A high-precision quality inspection system for CNC machined parts

Abstract

The present invention relates to the technical field of high-precision quality detection, and specifically to a high-precision quality detection system for CNC machined parts, including: a data acquisition module, an intelligent calibration and analysis module, an adaptive detection and analysis module, an execution control module, and a data repository. The present invention obtains the detection data of each sensor and analyzes the displacement detection information, pressure detection information, and optical detection information to obtain the detection status information of each sensor; and obtains the measured data of each workpiece and analyzes the measured data to obtain the measured status information of each workpiece, and obtains the execution control information by receiving the detection status information and comprehensively analyzing the detection status information and the measured status information; facilitating the monitoring and control of the detection instrument, avoiding operation problems caused by long-term operation from affecting the accuracy of the detection results, and reducing the chance of greater losses caused by unqualified products flowing into the market.

Description

Technical Field

[0001] The present invention relates to the technical field of high-precision quality inspection, and specifically to a high-precision quality inspection system for CNC machined parts. Background Art

[0002] With the continuous development of modern industry, through computer numerical control technology, CNC machined parts can achieve extremely high machining precision, and the dimensional error can be controlled within a very small range. Their status is increasing day by day, and they are applied in many fields such as aerospace, automobile manufacturing, and electronic equipment. They have a high degree of automation and fast machining speed, greatly improving production efficiency.

[0003] In order to ensure production efficiency, existing CNC machined parts usually need to run for a long time. However, during long-term operation, problems such as displacement, aging, slow response, and performance degradation are likely to occur in the detection instruments and control systems for high-precision quality inspection. This not only affects the accuracy of the detection results but also may lead to unqualified products flowing into the market, causing greater losses. Summary of the Invention

[0004] The present invention provides a high-precision quality inspection system for CNC machined parts to solve the above technical problems.

[0005] In a first aspect of the present invention, a high-precision quality inspection system for CNC machined parts is provided, including a data acquisition module, an intelligent calibration and analysis module, an adaptive detection and analysis module, an execution control module, and a data repository.

[0006] The data acquisition module collects the measured data of each machined part through sensors and collects the detection data of each sensor through a detection module, and sends the measured data and the detection data to the data repository;

[0007] The measured data includes workpiece dimension data, machining parameters, and surface image data; the detection data includes displacement detection information, pressure detection information, and optical detection information.

[0008] The intelligent calibration and analysis module is used to obtain the detection data of each sensor, identify the displacement detection information, pressure detection information, and optical detection information through the detection data, analyze the displacement detection information, pressure detection information, and optical detection information to obtain the detection status information of each sensor, and send the detection status information to the adaptive detection and analysis module.

[0009] As a further improvement of the present invention, the analysis of the displacement detection information, pressure detection information, and optical detection information is as follows:

[0010] A1: Identify the induction detection range, measurement dimension information, and environmental factor data through the displacement detection information;

[0011] A11: Obtain a preset detection standard range, compare the induction detection range with the detection standard range to obtain the difference range corresponding to the current displacement detection information, calculate the area of the difference range and mark the numerical value of the area as the difference influence value, obtain the difference influence values corresponding to the displacement detection information for multiple unit times, perform variance calculation on each difference influence value to obtain the variance, and record the numerical value of the variance as the instability index swz;

[0012] A12: Obtain a preset processed standard part, and obtain the standard dimension information corresponding to the processed standard part. Compare the measured dimension information of the processed standard part with the standard dimension information to obtain a dimension difference. Divide the dimension difference into multiple dimension difference intervals, and each dimension difference interval corresponds to a dimension difference influence value. Match the dimension difference corresponding to the measured dimension information of the current processed standard part with multiple dimension difference intervals to obtain the corresponding dimension difference influence value cyz;

[0013] A13: Identify the environmental factor data to obtain the temperature and humidity data, obtain a preset temperature and humidity reference value, calculate the difference between the temperature and humidity data corresponding to the current environmental factor data and the temperature and humidity reference value to obtain the temperature and humidity difference. Compare the temperature and humidity difference with the set temperature and humidity difference threshold. When the temperature and humidity difference is greater than the temperature and humidity difference threshold, mark the part where the temperature and humidity difference exceeds the temperature and humidity difference threshold as the temperature and humidity influence value wsz;

[0014] A14: Normalize the instability index, the dimension difference influence value, and the temperature and humidity influence value and take their numerical values. According to the formula Obtain the displacement state value WY; where, m1, m2, and m3 are all preset weight factors, and their values are 3.32, 2.09, and 2.72 respectively.

[0015] A2: Identify the pressure detection information to obtain the force values of each sensor under dynamic force conditions, and the dynamic force conditions include but are not limited to the vibration, impact, and collision conditions suffered by each sensor;

[0016] A21: Obtain the force values corresponding to each unit time of the sensor, and obtain the preset force threshold corresponding to each sensor. Compare the force values corresponding to each unit time of each sensor with the corresponding force threshold. When the force value is greater than the force threshold, mark the corresponding force value as the impact force value, count the number of impact force values and record it as the impact force count, and calculate the ratio of the impact force count to the total number of force values to obtain the impact ratio cjz.

[0017] A3: Obtain a preset defective processed part, and obtain the defective standard number and defective standard position of the defective processed part;

[0018] A31: Obtain the optical detection information of each sensor corresponding to the defective workpieces, and identify the optical detection information to obtain the defect detection count and the corresponding position detection information;

[0019] A32: Calculate the difference between the defect detection count corresponding to each sensor and the defect standard count corresponding to the defective workpieces to obtain the defect error count. Set the defect error count into multiple error count intervals, and each error count interval corresponds to an error impact value. Match the defect error count corresponding to each sensor with the multiple error count intervals to obtain the corresponding error impact value;

[0020] A33: Compare the position detection information corresponding to each sensor with the defect standard position of the defective workpieces to obtain the position offset value. Obtain the preset offset threshold. When the position offset value is greater than the offset threshold, mark the part exceeding the offset threshold as the offset impact value;

[0021] A34: Construct two circles with the values of the error impact value and the offset impact value as the diameters of the two circles. Starting from and ending at the centers of the two circles, draw a line segment perpendicular to each of the two circles respectively. The length of the line segment is a fixed value. Then construct a frustum of a cone with the two circles and the line segment, calculate the volume of the frustum of the cone and mark the value of the volume as the optical state value GX.

[0022] A4: Normalize the displacement state value, the impact occupancy ratio, and the optical state value and take their values. According to the formula Calculate to obtain the detection state value jct; where, Δcjz is marked as the impact value tolerance; n1, n2, and n3 are all preset weight factors, and their values are 0.781, 0.749, and 1.021 respectively;

[0023] A5: Obtain the preset detection state threshold, compare the detection state value currently corresponding to the sensor with the detection state threshold. When the detection state value is greater than the detection state threshold, generate the corresponding detection state information as the detection state being abnormal.

[0024] The adaptive detection and analysis module is used to obtain the measured data of each workpiece and analyze the measured data to obtain the measured state information of each workpiece. By receiving the detection state information and comprehensively analyzing the detection state information and the measured state information, obtain the execution control information, and send the execution control information to the execution control module.

[0025] As a further improvement of the present invention, analyze the measured data, and the specific analysis method is as follows:

[0026] The measured data includes workpiece dimension data, machining parameters, and surface image data; obtaining the dimension values of each key dimension of each workpiece based on the workpiece dimension data, acquiring the corresponding dimension reference values for each key dimension, calculating the difference between each key dimension of each workpiece and the corresponding dimension reference value to obtain the key dimension difference, obtaining the allowable value of the dimension difference corresponding to each key dimension, when the key dimension difference is greater than the allowable value of the dimension difference, marking the corresponding key dimension difference as the dimension influence value, and calculating and summing the dimension influence values corresponding to each key dimension to obtain the total dimension influence value; the key dimensions include but are not limited to length, width, height, and hole diameter.

[0027] Identifying the cutting force and cutting temperature from the machining parameters; obtaining the preset cutting set force, calculating the difference between the cutting force corresponding to each workpiece and the cutting set force to obtain the force fluctuation value, dividing the force fluctuation value into multiple fluctuation value intervals, each fluctuation value interval corresponding to a force influence value, and matching the current force fluctuation values corresponding to each workpiece with the multiple fluctuation value intervals to obtain the corresponding force influence value;

[0028] Obtaining the preset cutting temperature threshold, comparing the cutting temperature corresponding to the current workpiece with the set cutting temperature threshold, and when the cutting temperature is greater than the cutting temperature threshold, calculating the difference between the cutting temperature and the cutting temperature threshold to obtain the temperature overflow value; calculating and summing the force influence value and the temperature overflow value to obtain the machining influence value.

[0029] Dividing the surface image data corresponding to the workpiece into multiple image blocks, obtaining the defect area corresponding to each image block, calculating and summing the curve areas of each block to obtain the total defect area corresponding to the workpiece, calculating the ratio of the total defect area to the total area of the workpiece to obtain the defect area ratio, obtaining the preset defect area threshold, and when the defect area ratio is greater than the defect area threshold, calculating the difference between the defect area and the defect area threshold to obtain the image status value.

[0030] Constructing a rhombus with the values of the total dimension influence value and the machining influence value as the two diagonals of the rhombus, starting from the intersection point of the two diagonals of the rhombus, drawing a straight line perpendicular to the rhombus, the length of the straight line being equal to the value of the image status value, and then constructing a quadrangular pyramid with the rhombus and the straight line, calculating the volume of the quadrangular pyramid and marking the value of the volume as the measured status value; when the measured status value is greater than the set threshold, generating the corresponding measured status information as the measured status being abnormal.

[0031] As a further improvement of the present invention, comprehensively analyzing the detection status information and the measured status information, and the specific analysis method is as follows:

[0032] When the measured status information is abnormal, obtain the corresponding measured status value, subtract the corresponding set threshold from the measured status value to calculate the measured status overflow value, divide the measured status overflow value into multiple status overflow intervals, each status overflow interval corresponds to a measured instability value, and match the current corresponding measured status overflow value with the multiple status overflow intervals to obtain the corresponding measured instability value;

[0033] Generate corresponding adjustment information based on the measured instability value, and obtain the adjusted corresponding detection status information based on the adjustment information. When the detection status information corresponds to normal detection status, use the adjustment information as the corresponding execution control information.

[0034] The execution control module is used to receive the execution control information, generate control instructions for the sensor according to the execution control information, and perform control execution according to the control instructions.

[0035] The data repository is used to store the measured data and the detection data, and is also used to store the detection status information and the measured status information.

[0036] In the technical solution provided by the present invention, compared with the prior art, the beneficial effects are as follows:

[0037] In the present invention, by obtaining the detection data of each sensor and identifying the detection data to obtain displacement detection information, pressure detection information, and optical detection information, and then analyzing the displacement detection information, pressure detection information, and optical detection information to obtain the detection status information of each sensor; and obtaining the measured data of each workpiece and analyzing the measured data to obtain the measured status information of each workpiece, and obtaining the execution control information by receiving the detection status information and comprehensively analyzing the detection status information and the measured status information; it is convenient to monitor and control the detection instrument, avoid operation problems caused by long-term operation from affecting the accuracy of the detection results, and reduce the chance of greater losses caused by unqualified products flowing into the market. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings required for the description of the embodiments. The following drawings are not deliberately drawn to scale in actual size, and the focus is on showing the gist of the present application.

[0039] Figure 1 It is the principle block diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0040] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0041] For ease of understanding, the specific process of the embodiments of the present invention will be described below. Please refer to Figure 1 , in an embodiment of the present invention, an embodiment of a high-precision quality inspection system for CNC machined parts includes: a data acquisition module, an intelligent calibration analysis module, an adaptive detection analysis module, an execution control module, and a data repository.

[0042] The data acquisition module collects the measured data of each machined part through sensors and collects the detection data of each sensor through a detection module, and sends the measured data and the detection data to the data repository;

[0043] The measured data includes workpiece size data, machining parameters, and surface image data; the detection data includes displacement detection information, pressure detection information, and optical detection information.

[0044] The intelligent calibration analysis module obtains the detection data of each sensor and identifies the displacement detection information, pressure detection information, and optical detection information by analyzing the detection data, analyzes the displacement detection information, pressure detection information, and optical detection information to obtain the detection status information of each sensor, and sends the detection status information to the adaptive detection analysis module.

[0045] The analysis of the displacement detection information, pressure detection information, and optical detection information is as follows:

[0046] A1: Identify the induction detection range, measurement size information, and environmental factor data by analyzing the displacement detection information;

[0047] A11: Obtain the preset detection standard range, compare the induction detection range with the detection standard range to obtain the difference range corresponding to the current displacement detection information, calculate the area of the difference range and mark the numerical value of the area as the difference influence value, obtain the difference influence values corresponding to the displacement detection information for multiple unit times, calculate the variance of each difference influence value to obtain the variance, and record the numerical value of the variance as the instability index;

[0048] A12: Obtain a preset processed standard part, and obtain the corresponding standard dimension information of the processed standard part. Compare the measured dimension information of the processed standard part with the standard dimension information to obtain a dimension difference. Divide the dimension difference into multiple dimension difference intervals, and each dimension difference interval corresponds to a dimension difference influence value. Match the dimension difference corresponding to the measured dimension information of the current processed standard part with the multiple dimension difference intervals to obtain the corresponding dimension difference influence value;

[0049] A13: Identify the environmental factor data to obtain temperature and humidity data. Obtain a preset temperature and humidity reference value. Calculate the difference between the temperature and humidity data corresponding to the current environmental factor data and the temperature and humidity reference value to obtain a temperature and humidity difference. Compare the temperature and humidity difference with a set temperature and humidity difference threshold. When the temperature and humidity difference is greater than the temperature and humidity difference threshold, mark the part of the temperature and humidity difference that exceeds the temperature and humidity difference threshold as the temperature and humidity influence value;

[0050] A14: Normalize and take the values of the instability index, dimension difference influence value, and temperature and humidity influence value. According to the formula Obtain the displacement state value WY; where, swz, cyz, and wsz represent the instability index, dimension difference influence value, and temperature and humidity influence value respectively; m1, m2, and m3 are all preset weight factors, and their values are 3.32, 2.09, and 2.72 respectively.

[0051] A2: Identify the pressure detection information to obtain the force values of each sensor under dynamic force conditions. The dynamic force conditions include but are not limited to the vibration, impact, and collision conditions received by each sensor;

[0052] A21: Obtain the force values corresponding to each unit time of the sensor, and obtain the preset force threshold corresponding to each sensor. Compare the force values corresponding to each unit time of each sensor with the corresponding force threshold. When the force value is greater than the force threshold, mark the corresponding force value as the impact force value, count the number of impact force values and record it as the impact force count, and calculate the ratio of the impact force count to the total number of force values to obtain the impact ratio.

[0053] A3: Obtain a preset defective processed part, and obtain the defective standard number and defective standard position of the defective processed part;

[0054] A31: Obtain the optical detection information of each sensor corresponding to the defective processed part, and identify the optical detection information to obtain the defective detection number and the corresponding position detection information;

[0055] A32: Calculate the difference between the corresponding defect detection numbers of each sensor and the defect standard number of the defective workpiece to obtain the defect error number. Set the defect error number into multiple error number intervals, and each error number interval corresponds to an error influence value. Match the defect error numbers corresponding to each sensor with the multiple error number intervals to obtain the corresponding error influence values;

[0056] A33: Compare the position detection information corresponding to each sensor with the defect standard position of the defective workpiece to obtain the position offset value. Obtain the preset offset threshold. When the position offset value is greater than the offset threshold, mark the part exceeding the offset threshold as the offset influence value;

[0057] A34: Construct two circles with the values of the error influence value and the offset influence value as the diameters of the two circles. Starting from and ending at the centers of the two circles, draw a line segment perpendicular to each of the two circles. The length of the line segment is a fixed value. Then construct a frustum of a cone with the two circles and the line segment, calculate the volume of the frustum of the cone and mark the value of the volume as the optical state value.

[0058] A4: Normalize the displacement state value, the impact occupancy ratio, and the optical state value and take their values. According to the formula calculate to obtain the detection state value jct; where, GX and cjz respectively represent the optical state value and the impact occupancy ratio, and Δcjz is marked as the impact value tolerance; n1, n2, and n3 are all preset weight factors, and their values are 0.781, 0.749, and 1.021 respectively;

[0059] A5: Obtain the preset detection state threshold, compare the current detection state value corresponding to the sensor with the detection state threshold. When the detection state value is greater than the detection state threshold, generate the corresponding detection state information as the detection state is abnormal.

[0060] The adaptive detection and analysis module obtains the measured data of each workpiece and analyzes the measured data to obtain the measured state information of each workpiece. By receiving the detection state information and comprehensively analyzing the detection state information and the measured state information, it obtains the execution control information and sends the execution control information to the execution control module.

[0061] Analyze the measured data, and the specific analysis method is as follows:

[0062] The measured data includes workpiece dimension data, machining parameters, and surface image data; the dimension values of each key dimension of each workpiece are obtained based on the workpiece dimension data, the dimension reference values corresponding to each key dimension are acquired, the difference between each key dimension corresponding to each workpiece and the corresponding dimension reference value is calculated to obtain the key dimension difference, the allowable value of the dimension difference corresponding to each key dimension is obtained, when the key dimension difference is greater than the allowable value of the dimension difference, the corresponding key dimension difference is marked as the dimension influence value, and the sum of the dimension influence values corresponding to each key dimension is calculated to obtain the total dimension influence value; the key dimensions include but are not limited to length, width, height, and hole diameter.

[0063] The cutting force and cutting temperature are obtained by identifying the machining parameters; the preset cutting set force is acquired, the difference between the cutting force corresponding to each workpiece and the cutting set force is calculated to obtain the force fluctuation value, the force fluctuation value is divided into multiple fluctuation value intervals, each fluctuation value interval corresponds to a force influence value, and the current force fluctuation value corresponding to each workpiece is matched with the multiple fluctuation value intervals to obtain the corresponding force influence value;

[0064] The preset cutting temperature threshold is obtained, the cutting temperature corresponding to the current workpiece is compared with the set cutting temperature threshold, when the cutting temperature is greater than the cutting temperature threshold, the difference between the cutting temperature and the cutting temperature threshold is calculated to obtain the temperature overflow value; the force influence value and the temperature overflow value are calculated and summed to obtain the machining influence value.

[0065] The surface image data corresponding to the workpiece is divided into multiple image blocks, the defect area corresponding to each image block is obtained, the sum of the curve areas of each block is calculated to obtain the total defect area corresponding to the workpiece, the ratio of the total defect area to the total area of the workpiece is calculated to obtain the defect area ratio, the preset defect area threshold is obtained, when the defect area ratio is greater than the defect area threshold, the defect area minus the defect area threshold is calculated to obtain the image status value.

[0066] A rhombus is constructed with the values of the total dimension influence value and the machining influence value as the two diagonals of the rhombus. Starting from the intersection point of the two diagonals of the rhombus, a straight line perpendicular to the rhombus is drawn, and the length of the straight line is equal to the value of the image status value. Then, a quadrangular pyramid is constructed with the rhombus and the straight line, and the volume of the quadrangular pyramid is calculated and the value of the volume is marked as the measured status value; when the measured status value is greater than the set threshold, the corresponding measured status information is generated as the measured status anomaly.

[0067] The detection status information and the measured status information are comprehensively analyzed, and the specific analysis method is as follows:

[0068] When the measured status information is abnormal, obtain the corresponding measured status value, calculate the measured status overflow value by subtracting the corresponding set threshold from the measured status value, divide the measured status overflow value into multiple status overflow intervals, each status overflow interval corresponds to a measured instability value, and match the current corresponding measured status overflow value with the multiple status overflow intervals to obtain the corresponding measured instability value;

[0069] Generate corresponding adjustment information based on the measured instability value, and obtain the corresponding detected status information after adjustment based on the adjustment information. When the detected status information corresponds to normal detection status, use the adjustment information as the corresponding execution control information.

[0070] The execution control module receives the execution control information, generates the control instruction of the sensor according to the execution control information, and performs the control execution according to the control instruction.

[0071] The data repository stores the measured data and the detected data, and is used to store the detected status information and the measured status information.

[0072] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A high-precision quality inspection system for CNC machined parts, comprising a data acquisition module and a data storage library, characterized in that: Also includes: An intelligent calibration and analysis module is used to obtain detection data of each sensor and obtain displacement detection information, pressure detection information and optical detection information by identifying the detection data, analyze the displacement detection information, pressure detection information and optical detection information to obtain detection status information of each sensor, and send the detection status information to the adaptive detection and analysis module; The adaptive detection and analysis module is used to obtain the measured data of each workpiece and analyze the measured data to obtain the measured state information of each workpiece, receive the detection state information and perform a comprehensive analysis on the detection state information and the measured state information to obtain the execution control information, and send the execution control information to the execution control module; The specific analysis method of the measured data is as follows: The measured data includes workpiece dimension data, processing parameters and surface image data; the dimension value of each key dimension of each workpiece is obtained according to the workpiece dimension data, the dimension reference value corresponding to each key dimension is obtained, the difference between each key dimension corresponding to each processed part and the corresponding dimension reference value is calculated to obtain the key dimension difference, the dimension difference allowable value corresponding to each key dimension is obtained, when the key dimension difference is greater than the dimension difference allowable value, the corresponding key dimension difference is marked as the dimension influence value, and the dimension influence value corresponding to each key dimension is calculated and summed to obtain the dimension total shadow value; The cutting force and cutting temperature are obtained by identifying the processing parameters; a preset cutting setting force is obtained, the difference between the cutting force corresponding to each workpiece and the cutting setting force is calculated to obtain a force fluctuation value, the force fluctuation value is divided into a plurality of fluctuation value intervals, each fluctuation value interval corresponds to a force influence value, and the force fluctuation value corresponding to each current workpiece is matched with the plurality of fluctuation value intervals to obtain a corresponding force influence value; Obtain a preset cutting temperature threshold, compare the cutting temperature corresponding to the current workpiece with the set cutting temperature threshold, and when the cutting temperature is greater than the cutting temperature threshold, calculate the difference between the cutting temperature and the cutting temperature threshold to obtain a temperature overflow value; The force influence value and the temperature overflow value are calculated and summed to obtain the processing influence value; the surface image data corresponding to the workpiece is divided into multiple image blocks, the defect area corresponding to each image block is obtained, the curve area of ​​each block is calculated and summed to obtain the total defect area corresponding to the workpiece, the total defect area is calculated to be a ratio of the total defect area to the total area of ​​the workpiece to obtain the defect area ratio, and a preset defect area threshold is obtained. When the defect area ratio is greater than the defect area threshold, the defect area is subtracted from the defect area threshold to obtain the image state value; The execution control module is used to receive the execution control information, generate the control instruction of the sensor according to the execution control information, and perform control execution according to the control instruction.

2. A high-precision quality inspection system for CNC machined parts according to claim 1, characterized in that: The data acquisition module obtains the measured data of each processed part through sensors, and obtains the detection data of each sensor through the detection module, and sends the measured data and the detection data to the data storage library; the measured data includes workpiece size data, processing parameters and surface image data; the detection data includes displacement detection information, pressure detection information and optical detection information.

3. A high-precision quality inspection system for CNC machined parts according to claim 1, characterized in that: The displacement detection information, pressure detection information and optical detection information are analyzed in the following specific analysis method: A1: The sensing detection range, measurement size information and environmental factor data are obtained by identifying the displacement detection information; A11: Obtain a preset detection standard range, overlap and compare the sensing detection range with the detection standard range to obtain a difference range corresponding to the current displacement detection information, calculate the area of ​​the difference range and mark the area value as a difference impact value, obtain the difference impact values ​​corresponding to the displacement detection information corresponding to multiple unit times, perform variance calculation on each difference impact value to obtain the variance, and record the variance value as the instability index swz; A12: Obtain a preset processing standard part and obtain the standard size information corresponding to the processing standard part, overlap and compare the measured size information of the processing standard part with the standard size information to obtain a size difference, divide the size difference into multiple size difference intervals, each size difference interval corresponds to an inch difference influence value, match the size difference corresponding to the measured size information corresponding to the current processing standard part with multiple size difference intervals to obtain the corresponding inch difference influence value cyz; A13: Identify the environmental factor data to obtain temperature and humidity data, obtain a preset temperature and humidity reference value, calculate the difference between the temperature and humidity data corresponding to the current environmental factor data and the temperature and humidity reference value to obtain a temperature and humidity difference, compare the temperature and humidity difference with a set temperature and humidity difference threshold, and when the temperature and humidity difference is greater than the temperature and humidity difference threshold, mark the portion of the temperature and humidity difference that exceeds the temperature and humidity difference threshold as a temperature and humidity impact value wsz; A14: Normalize the instability index, dimensional difference influence value and temperature and humidity influence value and take their values. According to the formula The displacement state value WY is obtained; wherein m1, m2 and m3 are all preset weight factors; A2: The force value of each sensor under dynamic force conditions is obtained by identifying the pressure detection information. The dynamic force conditions include but are not limited to vibration, impact and bump conditions to which each sensor is subjected; A21: Obtain the force value corresponding to each unit time of the sensor, and obtain the preset force threshold corresponding to each sensor, compare the force value corresponding to each unit time of each sensor with the corresponding force threshold, when the force value is greater than the force threshold, mark the corresponding force value as an impact force value, count the number of impact force values ​​and record it as the impact force number, and calculate the ratio of the impact force number to the total number of force values ​​to obtain the impact ratio value cjz; A3: Obtain a preset defective workpiece, and obtain the defect standard number and defect standard position of the defective workpiece; A31: Obtain optical detection information of defective workpieces corresponding to each sensor, and identify the optical detection information to obtain defect detection numbers and corresponding position detection information; A32: performing difference calculation on the defect detection number corresponding to each sensor and the defect standard number corresponding to the defective workpiece to obtain the defect error number, setting the defect error number to multiple error number intervals, each error number interval corresponding to an error influence value, matching the defect error number corresponding to each sensor with the multiple error number intervals to obtain the corresponding error influence value; A33: The position detection information corresponding to each sensor is overlapped and compared with the defect standard position of the defective workpiece to obtain a position offset value, and a preset offset threshold is obtained. When the position offset value is greater than the offset threshold, the portion of the offset threshold that exceeds the offset threshold is marked as an offset influence value; A34: construct two circles with the values ​​of the error influence value and the offset influence value as the diameters of the two circles, and make a line segment perpendicular to the two circles with the centers of the two circles as the starting point and the end point. The length of the line segment is a fixed value, and then construct a frustum with the two circles and the line segment. Calculate the volume of the frustum and mark the volume value as the optical state value GX; A4: Normalize the displacement state value, impact ratio value and optical state value and take their values ​​according to the formula The detection state value jct is calculated; wherein Δcjz is marked as the allowable difference of the impact value; n1, n2 and n3 are all preset weight factors; A5: Obtain a preset detection state threshold, compare the current detection state value of the sensor with the detection state threshold, and when the detection state value is greater than the detection state threshold, generate corresponding detection state information as detection state abnormality.

4. A high-precision quality inspection system for CNC machined parts according to claim 1, characterized in that: A rhombus is constructed with the values ​​of the total shadow value of the size and the processing influence value as the two diagonals of the rhombus, a straight line perpendicular to the rhombus is drawn with the intersection of the two diagonals of the rhombus as the starting point, and the length of the straight line is equal to the value of the image state value, and then a quadrangular pyramid is constructed with the rhombus and the straight line, the volume of the quadrangular pyramid is calculated and the value of the volume is marked as the measured state value; when the measured state value is greater than the set threshold value, the corresponding measured state information is generated as a measured state abnormality.

5. A high-precision quality inspection system for CNC machined parts according to claim 1, characterized in that: The comprehensive analysis of the detection status information and the measured status information is performed as follows: When the measured state information is that the measured state is abnormal, the corresponding measured state value is obtained, and the measured state value is subtracted from the corresponding set threshold value to obtain the measured state overflow value, and the measured state overflow value is divided into multiple state overflow intervals, each state overflow interval corresponds to a measured instability value, and the current corresponding measured state overflow value is matched with multiple state overflow intervals to obtain the corresponding measured instability value; Corresponding adjustment information is generated based on the measured instability value, and detection state information corresponding to the adjustment is obtained based on the adjustment information. When the detection state information corresponds to a normal detection state, the adjustment information is used as corresponding execution control information.

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