A product production detection system based on big data

Abstract

The present invention discloses a product production inspection system based on big data, which relates to big data product production inspection technology, including a product data inspection module, a product qualification database, a big data platform, an inspection and analysis execution module, an internal and external analysis module and an operation analysis module; the existing product production inspection system based on big data is a comprehensive system that integrates modern information technology, sensor technology, artificial intelligence and other technologies; there are problems such as failure to timely discover and solve potential quality problems, the existence of products that do not require internal inspection, but still carry out the inspection, resulting in low inspection efficiency, and the problem that only one product can be inspected. The inspection and analysis execution module, the internal and external analysis module and the operation analysis module of the present invention perform monitoring and analysis, solve the problem of directly skipping this step for products that do not require internal inspection, improve inspection efficiency, achieve optimal allocation of inspection resources, and improve overall inspection efficiency.

Description

Technical Field

[0001] The present invention relates to a big data product production detection technology, and in particular to a product production detection system based on big data. Background Art

[0002] The product production inspection system is a comprehensive system that integrates modern information technology, sensor technology, artificial intelligence (AI), etc. The system collects, stores, analyzes and mines massive data in the product production process to achieve real-time monitoring and early warning of product quality.

[0003] However, there are still some problems with the product inspection system, including the inability to promptly detect and resolve potential product quality problems and the inability to filter out products that do not require internal inspection, resulting in the continued inspection of products that do not require internal inspection, causing waste of resources and low inspection efficiency. There is also the problem of only being able to inspect one product. Summary of the invention

[0004] The purpose of the present invention is to propose a product production inspection system based on big data in order to solve the problems of not being able to discover and solve potential quality problems in time, the existence of products that do not need internal inspection but still undergo inspection, resulting in low inspection efficiency, and the problem of only being able to inspect one product.

[0005] The object of the present invention can be achieved by the following technical solutions: A product production inspection system based on big data, including a big data platform, a product qualification database, a detection and analysis execution module, an internal and external analysis module, and an operation analysis module;

[0006] The detection and analysis execution module is used to perform detection data analysis on the received data information, obtain the product category of the product, obtain the detection standard data, detection application scenarios and test cases of the corresponding type of product from the product qualification database and the big data platform for analysis;

[0007] The internal and external analysis module is used to analyze the inside and outside of the product, by obtaining product appearance data, and inspecting and analyzing the product size and shape information to generate a shape difference signal or a combination signal; then inspecting and analyzing the product surface quality by obtaining the product surface quality situation to obtain the product surface quality value, and compare it with the preset surface quality threshold to generate a surface quality difference signal; when inspecting and analyzing the product coating identification information, the coating identification content is obtained through an industrial high-definition camera, and then the corresponding preset size and shape are compared with the product size and shape to generate a coating identification difference signal; the inside of the product is inspected and analyzed, by obtaining the product category, and then whether internal inspection is required based on the product category. If internal inspection is required, the internal parts information and assembly information of the product are obtained for inspection and analysis, and the obtained parts information and assembly information are compared with the preset internal qualified data to generate a zero difference signal or an assembly difference signal;

[0008] The operation analysis module performs operation analysis on the product, obtains product operation data, including performance detection information and status monitoring information, obtains detection standard data, detection application scenarios and test cases corresponding to product categories through the product qualification database; monitors and analyzes product detection application scenarios, obtains scene environment data through environmental scene equipment, assigns scene environment data, and then obtains scene values ​​through calculation, matches the scene values ​​with preset detection application scenario intervals, and generates scene difference signals; analyzes and executes product status monitoring, obtains status monitoring information, including operation and usage monitoring and fault and abnormality monitoring, and analyzes and generates operation difference signals.

[0009] As a preferred embodiment of the present invention, it also includes a product data inspection module, a big data platform and a product qualification database;

[0010] The product data acquisition module is used to collect product categories and product appearance data, product internal data, product operation data, product assembly data and environmental data;

[0011] The big data platform and product qualification database are used to provide testing standard data, testing application scenarios and test cases for product types.

[0012] As a preferred embodiment of the present invention, the internal and external analysis module performs inspection and analysis on the product size and shape information, and the specific process is as follows:

[0013] The size and shape of the product are obtained by a 3D scanner, and the speaker is scanned by a mesh beam of the 3D scanner to obtain the deformation of the mesh beam, and then the deformation of the mesh beam is imported into the computer 3D model to obtain the shape of the product; and the obtained product shape is compared with the preset product by scaling and overlapping; if the product does not match the preset product, a shape difference signal is generated; otherwise, a combination signal 1 is generated; the product size is proportionally converted according to the size of the scanner monitoring platform on the 3D scanner; the obtained product size is compared with the preset product size; if the product size is not equal to the preset product size, a corresponding size difference signal is generated; otherwise, a combination signal 2 is generated; when the combination signal 1 and the combination signal 2 are generated at the same time, the surface quality of the product is inspected and analyzed, specifically:

[0014] The surface quality of the product is obtained through an industrial high-definition camera. The surface flatness is measured by lateral illumination. The shadow area of ​​the illuminated area is collected by the industrial high-definition camera, and the shadow color depth is compared with the preset shadow color depth threshold. If the shadow color depth is greater than the preset shadow color depth threshold, it is marked as a valid shadow area; otherwise, it is an invalid shadow area. The surface flatness of the product is obtained by converting the effective shadow area at a certain ratio. The number and degree of scratches, cracks, pits and bubbles on the surface are directly obtained through the industrial high-definition camera. The surface defect data is then assigned to the The surface finish of the product is obtained by computer weighted calculation; the surface finish is illuminated from the side, and the reflected brightness is collected by an industrial high-definition camera, and then the surface finish of the product is converted according to a certain ratio with the reflected brightness; the surface finish, surface defect value and surface flatness of the product are substituted into the computer model to obtain the model volume in the product surface quality map, and the model volume value in the map is used as the product surface quality value; then the product surface quality value is compared with the preset surface quality threshold. If the product surface quality value is greater than the preset surface quality threshold, a surface quality difference signal is generated; otherwise, the product coating identification information is inspected and analyzed, specifically:

[0015] The coating identification content is obtained through an industrial high-definition camera and the product size and shape is obtained based on a three-dimensional scanner; then the coating identification content is identified to obtain the corresponding preset size and shape; the corresponding preset size and shape are compared with the product size and shape; if the preset size and shape of the coating identification content does not match the product size and shape, a coating identification difference signal is generated; otherwise, the inside of the product is detected and analyzed to obtain a zero difference signal and an installation difference signal.

[0016] As a preferred implementation of the present invention, the operation analysis module monitors and analyzes the product detection application scenario, specifically:

[0017] The scene environment data is obtained through the environmental scene equipment, including the environmental noise intensity level, noise source type, particle concentration and airflow data; the noise source type includes continuous noise and instantaneous noise; the airflow data includes wind speed and wind direction; the noise source types continuous noise and instantaneous noise are assigned as noise class value one and noise class value two, respectively, collectively referred to as noise class values; the environmental noise intensity level is marked as a noise value according to the noise intensity; the wind direction in the airflow data is assigned as a wind direction value according to the direction; then a detection application scenario model is established, and the acquired data is substituted into the detection application scenario model to obtain the line segment length, and the line segment length is used as the scene value, and the scene value is matched with the preset detection application scenario interval. If the scene value belongs to the preset detection application scenario interval, the mechanical properties of the product are tested and analyzed, and performance detection information is obtained, including acoustic performance test information, electrical performance test information and mechanical performance test information; otherwise, a scene difference signal is generated.

[0018] As a preferred implementation of the present invention, the operation analysis module analyzes the product status monitoring, specifically:

[0019] The operation and usage monitoring includes audio signal characteristics, usage time and user operation records; the audio signal characteristics are assigned to frequency characteristics according to the frequency, amplitude and waveform characteristics of the audio signal; the usage time is marked as cumulative time value and continuous time value according to the cumulative usage time and continuous usage time of the speaker; the user operation record divides the sound effect setting into several preset sound effect intervals according to the obtained speaker volume and sound effect settings, obtains the sound effect setting as a certain interval of several preset sound effect intervals, and assigns it to the sound effect value; substitutes the data into the calculation model to obtain the operation value, and matches it with the preset operation interval; if the operation value belongs to the preset operation interval, the product fault and abnormal monitoring are recorded and displayed, specifically: by obtaining fault and abnormal monitoring data, including fault display and alarm mechanism; the fault display obtains various difference signals, counts the occurrence frequency, calculates the product qualification rate, and compares it with the preset corresponding product qualification rate; if the product qualification rate is less than the preset corresponding product qualification rate, an alarm is issued; otherwise, no alarm is issued; the alarm reminds the inspection personnel to make adjustments; otherwise, an operation difference signal is generated.

[0020] Compared with the prior art, the present invention has the following beneficial effects:

[0021] 1. The present invention analyzes the inside and outside of the product through the internal and external analysis module. Through advanced equipment such as 3D scanners and industrial high-definition cameras, the size and shape information of the product can be accurately captured and compared with the preset data. This precise data comparison helps to ensure the accuracy of product size and shape, thereby improving the consistency and stability of product quality. Industrial high-definition cameras can not only detect surface flatness, defects and smoothness, but also integrate these data into the 3D coordinate system model to generate an intuitive product surface quality map. Comprehensive surface quality analysis provides production personnel with a detailed basis for quality assessment, which helps to promptly discover and solve potential quality problems.

[0022] 2. The present invention verifies the coating identification information through internal and external analysis modules to ensure the consistency between the product and its coating identification content, thereby enhancing consumers' trust and satisfaction with the product. Flexible internal detection mechanism, the internal detection mechanism can be flexibly adjusted according to different product categories. For products that require internal detection, the internal parts information and assembly information obtained by the X-ray internal scanner can be compared with the preset internal qualified data to ensure the internal quality of the product. For products that do not require internal detection, this step is skipped directly, which improves detection efficiency, helps to achieve the optimal allocation of detection resources, and improves overall detection efficiency.

[0023] 3. The present invention performs operation analysis on the product through the operation analysis module. Based on the product operation data collected by the product data acquisition module, combined with the detection standard data, detection application scenarios and test cases in the product qualification database, a comprehensive analysis of the product performance can be performed. Accurate data analysis ensures the stability and reliability of the product in various application scenarios. By establishing a detection application scenario model and substituting the data obtained by the environmental scene equipment into the model, the product scene inspection map can be obtained, thereby evaluating the adaptability of the product under different environmental conditions. Flexible detection application scenario models help ensure that the product can maintain excellent performance in various complex environments.

[0024] 4. The present invention performs operation analysis on the product through the operation analysis module, and conducts comprehensive testing and analysis on the acoustic performance, electrical performance and mechanical performance of the product to ensure that the performance of the product in all aspects meets the preset standards; comprehensive performance testing helps to improve the overall quality of the product. The operation and use of the product are monitored in real time, and faults and anomalies are recorded and displayed, so that problems can be discovered and solved in time. At the same time, when the product qualification rate is lower than the preset value, the alarm mechanism will be automatically triggered to remind the inspection personnel to make adjustments; the real-time status monitoring and fault alarm mechanism ensures the stability and reliability of the product and increases the service life of the product. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0026] Figure 1 It is a principle block diagram of the present invention;

[0027] Figure 2 This is a surface quality diagram of the product of the present invention;

[0028] Figure 3 Check the pictures for the products of the present invention;

[0029] Figure 4 This is a product operation monitoring diagram of the present invention. DETAILED DESCRIPTION

[0030] The technical scheme of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0031] See also Figure 1 As shown, a product production and testing system based on big data includes a product data inspection and acquisition module, a product qualification database, a big data platform, a detection and analysis execution module, an internal and external analysis module, and an operation analysis module;

[0032] The product data inspection module is used to collect product categories and product appearance data, product internal data, product operation data, product assembly data and environmental data; the product categories are mainly mobile phones, headphones and tablet spare parts including display components, batteries, connecting parts, microphones, speakers and peripherals, etc.; product appearance data includes size and shape information, surface quality information and coating identification information; product internal data includes internal quality control information, internal material list information and production equipment parameter information; product operation data includes performance test information and status monitoring information; product assembly data includes assembly process information, parts inspection information, size and tolerance information and connection and fastening data;

[0033] The product data inspection module is also used to identify the product. After the product appearance is collected by the identification camera, it is analyzed to obtain the corresponding product category. Specifically, the product picture is obtained, and the product picture is analyzed according to the contrast and similarity of two pixels in the picture. The contrast and similarity thresholds are preset, marked as the contrast threshold and the similarity threshold, and compared with the contrast and similarity of the two pixels; if the contrast is less than the contrast threshold and the similarity is greater than the similarity threshold, the two pixels are marked as the same color; otherwise, they are different colors, and then the pixel area of ​​the enclosure is obtained by connecting two different pixels, and the preset product category parts or equipment shapes are compared with the pixel area of ​​the enclosure to obtain the product category;

[0034] The product data inspection and collection module then sends the collected data information to the detection and analysis execution module;

[0035] The detection and analysis execution module is used to perform detection data analysis on the received data information by obtaining the product category of the product and obtaining the detection standard data, detection application scenarios and test cases of the corresponding product type from the product qualification database and big data platform for analysis; for example: if the product category part is a mobile phone speaker.

[0036] The specific detection process is:

[0037] The specific process of analyzing the inside and outside of the mobile phone speaker through the internal and external analysis module is as follows:

[0038] Collect appearance data, including the size and shape information of the mobile phone speaker, the surface quality information of the mobile phone speaker, and the coating identification information of the mobile phone speaker;

[0039] The size and shape information of the mobile phone speaker is inspected and analyzed, and the size and shape of the mobile phone speaker is obtained by a three-dimensional scanner; the speaker is scanned by a mesh beam of the three-dimensional scanner, and then the deformation of the mesh beam is obtained, and then the deformation of the mesh beam is imported into the computer three-dimensional model to obtain the shape of the mobile phone speaker; and the obtained shape of the mobile phone speaker is compared with the preset mobile phone speaker by scaling; if the shape of the mobile phone speaker does not match the preset mobile phone speaker, a shape difference signal is generated; otherwise, a combination signal 1 is generated; the size of the mobile phone speaker is proportionally converted according to the size of the scanner monitoring platform on the three-dimensional scanner; the obtained size of the mobile phone speaker is compared with the preset size of the mobile phone speaker; if the size of the mobile phone speaker is not equal to the preset size of the mobile phone speaker, a corresponding size difference signal is generated; otherwise, a combination signal 2 is generated; when the combination signal 1 and the combination signal 2 are generated at the same time, the surface quality of the mobile phone speaker is inspected and analyzed;

[0040] See also Figure 2As shown in the figure, the surface quality of the mobile phone speaker is inspected and analyzed: the surface quality of the mobile phone speaker is obtained by an industrial high-definition camera, including surface flatness, surface defects and surface finish; the surface flatness is measured by lateral illumination, and then the shadow area of ​​the illuminated area is collected by the industrial high-definition camera, and the shadow color depth is compared with the preset shadow color depth threshold. If the shadow color depth is greater than the preset shadow color depth threshold, it is marked as a valid shadow area; otherwise, it is an invalid shadow area; the surface flatness of the mobile phone speaker is obtained by converting the effective shadow area by a certain ratio; the number and degree of scratches, cracks, pits and bubbles on the surface defects are directly obtained by the industrial high-definition camera; the surface defect data is assigned to the computer for weighted calculation to obtain the mobile phone speaker. The surface finish of the mobile phone speaker is obtained by illuminating the surface from the side, and the reflected brightness is collected by an industrial high-definition camera, and then the surface finish of the mobile phone speaker is obtained by converting the reflected brightness according to a certain ratio; the surface finish, surface defect value and surface flatness of the mobile phone speaker are substituted into the computer three-dimensional coordinate system model, and the surface finish, surface defect value and surface flatness are substituted into the Y axis, Z axis and X axis respectively at a certain conversion ratio to obtain the mobile phone speaker surface quality map, and the model volume in the product surface quality map is calculated, and the value of the model volume in the map is used as the surface quality value of the mobile phone speaker; then the surface quality value of the mobile phone speaker is compared with the preset surface quality threshold value. If the surface quality value of the mobile phone speaker is greater than the preset surface quality threshold value, a surface quality difference signal is generated; otherwise, the coating identification information of the mobile phone speaker is inspected and analyzed;

[0041] Inspect and analyze the coating identification information of the mobile phone speaker: obtain the coating identification content through an industrial high-definition camera; obtain the size and shape of the mobile phone speaker based on a three-dimensional scanner; obtain the corresponding preset size and shape by identifying the coating identification content; then compare the corresponding preset size and shape with the size and shape of the mobile phone speaker; if the preset size and shape of the coating identification content does not match the size and shape of the mobile phone speaker, generate a coating identification difference signal; otherwise, detect and analyze the inside of the mobile phone speaker;

[0042] Detect and analyze the inside of the mobile phone speaker: obtain the product category, and then determine whether internal detection is required through the product category. If internal detection is required, obtain the internal parts information and assembly information of the mobile phone speaker through an X-ray internal scanner for inspection; internal parts information includes parts cracks, parts specifications and parts material list; assembly information includes production equipment parameters and assembly completion; then obtain the internal qualified data of the corresponding product category in the product qualification database and mark it as preset internal qualified data; then compare the obtained parts information and assembly information with the preset internal qualified data. When the obtained parts information is consistent with the preset internal qualified data, perform operation analysis on the mobile phone speaker, otherwise generate a zero difference signal; when the obtained assembly information is consistent with the preset internal qualified data, perform operation analysis on the mobile phone speaker, otherwise generate an assembly difference signal; if internal detection is not required, perform operation analysis on the mobile phone speaker;

[0043] The operation analysis module is used to analyze the operation of the mobile phone speaker, specifically:

[0044] Analyze the product operation data collected by the product data inspection module, which includes performance test information and status monitoring information, and then obtain the test standard data, test application scenarios and test cases corresponding to the product category through the product qualification database;

[0045] See also Figure 3 As shown, the mobile phone speaker detection application scenario is monitored and analyzed: the scene environment data is obtained through the environmental scene equipment, including but not limited to the environmental noise intensity level, noise source type, particle concentration and airflow data; the noise source type includes continuous noise and instantaneous noise; the airflow data includes wind speed and wind direction; the noise source types continuous noise and instantaneous noise are assigned values, which are noise class value one and noise class value two respectively, collectively referred to as noise class values; the environmental noise intensity level is marked as a noise value according to the noise intensity; the wind direction in the airflow data is assigned to a wind direction value according to the direction; then a detection application scenario model is established, and the acquired data is substituted into the detection application scenario model to obtain the mobile phone speaker scene detection map; the noise value is substituted into the Substitute the noise value into the X-axis, substitute the noise value into the Y-axis to get the intersection, marked as point 1; substitute the particle concentration into the intersection of the Z-axis and the noise value, marked as point 2; draw a line segment perpendicular to the XY plane with point 1, and the length is the particle concentration, and the endpoint of the line segment is marked as point 3; the wind speed is drawn in the direction of the Y-axis, with the starting point being point 3, and the endpoint of the line segment is marked as point 4; the wind direction value is drawn in the opposite direction of the X-axis, with the starting point being point 4, and the endpoint of the line segment is marked as point 5; connect point 5 with the origin o to get the length of the line segment, and use the length of the line segment as the scene value; match the scene value with the preset detection application scenario interval, if the scene value belongs to the preset detection application scenario interval, analyze the performance detection of the mobile phone speaker; otherwise, generate a scene difference signal;

[0046] Analyze the performance test of the mobile phone speaker: by obtaining performance test information, including but not limited to acoustic performance test information, electrical performance test information and mechanical performance test information;

[0047] Test and analyze the acoustic performance of mobile phone speakers: By testing acoustic testing equipment such as microphones, spectrum analyzers and audio analyzers, and obtaining frequency range, frequency response curve, frequency response flatness, sound pressure level value, maximum sound pressure level, sound pressure level curve, etc.; then by obtaining the acoustic performance test standards in the product qualification database, match the data obtained by the acoustic testing equipment with the performance test standard range; if the data obtained by the acoustic testing equipment does not belong to the performance test standard range, generate an acoustic difference signal; otherwise, test and analyze the electrical performance of the mobile phone speaker;

[0048] Test and analyze the electrical performance of mobile phone speakers: obtain rated impedance, impedance curve, minimum impedance value, DC resistance value, voice coil inductance, rated power, peak power and efficiency value through electrical testing equipment such as precision multimeter, power amplifier and audio signal generator; then match the data obtained by the electrical testing equipment with the electrical performance test standard range by obtaining the electrical performance test standards in the product qualification database; if the data obtained by the electrical testing equipment does not belong to the electrical performance test standard range, generate a poor acoustic signal; otherwise, perform test and analysis on the mechanical performance of the mobile phone speaker;

[0049] Test and analyze the mechanical performance of mobile phone speakers: obtain vibration frequency, vibration displacement, vibration acceleration, continuous working test, thermal cycle test, mechanical resonance frequency and damping coefficient through mechanical testing equipment such as vibration table, thermal cycle test box, drop tester and tensile tester; then match the data obtained by the mechanical testing equipment with the mechanical performance test standard range by obtaining the mechanical performance test standards in the product qualification database; if the data obtained by the mechanical testing equipment does not belong to the mechanical performance test standard range, generate a poor acoustic signal; otherwise, perform analysis on the status monitoring of the mobile phone speaker;

[0050] Analyze the status monitoring of the mobile phone speaker: By obtaining status monitoring information, including operation and usage monitoring and fault and abnormality monitoring, analyze the operation and usage monitoring of the mobile phone speaker: Operation and usage monitoring includes audio signal characteristics, usage time and user operation records; audio signal characteristics are assigned to frequency characteristics according to the frequency, amplitude and waveform characteristics of the audio signal; usage time is marked as cumulative time value and continuous time value according to the cumulative usage time and continuous usage time of the speaker respectively; user operation records are set according to the speaker volume and sound effect settings. The sound effect setting is divided into several preset sound effect intervals, and the sound effect setting is obtained as a certain interval of the preset sound effect intervals, and the sound effect value is assigned; the data is substituted into the calculation model to obtain the operation value, specifically: the frequency characteristic value is converted into a fixed length at a certain ratio, and then the fixed length is used as the length and width of the rectangle; by analogy, the operation monitoring diagram of the mobile phone speaker is obtained, and the area of ​​the diagram is calculated, and the area value is used as the operation value; it is matched with the preset operation interval; if the operation value belongs to the preset operation interval, the fault and abnormal monitoring of the mobile phone speaker is recorded and displayed; otherwise, an operation difference signal is generated;

[0051] Record and display the fault and abnormal monitoring of the mobile phone speaker: by obtaining fault and abnormal monitoring data, including fault display and alarm mechanism; fault display obtains various difference signals, counts the occurrence frequency, and calculates the product qualification rate, and compares it with the preset qualification rate of the corresponding product; if the product qualification rate is less than the preset qualification rate of the corresponding product, an alarm is issued; otherwise, no alarm is issued; the alarm reminds the inspection personnel to make adjustments.

[0052] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A product production inspection system based on big data, including a big data platform, a product qualification database, a detection and analysis execution module, an internal and external analysis module and an operation analysis module; characterized in that: The detection and analysis execution module is used to perform detection data analysis on the received data information, obtain the product category of the product, obtain the detection standard data, detection application scenarios and test cases of the corresponding type of product from the product qualification database and the big data platform for analysis; The internal and external analysis module is used to analyze the inside and outside of the product, by acquiring product appearance data, and inspecting and analyzing product size and shape information to generate a shape difference signal or a combination signal; then, by acquiring product surface quality conditions, inspecting and analyzing the product surface quality to obtain a product surface quality value, and comparing it with a preset surface quality threshold to generate a surface quality difference signal; When inspecting and analyzing the coating identification information of the product, the coating identification content is obtained through an industrial high-definition camera, and then the corresponding preset size and shape are compared with the product size and shape to generate a coating identification difference signal; the internal part of the product is inspected and analyzed by obtaining the product category, and then whether internal inspection is required based on the product category. If internal inspection is required, the internal part information and assembly information of the product are obtained for inspection and analysis, and the obtained part information and assembly information are compared with the preset internal qualified data to generate a zero difference signal or an assembly difference signal; The operation analysis module performs operation analysis on the product, obtains product operation data, including performance detection information and status monitoring information, obtains detection standard data, detection application scenarios and test cases corresponding to product categories through the product qualification database; monitors and analyzes product detection application scenarios, obtains scene environment data through environmental scene equipment, assigns values ​​to the scene environment data, and then obtains scene values ​​through calculation, matches the scene values ​​with preset detection application scenario intervals, and generates scene difference signals; Analyze and execute product status monitoring by acquiring status monitoring information, including operation and usage monitoring and fault and abnormality monitoring, and analyze and generate operation error signals.

2. According to the big data-based product production detection system of claim 1, it is characterized in that: It also includes product data inspection and acquisition modules, big data platforms and product qualification databases; The product data acquisition module is used to collect product categories and product appearance data, product internal data, product operation data, product assembly data and environmental data; The big data platform and product qualification database are used to provide testing standard data, testing application scenarios and test cases for product types.

3. The product production detection system based on big data according to claim 1 is characterized in that: The internal and external analysis module inspects and analyzes the product size and shape information. The specific process is as follows: The size and shape of the product are obtained by a 3D scanner, and the speaker is scanned by a mesh beam of the 3D scanner to obtain the deformation of the mesh beam, and then the deformation of the mesh beam is imported into the computer 3D model to obtain the shape of the product; and the obtained product shape is compared with the preset product by scaling and overlapping; if the product does not match the preset product, a shape difference signal is generated; otherwise, a combination signal 1 is generated; the product size is proportionally converted according to the size of the scanner monitoring platform on the 3D scanner; the obtained product size is compared with the preset product size; if the product size is not equal to the preset product size, a corresponding size difference signal is generated; otherwise, a combination signal 2 is generated; when the combination signal 1 and the combination signal 2 are generated at the same time, the surface quality of the product is inspected and analyzed, specifically: The surface quality of the product is obtained through an industrial high-definition camera. The surface flatness is measured by lateral illumination. The shadow area of ​​the illuminated area is collected by the industrial high-definition camera, and the shadow color depth is compared with the preset shadow color depth threshold. If the shadow color depth is greater than the preset shadow color depth threshold, it is marked as a valid shadow area; otherwise, it is an invalid shadow area. The surface flatness of the product is obtained by converting the effective shadow area by a certain ratio. The number and degree of scratches, cracks, pits and bubbles on the surface defects are directly obtained through the industrial high-definition camera. The product table missing value is obtained by assigning the obtained surface defect data to the computer for weighted calculation. The surface finish is illuminated from the side, and the reflected brightness is collected by an industrial high-definition camera. The reflected brightness is then converted according to a certain ratio to obtain the surface finish of the product. The surface finish, surface defect value and surface flatness of the product are substituted into the computer model to obtain the model volume in the product surface quality map, and the model volume value in the map is used as the product surface quality value. The product surface quality value is then compared with the preset surface quality threshold. If the product surface quality value is greater than the preset surface quality threshold, a surface quality difference signal is generated. Otherwise, the product coating identification information is inspected and analyzed, specifically: The coating identification content is obtained through an industrial high-definition camera and the product size and shape is obtained based on a 3D scanner; then the coating identification content is identified to obtain the corresponding preset size and shape; The corresponding preset size and shape are compared with the product size and shape; if the preset size and shape of the coating identification content does not match the product size and shape, a coating identification difference signal is generated; otherwise, the inside of the product is detected and analyzed to obtain a zero difference signal and an installation difference signal.

4. The product production detection system based on big data according to claim 1 is characterized in that: The operation analysis module monitors and analyzes the product detection application scenario, specifically: Obtain scene environment data through environmental scene equipment, including environmental noise intensity level, noise source type, particle concentration and airflow data; noise source types include continuous noise and instantaneous noise; airflow data includes wind speed and wind direction; assign values ​​to noise source types continuous noise and instantaneous noise, which are noise class value one and noise class value two, respectively, collectively referred to as noise class values; environmental noise intensity level is marked as noise value according to noise intensity; wind direction in airflow data is assigned as wind direction value according to direction; then establish a detection application scene model, substitute the acquired data into the detection application scene model to obtain the line segment length, use the line segment length as the scene value, match the scene value with the preset detection application scene interval, if the scene value belongs to the preset detection application scene interval, test and analyze the mechanical properties of the product, and obtain performance detection information, including acoustic performance test information, electrical performance test information and mechanical performance test information; Otherwise, a poor response signal is generated.

5. The product production detection system based on big data according to claim 4 is characterized in that: The operation analysis module analyzes the product status monitoring, specifically: The operation and usage monitoring includes audio signal characteristics, usage time and user operation records; the audio signal characteristics are assigned to frequency characteristics according to the frequency, amplitude and waveform characteristics of the audio signal; the usage time is marked as cumulative time value and continuous time value according to the cumulative usage time and continuous usage time of the speaker; the user operation record is divided into several preset sound effect intervals according to the volume and sound effect settings of the speaker, and the sound effect setting is obtained as a certain interval of several preset sound effect intervals, and the sound effect value is assigned; the data is substituted into the calculation model to obtain the operation value, and it is matched with the preset operation interval; if the operation value belongs to the preset operation interval, the product fault and abnormal monitoring are recorded and displayed, specifically: by obtaining fault and abnormal monitoring data, including fault display and alarm mechanism; the fault display obtains various difference signals, counts the occurrence frequency, calculates the product qualification rate, and compares it with the preset corresponding product qualification rate; if the product qualification rate is less than the preset corresponding product qualification rate, an alarm is issued; Otherwise, no alarm will be issued; the alarm will remind the inspector to make adjustments; Otherwise, a control difference signal is generated.

Images