judging whether the first simulation signal value of each simulation sampling point is larger than a second preset value from the simulation sampling point with the minimum simulation sampling moment; the second judging sub-module is used for skipping the current simulation sampling point and judging whether the first simulation signal value of the next simulation sampling point is a second preset value or not under the condition that the first simulation signal value of the current simulation sampling point is not the second preset value; the determining submodule is used for determining the first simulation signal value of the previous simulation sampling point of the current simulation sampling point as the first simulation signal value of the current simulation sampling point under the condition that the first simulation signal value of the current simulation sampling point is a second preset value until all the simulation sampling points are traversed, and a plurality of second simulation signal values are obtained.
Optionally, in the data processing apparatus provided in the embodiment of the present application, the apparatus further includes: the first judging unit is used for judging whether each initial signal data carries a frame loss mark or not; the second determining unit is used for determining the signal sampling time corresponding to the frame loss identification under the condition that the initial signal data carries the frame loss identification; and the third determining unit is used for determining the signal value of the signal sampling moment corresponding to the frame loss identification as a preset value.
Optionally, in the data processing apparatus provided in the embodiment of the present application, the apparatus further includes: a fourth determining unit, configured to determine time differences between adjacent sampling moments in each initial signal data, respectively, to obtain multiple sets of time differences; the first calculating unit is used for calculating the frame loss rate in each initial signal data according to the following formula to obtain a plurality of frame loss rates:
Wherein epsilon i.j is the frame loss rate of the ith-1 time difference value of the jth signal, p j is the initial signal period of the jth signal, and Deltat i.j is the time difference value between the ith signal sampling time and the ith-1 signal sampling time of the jth signal; the second judging unit is used for judging whether the frame loss rates are larger than a preset frame loss threshold value or not; the third obtaining unit is configured to obtain a frame loss rate greater than a preset frame loss threshold value when the frame loss rates are greater than the preset frame loss threshold value, obtain a target frame loss rate, and add a frame loss identifier to initial signal data corresponding to the target frame loss rate.
Optionally, in the data processing apparatus provided in the embodiment of the present application, the apparatus further includes: the third judging unit is used for judging whether initial signal data corresponding to each group of target simulation data carries a first type identifier, wherein the first type identifier represents a discrete signal; the second calculation unit is used for calculating the difference value between the signal values of each group of adjacent sampling moments in the initial signal data corresponding to the target simulation data under the condition that the initial signal data corresponding to any group of target simulation data carries the first type identifier, so as to obtain a plurality of difference values; a fourth judging unit, configured to judge whether an abnormal difference exists in the differences, and determine an adjacent sampling time group corresponding to the abnormal difference and determine a larger signal sampling time in the adjacent sampling time group as a first sampling time when the abnormal difference exists; a fifth determining unit, configured to determine a last sampling time of the first sampling time in the initial signal data corresponding to the target simulation data, obtain a second sampling time, and determine a next sampling time of the first sampling time in the initial signal data corresponding to the target simulation data, obtain a third sampling time; the first changing unit is used for determining the signal value of the second sampling time to obtain a first signal value, and changing the simulation signal values corresponding to a plurality of simulation sampling times between the first simulation sampling time corresponding to the first sampling time and the first simulation sampling time corresponding to the third sampling time into the first signal value in the target simulation data, so that the changed target simulation data is obtained.
Optionally, in the data processing apparatus provided in the embodiment of the present application, the apparatus further includes: a fifth judging unit, configured to judge whether initial signal data corresponding to each group of target simulation data carries a second type identifier, where the second type identifier represents a continuous signal; a sixth determining unit, configured to determine, when the initial signal data corresponding to any one set of target simulation data carries the second type identifier, a deviation ratio between signal values of each set of adjacent sampling moments in the initial signal data corresponding to the target simulation data, so as to obtain a plurality of deviation ratios; a sixth judging unit, configured to judge whether an abnormal deviation rate exists in the deviation rates, and calculate an adjacent sampling time group corresponding to the abnormal deviation rate when the abnormal deviation rate exists, and determine a larger signal sampling time in the adjacent sampling time group as a fourth sampling time; a seventh determining unit, configured to determine a last sampling time of the fourth sampling time in the initial signal data corresponding to the target simulation data, to obtain a fifth sampling time, and determine a next sampling time of the fourth sampling time in the initial signal data corresponding to the target simulation data, to obtain a sixth sampling time; the second changing unit is configured to determine a signal value at a fifth sampling time to obtain a second signal value, and change, in the target simulation data, simulation signal values corresponding to a plurality of simulation sampling times between a first simulation sampling time corresponding to a fourth sampling time and a first simulation sampling time corresponding to a sixth sampling time to the second signal value, thereby obtaining changed target simulation data.
The data processing apparatus includes a processor and a memory, and the first acquiring unit 21, the second acquiring unit 22, the generating unit 23, the first determining unit 24, and the like are stored in the memory as program units, and the processor executes the program units stored in the memory to realize the corresponding functions.
The processor includes a kernel, and the kernel fetches the corresponding program unit from the memory. The kernel can be provided with one or more than one kernel, and the problem that the failure cause cannot be accurately determined due to the fact that the time required by a method for manually processing signal data is long and the accuracy is low in the related art is solved by adjusting kernel parameters.
The memory may include volatile memory, random Access Memory (RAM), and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM), among other forms in computer readable media, the memory including at least one memory chip.
An embodiment of the present invention provides a computer-readable storage medium having stored thereon a program which, when executed by a processor, implements the data processing method.
The embodiment of the invention provides a processor which is used for running a program, wherein the data processing method is executed when the program runs.
The embodiment of the invention provides an electronic device, which comprises a processor, a memory and a program stored on the memory and capable of running on the processor, wherein the following steps are realized when the processor executes the program: acquiring at least one initial signal data when a vehicle fails, wherein each initial signal data at least comprises an initial signal period, a plurality of signal values and a signal sampling time of each signal value; acquiring initial signal periods in each initial signal data, obtaining at least one initial signal period, determining the initial signal period with the shortest period from the at least one initial signal period, and obtaining a target signal period; determining a plurality of simulation sampling moments through a target signal period, and generating a plurality of simulation signal values of each initial signal data according to the simulation sampling moments, the signal values of each initial signal data and the signal sampling moments; and respectively establishing association relations between a plurality of simulation sampling moments and a plurality of simulation signal values of each initial signal data to obtain a plurality of groups of target simulation data, and determining the plurality of groups of target simulation data as simulation data corresponding to faults. The device herein may be a server, PC, PAD, cell phone, etc.
The application also provides a computer program product adapted to perform, when executed on a data processing device, a program initialized with the method steps of: acquiring at least one initial signal data when a vehicle fails, wherein each initial signal data at least comprises an initial signal period, a plurality of signal values and a signal sampling time of each signal value; acquiring initial signal periods in each initial signal data, obtaining at least one initial signal period, determining the initial signal period with the shortest period from the at least one initial signal period, and obtaining a target signal period; determining a plurality of simulation sampling moments through a target signal period, and generating a plurality of simulation signal values of each initial signal data according to the simulation sampling moments, the signal values of each initial signal data and the signal sampling moments; and respectively establishing association relations between a plurality of simulation sampling moments and a plurality of simulation signal values of each initial signal data to obtain a plurality of groups of target simulation data, and determining the plurality of groups of target simulation data as simulation data corresponding to faults.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, etc., such as Read Only Memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.
Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises an element.
The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and variations of the present application will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. which come within the spirit and principles of the application are to be included in the scope of the claims of the present application.

Claims (7)

1. A method of data processing, comprising:
Acquiring at least one initial signal data when a vehicle fails, wherein each initial signal data at least comprises an initial signal period, a plurality of signal values and a signal sampling time of each signal value;
acquiring initial signal periods in the initial signal data to obtain at least one initial signal period, and determining the initial signal period with the shortest period from the at least one initial signal period to obtain a target signal period;
Determining a plurality of simulation sampling moments through the target signal period, and generating a plurality of simulation signal values of each initial signal data according to the simulation sampling moments, the signal values of each initial signal data and the signal sampling moments respectively;
Respectively establishing association relations between a plurality of simulation sampling moments and a plurality of simulation signal values of each initial signal data to obtain a plurality of groups of target simulation data, and determining the plurality of groups of target simulation data as simulation data corresponding to the faults;
Determining a plurality of simulated sampling instants from the target signal period comprises: acquiring the minimum signal sampling time and the maximum signal sampling time in the signal sampling time of all the initial signal data, and determining the difference value between the maximum signal sampling time and the initial information sampling time as simulation duration; dividing the target signal period by a preset proportion to reduce the target signal period to obtain a simulation signal period; generating a plurality of simulation sampling points of each initial signal data according to the simulation signal period in the simulation time length, and simulating sampling time of each simulation sampling point;
Generating a plurality of simulated signal values for each of the initial signal data according to the plurality of simulated sampling moments, the signal value for each of the initial signal data, and the signal sampling moment, respectively, includes: respectively obtaining simulation sampling moments with shortest signal sampling moment intervals from a plurality of simulation sampling moments, and obtaining a plurality of first simulation sampling moments, wherein the target initial signal data is any one initial signal data; setting the simulation signal value of each simulation sampling point at the first simulation sampling moment as the corresponding signal value at the signal sampling moment, and setting the simulation signal values of the rest simulation sampling points to zero to obtain a plurality of first simulation signal values, wherein the rest simulation sampling points are simulation sampling points except the simulation sampling points at the first simulation sampling moment in the plurality of simulation sampling points; the first simulation signal value of each simulation sampling point is adjusted according to the sequence from small to large at the simulation sampling moment, so that a plurality of second simulation signal values are obtained; determining a plurality of the second simulation signal values as simulation signal values of the target initial signal data;
Adjusting the first simulation signal value of each simulation sampling point according to the sequence from small to large at the simulation sampling moment to obtain a plurality of second simulation signal values, wherein the steps comprise: starting from the simulation sampling point with the minimum simulation sampling moment, judging whether the first simulation signal value of each simulation sampling point is larger than a second preset value or not in sequence; skipping the current simulation sampling point and judging whether the first simulation signal value of the next simulation sampling point is the second preset value under the condition that the first simulation signal value of the current simulation sampling point is larger than the second preset value; and under the condition that the first simulation signal value of the current simulation sampling point is not larger than the second preset value, determining the first simulation signal value of the simulation sampling point before the current simulation sampling point as the first simulation signal value of the current simulation sampling point until all the simulation sampling points are traversed, and obtaining a plurality of second simulation signal values.
2. The method of claim 1, wherein prior to determining a plurality of simulated sampling instants from the target signal period and generating a plurality of simulated signal values for each of the initial signal data based on the plurality of simulated sampling instants, the signal value for each of the initial signal data, and the signal sampling instants, respectively, the method further comprises:
Judging whether each initial signal data carries a frame loss identification;
under the condition that the initial signal data carries the frame loss identification, determining a signal sampling moment corresponding to the frame loss identification;
And determining a signal value of the signal sampling moment corresponding to the frame loss identification as a preset value.
3. The method of claim 2, wherein prior to determining whether each of the initial signal data carries a frame loss indicator, the method further comprises:
Respectively determining time differences between adjacent sampling moments in each initial signal data to obtain a plurality of groups of time differences;
calculating the frame loss rate in each initial signal data according to the following formula to obtain a plurality of frame loss rates:
，
wherein, The frame loss rate for the i-1 time difference of the jth signal, pj is the initial signal period of the jth signal,Is the time difference between the ith signal sampling time and the (i-1) th signal sampling time of the jth signal;
judging whether the frame loss rates are larger than a preset frame loss threshold or not;
Under the condition that the frame loss rate larger than the preset frame loss threshold exists in the plurality of frame loss rates, acquiring the frame loss rate larger than the preset frame loss threshold to obtain a target frame loss rate, and adding the frame loss identification into the initial signal data corresponding to the target frame loss rate.
4. The method according to claim 1, wherein after establishing association relations between the plurality of simulation sampling moments and the plurality of simulation signal values of each of the initial signal data, respectively, to obtain a plurality of sets of target simulation data, and determining the plurality of sets of target simulation data as the simulation data corresponding to the fault, the method further comprises:
judging whether initial signal data corresponding to each group of target simulation data carries a first type identifier, wherein the first type identifier represents a discrete signal;
Under the condition that the initial signal data corresponding to any group of the target simulation data carries the first type identifier, calculating the difference value between the signal values of each group of adjacent sampling moments in the initial signal data corresponding to the target simulation data to obtain a plurality of difference values;
Judging whether an abnormal difference value exists in the difference values, determining an adjacent sampling time group corresponding to the abnormal difference value under the condition that the abnormal difference value exists, and determining the larger signal sampling time in the adjacent sampling time group as a first sampling time;
Determining the last sampling time of the first sampling time in the initial signal data corresponding to the target simulation data to obtain a second sampling time, and determining the next sampling time of the first sampling time in the initial signal data corresponding to the target simulation data to obtain a third sampling time;
Determining a signal value of the second sampling moment to obtain a first signal value, and changing simulation signal values corresponding to a plurality of simulation sampling moments between the first simulation sampling moment corresponding to the first sampling moment and the first simulation sampling moment corresponding to the third sampling moment into the first signal value in the target simulation data, so that the changed target simulation data are obtained.
5. The method according to claim 1, wherein after establishing association relations between the plurality of simulation sampling moments and the plurality of simulation signal values of each of the initial signal data, respectively, to obtain a plurality of sets of target simulation data, and determining the plurality of sets of target simulation data as the simulation data corresponding to the fault, the method further comprises:
Judging whether initial signal data corresponding to each group of target simulation data carries a second type identifier, wherein the second type identifier represents a continuous signal;
Under the condition that the initial signal data corresponding to any group of target simulation data carries the second type identifier, determining the deviation rate between the signal values of each group of adjacent sampling moments in the initial signal data corresponding to the target simulation data to obtain a plurality of deviation rates;
Judging whether an abnormal deviation rate exists in the deviation rate, calculating an adjacent sampling time group corresponding to the abnormal deviation rate under the condition that the abnormal deviation rate exists, and determining the larger signal sampling time in the adjacent sampling time group as a fourth sampling time;
Determining the last sampling time of the fourth sampling time in the initial signal data corresponding to the target simulation data to obtain a fifth sampling time, and determining the next sampling time of the fourth sampling time in the initial signal data corresponding to the target simulation data to obtain a sixth sampling time;
Determining a signal value of the fifth sampling moment to obtain a second signal value, and changing simulation signal values corresponding to a plurality of simulation sampling moments between the first simulation sampling moment corresponding to the fourth sampling moment and the first simulation sampling moment corresponding to the sixth sampling moment into the second signal value in the target simulation data, so as to obtain changed target simulation data.
6. A vehicle characterized in that a controller of the vehicle performs the data processing method of any one of claims 1 to 5.
7. A data processing apparatus, comprising:
the first acquisition unit is used for acquiring at least one initial signal data when the vehicle fails, wherein each initial signal data at least comprises an initial signal period, a plurality of signal values and a signal sampling time of each signal value;
The second acquisition unit is used for acquiring initial signal periods in the initial signal data to obtain at least one initial signal period, and determining the initial signal period with the shortest period from the at least one initial signal period to obtain a target signal period;
the generating unit is used for determining a plurality of simulation sampling moments through the target signal period and generating a plurality of simulation signal values of each initial signal data according to the simulation sampling moments, the signal values of each initial signal data and the signal sampling moments respectively;
the first determining unit is used for respectively establishing association relations between a plurality of simulation sampling moments and a plurality of simulation signal values of each initial signal data to obtain a plurality of groups of target simulation data, and determining the plurality of groups of target simulation data as simulation data corresponding to the faults;
The generation unit includes: the first acquisition module is used for acquiring the minimum signal sampling time and the maximum signal sampling time in the signal sampling time of all the initial signal data, and determining the difference value between the maximum signal sampling time and the initial information sampling time as simulation duration; the reduction module is used for dividing the target signal period by a preset proportion to reduce the target signal period to obtain a simulation signal period; the generation module is used for generating a plurality of simulation sampling points of each initial signal data according to the simulation signal period and simulation sampling time of each simulation sampling point in the simulation time length;
The generation unit includes: the second acquisition module is used for respectively acquiring simulation sampling moments with the shortest interval with each signal sampling moment in the target initial signal data from a plurality of simulation sampling moments to obtain a plurality of first simulation sampling moments, wherein the target initial signal data is any initial signal data; the setting module is used for setting the simulation signal value of each simulation sampling point at the first simulation sampling moment to be the signal value of the corresponding signal sampling moment, and setting the simulation signal values of the rest simulation sampling points to be zero to obtain a plurality of first simulation signal values, wherein the rest simulation sampling points are simulation sampling points except the simulation sampling points at the first simulation sampling moment in the plurality of simulation sampling points; the adjusting module is used for adjusting the first simulation signal value of each simulation sampling point from small to large according to the simulation sampling time to obtain a plurality of second simulation signal values; a determining module for determining a plurality of second simulation signal values as simulation signal values of the target initial signal data;
The adjustment module comprises: the first judging sub-module is used for sequentially judging whether the first simulation signal value of each simulation sampling point is larger than a second preset value from the simulation sampling point with the minimum simulation sampling moment; the second judging sub-module is used for skipping the current simulation sampling point and judging whether the first simulation signal value of the next simulation sampling point is a second preset value or not under the condition that the first simulation signal value of the current simulation sampling point is larger than the second preset value; and the determining submodule is used for determining the first simulation signal value of the previous simulation sampling point of the current simulation sampling point as the first simulation signal value of the current simulation sampling point until all the simulation sampling points are traversed to obtain a plurality of second simulation signal values under the condition that the first simulation signal value of the current simulation sampling point is not larger than the second preset value.
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