Three-way valve pipe pump production quality evaluation system

Abstract

The invention discloses a three-way valve pipe pump production quality evaluation system, relates to the technical field of production quality evaluation, and solves the problem that the production quality parameters and product appearance quality parameters of a three-way valve pipe pump are difficult to calculate to obtain corresponding test values. And whether the production quality parameters are abnormal or not is difficult to judge according to the comparison result of the production quality coefficients. The production quality parameter acquisition module is used for dividing a specific monitoring area into a plurality of monitoring sub-areas and collecting production quality parameters including rotating speed, pressure and flow data from the sub-areas; the component appearance quality detection module is used for calculating product appearance quality parameters, including chromaticity, area and perimeter data, of the component; the production quality parameter testing module is used for acquiring an appearance testing value, a rotating speed testing value, a pressure testing value and a flow testing value; and the production quality parameter abnormity evaluation module is used for judging whether the production quality parameters are abnormal or not according to the comparison result of the comprehensive production quality coefficients.

Description

Technical Field

[0001] The invention belongs to the technical field of production quality assessment, and in particular relates to a three-way valve tube pump production quality assessment system. Background Art

[0002] With the continuous development of automation technology, the importance of production quality assessment systems continues to increase. The three-way valve tube pump production quality assessment system uses image processing technology to obtain product appearance quality measurement values ​​and historical data analysis to obtain a variety of production quality parameter measurement values ​​and compares the comprehensive first production quality value and the comprehensive second production quality value to obtain a comprehensive production quality coefficient to determine whether the production quality is abnormal, thereby better achieving the stability and efficiency of production quality.

[0003] Although the existing three-way valve tube pump production quality assessment system has achieved production quality assessment to a certain extent, the traditional production method relies on manual inspection and experience judgment, which is inefficient and prone to errors. It is difficult to combine the production quality parameters of the three-way valve tube pump and the product appearance quality parameters to calculate the corresponding test values, and it is also difficult to combine the results of the production quality coefficient comparison to determine whether there are abnormalities in the production quality parameters, resulting in unstable product quality. Summary of the invention

[0004] The present invention aims to solve at least one of the technical problems existing in the prior art; to this end, the present invention proposes a three-way valve pipe pump production quality assessment system for solving the following technical problems:

[0005] Although the existing three-way valve tube pump production quality assessment system has achieved production quality assessment to a certain extent, the traditional production method relies on manual inspection and experience judgment, which is inefficient and prone to errors. It is difficult to combine the production quality parameters of the three-way valve tube pump and the product appearance quality parameters to calculate the corresponding test values, and it is also difficult to comprehensively compare the results of the production quality coefficient to determine whether there are any abnormalities in the production quality parameters.

[0006] To solve the above problems, the first aspect of the present invention provides a three-way valve tube pump production quality assessment system, including the following modules:

[0007] Production quality parameter acquisition module: used to divide various types of production equipment in the production plant into specific monitoring areas, and divide the specific monitoring areas into several monitoring sub-areas, marked as 1, 2, 3, ..., n, respectively, to collect the production quality parameters of the three-way valve tube pump in the sub-areas, including speed, pressure, and flow data;

[0008] Component appearance quality detection module: used to monitor the image data of the three-way valve pipe pump components obtained by the camera in the sub-area, analyze the image chromaticity by using image processing technology, extract feature information after preprocessing the image data, obtain the chromaticity average value, identify the image components by machine learning algorithm, extract the geometric features of the components according to the contour information, including the area and perimeter of the normal contour area and the abnormal contour area, compare the product appearance quality measurement value composed of the product appearance quality parameters with the comprehensive appearance standard value as the comprehensive first production quality value to obtain the first production quality coefficient calculation value;

[0009] Production quality parameter test module: used to perform corresponding calculations on the received speed data, pressure data and flow data, and obtain speed test values, pressure test values ​​and flow test values;

[0010] Production quality parameter abnormality assessment module: used to take the comprehensive average value of historical speed, pressure and flow data as the comprehensive second production quality value and compare it with the comprehensive production quality test value of the speed test value, pressure test value and flow test value to obtain the second production quality coefficient, and judge whether the production quality parameters are abnormal based on the result of the comprehensive production quality coefficient comparison.

[0011] As a further solution of the present invention: the production quality parameter acquisition module is used to divide various types of production equipment in the production plant into specific monitoring areas, and divide the specific monitoring area into a number of monitoring sub-areas, respectively marked as 1, 2, 3, ..., n, and collect the production quality parameters of the three-way valve tube pump in the sub-areas, including speed, pressure, and flow data, including the following steps:

[0012] Analyze the layout of the distribution of various types of production equipment in the production plant, divide the production plant into several specific monitoring areas, each monitoring area contains a group of production equipment with different functions, and divides into several monitoring sub-areas, marked as 1, 2, 3, ..., n, and in each monitoring sub-area, the speed sensor installed on the pipe pump shaft monitors and records the speed data of the pipe pump in real time; the pressure sensor and flow sensor installed on the pipe pump pipeline monitor and record the pressure data and flow data of the pipe pump in real time;

[0013] Among them, the specific monitoring areas are the raw material handling area, production and processing area, and quality inspection and packaging area.

[0014] As a further solution of the present invention: the component appearance quality detection module is used to monitor the image data of the three-way valve pipe pump component obtained by the camera in the sub-area, analyze the image chromaticity by using image processing technology, extract feature information after pre-processing the image data, and obtain the chromaticity average value, including the following steps:

[0015] The original image data of the components of the three-way valve pipe pump are collected by the camera in the monitoring sub-area, and the original data are preprocessed, including image enhancement, brightness adjustment and noise removal. Two-thirds of the image data after preprocessing are randomly selected, and the color chromaticity range is set to 0-225. The color chromaticity is divided into five levels, each level table contains 45 chromaticity units, and the boundary values ​​are 0-44, 45-89, 90-134, 135-179 and 180-225 respectively. In the image processing process, the chromaticity value of the pixel is classified into the corresponding level by comparing the size of the chromaticity value of the pixel with the boundary value;

[0016] The formula for calculating the average chromaticity value is:

[0017]

[0018] Among them, C A is the average chromaticity value, N is the number of pixels, C i is the chromaticity value of the i-th pixel, W i is the weight coefficient corresponding to the chromaticity value of the i-th pixel.

[0019] As a further solution of the present invention: the image component is identified by a machine learning algorithm, and the geometric features of the component are extracted according to the contour information, including the area and perimeter of the normal contour area and the abnormal contour area, including the following steps:

[0020] Preprocess the collected image data, including denoising, smoothing and graying, use edge detection algorithms to extract edge information from the image data, perform morphological operations on the edge detection results, process the shape and structure in the image, use contour extraction algorithms to extract the contours of normal areas and abnormal areas from the processed edge images and mark them, use the marked data set to train a machine learning model to identify the components of the three-way valve tube pump, and extract the geometric features of the components, including area and perimeter, based on the contour information;

[0021] Connect the vertices on the contour of the abnormal area in sequence as a polygon composed of straight line segments to obtain the area of ​​the abnormal area of ​​the component;

[0022] Abnormal area calculation formula:

[0023]

[0024] Among them, S is the calculated value of the abnormal area, n is the total number of vertices on the contour, (x i ,y i ) is the i-th coordinate of the polygon vertex;

[0025] By calculating the length of each side of the polygon and adding them together, the perimeter of the abnormal area of ​​the component is obtained;

[0026] Abnormal area perimeter calculation formula:

[0027]

[0028] Among them, U is the calculated value of the perimeter of the abnormal area, n is the total number of vertices on the contour, (x i ,y i ) is the i-th coordinate of the polygon vertex.

[0029] As a further solution of the present invention: the method of comparing the product appearance quality measurement value constituted by the product appearance quality parameter with the comprehensive appearance standard value as the comprehensive first production quality value to obtain the first production quality coefficient calculation value comprises the following steps:

[0030] Obtain product appearance quality parameters of components in the image, including chromaticity, area and perimeter, standardize the color chromaticity average value in the image with the area and perimeter data of the image to obtain the product appearance quality measurement value, consult the technical manual to obtain the comprehensive appearance standard value obtained by the chromaticity standard value, area standard value and perimeter standard value as the comprehensive first production quality value, and compare it with the product appearance quality measurement value obtained by the chromaticity average value, the abnormal area area calculation value and the abnormal area perimeter calculation value, and obtain the comprehensive first production quality coefficient calculation value through the ratio of the two;

[0031] The calculation formula of the comprehensive first production quality coefficient is:

[0032]

[0033] Among them, M1 is the calculated value of the comprehensive first production quality coefficient, C A is the average chromaticity value, S is the calculated value of the abnormal area, U is the calculated value of the perimeter of the abnormal area, C S is the color standard value, S S is the standard value of area, U S The standard value of circumference.

[0034] As a further solution of the present invention: the production quality parameter test module is used to perform corresponding calculations on the received speed data, pressure data and flow data, respectively, to obtain a speed test value, a pressure test value and a flow test value, including the following steps:

[0035] The speed data, pressure data and flow data obtained by the production quality parameter acquisition module are received and presented in the form of a time series, and the measurement value data at different time points are recorded as historical data. After data conversion, the test value calculation formulas of the speed data, pressure data and flow data are obtained respectively;

[0036] Flow test value calculation formula:

[0037]

[0038] Among them, Q is the flow test value, Q max is the maximum flow rate, Q min is the minimum flow rate, π is a constant in this calculation formula, R is the radius of the tube pump, ΔD is the distance the fluid flows per unit time, ΔT is the unit time, is the flow rate of the fluid;

[0039] Speed ​​test value calculation formula:

[0040]

[0041] Among them, V is the speed test value, V max is the maximum speed, V min is the minimum speed, is the average speed, n is the number of detections, V i is the speed value detected for the i-th time, and e is a constant in the calculation formula;

[0042] Stress test value calculation formula:

[0043]

[0044] Among them, P is the pressure test value, P max is the maximum pressure, P min is the minimum pressure, μ is the friction coefficient, L is the length of the tube pump, and R is the radius of the tube pump.

[0045] As a further solution of the present invention: the production quality parameter abnormality assessment module is used to compare the comprehensive average value of historical speed, pressure and flow data as the comprehensive second production quality value with the comprehensive production quality test value of the speed test value, the pressure test value and the flow test value to obtain a second production quality coefficient, and judge whether the production quality parameter is abnormal based on the result of the comprehensive production quality coefficient comparison, including the following steps:

[0046] The comprehensive average value of the historical speed, pressure and flow data is used as the comprehensive second production quality value, which is compared with the comprehensive production quality test value obtained by the speed test value, the pressure test value and the flow test value, and the second production quality coefficient is obtained by the ratio of the two;

[0047] Comprehensive second production quality numerical calculation formula:

[0048]

[0049] Among them, Z1 is the comprehensive second production quality value, n is the number of tests, Q i is the flow value detected for the i-th time, P i is the pressure value detected at the ith time, V i is the speed value detected for the i-th time, α1, α2 and α3 are weight coefficients;

[0050] The comprehensive production quality test value is obtained by adding the speed test value, pressure test value and flow test value with corresponding weights;

[0051] Comprehensive production quality test numerical calculation formula:

[0052] Z2=α1×Q+α2×P+α3×V

[0053] Among them, Z2 is the comprehensive production quality test value, Q is the flow test value, P is the pressure test value, V is the speed test value, α1, α2 and α3 are weight coefficients;

[0054] The second production quality coefficient calculation formula:

[0055]

[0056] Wherein, M2 is the second production quality coefficient value, Z1 is the comprehensive second production quality value, and Z2 is the comprehensive production quality test value;

[0057] A comprehensive production quality coefficient value is obtained by using the first production quality coefficient value and the second production quality coefficient value, and whether the quality of the produced component parts is abnormal is determined based on the comprehensive production quality coefficient value.

[0058] As a further solution of the present invention: the method of obtaining a comprehensive production quality coefficient value by using the first production quality coefficient value and the second production quality coefficient value, and judging whether the quality of the produced component parts is abnormal according to the comprehensive production quality coefficient value, comprises the following steps:

[0059] Comprehensive production quality coefficient calculation formula:

[0060] M=M1+M2

[0061] Wherein, M is the comprehensive production quality coefficient, M1 is the comprehensive first production quality coefficient value, and M2 is the second production quality coefficient value;

[0062] If M ≥ 2, it means that the quality of the produced components is normal;

[0063] If M < 2, it means that the quality of the produced components is abnormal.

[0064] Beneficial effects of the present invention:

[0065] After collecting image data of a three-way valve tube pump through image processing technology, the present invention performs preprocessing, including image enhancement, brightness adjustment and noise removal. Two-thirds of the image data after preprocessing are randomly sampled to estimate the chromaticity distribution of the overall image data. Random sampling can reduce the impact of a single outlier or noise on the overall result, thereby improving the robustness of the algorithm.

[0066] The present invention uses an edge detection algorithm to extract edge information in image data, performs morphological operations on edge detection results to make contours clearer, processes shapes and structures in images, extracts contours from processed edge images using a contour extraction algorithm and marks them, trains a machine learning model with the marked data set to identify components of a three-way valve tube pump, extracts geometric features of the components through contour information, including the area and perimeter of a normal contour area and an abnormal contour area, realizes automatic recognition and analysis of components of a three-way valve tube pump, and improves production efficiency;

[0067] The present invention obtains a comprehensive production quality coefficient value by measuring the product quality in the production process, reflecting the degree of compliance with the production specifications in the production process, and judging whether there are abnormal products, by obtaining a first production quality coefficient value obtained by ratioing the product appearance quality measurement value with the comprehensive appearance standard value and a second production quality coefficient value obtained by ratioing the product appearance quality measurement value with the comprehensive average value of historical rotation speed, pressure and flow data of the comprehensive production quality test value. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0069] Figure 1 Schematic diagram of the system framework of the present invention. DETAILED DESCRIPTION

[0070] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0071] See also Figure 1 As shown, the present invention is a three-way valve tube pump production quality assessment system, including the following modules:

[0072] Production quality parameter acquisition module: used to divide various types of production equipment in the production plant into specific monitoring areas, and divide the specific monitoring areas into several monitoring sub-areas, marked as 1, 2, 3, ..., n, respectively, to collect the production quality parameters of the three-way valve tube pump in the sub-areas, including speed, pressure, and flow data;

[0073] Component appearance quality detection module: used to monitor the image data of the three-way valve pipe pump components obtained by the camera in the sub-area, analyze the image chromaticity by using image processing technology, extract feature information after preprocessing the image data, obtain the chromaticity average value, identify the image components by machine learning algorithm, extract the geometric features of the components according to the contour information, including the area and perimeter of the normal contour area and the abnormal contour area, compare the product appearance quality measurement value composed of the product appearance quality parameters with the comprehensive appearance standard value as the comprehensive first production quality value to obtain the first production quality coefficient calculation value;

[0074] Production quality parameter test module: used to perform corresponding calculations on the received speed data, pressure data and flow data, and obtain speed test values, pressure test values ​​and flow test values;

[0075] Production quality parameter abnormality assessment module: used to take the comprehensive average value of historical speed, pressure and flow data as the comprehensive second production quality value and compare it with the comprehensive production quality test value of the speed test value, pressure test value and flow test value to obtain the second production quality coefficient, and judge whether the production quality parameters are abnormal based on the result of the comprehensive production quality coefficient comparison.

[0076] Specifically, various types of production equipment in the production plant are divided into specific monitoring areas, each area has corresponding key equipment, which is convenient for centralized management and monitoring. The specific monitoring area is divided into several monitoring sub-areas, and the production quality parameters of the three-way valve tube pump, including speed, pressure, and flow data, are collected in the sub-areas; the image data of the three-way valve tube pump is captured by the camera in the monitoring sub-area, and the acquired image is preprocessed to improve the accuracy of subsequent feature extraction, and the required feature information, including chromaticity, area and perimeter data, is extracted from the preprocessed image, and the comprehensive appearance standard value is used as the comprehensive first production quality value to compare with the product appearance quality measurement value to obtain the first production quality coefficient; the speed sensor, pressure sensor and flow sensor are installed on the three-way valve tube pump to record the speed, pressure and flow data within a certain period of time, and the collected speed, pressure and flow data are analyzed to obtain the corresponding speed test value, pressure test value and flow test value; the comprehensive average value of the historical speed, pressure and flow data is used as the comprehensive second production quality value and compared with the comprehensive production quality test value of the speed test value, pressure test value and flow test value to obtain the second production quality coefficient, and the production quality parameter is judged whether it is abnormal according to the result of the comparison of the comprehensive production quality coefficient.

[0077] In one embodiment of the present invention, the production quality parameter acquisition module is used to divide various types of production equipment in the production plant into specific monitoring areas, and divide the specific monitoring area into a number of monitoring sub-areas, respectively marked as 1, 2, 3, ..., n, and collect the production quality parameters of the three-way valve tube pump in the sub-areas, including speed, pressure, and flow data, including the following steps:

[0078] Analyze the layout of the distribution of various types of production equipment in the production plant, divide the production plant into several specific monitoring areas, each monitoring area contains a group of production equipment with different functions, and divides into several monitoring sub-areas, marked as 1, 2, 3, ..., n, and in each monitoring sub-area, the speed sensor installed on the pipe pump shaft monitors and records the speed data of the pipe pump in real time; the pressure sensor and flow sensor installed on the pipe pump pipeline monitor and record the pressure data and flow data of the pipe pump in real time;

[0079] Among them, the specific monitoring areas are the raw material handling area, production and processing area, and quality inspection and packaging area.

[0080] Specifically, various types of production equipment in the production plant are divided into specific monitoring areas. Each area has corresponding key equipment to facilitate centralized management and monitoring. The specific monitoring area is divided into several monitoring sub-areas, and the production quality parameters of the three-way valve tube pump are collected in the sub-areas, including speed, pressure, and flow data.

[0081] In one embodiment of the present invention, the component appearance quality detection module is used to monitor the image data of the three-way valve pipe pump component obtained by the camera in the sub-area, analyze the image chromaticity by using image processing technology, extract feature information after pre-processing the image data, and obtain the chromaticity average value, including the following steps:

[0082] The original image data of the components of the three-way valve pipe pump are collected by the camera in the monitoring sub-area, and the original data are preprocessed, including image enhancement, brightness adjustment and noise removal. Two-thirds of the image data after preprocessing are randomly extracted, and the color chromaticity range is set to 0-225. The color chromaticity is divided into five levels, each level contains 45 chromaticity units, and the boundary values ​​are 0-44, 45-89, 90-134, 135-179 and 180-225 respectively. In the image processing process, the chromaticity value of the pixel is classified into the corresponding level by comparing the size of the chromaticity value of the pixel with the boundary value;

[0083] The formula for calculating the average chromaticity value is:

[0084]

[0085] Among them, C A is the average chromaticity value, N is the number of pixels, C i is the chromaticity value of the i-th pixel, W i is the weight coefficient corresponding to the chromaticity value of the i-th pixel.

[0086] Specifically, the original image data of the components of the three-way valve tube pump are collected by the camera in the monitoring sub-area, the original data is preprocessed, two-thirds of the image data are randomly extracted, the color chromaticity range is set, and the chromaticity level is equally divided into five levels, and the chromaticity value of the pixel is classified into the corresponding level by comparing the size of the chromaticity value of the pixel with the boundary value, and the chromaticity average value is obtained according to the corresponding weight corresponding to each level and the comprehensive average value of the chromaticity value, so as to simplify the calculation process and improve the robustness of the algorithm; wherein, each level contains 45 chromaticity units, the weight in the range of 0-44 is 1, the weight in the range of 45-89 is 2, the weight in the range of 90-134 is 3, the weight in the range of 135-179 is 4, and the weight in the range of 180-225 is 5.

[0087] In one embodiment of the present invention, the image component is identified by a machine learning algorithm, and the geometric features of the component, including the area and perimeter of the normal contour area and the abnormal contour area, are extracted according to the contour information, including the following steps:

[0088] Preprocess the collected image data, including denoising, smoothing and graying, use edge detection algorithms to extract edge information from the image data, perform morphological operations on the edge detection results, process the shape and structure in the image, use contour extraction algorithms to extract the contours of normal areas and abnormal areas from the processed edge images and mark them, use the marked data set to train a machine learning model to identify the components of the three-way valve tube pump, and extract the geometric features of the components, including area and perimeter, based on the contour information;

[0089] Connect the vertices on the contour of the abnormal area in sequence as a polygon composed of straight line segments to obtain the area of ​​the abnormal area of ​​the component;

[0090] Abnormal area calculation formula:

[0091]

[0092] Among them, S is the calculated value of the abnormal area, n is the total number of vertices on the contour, (x i ,y i ) is the i-th coordinate of the polygon vertex;

[0093] By calculating the length of each side of the polygon and adding them together, the perimeter of the abnormal area of ​​the component is obtained;

[0094] Abnormal area perimeter calculation formula:

[0095]

[0096] Among them, U is the calculated value of the perimeter of the abnormal area, n is the total number of vertices on the contour, (x i ,y i ) is the i-th coordinate of the polygon vertex.

[0097] Specifically, an edge detection algorithm is used to extract edge information from image data, morphological operations are performed on the edge detection results, the shape and structure in the image are processed, and a contour extraction algorithm is used to extract and mark the contours of normal and abnormal areas from the processed edge image. The geometric features of the component, including area and perimeter, are extracted based on the contour information, and the area and perimeter of the abnormal area are obtained through the polygon coordinate point calculation formula.

[0098] In one embodiment of the present invention, the step of comparing the product appearance quality measurement value formed by the product appearance quality parameters with the comprehensive appearance standard value as the comprehensive first production quality value to obtain the first production quality coefficient calculation value comprises the following steps:

[0099] Obtain product appearance quality parameters of components in the image, including chromaticity, area and perimeter, standardize the color chromaticity average value in the image with the area and perimeter data of the image to obtain the product appearance quality measurement value, consult the technical manual to obtain the comprehensive appearance standard value obtained by the chromaticity standard value, area standard value and perimeter standard value as the comprehensive first production quality value, and compare it with the product appearance quality measurement value obtained by the chromaticity average value, the abnormal area area calculation value and the abnormal area perimeter calculation value, and obtain the comprehensive first production quality coefficient calculation value through the ratio of the two;

[0100] The calculation formula of the comprehensive first production quality coefficient is:

[0101]

[0102] Among them, M1 is the calculated value of the comprehensive first production quality coefficient, C A is the average chromaticity value, S is the calculated value of the abnormal area, U is the calculated value of the perimeter of the abnormal area, C S is the color standard value, S S is the standard value of area, U S The standard value of circumference.

[0103] Specifically, the product appearance quality parameters of the components in the image are obtained, including chromaticity, area and perimeter, and the technical manual is consulted to combine the chromaticity standard value, area standard value and perimeter standard value to obtain a comprehensive appearance standard value, and the comprehensive appearance standard value is used as the comprehensive first production quality value. The first production quality coefficient is obtained by weighted averaging the ratios of the chromaticity average value, the area value of the abnormal area and the perimeter value of the abnormal area in the product appearance quality parameters to the chromaticity standard value, the area standard value and the perimeter standard value, respectively. This can not only show the degree of deviation of the abnormal area value from the standard value, but also can comprehensively evaluate the overall appearance quality of the product.

[0104] In one embodiment of the present invention, the production quality parameter test module is used to perform corresponding calculations on the received speed data, pressure data and flow data, respectively, to obtain a speed test value, a pressure test value and a flow test value, including the following steps:

[0105] The speed data, pressure data and flow data obtained by the production quality parameter acquisition module are received and presented in the form of a time series, and the measurement value data at different time points are recorded as historical data. After data conversion, the test value calculation formulas of the speed data, pressure data and flow data are obtained respectively;

[0106] Flow test value calculation formula:

[0107]

[0108] Among them, Q is the flow test value, Qmax is the maximum flow rate, Q min is the minimum flow rate, π is a constant in this calculation formula, R is the radius of the tube pump, ΔD is the distance the fluid flows per unit time, ΔT is the unit time, is the flow rate of the fluid;

[0109] Speed ​​test value calculation formula:

[0110]

[0111] Among them, V is the speed test value, V max is the maximum speed, V min is the minimum speed, ∑ i n ＝1 V i is the average speed, n is the number of detections, V i is the speed value detected for the i-th time, and e is a constant in the calculation formula;

[0112] Stress test value calculation formula:

[0113]

[0114] Among them, P is the pressure test value, P max is the maximum pressure, P min is the minimum pressure, μ is the friction coefficient, L is the length of the tube pump, and R is the radius of the tube pump.

[0115] Specifically, the speed, pressure and flow values ​​measured at different time points are received, the units of the data are unified after data conversion, the corresponding maximum and minimum values ​​of the speed, pressure and flow are obtained through historical data, and the speed test value, pressure test value and flow test value are obtained by comprehensive calculation of multiple data.

[0116] In one embodiment of the present invention, the production quality parameter abnormality assessment module is used to compare the comprehensive average value of historical speed, pressure and flow data as the comprehensive second production quality value with the comprehensive production quality test value of the speed test value, the pressure test value and the flow test value to obtain a second production quality coefficient, and judge whether the production quality parameter is abnormal according to the result of the comprehensive production quality coefficient comparison, including the following steps:

[0117] The comprehensive average value of the historical speed, pressure and flow data is used as the comprehensive second production quality value, which is compared with the comprehensive production quality test value obtained by the speed test value, the pressure test value and the flow test value, and the second production quality coefficient is obtained by the ratio of the two;

[0118] Comprehensive second production quality numerical calculation formula:

[0119]

[0120] Among them, Z1 is the comprehensive second production quality value, n is the number of tests, Q i is the flow value detected for the i-th time, P i is the pressure value detected at the ith time, V i is the speed value detected for the i-th time, α1, α2 and α3 are weight coefficients;

[0121] The comprehensive production quality test value is obtained by adding the speed test value, pressure test value and flow test value with corresponding weights;

[0122] Comprehensive production quality test numerical calculation formula:

[0123] Z2=α1×Q+α2×P+α3×V

[0124] Among them, Z2 is the comprehensive production quality test value, Q is the flow test value, P is the pressure test value, V is the speed test value, α1, α2 and α3 are weight coefficients;

[0125] The second production quality coefficient calculation formula:

[0126]

[0127] Wherein, M2 is the second production quality coefficient value, Z1 is the comprehensive second production quality value, and Z2 is the comprehensive production quality test value;

[0128] A comprehensive production quality coefficient value is obtained by using the first production quality coefficient value and the second production quality coefficient value, and whether the quality of the produced component parts is abnormal is determined based on the comprehensive production quality coefficient value.

[0129] Specifically, the average values ​​of the historical speed, pressure and flow data are assigned corresponding weights and added together to form the comprehensive second production quality value; the speed test value, pressure test value and flow test value are assigned corresponding weights and added together to form the comprehensive production quality test value; the second production quality coefficient is obtained by the ratio of the comprehensive production quality test value to the comprehensive second production quality value; wherein α1, α2 and α3 are weight coefficients respectively, the value of α1 is 0.5, the value of α2 is 0.3, and the value of α3 is 0.2.

[0130] In one embodiment of the present invention, the step of obtaining a comprehensive production quality coefficient value by using the first production quality coefficient value and the second production quality coefficient value, and judging whether the quality of the produced component parts is abnormal according to the comprehensive production quality coefficient value comprises the following steps:

[0131] Comprehensive production quality coefficient calculation formula:

[0132] M=M1+M2

[0133] Wherein, M is the comprehensive production quality coefficient, M1 is the comprehensive first production quality coefficient value, and M2 is the second production quality coefficient value;

[0134] If M ≥ 2, it means that the quality of the produced components is normal;

[0135] If M < 2, it means that the quality of the produced components is abnormal.

[0136] Specifically, the first production quality coefficient and the second production quality coefficient are combined to obtain a comprehensive production quality coefficient, and whether the production quality parameter is abnormal is determined based on a comparison result of the comprehensive production quality coefficient.

[0137] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. The three-way valve tube pump production quality assessment system is characterized by: Includes the following modules: Production quality parameter acquisition module: used to divide various types of production equipment in the production plant into specific monitoring areas, and divide the specific monitoring areas into several monitoring sub-areas, marked as 1, 2, 3, ..., n, respectively, to collect the production quality parameters of the three-way valve tube pump in the sub-areas, including speed, pressure, and flow data; Component appearance quality detection module: used to monitor the image data of the three-way valve pipe pump components obtained by the camera in the sub-area, analyze the image chromaticity by using image processing technology, extract feature information after preprocessing the image data, obtain the chromaticity average value, identify the image components by machine learning algorithm, extract the geometric features of the components according to the contour information, including the area and perimeter of the normal contour area and the abnormal contour area, compare the product appearance quality measurement value composed of the product appearance quality parameters with the comprehensive appearance standard value as the comprehensive first production quality value to obtain the first production quality coefficient calculation value; Production quality parameter test module: used to perform corresponding calculations on the received speed data, pressure data and flow data, and obtain speed test values, pressure test values ​​and flow test values; Production quality parameter abnormality assessment module: used to take the comprehensive average value of historical speed, pressure and flow data as the comprehensive second production quality value and compare it with the comprehensive production quality test value of the speed test value, pressure test value and flow test value to obtain the second production quality coefficient, and judge whether the production quality parameters are abnormal based on the result of the comprehensive production quality coefficient comparison.

2. The three-way valve tube pump production quality assessment system according to claim 1 is characterized in that: The production quality parameter acquisition module is used to divide various types of production equipment in the production plant into specific monitoring areas, and divide the specific monitoring areas into several monitoring sub-areas, which are marked as 1, 2, 3, ..., n, respectively, and collect the production quality parameters of the three-way valve tube pump in the sub-areas, including speed, pressure, and flow data, including the following steps: Analyze the layout of the distribution of various types of production equipment in the production plant, divide the production plant into several specific monitoring areas, each monitoring area contains a group of production equipment with different functions, and divides into several monitoring sub-areas, marked as 1, 2, 3, ..., n, and in each monitoring sub-area, the speed sensor installed on the pipe pump shaft monitors and records the speed data of the pipe pump in real time; the pressure sensor and flow sensor installed on the pipe pump pipeline monitor and record the pressure data and flow data of the pipe pump in real time; Among them, the specific monitoring areas are the raw material handling area, production and processing area, and quality inspection and packaging area.

3. The three-way valve tube pump production quality assessment system according to claim 1 is characterized in that: The component appearance quality detection module is used to monitor the image data of the three-way valve pipe pump component obtained by the camera in the sub-area, analyze the image chromaticity by using image processing technology, extract feature information after pre-processing the image data, and obtain the chromaticity average value, including the following steps: The original image data of the components of the three-way valve pipe pump are collected by the camera in the monitoring sub-area, and the original data are preprocessed, including image enhancement, brightness adjustment and noise removal. Two-thirds of the image data after preprocessing are randomly extracted, and the color chromaticity range is set to 0-225. The color chromaticity is divided into five levels, each level contains 45 chromaticity units, and the boundary values ​​are 0-44, 45-89, 90-134, 135-179 and 180-225 respectively. In the image processing process, the chromaticity value of the pixel is classified into the corresponding level by comparing the size of the chromaticity value of the pixel with the boundary value; Chromaticity average calculation formula Among them, C A is the average chromaticity value, N is the number of pixels, C i is the chromaticity value of the i-th pixel, W i is the weight coefficient corresponding to the chromaticity value of the i-th pixel.

4. The three-way valve tube pump production quality assessment system according to claim 1, characterized in that: The image components are identified by machine learning algorithms, and the geometric features of the components are extracted according to the contour information, including the area and perimeter of the normal contour area and the abnormal contour area, including the following steps: Preprocess the collected image data, including denoising, smoothing and graying, use edge detection algorithms to extract edge information from the image data, perform morphological operations on the edge detection results, process the shape and structure in the image, use contour extraction algorithms to extract the contours of normal areas and abnormal areas from the processed edge images and mark them, use the marked data set to train a machine learning model to identify the components of the three-way valve tube pump, and extract the geometric features of the components, including area and perimeter, based on the contour information; Connect the vertices on the contour of the abnormal area in sequence as a polygon composed of straight line segments to obtain the area of ​​the abnormal area of ​​the component; Abnormal area calculation formula: Among them, S is the calculated value of the abnormal area, n is the total number of vertices on the contour, (x i ,y i ) is the i-th coordinate of the polygon vertex; By calculating the length of each side of the polygon and adding them together, the perimeter of the abnormal area of ​​the component is obtained; Abnormal area perimeter calculation formula: Among them, U is the calculated value of the perimeter of the abnormal area, n is the total number of vertices on the contour, (x i ,y i ) is the i-th coordinate of the polygon vertex.

5. The three-way valve tube pump production quality assessment system according to claim 1, characterized in that: The method of comparing the product appearance quality measurement value formed by the product appearance quality parameters with the comprehensive appearance standard value as the comprehensive first production quality value to obtain the first production quality coefficient calculation value comprises the following steps: Obtain product appearance quality parameters of components in the image, including chromaticity, area and perimeter, standardize the color chromaticity average value in the image with the area and perimeter data of the image to obtain the product appearance quality measurement value, consult the technical manual to obtain the comprehensive appearance standard value obtained by the chromaticity standard value, area standard value and perimeter standard value as the comprehensive first production quality value, and compare it with the product appearance quality measurement value obtained by the chromaticity average value, the abnormal area area calculation value and the abnormal area perimeter calculation value, and obtain the comprehensive first production quality coefficient calculation value through the ratio of the two; The calculation formula of the comprehensive first production quality coefficient is: Among them, M1 is the calculated value of the comprehensive first production quality coefficient, C A is the average chromaticity value, S is the calculated value of the abnormal area, U is the calculated value of the perimeter of the abnormal area, C S is the color standard value, S S is the standard value of area, U S The standard value of circumference.

6. The three-way valve tube pump production quality assessment system according to claim 1, characterized in that: The production quality parameter test module is used to perform corresponding calculations on the received speed data, pressure data and flow data, respectively, to obtain a speed test value, a pressure test value and a flow test value, and includes the following steps: The speed data, pressure data and flow data obtained by the production quality parameter acquisition module are received and presented in the form of a time series, and the measured value data at different time points are recorded as historical data. After data conversion, the test value calculation formulas of the speed data, pressure data and flow data are obtained respectively; Flow test value calculation formula: Among them, Q is the flow test value, Q max is the maximum flow rate, Q min is the minimum flow rate, π is a constant in this calculation formula, R is the radius of the tube pump, ΔD is the distance the fluid flows per unit time, ΔT is the unit time, is the flow rate of the fluid; Speed ​​test value calculation formula: Among them, V is the speed test value, V max is the maximum speed, V min is the minimum speed, is the average speed, n is the number of detections, V i is the speed value detected for the i-th time, and e is a constant in the calculation formula; Stress test value calculation formula: Among them, P is the pressure test value, P max is the maximum pressure, P min is the minimum pressure, μ is the friction coefficient, L is the length of the tube pump, and R is the radius of the tube pump.

7. The three-way valve tube pump production quality assessment system according to claim 1, characterized in that: The production quality parameter abnormality assessment module is used to compare the comprehensive average value of historical speed, pressure and flow data as the comprehensive second production quality value with the comprehensive production quality test value of the speed test value, the pressure test value and the flow test value to obtain a second production quality coefficient, and judge whether the production quality parameter is abnormal according to the result of the comprehensive production quality coefficient comparison, including the following steps: The comprehensive average value of the historical speed, pressure and flow data is used as the comprehensive second production quality value, which is compared with the comprehensive production quality test value obtained by the speed test value, the pressure test value and the flow test value, and the second production quality coefficient is obtained by the ratio of the two; Comprehensive second production quality numerical calculation formula: Among them, Z1 is the comprehensive second production quality value, n is the number of tests, Q i is the flow value detected for the i-th time, P i is the pressure value detected at the ith time, V i is the speed value detected for the i-th time, α1, α2 and α3 are weight coefficients; The comprehensive production quality test value is obtained by adding the speed test value, pressure test value and flow test value with corresponding weights; Comprehensive production quality test numerical calculation formula: Z2=α1×Q+α2×P+α3×V Among them, Z2 is the comprehensive production quality test value, Q is the flow test value, P is the pressure test value, V is the speed test value, α1, α2 and α3 are weight coefficients; The second production quality coefficient calculation formula: Wherein, M2 is the second production quality coefficient value, Z1 is the comprehensive second production quality value, and Z2 is the comprehensive production quality test value; A comprehensive production quality coefficient value is obtained by using the first production quality coefficient value and the second production quality coefficient value, and whether the quality of the produced component parts is abnormal is determined based on the comprehensive production quality coefficient value.

8. The three-way valve tube pump production quality assessment system according to claim 7, characterized in that: The method of obtaining a comprehensive production quality coefficient value by using the first production quality coefficient value and the second production quality coefficient value, and judging whether the quality of the produced component parts is abnormal according to the comprehensive production quality coefficient value, comprises the following steps: Comprehensive production quality coefficient calculation formula: M=M1+M2 Wherein, M is the comprehensive production quality coefficient, M1 is the comprehensive first production quality coefficient value, and M2 is the second production quality coefficient value; If M ≥ 2, it means that the quality of the produced components is normal; If M < 2, it means that the quality of the produced components is abnormal.

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