Defect detection method and system for mobile phone electronic components

Abstract

The present invention relates to the field of quality control technology, specifically to a defect detection method and system for mobile phone electronic components, comprising the following steps: based on the mobile phone circuit design requirements, selecting a current source and a control element, setting the current size and injection frequency of the electronic components, adjusting the circuit parameters to reach a preset standard, and obtaining the current injection configuration. In the present invention, by forming a continuous data sequence and optimizing the real-time processing and analysis of data, not only the defect recognition speed is improved, but also the data accuracy in the detection process is enhanced, subtle defects can be identified in the early stage, and costly post-processing can be avoided. By combining thermal imaging technology, the defect position can be accurately located through hot spot analysis, so that subsequent repair measures are more targeted, the rework rate is reduced, production efficiency and product quality are improved, the intelligent level of the production process of mobile phone electronic components is improved, and the real-time control and defect detection capabilities of the production line are enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of quality control, and in particular to a defect detection method and system for mobile phone electronic components. Background Art

[0002] The field of quality control technology aims to monitor, evaluate and ensure that product quality meets specific standards, including the entire process from raw material inspection to finished product inspection, using a variety of technologies and tools to identify defects and inconsistencies in the manufacturing process. Quality control methods include statistical quality control (SQC), six sigma management, failure mode and effect analysis (FMEA), etc., and the technologies involved range from simple visual inspection to automation and computer-aided inspection systems. Technology helps improve product reliability, optimize production processes, reduce scrap rates, and bring economic benefits and competitive advantages to companies.

[0003] Among them, defect detection methods for mobile phone electronic components refer to technologies and processes used to identify and analyze physical, electrical or functional defects that occur in mobile phone components during the production process. The purpose is to ensure that all components meet quality standards before being assembled into mobile phones, reduce the return rate and improve user satisfaction. Through detection technology, problems can be discovered at an early stage, avoiding costly later product recalls, while ensuring the durability and reliability of the product.

[0004] The main problem that existing technologies face in the rapidly developing electronics manufacturing industry is the lack of high automation and real-time feedback mechanisms. Although a variety of quality control methods are used, they focus on post-analysis rather than prevention and real-time monitoring. For example, in the traditional defect detection process, some subtle electrical or functional defects are difficult to identify before product assembly, resulting in high return rates and reduced user satisfaction. The analysis of defects is not in-depth enough to accurately locate the specific location and type of defects, affecting the effectiveness of repair measures. The lack of high-precision detection technology for complex electronic components has limited production efficiency, and in some cases, traditional technologies have failed to detect defects in time, resulting in costly product recalls and damaged brand reputation. The shortcomings of existing technologies are particularly prominent in modern electronic manufacturing, and they urgently need to be overcome through highly automated and intelligent solutions. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a defect detection method and system for mobile phone electronic components.

[0006] In order to achieve the above object, the present invention adopts the following technical scheme, a method for detecting defects of mobile phone electronic components, comprising the following steps:

[0007] S1: Based on the design requirements of the mobile phone circuit, select the current source and control components, set the current size and injection frequency of the electronic components, adjust the circuit parameters to meet the preset standards, and obtain the current injection configuration;

[0008] S2: using the current injection configuration, installing a resistance measuring device, monitoring the resistance change caused by the current in the circuit in real time, recording the data to form a continuous time series, and obtaining resistance time series data;

[0009] S3: performing trend analysis and pattern recognition on resistance changes through the resistance time series data, recording data points that deviate from the normal range, and generating abnormal detection results;

[0010] S4: Based on the abnormality detection result, the defect position of the mobile phone electronic component is identified, and the shape and size information of the defect is analyzed by comparing with the electronic component design data, and the heat source point and heat setting are selected according to the defect type and the position in the electronic component to obtain a heat source application plan;

[0011] S5: adopting the heat source application plan, adjusting the output and position of the local heat source, using infrared thermal imaging technology to monitor and record the heat flux distribution during the heating process, identifying abnormal hot spots, and obtaining a heat flux distribution data set;

[0012] S6: Analyze the correlation between abnormal hot spots and preset sensitive areas in component design data through the heat flux distribution data set, record the types and properties of defects, and generate a defect detection log.

[0013] As a further solution of the present invention, the current injection configuration includes the set current value, frequency, voltage and impedance, the resistance time series data includes the recorded resistance value, the corresponding time point and the current size, the abnormality detection result includes the identified abnormal resistance value, the corresponding time point and the degree of abnormality, the heat source application plan includes the selected heat source location, heat size and heating time, the heat flux distribution data set includes the recorded temperature value, the corresponding location and time point, and the defect detection log includes the defect type, location, size, shape, and comparison information with the preset sensitive area.

[0014] As a further solution of the present invention, based on the mobile phone circuit design requirements, the current source and control element are selected, the current size and injection frequency of the electronic components are set, and the circuit parameters are adjusted to reach the preset standards. The steps of obtaining the current injection configuration are specifically as follows:

[0015] S101: Based on the mobile phone circuit design requirements, select the current source and control components, install them on the mobile phone circuit board, connect the test device, check the compatibility and stability with the circuit board, weld and fix the connection points, check the fluidity of the current, and obtain the current source installation configuration;

[0016] S102: using the current source installation configuration, adjusting the current magnitude and injection frequency, setting the current value through the current adjustment knob, using the frequency generator to set the required injection frequency, and monitoring the stability of the current and frequency in real time, checking whether the predetermined performance parameters are achieved, and obtaining the parameter adjustment results;

[0017] S103: Based on the parameter adjustment result, by adjusting the current gain and frequency compensation, continuous performance testing is performed to verify the stable operation efficiency of the circuit under predetermined conditions, and a current injection configuration is obtained.

[0018] As a further solution of the present invention, the current injection configuration is adopted, a resistance measuring device is installed, the resistance change caused by the current in the circuit is monitored in real time, and the data is recorded to form a continuous time series. The steps of obtaining the resistance time series data are specifically as follows:

[0019] S201: using the current injection configuration, installing a resistance measuring device, setting the device monitoring mode to automatically record changes in resistance values, and obtaining resistance measurement data by continuously monitoring real-time current changes;

[0020] S202: using the resistance measurement data, configuring the sampling frequency of the data recorder, connecting the data recording device and the measuring device, synchronizing the timestamp to check the consistency of the data, and obtaining the resistance time series record by recording the resistance value at each time point in real time;

[0021] S203: Based on the resistance time series record, identify and record key time points of resistance value changes to generate resistance time series data.

[0022] As a further solution of the present invention, the steps of performing trend analysis and pattern recognition on resistance changes through the resistance time series data, recording data points that deviate from the normal range, and generating abnormal detection results are specifically as follows:

[0023] S301: using the resistance time series data, identifying the long-term and short-term change patterns of the resistance value, using the sliding window technology to divide the data sequence, analyzing the statistical characteristics of the resistance value in the time window, and generating trend analysis results;

[0024] S302: Based on the trend analysis result, a threshold value of normal resistance change is set, a deviation between the differentiated data point and the threshold value is compared, abnormal data points exceeding the threshold value are marked, and a timestamp and resistance value of the abnormal data point are recorded to obtain a record of the abnormal data point;

[0025] S303: Classifying the patterns of the abnormal data points through the abnormal data point records, evaluating potential circuit problems, formulating abnormal response measures, and generating abnormal detection results.

[0026] As a further solution of the present invention, based on the abnormality detection results, the defect position of the mobile phone electronic component is identified, and the shape and size information of the defect is analyzed by comparing with the electronic component design data, and the heat source point and heat setting are selected according to the defect type and the position in the electronic component. The steps of obtaining the heat source application plan are specifically as follows:

[0027] S401: using the abnormal detection result, combined with the CAD model of the mobile phone electronic component, using the principal component analysis algorithm, performing dimensionality reduction processing on the abnormal data points to identify the location of the defective part, and recording the coordinates of the defective part and the deviation from the normal component model, to generate a defect location identification result;

[0028] S402: Based on the defect position identification result, analyze the shape and size information of the defect, measure the diameter of the defect, adjust the analysis parameters according to the defect type and size, record the data of the defect shape and size, and obtain the defect shape and size analysis result;

[0029] S403: Using the defect shape and size analysis results, analyze the heat source points and heat settings required for repair, select heating equipment and parameters, and formulate a heat source application plan based on the defects of differentiated types and locations.

[0030] As a further solution of the present invention, the formula of the principal component analysis algorithm is as follows:

[0031] in, is the principal component score of the defect part, For the The weight coefficient of each dimension, For abnormal data points The actual measured values ​​in the dimensions, Under normal conditions The average value of the dimensions, For the The standard deviation of the dimension, For Dimension The sensitivity coefficient, For Dimension The actual measured value on For Dimension The expected average value of For Dimension The standard deviation of and is the adjustment coefficient, and The dimensions are and The number of

[0032] As a further solution of the present invention, the steps of adopting the heat source application plan, adjusting the output and position of the local heat source, using infrared thermal imaging technology to monitor and record the heat flux distribution during the heating process, identifying abnormal hot spots, and obtaining the heat flux distribution data set are specifically as follows:

[0033] S501: using the heat source application plan, adjusting the output power and position of the heat source to match the defect position and size requirements of the target, verifying that the heat energy evenly covers the target area by adjusting the heat source, and generating an adjusted heat source setting;

[0034] S502: Using the adjusted heat source setting, the heating process is monitored in real time, the flow and distribution of heat energy on the surface of the component are recorded, the thermal image data at different time points are captured, the dynamic change of heat flow is analyzed, and the real-time heat flow monitoring record is obtained;

[0035] S503: Based on the real-time heat flow monitoring record, analyze the heat flow data, identify abnormal hot spots in the heating process, and record the location and characteristics of the abnormal hot spots by comparing the differences between the hot spots and the surrounding normal temperature areas to generate a heat flow distribution data set.

[0036] As a further solution of the present invention, the steps of analyzing the correlation between abnormal hot spots and preset sensitive areas in the component design data through the heat flux distribution data set, recording the types and properties of defects, and generating defect detection logs are specifically as follows:

[0037] S601: using the heat flow distribution data set, comparing and analyzing abnormal hot spots and sensitive areas preset in the mobile phone component design data, identifying the spatial correspondence between the hot spots and the sensitive areas, and evaluating the degree of association, analyzing the impact of the hot spots on the functions of the mobile phone electronic components, and generating abnormal hot spot association analysis results;

[0038] S602: Using the abnormal hotspot association analysis result, a convolutional neural network algorithm is used to calculate the metric value of the defect type, perform feature recognition of the abnormal hotspot and mapping of sensitive areas, and obtain a defect classification record value;

[0039] S603: Analyze the defect type and nature of the abnormal point according to the defect classification record value, and monitor the defect problems of the mobile phone electronic components in real time with reference to the type, location and impact of the defect, and generate a defect detection log.

[0040] As a further solution of the present invention, the formula of the convolutional neural network algorithm is as follows:

[0041] in, is the defect type metric, Represents the height value of the hotspot. Represents the width of the hotspot. represents the heat flow threshold, represents the actual measured heat flow value, Represents the maximum allowable thermal capacity. A defect detection system for mobile phone electronic components, the defect detection system for mobile phone electronic components is used to execute the above-mentioned defect detection method for mobile phone electronic components, the system comprises:

[0042] The circuit parameter configuration module selects the target current source and control element, sets the current magnitude and injection frequency of the electronic components, adjusts the circuit parameters to the preset standards, and obtains the current injection configuration;

[0043] The resistance monitoring module uses the current injection configuration, installs a resistance measuring device, monitors the resistance change caused by the current in the circuit in real time, and obtains the resistance time series result;

[0044] The abnormal analysis module analyzes the resistance change trend through the resistance time series results, identifies and records the data points that deviate from the normal range, and generates abnormal detection results;

[0045] The heat source configuration module analyzes the shape and size of the defective parts according to the abnormality detection results, sets matching heat source points and heat parameters, and establishes a heat source application plan;

[0046] The heat flow monitoring module uses the heat source application plan to adjust the output and position of the heat source, uses infrared thermal imaging technology to monitor the heat flow distribution during the heating process, identifies abnormal hot spots, records the types and properties of defects in mobile phone electronic components, and obtains a defect detection log.

[0047] Compared with the prior art, the advantages and positive effects of the present invention are:

[0048] In the present invention, the accuracy of defect detection is greatly improved by finely adjusting the current injection parameters and monitoring the resistance change in real time. By forming a continuous data sequence and optimizing the real-time processing and analysis of data, not only the defect recognition speed is improved, but also the data accuracy in the detection process is enhanced. Minor defects can be identified at an early stage to avoid costly post-processing. By combining thermal imaging technology, the defect position can be accurately located through hot spot analysis, making subsequent repair measures more targeted, effectively reducing the rework rate, and improving production efficiency and product quality. Through automated analysis and trend prediction, the intelligence level of the production process of mobile phone electronic components is improved, and the real-time control and defect detection capabilities of the production line are enhanced. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a schematic diagram of the workflow of the present invention;

[0050] Figure 2 This is a detailed flow chart of S1 of the present invention;

[0051] Figure 3 This is a detailed flow chart of S2 of the present invention;

[0052] Figure 4 This is a detailed flow chart of S3 of the present invention;

[0053] Figure 5 This is a detailed flow chart of S4 of the present invention;

[0054] Figure 6 This is a detailed flow chart of S5 of the present invention;

[0055] Figure 7 This is a detailed flow chart of S6 of the present invention;

[0056] Figure 8 It is a system flow chart of the present invention. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0058] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0059] See also Figure 1 The present invention provides a technical solution, a method for detecting defects in mobile phone electronic components, comprising the following steps:

[0060] S1: Based on the design requirements of the mobile phone circuit, select the current source and control components, set the current size and injection frequency of the electronic components, adjust the circuit parameters to meet the preset standards, and obtain the current injection configuration;

[0061] S2: Use current injection configuration, install resistance measurement equipment, monitor the resistance change caused by current in the circuit in real time, record data to form a continuous time series, and obtain resistance time series data;

[0062] S3: Perform trend analysis and pattern recognition on resistance changes through resistance time series data, record data points that deviate from the normal range, and generate abnormal detection results;

[0063] S4: Based on the abnormality detection results, the defect location of the mobile phone electronic components is identified, and the shape and size information of the defect is analyzed by comparing with the electronic component design data. According to the defect type and the location in the electronic component, the heat source point and heat setting are selected to obtain the heat source application plan;

[0064] S5: Adopt the heat source application plan, adjust the output and position of the local heat source, use infrared thermal imaging technology to monitor and record the heat flux distribution during the heating process, identify abnormal hot spots, and obtain the heat flux distribution data set;

[0065] S6: Analyze the correlation between abnormal hot spots and preset sensitive areas in component design data through heat flow distribution data set, record the types and properties of defects, and generate defect detection logs.

[0066] The current injection configuration includes the set current value, frequency, voltage and impedance. The resistance time series data includes the recorded resistance value, the corresponding time point and the current size. The anomaly detection results include the identified abnormal resistance value, the corresponding time point and the degree of anomaly. The heat source application plan includes the selected heat source location, heat size and heating time. The heat flux distribution data set includes the recorded temperature value, the corresponding location and time point. The defect detection log includes the defect type, location, size, shape, and comparison information with the preset sensitive area.

[0067] See also Figure 2 , based on the mobile phone circuit design requirements, select the current source and control components, set the current size and injection frequency of the electronic components, adjust the circuit parameters to meet the preset standards, and obtain the current injection configuration steps as follows:

[0068] S101: Based on the mobile phone circuit design requirements, select the current source and control components, install them on the mobile phone circuit board, connect the test device, check the compatibility and stability with the circuit board, weld and fix the connection points, check the fluidity of the current, and obtain the execution process of the current source installation configuration as follows;

[0069] Select suitable current sources and control components and install them on the mobile phone circuit board. The specific process involves selecting a current source that matches the mobile phone circuit design parameters to ensure that the current output is consistent with the input requirements of the mobile phone circuit board. At the same time, select control components, such as current regulators and frequency regulators, to ensure that the changes in current and frequency can be accurately controlled. The connection test device mainly includes connecting current and frequency monitoring equipment to evaluate the interface compatibility between the current source and the mobile phone circuit board, evaluating the load-bearing capacity of the circuit board and the response speed to current and frequency changes, welding fixed connection points and ensuring a stable connection between the current source and the circuit board through welding technology to prevent loose or disconnected connections during subsequent use. Checking the fluidity of the current includes monitoring whether the current is evenly distributed in the circuit board to ensure that the flow of current on the board will not affect the normal operation of the mobile phone due to local overheating or short circuits, and obtaining the current source installation configuration.

[0070] S102: Use the current source installation configuration to adjust the current size and injection frequency, set the current value through the current adjustment knob, use the frequency generator to set the required injection frequency, and monitor the stability of the current and frequency in real time to check whether the predetermined performance parameters are achieved. The execution process of obtaining the parameter adjustment results is as follows;

[0071] Adjust the current size and injection frequency according to the formula and , calculate the required current and frequency In the formula, represents voltage, represents resistance, Represents the time period. Refer to a simplified circuit where the voltage Set to 5 volts, resistor Assuming it is 10 ohms, according to Ohm's law , calculate the current for . Set the time period is 0.1 seconds, according to the frequency calculation formula , and the frequency is This indicates that the circuit will have 10 cycles of current fluctuation per second. This parameter setting allows precise control of current and frequency changes to meet the performance requirements of the circuit.

[0072] S103: Based on the parameter adjustment result, by adjusting the current gain and frequency compensation, a continuous performance test is performed to verify the stable operation efficiency of the circuit under predetermined conditions, and the execution process of the current injection configuration is obtained as follows;

[0073] The continuous performance test includes precise control of current gain and setting of frequency compensation. Current gain control involves fine-tuning the increase or decrease in current transmission to achieve the preset current output. Frequency compensation adjusts the stability of the circuit in response to different operating frequencies. The continuous performance test verifies the continuous operating efficiency of the circuit under set operating conditions. It involves running the circuit for a long time and monitoring performance indicators, such as current stability and response speed, to ensure that the circuit can maintain the predetermined performance standards under different operating conditions and obtain the current injection configuration.

[0074] See also Figure 3 , using current injection configuration, installing resistance measurement equipment, real-time monitoring of resistance changes caused by current in the circuit, recording data to form a continuous time series, the steps to obtain resistance time series data are as follows:

[0075] S201: Using the current injection configuration, installing the resistance measurement device, setting the device monitoring mode to automatically record the change of the resistance value, and obtaining the resistance measurement data by continuously monitoring the real-time current change is as follows;

[0076] Connect the resistance measuring device to the circuit and ensure that the device is correctly matched with the current source. Set the device monitoring mode to automatic to capture and record any changes in resistance value in real time. The automatic recording function in this process ensures that the resistance value change from the start of current source injection to the end of measurement can be continuously monitored to evaluate the stability of the circuit and the performance of the resistor element. Continuous monitoring of real-time current changes is mainly achieved through current detection instruments. The instrument can accurately capture the instantaneous changes in current and associate them with the resistance change data to provide a comprehensive evaluation of resistance performance and obtain resistance measurement data.

[0077] S202: Using the resistance measurement data, configure the sampling frequency of the data recorder, connect the data recording device and the measuring device, synchronize the timestamp to check the consistency of the data, and obtain the resistance time series record by real-time recording the resistance value at each time point. The execution process is as follows;

[0078] Using resistance measurement data to configure the sampling frequency of the data recorder involves selecting a suitable sampling frequency to most accurately reflect the speed and mode of resistance change. Synchronizing timestamps during the configuration process ensures the consistency of the measurement data, that is, all recorded resistance values ​​are accurately marked with the measurement time, ensuring the effectiveness of data analysis. Connecting the data recording device to the measuring device mainly involves physical connection and data transmission configuration, ensuring that data can be accurately transmitted from the measuring device to the recorder, recording the resistance value at each time point in real time, and reflecting in detail the dynamic changes of resistance over time, providing basic data for further data analysis, and obtaining resistance time series records.

[0079] S203: Based on the resistance time series record, identify and record the key time points of the resistance value change, and generate the resistance time series data. The execution process is as follows;

[0080] Identify and record the key time points of resistance value change, according to the formula , calculate the resistance In the formula, represents voltage, Represents the current. Sets the voltage measured at a critical point in time is 10 volts, the current is 2 amperes, according to Ohm's law , the calculated resistance for By monitoring the resistance value at key time points, the performance stability of the circuit and its performance under different working conditions can be analyzed. By calculating the resistance value in real time, data support can be provided for the maintenance and optimization of the circuit to ensure long-term stable operation of the circuit.

[0081] See also Figure 4 ,Through the resistance time series data, the resistance change is trend analyzed and pattern recognized, and the data points deviating from the normal range are recorded. The steps to generate the abnormal detection results are as follows:

[0082] S301: Using the resistance time series data, identifying the long-term and short-term change patterns of the resistance value, using the sliding window technology to divide the data series, analyzing the statistical characteristics of the resistance value within the time window, and generating the trend analysis results. The execution process is as follows;

[0083] Use sliding window technology to divide the data sequence according to the formula Calculate the average resistance value within the window In the formula, Representative The resistance value of each data point is Represents the number of data points. Formula explanation and formula calculation derivation process: Set a sliding window containing 5 data points, and the resistance values ​​are 10Ω, 12Ω, 11Ω, 13Ω, and 9Ω respectively. According to the average value formula, the average value of the resistance in the window is calculated as This average value helps identify the statistical characteristics of the resistance value within a specific time window and generates trend analysis results of the resistance change, which is a key step in understanding the resistance change pattern over time. By calculating the average value, the short-term fluctuations and long-term change trends of the resistance can be captured.

[0084] S302: Based on the trend analysis result, a threshold value of normal resistance change is set, the deviation of the differentiated data point and the threshold value is compared, the abnormal data point exceeding the threshold value is marked, and the timestamp and resistance value of the abnormal data point are recorded. The execution process of obtaining the abnormal data point record is as follows;

[0085] Setting a threshold for normal resistance change involves determining a threshold based on historical resistance data and statistical analysis. The threshold is used to identify abnormal resistance values. The threshold is determined based on the average value and standard deviation of the resistance value. Comparing the deviation of differentiated data points from the threshold is achieved by calculating the difference between each data point and the threshold. Marking abnormal data points that exceed the threshold includes recording the resistance value and timestamp of the point. Recording the timestamp and resistance value of the abnormal data point is for detailed tracking of data points indicating circuit problems, helping to further analyze the stability of the circuit and identify potential circuit failures, and obtaining abnormal data point records.

[0086] S303: By recording abnormal data points, classifying the patterns of abnormal data points, evaluating potential circuit problems, and formulating abnormal response measures, the execution process of generating abnormal detection results is as follows;

[0087] The patterns of abnormal data points are classified. This process involves analyzing the occurrence patterns and causes of abnormal data points. Potential circuit problems are evaluated by conducting in-depth analysis of the changes in resistance values ​​behind the abnormal data points. Abnormal response measures are formulated, including preventive maintenance of the circuit problems or replacement of affected components. This provides a scientific basis for circuit maintenance, not only showing the type and frequency of abnormal data points, but also revealing the severity and urgency of potential problems, ensuring the long-term stability and safe operation of the circuit system, and generating abnormal detection results.

[0088] See also Figure 5 Based on the anomaly detection results, the defect locations of mobile phone electronic components are identified. By comparing with the electronic component design data, the shape and size information of the defects are analyzed. According to the defect type and location in the electronic component, the heat source point and heat setting are selected. The specific steps of obtaining the heat source application plan are as follows:

[0089] S401: Using the abnormal detection results, combined with the CAD model of the mobile phone electronic parts, the principal component analysis algorithm is used to perform dimensionality reduction processing on the abnormal data points to identify the location of the defective part, and the coordinates of the defective part and the deviation from the normal part model are recorded. The execution process of generating the defect position identification result is as follows;

[0090] The formula for the principal component analysis algorithm is as follows:

[0091] in, is the principal component score of the defect part, For the The weight coefficient of each dimension, For abnormal data points The actual measured values ​​in the dimensions, Under normal conditions The average value of the dimensions, For the The standard deviation of the dimension, For Dimension The sensitivity coefficient, For Dimension The actual measured value on For Dimension The expected average value of For Dimension The standard deviation of and is the adjustment coefficient, and The dimensions are and The number of

[0092] The formula uses principal component analysis (PCA) to locate the defect. The numerator of the formula involves the sum of the weighted deviations of the original dimension and the newly added dimension, and the denominator is the square root of the sum of the squares of the standard deviations of the original dimension and the newly added dimension, which is used to normalize the results. The parameters are explained in detail as follows:

[0093] It is The weight coefficient of the original dimension is assigned according to the importance of the dimension in defect detection. It is obtained by analyzing the historical failure data obtained from the relevant departments. Assuming that in a specific case, , ;

[0094] The abnormal data point is The actual measurement value of the original dimension is directly monitored by the sensor, and is set in a specific detection. , ;

[0095] Under normal conditions, The average value of the original dimensions is obtained through historical quality control data. Set , ;

[0096] It is The standard deviation of the original dimension is determined based on statistical analysis of historical data, for example, , ;

[0097] , , and are parameters related to the newly added dimension, obtained and set in the same way as the original dimension. , , , ;

[0098] and It is the adjustment coefficient, which is used to balance the impact of the original dimension and the new dimension. The coefficient is determined through simulation experiments and optimization algorithms. , ;

[0099] Calculation process example:

[0100] For the original dimension, calculate the weighted bias:

[0101] ;

[0102] For the newly added dimension, calculate the weighted deviation:

[0103] ;

[0104] Calculation of the denominator:

[0105] ;

[0106] Calculation of value:

[0107]

[0108] This result shows that the calculated A larger value means a larger deviation from the normal data, indicating that the defective part is more obvious, which in turn determines whether the component needs further inspection or replacement. The numerical result reflects the degree of deviation between the abnormal data point and the normal range, which helps to accurately locate the defect.

[0109] S402: Based on the defect position identification result, the shape and size information of the defect is analyzed, the diameter of the defect is measured, the analysis parameters are adjusted according to the defect type and size, the data of the defect shape and size are recorded, and the execution process of obtaining the defect shape and size analysis result is as follows;

[0110] The geometric features of the defect shape are measured in detail. The diameter of the defect is measured by using precision measuring tools such as calipers or micrometer screw gauges. The analysis parameters are adjusted according to the type and size of the defect, including adjusting the resolution and contrast of the image analysis software to better visually identify the defect details. Recording the data of the defect shape and size is crucial to understanding the causes and potential impacts of defect formation, and obtaining the defect shape and size analysis results.

[0111] S403: Using the defect shape and size analysis results, analyzing the heat source points and heat settings required for repair, selecting heating equipment and parameters, and formulating the execution process of the heat source application plan according to the defects of differentiated types and locations are as follows;

[0112] The key to selecting the right heating equipment and parameter settings to suit defects of different types and locations is to ensure the accuracy and efficiency of the repair work, calculate the required amount of heat and select the best heating point location to ensure that the material at the defect is heated evenly and fully, avoid further damage or repair failure caused by overheating or insufficient heating, ensure that the heat and heating technology used in the repair process can restore the function and appearance of the component to the maximum extent, and develop a heat source application plan.

[0113] See also Figure 6 , adopt the heat source application plan, adjust the output and position of the local heat source, use infrared thermal imaging technology to monitor and record the heat flux distribution during the heating process, identify abnormal hot spots, and obtain the heat flux distribution data set. The specific steps are:

[0114] S501: Adopt the heat source application plan, adjust the output power and position of the heat source, match the defect position and size requirements of the target, verify that the heat energy evenly covers the target area by adjusting the heat source, and generate the execution process of the adjusted heat source setting as follows;

[0115] Adjust the output power and position of the heat source to match the specific location and size requirements of the target defect. In this process, adjusting the heat source mainly involves precise control of the output power of the heat source and precise positioning of the heat source to ensure that the heat energy can evenly cover the entire target area. Verifying that the heat energy evenly covers the target area is by using a thermal imager or thermal sensing equipment to monitor the distribution of the heat energy generated by the heat source in the target area to confirm the uniformity of the heat distribution and the appropriateness of the heat, providing important information on how to optimize the application of the heat source to improve the efficiency and quality of repair, and generating the adjusted heat source settings.

[0116] S502: Using the adjusted heat source settings, the heating process is monitored in real time, the flow and distribution of heat energy on the surface of the component are recorded, the thermal image data at different time points are captured, the dynamic changes of the heat flow are analyzed, and the execution process of obtaining the real-time heat flow monitoring record is as follows;

[0117] Use thermal imaging cameras or temperature sensors to record the flow and distribution of heat on the surface of components. The monitoring process is to ensure that the adjustment of the heat source is consistent with the actual heating effect. The thermal imaging data captured at different time points is mainly to analyze the dynamic changes of heat flow during the heating process. It can timely adjust the heat source settings or further optimize the heating program. It can provide basic data for subsequent analysis, help understand the heating effect and predict heating problems, and obtain real-time heat flow monitoring records.

[0118] S503: Based on the real-time heat flow monitoring record, analyze the heat flow data, identify the abnormal hot spots in the heating process, and record the location and characteristics of the abnormal hot spots by comparing the differences between the hot spots and the surrounding normal temperature areas. The execution process of generating the heat flow distribution data set is as follows;

[0119] The heat flow data is analyzed in detail to find any abnormally high or low temperature areas. By comparing the differences between the hot spots and the surrounding normal temperature areas, the specific location and characteristics of the abnormal hot spots can be located. The location and characteristics of the abnormal hot spots are recorded to provide detailed information for further diagnosis and repair strategy formulation, to provide a scientific basis for repair work, to ensure the correctness of heat source application and the safety of the heating process, and to generate a heat flow distribution data set.

[0120] See also Figure 7 , through the heat flow distribution data set, analyze the correlation between abnormal hot spots and preset sensitive areas in the component design data, record the types and properties of defects, and generate defect detection logs in the following steps:

[0121] S601: using the heat flow distribution data set, comparing and analyzing the abnormal hot spots and the preset sensitive areas in the mobile phone component design data, identifying the spatial correspondence between the hot spots and the sensitive areas, and evaluating the degree of association, analyzing the impact of the hot spots on the functions of the mobile phone electronic components, and generating the abnormal hot spot association analysis results. The execution process is as follows;

[0122] Accurately measure and locate abnormal hotspots, and spatially match them with sensitive areas in the design data. Identifying the spatial correspondence between hotspots and sensitive areas is mainly achieved through advanced image processing software or spatial analysis tools. Evaluating the degree of association is to determine the impact of abnormal hotspots on sensitive areas. Analyzing the impact of hotspots on the functions of mobile phone electronic components involves evaluating the changes in circuit performance or physical damage caused by hotspots, which is used to guide further maintenance or design improvement measures, ensure the functional safety and stable performance of the mobile phone, and generate abnormal hotspot association analysis results.

[0123] S602: Based on the abnormal hotspot correlation analysis results, a convolutional neural network algorithm is used to calculate the metric value of the defect type, perform feature recognition of the abnormal hotspot and mapping of the sensitive area, and obtain the defect classification record value. The execution process is as follows;

[0124] The formula of the convolutional neural network algorithm is as follows:

[0125] in, is the defect type metric, Represents the height value of the hotspot. Represents the width of the hotspot. represents the heat flow threshold, represents the actual measured heat flow value, Represents the maximum allowable heat capacity.

[0126] The formula is used to calculate the comprehensive metric value of the defect type of an abnormal hot spot in the equipment, where the specific sources of the parameters are as follows:

[0127] (Hotspot height value): Get the sensor data from the device and set the monitored hotspot height to 0.5 meters;

[0128] (Hotspot width value): also obtained through internal sensor monitoring, the hotspot width monitoring value is set to 0.3 meters;

[0129] (Heat flow threshold): Determined by the equipment manufacturing standard, this threshold is set at 1500W / m2, which is a standard value based on the upper limit of safe operation of the equipment;

[0130] (Actual heat flow value): Real-time monitoring by heat flow sensor, assuming that a certain monitoring result is 1600W / m2;

[0131] (Maximum allowable heat capacity): Based on the equipment design parameters, this value is set to 2500 J / K and is used to describe the maximum amount of heat that the equipment can withstand without causing damage;

[0132] Substituting parameter values ​​into the calculation process is as follows:

[0133] calculate ,Right now ,calculate ,Right now The square root of

[0134] According to the formula , substitute the value into:

[0135]

[0136] The results show that under given measurement conditions and parameter settings, the obtained defect type comprehensive metric value The value is 0.3, which reflects the abnormality of the hotspot. The larger the value, the higher the abnormality. This result is used for further equipment diagnosis and safety assessment, indicating that the current abnormal hotspot has a low risk level, but it still needs to be continuously monitored to ensure equipment safety.

[0137] S603: According to the defect classification record value, the defect type and nature of the abnormal point are analyzed, and the defect problem of the mobile phone electronic components is monitored in real time with reference to the type, location and impact of the defect. The execution process of generating the defect detection log is as follows;

[0138] In-depth analysis is conducted on the data in the defect classification record values ​​to identify the specific type and nature of the defects. The type, location and impact of the defects are referenced in order to develop more effective maintenance strategies or improvement measures. Real-time monitoring of defects in mobile phone electronic components is mainly achieved through continuous performance testing and condition monitoring. Providing detailed defect development records and status updates to maintenance teams and designers is the basis for ensuring product quality and user satisfaction, and generating defect detection logs.

[0139] See also Figure 8 , A defect detection system for mobile phone electronic components, the defect detection system for mobile phone electronic components is used to execute the above-mentioned defect detection method for mobile phone electronic components, the system comprises:

[0140] The circuit parameter configuration module selects the target current source and control element, sets the current magnitude and injection frequency of the electronic components, adjusts the circuit parameters to the preset standards, and obtains the current injection configuration;

[0141] The resistance monitoring module uses current injection configuration and installs resistance measurement equipment to monitor the resistance change caused by current in the circuit in real time and obtain the resistance time series results;

[0142] The abnormal analysis module analyzes the resistance change trend through the resistance time series results, identifies and records the data points that deviate from the normal range, and generates abnormal detection results;

[0143] The heat source configuration module analyzes the shape and size of defective parts based on the abnormality detection results, sets matching heat source points and heat parameters, and establishes a heat source application plan;

[0144] The heat flow monitoring module uses the heat source application plan to adjust the output and position of the heat source, uses infrared thermal imaging technology to monitor the heat flow distribution during the heating process, identifies abnormal hot spots, records the types and properties of defects in mobile phone electronic components, and obtains a defect detection log.

[0145] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A method for detecting defects in mobile phone electronic components, characterized in that: The following steps are involved: Based on the design requirements of the mobile phone circuit, select the current source and control components, set the current size and injection frequency of the electronic components, adjust the circuit parameters to meet the preset standards, and obtain the current injection configuration; Using the current injection configuration, installing a resistance measuring device, setting the device monitoring mode to automatically record changes in resistance values, and obtaining resistance measurement data by continuously monitoring real-time current changes; Using the resistance measurement data, configure the sampling frequency of the data recorder, connect the data recording device and the measuring device, synchronize the timestamp to check the consistency of the data, and obtain the resistance time series record by recording the resistance value at each time point in real time; Based on the resistance time series record, identifying and recording key time points of resistance value changes to generate resistance time series data; Using the resistance time series data, identifying the long-term and short-term change patterns of the resistance value, using the sliding window technology to divide the data series, analyzing the statistical characteristics of the resistance value within the time window, and generating trend analysis results; Based on the trend analysis result, a threshold value of normal resistance change is set, deviations of differentiated data points from the threshold value are compared, abnormal data points exceeding the threshold value are marked, and timestamps and resistance values ​​of the abnormal data points are recorded to obtain abnormal data point records; By recording the abnormal data points, the patterns of the abnormal data points are classified, potential circuit problems are evaluated, and abnormal response measures are formulated to generate abnormal detection results; Based on the abnormality detection results, the defect location of the mobile phone electronic component is identified, and the shape and size information of the defect is analyzed by comparing with the electronic component design data, and the heat source point and heat setting are selected according to the defect type and the location in the electronic component to obtain a heat source application plan; Adopting the heat source application plan, adjusting the output and position of the local heat source, using infrared thermal imaging technology to monitor and record the heat flux distribution during the heating process, identifying abnormal hot spots, and obtaining a heat flux distribution data set; The heat flux distribution data set is used to analyze the degree of correlation between abnormal hot spots and preset sensitive areas in the component design data, record the types and properties of defects, and generate a defect detection log.

2. The defect detection method for mobile phone electronic components according to claim 1, characterized in that: The current injection configuration includes the set current value, frequency, voltage and impedance, the resistance time series data includes the recorded resistance value, the corresponding time point and the current size, the abnormality detection result includes the identified abnormal resistance value, the corresponding time point and the degree of abnormality, the heat source application plan includes the selected heat source location, heat size and heating time, the heat flux distribution data set includes the recorded temperature value, the corresponding location and time point, and the defect detection log includes the defect type, location, size, shape, and comparison information with the preset sensitive area.

3. The defect detection method for mobile phone electronic components according to claim 1, characterized in that: Based on the design requirements of the mobile phone circuit, select the current source and control components, set the current size and injection frequency of the electronic components, adjust the circuit parameters to meet the preset standards, and obtain the current injection configuration steps as follows: Based on the mobile phone circuit design requirements, select the current source and control components, install them on the mobile phone circuit board, connect the test device, check the compatibility and stability with the circuit board, weld and fix the connection points, check the fluidity of the current, and obtain the current source installation configuration; The current source installation configuration is adopted to adjust the current magnitude and injection frequency, the current value is set by the current adjustment knob, the required injection frequency is set by the frequency generator, and the stability of the current and frequency is monitored in real time to check whether the predetermined performance parameters are achieved, and the parameter adjustment results are obtained; Based on the parameter adjustment results, by adjusting the current gain and frequency compensation, continuous performance testing is performed to verify the stable operating efficiency of the circuit under predetermined conditions, and the current injection configuration is obtained.

4. The defect detection method for mobile phone electronic components according to claim 1, characterized in that: Based on the abnormal detection results, the defect location of the mobile phone electronic component is identified, and the shape and size information of the defect is analyzed by comparing with the electronic component design data. According to the defect type and the location in the electronic component, the heat source point and heat setting are selected to obtain the heat source application plan. Specifically, the steps are as follows: The abnormal detection results are combined with the CAD model of the mobile phone electronic parts, and the principal component analysis algorithm is used to perform dimensionality reduction processing on the abnormal data points to identify the location of the defective part, and the coordinates of the defective part and the deviation from the normal part model are recorded to generate the defect position identification result; Based on the defect position identification result, analyzing the shape and size information of the defect, measuring the diameter of the defect, adjusting the analysis parameters according to the defect type and size, recording the data of the defect shape and size, and obtaining the defect shape and size analysis result; The defect shape and size analysis results are used to analyze the heat source points and heat settings required for repair, select heating equipment and parameters, and formulate a heat source application plan based on the defects of differentiated types and locations.

5. The defect detection method for mobile phone electronic components according to claim 4, characterized in that: The formula of the principal component analysis algorithm is as follows: in, is the principal component score of the defect part, For the The weight coefficient of each dimension, For abnormal data points The actual measured values ​​in the dimensions, Under normal conditions The average value of the dimensions, For the The standard deviation of the dimension, For Dimension The sensitivity coefficient, For Dimension The actual measured value on For Dimension The expected average value of For Dimension The standard deviation of and is the adjustment coefficient, and The dimensions are and The number of 6. The defect detection method for mobile phone electronic components according to claim 1, characterized in that: The steps of adopting the heat source application plan, adjusting the output and position of the local heat source, using infrared thermal imaging technology to monitor and record the heat flux distribution during the heating process, identifying abnormal hot spots, and obtaining the heat flux distribution data set are as follows: Adopting the heat source application plan, adjusting the output power and position of the heat source to match the defect position and size requirements of the target, verifying that the heat energy evenly covers the target area by adjusting the heat source, and generating an adjusted heat source setting; Using the adjusted heat source setting, the heating process is monitored in real time, the flow and distribution of heat energy on the surface of the component are recorded, the thermal image data at different time points are captured, the dynamic changes of heat flow are analyzed, and real-time heat flow monitoring records are obtained; Based on the real-time heat flow monitoring record, the heat flow data is analyzed to identify abnormal hot spots in the heating process. By comparing the difference between the hot spots and the surrounding normal temperature areas, the location and characteristics of the abnormal hot spots are recorded to generate a heat flow distribution data set.

7. The defect detection method for mobile phone electronic components according to claim 1, characterized in that: The steps of analyzing the correlation between abnormal hot spots and preset sensitive areas in the component design data through the heat flux distribution data set, recording the types and properties of defects, and generating defect detection logs are as follows: Using the heat flow distribution data set, comparing and analyzing abnormal hot spots with sensitive areas preset in the design data of mobile phone components, identifying the spatial correspondence between hot spots and sensitive areas, and evaluating the degree of association, analyzing the impact of hot spots on the functions of mobile phone electronic components, and generating abnormal hot spot association analysis results; Based on the abnormal hotspot association analysis results, a convolutional neural network algorithm is used to calculate the metric value of the defect type, perform feature recognition of the abnormal hotspot and mapping of sensitive areas, and obtain a defect classification record value; According to the defect classification record value, the defect type and nature of the abnormal point are analyzed, and the defect problems of the mobile phone electronic components are monitored in real time with reference to the type, location and impact of the defect, and a defect detection log is generated; The formula of the convolutional neural network algorithm is as follows: in, is the defect type metric, Represents the height value of the hotspot. Represents the width of the hotspot. represents the heat flow threshold, represents the actual measured heat flow value, Represents the maximum allowable heat capacity.

8. A defect detection system for mobile phone electronic components, characterized in that: According to the defect detection method for mobile phone electronic components according to any one of claims 1 to 7, the system comprises: The circuit parameter configuration module selects the target current source and control element, sets the current magnitude and injection frequency of the electronic components, adjusts the circuit parameters to the preset standards, and obtains the current injection configuration; The resistance monitoring module uses the current injection configuration, installs a resistance measuring device, monitors the resistance change caused by the current in the circuit in real time, and obtains the resistance time series result; The abnormal analysis module analyzes the resistance change trend through the resistance time series results, identifies and records the data points that deviate from the normal range, and generates abnormal detection results; The heat source configuration module analyzes the shape and size of the defective parts according to the abnormality detection results, sets matching heat source points and heat parameters, and establishes a heat source application plan; The heat flow monitoring module uses the heat source application plan to adjust the output and position of the heat source, uses infrared thermal imaging technology to monitor the heat flow distribution during the heating process, identifies abnormal hot spots, records the types and properties of defects in mobile phone electronic components, and obtains a defect detection log.

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