A kind of intelligent testing method and system for acoustic production defects

Abstract

The present application discloses an intelligent testing method and system for audio production defects, which relates to the technical field of audio defect testing. The method includes performing image acquisition on the production results of a production sub-process to obtain production image data; performing fault analysis on the production image data, and if it is determined that there is a problem with the production image data, determining the processing equipment according to the fault area data, and performing data self-adjustment on the processing equipment according to the production image data; according to the process sequence, when there is no problem with the production image data of the last production sub-process, performing functional testing on the final product based on the functional testing equipment, and if the audio function is not complete, matching the audio function defect to the quality event database to determine the cause of the corresponding functional defect and the treatment measures; performing fault treatment on the current audio based on the treatment measures, and treating the process according to the cause of the audio failure. The present application has the effect of improving the efficiency of defect testing.

Description

Technical Field

[0001] The present application relates to the technical field of audio defect testing, and in particular to an intelligent testing method and system for audio production defects. Background Art

[0002] In the production process of audio products, quality control and defect detection are key links to ensure product performance, stability and user satisfaction. With the continuous development of audio technology and the increasing demand for sound quality from consumers, the functionality and complexity of audio products are also increasing.

[0003] In the related technology, most of the corresponding function tests are carried out on the finished audio equipment through the related function testing equipment to determine whether there is a problem with the corresponding function of the audio. Then, according to the problem with the corresponding function, the tester judges the cause of the fault based on personal experience, and determines the corresponding treatment measures to correct the problematic audio and ensure the normal use of the audio.

[0004] Regarding the above-mentioned related technologies, the testers make subjective judgments on the causes of audio failures based on their work experience, which leads to strong subjectivity, and thus problems such as low judgment accuracy and low efficiency. There is room for improvement. Summary of the invention

[0005] In order to improve testing efficiency, the present application provides an intelligent testing method and system for audio production defects.

[0006] In the first aspect, the present application provides an intelligent testing method for audio production defects, which adopts the following technical solution:

[0007] An intelligent testing method for acoustic production defects, comprising:

[0008] Acquire the production process of the audio system and split the production process to obtain production sub-processes with a process sequence, and collect images of the production results of the audio components of the production sub-processes to obtain production image data of the audio components of the corresponding production sub-processes;

[0009] Performing production defect analysis on production image data of the audio component to determine whether the audio component produced by each production sub-process has production defects;

[0010] If it is determined that the sound component produced by the production sub-process does not have a production defect, the sound component of the production sub-process is moved to the next production sub-process according to the process sequence;

[0011] If it is determined that the audio component produced by the production sub-process has a production defect, then marking the area determined to have the production defect on the production image data of the audio component as fault area data;

[0012] Determine the processing equipment corresponding to the fault area of ​​the audio component with defects in production according to the fault area data, and obtain the processing error amount of the processing equipment. If the processing error amount of the processing equipment is lower than a preset threshold, do not adjust the production processing parameters of the processing equipment; the processing error amount of the processing equipment is the number of times the audio component processed by the processing equipment in the production process of the production sub-process is unqualified;

[0013] If the processing error amount of the processing equipment is higher than a preset threshold, adjusting the production processing parameters of the processing equipment according to the production image data;

[0014] According to the process sequence, when the production image data of the last production sub-process does not contain production defects, the functional test of the final audio product is performed based on the functional test equipment to determine the integrity of the audio function;

[0015] If the audio function is complete, the audio is packaged and output;

[0016] If the audio function is not complete, the quality event database is matched according to the audio function defects tested by the functional testing equipment to determine the cause of the corresponding functional defects and the treatment measures;

[0017] Based on the processing measures, the audio system with functional defects is restored to its original state so that the audio system has complete functions. The corresponding production sub-process is processed according to the cause of the fault to eliminate the cause of the fault.

[0018] Preferably, the production image data is compared with the built-in standard image data to determine whether there is any difference in the image data;

[0019] If it is determined that there is a difference between the production image data and the standard image data, obtaining the simulated image data, and comparing the production image data with the simulated image data to determine whether there is a difference between the production image data and the simulated image data;

[0020] If it is determined that the production image data is the same as the simulation image data, then it is determined that the production sub-process corresponding to the production image data has a defect, that is, a process defect;

[0021] If it is determined that the production image data is different from the simulation image data, the simulation image data is judged to be different from the standard image data;

[0022] If the simulated image data is the same as the standard image data, it is determined that the production result has defects in the handling process, that is, handling defects;

[0023] If the simulated image data is different from the standard image data, it is determined that the production result of the corresponding generation sub-process is defective, that is, the audio component is defective;

[0024] If the production image data is identical to the standard image data, it is determined that the production image data has no production defects.

[0025] Preferably, when the first piece of audio is produced, the process sequence of the current production sub-process is obtained, and the image data of the production result of the production sub-process of the previous process sequence is read according to the process sequence, and recorded as the previous production image data;

[0026] Obtain the production and processing parameters of each processing equipment in the current production sub-process and the processing type of the corresponding processing equipment, obtain the parameter information of the audio components that need to be processed in the current production sub-process, and perform image simulation on the previous production image data according to the production and processing parameters, processing type and structural parameter information of the audio components to obtain the simulated image data of the current production sub-process.

[0027] Preferably, the defect type corresponding to the production image data is obtained. If the defect type of the production image data is a process defect, the processing category information of the processing equipment corresponding to the fault area is obtained, and it is determined whether the production processing parameters of the processing equipment can be automatically adjusted according to the processing category information;

[0028] Determine, based on the processing category information, processing data items that can directly affect the implementation of corresponding functions of the processing equipment;

[0029] Based on the historical production image data of the corresponding production sub-process, the evaluation parameter value of the processing effect diagram of the corresponding processing equipment and the numerical value of the corresponding processing data item are obtained, and the evaluation parameter value of the processing effect diagram and the numerical value of the processing data item are linearly judged to determine whether there is a linear relationship between the processing effect and the processing data item;

[0030] If the processing effect has a linear relationship with the processing data item, it is determined that the processing equipment can be automatically adjusted, the production image data and the standard image data are compared to determine the correction data, and the production processing parameters of the processing equipment are adjusted according to the correction data;

[0031] If the processing effect does not have a linear relationship with the processing data item, the production image data is compared with the standard image data to determine the fault category of the fault area on the production image data; the fault category includes functional correctness and position correctness;

[0032] If the fault category is functional correctness, but the position is not correct, the production image data and the standard image data are compared to determine correction data, and the production processing parameters of the processing equipment are adjusted according to the correction data;

[0033] If the fault category is that the function is not correct, an alarm signal for the production sub-process is output.

[0034] Preferably, if the defect type of the production image data is a handling defect, a comparison is performed based on the production image data and the standard image data to determine the position offset data of the audio component after processing corresponding to the fault area;

[0035] Obtain the number of handling equipment located before the processing equipment in the production sub-process, recorded as the number of front handling equipment, and obtain the number of handling equipment located after the processing equipment in the production sub-process, recorded as the number of rear handling equipment;

[0036] The front transport equipment and the rear transport equipment are numbered according to the position distance between the transport equipment and the processing equipment, and the number of the front transport equipment closest to the processing equipment is recorded as the first front transport equipment, and the number of the rear transport equipment closest to the processing equipment is recorded as the first rear transport equipment, and so on, to obtain the numbering data of the corresponding front transport equipment and the numbering data of the rear transport equipment;

[0037] Based on the numbering sequence of the numbering data of the front transporting devices, the adjustable displacement data of the first front transporting device is compared with the position offset data to determine whether the adjustable displacement data of the first front transporting device is greater than or equal to the position offset data;

[0038] If it is determined that the adjustable displacement data of the first front transport device is greater than or equal to the position offset data, then the transport device is adjusted according to the position offset data;

[0039] If it is determined that the adjustable displacement data of the first front handling equipment is less than the position offset data, then the subsequent multiple front handling equipment are jointly mobilized one by one according to the number and number data of the front handling equipment, and the number of jointly mobilized handling equipment is compared with the number of front handling equipment. If the number of jointly mobilized handling equipment is less than or equal to the number of front handling equipment, the jointly mobilized adjustable displacement data is adjusted until the jointly mobilized adjustable displacement data is greater than or equal to the position offset data; if the number of jointly mobilized handling equipment is greater than the number of front handling equipment, an alarm is output for the current production sub-process;

[0040] Similarly, the adjustable data comparison is performed on the first rear transport device of the current processing device, so as to schedule and adjust the rear transport device according to the position offset data.

[0041] Preferably, if the defect type of the production image data is an acoustic component defect, the production image data of the previous production sub-process is acquired according to the process sequence and recorded as the previous production image data;

[0042] De-processing the production image data based on the functions of each processing equipment in the current production sub-process to obtain image data before processing and record it as pre-processed image data;

[0043] Comparing the previous production image data and the pre-processed image data based on the fault area data of the current production image data to determine whether the image data of the previous production image data and the image data of the pre-processed image data on the fault area are the same;

[0044] If it is determined that the image data on the faulty area is different, the current production sub-process is marked;

[0045] If it is determined that the image data on the faulty area are the same, the production image data of the production sub-process flow preceding the current production sub-process flow sequence is matched according to the previous production image data, so as to trace the production sub-process where the device fails, and mark the corresponding production sub-process;

[0046] Output alarm for marked production sub-process.

[0047] Preferably, historical fault handling records are counted to obtain a sound quality event database;

[0048] Based on the knowledge graph technology, the quality event database of the audio system is matched to obtain the fault relationship including the correlation between the problem description, defect problem, fault cause and treatment measures;

[0049] Matching the functional defects of the audio system based on the fault relationship to determine the fault cause of the corresponding functional defect and the component information of the corresponding functional defect;

[0050] The fault relationship is re-matched based on the component information of the corresponding functional defect and the fault cause to determine the treatment measures for the corresponding component when the fault cause occurs.

[0051] In the second aspect, the present application provides an intelligent testing system for audio production defects, which adopts the following technical solutions:

[0052] An intelligent testing system for acoustic production defects, comprising: an image acquisition module, an image analysis module, a structural defect processing module, a functional defect analysis module, and a functional defect processing module;

[0053] The image acquisition module acquires the production process of the audio system and splits the production process to obtain production sub-processes with a process sequence, and performs image acquisition on the production results of the audio components of the production sub-processes to obtain production image data of the audio components of the corresponding production sub-processes;

[0054] The image analysis module performs production defect analysis on the production image data of the audio component to determine whether the audio component produced by each production sub-process has production defects;

[0055] The structural defect processing module, if it is determined that the audio component produced by the production sub-process does not have a production defect, then the audio component of the production sub-process is moved to the next production sub-process according to the process sequence; if it is determined that the audio component produced by the production sub-process has a production defect, the area determined to have a production defect on the production image data of the audio component is marked as fault area data; the processing equipment corresponding to the fault area of ​​the audio component with production defects is determined according to the fault area data, and the processing error amount of the processing equipment is obtained, and if the processing error amount of the processing equipment is lower than a preset threshold, the production processing parameters of the processing equipment are not adjusted; the processing error amount of the processing equipment is the number of times the audio component processed by the processing equipment during the production process of the production sub-process is unqualified; if the processing error amount of the processing equipment is higher than the preset threshold, the production processing parameters of the processing equipment are adjusted according to the production image data;

[0056] The functional defect analysis module, according to the process sequence, performs a functional test on the final audio product based on the functional testing equipment to determine the integrity of the audio function when the production image data of the last production sub-process does not have a production defect;

[0057] The functional defect processing module packages and outputs the audio if the audio function is complete; if the audio function is not complete, the quality event database is matched according to the audio function defect tested by the functional testing equipment to determine the cause of the corresponding functional defect and the treatment measures; based on the treatment measures, the audio currently having the functional defect is subjected to fault recovery processing to make the audio function complete, and the corresponding production sub-process is processed according to the cause of the fault to eliminate the cause of the fault.

[0058] In summary, the present application includes at least one of the following beneficial technical effects:

[0059] By dividing the test phases of the audio system and conducting targeted analysis on each phase after division, the judgment results of production defects are made more accurate. When conducting structural fault analysis on the audio system, fault analysis is performed on the collected production image data, and the corresponding processing equipment is automatically adjusted according to the fault obtained by analysis to eliminate the fault, thereby improving the automation level of the test system. When conducting functional defect analysis on the audio system, the knowledge graph technology is used to match the fault causes and treatment measures for the functional defects obtained in the test, and then the fault causes of production equipment and audio products are eliminated and audio faults are repaired according to the fault causes and treatment measures, thereby improving the efficiency of fault handling.

[0060] By using the function information and corresponding parameter information of the processing equipment corresponding to the generated sub-process, the processing result of the production sub-process is simulated, so that the simulated image data obtained by simulation is more standardized and the evaluation result is more accurate. Then, by comparing the actually collected production image data, standard image data and simulated image data, it is clear whether the production result is qualified and the corresponding defect type, thereby improving the test efficiency and the accuracy of the test result.

[0061] By comprehensively utilizing different processing methods for different defect types, targeted analysis can be conducted on process defects, handling defects and audio component defects, so as to determine the linear relationship between the processing effect and the processing data items of process defects, to ensure that the production and processing parameters of the processing equipment can be automatically adjusted for process defects, to analyze the quantity scheduling of handling defects to reduce the impact on other processing equipment when making corrections, and to trace the fault process of audio component defects to clarify the production sub-process when the audio component has defects. Through targeted analysis of different defect types, the accuracy of production defect test results can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 This is a flowchart of the steps of the intelligent testing method for audio production defects in this embodiment;

[0063] Figure 2 This is a module block diagram of the intelligent testing system for audio production defects in this embodiment.

[0064] Figure numerals: 1. Image acquisition module; 2. Image analysis module; 3. Structural defect processing module; 4. Functional defect analysis module; 5. Functional defect processing module. DETAILED DESCRIPTION

[0065] The following is combined with Figure 1-Figure 2 This application is described in further detail.

[0066] The embodiments of the present application disclose a method and system for intelligent testing of audio production defects.

[0067] Example: Figure 1 As shown, the present invention provides an intelligent testing method for acoustic production defects, comprising:

[0068] S100, obtaining the production process of the audio system and splitting the production process to obtain production sub-processes with a process sequence, and performing image acquisition on the production results of the audio components of the production sub-processes to obtain production image data of the audio components of the corresponding production sub-processes; wherein, the production process can be split according to the production processes of different parts and components, for example, the production of audio housings, welding of circuit boards, and assembly of batteries, speakers, circuit boards, housings, etc.

[0069] S200, performing production defect analysis on production image data of the audio component to determine whether the audio component produced by each production sub-process has production defects;

[0070] S300, if it is determined that the audio component produced by the production sub-process does not have a production defect, the audio component of the production sub-process is transferred to the next production sub-process according to the process sequence;

[0071] S400, if it is determined that the audio component produced by the production sub-process has a production defect, then marking the area determined to have the production defect on the production image data of the audio component as fault area data;

[0072] S500, determining the processing equipment corresponding to the fault area of ​​the defective audio component according to the fault area data, and obtaining the processing error amount of the processing equipment, if the processing error amount of the processing equipment is lower than the preset threshold, then the production processing parameters of the processing equipment are not adjusted; the processing error amount of the processing equipment is the number of times the audio component processed by the processing equipment in the production process of the production sub-process is unqualified; wherein, when it is determined that the processing error amount of the processing equipment is lower than the preset threshold, the processing error amount of the processing equipment is accumulated. The preset threshold can be set in decimal form, for example, 10.5.

[0073] S600, if the processing error amount of the processing equipment is higher than a preset threshold, adjusting the production processing parameters of the processing equipment according to the production image data;

[0074] S700, according to the process sequence, when the production image data of the last production sub-process does not have production defects, a functional test is performed on the final audio product based on the functional testing equipment to determine the integrity of the audio function; wherein the integrity of the audio function refers to whether all the functions of the audio can be used normally.

[0075] S800, if the audio function is complete, the audio is packaged and output;

[0076] S900, if the audio function is not complete, matching the quality event database according to the audio function defect tested by the functional testing equipment to determine the cause of the corresponding function defect and the treatment measures;

[0077] S1000, based on the processing measures, the fault recovery process is performed on the audio device with functional defects, so that the audio device has complete functions, and the corresponding production sub-process is processed according to the fault cause to eliminate the fault cause. The processing measures are used to repair the audio product, and the fault cause is used to eliminate the fault cause of the audio production equipment.

[0078] In this embodiment, during the test of audio production defects, the test is divided into two parts: a structural defect test during the production process and a functional defect test after the production is completed. The structural defect test and the functional defect test are analyzed in a targeted manner to make the production defect test results more accurate. In the structural defect test, the production process is split, and the production results of the audio components of each split production sub-process are imaged. Production defect analysis is performed on the collected production image data to determine whether the audio components produced by the corresponding production sub-process have production defects. If it is determined that the corresponding audio components have production defects, the production sub-process is analyzed according to the defects. The corresponding processing equipment in the process is adjusted, and the production defects in the audio production process are eliminated by automatically adjusting the production and processing parameters of the processing equipment; in the functional defect test, the functional test of the audio that has been produced is carried out by using professional functional testing equipment to determine the functional defects of the corresponding audio products, and then the knowledge graph technology is used to establish the association between the historical functional defects and the corresponding processing methods and the corresponding faulty parts, and then the knowledge graph is matched through the functional defects that have been tested, and then the fault processing method and faulty parts corresponding to the functional defect are determined, making the maintenance process more convenient, while abandoning the talk of experience and improving the accuracy of judgment.

[0079] By dividing the audio test stages and conducting targeted analysis on each stage, the production defect judgment results are made more accurate. When analyzing the structural defects of the audio, the defects are eliminated by analyzing the collected production image data and automatically adjusting the processing equipment corresponding to the defects based on the defects obtained from the analysis, thereby improving the automation level of the test system. When analyzing the functional defects of the audio, the knowledge graph technology is used to match the fault causes and treatment measures for the functional defects obtained from the test, and then the production equipment and audio products are respectively troubleshooted and the audio faults are repaired based on the fault causes and treatment measures, thereby improving the fault handling efficiency.

[0080] For example, in the process of judging the structure of the speaker, there is a production sub-process for welding components a and b, and the production image data ab after welding is obtained. The corresponding process analysis is performed on the production image data ab, that is, whether the welding of a and b is correct, so as to judge whether there is a defect. If it is determined that components a and b have a cold solder joint or are not welded at the specified position, that is, whether there is a corresponding component in the corresponding area, it is determined that the production image data ab has a production defect, and then the corresponding welding equipment is determined according to components a and b, and the welding equipment is self-adjusted according to the defects of components a and b, so that a and b are repaired. In the process of judging the function of the speaker, for example, it is found that the XLR on the back panel has no sound. Through matching, it is found that the cause of the fault is that the PCB board on the XLR seat is welded in the wrong direction, causing +1 and -1 on the PCB board to be on +2 and -2 of the XLR seat. Under normal circumstances, the PCB board and the XLR seat should correspond to +1.-1, so there is no sound. The treatment measure is to re-weld the PCB board, and adjust the welding process of the component according to the cause of the fault to ensure that the subsequent welding is correct.

[0081] In step S200, production defect analysis is performed on the production image data of the audio component to determine whether the audio component produced by each production sub-process has production defects, including the following steps:

[0082] S210, comparing the production image data with the built-in standard image data to determine whether there is a difference in the image data;

[0083] S220, if it is determined that there is a difference between the production image data and the standard image data, then the simulation image data is obtained, and the production image data is compared with the simulation image data to determine whether there is a difference between the production image data and the simulation image data; wherein the simulation image data is: when the first piece of audio is produced, the process sequence of the current production sub-process is obtained, and the image data of the production result of the production sub-process of the previous process sequence is read according to the process sequence, and recorded as the previous production image data; the production processing parameters of each processing equipment in the current production sub-process and the processing type of the corresponding processing equipment are obtained, the parameter information of the audio component to be processed in the current production sub-process is obtained, and the image simulation of the previous production image data is performed according to the production processing parameters, the processing type and the structural parameter information of the audio component to obtain the simulation image data of the current production sub-process. The processing type is the processing function of the processing equipment, such as welding, stamping, cutting, etc. The image simulation is based on 3D modeling technology to determine the position information of each processing equipment during the non-processing process, and then determine the position change of the corresponding processing equipment during the processing process based on the production and processing parameters. Based on the processing type, the expression form of the processing equipment when implementing this function in the 3D model is determined. Finally, based on the structural parameter information of the audio component, the position relationship between the audio component to be processed and the corresponding processing equipment is determined, and then 3D simulation is performed according to the production and processing parameters to obtain the corresponding simulated image data.

[0084] S230, if it is determined that the production image data is the same as the simulation image data, then it is determined that the production sub-process corresponding to the production image data has a defect, that is, a process defect;

[0085] S240, if it is determined that the production image data is different from the simulation image data, then the simulation image data is judged to be different from the standard image data;

[0086] S250, if the simulated image data is the same as the standard image data, it is determined that the production result has defects in the transportation process, that is, a transportation defect; wherein, the transportation defect may be caused by machine vibration, mechanical error and other reasons during the production process, which causes the position of the audio component to be processed to change during the transportation process, thereby causing the processing position of the processing equipment to be different from the position required to be processed when processing the audio component, and then it is determined to be a transportation defect.

[0087] S260, if the simulated image data is different from the standard image data, it is determined that the production result of the corresponding generation sub-process has a defect, that is, the sound component is defective;

[0088] S270: If the production image data is the same as the standard image data, it is determined that there is no production defect in the production image data.

[0089] In this embodiment, when making structural judgments in the audio production process, the production image data is compared with the standard image data for the first time to determine whether the production result is qualified, and the production image data is compared with the simulation image data for the second time to determine the problem of the unqualified production result. By comparing the production image data, the standard image data and the simulation image data, not only the qualification of the production result but also the reason for the unqualified production result is determined, thereby improving the test efficiency. At the same time, since the simulation image data is the result of simulating the image data of the production result of the previous production sub-process through the processing equipment function of the current production sub-process, the simulation image data is more ideal and standardized, and the simulation image data can feedback the correctness of the current production sub-process, thereby improving the accuracy of production defect judgment.

[0090] Exemplarily, since the standard image data represents the qualification of the production result, and the simulation image data is obtained by simulating the function of the processing equipment of the production sub-process and the parameters of the corresponding processing equipment, and represents the ideal result of the production sub-process, when the production image data is different from the standard image data, it indicates that the production result of the production sub-process is unqualified. The production image data is compared with the simulation image data to determine whether the production sub-process is correct. When the production image data is the same as the simulation image data, it indicates that the simulation image data is different from the standard image data, which further indicates that the production result of the production sub-process under the ideal state is also unqualified, and then it is determined that the production sub-process itself is unqualified, that is, there is a process problem. When the production image data is different from the simulation image data, it is necessary to judge the simulation image data and the standard image data. When the simulation image data is the same as the standard image data, it indicates that the production process is qualified, but the actual production result is unqualified, and then it is determined that there is a problem in the transportation process of the processed audio component, resulting in an error. When the simulation image data is different from the standard image data, it indicates that there are problems in both the production process and the production process, and then it is determined that there is a problem with the audio component to be processed.

[0091] In step S600, if the processing error amount of the processing equipment is higher than a preset threshold, the production processing parameters of the processing equipment are adjusted according to the production image data, including the following steps:

[0092] S611, obtaining a defect type corresponding to the production image data. If the defect type of the production image data is a process defect, obtaining processing category information of the processing equipment corresponding to the fault area, and determining whether the production processing parameters of the processing equipment can be automatically adjusted according to the processing category information;

[0093] S612, determining, based on the processing category information, processing data items that can directly affect the processing equipment in implementing corresponding functions;

[0094] S613, based on the historical production image data of the corresponding production sub-process, obtaining the evaluation parameter value of the processing effect diagram of the corresponding processing equipment and the numerical value of the corresponding processing data item, and performing a linear judgment on the evaluation parameter value of the processing effect diagram and the numerical value of the processing data item to determine whether there is a linear relationship between the processing effect and the processing data item;

[0095] S614, if the processing effect has a linear relationship with the processing data item, it is determined that the processing equipment can be automatically adjusted, the production image data and the standard image data are compared to determine the correction data, and the production processing parameters of the processing equipment are adjusted according to the correction data;

[0096] S615, if the processing effect and the processing data item do not have a linear relationship, the production image data are compared with the standard image data to determine the fault category of the fault area on the production image data; the fault category includes functional correctness and positional correctness; wherein, functional correctness means that the processing effect of the processing equipment on the audio component is qualified, and positional correctness means that the processing position of the processing equipment on the audio component is correct.

[0097] S616, if the fault category is functional correctness, but the position is not correct, the production image data and the standard image data are compared to determine correction data, and the production processing parameters of the processing equipment are adjusted according to the correction data;

[0098] S617: If the fault category is that the function is not correct, an alarm signal of the production sub-process is output.

[0099] In this embodiment, during the process of automatically adjusting the production and processing parameters of the processing equipment, since different defect types correspond to different processing methods, the fault type is accurately analyzed and processed to ensure that the processing result is more accurate and effective.

[0100] When the defect type of the production image data is determined to be a process problem, by determining whether there is a linear relationship between the processing effect of the processing equipment and the processing data item, it is determined whether the processing equipment can automatically correct the production processing parameters to reduce the number of manual maintenance times. When it is determined that there is a linear relationship between the processing effect and the processing data item, it indicates that the processing equipment can be automatically corrected. Therefore, the correction data of the processing equipment is determined by comparing the production image data and the standard image data. When it is determined that there is no linear relationship between the processing effect and the processing data item, it indicates that the processing equipment cannot be automatically corrected. Therefore, it is necessary to determine the fault category of the fault area for the production image data and the standard image data, and then determine whether the fault is related to the function of the processing equipment through the fault category. If the fault category is incorrect position, it indicates that the functional result after processing is qualified, but the position is unqualified, so only the processing position of the processing equipment needs to be adjusted to achieve the adjustment effect. Conversely, if the fault category is incorrect function, it indicates that the processing effect of the processing equipment is unqualified, and since there is no linear relationship between the processing effect and the processing data item, manual adjustment is required to reduce the error rate of automatic adjustment.

[0101] For example, when welding components, if pressure welding is used, since there is no linear relationship between the pressure value and the welding effect, the fault category is determined by comparing the production image data and the standard image data. If the fault category of the production image data is poor processing effect, which leads to poor welding effect, it is necessary to adjust the pressure of the processing equipment. Since there is no linear relationship between the pressure value and the welding effect, manual adjustment is required. If the fault category of the production image data is incorrect processing position, it is only necessary to determine the deviation of the corresponding displacement through comparison so that the processing equipment can process the correct position.

[0102] In step S600, if the processing error amount of the processing equipment is higher than a preset threshold, the production processing parameters of the processing equipment are adjusted according to the production image data, including the following steps:

[0103] S621, if the defect type of the production image data is a handling defect, compare the production image data with the standard image data to determine the position offset data of the audio component corresponding to the fault area after processing;

[0104] S622, obtaining the number of handling equipment located before the processing equipment performs processing in the production sub-process, recorded as the number of front handling equipment, and obtaining the number of handling equipment located after the processing equipment performs processing in the production sub-process, recorded as the number of rear handling equipment;

[0105] S623, numbering the front transport equipment and the rear transport equipment according to the position distance between the transport equipment and the processing equipment, recording the number of the front transport equipment closest to the processing equipment as the first front transport equipment, recording the number of the rear transport equipment closest to the processing equipment as the first rear transport equipment, and so on, to obtain the numbering data of the corresponding front transport equipment and the numbering data of the rear transport equipment;

[0106] S624, based on the numbering sequence of the numbering data of the front transporting equipment, comparing the adjustable displacement data of the first front transporting equipment with the position offset data to determine whether the adjustable displacement data of the first front transporting equipment is greater than or equal to the position offset data;

[0107] S625, if it is determined that the adjustable displacement data of the first front transport device is greater than or equal to the position offset data, then the transport device is adjusted according to the position offset data;

[0108] S626, if it is determined that the adjustable displacement data of the first front handling device is less than the position offset data, then the subsequent multiple front handling devices are jointly mobilized one by one according to the number and number data of the front handling devices, and the number of the jointly mobilized handling devices is compared with the number of the front handling devices. If the number of the jointly mobilized handling devices is less than or equal to the number of the front handling devices, the jointly mobilized adjustable displacement data is adjusted until the jointly mobilized adjustable displacement data is greater than or equal to the position offset data; if the number of the jointly mobilized handling devices is greater than the number of the front handling devices, an alarm is output for the current production sub-process;

[0109] S627, similarly, compare the adjustable data of the first rear transport device of the current processing device to schedule and adjust the rear transport device according to the position offset data.

[0110] In this embodiment, when it is determined that the defect type of the production image data is a handling problem, the corresponding position offset data is determined through the production image data and the standard image data, and then the number of handling equipment that can be used for handling displacement adjustment is determined through the position of the processing equipment corresponding to the fault area. The adjustable data is judged by the first front handling equipment corresponding to the current processing equipment to determine whether the adjustment requirements of the position offset data can be met. If so, corresponding adjustments are made. If not, the position offset data is adjusted by gradually increasing the number of handling equipment for position offset adjustment. By gradually increasing the number of handling equipment, the impact on other processing equipment during the adjustment process is reduced, thereby improving the efficiency and effectiveness of the adjustment.

[0111] For example, if the position offset data is a, and the adjustable data of the handling equipment B corresponding to the current processing equipment is b, when a>b, it indicates that the current handling equipment cannot correct the position offset data, so other handling equipment needs to be scheduled. For example, the adjustable data of the handling equipment C located before the current handling equipment B is c, so the comprehensive adjustable data of the current handling equipment B and the handling equipment C located before the current handling equipment is b+c, and when b+c>a, the position offset data is corrected by simultaneously scheduling the handling equipment B and the handling equipment C.

[0112] In step S600, if the processing error amount of the processing equipment is higher than a preset threshold, the production processing parameters of the processing equipment are adjusted according to the production image data, including the following steps:

[0113] S631, if the defect type of the production image data is an audio component defect, the production image data of the previous production sub-process is obtained according to the process sequence and recorded as the previous production image data;

[0114] S632, based on the functions of each processing equipment in the current production sub-process, the production image data is de-processed to obtain image data before processing and recorded as pre-processed image data; wherein, the de-processing is to eliminate only the processing traces of the production sub-process that already exist in the production image data. For example: in the process of processing glass, the current production sub-process is used to punch holes in the glass, and the image data of the glass entering the production sub-process is a complete glass image, and after processing, the image data obtained is an image with processing traces such as punching, and punching is the function of the process. When de-processing is performed, only the punching in the image with processing traces such as punching is eliminated, and glass fragments, scratches, cracks, etc. caused by the processing are not eliminated.

[0115] S633, comparing the previous production image data and the pre-processed image data based on the fault area data of the current production image data to determine whether the image data of the previous production image data and the image data of the pre-processed image data on the fault area are the same;

[0116] S634, if it is determined that the image data on the fault area is different, the current production sub-process is marked;

[0117] S635, if it is determined that the image data on the faulty area is the same, then the production image data of the production sub-process flow located before the current production sub-process flow sequence is matched according to the previous production image data, so as to trace the production sub-process where the device fails, and mark the corresponding production sub-process;

[0118] S636, output an alarm for the marked production sub-process.

[0119] In this embodiment, when the defect type is determined to be a device problem, the production graphic data of the current production sub-process is processed to obtain pre-processed image data of the production sub-process. The pre-processed image data is used as reference data, and the production image data of the previous production sub-process is compared with the pre-processed image data to determine whether the problem with the current production result is caused by the current production sub-process. If the image data on the fault area are different, it indicates that the fault occurred in the current production sub-process. If the image data on the fault area are the same, it indicates that the fault already existed in the previous production sub-process. Therefore, it is necessary to re-judge the previous production sub-process to trace back to the production sub-process that ultimately caused the device failure.

[0120] By de-processing the production image data of the current sub-process to determine the simulated input state of the current production sub-process under actual conditions, the comparison result of the pre-processed image data with the production image data of the previous production sub-process is more accurate. By comparing the changes between the actual input state and the simulated input state, it is possible to quickly determine whether the production result problem of the current process is caused by the processing of the device by the current production sub-process, and then quickly determine the source of the problem in the production result, thereby improving the judgment efficiency.

[0121] Exemplarily, for example, for welding of a PCB board, the production image data of the previous production sub-process is recorded as image data A, and the production image data of the current production sub-process is recorded as image data B, that is, image data A is input into the current production sub-process for processing to obtain image data B, and image data C is obtained by de-processing image data B. If the current production sub-process does not damage the PCB board after processing, the de-processed image data C obtained is the same as the input image data A. Similarly, when image data C is different from image data A, it indicates that the current production sub-process damages the PCB board during processing.

[0122] In step S900, if the audio function is not complete, the quality event database is matched according to the audio function defect tested by the function test equipment to determine the cause of the corresponding function defect and the treatment measures, including the following steps:

[0123] S910, collecting statistics on historical fault handling records to obtain a sound quality event database;

[0124] S920, matching the audio quality event database based on the knowledge graph technology to obtain a fault relationship including a correlation relationship between a problem description, a defect problem, a fault cause, and a treatment measure;

[0125] S930, matching the functional defects of the audio system based on the fault relationship to determine the fault cause of the corresponding functional defect and the component information of the corresponding functional defect;

[0126] S940, rematching the fault relationship based on the component information of the corresponding functional defect and the fault cause to determine the processing measures of the corresponding component when the fault cause occurs.

[0127] In this embodiment, historical fault handling records are collected for statistics to facilitate the search and use of fault information, and a quality event database is modeled using knowledge graph technology to clarify the relationships between quality events. The fault relationships are then matched based on the functional defects of the audio obtained from the test to determine the fault causes and component information corresponding to the functional defects. The fault relationships are then matched based on the component information and the fault causes to further narrow down the treatment measures for the corresponding functional faults, thereby improving the accuracy and effectiveness of the matched treatment measures.

[0128] For example, if there is no sound from the XLR on the back panel, through matching, it is found that the fault is caused by the wrong direction of soldering the PCB board on the XLR socket, causing +1 and -1 on the PCB board to be on +2 and -2 of the XLR socket. Normally, the PCB board and the XLR socket should correspond to +1 and -1, so there is no sound. The treatment measure is to re-solder the PCB board, and adjust the welding process of the component according to the cause of the fault to ensure that subsequent welding is correct.

[0129] Based on the description of the above-mentioned embodiment of the intelligent testing method for acoustic production defects, the embodiment of the present invention further discloses an intelligent testing system for acoustic production defects:

[0130] like Figure 2 As shown, an intelligent testing system for audio production defects, by applying the above-mentioned intelligent testing method for audio production defects, includes: an image acquisition module 1, an image analysis module 2, a structural defect processing module 3, a functional defect analysis module 4, and a functional defect processing module 5.

[0131] Image acquisition module 1, obtains the production process of the audio system and splits the production process to obtain production sub-processes with a process sequence, and performs image acquisition on the production results of the audio components of the production sub-processes to obtain production image data of the audio components of the corresponding production sub-processes;

[0132] Image analysis module 2, performing production defect analysis on the production image data of the audio component to determine whether the audio component produced by each production sub-process has production defects;

[0133] Structural defect processing module 3, if it is determined that the audio component produced by the production sub-process does not have production defects, the audio component of the production sub-process is moved to the next production sub-process according to the process sequence; if it is determined that the audio component produced by the production sub-process has production defects, the area where the production defects are determined to exist on the production image data of the audio component is marked as fault area data; the processing equipment corresponding to the fault area of ​​the audio component with production defects is determined according to the fault area data, and the processing error amount of the processing equipment is obtained, and if the processing error amount of the processing equipment is lower than the preset threshold, the production processing parameters of the processing equipment are not adjusted; the processing error amount of the processing equipment is the number of times the audio component processed by the processing equipment during the production process of the production sub-process is unqualified; if the processing error amount of the processing equipment is higher than the preset threshold, the production processing parameters of the processing equipment are adjusted according to the production image data;

[0134] Functional defect analysis module 4, according to the process sequence, when the production image data of the last production sub-process does not have production defects, the functional test of the final audio product is performed based on the functional test equipment to determine the integrity of the audio function;

[0135] Function defect processing module 5, if the audio function is complete, the audio is packaged and output; if the audio function is not complete, the quality event database is matched according to the audio function defect tested by the functional testing equipment to determine the cause of the corresponding functional defect and the treatment measures; based on the treatment measures, the audio with the current functional defect is subjected to fault recovery processing to make the audio function complete, and the corresponding production sub-process is processed according to the cause of the fault to eliminate the cause of the fault.

[0136] Compared with the existing intelligent testing method and system for acoustic production defects, the present invention improves the efficiency of defect testing.

[0137] The above are all preferred embodiments of the present application, and the protection scope of the present application is not limited thereto. Therefore, any equivalent changes made according to the structure, shape, and principle of the present application should be included in the protection scope of the present application.

Claims

1. An intelligent testing method for acoustic production defects, characterized in that: include: Acquire the production process of the audio system and split the production process to obtain production sub-processes with a process sequence, and collect images of the production results of the audio components of the production sub-processes to obtain production image data of the audio components of the corresponding production sub-processes; Performing production defect analysis on production image data of the audio component to determine whether the audio component produced by each production sub-process has production defects; Compare the production image data with the built-in standard image data to determine whether there are any differences in the image data; If it is determined that there is a difference between the production image data and the standard image data, obtaining the simulated image data, and comparing the production image data with the simulated image data to determine whether there is a difference between the production image data and the simulated image data; If it is determined that the production image data is the same as the simulation image data, then it is determined that the production sub-process corresponding to the production image data has a defect, that is, a process defect; If it is determined that the production image data is different from the simulation image data, the simulation image data is compared with the standard image data for difference determination; If the simulated image data is the same as the standard image data, it is determined that the production result has defects in the handling process, that is, handling defects; If the simulated image data is different from the standard image data, it is determined that the production result of the corresponding generation sub-process is defective, that is, the audio component is defective; If the production image data is the same as the standard image data, it is determined that the production image data does not have a production defect; If it is determined that the sound component produced by the production sub-process does not have a production defect, the sound component of the production sub-process is moved to the next production sub-process according to the process sequence; If it is determined that the audio component produced by the production sub-process has a production defect, then marking the area determined to have the production defect on the production image data of the audio component as fault area data; Determine the processing equipment corresponding to the fault area of ​​the audio component with defects in production according to the fault area data, and obtain the processing error amount of the processing equipment. If the processing error amount of the processing equipment is lower than a preset threshold, do not adjust the production processing parameters of the processing equipment; the processing error amount of the processing equipment is the number of times the audio component processed by the processing equipment in the production process of the production sub-process is unqualified; If the processing error amount of the processing equipment is higher than a preset threshold, adjusting the production processing parameters of the processing equipment according to the production image data; According to the process sequence, when the production image data of the last production sub-process does not contain production defects, the functional test of the final audio product is performed based on the functional test equipment to determine the integrity of the audio function; If the audio function is complete, the audio is packaged and output; If the audio function is not complete, the quality event database is matched according to the audio function defects tested by the functional testing equipment to determine the cause of the corresponding functional defects and the treatment measures; Based on the processing measures, the audio system with functional defects is restored to its original state so that the audio system has complete functions. The corresponding production sub-process is processed according to the cause of the fault to eliminate the cause of the fault.

2. The intelligent testing method for acoustic production defects according to claim 1, characterized in that: The acquiring of the simulated image data is specifically as follows: When the first piece of audio equipment is produced, the process sequence of the current production sub-process is obtained, and the image data of the production result of the production sub-process of the previous process sequence is read according to the process sequence, and recorded as the previous production image data; Obtain the production and processing parameters of each processing equipment in the current production sub-process and the processing type of the corresponding processing equipment, obtain the parameter information of the audio components that need to be processed in the current production sub-process, and perform image simulation on the previous production image data according to the production and processing parameters, processing type and structural parameter information of the audio components to obtain the simulated image data of the current production sub-process.

3. The intelligent testing method for acoustic production defects according to claim 2 is characterized by: If the processing error amount of the processing equipment is higher than the preset threshold, the production processing parameters of the processing equipment are adjusted according to the production image data, specifically: Obtaining the defect type corresponding to the production image data. If the defect type of the production image data is a process defect, obtaining the processing category information of the processing equipment corresponding to the fault area, and determining whether the production processing parameters of the processing equipment can be automatically adjusted according to the processing category information; Determine, based on the processing category information, processing data items that can directly affect the implementation of corresponding functions of the processing equipment; Based on the historical production image data of the corresponding production sub-process, the evaluation parameter value of the processing effect diagram of the corresponding processing equipment and the numerical value of the corresponding processing data item are obtained, and the evaluation parameter value of the processing effect diagram and the numerical value of the processing data item are linearly judged to determine whether there is a linear relationship between the processing effect and the processing data item; If the processing effect has a linear relationship with the processing data item, it is determined that the processing equipment can be automatically adjusted, the production image data and the standard image data are compared to determine the correction data, and the production processing parameters of the processing equipment are adjusted according to the correction data; If the processing effect does not have a linear relationship with the processing data item, the production image data is compared with the standard image data to determine the fault category of the fault area on the production image data; the fault category includes functional correctness and position correctness; If the fault category is functional correctness, but the position is not correct, the production image data and the standard image data are compared to determine correction data, and the production processing parameters of the processing equipment are adjusted according to the correction data; If the fault category is that the function is not correct, an alarm signal for the production sub-process is output.

4. The intelligent testing method for acoustic production defects according to claim 3 is characterized by: If the processing error amount of the processing equipment is higher than a preset threshold, adjusting the production processing parameters of the processing equipment according to the production image data also includes: If the defect type of the production image data is a handling defect, the production image data is compared with the standard image data to determine the position offset data of the audio component after processing in the corresponding fault area; Obtain the number of handling equipment located before the processing equipment in the production sub-process, recorded as the number of front handling equipment, and obtain the number of handling equipment located after the processing equipment in the production sub-process, recorded as the number of rear handling equipment; The front transport equipment and the rear transport equipment are numbered according to the position distance between the transport equipment and the processing equipment, and the number of the front transport equipment closest to the processing equipment is recorded as the first front transport equipment, and the number of the rear transport equipment closest to the processing equipment is recorded as the first rear transport equipment, and so on, to obtain the numbering data of the corresponding front transport equipment and the numbering data of the rear transport equipment; Based on the numbering sequence of the numbering data of the front transporting devices, the adjustable displacement data of the first front transporting device is compared with the position offset data to determine whether the adjustable displacement data of the first front transporting device is greater than or equal to the position offset data; If it is determined that the adjustable displacement data of the first front transport device is greater than or equal to the position offset data, then the transport device is adjusted according to the position offset data; If it is determined that the adjustable displacement data of the first front handling equipment is less than the position offset data, then the subsequent multiple front handling equipment are jointly mobilized one by one according to the number and number data of the front handling equipment, and the number of jointly mobilized handling equipment is compared with the number of front handling equipment. If the number of jointly mobilized handling equipment is less than or equal to the number of front handling equipment, the jointly mobilized adjustable displacement data is adjusted until the jointly mobilized adjustable displacement data is greater than or equal to the position offset data; if the number of jointly mobilized handling equipment is greater than the number of front handling equipment, an alarm is output for the current production sub-process; Similarly, the adjustable data comparison is performed on the first rear transport device of the current processing device, so as to schedule and adjust the rear transport device according to the position offset data.

5. The intelligent testing method for acoustic production defects according to claim 4 is characterized by: If the processing error amount of the processing equipment is higher than a preset threshold, adjusting the production processing parameters of the processing equipment according to the production image data also includes: If the defect type of the production image data is an audio component defect, the production image data of the previous production sub-process is obtained according to the process sequence and recorded as the previous production image data; De-processing the production image data based on the functions of each processing equipment in the current production sub-process to obtain image data before processing and record it as pre-processed image data; Comparing the previous production image data and the pre-processed image data based on the fault area data of the current production image data to determine whether the image data of the previous production image data and the image data of the pre-processed image data on the fault area are the same; If it is determined that the image data on the faulty area is different, the current production sub-process is marked; If it is determined that the image data on the faulty area are the same, the production image data of the production sub-process flow preceding the current production sub-process flow sequence is matched according to the previous production image data, so as to trace the production sub-process where the device fails, and mark the corresponding production sub-process; Output alarm for marked production sub-process.

6. The intelligent testing method for acoustic production defects according to claim 1 is characterized by: If the audio function is not complete, the quality event database is matched according to the audio function defects tested by the functional testing equipment to determine the cause of the corresponding functional defects and the treatment measures, specifically: Collect statistics on historical fault handling records to obtain the audio quality event database; Based on the knowledge graph technology, the quality event database of the audio system is matched to obtain the fault relationship including the correlation between the problem description, defect problem, fault cause and treatment measures; Matching the functional defects of the audio system based on the fault relationship to determine the fault cause of the corresponding functional defect and the component information of the corresponding functional defect; The fault relationship is re-matched based on the component information of the corresponding functional defect and the fault cause to determine the treatment measures for the corresponding component when the fault cause occurs.

7. An intelligent testing system for acoustic production defects, characterized in that: The system is used to implement an intelligent testing method for acoustic production defects as described in any one of claims 1 to 6: comprising: an image acquisition module, an image analysis module, a structural defect processing module, a functional defect analysis module, and a functional defect processing module; The image acquisition module acquires the production process of the audio system and splits the production process to obtain production sub-processes with a process sequence, and performs image acquisition on the production results of the audio components of the production sub-processes to obtain production image data of the audio components of the corresponding production sub-processes; The image analysis module performs production defect analysis on the production image data of the audio component to determine whether the audio component produced by each production sub-process has production defects; The structural defect processing module, if it is determined that the audio component produced by the production sub-process does not have a production defect, then the audio component of the production sub-process is moved to the next production sub-process according to the process sequence; if it is determined that the audio component produced by the production sub-process has a production defect, the area determined to have a production defect on the production image data of the audio component is marked as fault area data; the processing equipment corresponding to the fault area of ​​the audio component with production defects is determined according to the fault area data, and the processing error amount of the processing equipment is obtained, and if the processing error amount of the processing equipment is lower than a preset threshold, the production processing parameters of the processing equipment are not adjusted; the processing error amount of the processing equipment is the number of times the audio component processed by the processing equipment during the production process of the production sub-process is unqualified; if the processing error amount of the processing equipment is higher than the preset threshold, the production processing parameters of the processing equipment are adjusted according to the production image data; The functional defect analysis module, according to the process sequence, performs a functional test on the final audio product based on the functional testing equipment to determine the integrity of the audio function when the production image data of the last production sub-process does not have a production defect; The functional defect processing module packages and outputs the audio if the audio function is complete; if the audio function is not complete, the quality event database is matched according to the audio function defect tested by the functional testing equipment to determine the cause of the corresponding functional defect and the treatment measures; based on the treatment measures, the audio currently having the functional defect is subjected to fault recovery processing to make the audio function complete, and the corresponding production sub-process is processed according to the cause of the fault to eliminate the cause of the fault.

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