Method, device and storage medium for evaluating engine quality stability

Abstract

Disclosed are a method and device for evaluating engine quality stability and a storage medium. The method for evaluating engine quality stability includes: for each of a plurality of engines on a production line: receiving information indicating the type and number of the engine; based on the type and number of the engine, obtaining cold test values ​​of the engine related to a plurality of test items, wherein the plurality of test items are determined according to the type of the engine; grouping the cold test values ​​of the plurality of engines at least according to the type of the engine; and for each group of cold test values, for each test item in the plurality of test items, evaluating whether the cold test value is stable, and generating an evaluation result on whether the cold test value is stable.

Description

Technical Field

[0001] The present disclosure relates to a method and apparatus and a storage medium for evaluating engine quality stability. Background Art

[0002] The engine cold test is a method used to test the assembly quality of internal combustion engines. When this technology is used to test the engine, the engine does not need fuel to run, nor does it need coolant to cool. The engine under test enters the test bench, and the servo motor of the test bench drives the engine to rotate at different speeds. At the same time, the test system collects the test process data of the engine air inlet, air outlet, oil channel, etc. through the data acquisition card, and provides it to the later analysis system to determine whether the engine is assembled correctly.

[0003] The engine cold test bench is the working environment for implementing the engine cold test. The current mainstream engine cold test bench suppliers include ThyssenKrupp, KUKA, AVL, Frorich, ADT, A&G, etc. The engine cold test bench can test up to 2,000 test items on each engine and collect the corresponding test values. Test items may include, for example, torque, speed, water pressure, oil pressure, oil temperature, etc. The engine cold test bench usually includes multiple workbenches that perform cold test tests in parallel.

[0004] In the current mainstream engine cold test bench, static test thresholds can be configured for the cold test values ​​to evaluate whether the various technical indicators of the engine meet the design requirements of the engine. Summary of the invention

[0005] An object of the present disclosure is to provide an improved engine quality stability assessment method and apparatus.

[0006] The present disclosure proposes a method for evaluating engine quality stability, the method comprising: for each of a plurality of engines on a production line: receiving information indicating the type and number of the engine; based on the type and number of the engine, obtaining cold test values ​​of the engine related to a plurality of test items, wherein the plurality of test items are determined according to the type of the engine; grouping the cold test values ​​of the plurality of engines at least according to the type of the engine; and for each group of cold test values, for each test item in the plurality of test items, evaluating whether the cold test value is stable, and generating an evaluation result on whether the cold test value is stable.

[0007] Other features and advantages of the present disclosure will become apparent from the following description with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments of the present disclosure and, together with the description, serve to explain the principles of the present disclosure without limitation. In the various figures, like reference numerals are used to represent like items.

[0009] Figure 1 is a block diagram of an exemplary engine quality stability assessment apparatus according to some embodiments of the present disclosure.

[0010] Figure 2 is a flow chart illustrating an exemplary engine quality stability assessment method according to some embodiments of the present disclosure.

[0011] Figure 3 is a flow chart illustrating example evaluation operations according to some embodiments of the present disclosure.

[0012] Figure 4 is a flow chart illustrating an example engine quality issue batch traceback operation according to some embodiments of the present disclosure.

[0013] Figure 5 A general hardware environment in which the present disclosure may be applied according to some embodiments of the present disclosure is shown. DETAILED DESCRIPTION

[0014] In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the described exemplary embodiments. However, it is clear to those skilled in the art that the described embodiments may be practiced without some or all of these specific details. In the described exemplary embodiments, well-known structures or processing steps are not described in detail in order to avoid unnecessarily obscuring the concepts of the present disclosure.

[0015] The blocks in each block diagram shown below can be implemented by hardware, software, firmware or any combination thereof to implement the principles of the present disclosure. It should be understood by those skilled in the art that the blocks described in each block diagram can be combined or divided into sub-blocks to implement the principles of the present disclosure.

[0016] The steps of the method presented in this disclosure are intended to be illustrative. In certain embodiments, the method can be completed with one or more additional steps not described and / or completed without the one or more steps discussed. In addition, the order in which the steps of the method are illustrated and described is not intended to be restrictive.

[0017] Hereinafter, a description is given taking the stability evaluation of an engine of a vehicle as an example.

[0018] Figure 1 is a block diagram of an exemplary engine quality stability assessment apparatus 100 according to some embodiments of the present disclosure. Figure 1As shown, the apparatus 100 may include: an information receiving module 110, a data acquisition module 120, a cold test value grouping module 130, and a quality stability evaluation module 140. The apparatus 100 may also include: an alarm module 150, a data query module 160, and a quality problem batch tracing module 170. In addition, the apparatus 100 may also include a storage device 180.

[0019] The information receiving module 110 can receive information indicating the type and number of each engine in a plurality of engines on an engine production line from an engine production control system. The engine production line simultaneously produces multiple types of engines, such as 3-cylinder engines, 4-cylinder engines, and their respective sub-types (such as transverse and longitudinal types, etc.). In the present disclosure, engines of each sub-type are regarded as different types of engines. Alternatively, the engines can be classified into coarser or newer types according to actual needs. The engine number uniquely identifies an engine. The engine production control system controls the assembly process of each engine on the engine production line, and provides information indicating the type and number of each engine to the device 100.

[0020] The data acquisition module 120 can obtain the cold test test values ​​related to multiple test items of the engine from the engine cold test test bench based on the type and number of the engine received by the information receiving module 110, wherein the multiple test items are determined according to the type of the engine. In some embodiments, the data acquisition module 120 can also obtain the information of the workbench that performs the cold test corresponding to the engine and the information of the time when the cold test is performed corresponding to the engine from the engine cold test test bench based on the type and number of the engine received by the information receiving module 110. Here, the workbench information can be information indicating which workbench performed the cold test, such as a workbench identification (ID), etc. The time information can be information indicating the time when the cold test was performed, such as the test start time, a specific test time period, etc.

[0021] In the present disclosure, the engine cold test bench is, for example, a KUKA test bench adopted by BMW Brilliance Automotive Co., Ltd. The engine cold test bench is not limited thereto, but other suitable test benches may be adopted. The engine cold test bench may record the aforementioned bench information and time information. The engine cold test bench may store a test number that uniquely identifies a test in association with an engine number, an engine type, test bench information, test time information, and a cold test value for each test item.

[0022] In the present disclosure, the aforementioned multiple test items are determined according to the type of engine. For example, for a type A engine, only the cold test values ​​regarding torque and speed may be obtained. This is because the test indicators of interest may be different for different types of engines. It should be noted that for different types of engines, the cold test values ​​of which test items are obtained are user-configurable. In other words, the user of the device 100 can specify in advance which cold test values ​​of which test items need to be obtained for different types of engines. By selectively obtaining cold test values, rather than obtaining all cold test values, the computational burden of the device 100 can be reduced and the evaluation efficiency of the device 100 can be improved, while enabling user-customizable evaluations.

[0023] The cold test value grouping module 130 can group the cold test values ​​of multiple engines on the engine production line according to at least the engine type received by the information receiving module 110. In some embodiments, the cold test value grouping module 130 can group the cold test values ​​of multiple engines according to the engine type received by the information receiving module 110, the workbench information obtained by the data acquisition module 120, and the time information. Specifically, the cold test value grouping module 130 can divide the cold test values ​​of engines of the same type, tested on the same workbench, and tested in the same time period into the same group. For example, the cold test value grouping module 130 can divide the cold test values ​​of engines of type A, tested on workbench No. 1, and tested between 8:00 and 11:00 in the morning into one group. By grouping the cold test values, the disturbance of the stability evaluation by external factors can be avoided in the quality stability evaluation process described later, thereby improving the accuracy of the evaluation.

[0024] The quality stability evaluation module 140 can evaluate whether the cold test value is stable for each group of cold test values ​​and for each test item in the aforementioned multiple test items, and generate an evaluation result on whether the cold test value is stable. The evaluation operation of the quality stability evaluation module 140 will be further described in detail below.

[0025] The alarm module 150 can generate and send an alarm message when the generated evaluation result indicates that the cold test value is unstable. The alarm message may include the following content items: the number of the relevant engine, the group ID of the cold test value, the test item ID, the relevant cold test value, and the reason why the cold test value is evaluated as unstable. The number of the relevant engine may include the number of one or more engines that cause unstable evaluation results. The relevant cold test value may include one or more cold test values ​​that cause unstable evaluation results. The alarm module 150 can send the alarm message to an email server, and send the alarm message to the relevant engine quality analysis control personnel via the email server. Alternatively, the alarm message can be notified via an instant message. By reporting the engine quality anomaly to the relevant personnel in real time, the relevant personnel can locate, analyze and control the engine quality risk in a timely manner.

[0026] The data query module 160 can provide associated evaluation process data in response to a data query request containing the number of the relevant engine, the group ID of the cold test value, and the test item ID. In some embodiments, after receiving the alarm message, the engine quality analysis control personnel need to further retrieve detailed data to analyze the quality risks. The engine quality analysis control personnel can input the aforementioned data query request into the data query module 160, and then the data query module 160 can provide the engine quality analysis control personnel with the associated evaluation process data in response to the request. Here, the associated evaluation process data can be various data associated with the data query request and used in the evaluation operation. More specifically, the evaluation process data can include the cold test value based on which the evaluation result is generated, and / or the evaluation criteria, evaluation parameters, etc. used to generate the evaluation result.

[0027] The quality problem batch tracing module 170 can receive information specifying a test item and a numerical range for the test item, receive the numbers of a group of engines of interest among multiple engines on the engine production line, and based on the specified test items and numerical ranges, refer to the obtained cold test values ​​of multiple engines on the production line, and output the numbers of the engines in the group of engines whose cold test values ​​for the specified test items meet the specified numerical range and the corresponding cold test values ​​for the specified test items. In the present disclosure, the obtained cold test values ​​of multiple engines on the production line can be stored in the storage device 180 described later. Alternatively, the obtained cold test values ​​can be stored outside the device 100. The operation of the quality problem batch tracing module 170 will be described in further detail below.

[0028] The storage device 180 can store a library of evaluation models for evaluating engine quality stability (evaluation model library). The evaluation model library provides a set of algorithms guided by production experience and based on statistical principles to evaluate engine quality stability. In the present disclosure, the evaluation model library used uses the SPC (Statistical Process Control) standard tool in IATF16949 (automotive industry quality management system standard) as a reference prototype, and allows users to configure different evaluation criteria and evaluation parameters for different engine types. The storage device 180 can also store the engine number, engine type, test number of the engine cold test bench, test bench information, test time information, cold test test values ​​for each test item, and evaluation results of the cold test test values ​​for each test item in association as an engine evaluation record table. The storage device 180 can be any storage device that can implement a data repository. Although in Figure 1 2 and 3 , the storage device 180 is shown to be included in the apparatus 100 , but the present disclosure is not limited thereto, and the storage device 180 may be located outside the apparatus 100 .

[0029] In some embodiments, the device 100 may only include the information receiving module 110, the data acquisition module 120, the cold test value grouping module 130, and the quality stability evaluation module 140. In other embodiments, the device 100 may only include the information receiving module 110, the data acquisition module 120, the cold test value grouping module 130, the quality stability evaluation module 140, and the alarm module 150. In other words, the data query module 160 and the quality problem batch tracing module 170 are optional modules.

[0030] The following will further describe in detail Figure 1 The operation of each component is shown.

[0031] Figure 2 is a flow chart illustrating an exemplary engine mass stability assessment method 200 according to some embodiments of the present disclosure.

[0032] The method 200 starts from step S210, where the information receiving module 110 receives information indicating the type and number of each engine in a plurality of engines on an engine production line from an engine production control system. In the present disclosure, the information receiving module 110 receives the type and number information of each engine (hereinafter referred to as the "current engine") as it comes off the engine production line.

[0033] The method 200 proceeds to step S220, where the data acquisition module 120 acquires the test number, the test bench information and test time information corresponding to the engine, and the cold test values ​​of multiple test items of the engine according to the engine type from the engine cold test bench based on the type and number of the engine received in step S210. Furthermore, the data acquisition module 120 sends these information items to the storage device 180 to be stored in the engine evaluation record table.

[0034] The method 200 proceeds to step S230, where the cold test value grouping module 130 divides the engine into corresponding groups according to the engine type and the test bench information and test time information corresponding to the engine. As previously mentioned, the cold test value grouping module 130 can divide the cold test values ​​of engines of the same type, tested on the same bench, and tested in the same time period into the same group. Here, the time period can be configured by the user according to actual needs. More specifically, at step S230, the cold test value grouping module 130 divides the cold test values ​​of the current engine into corresponding groups (hereinafter referred to as "current groups").

[0035] Next, the method 200 proceeds to step S240, where the quality stability assessment module 140 assesses whether the cold test value is stable for each test item in the current group and generates an assessment result on whether the cold test value is stable. In some embodiments, a single module 140 assesses each test item in series for the current group. In other embodiments, multiple modules 140 assess multiple test items in parallel for the current group. For example, in the case where three modules 140 are arranged in parallel, the three modules 140 can assess different test items for the current group, respectively. This can shorten the time of the assessment operation. In actual production, an engine is offline approximately every 20 seconds. By using multiple assessment modules working in parallel, stability assessment can be achieved synchronously with the output of the production line. It should be understood that the number of modules 140 working in parallel can be configured by the user according to actual needs.

[0036] Figure 3 is a flowchart illustrating an exemplary detailed process of step S240.

[0037] like Figure 3As shown, at sub-step S2401, module 140 determines whether there are test items to be evaluated for the current group. If yes, the method proceeds to sub-step S2402, where module 140 takes out a test item to be evaluated (hereinafter referred to as "current test item") from the list of test items to be evaluated and deletes the item from the list. If no, step S240 ends, and method 200 proceeds to step S250.

[0038] Method 200 proceeds to sub-step S2403, where, for the current group, for the current test item, module 140 determines whether the number of cold test values ​​in the current group (that is, the number of engines divided into the current group) reaches a predetermined number (e.g., 200). If not, then at sub-step S2404, module 140 adds the cold test value of the current test item of the current engine to the current group, and method 200 returns to sub-step S2401. If yes, then at sub-step S2405, module 140 deletes the oldest cold test value from the current group in time, and adds the cold test value of the current test item of the current engine to the current group, thereby maintaining the cold test value in the current group as the cold test value of the most recently generated predetermined number (e.g., 200) in time. Here, the value of the predetermined number can be configured by the user according to actual needs.

[0039] The method 200 proceeds to sub-step S2406, where the module 140 determines the mean μ and variance σ of a predetermined number (e.g., 200) of cold test values ​​in the current group. In some embodiments, the module 140 calculates the mean μ and variance σ. In other embodiments, the module 140 obtains a preset mean μ and variance σ. For example, the module 140 may obtain a preset mean μ and variance σ from the storage device 180. Here, the preset mean μ and variance σ may be preset according to the engine type.

[0040] The method 200 proceeds to sub-step S2407, where the module 140 uses the evaluation model to evaluate whether the cold test value is stable based on the mean μ and variance σ determined at sub-step S2406. Specifically, the module 140 calls the evaluation model from the storage device 180 and uses the evaluation model to evaluate the stability of the cold test value of the current group and the current test item. The evaluation model can use one or more evaluation criteria for evaluation. The evaluation model can output an evaluation result corresponding to each evaluation criterion. The evaluation model evaluates that the cold test value is unstable when at least one of the following evaluation criteria is met:

[0041] (1) The cold test value of an individual falls outside the statistical interval [μ–n1σ, μ+n1σ];

[0042] (2) P1 consecutive cold test values ​​are on the same side of μ;

[0043] (3) The values ​​of the consecutive P1 cold tests have the same changing trend;

[0044] (4) P2 consecutive cold test values ​​have P3 or more cold test values ​​falling outside the statistical interval [μ – n2σ, μ + n2σ]; and

[0045] (5) Among the P2 consecutive cold test values, equal to or more than P3 cold test values ​​fall within the statistical interval [μ–n3σ, μ+n3σ];

[0046] Wherein, μ represents the mean, σ represents the variance, P1, P2, P3, n1, n2, n3 are configurable evaluation parameters, and where P1, P2, P3 are positive integers, P3 ≤ P2, and n1, n2, n3 are arbitrary values. Here, P1 may be equal to or not equal to P2 (or P3). n1, n2, n3 may be equal or not equal.

[0047] Evaluation criterion (1) can be used to evaluate whether individual cold test values ​​are abnormal. Evaluation criterion (2) can be used to evaluate whether similar batch problems have occurred. Evaluation criterion (3) can be used to evaluate the changing trend of test values, such as gradually increasing or decreasing. Evaluation criterion (4) can be used to evaluate whether similar batch problems have occurred. Evaluation criterion (5) can be used to evaluate whether the cold test bench can stably measure the product. When the distinction between multiple consecutive measurement values ​​is very small, it is necessary to determine whether the cold test bench can measure the data correctly. The test values ​​should conform to the normal distribution. It is abnormal for the test values ​​to be concentrated in a very small range.

[0048] In some embodiments, the evaluation criteria used are user configurable. For example, a user can select any one or more of the above criteria (1)-(5) to evaluate. The evaluation parameters used are also user configurable. For example, a user can set the above evaluation parameters P1, P2, P3, n1, n2, n3 according to actual product requirements. In some embodiments, although not shown, before sub-step S2407, method 200 may also include the step of configuring the evaluation criteria and / or evaluation parameters. By allowing the evaluation criteria and / or evaluation parameters to be configured, user-customizable evaluation can be achieved.

[0049] In addition, at sub-step S2407, module 140 generates an evaluation result on whether the cold test value is stable. The evaluation result may include an evaluation result corresponding to each evaluation criterion. In other words, the evaluation result may indicate the reason why the cold test value is evaluated as unstable (i.e., which evaluation criterion or criteria are not satisfied). For example, the evaluation result may include: 20 consecutive cold test values ​​(181-200 cold test values) are on the same side of the mean μ, so the cold test value is unstable. In addition, module 140 may send the number of the relevant engine, the group ID of the cold test value, the test item ID, the relevant cold test value, and the evaluation result to the alarm module 150. Here, the number of the relevant engine may be, for example, the number of the current engine. In addition, module 140 may send the number of the current engine, the group ID, the test item ID, and the evaluation result to the storage device 180 to store in the engine evaluation record table.

[0050] In some embodiments, module 140 may also send an evaluation parameter list to alarm module 150. The evaluation parameter list may include the evaluation parameters used and their values. The evaluation parameters may include the mean, variance, and configurable evaluation parameters as described above. In this case, the alarm message may further include the evaluation parameter list. In this case, the engine evaluation record table may also include the evaluation parameter list.

[0051] After sub-step S2407, method 200 returns to sub-step S2401.

[0052] Return to reference Figure 2 , the method 200 proceeds to step S250, where the alarm module 150 generates and sends an alarm message when the generated evaluation result indicates that the cold test value is unstable. The alarm message may include the following content items: the number of the relevant engine, the group ID of the cold test value, the test item ID, the relevant cold test value, and the reason why the cold test value is evaluated as unstable. For example, the reason why the cold test value is evaluated as unstable may be that 20 consecutive cold test values ​​(the 181st to 200th cold test values) are on the same side of the mean μ, so the cold test value is unstable. In addition, at step S250, when the generated evaluation result indicates that the cold test value is stable, the alarm module 150 does not act.

[0053] The method 200 proceeds to step S260, where the data query module 160 responds to the data query request including the number of the relevant engine, the group ID of the cold test value, and the test item ID, and provides the associated evaluation process data. Based on the provided evaluation process data, the engine quality analysis control personnel can conveniently locate and analyze quality risks.

[0054] The method 200 proceeds to step S270 , where the quality problem batch tracing module 170 performs an engine quality problem batch tracing operation. Figure 4 is a flowchart illustrating an exemplary detailed process of step S270.

[0055] like Figure 4 As shown, at sub-step S2701, module 170 receives information specifying a test item and a numerical range for the test item. At sub-step S2702, module 170 receives the number of a group of engines of interest. This group of engines can be a batch of engine products. For example, the user of device 100 wants to review the quality stability of this group of engine products. At sub-step S2703, module 170 refers to the engine evaluation record table stored in storage device 180, retrieves the cold test value of the specified test item for each engine for the number of the group of engines received in sub-step S2702, and selects the engine whose cold test value meets the specified numerical range. Here, the cold test value meets the specified numerical range includes: the cold test value falls within the specified numerical range, or the cold test value falls outside the specified numerical range. Module 170 outputs the number of the engine in this group of engines that meets the specified test item and numerical range and the specific cold test value of each engine for the specified test item. With this quality problem batch tracing operation, it is possible to trace and find engines that may have quality stability problems in a batch of engine products of interest by using filtering conditions.

[0056] It should be noted that in method 200, steps S250-S270 are optional steps. Alternatively, in method 200, step S260 and / or step S270 are optional steps.

[0057] As described above, the present disclosure provides a user-customizable, highly accurate, and real-time alarm engine quality stability assessment method and device. In addition, the engine quality stability assessment method and device of the present disclosure has a novel problem batch tracing function.

[0058] Hardware Implementation

[0059] Figure 5 A general hardware environment 500 is shown in which the present disclosure may be applied according to an exemplary embodiment of the present disclosure.

[0060] refer to Figure 5, a computing device 500 will now be described as an example of a hardware device applicable to various aspects of the present disclosure. The computing device 500 may be any machine configured to perform processing and / or computing, and may be, but is not limited to, a workstation, a server, a desktop computer, a laptop computer, a tablet computer, a personal digital assistant, a smart phone, a portable camera, or any combination thereof. The above-mentioned apparatus 100 may be implemented in whole or at least in part by the computing device 500 or a similar device or system.

[0061] The computing device 500 may include elements that can be connected to or communicate with the bus 502 via one or more interfaces. For example, the computing device 500 may include a bus 502, one or more processors 504, one or more input devices 506, and one or more output devices 508. The one or more processors 504 may be any type of processor, and may include, but are not limited to, one or more general-purpose processors and / or one or more special-purpose processors (such as special-purpose processing chips). The input device 506 may be any type of device that can input information to the computing device, and may include, but are not limited to, a mouse, a keyboard, a touch screen, a microphone, and / or a remote controller. The output device 508 may be any type of device that can present information, and may include, but are not limited to, a display, a speaker, a video / audio output terminal, and / or a printer. The computing device 500 may also include or be connected to a non-transient storage device 510, which may be any storage device that is non-transient and can implement a data repository, and may include but is not limited to a disk drive, an optical storage device, a solid-state storage device, a floppy disk, a flexible disk, a hard disk, a magnetic tape or any other magnetic medium, a compact disk or any other optical medium, a ROM (read-only memory), a RAM (random access memory), a cache memory and / or any other memory chip or cartridge, and / or any other medium from which a computer can read data, instructions and / or code. The non-transient storage device 510 may be detachable from the interface. The non-transient storage device 510 may have data / instructions / code for implementing the above methods and steps. The computing device 500 may also include a communication device 512. The communication device 512 may be any type of device or system capable of communicating with an external device and / or with a network, and may include but is not limited to a modem, a network card, an infrared communication device, a wireless communication equipment and / or a communication device such as Bluetooth. TM Chipsets for devices, 502.11 devices, WiFi devices, WiMax devices, cellular communication facilities, etc.

[0062] The bus 502 may include, but is not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MCA) bus, an Enhanced ISA (EISA) bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.

[0063] The computing device 500 may also include working memory 514, which may be any type of working memory that can store instructions and / or data useful for the operation of the processor 504, and may include, but is not limited to, random access memory and / or read-only memory devices.

[0064] The software elements may be located in the working memory 514, including but not limited to an operating system 516, one or more application programs 518, a driver and / or other data and code. Instructions for executing the above methods and steps may be included in one or more application programs 518, and the components in the above device 100 may be implemented by the processor 504 reading and executing the instructions of one or more application programs 518. More specifically, the information receiving module 110 may be implemented, for example, by the processor 504 when executing the application program 518 having an instruction to execute step S210. The data acquisition module 120 may be implemented, for example, by the processor 504 when executing the application program 518 having an instruction to execute step S220. The cold test value grouping module 130 may be implemented, for example, by the processor 504 when executing the application program 518 having an instruction to execute step S230. The quality stability assessment module 140 may be implemented, for example, by the processor 504 when executing the application program 518 having an instruction to execute step S240. And, similarly, the alarm module 150, the data query module 160, and the quality problem batch tracing module 170 can be implemented, for example, by the processor 504 when executing the application 518 having instructions for respectively executing steps S250, S260, and S270. The executable code or source code of the instructions of the software element can be stored in a non-transitory computer-readable storage medium (such as the above-mentioned (one or more) storage devices 510), and can be read into the working memory 514 when it is possible to compile and / or install. The executable code or source code of the instructions of the software element can also be downloaded from a remote location.

[0065] From the above embodiments, it will be clear to those skilled in the art that the present disclosure can be implemented by software and necessary hardware, or can be implemented by hardware, firmware, etc. Based on this understanding, the embodiments of the present disclosure can be partially implemented in the form of software. Computer software can be stored in a computer-readable storage medium, such as a floppy disk, a hard disk, an optical disk, or a flash memory. Computer software includes a series of instructions that enable a computer (such as a personal computer, a service station, or a network terminal) to run a method according to each embodiment of the present disclosure or a part thereof.

[0066] The disclosure having thus been described, it will be apparent that the disclosure may be varied in many ways. Such variations are not to be regarded as a departure from the spirit and scope of the disclosure, and all such modifications as would be obvious to one skilled in the art are intended to be included within the scope of the following claims.

Claims

1. A method for evaluating engine quality stability, characterized in that: include: For each of the multiple engines on the engine production line: receiving information indicating the type and number of the engine; Based on the type and number of the engine, obtain cold test values ​​of the engine related to a plurality of test items, wherein the plurality of test items are determined according to the type of the engine; Based on the type and number of the engine, information of the workbench corresponding to the engine for executing the cold test and information of the time when the cold test was executed corresponding to the engine are obtained, grouping the cold test values ​​of the plurality of engines according to the type of the engine, the information of the workbench corresponding to the engine at which the cold test is performed, and the information of the time at which the cold test is performed corresponding to the engine; and For each set of cold test values, for each of the plurality of test items, evaluating whether the cold test value is stable, and generating an evaluation result on whether the cold test value is stable, Wherein, for each set of cold test values, for each test item in the plurality of test items, evaluating whether the cold test value is stable comprises: For each set of cold test values, for each test item in the plurality of test items, determining a mean and a variance of a predetermined number of cold test values, wherein the predetermined number of cold test values ​​are from a predetermined number of engines in the same group, Based on the determined mean and variance, an evaluation model was used to assess whether the cold test values ​​were stable.

2. The method according to claim 1, further comprising: When the generated evaluation result indicates that the cold test value is unstable, an alarm message is generated and sent, wherein the alarm message The following items are included: the number of the relevant engine, the group identification of the cold test value, the test item identification, the relevant cold test value, and the reason why the cold test value is evaluated as unstable.

3. The method according to claim 2, further comprising: In response to a data query request containing the serial number of the relevant engine, the group identifier of the cold test value, and the test item identifier, the associated evaluation process data is provided.

4. The method according to claim 1, wherein: The evaluation model evaluates the cold test value to be unstable if at least one of the following evaluation criteria is met: The cold test value of an individual falls outside the statistical interval [μ– n1σ, μ+ n1σ]; P1 consecutive cold test values ​​are on the same side of μ; The values ​​of the consecutive P1 cold tests have the same trend of change; There are P2 consecutive cold test values, equal to or more than P3 cold test values, which fall outside the statistical interval [μ – n2σ, μ + n2σ]; and There are P2 consecutive cold test values, equal to or more than P3 cold test values, falling within the statistical interval [μ – n3σ, μ + n3σ]; Wherein, μ represents the mean, σ represents the variance, P1, P2, P3, n1, n2, n3 are configurable evaluation parameters, and where P1, P2, P3 are positive integers, P3≤P2, and n1, n2, n3 are arbitrary values.

5. The method according to claim 1, further comprising: receiving information specifying a test item and a value range for the test item; receiving a set of engine numbers of interest from among the plurality of engines; and According to the specified test items and numerical ranges, with reference to the cold test values ​​obtained for the multiple engines, the numbers of the engines in the group of engines whose cold test values ​​for the specified test items satisfy the specified numerical range and the corresponding cold test values ​​for the specified test items are output.

6. A device for evaluating engine quality stability, characterized in that: include: Module for performing the method as claimed in any one of claims 1-5.

7. A device for evaluating engine quality stability, characterized in that: include: at least one processor; as well as At least one storage device stores instructions, which, when executed by the at least one processor, cause the at least one processor to perform the method according to any one of claims 1 to 5.

8. A non-transitory computer-readable storage medium, characterized in that: Instructions are stored which, when executed by a processor, cause the method according to any one of claims 1 to 5 to be performed.

Images