513results about How to "Improve quality control" patented technology

The invention relates to the technical field of image data processing, in particular to a carton printing defect detection method and system based on visual identification, and the method comprises the steps: obtaining a carton image through an image collection device, calculating the gray feature quantity of a pixel point based on the gray value of each pixel point in the image and the gray difference in the neighborhood of the pixel point, and calculating the gray feature quantity of the pixel point; the gray scale is used for reflecting gray scale change conditions of local areas; the change degree of the pixel points is calculated based on the gray feature quantity, the change degree represents the clutter degree of the pixel points, and a change degree co-occurrence matrix is constructed to describe the joint distribution characteristic between different change degrees. Calculating the defect degree of each pixel point according to the change degree co-occurrence matrix; the defect degree of each pixel point is calculated, and the pixel points with the defect degrees larger than a set threshold value are responded to be defective pixel points. The problem that the accuracy of carton printing defect detection is not high is solved.

The invention discloses an intelligent detection system for the surface quality of a copper foil. The intelligent detection system comprises an acquisition module, a construction module and a detection module, the acquisition module is used for acquiring a multi-angle multi-spectral image of the surface of the copper foil and preprocessing the multi-angle multi-spectral image; the construction module is used for carrying out automatic identification and positioning on the surface of the copper foil by utilizing a defect detection algorithm based on deep learning based on the preprocessed multi-angle multispectral image, and constructing a copper foil surface defect identification model; and the detection module is used for comprehensively detecting the surface defects of the copper foil to be detected by using the copper foil surface defect identification model. According to the invention, comprehensive and accurate detection of surface defects of the copper foil can be realized, and the quality control level of the copper foil is improved.

The invention discloses a garment fabric color fastness detection method and system, and relates to the technical field of fabric detection.The method comprises the steps that initial color information and initial texture information of a to-be-detected garment fabric are integrated; simulating the action factors of the to-be-detected garment fabric in the various preset scenes so as to perform color fastness testing on the to-be-detected garment fabric in the various preset scenes; wherein the action factors in the multiple preset scenes comprise friction, water washing, raining, insolation, illumination, seawater impregnation, saliva impregnation, water stains and sweat stains; collecting a reference color information set and a reference texture information set of the to-be-detected garment fabric subjected to the color fastness test in the various preset scenes; analyzing the initial color information and the reference color information set after the color fastness test in various preset scenes; and evaluating the color fastness of the to-be-detected garment fabric according to the calculated color difference condition and the change condition of the surface structure of the to-be-detected garment fabric.

The invention discloses a template embedded type dam face permanent heat preservation protection module and a prefabrication and construction method. Comprising a heat preservation core layer, a facing anti-seepage protection layer is arranged on the side, close to a concrete pouring formwork, of the heat preservation core layer, an internal pressure-bearing protection layer is arranged on the side, close to dam surface layer crack limiting steel bars, of the heat preservation core layer, and a thermal broken bridge supporting keel is arranged in the heat preservation core layer; an anchoring device is arranged in the area between the internal pressure-bearing protection layer and the dam surface layer crack limiting steel bars. The modular prefabrication and construction method is adopted, the prefabrication and installation method of a single module is simple and efficient, details such as anchoring protection measures are fully considered, the engineering construction operability is high, convenience and high efficiency are achieved, and the construction time of the heat preservation layer is greatly saved.

The coarse aggregate ultra-high performance concrete premix lifting, transferring and mixing device comprises a control system, an aggregate batching system, an aggregate lifting system, a dry mixing main machine system, a feeding vehicle, a steel fiber feeding system and a stirring system, the whole stirring process is automatically controlled and comprises key steps of automatic metering, automatic raw material feeding, mixing and the like, so that manual operation is remarkably reduced, errors and inconsistency caused by manual metering are avoided, and the accuracy and repeatability of stirring each time are ensured; step-by-step feeding of each part is coordinated through a control system, so that the stirring efficiency and the uniformity of concrete are improved; by establishing a relational expression between a concrete mixture stirring uniformity index and parameters such as the stirring time, the stirring speed, the number of stirring blades, the vibration frequency of the two-stage vibrating screen and the like, key parameters in the stirring process are more accurately controlled, and it is ensured that the stirring uniformity of each batch of concrete reaches a preset standard.

The invention belongs to the technical field of road engineering materials, and discloses a wide-temperature-range crack pouring adhesive based on rubber modified asphalt and a preparation method thereof.The wide-temperature-range crack pouring adhesive is prepared by taking the rubber modified asphalt as a matrix through a response surface method and adding SBS, basalt fibers and a modifier. The performance of the material is tested through a conventional test, and meanwhile, a test with more characteristics in northeast regions is provided, and the performance of the material is detected through injection depth, viscosity, low-temperature stretching after aging and freeze-thaw cycle stretching. Results show that a test designed by a response surface method has very strong reliability, and the modified heating type crack pouring adhesive added with the basalt fiber can significantly improve the high and low temperature performance of the crack pouring adhesive, and also has good anti-aging performance and freeze-thaw cycle resistance. And the filling depth and the viscosity of the sealant are not obviously lower than those of the same type of sealant.

The invention relates to a wall column perpendicularity detection device and method. The wall column perpendicularity detection device comprises a supporting frame, a lifting base, a driving assembly, a rolling assembly and a marking assembly. The lifting base is installed on the supporting frame in a sliding mode in the vertical direction and can slide in a lifting mode along the supporting frame under the action of the driving assembly. The rolling assembly comprises a connecting frame and a measuring roller; the measuring roller is rotationally mounted on the connecting frame; the connecting frame is installed on the inner side of the lifting base through a telescopic assembly, and the telescopic assembly can enable the measuring roller to adaptively adjust the distance between the connecting frame and the lifting base in the lifting process along the wall face. And a fixed measuring track can be formed on the rolling assembly through the marking assembly in the process that the measuring roller ascends and descends along the wall surface. The method effectively solves the problems that a traditional detection method is low in efficiency, poor in precision, weak in applicability and the like, and greatly improves the efficiency and accuracy of wall column perpendicularity detection.

The invention provides a high-efficiency and environment-friendly sandstone material processing control system, and relates to the technical field of sandstone material processing control, and the system comprises a production demand determination module, a blank raw material determination module, a processing workshop control module, a processing workshop fault evaluation module, an environment-friendly monitoring processing module and a sandstone aggregate online detection module. According to the invention, intelligent control of gravel production is realized, physical online detection of finished aggregate detects particle size and shape of the finished aggregate, chemical online detection of harmful substances chloride and methylene blue in the finished aggregate is realized, the detection efficiency is improved, the labor intensity of testers is reduced, and the production cost is reduced. Online collection, real-time detection, remote analysis and dynamic feedback of the finished aggregate are realized, and the quality control level of the finished aggregate is improved.

The invention discloses a wafer film defect detection system and method, and relates to the technical field of wafer film defect detection.The wafer film defect detection method comprises the following steps that in the wafer film defect detection process, laser beams are emitted through a laser scanner according to the preset light beam coverage rate, and the surface of a wafer is covered for preliminary scanning; in the laser beam scanning process, the intensity and the consistency of laser reflection signals are analyzed in real time. According to the invention, preliminary scanning is carried out by presetting the light beam coverage rate, the significance of the potential flaw area is evaluated by using the convolutional neural network, accurate classification of the flaw obvious area and the flaw non-obvious area is realized, high-density secondary scanning is carried out by dynamically adjusting the light beam coverage rate for the flaw non-obvious area, and finer surface information is captured. The detection efficiency is improved, the risks of missing detection and false detection are effectively reduced, the accurate detection of tiny flaws is ensured, the quality control of wafer film pasting is remarkably improved, and the production loss is avoided.

The invention relates to a method for improving quality control of cefditoren pivoxil granules, which comprises the following steps: injecting a cefditoren pivoxil granule sample solution into a high performance liquid chromatograph for analysis so as to detect impurities in the cefditoren pivoxil granules, in the high performance liquid chromatography, a mixed solution of an ammonium formate solution, acetonitrile and methanol (43-47): (23-27): (23-27) is used as a mobile phase A, a mixed solution of an ammonium formate solution, acetonitrile and methanol (43-47): (53-57): (53-57) is used as a mobile phase B, gradient elution is adopted, and a cefditoren pivoxil particle sample solution is prepared by using the mobile phase A as a diluent. According to the method disclosed by the invention, the forward delay phenomenon of an open-loop impurity peak of the cefditoren pivoxil in the cefditoren pivoxil granules and the separation degree of an unknown impurity peak are improved, the reproducibility is good, and the accuracy is high, so that the quality control level of the cefditoren pivoxil granules is improved.

The invention provides a manufacturing method of a space converter of a probe card. The manufacturing method comprises the following steps: sequentially forming a titanium layer and a first copper layer on the upper surface of a ceramic substrate; forming a first circuit pattern on the upper surface of the first copper layer; forming a second copper layer on the first circuit pattern; removing the titanium layer and the first copper layer except the titanium layer below the second copper layer; sequentially forming a nickel layer and a first gold layer on the upper surface of the structure; forming a polyimide layer on the upper surface of the structure; removing the polyimide layer on the upper surface of the target position of the first gold layer to form a second circuit pattern; forming a first nickel-cobalt alloy layer on the second circuit pattern, and then forming a third circuit pattern; forming a second nickel-cobalt alloy layer on the third circuit pattern, and then forming a fourth circuit pattern; forming a second gold layer on the fourth circuit pattern; and removing the photoresist to obtain the space converter. According to the manufacturing method of the space converter of the probe card, the installation position of the probe can be accurately adjusted, and the alignment precision of the probe is improved.

The invention provides a cast-in-place pile construction over-pouring detection calculation method and system, and belongs to the field of physical data detection.The compressive strength and density corresponding to all subareas in a cast-in-place pile can be obtained by obtaining the ultrasonic wave speed and attenuation coefficient corresponding to all the subareas in the cast-in-place pile; dimension calculation is carried out through derivatives between the ultrasonic wave velocity and attenuation coefficient and the concrete compressive strength and density, and a sound velocity compressive strength difference vector and an attenuation density difference vector are obtained; and comparing the sound velocity compression resistance difference vector with the attenuation density difference vector to judge abnormity. According to the method, the problems of concrete non-uniformity, sediment accumulation and the like can be effectively recognized, the quality control level in the cast-in-place pile construction process is improved, particularly, high precision and sensitivity are achieved in the pile bottom area with the depth increasing progressively, and the safety and reliability of the overall state of an over-cast construction pile body structure are ensured.

The invention provides a carbon emission data quality analysis method which comprises the following steps: acquiring various activity level data influencing product / enterprise carbon emission, calculating carbon emission intensity, longitudinally comparing the carbon emission intensity with historical data and transversely comparing the carbon emission intensity with an industry reference value, and acquiring first quality evaluation data of the carbon emission activity level data; according to the production / business logic of the enterprise, analyzing the correlation of the activity level data in the production process, and obtaining second quality evaluation data of the carbon emission activity level data; constructing a multiple regression model, performing multiple regression analysis on correlation between molecules and denominators of the carbon emission intensity indexes and noise influence on time, places, processes / technologies and quality of the carbon emission intensity indexes, and obtaining third quality evaluation data of the carbon emission activity level data; and the authenticity of the carbon emission data is judged according to the first, second and third quality evaluation data, so that the carbon emission data quality can be improved, and disordered filling, wrong filling and counterfeiting of the data are avoided.

The invention discloses a pavement compaction degree real-time monitoring system and method based on a high-precision vibration acceleration sensor, a signal processing algorithm and intelligent data analysis, and is suitable for vibratory roller operation. According to the system, fine vibration characteristics in the construction process are captured through the three-axis acceleration sensor installed on the vibration wheel, and the analysis precision of mechanical behaviors in the compaction process is improved by combining the viscoelastic-plastic performance, described by the three-degree-of-freedom two-dimensional viscoelastic-plastic block model, of the asphalt mixture. A compaction degree prediction model is constructed by adopting machine learning, a vibration signal is analyzed in real time, a compaction degree estimation value is output, a result is displayed through a user interface, and an optimization suggestion is provided according to a compaction effect. The system has an early warning function, gives an alarm when the compaction degree does not reach the standard, and guides constructors to adjust strategies in time, so that the road construction quality control level is effectively improved.

The invention relates to a woolen sweater defect detection method. The method is characterized by comprising the following four main steps: a data preprocessing step, a model construction step, a model training step and a defect detection step. Wherein in the model construction step, strategies such as an attention mechanism and a network structure optimization are introduced, so that the identification capability of the model on woolen sweater defects is improved; in the detection process, automatic positioning and classification of defect areas are realized through a series of key functions. The method is high in detection efficiency, low in comprehensive detection cost and high in detection accuracy.

The invention relates to the field of mineral aggregate detection, in particular to a mineral aggregate crushing degree detection method based on image analysis. The method comprises the following steps: acquiring a preprocessed mineral aggregate grey-scale map, calculating a gradient value of any pixel point in the mineral aggregate grey-scale map, and calculating the division difficulty of the mineral aggregate grey-scale map; obtaining edges in the mineral aggregate grey-scale map based on edge detection, constructing a minimum enclosing rectangle of a target edge, and counting the number of reference edges in the minimum enclosing rectangle to calculate the outer contour probability of the target edge; traversing to obtain outer contour probabilities of all edges in the mineral aggregate grey-scale map, determining an outer contour of the mineral aggregate, converting the mineral aggregate grey-scale map into a binary image according to the outer contour of the mineral aggregate, inputting the binary image into a preset neural network, obtaining a crushing result probability value, and completing crushing degree detection. According to the technical scheme, the precision and efficiency of the detection result of the crushing degree of the mineral aggregate can be improved.

The invention relates to the technical field of quality detection, in particular to a meat dish quality detection system which comprises a data acquisition module, a first determination module, a second determination module, a judgment module, a correction module and an alarm sending module. According to the method, the quality control level of the meat ball production line is effectively improved through accurate multi-parameter analysis and a step-by-step judgment mechanism, potential quality problems such as cracks, over-wet or over-dry defects can be accurately recognized by monitoring the moisture content, the sphericity and the deformation quantity of the meat balls in real time, the clamping pressure is dynamically adjusted, and the quality of the meat balls is improved. The system can adapt to different production conditions in real time, the influence of too large or too small clamping force on the shape and taste of meatballs is avoided, a real-time feedback mechanism of the correction module ensures that the production process can be rapidly adjusted during fluctuation, the defective rate in production is effectively reduced, and the production efficiency is improved. The problems of low detection precision and slow response speed caused by dependence on static data are effectively solved.

The invention relates to an intelligent defect detection and marking system and method, which is applied to the field of defect detection, and comprises an X-ray detection module used for scanning a to-be-detected package and generating a package X-ray image in real time; the image processing module is connected to the X-ray detection module and is used for receiving the X-ray image of the packaging part and carrying out defect detection on the packaging part to be detected according to the X-ray image of the packaging part; the control module is connected to the image processing module and is used for outputting a control instruction according to the defect detection result and controlling the laser marking module to mark the packaging piece; and the laser marking module is connected to the control module and is used for receiving the control instruction and carrying out marking treatment on the packaging piece subjected to defect detection according to the control instruction. The method has the technical effects that the defect detection is completed before the marking process of the packaging piece, the operation process is simplified, and the production efficiency is improved.

The invention discloses a semiconductor test management system, relates to the technical field of semiconductor test, and solves the technical problems that performance detection and evaluation in different stages of wafer production are lacked, and it is difficult to detect whether a wafer has performance abnormity in the production stage in time. According to the stage performance evaluation coefficient of the semiconductor wafer of each node, a node early warning module performs stage early warning on the semiconductor wafer with stage performance abnormity, analyzes the comprehensive performance coefficient of the semiconductor wafer, and performs early warning on the semiconductor wafer which does not meet the standard; by monitoring and analyzing stage performance coefficients in real time, semiconductor wafers which do not meet the standard can be quickly identified, measures are taken in advance, and greater loss generated in the subsequent process is avoided. By detecting whether the performance of the wafer is abnormal or not in the production stage, resources can be reasonably allocated, and defective wafers can be centrally processed or re-evaluated instead of wasting time and materials on possibly failed products.

The invention discloses a heavy duty gas turbine intelligent control method integrating error active disturbance rejection control and an improved hyperbolic sine and cosine optimizer. The heavy duty gas turbine has the characteristics of numerous monitoring parameters, strong nonlinearity and high coupling degree. The method is used for solving the problem that the control effect is not ideal when the traditional PID control strategy faces the system. The method comprises the steps of collecting and preprocessing data of the heavy-duty gas turbine, establishing a Wiener model of the heavy-duty gas turbine based on variational Bayesian identification, designing an extended state observer and an error active-disturbance-rejection control strategy, and designing a multi-target operation optimization target function of the heavy-duty gas turbine; and then solving the optimal solution of the decision variable of the heavy duty gas turbine controller by using an improved hyperbolic sine and cosine optimizer. The invention provides a scheme and thought for the intelligent control method of the heavy duty gas turbine.

According to the method, a polysaccharide derivative bonding type chiral chromatographic column with silica gel surface bonded amylose-tri (3, 5-dichlorophenyl carbamate) as a filler is adopted, a mixed solution of n-hexane and isopropanol is used as a mobile phase, the column temperature is 28-32 DEG C, the flow velocity is 1.1-1.3 ml / min, the column temperature is 20-30 DEG C, the column temperature is 20-30 DEG C, the column temperature is 20-30 DEG C, the column temperature is 20-30 DEG C, the column temperature is 20-30 DEG C, and the column temperature is 20-30 DEG C; an ultraviolet detector is adopted, the wavelength is 205-220 nm, and effective separation of the etomidate intermediate and the enantiomer thereof is achieved. The method is good in detection result accuracy and high in sensitivity, and compared with an existing analysis method, the method is better in separation effect, simpler in mobile phase composition, more durable in chromatographic column and lower in cost, so that a good guarantee is provided for quality control of the etomidate intermediate and etomidate.

The invention discloses an induction culture medium for preparing human umbilical cord mesenchymal stem cell exosomes and application of the induction culture medium, and relates to the technical field of exosome culture. The additive is prepared from the following components: 0.8 to 1.5 percent of ITS, 0.03 to 0.05 percent of a luteolin extract, 0.04 to 0.06 percent of a herba taraxaci extract, 0.02 to 0.04 percent of a radix ginseng extract, 0.03 to 0.05 percent of resveratrol, 0.01 to 0.03 percent of vitamin C, 0.03 to 0.05 percent of a pimpinella thellungiana extract, 0.01 to 0.03 percent of a rhizoma dioscoreae extract and 0.01 to 0.02 percent of sodium citrate; the induction culture medium provided by the invention not only can avoid introduction of exogenous substances and reduce the pollution risk, but also can promote proliferation of stem cells and effectively induce synthesis and exosome secretion of a large number of human umbilical cord mesenchymal stem cells.

The invention discloses a pellet positioning circle measurement defect detection method and device based on an SOD-YOLOv5 model, and the method comprises the following steps: placing a plurality of pellets in grid holes of a pellet box, precisely positioning the center of each pellet through a microscope lens, detecting a pellet image through the SOD-YOLOv5 model, calculating the center offset, and determining the defect of the pellet positioning circle measurement defect. Fine positioning of the pellet is realized; then, the maximum inscribed circle of the pellet is extracted, edge detection is carried out along the circumference, and a circular contour is fitted through a least square method so as to calculate geometrical characteristics such as roundness and diameter; identifying and positioning the surface defects of the pellet by using an SOD-YOLOv5 model and a difference method; a microscope lens automatically moves to the position of each hole, and multi-pellet detection is carried out in sequence; the device can adapt to various colors and illumination conditions, high-precision, automatic and batch detection is realized, and the reliability of a detection result is ensured.

The invention provides a method for detecting related substances of bromo-n-butane, which adopts a gas chromatography detection method, and the chromatographic conditions are as follows: a chromatographic column is a DB-624 quartz capillary column, and the specification is 30m * 0.32 mm * 1.8 [mu] m; the column temperature is 40 DEG C; the stationary phase is 6% of cyanopropyl phenyl-94% of dimethyl polysiloxane; the temperature of a sample injector is 250 DEG C; the sample size is 1 [mu] L; the split ratio is 20: 1; the carrier gas is nitrogen; the flow rate of nitrogen is 2.1 mL / min; a detector is a hydrogen ion spark detector, and the temperature of the detector is 250 DEG C. The invention further provides application of the method. The method can be used for rapidly and accurately detecting the related substances of the n-butyl bromide, realizes effective separation of the n-butyl bromide and impurities thereof, and is of great significance in improving the effective quality of the n-butyl bromide, controlling the content of the impurities brought into the synthesis reaction of the bupivacaine hydrochloride by the starting material and improving the quality stability of the bupivacaine hydrochloride.

The utility model relates to the technical field of commercial concrete production supervision, in particular to a dynamic intelligent supervision device for a concrete mixing station. The system comprises a data acquisition module, a process monitoring module, a data storage module and an exit following module, the data acquisition module comprises an environment data detection module and a concrete data detection module, and the process monitoring module comprises a monitoring system, a control computer and an alarm device. The data acquisition module is used for collecting multiple items of working data in the concrete mixing station, comprehensive judgment and guarantee of the concrete production quality are facilitated, the process monitoring module is used for monitoring and controlling the production process of the concrete in the whole process, the production process is monitored and mastered, the quality control of the concrete production is further improved, and the working efficiency is improved. The data storage module is used for storing data and monitoring information collected by the data acquisition module and the process monitoring module, and the delivery following module is used for monitoring the delivery condition of finished concrete after the finished concrete is delivered, so that the whole-course quality control is realized.

The present invention relates to the field of defect detection technology, specifically to a part surface defect detection system and method based on machine vision, the system comprising an image optimization processing module, a defect type recognition module, a defect quantification evaluation module and an overall defect evaluation module. The present invention improves the image quality by optimizing the part surface image, makes the local contrast analysis more accurate, enhances the recognizability of defects in the image, and can accurately match and identify the defect type by comparing with a preset part defect feature library, effectively improves the accuracy of defect classification, and accurately quantifies the severity of the defect by evaluating the area and shape of each type of defect, providing detailed data support for the overall defect evaluation, and can effectively grade the surface integrity of the part, optimize the quality control of the part, and ensure that the final quality of the product meets high standards.

The invention belongs to the technical field of monoclonal antibody preparation, and particularly relates to a human-mouse chimeric monoclonal antibody for resisting human myelin sheath oligodendrocyte glycoprotein (MOG) and application of the human-mouse chimeric monoclonal antibody. Complementary determining regions in variable regions of a heavy chain and a light chain of the human-mouse chimeric monoclonal antibody of the anti-human MOG protein come from a mouse, parent activity is reserved to the maximum extent, a constant region is a human antibody constant region, immunogenicity is greatly reduced due to introduction of the human antibody constant region, the occurrence probability of a human anti-mouse antibody reaction is reduced, and the anti-human MOG protein is prepared. The specificity of the antibody is improved. The human-mouse chimeric monoclonal antibody resisting the human MOG protein has antigen binding specificity, the heterology of a mouse monoclonal antibody is greatly reduced, the biological activity of the human-mouse chimeric monoclonal antibody is good, and the human-mouse chimeric monoclonal antibody resisting the human MOG protein can specifically detect the MOG protein.

The present invention provides a clay calcination color control system, which includes a suspension calcination subsystem and a rotary cooling subsystem. The suspension calcination subsystem is used for preheating, calcining, decomposing and separating clay materials, and the rotary cooling subsystem is used for cooling the clay materials after calcination and decomposition; wherein the rotary cooling subsystem includes a rotatable cooler, and the cooler is provided with a first water spraying device at least at the inlet end or outlet end of the material, which is used to spray cooling water, so that the cooling water vaporizes to generate water vapor and fills the inlet or outlet part, isolates the air exchange inside and outside the cooler, and prevents the clay material from being oxidized and discolored during the cooling process, so as to achieve color control of the finished clay. The present invention performs calcination and cooling in different equipment respectively; while improving the stability of the operation of the entire system, improving the heat exchange effect, and simplifying the quality control, the present invention also achieves stable and reliable color control in production.

The invention provides an industrial product commodity picture generation method and system based on a large model picture processing method. The industrial product commodity picture generation method comprises the steps of obtaining an original industrial product commodity picture; preprocessing the original industrial product commodity picture stored in the object storage server to obtain the preprocessed original industrial product commodity picture; capturing the preprocessed original industrial goods pictures in the object storage server, storing the captured pictures to a kafka queue service, and asynchronously calling a large model to carry out parallel processing on the pictures in the kafka queue service to obtain processed pictures; whether the processed picture meets a preset quality requirement or not is judged, and when the preset quality requirement is met, the currently processed picture is regarded as an available finished picture and stored in an object storage server; and when the picture does not meet the preset requirement, calling the large model to perform repeated processing until the picture meeting the requirement is obtained.

The invention relates to the technical field of robot automatic manufacturing, in particular to a robot intelligent grinding and polishing machining method based on online measurement, which comprises the following steps: collecting real-time data in the robot grinding and polishing machining process through online monitoring, measuring the wear rate, monitoring the environment temperature, detecting the hardness change of a machining material, and obtaining real-time monitoring data. According to the method, key change nodes appearing in the machining process can be recognized in time by monitoring the abrasion rate, the material hardness change and real-time data of the environment temperature, the rejection rate is remarkably reduced, the production cost is reduced, the grinding and polishing path points needing to be adjusted are predicted by intelligently analyzing the trend result and combining the linear regression model, and the grinding and polishing precision is improved. The operation efficiency of the robot and the surface treatment effect of the workpiece are further optimized, through coherent treatment and feedback, the quality control of the whole grinding and polishing process is improved, and meanwhile the use efficiency of materials and the overall quality of the workpiece are greatly improved.