A method for detecting overprinting line pollution and related equipment

Abstract

An embodiment of the present invention provides a method for detecting the pollution of a color - matching line, including: constructing an initial simulation model of the color - matching line based on the equipment structure and parameters of the color - matching line; under different working conditions, performing a first adjustment on the initial simulation model through the historical operation data of the color - matching line, and performing a second adjustment on the initial simulation model through the historical pollution generation data of the color - matching line to obtain target simulation models for different working conditions, where each working condition corresponds to a target simulation model; performing simulation on the color - matching line through the corresponding target simulation model to obtain pollution simulation results under different working conditions; and determining the pollution detection results of the color - matching line under different working conditions based on the pollution simulation results. The present invention can solve the problems of inaccurate pollution detection and inability to comprehensively reflect the environmental quality in the existing pollution detection methods.

Description

Technical Field

[0001] The present invention relates to the technical field of pollution detection, and particularly to a method for detecting the pollution of overprinting lines and related equipment. Background Art

[0002] With the rapid development of the automotive industry, automobiles have become one of the indispensable means of transportation for people to travel. Automobile painting is one of the processes with the highest energy consumption and the most generation of three wastes in the automobile manufacturing process. The pollution problem of overprinting lines mainly comes from the painting line. For example, the waste gas generated by the volatilization of solvents during the drying of coatings, the production water for electrophoresis and the wastewater in the upper and middle coating circulation water tanks, and the paint sludge generated after painting. In the existing pollution detection methods, due to technical limitations, there are problems such as inaccurate pollution detection and inability to comprehensively reflect the environmental quality. Summary of the Invention

[0003] An embodiment of the present invention provides a method for detecting the pollution of overprinting lines, aiming to solve the problems of inaccurate pollution detection and inability to comprehensively reflect the environmental quality in the pollution detection method. By constructing an initial simulation model of the overprinting line according to the equipment structure and parameters of the overprinting line, under different working conditions, the initial simulation model is first adjusted through the historical operation data of the overprinting line, and then the initial simulation model is secondarily adjusted through the historical pollution generation data of the overprinting line to obtain the target simulation models under different working conditions, and the overprinting line is simulated through the corresponding target simulation models to obtain the pollution simulation results under different working conditions, and the pollution detection results of the overprinting line under different working conditions are determined according to the pollution simulation results, so as to solve the problems of inaccurate pollution detection and inability to comprehensively reflect the environmental quality in the pollution detection method.

[0004] In a first aspect, an embodiment of the present invention provides a method for detecting the pollution of overprinting lines, the method comprising:

[0005] Constructing an initial simulation model of the overprinting line based on the equipment structure and parameters of the overprinting line;

[0006] Under different working conditions, first adjusting the initial simulation model through the historical operation data of the overprinting line, and secondarily adjusting the initial simulation model through the historical pollution generation data of the overprinting line to obtain target simulation models under different working conditions, each working condition corresponding to a target simulation model;

[0007] Performing simulation on the overprinting line through the corresponding target simulation model to obtain pollution simulation results under different working conditions;

[0008] Determining the pollution detection results of the overprinting line under different working conditions based on the pollution simulation results.

[0009] Optionally, the step of first adjusting the initial simulation model by using the historical operation data of the overprinting line under different working conditions includes:

[0010] Obtain the historical operation data of the overprinting line under each working condition;

[0011] For each working condition, fit or predict the historical operation data in multiple dimensions to obtain multi-dimensional operation parameters, and each working condition corresponds to one set of the multi-dimensional operation parameters;

[0012] Based on the multi-dimensional operation parameters, perform a first adjustment on the initial simulation model.

[0013] Optionally, the step of second adjusting the initial simulation model by using the historical pollution generation data of the overprinting line includes:

[0014] Obtain the historical pollution generation data of the overprinting line under each working condition;

[0015] For each working condition, divide the historical pollution generation data by time period to obtain a pollution generation data sequence, and each working condition corresponds to one set of the pollution generation data sequence. Each pollution generation data sequence includes N pollution generation data segments sorted by time period;

[0016] Considering pollution residue, calculate the weights of the pollution generation data sequence to obtain a target pollution generation data sequence;

[0017] Through a time series prediction network, predict the target pollution generation data sequence to obtain predicted pollution source parameters, and each working condition corresponds to one set of the predicted pollution source parameters;

[0018] Based on the predicted pollution source parameters, perform a second adjustment on the initial simulation model.

[0019] Optionally, the step of considering pollution residue, calculating the weights of the pollution generation data sequence, and obtaining a target pollution generation data sequence includes:

[0020] Determine the time sequence position of each pollution generation data segment;

[0021] According to the time sequence position, determine the pollution weights of the respective pollution generation data segments. The later the time sequence position, the greater the pollution weight. The pollution weight is calculated according to the following formula:

[0022]

[0023] where W i represents the pollution weight of the pollution generation data segment at the i-th time sequence position, and t irepresents the time interval from the i-th time sequence position to the starting time, N represents the number of pollution generation data segments, and softmax() represents the normalization function;

[0024] Perform weighted calculation on each of the pollution generation data segments based on the pollution weights to obtain a target pollution generation data sequence.

[0025] Optionally, the step of simulating and emulating the overprinting line through the corresponding target simulation model to obtain pollution simulation results under different working conditions includes:

[0026] Under the current working condition, match the target simulation model corresponding to the working condition, and each working condition corresponds to one target simulation model;

[0027] Transmit the operating parameters of the overprinting line under the current working condition to the target simulation model in real time, and set a fourth time period;

[0028] Output the pollution simulation results of the overprinting line in the fourth time period under the current working condition through the target simulation model.

[0029] Optionally, the target inverse model includes a historical data processing unit, a reference data processing unit, and an output data processing unit, and the historical data processing unit, the data processing unit, and the output data processing unit are continuous in time; the step of obtaining the pollution simulation results of the overprinting line under the current working condition through the target simulation model includes:

[0030] Keep the operating parameters unchanged within the first time period through the historical data processing unit;

[0031] Update the reference operating parameters within the second time period according to the operating parameters within the first time period through the reference data processing unit, keep the reference operating parameters similar to or the same as the operating parameters within the second time period, and obtain the model prediction parameters within the second time period. The first time period is before the second time period, and the end time of the second time period is the current moment or between the current moments;

[0032] Update the pollution simulation results of the fourth time period according to the operating parameters within the third time period and the model prediction parameters within the second time period through the output data processing unit. The third time period ends at the current time, the length of the third time period is the same as the length of the first time period, and the fourth time period is after the third time period.

[0033] Optionally, the step of determining the pollution detection results of the overprinting line under different working conditions based on the pollution simulation results includes:

[0034] For the current working condition, obtain the confidence level of the pollution simulation result, where the confidence level is output by the target simulation model, and the above pollution simulation result corresponds to a confidence level;

[0035] When the confidence level is less than the first confidence level threshold, determine the pollution detection result of the overprint line under the current working condition according to the pollution simulation result at the next moment;

[0036] When the confidence level is greater than or equal to the first confidence level threshold and less than the second confidence level threshold, compensate the pollution simulation result according to the compensation coefficient corresponding to the current working condition, and determine the compensated pollution simulation result as the pollution detection result of the overprint line under the current working condition, where the second confidence level threshold is greater than the first confidence level threshold;

[0037] When the confidence level is greater than or equal to the second confidence level threshold, determine the pollution simulation result as the pollution detection result of the overprint line under the current working condition.

[0038] In a second aspect, an embodiment of the present invention further provides an overprint line pollution detection device, where the overprint line pollution detection device includes:

[0039] A construction module for constructing an initial simulation model of the overprint line based on the device structure and parameters of the overprint line;

[0040] An adjustment module for, under different working conditions, performing a first adjustment on the initial simulation model through the historical operation data of the overprint line, and performing a second adjustment on the initial simulation model through the historical pollution generation data of the overprint line to obtain target simulation models for different working conditions, where each working condition corresponds to a target simulation model;

[0041] A simulation module for performing simulation on the overprint line through the corresponding target simulation model to obtain pollution simulation results under different working conditions;

[0042] A determination module for determining the pollution detection result of the overprint line under different working conditions based on the pollution simulation result.

[0043] In a third aspect, an embodiment of the present invention provides an electronic device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, where when the processor executes the computer program, the steps in the overprint line pollution detection method provided by the embodiment of the present invention are implemented.

[0044] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps in the overprint line pollution detection method provided by the embodiment of the invention are implemented.

[0045] In an embodiment of the present invention, an initial simulation model of the color - matching line is constructed based on the equipment structure and parameters of the color - matching line; under different working conditions, the initial simulation model is first adjusted through the historical operation data of the color - matching line, and second adjusted through the historical pollution generation data of the color - matching line to obtain a target simulation model for different working conditions, with each working condition corresponding to a target simulation model; the color - matching line is simulated through the corresponding target simulation model to obtain pollution simulation results under different working conditions; based on the pollution simulation results, the pollution detection results of the color - matching line under different working conditions are determined. The present invention can solve the problems of inaccurate pollution detection and inability to comprehensively reflect environmental quality in existing pollution detection methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or in the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following - described drawings are only some embodiments of the present invention, and those of ordinary skill in the art can obtain other drawings based on these drawings without creative efforts.

[0047] Figure 1 is a flowchart of a method for detecting pollution of a color - matching line provided by an embodiment of the present invention;

[0048] Figure 2 is a schematic structural diagram of a device for detecting pollution of a color - matching line provided by an embodiment of the present invention;

[0049] Figure 3 is a schematic structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0050] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the 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 of them. All other embodiments obtained by those of ordinary skill in the art without creative efforts based on the embodiments of the present invention belong to the scope of protection of the present invention.

[0051] As Figure 1 shown, Figure 1 is a method flowchart of a method for detecting pollution of a color - matching line provided by an embodiment of the present invention. The method for detecting pollution of the color - matching line includes the following steps:

[0052] 10 1. Based on the equipment structure and parameters of the color - matching line, construct an initial simulation model of the color - matching line.

[0053] In an embodiment of the present invention, the above-described overprinting line pollution detection method can be applied to an intelligent device, which can be understood as an intelligent device that needs to perform overprinting line pollution detection, such as various production line terminal devices.

[0054] The above-described overprinting line can be understood as a process for achieving a layered effect of different colors or materials on the vehicle surface. The above device structure includes the components of the device, such as an unwinder, a spraying machine, an electrophoresis device, a printing machine, a winder, etc. The above parameters include various parameters of the device operation, such as working speed, production efficiency, energy consumption, etc.

[0055] The above simulation model is a dynamic simulation model, which can simulate the real production environment and the device operation conditions. The above simulation model can include a three-dimensional dynamic simulation model established using Delmia-Quest software and a data processing model based on time series. In the three-dimensional dynamic simulation model, each device structure receives corresponding operation parameters and simulates corresponding operation states according to the corresponding operation parameters to output corresponding simulation data. The data processing model performs pollution detection based on the simulation data output by the three-dimensional dynamic simulation model.

[0056] The above initial simulation model can be understood as a simulation model used to describe the initial state and performance of the overprinting line.

[0057] It should be noted that by constructing an initial simulation model of the overprinting line according to the device structure and parameters of the overprinting line, the overprinting line in the real production environment and device operation conditions, as well as the pollution generation situation, can be simulated.

[0058] 102. Under different working conditions, the initial simulation model is first adjusted by the historical operation data of the overprinting line, and then second adjusted by the historical pollution generation data of the overprinting line to obtain a target simulation model for different working conditions.

[0059] In an embodiment of the present invention, each working condition corresponds to a target simulation model.

[0060] The above different working conditions can be different production environments, different device states, different operation methods, etc.

[0061] The above historical operation data of the overprinting line can be understood as data such as operation parameters and performance indicators of the historical overprinting line under different working conditions. By analyzing the historical operation data of the overprinting line under different working conditions, the performance of the overprinting line under various working conditions can be understood. The historical operation data of the overprinting line includes operation speed, paint type and characteristics, etc. Under different working conditions, the operation speed of the overprinting line may be different; under different working conditions, the operation method of the overprinting line may be different. The above historical operation data of the overprinting line can come from the records of the historical actual production process.

[0062] The historical pollution generation data of the above-mentioned color printing line can be understood as the pollution data generated by the historical color printing line under different working conditions. By analyzing the historical pollution generation data of the color printing line under different working conditions, the pollution data of the color printing line under different working conditions can be understood. The historical pollution generation data of the color printing line includes the types and concentrations of pollutants, etc. Under different working conditions, the color printing line may generate different types of pollutants, such as paint residues, heavy metals, etc.

[0063] The above-mentioned first adjustment and second adjustment are both processes of adjusting and optimizing the parameters, algorithms or structures of the data processing model in the simulation model to improve the performance of the simulation model in simulating actual working conditions and the generated pollution data. The above-mentioned data processing model can be a time series model based on a recurrent neural network (RNN) or a long short-term memory network (LSTM). The above-mentioned data processing model can be a pre-trained model. The above-mentioned first adjustment can be an adaptive adjustment or adaptive training to improve the generalization ability of the data processing model. The above-mentioned second adjustment can be a targeted adjustment or targeted training to improve the accuracy of the data processing model for pollution detection. In a possible embodiment, the pollution detection result of the above-mentioned data processing model can also adjust the above-mentioned three-dimensional dynamic simulation model in the form of negative feedback. The above-mentioned adjustment can be reinforcement learning based on rewards, and the reward value can be the confidence level of the pollution detection result. The higher the confidence level, the greater the reward value.

[0064] Under different working conditions, the initial simulation model is first adjusted through the historical operation data of the color printing line so that the simulation model can better simulate the performance of the color printing line under different working conditions. Under different working conditions, the initial simulation model is second adjusted through the historical pollution generation data of the color printing line so that the simulation model can better simulate the different degrees of pollution data generated by the color printing line under different working conditions.

[0065] The above-mentioned different target simulation models can simulate the influence of different production processes, equipment parameters, environmental conditions and other factors on pollutants, so as to predict the pollutant concentration and distribution under different working conditions through the data processing model.

[0066] It should be noted that under different working conditions, the initial simulation model is first adjusted and second adjusted according to the historical operation data and historical pollution generation data of the color printing line, so as to obtain the target simulation model for different working conditions.

[0067] 103. Simulate and simulate the color printing line through the corresponding target simulation model to obtain the pollution simulation results under different working conditions.

[0068] In the embodiment of the present invention, the above-mentioned one target simulation model corresponds to one working condition.

[0069] Under different working conditions, the overprinting line is simulated and the data is processed through the corresponding target simulation model, so as to obtain the pollution simulation results under different working conditions.

[0070] The above pollution simulation results can be understood as the evaluation effects generated during the process of simulating the pollution situation, and can be the prediction results output by the data processing model. The pollution simulation results can predict and analyze the possible pollution problems in the production process.

[0071] 104. Based on the pollution simulation results, determine the pollution detection results of the overprinting line under different working conditions.

[0072] In the embodiment of the present invention, the pollution detection results of the overprinting line under different working conditions can be determined according to the pollution simulation results.

[0073] The above pollution detection results are quantitative or qualitative measurements and analyses of the pollutants generated during the production process. The pollution detection results are used to monitor the pollutant content in emissions such as waste gas, waste water and waste residue to ensure that the pollutant content meets the environmental protection standards.

[0074] In the embodiment of the present invention, through the simulation model, the pollution simulation results under different working conditions can be predicted, and based on the pollution simulation results, the pollution detection results of the overprinting line under different working conditions can be determined. The present invention can effectively improve the accuracy of pollution detection.

[0075] In the embodiment of the present invention, based on the equipment structure and parameters of the overprinting line, an initial simulation model of the overprinting line is constructed; under different working conditions, the initial simulation model is first adjusted through the historical operation data of the overprinting line, and the initial simulation model is second adjusted through the historical pollution generation data of the overprinting line to obtain target simulation models for different working conditions, each working condition corresponding to a target simulation model; the overprinting line is simulated through the corresponding target simulation model to obtain pollution simulation results under different working conditions; based on the pollution simulation results, the pollution detection results of the overprinting line under different working conditions are determined. The present invention can solve the problems of inaccurate pollution detection and inability to comprehensively reflect the environmental quality in the existing pollution detection methods.

[0076] Optionally, the step of first adjusting the initial simulation model through the historical operation data of the overprinting line under different working conditions includes:

[0077] Obtain the historical operation data of the overprinting line under each working condition; for each working condition, fit or predict the historical operation data in multiple dimensions to obtain multi-dimensional operation parameters, each working condition corresponding to a multi-dimensional operation parameter; first adjust the initial simulation model based on the multi-dimensional operation parameters.

[0078] In the embodiments of the present invention, the above-mentioned working conditions can be understood as the operating states of the color - matching lines. Different working conditions include different production environments, different equipment states, different operation modes, etc.

[0079] The above - mentioned historical operation data can be from the records of the historical actual production process. The historical operation data includes operation parameters, performance indicators, etc. of the historical color - matching lines under different working conditions.

[0080] The above - mentioned multiple dimensions can be temperature, pressure, speed, humidity, etc.

[0081] The above - mentioned multi - dimensional operation parameters can be understood as that when describing the performance of the color - matching line under different working conditions, multiple factors and dimensions need to be considered, including temperature, pressure, speed, humidity, etc. The multi - dimensional operation parameters can be used as the input of the optimization algorithm to further optimize the production process and improve product quality and production efficiency.

[0082] For each working condition, it is necessary to fit or predict the historical operation data under this working condition, and extract multi - dimensional operation parameters from the historical data. The multi - dimensional parameters can reflect the performance of the color - matching line under this working condition.

[0083] The above - mentioned fitting or prediction can be methods such as linear regression, support vector machine, neural network, etc.

[0084] The above - mentioned first adjustment can be understood as the process of adjusting and optimizing the parameters, algorithms or structures of the data - processing model in the simulation model to improve the performance of the simulation model in simulating actual working conditions.

[0085] It should be noted that the initial simulation model can be adjusted and optimized with multi - dimensional operation parameters through multi - dimensional operation parameters.

[0086] Optionally, the steps of performing a second adjustment on the initial simulation model through the historical pollution generation data of the color - matching line include:

[0087] Obtain the historical pollution generation data of the color - matching line under each working condition; for each working condition, divide the historical pollution generation data by time period to obtain a pollution generation data sequence. Each working condition corresponds to a pollution generation data sequence, and each pollution generation data sequence includes N pollution generation data segments sorted by time period; considering pollution residue, calculate the weights of the pollution generation data sequence to obtain a target pollution generation data sequence; predict the target pollution generation data sequence through a time - series prediction network to obtain predicted pollution source parameters. Each working condition corresponds to a predicted pollution source parameter; perform a second adjustment on the initial simulation model based on the predicted pollution source parameters.

[0088] In the embodiments of the present invention, the above historical pollution generation data is the pollution data generated by the historical overprinting line under different working conditions. The historical pollution generation data of the overprinting line includes the types, distributions, and concentrations of pollutants, etc.

[0089] The above division by time period is to divide the historical pollution generation data only in the order of a certain time interval. For example, every fifteen minutes, every 30 minutes, every hour, every day, etc.

[0090] The above pollution generation data sequence can be understood as a sequence containing multiple data segments. Each sequence represents the pollution data within a specific time period and can be used to analyze and predict the pollution generation situation of the overprinting line under different working conditions.

[0091] The above weight calculation is used to determine the importance of different factors. The weight calculation can be performed using methods such as the analytic hierarchy process and the entropy method.

[0092] The above time series prediction network is a deep learning model that can process and predict time series data. The time series prediction network can be a recurrent neural network (RNN), a long short-term memory network (LSTM), a convolutional neural network (CNN), etc.

[0093] The above predicted pollution source parameters can be various indicators related to pollutants, such as concentration, emission amount, etc.

[0094] The above second adjustment can be understood as a process of adjusting and optimizing the parameters, algorithms, or structures of the data processing model in the simulation model to improve the performance of the simulation model in simulating actual working conditions.

[0095] It should be noted that the initial simulation model can be adjusted and optimized for the pollution source parameters through the predicted pollution source parameters.

[0096] Optionally, considering pollution residue, the steps of calculating the weights of the pollution generation data sequence to obtain the target pollution generation data sequence include:

[0097] Determine the time sequence position of each pollution generation data segment; according to the time sequence position, determine the pollution weight of each pollution generation data segment. The later the time sequence position, the greater the pollution weight; the pollution weight is calculated according to the following formula:

[0098]

[0099] Among them, W i represents the pollution weight of the pollution generation data segment at the i-th time sequence position, t irepresents the time interval from the i-th time sequence position to the starting time, N represents the number of pollution generation data segments, and softmax() represents the normalization function; based on the pollution weights, weighted calculation is performed on each pollution generation data segment to obtain the target pollution generation data sequence.

[0100] In the embodiments of the present invention, the above time sequence position is an identifier of the position or order of a data element in the time sequence. In a time sequence, each data element has a unique time sequence position, which is used to represent its position in the sequence. For example, assume there is a time sequence containing 10 pollution generation data segments, then these data segments will be assigned serial numbers from 1 to 10 to represent their positions in the time sequence. The serial number of the first data segment is 1, the serial number of the second data segment is 2, and so on, and the serial number of the tenth data segment is 10.

[0101] The above pollution weight can be a ratio, fraction or other numerical value, which is used to represent the degree of influence of the position of this data segment in the time sequence on the total pollution..

[0102] The above weighted summation can be understood as summing a set of data or vectors after weighting them according to different weights. Specifically, for each data or vector, it will be multiplied by a weight, and then all the products are summed to obtain the result.

[0103] It should be noted that first, it is necessary to determine the position or order of each pollution generation data segment in the time sequence, that is, the time sequence position. Then, according to the time sequence position of this data segment, its pollution weight is determined. Next, multiply the pollution weight of each data segment by its corresponding pollution generation data, and then sum all the products to obtain the target pollution generation data sequence.

[0104] Optionally, the steps of simulating the overprinting line through the corresponding target simulation model to obtain the pollution simulation results under different working conditions include:

[0105] Under the current working condition, match the target simulation model corresponding to the working condition, and each working condition corresponds to a target simulation model; transmit the operating parameters of the overprinting line under the current working condition into the target simulation model in real time, and set the fourth time period; output the pollution simulation results of the overprinting line in the fourth time period under the current working condition through the target simulation model.

[0106] In the embodiments of the present invention, the above fourth time period can be understood as the fourth time point or time period set in the simulation model. The fourth time period can be used to observe the performance of the overprinting line within the fourth time period.

[0107] The above pollution simulation results can be understood as the evaluation effect generated by the process of simulating the pollution situation. The pollution simulation results can predict and analyze possible pollution problems in the production process.

[0108] It can be understood that under the current working condition, a target simulation model corresponding to the current working condition is matched, and the operating parameters of the overprinting line under the current working condition are transmitted into the target simulation model in real time. A fourth time period is set, and the target simulation model outputs a pollution simulation result of the overprinting line within the fourth time period under the current working condition according to the input operating parameters and the set fourth time period.

[0109] Optionally, the data processing model in the target simulation model may include a historical data processing unit, a reference data processing unit, and an output data processing unit, and the historical data processing unit, the reference data processing unit, and the output data processing unit are continuous in time. The steps of outputting the pollution simulation result of the overprinting line under the current working condition through the target simulation model include:

[0110] The historical data processing unit keeps the operating parameters within the first time period unchanged; the reference data processing unit updates the reference operating parameters within the second time period according to the operating parameters within the first time period, and keeps the reference operating parameters similar to or the same as the operating parameters within the second time period, and obtains the model prediction parameters within the second time period. The first time period is before the second time period, and the end time of the second time period is the current time or between the current times; the output data processing unit updates the pollution simulation result of the fourth time period according to the operating parameters within the third time period and the model prediction parameters within the second time period. The third time period ends at the current time, the length of the third time period is the same as the length of the first time period, and the fourth time period is after the third time period. The length of the second time period is the same as the length of the fourth time period.

[0111] In the embodiment of the present invention, the above-mentioned historical data processing unit is responsible for keeping the operating parameters within the first time period unchanged; the above-mentioned reference data processing unit is responsible for updating the reference operating parameters within the second time period according to the operating parameters within the first time period; the above-mentioned output data processing unit is responsible for updating the pollution simulation result of the fourth time period according to the operating parameters within the third time period and the model prediction parameters within the second time period. The historical data processing unit, the reference data processing unit, and the output data processing unit are continuous in time, that is, the reference data processing unit works after the historical data processing unit, and the output data processing unit works after the reference data processing unit.

[0112] The above-mentioned first time period can be understood as the first time point or time period set in the simulation model. The second time period can be understood as the second time point or time period set in the simulation model. The third time period can be understood as the third time point or time period set in the simulation model. The first time period is before the second time period, the end time of the second time period is the current time or between the current times, the third time period ends at the current time, the length of the third time period is the same as the length of the first time period, and the fourth time period is after the third time period.

[0113] It should be noted that by processing and analyzing data in different time periods, more accurate pollution simulation results can be obtained.

[0114] Optionally, based on the pollution simulation results, the steps of determining the pollution detection results of the color registration line under different working conditions include:

[0115] For the current working condition, obtain the confidence level of the pollution simulation result, which is output by the target simulation model, and the above pollution simulation result corresponds to a confidence level; when the confidence level is less than the first confidence level threshold, then determine the pollution detection result of the color registration line under the current working condition according to the pollution simulation result of the next moment; when the confidence level is greater than or equal to the first confidence level threshold and less than the second confidence level threshold, then compensate and process the pollution simulation result according to the compensation coefficient corresponding to the current working condition, and determine the compensated pollution simulation result as the pollution detection result of the color registration line under the current working condition, and the second confidence level threshold is greater than the first confidence level threshold; when the confidence level is greater than or equal to the second confidence level threshold, then determine the pollution simulation result as the pollution detection result of the color registration line under the current working condition.

[0116] In the embodiment of the present invention, the above confidence level can be understood as the degree of trust in the output result of the simulation model. A high confidence level means that one believes more that this result is accurate; if the confidence level is low, then there is some doubt about the accuracy of this result.

[0117] The above first confidence level threshold and second confidence level threshold are confidence level thresholds preset by the system, and the second confidence level threshold is greater than the first confidence level threshold.

[0118] The above compensation coefficient is determined according to the specific working condition and the simulation model, and is used to compensate and process the pollution simulation result. The above compensation process can be understood as a process of compensating and calculating according to the confidence level of the simulation result and the compensation coefficient when determining the pollution detection result of the color registration line under the current working condition.

[0119] It should be noted that when the confidence level is less than the first confidence level threshold, it is necessary to determine the pollution detection result of the color registration line under the current working condition according to the pollution simulation result of the next moment. When the confidence level is greater than or equal to the first confidence level threshold and less than the second confidence level threshold, it is necessary to compensate and process the pollution simulation result according to the compensation coefficient corresponding to the current working condition to improve the accuracy of the detection result. The compensated pollution simulation result is the pollution detection result of the color registration line under the current working condition. When the confidence level is greater than or equal to the second confidence level threshold, the pollution simulation result can be directly used as the pollution detection result of the color registration line under the current working condition.

[0120] As Figure 2 shown, the embodiment of the present invention provides a color registration line pollution detection device, and the color registration line pollution detection device includes:

[0121] A building module 201 for constructing an initial simulation model of the overprinting line based on the device structure and parameters of the overprinting line;

[0122] An adjustment module 202 for, under different working conditions, performing a first adjustment on the initial simulation model through the historical operation data of the overprinting line, and performing a second adjustment on the initial simulation model through the historical pollution generation data of the overprinting line to obtain a target simulation model for different working conditions, with each working condition corresponding to a target simulation model;

[0123] A simulation module 203 for performing simulation on the overprinting line through the corresponding target simulation model to obtain pollution simulation results under different working conditions;

[0124] A determination module 204 for determining the pollution detection results of the overprinting line under different working conditions based on the pollution simulation results.

[0125] Optionally, the adjustment module 202 is further configured to obtain the historical operation data of the overprinting line under each working condition; for each working condition, fitting or predicting the historical operation data in multiple dimensions to obtain multi-dimensional operation parameters, with each working condition corresponding to one set of the multi-dimensional operation parameters; and performing a first adjustment on the initial simulation model based on the multi-dimensional operation parameters.

[0126] Optionally, the adjustment module 202 is further configured to obtain the historical pollution generation data of the overprinting line under each working condition; for each working condition, dividing the historical pollution generation data by time period to obtain a pollution generation data sequence, with each working condition corresponding to one pollution generation data sequence, and each pollution generation data sequence including N pollution generation data segments sorted by time period; considering pollution residue, calculating weights for the pollution generation data sequence to obtain a target pollution generation data sequence; predicting the target pollution generation data sequence through a time series prediction network to obtain predicted pollution source parameters, with each working condition corresponding to one set of the predicted pollution source parameters; and performing a second adjustment on the initial simulation model based on the predicted pollution source parameters.

[0127] Optionally, the adjustment module 202 is further configured to determine the time sequence position of each pollution generation data segment; according to the time sequence position, determine the pollution weight of each pollution generation data segment, and the later the time sequence position, the greater the pollution weight; the pollution weight is calculated according to the following formula:

[0128]

[0129] where W i represents the pollution weight of the pollution generation data segment at the i-th time sequence position, ti represents the time interval from the i-th time sequence position to the starting time, N represents the number of pollution generation data segments, and softmax() represents the normalization function; based on the pollution weights, weighted calculation is performed on each of the pollution generation data segments to obtain a target pollution generation data sequence.

[0130] Optionally, the simulation module 203 is further configured to, under the current working condition, match the target simulation model corresponding to the working condition, and each working condition corresponds to one target simulation model; transmit the operating parameters of the overprint line under the current working condition to the target simulation model in real time, and set a fourth time period; output, through the target simulation model, the pollution simulation result of the overprint line in the fourth time period under the current working condition.

[0131] Optionally, the simulation module 203 is further configured to keep the operating parameters within the first time period unchanged through the historical data processing unit; update, through the reference data processing unit, the reference operating parameters within the second time period according to the operating parameters within the first time period, keep the reference operating parameters similar to or the same as the operating parameters within the second time period, and obtain the model prediction parameters within the second time period, the first time period is before the second time period, and the end time of the second time period is the current time or between the current times; update, through the output data processing unit, the pollution simulation result of the fourth time period according to the operating parameters within the third time period and the model prediction parameters within the second time period, the third time period ends at the current time, the length of the third time period is the same as the length of the first time period, and the fourth time period is after the third time period.

[0132] Optionally, the determination module 204 is further configured to, for the current working condition, obtain the confidence level of the pollution simulation result, the confidence level is output by the target simulation model, and the above pollution simulation result corresponds to a confidence level; when the confidence level is less than the first confidence level threshold, then determine the pollution detection result of the overprint line under the current working condition according to the pollution simulation result of the next moment; when the confidence level is greater than or equal to the first confidence level threshold and less than the second confidence level threshold, then perform compensation processing on the pollution simulation result according to the compensation coefficient corresponding to the current working condition, and determine the compensated pollution simulation result as the pollution detection result of the overprint line under the current working condition, the second confidence level threshold is greater than the first confidence level threshold; when the confidence level is greater than or equal to the second confidence level threshold, then determine the pollution simulation result as the pollution detection result of the overprint line under the current working condition.

[0133] The overprint line pollution detection device provided by the embodiments of the present invention can implement each process implemented by the overprint line pollution detection method in the above method embodiments, and can achieve the same beneficial effects. To avoid repetition, it will not be elaborated here.

[0134] See Figure 3 , Figure 3 which is a schematic structural diagram of an electronic device provided by an embodiment of the present invention. As shown in Figure 3 , it includes: a memory 302, a processor 301, and a computer program of the overprint line pollution detection method stored on the memory 302 and executable on the processor 301, where:

[0135] The processor 301 is configured to call the computer program stored in the memory 302 and execute the following steps:

[0136] Based on the device structure and parameters of the overprint line, construct an initial simulation model of the overprint line;

[0137] Under different working conditions, perform a first adjustment on the initial simulation model through the historical operation data of the overprint line, and perform a second adjustment on the initial simulation model through the historical pollution generation data of the overprint line to obtain a target simulation model for different working conditions, and each working condition corresponds to a target simulation model;

[0138] Perform simulation on the overprint line through the corresponding target simulation model to obtain pollution simulation results under different working conditions;

[0139] Based on the pollution simulation results, determine the pollution detection results of the overprint line under different working conditions.

[0140] Optionally, the step of performing a first adjustment on the initial simulation model through the historical operation data of the overprint line executed by the processor 301 includes:

[0141] Obtain the historical operation data of the overprint line under each working condition;

[0142] For each working condition, fit or predict the historical operation data in multiple dimensions to obtain multi-dimensional operation parameters, and each working condition corresponds to one set of multi-dimensional operation parameters;

[0143] Perform a first adjustment on the initial simulation model based on the multi-dimensional operation parameters.

[0144] Optionally, the step of performing a second adjustment on the initial simulation model through the historical pollution generation data of the overprint line executed by the processor 301 includes:

[0145] Obtain the historical pollution generation data of the overprint line under each working condition;

[0146] For each working condition, divide the historical pollution generation data by time period to obtain a pollution generation data sequence. Each working condition corresponds to one such pollution generation data sequence, and each pollution generation data sequence includes N pollution generation data segments sorted by time period;

[0147] Considering pollution residue, calculate the weights of the pollution generation data sequence to obtain a target pollution generation data sequence;

[0148] Predict the target pollution generation data sequence through a time series prediction network to obtain predicted pollution source parameters. Each working condition corresponds to one such predicted pollution source parameter;

[0149] Based on the predicted pollution source parameters, perform a second adjustment on the initial simulation model.

[0150] Optionally, the step of considering pollution residue and calculating the weights of the pollution generation data sequence executed by the processor 301 includes:

[0151] Determine the time order position of each pollution generation data segment;

[0152] According to the time order position, determine the pollution weights of each pollution generation data segment. The later the time order position, the greater the pollution weight; the pollution weight is calculated according to the following formula:

[0153]

[0154] Where W i represents the pollution weight of the pollution generation data segment at the i-th time order position, t i represents the time interval from the i-th time order position to the starting time, N represents the number of pollution generation data segments, and softmax() represents the normalization function;

[0155] Perform weighted calculation on each pollution generation data segment based on the pollution weights to obtain a target pollution generation data sequence.

[0156] Optionally, the step of performing simulation on the overprinting line through the corresponding target simulation model to obtain pollution simulation results under different working conditions executed by the processor 301 includes:

[0157] Under the current working condition, match the target simulation model corresponding to the working condition. Each working condition corresponds to one such target simulation model;

[0158] Transmit the operating parameters of the overprinting line under the current working condition into the target simulation model in real time and set the fourth time period;

[0159] Output the pollution simulation result of the color separation line in the fourth time period under the current working condition through the target simulation model.

[0160] Optionally, the target inverse model includes a historical data processing unit, a reference data processing unit, and an output data processing unit, and the historical data processing unit, the data processing unit, and the output data processing unit are continuous in time; the step of the processor 301 executing to output the pollution simulation result of the color separation line under the current working condition through the target simulation model data includes:

[0161] Keep the operating parameters unchanged within the first time period through the historical data processing unit;

[0162] Update the reference operating parameters in the second time period according to the operating parameters in the first time period through the reference data processing unit, keep the reference operating parameters similar or the same as the operating parameters in the second time period, and obtain the model prediction parameters in the second time period. The first time period is before the second time period, and the end time of the second time period is the current time or between the current times;

[0163] Update the pollution simulation result of the fourth time period according to the operating parameters in the third time period and the model prediction parameters in the second time period through the output data processing unit. The third time period ends at the current time, the length of the third time period is the same as the length of the first time period, and the fourth time period is after the third time period.

[0164] Optionally, the step of the processor 301 executing to determine the pollution detection result of the color separation line under different working conditions based on the pollution simulation result includes:

[0165] For the current working condition, obtain the confidence level of the pollution simulation result, which is output by the target simulation model, and the above pollution simulation result corresponds to a confidence level;

[0166] When the confidence level is less than the first confidence level threshold, then determine the pollution detection result of the color separation line under the current working condition according to the pollution simulation result at the next moment;

[0167] When the confidence level is greater than or equal to the first confidence level threshold and less than the second confidence level threshold, then perform compensation processing on the pollution simulation result according to the compensation coefficient corresponding to the current working condition, and determine the compensated pollution simulation result as the pollution detection result of the color separation line under the current working condition. The second confidence level threshold is greater than the first confidence level threshold;

[0168] When the confidence level is greater than or equal to the second confidence level threshold, then determine the pollution simulation result as the pollution detection result of the color separation line under the current working condition.

[0169] The electronic device provided by the embodiment of the present invention can implement each process implemented by the color registration line pollution detection method in the above method embodiment, and can achieve the same beneficial effects. To avoid repetition, it will not be elaborated here.

[0170] The embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements each process of the color registration line pollution detection method or the color registration line pollution detection method of the application end provided by the embodiment of the present invention, and can achieve the same technical effects. To avoid repetition, it will not be elaborated here.

[0171] Those of ordinary skill in the art can understand that all or part of the processes in implementing the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above methods. Among them, the computer-readable storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM), etc.

[0172] The above-disclosed are only the preferred embodiments of the present invention. Of course, the scope of the rights of the present invention cannot be limited thereby. Therefore, equivalent changes made according to the claims of the present invention still fall within the scope covered by the present invention.

Claims

1. A color line contamination detection method, characterized in that: include: Based on the equipment structure and parameters of the color-coding line, an initial simulation model of the color-coding line is constructed; Under different working conditions, the historical operating data of the color line under each working condition is obtained; for each working condition, the historical operating data is fitted or predicted in multiple dimensions to obtain multi-dimensional operating parameters, and each working condition corresponds to one multi-dimensional operating parameter; based on the multi-dimensional operating parameters, the initial simulation model is first adjusted; and the historical pollution generation data of the color line under each working condition is obtained; for each working condition, the historical pollution generation data is divided into time periods to obtain a pollution generation data sequence, and each working condition corresponds to one pollution generation data sequence, and each pollution generation data sequence includes N pollution generation data segments sorted by time periods; considering the pollution residue, the pollution generation data sequence is weighted to obtain a target pollution generation data sequence; the target pollution generation data sequence is predicted by a time series prediction network to obtain a predicted pollution source parameter, and each working condition corresponds to one predicted pollution source parameter; based on the predicted pollution source parameters, the initial simulation model is secondly adjusted to obtain target simulation models for different working conditions, and each working condition corresponds to one target simulation model; The color line is simulated by the corresponding target simulation model to obtain the pollution simulation results under different working conditions; Based on the pollution simulation result, the pollution detection result of the color matching line under different working conditions is determined.

2. The method according to claim 1, characterized in that The step of taking into account the pollution residue and performing weight calculation on the pollution generation data sequence to obtain the target pollution generation data sequence comprises: Determine the time sequence of each of the pollution generating data segments; According to the time sequence, the pollution weight of each of the pollution generating data segments is determined. The later the time sequence, the greater the pollution weight. The pollution weight is calculated according to the following formula: Among them, W i represents the pollution weight of the pollution-generating data segment at the i-th time sequence, t i represents the time interval from the i-th time sequence to the start time, N represents the number of pollution-generated data segments, and softmax() represents the normalization function; A weighted calculation is performed on each of the pollution generating data segments based on the pollution weight to obtain a target pollution generating data sequence.

3. The method according to claim 1 or 2, characterized in that The step of simulating the color line by using the corresponding target simulation model to obtain the pollution simulation results under different working conditions includes: Under the current working condition, matching the target simulation model corresponding to the working condition, each working condition corresponds to one target simulation model; The operating parameters of the color line under the current working condition are transmitted to the target simulation model in real time, and a fourth time period is set; The pollution simulation result of the color line in the fourth time period under the current working condition is outputted through the target simulation model.

4. The method according to claim 3, characterized in that The target simulation model includes a historical data processing unit, a reference data processing unit and an output data processing unit, wherein the historical data processing unit, the reference data processing unit and the output data processing unit are continuous in time; The step of outputting the pollution simulation result of the color line under the current working condition through the target simulation model comprises: Maintaining the operating parameters in the first period unchanged by the historical data processing unit; The reference data processing unit updates the reference operating parameters in the second time period according to the operating parameters in the first time period, keeps the reference operating parameters similar to or the same as the operating parameters in the second time period, and obtains the model prediction parameters in the second time period, the first time period is before the second time period, and the end time of the second time period is the current time or between the current time and the reference operating parameters in the second time period; The output data processing unit updates the pollution simulation results of the fourth time period based on the operating parameters in the third time period and the model prediction parameters in the second time period. The third time period ends at the current time, the length of the third time period is the same as the length of the first time period, and the fourth time period is after the third time period.

5. The method according to claim 4, characterized in that The step of determining the pollution detection result of the color matching line under different working conditions based on the pollution simulation result includes: For the current working condition, obtain the confidence of the pollution simulation result, the confidence is output by the target simulation model, and the pollution simulation result corresponds to a confidence; When the confidence level is less than a first confidence level threshold, the pollution detection result of the color set line under the current working condition is determined according to the pollution simulation result at the next moment; When the confidence is greater than or equal to a first confidence threshold and less than a second confidence threshold, the pollution simulation result is compensated according to a compensation coefficient corresponding to the current working condition, and the compensated pollution simulation result is determined as the pollution detection result of the color line under the current working condition, and the second confidence threshold is greater than the first confidence threshold; When the confidence level is greater than or equal to the second confidence level threshold, the pollution simulation result is determined as the pollution detection result of the color wire under the current working condition.

6. A color line contamination detection device, characterized in that: The color line pollution detection device comprises: A construction module, used to construct an initial simulation model of the color set line based on the equipment structure and parameters of the color set line; An adjustment module is used to obtain the historical operation data of the color line under various working conditions under different working conditions; for each working condition, fit or predict the historical operation data in multiple dimensions to obtain multi-dimensional operation parameters, and each working condition corresponds to one multi-dimensional operation parameter; based on the multi-dimensional operation parameters, the initial simulation model is first adjusted; and the historical pollution generation data of the color line under various working conditions is obtained; for each working condition, the historical pollution generation data is divided into time periods to obtain a pollution generation data sequence, and each working condition corresponds to one pollution generation data sequence, and each pollution generation data sequence includes N pollution generation data segments sorted by time periods; considering the pollution residue, the pollution generation data sequence is weighted to obtain a target pollution generation data sequence; the target pollution generation data sequence is predicted by a time series prediction network to obtain a predicted pollution source parameter, and each working condition corresponds to one predicted pollution source parameter; based on the predicted pollution source parameters, the initial simulation model is secondly adjusted to obtain target simulation models for different working conditions, and each working condition corresponds to one target simulation model; A simulation module, used to simulate the color line through the corresponding target simulation model to obtain pollution simulation results under different working conditions; A determination module is used to determine the pollution detection results of the color matching line under different working conditions based on the pollution simulation results.

7. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the color line contamination detection method as claimed in any one of claims 1 to 5 when executing the computer program.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the color line contamination detection method according to any one of claims 1 to 5 are implemented.

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