CN113408560B - Engine test data classification method, electronic device, and readable storage medium - Google Patents
Engine test data classification method, electronic device, and readable storage medium Download PDFInfo
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Abstract
The invention provides an engine test data classification method, electronic equipment and a readable storage medium, which are characterized in that after engine test data are acquired, the engine test data are resampled according to a set sampling frequency to form a first array, data in the first array are sequenced from small to large to form a second array, the second array is divided into a plurality of test windows, the stability of the data in each test window is further judged in sequence, a plurality of groups of operation interval values are detected in the second array according to the stability of the data in each test window, and a plurality of groups of operation interval values are sequentially output to form a final array, so that accurate operation interval groups can be automatically obtained from data files tested by an engine, a precondition is provided for subsequent automatic analysis, control parameters and the like.
Description
Technical Field
The present invention relates to the field of data processing, and in particular, to an engine test data classification method, an electronic device, and a readable storage medium.
Background
In the development process of a new vehicle model, for the purposes of reducing pollutant emission, reducing oil consumption, improving drivability and the like as much as possible, parameter traversal scanning is generally performed in an allowable working range of an engine to obtain pollutant emission in the working range (taking a combination of rotating speed and air inflow as an example), relevant parameters (log data) of oil consumption are obtained, and optimal control parameters are selected according to targets. Currently, after obtaining the above data, engineers manually record and group the working ranges scanned in this project by importing recorded engine operating condition (log) data into specific software. For example, after the carbon tank flow is tested, the PWM (pulse width modulation) value of the electromagnetic valve control during the test of the project needs to be manually calculated to obtain the working range of the test and the calculation of the subsequent control parameters, however, the manual opening software analysis log is not suitable for the analysis and optimization of the control parameters of big data automation in the manual analysis and summarization mode.
Disclosure of Invention
The invention aims to provide an engine test data classification method, electronic equipment and a readable storage medium, which can automatically obtain accurate running interval grouping from a data file of data test through a software algorithm, so as to solve the problems of insufficient simplicity, low reliability and low efficiency in test analysis of test data in the prior art.
In order to solve the technical problems, the invention provides an engine test data classification method, which comprises the following steps:
acquiring engine test data, and resampling the engine test data according to a set sampling frequency to form a first array;
sorting the data in the first array from small to large to form a second array;
dividing the second array into a plurality of test windows;
and sequentially judging the stability of the data in each test window, detecting a plurality of groups of operation interval values in the second array according to the stability of the data in each test window, and sequentially outputting the plurality of groups of operation interval values to form a final array.
Optionally, in the engine test data classification method, before sequentially judging the stability of the data in each test window, the engine test data classification method includes:
and calculating the maximum value, the minimum value and the average value of the data in each test window, so as to judge the stability of the data corresponding to the test window.
Optionally, in the method for classifying engine test data, the method for detecting multiple sets of operation interval values in the second array according to the stability of data in each test window includes:
sequentially judging whether the maximum value, the minimum value and the average value in each test window meet a set condition;
and if the set condition is met, taking the data in the test window meeting the set condition as a new running interval value.
Optionally, in the engine test data classification method, when the final array is empty, the setting condition includes:
max > Avg Fct1, and Min < Avg Fct2; wherein,
max represents the maximum value within the corresponding test window, min represents the minimum value within the corresponding test window, and Fct1 and Fct2 represent the adjustable scaling factor, respectively.
Optionally, in the engine test data classification method, when the final array is not empty, the setting condition includes:
max > Avg x Fct1, and Min < Avg x Fct2, and Avg > Dout (-1) * Fct3; wherein,
max represents the maximum value in the corresponding test window, min represents the minimum value in the corresponding test window, dout (-1) Representing the last data in the run interval value of the last outputFct1, fct2, and Fct3 represent adjustable scaling factors, respectively.
Optionally, in the method for classifying engine test data, the method for detecting multiple sets of operation interval values in the second array according to the stability of data in each test window further includes:
if the set condition is not met and the final array is not empty, judging whether the length of the remaining data in the second array is larger than the length of the test window, and if so, judging the stability of the data in the next window.
Optionally, in the method for classifying engine test data, after taking the data in the test window satisfying the set condition as a new operation interval value, the method for detecting multiple groups of operation interval values in the second array according to the stability of the data in each test window further includes:
judging whether the length of the data remained in the second array is larger than the length of the test window, if so, judging the stability of the data in the next window.
Optionally, in the method for classifying engine test data, the method for detecting multiple sets of operation interval values in the second array according to the stability of data in each test window further includes:
judging whether the length of the data remained in the second array is larger than the length of the test window, if not, ending the judgment of the stability of the data in the test window.
Based on the same inventive concept, the invention also provides an electronic device comprising a processor and a memory, the memory storing a computer program which, when executed by the processor, implements the method as described above.
Based on the same inventive concept, the present invention also provides a readable storage medium having stored therein a computer program which, when executed by a processor, implements the method as described above.
Compared with the prior art, the technical scheme of the invention has the following beneficial effects:
according to the engine test data classification method, the electronic equipment and the readable storage medium, after the engine test data is acquired, the engine test data is resampled according to the set sampling frequency to form the first array, the data in the first array is sequenced from small to large to form the second array, the second array is divided into a plurality of test windows, the stability of the data in each test window is further judged in sequence, a plurality of groups of operation interval values are detected in the second array according to the stability of the data in each test window, and a plurality of groups of operation interval values are sequentially output to form a final array, so that accurate operation interval groups can be automatically obtained from the data files of the engine test, a precondition is provided for subsequent automatic analysis, control parameters and the like.
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FIG. 1 is a flow chart of a method of classifying engine test data according to an embodiment of the present invention;
FIG. 2 is a process schematic diagram of the steps of an engine test data classification method according to an embodiment of the present invention.
Detailed Description
The engine test data classification method, the electronic device and the readable storage medium according to the present invention are described in further detail below with reference to the accompanying drawings and specific embodiments. Advantages and features of the invention will become more apparent from the following description and from the claims. It should be noted that the drawings are in a very simplified form and are all to a non-precise scale, merely for convenience and clarity in aiding in the description of embodiments of the invention. Furthermore, the structures shown in the drawings are often part of actual structures. In particular, the drawings are shown with different emphasis instead being placed upon illustrating the various embodiments.
Referring to fig. 1, an embodiment of the present invention provides an engine test data classification method, which includes the following steps:
s1, acquiring engine test data, and resampling the engine test data according to a set sampling frequency to form a first array;
s2, sorting the data in the first array from small to large to form a second array;
s3, dividing the second number group into a plurality of test windows;
and S4, sequentially judging the stability of the data in each test window, detecting a plurality of groups of operation interval values in the second array according to the stability of the data in each test window, and sequentially outputting the plurality of groups of operation interval values to form a final array (Dout array).
In general, performance parameters of an automobile under various working conditions are tested correspondingly in an automobile development stage, and the types of the tests are, for example, a knock test, an exhaust temperature test, a high-temperature road test, a plateau road test and a alpine road test, an electromagnetic interference and electromagnetic compatibility test, a steady-state dynamometer test, a closed-loop fuel control test, a transient fuel control test, an idle speed control test, a start control test, a fuel injection control test, an air conditioner control test, a hundred kilometer acceleration test, a start stop test and the like, and each test corresponds to the corresponding working condition of the automobile, for example, the idle speed control test is a performance test of the automobile running under the idle speed working condition. In each test process, engine test data such as engine speed, engine water temperature, oil temperature, air inlet temperature, speed, accelerator opening (i.e. throttle opening), acceleration, engine load, vibration frequency, engine running time and the like are respectively acquired through corresponding signal acquisition devices such as an engine speed sensor, a cooling liquid temperature sensor, an oil temperature sensor, an air inlet temperature sensor, a gear position switch, a vehicle speed sensor, a throttle position sensor, an accelerator pedal position sensor, an air conditioner switch sensor and the like, and the engine test data can also be called log files.
According to the characteristics of engine calibration and test, aiming at data of steady-state operation test: the switching of the required operation interval has a certain distinction degree (for example, the air inflow is switched from 15kg/h to 25 kg/h), and the steady state operation is performed for a certain time length (for example, 10 seconds), so that in the finally output array, multiple groups of operation interval values should be presented in a step form, in step S4, the multiple groups of operation interval values are detected in the second array according to the stability of the data in each test window, and based on the unfolding, the stability of the data is judged to distinguish the data which should be located in different steps.
Therefore, referring to fig. 2, in step S4, before determining the stability of the data in each test window, step S41 is performed, and the maximum value, the minimum value and the average value of the data in each test window are calculated for determining the stability of the data corresponding to the test window in the next step.
When judging the stability of data in a certain test window, the Dout array has a numerical value, which affects the judgment basis, because the running interval value should have a relatively obvious change when the step (running interval value) is switched, so when the Dout array is not empty, i.e. the step is generated, the value of a new step to be generated should be compared with the last value of the step to be generated, and only when a certain size relation is met, i.e. the new step generation condition is met, the new step can be generated. In view of this, before step S42, the method further includes: judging whether the Dout array is empty or not, and correspondingly, setting the following conditions:
(1) When the Dout array is empty, the setting conditions include:
max > Avg Fct1, and Min < Avg Fct2; wherein,
max represents the maximum value within the corresponding test window, min represents the minimum value within the corresponding test window, and Fct1 and Fct2 represent the adjustable scaling factor, respectively.
(2) When the Dout array is not empty, the setting conditions include:
max > Avg x Fct1, and Min < Avg x Fct2, and Avg＞Dout (-1) * Fct3; wherein,
max represents the maximum value in the corresponding test window, min represents the minimum value in the corresponding test window, dout (-1) And the last data in the running interval value which represents the last output, and Fct1, fct2 and Fct3 respectively represent adjustable scaling factors.
On this basis, the method for detecting multiple groups of operation interval values in the second array according to the stability of the data in each test window specifically includes the following steps:
s42, judging whether the maximum value, the minimum value and the average value in each test window meet a set condition or not in sequence; if the set condition is satisfied, whether the Dout array is empty or not, executing step S43 and step S44 in sequence; when the set condition is not satisfied and the final array is not empty, executing step S44;
s43, taking the data in the current test window as a new running interval value;
s44, judging whether the length of the data remained in the second array is larger than the length of the test window, if so, executing the step S45, otherwise, executing the step S46;
s45, judging the stability of data in a next window;
s46, ending the judgment of the stability of the data in the measurement window.
In step S45, when judging the stability of the data in the next window, the Dout array already inputs a part of the running interval values, so the setting condition (2) should be used as a judgment basis when judging the stability.
After the steps are finished, the method for classifying the engine test data automatically obtains accurate running interval groups from the data files of the engine test, is convenient for providing preconditions for subsequent automatic analysis, control parameters and the like, and is more efficient, rapid and simple in implementation process due to the adoption of a software algorithm mode.
Based on the same inventive concept, an embodiment of the present invention further provides an electronic device, where the electronic device includes a processor and a memory, and the memory stores a computer program, and when the computer program is executed by the processor, the engine test data classification method is implemented.
The processor may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like that is a control center of the electronic device, connecting various parts of the overall electronic device using various interfaces and lines.
The memory may be used to store the computer program, and the processor may implement various functions of the electronic device by running or executing the computer program stored in the memory, and invoking data stored in the memory.
The memory may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
Based on the same inventive concept, an embodiment of the present invention also provides a readable storage medium, on which a computer program is stored, which when executed by a processor, can implement the engine test data classification method according to an embodiment of the present invention.
The readable storage medium may be a tangible device that can hold and store instructions for use by an instruction execution device, such as, but not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the preceding. More specific examples (a non-exhaustive list) of the readable storage medium would include the following: portable computer disks, hard disks, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static Random Access Memory (SRAM), portable compact disk read-only memory (CD-ROM), digital Versatile Disks (DVD), memory sticks, floppy disks, mechanical coding devices, punch cards or in-groove structures such as punch cards or grooves having instructions stored thereon, and any suitable combination of the foregoing. The computer program described herein may be downloaded from a readable storage medium to a respective computing/processing device or to an external computer or external storage device via a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmissions, wireless transmissions, routers, firewalls, switches, gateway computers and/or edge servers. The network interface card or network interface in each computing/processing device receives the computer program from the network and forwards the computer program for storage in a readable storage medium in the respective computing/processing device. Computer programs for carrying out operations of the present invention may be assembly instructions, instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, c++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer program may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, aspects of the present invention are implemented by personalizing electronic circuitry, such as programmable logic circuits, field Programmable Gate Arrays (FPGAs), or Programmable Logic Arrays (PLAs), with state information for a computer program, which can execute computer-readable program instructions.
Aspects of the present invention are described herein with reference to flowchart illustrations and/or block diagrams of methods, systems, and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer programs. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the programs, when executed by the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer programs may also be stored in a readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the readable storage medium storing the computer program includes an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.
The computer program may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the computer program which is executed on the computer, other programmable apparatus or other devices implements the functions/acts specified in the flowchart and/or block diagram block or blocks.
In summary, the engine test data classification method, the electronic device and the readable storage medium can automatically obtain accurate running interval grouping through a software algorithm from the data files of the data test, thereby solving the problems of insufficient simplicity, low reliability and low efficiency in the test analysis of the test data in the prior art.
The above description is only illustrative of the preferred embodiments of the present invention and is not intended to limit the scope of the present invention, and any alterations and modifications made by those skilled in the art based on the above disclosure shall fall within the scope of the appended claims.
Claims (8)
1. An engine test data classification method, characterized in that the engine test data classification method comprises:
acquiring engine test data, and resampling the engine test data according to a set sampling frequency to form a first array;
sorting the data in the first array from small to large to form a second array;
dividing the second array into a plurality of test windows;
calculating the maximum value, the minimum value and the average value of the data in each test window, so as to judge the stability of the data corresponding to the test window;
sequentially judging the stability of the data in each test window, detecting a plurality of groups of operation interval values in the second array according to the stability of the data in each test window, and sequentially outputting the plurality of groups of operation interval values to form a final array;
the method for detecting the multiple groups of operation interval values in the second array according to the stability of the data in each test window comprises the following steps:
sequentially judging whether the maximum value, the minimum value and the average value in each test window meet a set condition;
if the set condition is met, taking the data in the test window meeting the set condition as a new running interval value; when a plurality of groups of operation interval values are obtained, switching of the operation intervals is required to have a certain degree of distinction, and each operation interval is operated in a steady state for a certain time length.
2. The engine test data classification method of claim 1, wherein the setting conditions when the final array is empty include:
max > Avg Fct1, and Min < Avg Fct2; wherein,
max represents the maximum value within the corresponding test window, min represents the minimum value within the corresponding test window, and Fct1 and Fct2 represent the adjustable scaling factor, respectively.
3. The engine test data classification method of claim 1, wherein the setting conditions include, when the final array is not empty:
max > Avg x Fct1, and Min < Avg x Fct2, and Avg > Dout （-1） * Fct3; wherein,
max represents the maximum value in the corresponding test window, min represents the minimum value in the corresponding test window, dout （-1） And the last data in the running interval value which represents the last output, and Fct1, fct2 and Fct3 respectively represent adjustable scaling factors.
4. The engine test data classification method of claim 1, wherein said method of detecting a plurality of sets of operating interval values in said second array based on the stability of data within each of said test windows further comprises:
if the set condition is not met and the final array is not empty, judging whether the length of the remaining data in the second array is larger than the length of the test window, and if so, judging the stability of the data in the next window.
5. The engine test data sorting method according to claim 1, wherein after taking the data in the test window satisfying the set condition as a new operation interval value, the method of detecting a plurality of sets of operation interval values in the second array according to the stability of the data in each of the test windows further comprises:
judging whether the length of the data remained in the second array is larger than the length of the test window, if so, judging the stability of the data in the next window.
6. The engine test data classification method of claim 4 or 5, wherein said method of detecting a plurality of sets of operating interval values in said second array based on the stability of data within each of said test windows further comprises:
judging whether the length of the data remained in the second array is larger than the length of the test window, if not, ending the judgment of the stability of the data in the test window.
7. An electronic device comprising a processor and a memory, the memory having stored thereon a computer program which, when executed by the processor, implements the method of any of claims 1 to 6.
8. A readable storage medium, characterized in that the readable storage medium has stored therein a computer program which, when executed by a processor, implements the method of any one of claims 1 to 6.
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