A method and system for detecting and analyzing flat-panel televisions based on intelligent feedback

Abstract

The present invention relates to the field of television detection technology, and in particular to a method and system for detecting and analyzing flat-panel televisions based on intelligent feedback. The electrical functions of a flat-panel television are analyzed according to various actual electrical parameter sets of the flat-panel television; the appearance quality of the flat-panel television is analyzed according to the actual appearance image of the flat-panel television; if the electrical analysis result of the flat-panel television is an unqualified product in electrical detection, the location of the electrical fault component of the flat-panel television is obtained, and the flat-panel television marked with the fault location is transmitted to a repair center; if the appearance analysis result of the flat-panel television is an unqualified product in appearance detection, the appearance singular location of the flat-panel television is obtained, and the flat-panel television marked with the appearance singular location is transmitted to a repair center. The present invention significantly improves the detection speed and efficiency, reduces manual intervention, and reduces costs by performing automated detection and analysis on flat-panel televisions.

Description

Technical Field

[0001] The invention relates to the technical field of television detection, and in particular to a detection and analysis method and system for a flat-panel television based on intelligent feedback. Background Art

[0002] With the rapid development of science and technology, as an important device for home entertainment, the performance and user experience of flat-panel TVs have been improved from simple display effects to multiple dimensions including picture quality, sound, intelligence, etc. However, ensuring that every flat-panel TV shipped out of the factory can meet the high quality standards expected by users is a complex and delicate task. Traditional flat-panel TV detection mainly relies on manual visual inspection and simple functional testing. This method is time-consuming, inefficient, and easily affected by human factors, and cannot achieve comprehensive and in-depth performance evaluation. With the advancement of artificial intelligence and big data technology, intelligent feedback detection systems have emerged. This system can collect and analyze the performance data of various electrical parameters of the TV in real time through built-in high-precision sensors and image recognition algorithms to detect and analyze flat-panel TVs, which can effectively improve detection efficiency, ensure product performance stability, and provide consumers with a better product experience. Based on this, the present invention proposes a flat-panel TV detection and analysis method and system based on intelligent feedback. Summary of the invention

[0003] The present invention overcomes the shortcomings of the prior art and provides a method and system for detecting and analyzing a flat-panel television based on intelligent feedback.

[0004] To achieve the above-mentioned purpose, the technical solution adopted by the present invention is:

[0005] The first aspect of the present invention discloses a method for detecting and analyzing a flat-panel television based on intelligent feedback, comprising the following steps:

[0006] Performing electrical testing on a flat-panel TV, and collecting actual electrical parameters of the flat-panel TV at a number of preset time points during the electrical testing; classifying and processing the actual electrical parameters collected at the number of preset time points to obtain various sets of actual electrical parameters of the flat-panel TV;

[0007] Analyze the electrical functions of the flat-panel TV according to various actual electrical parameter sets of the flat-panel TV to obtain electrical analysis results;

[0008] Acquire an actual appearance image of the flat-panel television set, and analyze the appearance quality of the flat-panel television set according to the actual appearance image of the flat-panel television set to obtain an appearance analysis result;

[0009] If the electrical analysis result of the flat-panel TV is that the flat-panel TV is unqualified in the electrical inspection, the location of the electrical fault component of the flat-panel TV is obtained, the location of the electrical fault component of the flat-panel TV is marked, and the flat-panel TV with the marked fault location is transmitted to a repair center;

[0010] If the appearance analysis result of the flat-panel television set is a failed appearance inspection product, obtaining the appearance singularity position of the flat-panel television set, marking the appearance singularity position of the flat-panel television set, and transmitting the flat-panel television set with the appearance singularity position marked to a repair center;

[0011] If the electrical analysis result of the flat-panel TV is that it is qualified in the electrical inspection and the appearance analysis result is that it is qualified in the appearance inspection, the flat-panel TV will be transferred to the packaging center.

[0012] Furthermore, in a preferred embodiment of the present invention, the actual electrical parameters collected at a number of preset time points are classified and processed to obtain various sets of actual electrical parameters of a flat-panel television, specifically:

[0013] Acquire various characteristic electrical parameters of the flat-panel television, acquire the frequency spectrum of each characteristic electrical parameter, and initialize a plurality of classification clusters according to the various characteristic electrical parameters of the flat-panel television;

[0014] Acquire each actual electrical parameter collected, perform Fourier transform processing on each actual electrical parameter, and obtain a frequency spectrum of each actual electrical parameter;

[0015] Matching and analyzing the frequency spectrum of each actual electrical parameter with the frequency spectrum of the characteristic electrical parameter in each classification cluster, and obtaining the matching degree between each actual electrical parameter and each classification cluster;

[0016] Determining the degree of membership between each actual electrical parameter and each classification cluster according to the matching degree between each actual electrical parameter and each classification cluster;

[0017] Compare the membership between each actual electrical parameter and each classification cluster set with a preset membership threshold; if the membership between an actual electrical parameter and a classification cluster set is greater than the preset membership threshold, map the actual electrical parameter to the classification cluster set;

[0018] Similarly, each actual electrical parameter is mapped to a corresponding classification cluster set, and an initial classification result is output; and the initial classification result is corrected to obtain a final classification result, and various actual electrical parameter sets of the flat-panel TV are obtained according to the final classification result.

[0019] Furthermore, in a preferred embodiment of the present invention, the initial classification result is corrected to obtain a final classification result, specifically:

[0020] Obtaining initial classification results, and obtaining actual electrical parameters belonging to each classification cluster according to the initial classification results;

[0021] Calculating the weighted average of the actual electrical parameters belonging to each classification cluster, and determining the cluster center of each classification cluster according to the weighted average;

[0022] Calculate the Hamming distance between each actual electrical parameter in each classification cluster and its cluster center, and compare the Hamming distance between each actual electrical parameter in each classification cluster and its cluster center with a preset distance threshold;

[0023] If the Hamming distance between a certain actual electrical parameter in a certain classification cluster and its cluster center is greater than a preset distance threshold, the actual electrical parameter in the classification cluster is marked as a classification singular actual electrical parameter;

[0024] If a certain actual electrical parameter is marked as a classification singular actual electrical parameter, the classification singular actual electrical parameter is screened out from the classification cluster to which it currently belongs; and the classification singular actual electrical parameter is simulated and assigned to the remaining classification clusters, and the Hamming distance between the classification singular actual electrical parameter and the cluster centers of the remaining classification clusters is calculated;

[0025] If the Hamming distances between the singular actual electrical parameter of the classification and the cluster centers of the other classification clusters are all greater than the preset distance threshold, it means that the singular actual electrical parameter of the classification is noise data, and the singular actual electrical parameter of the classification is completely screened out;

[0026] If the Hamming distance between the classification singular actual electrical parameter and the cluster center of one of the other classification clusters is not greater than the preset distance threshold, it means that the classification singular actual electrical parameter actually belongs to the classification cluster, and the classification singular actual electrical parameter is allocated to the classification cluster;

[0027] This process is deduced in this way until the actual electrical parameters in each classification cluster are corrected to obtain the final classification result.

[0028] Furthermore, in a preferred embodiment of the present invention, the electrical functions of the flat-panel television are analyzed according to various actual electrical parameter sets of the flat-panel television to obtain electrical analysis results, specifically:

[0029] Acquiring preset electrical requirement information of the flat-panel television set, determining various standard electrical parameter sets of the flat-panel television set during the detection process according to the preset electrical requirement information; and acquiring various actual electrical parameter sets of the flat-panel television set;

[0030] Calculating the Jaccard similarity coefficients between various actual electrical parameter sets of the flat-panel television and the corresponding standard electrical parameter sets; and comparing the Jaccard similarity coefficients between various actual electrical parameter sets of the flat-panel television and the corresponding standard electrical parameter sets with a preset coefficient threshold;

[0031] If the Jaccard similarity coefficient between a certain actual electrical parameter set of the flat-panel TV and the corresponding standard electrical parameter set is greater than a preset coefficient threshold, the corresponding actual electrical parameter is calibrated as a type of electrical parameter;

[0032] If the Jaccard similarity coefficient between a certain actual electrical parameter set of the flat-panel TV and the corresponding standard electrical parameter set is not greater than a preset coefficient threshold, the corresponding actual electrical parameter is calibrated as a second-class electrical parameter;

[0033] It is determined whether there are second-category electrical parameters among various actual electrical parameters of the flat-panel television. If not, the flat-panel television is determined to be a qualified product in electrical testing; if so, the flat-panel television is determined to be a failed product in electrical testing.

[0034] Furthermore, in a preferred embodiment of the present invention, the appearance quality of the flat-panel TV is analyzed based on the actual appearance image of the flat-panel TV to obtain the appearance analysis result, which is specifically:

[0035] Acquiring preset appearance requirement information of the flat-panel television, obtaining a standard appearance image of the flat-panel television according to the preset appearance requirement information; and acquiring an actual appearance image of the flat-panel television;

[0036] Calculating the cosine similarity between the actual appearance image and the standard appearance image based on a cosine similarity algorithm; and comparing the cosine similarity with a preset cosine similarity threshold;

[0037] If the cosine similarity is greater than a preset cosine similarity threshold, the flat-panel television is determined to be a qualified product in appearance inspection;

[0038] If the cosine similarity is not greater than a preset cosine similarity threshold, the flat-panel television is determined to be a failed product in appearance inspection.

[0039] Furthermore, in a preferred embodiment of the present invention, if the electrical analysis result of the flat-panel TV is a failed electrical test, the location of the electrical fault component of the flat-panel TV is obtained, specifically:

[0040] If the electrical analysis result of the flat-panel TV is a failed electrical test, the actual electrical parameters of the flat-panel TV calibrated as Class II electrical parameters are obtained, and characteristic function information of each component in the flat-panel TV is obtained;

[0041] According to the characteristic function information of each component, the actual electrical parameters marked as the second-class electrical parameters are analyzed for correlation with each component, and the components that are correlated with the actual electrical parameters marked as the second-class electrical parameters are defined as associated components;

[0042] Acquire detection log information of the flat-panel TV, and acquire electrical parameter information of the associated components during the test according to the detection log information;

[0043] The electrical parameter information of the associated components during the test is imported into the Bayesian network for fault prediction to obtain the failure probability of the associated components;

[0044] If the failure probability of the associated component is greater than the preset failure probability, the associated component is marked as an electrical failure component, and the location information of the electrical failure component is obtained.

[0045] Furthermore, in a preferred embodiment of the present invention, if the appearance analysis result of the flat-panel television is a failed appearance inspection product, the appearance singular position of the flat-panel television is obtained, specifically:

[0046] If the appearance analysis result of the flat-panel TV is a failed appearance inspection, an actual appearance image and a standard appearance image are obtained;

[0047] Performing wavelet transform processing on the actual appearance image to obtain a wavelet coefficient matrix of the actual appearance image; and performing wavelet transform processing on the standard appearance image to obtain a wavelet coefficient matrix of the standard appearance image;

[0048] Subtract the wavelet coefficient matrix of the actual appearance image from the wavelet coefficient matrix of the standard appearance image to obtain a difference matrix; wherein each element in the difference matrix represents the difference of the wavelet coefficients of the corresponding position in the two images;

[0049] Traverse each element in the difference matrix, find the position of the non-zero element in the difference matrix, and mark the position of the non-zero element in the difference matrix as a singular position point, and obtain several singular position points of the difference matrix;

[0050] The appearance singular positions in the actual appearance image are reversely located according to each singular position point of the difference matrix, and the appearance singular positions in the actual appearance image are colored.

[0051] The second aspect of the present invention discloses a flat-panel television detection and analysis system based on intelligent feedback, the flat-panel television detection and analysis system comprising a memory and a processor, the memory storing a flat-panel television detection and analysis method program, when the flat-panel television detection and analysis method program is executed by the processor, the following steps are implemented:

[0052] Performing electrical testing on a flat-panel TV, and collecting actual electrical parameters of the flat-panel TV at a number of preset time points during the electrical testing; classifying and processing the actual electrical parameters collected at the number of preset time points to obtain various sets of actual electrical parameters of the flat-panel TV;

[0053] Analyze the electrical functions of the flat-panel TV according to various actual electrical parameter sets of the flat-panel TV to obtain electrical analysis results;

[0054] Acquire an actual appearance image of the flat-panel television set, and analyze the appearance quality of the flat-panel television set according to the actual appearance image of the flat-panel television set to obtain an appearance analysis result;

[0055] If the electrical analysis result of the flat-panel TV is that the flat-panel TV is unqualified in the electrical inspection, the location of the electrical fault component of the flat-panel TV is obtained, the location of the electrical fault component of the flat-panel TV is marked, and the flat-panel TV with the marked fault location is transmitted to a repair center;

[0056] If the appearance analysis result of the flat-panel television set is a failed appearance inspection product, obtaining the appearance singularity position of the flat-panel television set, marking the appearance singularity position of the flat-panel television set, and transmitting the flat-panel television set with the appearance singularity position marked to a repair center;

[0057] If the electrical analysis result of the flat-panel TV is that it is qualified in the electrical inspection and the appearance analysis result is that it is qualified in the appearance inspection, the flat-panel TV will be transferred to the packaging center.

[0058] The present invention solves the technical defects existing in the background technology, and has the following beneficial effects: the present invention significantly improves the detection speed and efficiency, reduces manual intervention, and reduces costs by performing automated detection and analysis on flat-panel televisions; and the application of intelligent algorithms improves the accuracy and reliability of detection, and can accurately identify appearance defects and electrical faults, and timely discover product problems; at the same time, the detection results are shared with the maintenance center in real time, which speeds up the fault response and processing speed. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, drawings of other embodiments can be obtained based on these drawings without paying creative work.

[0060] Figure 1 The present invention is a flow chart of the overall method of a flat panel TV detection and analysis method based on intelligent feedback;

[0061] Figure 2 A partial method flow chart of a method for detecting and analyzing a flat-panel television based on intelligent feedback;

[0062] Figure 3 The system block diagram of a flat-panel TV detection and analysis system based on intelligent feedback. DETAILED DESCRIPTION

[0063] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0064] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0065] like Figure 1 As shown, the first aspect of the present invention discloses a flat-panel TV detection and analysis method based on intelligent feedback, comprising the following steps:

[0066] S102: performing an electrical test on the flat-panel TV, and collecting actual electrical parameters of the flat-panel TV at a number of preset time points during the electrical test; classifying the actual electrical parameters collected at the number of preset time points to obtain various sets of actual electrical parameters of the flat-panel TV;

[0067] S104: analyzing the electrical functions of the flat-panel television according to various actual electrical parameter sets of the flat-panel television to obtain electrical analysis results;

[0068] S106: Acquire an actual appearance image of the flat-panel television set, and analyze the appearance quality of the flat-panel television set according to the actual appearance image of the flat-panel television set to obtain an appearance analysis result;

[0069] S108: If the electrical analysis result of the flat-panel TV is that the flat-panel TV is unqualified, the location of the electrical fault component of the flat-panel TV is obtained, the location of the electrical fault component of the flat-panel TV is marked, and the flat-panel TV with the marked fault location is transmitted to a repair center;

[0070] S110: If the appearance analysis result of the flat-panel TV is that the appearance inspection fails, obtaining the appearance singularity position of the flat-panel TV, marking the appearance singularity position of the flat-panel TV, and transmitting the flat-panel TV with the appearance singularity position marked to a repair center;

[0071] S112: If the electrical analysis result of the flat-panel TV is that the electrical test is qualified and the appearance analysis result is that the appearance test is qualified, the flat-panel TV is transferred to a packaging center.

[0072] It should be noted that the electrical parameters include but are not limited to color accuracy, contrast, response time, voltage and current, power consumption, response time and delay, and electromagnetic compatibility.

[0073] The present invention significantly improves the detection speed and efficiency, reduces manual intervention and reduces costs by performing automated detection and analysis on flat-panel televisions. The application of intelligent algorithms improves the accuracy and reliability of detection, and can accurately identify appearance defects and electrical faults, and promptly discover product problems. At the same time, the detection results are shared with the maintenance center in real time, which speeds up fault response and processing.

[0074] like Figure 2 As shown, further, in a preferred embodiment of the present invention, the actual electrical parameters collected at several preset time nodes are classified and processed to obtain various actual electrical parameter sets of flat-panel televisions, specifically:

[0075] S202: Acquire various characteristic electrical parameters of the flat-panel television, acquire the frequency spectrum of each characteristic electrical parameter, and initialize a plurality of classification clusters according to the various characteristic electrical parameters of the flat-panel television;

[0076] S204: Acquire each collected actual electrical parameter, perform Fourier transform processing on each actual electrical parameter, and obtain a frequency spectrum of each actual electrical parameter;

[0077] S206: performing matching analysis on the frequency spectrum of each actual electrical parameter and the frequency spectrum of the characteristic electrical parameter in each classification cluster to obtain the matching degree between each actual electrical parameter and each classification cluster;

[0078] S208: determining the membership degree between each actual electrical parameter and each classification cluster according to the matching degree between each actual electrical parameter and each classification cluster;

[0079] S210: Compare the membership between each actual electrical parameter and each classification cluster set with a preset membership threshold; if the membership between a certain actual electrical parameter and a certain classification cluster set is greater than the preset membership threshold, map the actual electrical parameter to the classification cluster set;

[0080] S212: Similarly, each actual electrical parameter is mapped to a corresponding classification cluster set, and an initial classification result is output; and the initial classification result is corrected to obtain a final classification result, and various actual electrical parameter sets of the flat-panel TV are obtained according to the final classification result.

[0081] Among them, the characteristic electrical parameters of the flat-screen TV are characteristic data used to represent various electrical parameters in the flat-screen TV, and each characteristic electrical parameter contains characteristic information of various characteristic electrical parameters, such as current in amperes (A), voltage in volts (V), etc.

[0082] It should be noted that it is crucial to classify the actual electrical parameters collected, because this helps to organize and analyze data in the system so as to more effectively evaluate the performance of flat-panel TVs under specific usage states or conditions. Classification processing can group data by specific dimensions (such as time, operating mode, functional status, etc.), which can highlight the performance characteristics and potential problems of various electrical parameters of flat-panel TVs based on time series during the test process. By comparing these parameter sets, the efficiency, stability and reliability of flat-panel TVs under specific functions or operating modes can be analyzed. In summary, by classifying the actual electrical parameters collected, a series of electrical parameter sets with specific time series are formed, which helps to simplify the subsequent data analysis process, improve the system operation rate, and thus effectively improve the detection efficiency. In addition, this method can obtain data classification results with higher reliability, which can improve the accuracy of detection and effectively reduce the outflow of defective products.

[0083] Furthermore, in a preferred embodiment of the present invention, the initial classification result is corrected to obtain a final classification result, specifically:

[0084] Obtaining initial classification results, and obtaining actual electrical parameters belonging to each classification cluster according to the initial classification results;

[0085] Calculating the weighted average of the actual electrical parameters belonging to each classification cluster, and determining the cluster center of each classification cluster according to the weighted average;

[0086] Calculate the Hamming distance between each actual electrical parameter in each classification cluster and its cluster center, and compare the Hamming distance between each actual electrical parameter in each classification cluster and its cluster center with a preset distance threshold;

[0087] If the Hamming distance between a certain actual electrical parameter in a certain classification cluster and its cluster center is greater than a preset distance threshold, the actual electrical parameter in the classification cluster is marked as a classification singular actual electrical parameter;

[0088] If a certain actual electrical parameter is marked as a classification singular actual electrical parameter, the classification singular actual electrical parameter is screened out from the classification cluster to which it currently belongs; and the classification singular actual electrical parameter is simulated and assigned to the remaining classification clusters, and the Hamming distance between the classification singular actual electrical parameter and the cluster centers of the remaining classification clusters is calculated;

[0089] If the Hamming distances between the singular actual electrical parameter of the classification and the cluster centers of the other classification clusters are all greater than the preset distance threshold, it means that the singular actual electrical parameter of the classification is noise data, and the singular actual electrical parameter of the classification is completely screened out;

[0090] If the Hamming distance between the classification singular actual electrical parameter and the cluster center of one of the other classification clusters is not greater than the preset distance threshold, it means that the classification singular actual electrical parameter actually belongs to the classification cluster, and the classification singular actual electrical parameter is allocated to the classification cluster;

[0091] This process is deduced in this way until the actual electrical parameters in each classification cluster are corrected to obtain the final classification result.

[0092] It should be noted that after the actual electrical parameters collected are classified and classified to obtain the same type of actual electrical parameter sets of flat-panel TVs, the initial classification results need to be evaluated and corrected because this can ensure the accuracy and reliability of the data, thereby providing solid data support for the performance evaluation, quality control and product optimization of flat-panel TVs. The evaluation and correction processing mainly includes the following aspects: First, through statistical analysis and comparison, outliers or inconsistent data points in the parameter set can be identified. These data points may be caused by measurement errors or system abnormalities and need to be corrected or eliminated; secondly, the evaluation and correction processing helps to verify the consistency and repeatability of the data, ensuring that the collected parameter set can truly reflect the electrical performance of the TV under specific operating conditions; therefore, evaluating and correcting the classification results is an important part of ensuring the quality control of flat-panel TVs. For example, in the process of classifying the actual electrical parameters through the above classification method, misclassification may occur, such as classifying the current data of a certain time node into the voltage data set; in addition, due to a series of sensor acquisition environments, acquisition accuracy, and transmission signal quality issues, some noise data may be generated. In view of this, in order to further improve the reliability of data classification results and thus improve data quality, the present invention needs to evaluate and correct the initial classification results through this step.

[0093] Furthermore, in a preferred embodiment of the present invention, the electrical functions of the flat-panel television are analyzed according to various actual electrical parameter sets of the flat-panel television to obtain electrical analysis results, specifically:

[0094] Acquiring preset electrical requirement information of the flat-panel television set, determining various standard electrical parameter sets of the flat-panel television set during the detection process according to the preset electrical requirement information; and acquiring various actual electrical parameter sets of the flat-panel television set;

[0095] Calculating the Jaccard similarity coefficients between various actual electrical parameter sets of the flat-panel television and the corresponding standard electrical parameter sets; and comparing the Jaccard similarity coefficients between various actual electrical parameter sets of the flat-panel television and the corresponding standard electrical parameter sets with a preset coefficient threshold;

[0096] If the Jaccard similarity coefficient between a certain actual electrical parameter set of the flat-panel TV and the corresponding standard electrical parameter set is greater than a preset coefficient threshold, the corresponding actual electrical parameter is calibrated as a type of electrical parameter;

[0097] If the Jaccard similarity coefficient between a certain actual electrical parameter set of the flat-panel TV and the corresponding standard electrical parameter set is not greater than a preset coefficient threshold, the corresponding actual electrical parameter is calibrated as a second-class electrical parameter;

[0098] It is determined whether there are second-category electrical parameters among various actual electrical parameters of the flat-panel television. If not, the flat-panel television is determined to be a qualified product in electrical testing; if so, the flat-panel television is determined to be a failed product in electrical testing.

[0099] It should be noted that the Chinese name of the Jaccard similarity coefficient is "Jaccard similarity coefficient" or "Jaccard coefficient". It is a statistical indicator used to compare the similarity of sample sets, and is particularly suitable for comparing the similarity of two sample sets. The value range of the Jaccard coefficient is between 0 and 1. The larger the value, the higher the similarity of the two sets. It is particularly suitable for processing data sets with binary attributes, such as in fields such as text analysis, to measure the degree of overlap between two sets.

[0100] It should be noted that if the Jaccard similarity coefficient between a certain actual electrical parameter set of a flat-panel TV and the corresponding standard electrical parameter set is greater than the preset coefficient threshold, it means that the actual electrical parameter set is normal, and the corresponding actual electrical parameter is calibrated as a Class I electrical parameter; if the Jaccard similarity coefficient between a certain actual electrical parameter set of a flat-panel TV and the corresponding standard electrical parameter set is not greater than the preset coefficient threshold, it means that the actual electrical parameter set is abnormal, and the corresponding actual electrical parameter is calibrated as a Class II electrical parameter. It is determined whether there are Class II electrical parameters in the various actual electrical parameters of the flat-panel TV. If so, the flat-panel TV is judged as an unqualified product in electrical testing, otherwise, it is a qualified product in electrical testing. This method can quickly analyze whether the electrical function of the flat-panel TV meets the standard.

[0101] Furthermore, in a preferred embodiment of the present invention, the appearance quality of the flat-panel TV is analyzed based on the actual appearance image of the flat-panel TV to obtain the appearance analysis result, which is specifically:

[0102] Acquiring preset appearance requirement information of the flat-panel television, obtaining a standard appearance image of the flat-panel television according to the preset appearance requirement information; and acquiring an actual appearance image of the flat-panel television;

[0103] Calculating the cosine similarity between the actual appearance image and the standard appearance image based on a cosine similarity algorithm; and comparing the cosine similarity with a preset cosine similarity threshold;

[0104] If the cosine similarity is greater than a preset cosine similarity threshold, the flat-panel television is determined to be a qualified product in appearance inspection;

[0105] If the cosine similarity is not greater than a preset cosine similarity threshold, the flat-panel television is determined to be a failed product in appearance inspection.

[0106] It should be noted that the principle of calculating the similarity between two images by the cosine similarity algorithm is to use the vector space model to represent the image as a vector in a high-dimensional space, and then calculate the cosine value between these vectors to measure the similarity between them. Specifically, each pixel or area in the image is regarded as a dimension of the vector, and its value can be the brightness, color characteristics, etc. of the pixel. By calculating the dot product of two vectors and dividing it by the product of their modulus lengths, the result is the cosine similarity, which is between -1 and 1. The larger the value, the more similar the images are. Cosine similarity does not depend on the absolute size of the vector (i.e., it does not consider the length of the vector), but focuses on the similarity in direction, so it can effectively identify the similarity between images of different sizes. This method can quickly analyze whether the appearance quality of a flat-panel TV is up to standard.

[0107] Furthermore, in a preferred embodiment of the present invention, if the electrical analysis result of the flat-panel TV is a failed electrical test, the location of the electrical fault component of the flat-panel TV is obtained, specifically:

[0108] If the electrical analysis result of the flat-panel TV is a failed electrical test, the actual electrical parameters of the flat-panel TV calibrated as Class II electrical parameters are obtained, and characteristic function information of each component in the flat-panel TV is obtained;

[0109] According to the characteristic function information of each component, the actual electrical parameters marked as the second-class electrical parameters are analyzed for correlation with each component, and the components that are correlated with the actual electrical parameters marked as the second-class electrical parameters are defined as associated components;

[0110] Acquire detection log information of the flat-panel TV, and acquire electrical parameter information of the associated components during the test according to the detection log information;

[0111] Among them, the test log information of the flat-panel TV refers to the various data and information recorded during the test process on the performance, function and quality status of each component of the TV; the test log information is an electronic data record book;

[0112] The electrical parameter information of the associated components during the test is imported into the Bayesian network for fault prediction to obtain the failure probability of the associated components;

[0113] If the failure probability of the associated component is greater than the preset failure probability, the associated component is marked as an electrical failure component, and the location information of the electrical failure component is obtained.

[0114] It should be noted that the characteristic function information of each component in a flat-panel TV refers to the function and performance of each electronic component in the TV system. These components include but are not limited to display screens (such as LCD and OLED panels), power modules, signal processing chips, memories, interface controllers, and audio amplifiers. The display screen is responsible for displaying images, the voltage regulator provides stable power for the entire system, the signal processing chip is responsible for the conversion and processing of image and audio signals, the memory is used to store operating system and application data, the interface controller is used to connect external devices, and the audio amplifier enhances sound output. The characteristic function information of each component involves key parameters such as its physical properties, electrical performance, reliability, and compatibility. This information is essential to ensure the overall performance, stability, and user experience of the TV.

[0115] It should be noted that, according to the characteristic function information of each component, the actual electrical parameters calibrated as the second-class electrical parameters are analyzed for correlation with each component, and the components obtained by the analysis have correlation with the actual electrical parameters calibrated as the second-class electrical parameters are defined as associated components. For example, if the circuit voltage parameter is abnormal, and the voltage regulator is closely related to the circuit voltage, then the voltage regulator is defined as an associated component with abnormal voltage parameters.

[0116] It should be noted that the electrical parameter information of the related components in the flat-panel TV during the test process is imported into the Bayesian network for fault prediction. The principle is to analyze and infer the probability of failure of each component based on the Bayesian theorem and network structure. First of all, the Bayesian network is a graphical model, which consists of nodes and edges. The nodes represent random variables (such as the electrical parameter information of the components), and the edges represent the probabilistic dependencies between variables. By importing the electrical parameter information of the components (such as voltage, current, temperature, etc.) as input data into the Bayesian network, the network can use the statistical correlation between these parameters to infer the health status of the components. Then, the Bayesian network uses the prior probability (based on historical data or expert knowledge) and the conditional probability (based on the currently observed electrical parameters) to calculate the posterior probability of failure of each component, that is, the probability of component failure under the condition of given observation data.

[0117] Furthermore, in a preferred embodiment of the present invention, if the appearance analysis result of the flat-panel television is a failed appearance inspection product, the appearance singular position of the flat-panel television is obtained, specifically:

[0118] If the appearance analysis result of the flat-panel TV is a failed appearance inspection, an actual appearance image and a standard appearance image are obtained;

[0119] Performing wavelet transform processing on the actual appearance image to obtain a wavelet coefficient matrix of the actual appearance image; and performing wavelet transform processing on the standard appearance image to obtain a wavelet coefficient matrix of the standard appearance image;

[0120] Subtract the wavelet coefficient matrix of the actual appearance image from the wavelet coefficient matrix of the standard appearance image to obtain a difference matrix; wherein each element in the difference matrix represents the difference of the wavelet coefficients of the corresponding position in the two images;

[0121] Traverse each element in the difference matrix, find the position of the non-zero element in the difference matrix, and mark the position of the non-zero element in the difference matrix as a singular position point, and obtain several singular position points of the difference matrix;

[0122] The appearance singular positions in the actual appearance image are reversely located according to each singular position point of the difference matrix, and the appearance singular positions in the actual appearance image are colored.

[0123] It should be noted that the principle of performing wavelet transform on the appearance image to obtain the wavelet coefficient matrix of the appearance image is based on wavelet analysis theory, which is a multi-scale analysis method for image processing. Wavelet transform captures the characteristics of the image at different frequencies and spaces by decomposing the image into wavelet coefficients of different scales and positions. In the processing process, firstly, a suitable wavelet function is selected as the basis function, and then the image signal is convolved with the wavelet function to obtain the wavelet coefficients of the image at different scales. These coefficients reflect the local characteristics of the image at different spatial frequencies, including information such as edges, textures, and details. Through wavelet transform, the image can be converted from the time domain or space domain to the wavelet domain, thereby realizing image compression, denoising, feature extraction, and fault detection. The wavelet coefficient matrix is ​​a matrix formed by arranging these transformed wavelet coefficients according to certain rules. It retains the important characteristics of the original image and provides basic data for subsequent image analysis and processing.

[0124] The present invention compares the appearance singular positions in the appearance image by comparing the wavelet coefficient matrices of two images, and can effectively identify and locate abnormal areas or irregular features in the image, which may be caused by defects, damage or other unexpected changes. Wavelet transform can decompose the image into information of different scales and directions, thereby highlighting the local features of the image in the wavelet domain. Comparing the wavelet coefficient matrices of two images can reveal the differences between them, which usually correspond to singular positions in the appearance image, such as scratches, dents, stains or other irregular appearance changes; in this way, the detection efficiency can be effectively improved.

[0125] In summary, when the flat-panel TV is tested and analyzed, the strange appearance positions and electrical faulty component positions of the flat-panel TV are automatically detected, and these positions are marked and sent to the maintenance center. Through this automated detection process, the problem can be quickly identified, reducing the time required for manual inspection, providing the maintenance center with important fault diagnosis and processing information, and can effectively improve the subsequent maintenance efficiency of the flat-panel TV; and by automatically identifying and marking the fault location, the product is provided with traceability, which helps to improve the design and manufacturing process.

[0126] In addition, the method further comprises the following steps:

[0127] Obtain the locations of electrical faulty components and the locations of singular appearance of the flat-panel television, and define the locations of electrical faulty components and the locations of singular appearance of the flat-panel television as assembly abnormality areas;

[0128] Acquire assembly process information of a flat-panel television set and a three-dimensional model diagram of assembly equipment of the flat-panel television set; construct an assembly simulation system based on three-dimensional simulation software and in combination with the assembly process information and the three-dimensional model diagram of assembly equipment;

[0129] Performing simulated assembly production of a flat-panel TV based on the assembly simulation system, and obtaining sub-assembly equipment that has contact and collision with the assembly abnormality area during the simulated assembly production process, and defining them as suspicious sub-assembly equipment;

[0130] Acquire the real-time working parameters of the suspicious sub-assembly device, introduce a Markov chain, and calculate the state transition probability of the suspicious sub-assembly device based on the Markov chain and in combination with the real-time working parameters of the suspicious sub-assembly device;

[0131] Determine whether the state transition probability is greater than a preset probability value, and if so, obtain and calculate the difference between the real-time working parameter of the suspicious sub-assembly device and the preset working parameter to obtain the working parameter difference;

[0132] The real-time operating parameters of the suspicious sub-assembly equipment are regulated based on the operating parameter difference.

[0133] It should be noted that after detecting and analyzing the locations of the electrically faulty components and the abnormal appearance of the flat-screen TV, the states of the sub-assembly equipment related to the flat-screen TV are traced back based on the locations of the electrically faulty components and the abnormal appearance of the flat-screen TV, so as to determine whether the related sub-assembly equipment is normal, and thus timely pre-adjust the sub-assembly equipment with abnormal conditions, thereby optimizing the production process based on the intelligent feedback mechanism, avoiding the production of large quantities of defective products, and improving economic benefits.

[0134] In addition, the method further comprises the following steps:

[0135] Scanning and detecting the flat-panel TV using an ultrasonic detector, and obtaining ultrasonic data information fed back by the flat-panel TV, and constructing a three-dimensional model diagram of the actual assembly state of the flat-panel TV according to the ultrasonic data information fed back by the flat-panel TV;

[0136] Obtaining a standard assembly state three-dimensional model diagram of a flat-panel television set, and calculating the degree of overlap between the actual assembly state three-dimensional model diagram and the standard assembly state three-dimensional model diagram based on a Euclidean distance algorithm;

[0137] If the overlap degree is greater than the preset overlap degree, it means that the assembly quality of the flat-panel TV is qualified;

[0138] If the overlap is not greater than a preset overlap, the actual assembly state three-dimensional model diagram and the standard assembly state three-dimensional model diagram are colored with different colors, so that the actual assembly state three-dimensional model diagram is represented by a first color, and the standard assembly state three-dimensional model diagram is represented by a second color;

[0139] Constructing a registration space, importing the actual assembly state three-dimensional model image and the standard assembly state three-dimensional model image into the registration space for registration processing, and obtaining a registered assembly state three-dimensional model image;

[0140] The registered three-dimensional model image of the assembly state is analyzed to obtain a model area having only the first color, which is defined as an assembly abnormality area; and the assembly abnormality area is sent to a preset terminal for display.

[0141] It should be noted that the first color is different from the second color, such as the first color is green and the second color is black; the assembly status of the flat-screen TV is checked by this method, so as to detect whether there are assembly abnormality areas such as offset and gap in the flat-screen TV after assembly, and send the assembly abnormality area to a preset terminal for display, so as to optimize the assembly process according to the assembly abnormality area.

[0142] like Figure 3 As shown, the second aspect of the present invention discloses a flat-panel television detection and analysis system based on intelligent feedback, the flat-panel television detection and analysis system comprises a memory 10 and a processor 20, the memory 10 stores a flat-panel television detection and analysis method program, when the flat-panel television detection and analysis method program is executed by the processor 20, the following steps are implemented:

[0143] Performing electrical testing on a flat-panel TV, and collecting actual electrical parameters of the flat-panel TV at a number of preset time points during the electrical testing; classifying and processing the actual electrical parameters collected at the number of preset time points to obtain various sets of actual electrical parameters of the flat-panel TV;

[0144] Analyze the electrical functions of the flat-panel TV according to various actual electrical parameter sets of the flat-panel TV to obtain electrical analysis results;

[0145] Acquire an actual appearance image of the flat-panel television set, and analyze the appearance quality of the flat-panel television set according to the actual appearance image of the flat-panel television set to obtain an appearance analysis result;

[0146] If the electrical analysis result of the flat-panel TV is that the flat-panel TV is unqualified in the electrical inspection, the location of the electrical fault component of the flat-panel TV is obtained, the location of the electrical fault component of the flat-panel TV is marked, and the flat-panel TV with the marked fault location is transmitted to a repair center;

[0147] If the appearance analysis result of the flat-panel television set is a failed appearance inspection product, obtaining the appearance singularity position of the flat-panel television set, marking the appearance singularity position of the flat-panel television set, and transmitting the flat-panel television set with the appearance singularity position marked to a repair center;

[0148] If the electrical analysis result of the flat-panel TV is that it is qualified in the electrical inspection and the appearance analysis result is that it is qualified in the appearance inspection, the flat-panel TV will be transferred to the packaging center.

[0149] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0150] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0151] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0152] Those skilled in the art can understand that: all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiments; and the aforementioned storage medium includes: mobile storage devices, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), disks or optical disks, and other media that can store program codes.

[0153] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods of each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

[0154] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art who is familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for detecting and analyzing a flat-panel TV based on intelligent feedback, characterized in that: The following steps are involved: Performing electrical testing on a flat-panel TV, and collecting actual electrical parameters of the flat-panel TV at a number of preset time points during the electrical testing; classifying the actual electrical parameters collected at the number of preset time points to obtain various sets of actual electrical parameters of the flat-panel TV; Analyze the electrical functions of the flat-panel TV according to various actual electrical parameter sets of the flat-panel TV to obtain electrical analysis results; Acquire an actual appearance image of the flat-panel television set, and analyze the appearance quality of the flat-panel television set according to the actual appearance image of the flat-panel television set to obtain an appearance analysis result; If the electrical analysis result of the flat-panel TV is that the flat-panel TV is unqualified in the electrical inspection, the location of the electrical fault component of the flat-panel TV is obtained, the location of the electrical fault component of the flat-panel TV is marked, and the flat-panel TV with the marked fault location is transmitted to a repair center; If the appearance analysis result of the flat-panel television set is a failed appearance inspection product, obtaining the appearance singularity position of the flat-panel television set, marking the appearance singularity position of the flat-panel television set, and transmitting the flat-panel television set with the appearance singularity position marked to a repair center; If the electrical analysis result of the flat-panel TV is a qualified product in the electrical inspection and the appearance analysis result is a qualified product in the appearance inspection, the flat-panel TV will be transferred to the packaging center; The actual electrical parameters collected at several preset time points are classified and processed to obtain various actual electrical parameter sets of flat-panel televisions, specifically: Acquire various characteristic electrical parameters of the flat-panel television, acquire the frequency spectrum of each characteristic electrical parameter, and initialize a plurality of classification clusters according to the various characteristic electrical parameters of the flat-panel television; Acquire each actual electrical parameter collected, perform Fourier transform processing on each actual electrical parameter, and obtain a frequency spectrum of each actual electrical parameter; Matching and analyzing the frequency spectrum of each actual electrical parameter with the frequency spectrum of the characteristic electrical parameter in each classification cluster, and obtaining the matching degree between each actual electrical parameter and each classification cluster; Determining the degree of membership between each actual electrical parameter and each classification cluster according to the matching degree between each actual electrical parameter and each classification cluster; Compare the membership between each actual electrical parameter and each classification cluster set with a preset membership threshold; if the membership between an actual electrical parameter and a classification cluster set is greater than the preset membership threshold, map the actual electrical parameter to the classification cluster set; Similarly, each actual electrical parameter is mapped to a corresponding classification cluster set, and an initial classification result is output; and the initial classification result is corrected to obtain a final classification result, and various actual electrical parameter sets of the flat-panel television are obtained according to the final classification result; The initial classification result is corrected to obtain the final classification result, which is specifically: Obtaining initial classification results, and obtaining actual electrical parameters belonging to each classification cluster according to the initial classification results; Calculating the weighted average of the actual electrical parameters belonging to each classification cluster, and determining the cluster center of each classification cluster according to the weighted average; Calculate the Hamming distance between each actual electrical parameter in each classification cluster and its cluster center, and compare the Hamming distance between each actual electrical parameter in each classification cluster and its cluster center with a preset distance threshold; If the Hamming distance between a certain actual electrical parameter in a certain classification cluster and its cluster center is greater than a preset distance threshold, the actual electrical parameter in the classification cluster is marked as a classification singular actual electrical parameter; If a certain actual electrical parameter is marked as a classification singular actual electrical parameter, the classification singular actual electrical parameter is screened out from the classification cluster to which it currently belongs; and the classification singular actual electrical parameter is simulated and assigned to the remaining classification clusters, and the Hamming distance between the classification singular actual electrical parameter and the cluster centers of the remaining classification clusters is calculated; If the Hamming distances between the singular actual electrical parameter of the classification and the cluster centers of the other classification clusters are all greater than the preset distance threshold, it means that the singular actual electrical parameter of the classification is noise data, and the singular actual electrical parameter of the classification is completely screened out; If the Hamming distance between the classification singular actual electrical parameter and the cluster center of one of the other classification clusters is not greater than the preset distance threshold, it means that the classification singular actual electrical parameter actually belongs to the classification cluster, and the classification singular actual electrical parameter is allocated to the classification cluster; This process is repeated in this way until the actual electrical parameters in each classification cluster are corrected to obtain the final classification result. Among them, the electrical functions of the flat-panel TV are analyzed according to various actual electrical parameter sets of the flat-panel TV, and the electrical analysis results are obtained, specifically: Acquiring preset electrical requirement information of the flat-panel television set, determining various standard electrical parameter sets of the flat-panel television set during the detection process according to the preset electrical requirement information; and acquiring various actual electrical parameter sets of the flat-panel television set; Calculating the Jaccard similarity coefficients between various actual electrical parameter sets of the flat-panel television and the corresponding standard electrical parameter sets; and comparing the Jaccard similarity coefficients between various actual electrical parameter sets of the flat-panel television and the corresponding standard electrical parameter sets with a preset coefficient threshold; If the Jaccard similarity coefficient between a certain actual electrical parameter set of the flat-panel TV and the corresponding standard electrical parameter set is greater than a preset coefficient threshold, the corresponding actual electrical parameter is calibrated as a type of electrical parameter; If the Jaccard similarity coefficient between a certain actual electrical parameter set of the flat-panel TV and the corresponding standard electrical parameter set is not greater than a preset coefficient threshold, the corresponding actual electrical parameter is calibrated as a second-class electrical parameter; It is determined whether there are second-category electrical parameters among various actual electrical parameters of the flat-panel television. If not, the flat-panel television is determined to be a qualified product in electrical testing; if so, the flat-panel television is determined to be a failed product in electrical testing.

2. A method for detecting and analyzing a flat-panel television based on intelligent feedback according to claim 1, characterized in that: The appearance quality of the flat-panel TV is analyzed based on the actual appearance image of the flat-panel TV, and the appearance analysis results are obtained, specifically: Acquiring preset appearance requirement information of the flat-panel television, obtaining a standard appearance image of the flat-panel television according to the preset appearance requirement information; and acquiring an actual appearance image of the flat-panel television; Calculating the cosine similarity between the actual appearance image and the standard appearance image based on a cosine similarity algorithm; and comparing the cosine similarity with a preset cosine similarity threshold; If the cosine similarity is greater than a preset cosine similarity threshold, the flat-panel television is determined to be a qualified product in appearance inspection; If the cosine similarity is not greater than a preset cosine similarity threshold, the flat-panel television is determined to be a failed product in appearance inspection.

3. The method for detecting and analyzing a flat-panel TV based on intelligent feedback according to claim 1, characterized in that: If the electrical analysis result of the flat-panel TV is a failed electrical test, the location of the electrical fault component of the flat-panel TV is obtained, specifically: If the electrical analysis result of the flat-panel TV is a failed electrical test, the actual electrical parameters of the flat-panel TV calibrated as Class II electrical parameters are obtained, and characteristic function information of each component in the flat-panel TV is obtained; According to the characteristic function information of each component, the actual electrical parameters marked as the second-class electrical parameters are analyzed for correlation with each component, and the components that are correlated with the actual electrical parameters marked as the second-class electrical parameters are defined as associated components; Acquire detection log information of the flat-panel TV, and acquire electrical parameter information of the associated components during the test according to the detection log information; The electrical parameter information of the associated components during the test is imported into the Bayesian network for fault prediction to obtain the failure probability of the associated components; If the failure probability of the associated component is greater than the preset failure probability, the associated component is marked as an electrical failure component, and the location information of the electrical failure component is obtained.

4. The method for detecting and analyzing a flat-panel television based on intelligent feedback according to claim 1, characterized in that: If the appearance analysis result of the flat-panel TV is a failed appearance inspection product, then the appearance singularity position of the flat-panel TV is obtained, specifically: If the appearance analysis result of the flat-panel TV is a failed appearance inspection, an actual appearance image and a standard appearance image are obtained; Performing wavelet transform processing on the actual appearance image to obtain a wavelet coefficient matrix of the actual appearance image; and performing wavelet transform processing on the standard appearance image to obtain a wavelet coefficient matrix of the standard appearance image; Subtract the wavelet coefficient matrix of the actual appearance image from the wavelet coefficient matrix of the standard appearance image to obtain a difference matrix; wherein each element in the difference matrix represents the difference of the wavelet coefficients of the corresponding position in the two images; Traverse each element in the difference matrix, find the position of the non-zero element in the difference matrix, and mark the position of the non-zero element in the difference matrix as a singular position point, and obtain several singular position points of the difference matrix; The appearance singular positions in the actual appearance image are reversely located according to each singular position point of the difference matrix, and the appearance singular positions in the actual appearance image are colored.

5. A flat-panel TV detection and analysis system based on intelligent feedback, characterized in that: The flat-panel TV detection and analysis system comprises a memory and a processor. The memory stores a flat-panel TV detection and analysis method program. When the flat-panel TV detection and analysis method program is executed by the processor, the following steps are implemented: Performing electrical testing on a flat-panel TV, and collecting actual electrical parameters of the flat-panel TV at a number of preset time points during the electrical testing; classifying the actual electrical parameters collected at the number of preset time points to obtain various sets of actual electrical parameters of the flat-panel TV; Analyze the electrical functions of the flat-panel TV according to various actual electrical parameter sets of the flat-panel TV to obtain electrical analysis results; Acquire an actual appearance image of the flat-panel television set, and analyze the appearance quality of the flat-panel television set according to the actual appearance image of the flat-panel television set to obtain an appearance analysis result; If the electrical analysis result of the flat-panel TV is that the flat-panel TV is unqualified in the electrical inspection, the location of the electrical fault component of the flat-panel TV is obtained, the location of the electrical fault component of the flat-panel TV is marked, and the flat-panel TV with the marked fault location is transmitted to a repair center; If the appearance analysis result of the flat-panel television set is a failed appearance inspection product, obtaining the appearance singularity position of the flat-panel television set, marking the appearance singularity position of the flat-panel television set, and transmitting the flat-panel television set with the appearance singularity position marked to a repair center; If the electrical analysis result of the flat-panel TV is a qualified product in the electrical inspection and the appearance analysis result is a qualified product in the appearance inspection, the flat-panel TV will be transferred to the packaging center; The actual electrical parameters collected at several preset time points are classified and processed to obtain various actual electrical parameter sets of flat-panel televisions, specifically: Acquire various characteristic electrical parameters of the flat-panel television, acquire the frequency spectrum of each characteristic electrical parameter, and initialize a plurality of classification clusters according to the various characteristic electrical parameters of the flat-panel television; Acquire each actual electrical parameter collected, perform Fourier transform processing on each actual electrical parameter, and obtain a frequency spectrum of each actual electrical parameter; Matching and analyzing the frequency spectrum of each actual electrical parameter with the frequency spectrum of the characteristic electrical parameter in each classification cluster, and obtaining the matching degree between each actual electrical parameter and each classification cluster; Determining the degree of membership between each actual electrical parameter and each classification cluster according to the matching degree between each actual electrical parameter and each classification cluster; Compare the membership between each actual electrical parameter and each classification cluster set with a preset membership threshold; if the membership between an actual electrical parameter and a classification cluster set is greater than the preset membership threshold, map the actual electrical parameter to the classification cluster set; Similarly, each actual electrical parameter is mapped to a corresponding classification cluster set, and an initial classification result is output; and the initial classification result is corrected to obtain a final classification result, and various actual electrical parameter sets of the flat-panel television are obtained according to the final classification result; The initial classification result is corrected to obtain the final classification result, which is specifically: Obtaining initial classification results, and obtaining actual electrical parameters belonging to each classification cluster according to the initial classification results; Calculating the weighted average of the actual electrical parameters belonging to each classification cluster, and determining the cluster center of each classification cluster according to the weighted average; Calculate the Hamming distance between each actual electrical parameter in each classification cluster and its cluster center, and compare the Hamming distance between each actual electrical parameter in each classification cluster and its cluster center with a preset distance threshold; If the Hamming distance between a certain actual electrical parameter in a certain classification cluster and its cluster center is greater than a preset distance threshold, the actual electrical parameter in the classification cluster is marked as a classification singular actual electrical parameter; If a certain actual electrical parameter is marked as a classification singular actual electrical parameter, the classification singular actual electrical parameter is screened out from the classification cluster to which it currently belongs; and the classification singular actual electrical parameter is simulated and assigned to the remaining classification clusters, and the Hamming distance between the classification singular actual electrical parameter and the cluster centers of the remaining classification clusters is calculated; If the Hamming distances between the singular actual electrical parameter of the classification and the cluster centers of the other classification clusters are all greater than the preset distance threshold, it means that the singular actual electrical parameter of the classification is noise data, and the singular actual electrical parameter of the classification is completely screened out; If the Hamming distance between the classification singular actual electrical parameter and the cluster center of one of the other classification clusters is not greater than the preset distance threshold, it means that the classification singular actual electrical parameter actually belongs to the classification cluster, and the classification singular actual electrical parameter is allocated to the classification cluster; This process is repeated in this way until the actual electrical parameters in each classification cluster are corrected to obtain the final classification result. Among them, the electrical functions of the flat-panel TV are analyzed according to various actual electrical parameter sets of the flat-panel TV, and the electrical analysis results are obtained, specifically: Acquiring preset electrical requirement information of the flat-panel television set, determining various standard electrical parameter sets of the flat-panel television set during the detection process according to the preset electrical requirement information; and acquiring various actual electrical parameter sets of the flat-panel television set; Calculating the Jaccard similarity coefficients between various actual electrical parameter sets of the flat-panel television and the corresponding standard electrical parameter sets; and comparing the Jaccard similarity coefficients between various actual electrical parameter sets of the flat-panel television and the corresponding standard electrical parameter sets with a preset coefficient threshold; If the Jaccard similarity coefficient between a certain actual electrical parameter set of the flat-panel TV and the corresponding standard electrical parameter set is greater than a preset coefficient threshold, the corresponding actual electrical parameter is calibrated as a type of electrical parameter; If the Jaccard similarity coefficient between a certain actual electrical parameter set of the flat-panel TV and the corresponding standard electrical parameter set is not greater than a preset coefficient threshold, the corresponding actual electrical parameter is calibrated as a second-class electrical parameter; It is determined whether there are second-category electrical parameters among various actual electrical parameters of the flat-panel television. If not, the flat-panel television is determined to be a qualified product in electrical testing; if so, the flat-panel television is determined to be a failed product in electrical testing.

Images