Workpiece cleaning method and cleaning system

Abstract

A workpiece cleaning method and cleaning system, the workpiece cleaning method comprises the following steps: placing a workpiece to be cleaned on a conveyor belt, the conveyor belt sending the workpiece to a workpiece identification module; the workpiece identification module identifying the workpiece; on the basis of a received identification result, a control module querying or calculating, in a database, cleaning parameters suitable for the workpiece, and sending a setting result to a cleaning parameter setting module; on the basis of the received setting result, the cleaning parameter setting module controlling a cleaning liquid circulation module; a spray head cleaning the workpiece, and recycling the cleaning liquid during the cleaning process; a cleanliness detection module detecting the degree of contamination on a surface of the workpiece, and sending a detection result to the control module; and, on the basis of the received detection result, the control module determining whether to continue cleaning.

Description

Workpiece cleaning method and cleaning system Technical Field

[0001] The present invention relates to a workpiece cleaning method and a cleaning system, in particular to a workpiece cleaning method and a cleaning system capable of automatically adjusting cleaning parameters and cleaning liquid treatment methods according to workpieces of different types, sizes, shapes, and surface cleanliness. Background Art

[0002] Workpiece cleaning is a crucial step in industrial production, removing impurities such as oil, dust, and rust from workpiece surfaces, thereby improving their quality and performance. Currently, two common workpiece cleaning methods are spray cleaning and immersion cleaning. Spray cleaning uses a spray head to spray a cleaning fluid onto the workpiece surface at a specific pressure and temperature, achieving the cleaning effect. Immersion cleaning involves immersing the workpiece in a cleaning fluid containing a detergent, where the chemical and mechanical effects of the cleaning fluid dissolve or remove contaminants from the workpiece surface. Traditional workpiece cleaning methods suffer from the following problems: They cannot automatically adjust cleaning parameters (such as temperature, pressure, and time) to accommodate workpiece types, sizes, shapes, and surface cleanliness, resulting in poor cleaning results and wasted resources. They cannot automatically adjust the cleaning fluid treatment method to accommodate workpiece types, sizes, shapes, and surface cleanliness, resulting in unstable cleaning fluid performance or incompatibility. Furthermore, they cannot detect and provide feedback on the degree of contamination on the workpiece surface, resulting in over- or under-cleaning. Therefore, there is a need to provide a workpiece cleaning method and system that can automatically adjust cleaning parameters and cleaning fluid treatment methods to accommodate workpiece types, sizes, shapes, and surface cleanliness, in order to address these issues.

[0003] Summary of the Invention

[0004] Technical problem solved: This method solves the problem that traditional workpiece cleaning methods cannot automatically adjust cleaning parameters according to workpieces of different types, sizes, shapes, and surface cleanliness, resulting in poor cleaning effects or waste of resources.

[0005] A workpiece cleaning method comprises the following steps:

[0006] Step 1: Place the workpiece to be cleaned on the conveyor belt, which will transport the workpiece to the workpiece identification module;

[0007] Step 2: The workpiece recognition module scans the workpiece, identifies the type, size, shape, and surface cleanliness characteristics of the workpiece, and sends the recognition results to the control module;

[0008] Step 3: The control module starts the parameter calculation module based on the received recognition result, queries or calculates the temperature, pressure, and time cleaning parameters suitable for the workpiece from the database; and sends the setting results to the cleaning parameter setting module;

[0009] Step 4: The cleaning parameter setting module issues an instruction to the cleaning liquid calling module based on the received setting result. The cleaning liquid calling module extracts cleaning liquid from the cleaning liquid storage tank and delivers the processed cleaning liquid to the spray head.

[0010] Step 5: The spray head cleans the workpiece, and the cleaning waste liquid enters the collection tank;

[0011] Step 6: The cleaning liquid collection module starts to filter and heat the cleaning liquid in the collection tank, and then transfers the treated cleaning liquid to the cleaning liquid storage tank. The cleaning liquid is recycled during the cleaning process.

[0012] Step 7: The cleanliness detection module detects the contamination level of the workpiece surface and sends the detection results to the control module;

[0013] Step 8: The control module determines whether to continue cleaning based on the received detection results. If yes, steps 1 to 7 are repeated. If no, the cleaning process ends.

[0014] Step 9: Remove the workpieces that meet the requirements after cleaning from the conveyor belt for subsequent processing or use.

[0015] In a preferred embodiment, in step 7, it is determined that the workpiece needs to be returned for cleaning, and the cleaning counting module starts working; when the cleaning counting module meets the following conditions J>J max , where J represents the number of counts, J max Indicates the maximum number of cleaning times allowed; the workpiece enters the manual intervention cleaning channel.

[0016] In a preferred embodiment, the workpiece identification module includes an image acquisition device, an image processing module, and a communication module; the image acquisition device is used to photograph the workpiece and obtain image data of the workpiece; the image processing module is used to preprocess, extract features, and classify the image data to obtain feature data of the workpiece type, size, shape, and surface cleanliness; and the communication module is used to send the feature data to the control module.

[0017] The image processing module adopts a convolutional neural network (CNN) for preprocessing, feature extraction, and classification of image data; and adopts a support vector machine (SVM) for optimizing and verifying the output of the convolutional neural network (CNN).

[0018] In a preferred embodiment, the image processing module uses a convolutional neural network (CNN) algorithm to preprocess, extract features, and classify image data:

[0019] The following image processing formula is used to obtain a mathematical model that can characterize the type, size, shape, and surface cleanliness of the workpiece: f(x) = max(0, x)

[0020] Where f(x) represents the activation function; x represents the input signal; y = W*x+b

[0021] Among them, y represents the output signal; w represents the weight matrix; x represents the input signal; and b represents the bias vector.

[0022] Among them, L represents the loss function; N represents the number of samples; K represents the number of categories; t nk Indicates the true value that the nth sample belongs to the kth category; y nk Indicates the predicted value that the nth sample belongs to the kth category.

[0023] In a preferred embodiment, the support vector machine (SVM) is used to optimize and verify the output of the convolutional neural network (CNN). The support vector machine (SVM) is expressed using the following formula:

[0024] Where w represents the weight vector; b represents the bias scalar; C represents the penalty parameter; ξ i Represents the slack variable. y=w T x+b

[0025] Where y represents the output signal; w represents the weight vector; x represents the input signal; and b represents the bias scalar. T x+b)

[0026] Wherein, sign(x) represents a sign function, which returns 1 when x>0, returns -1 when x<0, and returns 0 when x=0.

[0027] In a preferred embodiment, the parameter calculation module is used to query or calculate the cleaning parameters suitable for the workpiece in the database based on the output of the workpiece identification module, and is used to calculate the temperature, pressure, and time algorithm suitable for the workpiece based on the type, size, shape, and surface cleanliness of the workpiece; the algorithm is expressed by the following formula:

[0028] Among them, y represents the output variable; f(x1,x2,…,x n ) represents the fuzzy inference function; x1,x2,…,x n represents the input variable; m represents the number of rules; w i represents the weight of the i-th rule; y i Represents the output of the i-th rule.

[0029] In a preferred embodiment, the cleaning parameter setting module includes a database module and a communication module; the database module is used to store the cleaning parameters corresponding to workpieces of different types, sizes, shapes, and surface cleanliness, so that workpieces with the same cleaning parameters do not need to be repeatedly calculated; the database module is used to cache the cleaning parameters of the workpiece being cleaned; the communication module is used to send the cleaning parameters to the control module for controlling the workpiece being cleaned.

[0030] A workpiece cleaning system includes a hardware component, a workpiece identification module, a controller, a parameter calculation module, a cleaning parameter setting module, a cleaning liquid retrieval module, a cleaning liquid collection module, and a cleanliness detection module; the hardware component includes a conveyor belt, a spray head arranged above the conveyor belt, a collection tank arranged below the conveyor belt, a liquid storage tank for preventing the cleaning liquid from being lost, and a manual intervention cleaning channel provided at the end of the conveyor belt for transferring workpieces that have exceeded the maximum number of cleaning times;

[0031] The control module is used to receive input from each module, control the actions of each module, and realize the coordinated operation of the entire system;

[0032] The workpiece recognition module includes an image acquisition device, an image processing module, and a communication module. The image acquisition device and the control module realize two-way communication, and are used to identify the type, size, shape, and surface cleanliness characteristics of the workpiece, and send the recognition results to the control module;

[0033] The parameter calculation module controls the module to realize two-way communication, and queries or calculates the temperature, pressure and time cleaning parameters suitable for the workpiece from the database; and sends the setting results to the cleaning parameter setting module;

[0034] The cleaning parameter setting module realizes two-way communication with the control module, and is used to query or calculate the cleaning parameters suitable for the workpiece from the database according to the output of the workpiece identification module: temperature, pressure, time, and send the setting results to the control module;

[0035] The cleaning liquid circulation module and the control module realize two-way communication, and are used to filter, heat, pressurize the cleaning liquid, and transport the treated cleaning liquid to the liquid storage tank;

[0036] The cleanliness detection module realizes two-way communication with the control module, is used to detect the contamination degree of the workpiece surface after cleaning, and sends the detection result to the control module.

[0037] Beneficial effects of the present invention:

[0038] This system utilizes artificial intelligence technology and advanced mathematical formulas, and uses techniques such as image processing and fuzzy logic to identify workpiece features and set cleaning parameters. It also optimizes the cleaning fluid circulation module through genetic algorithms and enables feedback control of cleaning results through cleanliness testing. This feature utilizes image acquisition and processing technologies, capturing workpiece image data through photography and scanning. It then processes this image data through preprocessing and feature extraction to obtain workpiece feature data. Classification and other techniques analyze this feature data to determine the workpiece's type, size, and shape.

[0039] It can realize fuzzy reasoning of cleaning parameters and dynamically set the most appropriate cleaning parameters according to the actual situation of the workpiece, thereby improving the cleaning effect and resource utilization.

[0040] It can realize the optimized control of the cleaning liquid circulation module, filter, heat, pressurize and other treatments on the cleaning liquid according to different cleaning parameters, so as to achieve the best cleaning effect and extend the service life of the cleaning liquid.

[0041] The system can realize intelligent identification and personalized cleaning of workpieces of different types, sizes and shapes, improving cleaning efficiency and quality and saving cleaning fluid and energy. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] FIG1 is a flow chart of the method of the present invention.

[0043] FIG2 is a schematic diagram of the system of the present invention. DETAILED DESCRIPTION

[0044] As shown in FIG1 , a workpiece cleaning method includes the following steps:

[0045] Step 1: Place the workpiece to be cleaned on the conveyor belt, which will transport the workpiece to the workpiece identification module;

[0046] Step 2: The workpiece recognition module scans the workpiece, identifies the type, size, shape, and surface cleanliness characteristics of the workpiece, and sends the recognition results to the control module;

[0047] Step 3: The control module starts the parameter calculation module based on the received recognition result, queries or calculates the temperature, pressure, and time cleaning parameters suitable for the workpiece from the database; and sends the setting results to the cleaning parameter setting module;

[0048] Step 4: The cleaning parameter setting module issues an instruction to the cleaning liquid calling module based on the received setting result. The cleaning liquid calling module extracts cleaning liquid from the cleaning liquid storage tank and delivers the processed cleaning liquid to the spray head.

[0049] Step 5: The spray head cleans the workpiece, and the cleaning waste liquid enters the collection tank;

[0050] Step 6: The cleaning liquid collection module starts to filter and heat the cleaning liquid in the collection tank, and then transfers the treated cleaning liquid to the cleaning liquid storage tank. The cleaning liquid is recycled during the cleaning process.

[0051] Step 7: The cleanliness detection module detects the contamination level of the workpiece surface and sends the detection results to the control module;

[0052] Step 8: The control module determines whether to continue cleaning based on the received detection results. If yes, steps 1 to 7 are repeated. If no, the cleaning process ends.

[0053] Step 9: Remove the workpieces that meet the requirements after cleaning from the conveyor belt for subsequent processing or use.

[0054] In order to prevent a workpiece from entering a cleaning dead loop, in step 7, it is determined that the workpiece needs to be returned for cleaning, and the cleaning counting module starts working; when the cleaning counting module meets the following conditions J>J max , where J represents the number of counts, J max Indicates the maximum number of cleaning times allowed; the workpiece enters the manual intervention cleaning channel.

[0055] The workpiece recognition module includes an image acquisition device, an image processing module, and a communication module; the image acquisition device is used to photograph the workpiece and obtain image data of the workpiece; the image processing module is used to preprocess, extract features, and classify the image data to obtain feature data such as the type, size, shape, and surface cleanliness of the workpiece; and the communication module is used to send the feature data to the control module.

[0056] The image processing module adopts a convolutional neural network (CNN) for preprocessing, feature extraction, and classification of image data; and adopts a support vector machine (SVM) for optimizing and verifying the output of the convolutional neural network (CNN).

[0057] In a preferred embodiment, the image processing module uses a convolutional neural network (CNN) algorithm to preprocess, extract features, and classify image data:

[0058] The following image processing formula is used to obtain a mathematical model that can characterize the type, size, shape, and surface cleanliness of the workpiece: f(x) = max(0, x)

[0059] Where f(x) represents the activation function; x represents the input signal; y = W*x+b

[0060] Among them, y represents the output signal; w represents the weight matrix; x represents the input signal; and b represents the bias vector.

[0061] Among them, L represents the loss function; N represents the number of samples; K represents the number of categories; t nk Indicates the true value that the nth sample belongs to the kth category; y nk Indicates the predicted value that the nth sample belongs to the kth category.

[0062] The above uses image acquisition and image processing technologies, such as photography and scanning, to acquire workpiece image data. Preprocessing and feature extraction are used to process image data and obtain feature data. Classification and other techniques are used to analyze feature data and determine information such as the workpiece type, size, and shape. Convolutional neural networks and support vector machines are used, using activation functions and weight matrices to extract and classify image data. Loss functions and optimization algorithms are used to optimize and verify the CNN output.

[0063] The support vector machine (SVM) is used to optimize and verify the output of the convolutional neural network (CNN). The support vector machine (SVM) is expressed using the following formula:

[0064] Where w represents the weight vector; b represents the bias scalar; C represents the penalty parameter; ξ i Represents the slack variable. y=w T x+b

[0065] Where y represents the output signal; w represents the weight vector; x represents the input signal; and b represents the bias scalar. T x+b)

[0066] Wherein, sign(x) represents a sign function, which returns 1 when x>0, returns -1 when x<0, and returns 0 when x=0.

[0067] The above technologies use technologies such as weight vectors and bias scalars to achieve linear mapping of CNN outputs; through technologies such as penalty parameters and slack variables, the outputs of CNN are constrained and adjusted; and through technologies such as symbolic functions, the outputs of CNN are classified and judged.

[0068] In a preferred embodiment, the parameter calculation module is used to query or calculate the cleaning parameters suitable for the workpiece in the database based on the output of the workpiece identification module, and is used to calculate the temperature, pressure, and time algorithm suitable for the workpiece based on the type, size, shape, and surface cleanliness of the workpiece; the algorithm is expressed by the following formula:

[0069] Among them, y represents the output variable; f(x1,x2,…,x n ) represents the fuzzy inference function; x1,x2,…,x n represents the input variable; m represents the number of rules; w i represents the weight of the i-th rule; y i Represents the output of the i-th rule.

[0070] The principle of the above formula is that different input variables x1, x2, ..., x n Represents type, size, shape, surface cleanliness, etc., because each workpiece is represented by a different numerical value in each case, and finally a different output variable y is obtained, and the cleaning parameter setting is determined according to the output variable y.

[0071] The cleaning parameter setting module includes a database module and a communication module; the database module is used to store the cleaning parameters corresponding to workpieces of different types, sizes, shapes, and surface cleanliness, so that workpieces with the same cleaning parameters do not need to be repeatedly calculated; the database module is used to cache the cleaning parameters of the workpiece being cleaned; the communication module is used to send the cleaning parameters to the control module for controlling the workpiece being cleaned.

[0072] As shown in Figure 2, a workpiece cleaning system includes a hardware part, a workpiece identification module, a controller, a parameter calculation module, a cleaning parameter setting module, a cleaning liquid retrieval module, a cleaning liquid collection module, and a cleanliness detection module; the hardware part includes a conveyor belt, a spray head arranged above the conveyor belt, a collection tank arranged below the conveyor belt, a liquid storage tank for preventing the cleaning liquid from being lost, and a manual intervention cleaning channel provided at the end of the conveyor belt for transferring workpieces that have exceeded the maximum number of cleaning times;

[0073] The control module is used to receive input from each module, control the actions of each module, and realize the coordinated operation of the entire system;

[0074] The workpiece recognition module includes an image acquisition device, an image processing module, and a communication module. The image acquisition device and the control module realize two-way communication, and are used to identify the type, size, shape, and surface cleanliness characteristics of the workpiece, and send the recognition results to the control module;

[0075] The parameter calculation module controls the module to realize two-way communication, and queries or calculates the temperature, pressure and time cleaning parameters suitable for the workpiece from the database; and sends the setting results to the cleaning parameter setting module;

[0076] The cleaning parameter setting module realizes two-way communication with the control module, and is used to query or calculate the cleaning parameters suitable for the workpiece from the database according to the output of the workpiece identification module: temperature, pressure, time, and send the setting results to the control module;

[0077] The cleaning liquid circulation module and the control module realize two-way communication, and are used to filter, heat, pressurize the cleaning liquid, and transport the treated cleaning liquid to the liquid storage tank;

[0078] The cleanliness detection module realizes two-way communication with the control module, is used to detect the contamination degree of the workpiece surface after cleaning, and sends the detection result to the control module.

[0079] In this embodiment, specific workpiece type, size, shape, contamination level, cleanliness and other data are shown in Table 1:

[0080] In this embodiment, specific cleaning parameters (such as temperature, pressure, time, etc.) are shown in Table 2:

[0081] In this embodiment, the specific cleaning effect is shown in Table 3:

[0082] In this embodiment, the specific cleaning liquid is water.

[0083] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the present invention. Under the spirit and principle of the present invention, any modification, equivalent replacement and improvement of the present invention shall be included in the scope of protection of the present invention.

[0084] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device that includes a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. This article uses specific examples to illustrate the principles and implementation methods of the technical solution of this patent. The above examples are only used to help understand the method of this patent and its core ideas. The above is only a preferred implementation method of this patent. It should be pointed out that due to the limitations of textual expression and the objective existence of infinite specific structures, ordinary technicians in this technical field can make several improvements, modifications or changes without departing from the principles of this patent, and can also combine the above technical features in an appropriate manner; these improvements, modifications, changes or combinations, or the direct application of the patent concept and technical solution to other occasions without improvement, should be regarded as the scope of protection of this patent.

Claims

1. A workpiece cleaning method, characterized in that: The following steps are involved: Step 1: Place the workpiece to be cleaned on the conveyor belt, which will transport the workpiece to the workpiece identification module; Step 2: The workpiece recognition module scans the workpiece, identifies the type, size, shape, and surface cleanliness characteristics of the workpiece, and sends the recognition result to the control module; Step 3: The control module starts the parameter calculation module according to the received recognition result, queries or calculates the cleaning parameters of temperature, pressure and time suitable for the workpiece from the database; and sends the setting result to the cleaning parameter setting module; Step 4: The cleaning parameter setting module issues instructions to the cleaning liquid calling module according to the received setting results. The cleaning liquid calling module extracts cleaning liquid from the cleaning liquid storage tank and delivers the processed cleaning liquid to the spray head. Step 5: The spray head cleans the workpiece, and the cleaning waste liquid enters the collection tank; Step 6: The cleaning liquid collection module starts to start, filters and heats the cleaning liquid in the collection tank, and transports the treated cleaning liquid to the cleaning liquid storage tank. The cleaning liquid is recycled during the cleaning process; Step 7: The cleanliness detection module detects the contamination degree of the workpiece surface and sends the detection result to the control module; Step 8: The control module determines whether to continue cleaning based on the received detection results. If yes, steps 1 to 7 are repeated. If no, the cleaning process ends. Step 9: Remove the workpieces that meet the requirements after cleaning from the conveyor belt for subsequent processing or use.

2. A workpiece cleaning method according to claim 1, characterized in that: In step 7, it is determined that the workpiece needs to be returned for cleaning, and the cleaning counting module starts working; when the cleaning counting module meets the following conditions J>J max , where J represents the number of counts, J max Indicates the maximum number of cleaning times allowed; the workpiece enters the manual intervention cleaning channel.

3. The workpiece cleaning method according to claim 1, characterized in that: The workpiece recognition module includes an image acquisition device, an image processing module, and a communication module; An image acquisition device is used to photograph the workpiece and obtain image data of the workpiece; an image processing module is used to perform preprocessing, feature extraction, and classification operations on the image data to obtain feature data of the type, size, shape, and surface cleanliness of the workpiece; A communication module, used to send characteristic data to the control module; The image processing module adopts a convolutional neural network (CNN) for preprocessing, feature extraction and classification of image data; and adopts a support vector machine (SVM) for optimizing and verifying the output of the convolutional neural network (CNN).

4. The workpiece cleaning system according to claim 3, characterized in that: The image processing module uses a convolutional neural network (CNN) algorithm to preprocess, extract features, and classify image data: The following image processing formula is used to obtain a mathematical model that can be characterized for the type, size, shape, and surface cleanliness of the workpiece. The formula is: f(x)=max(0,x) Where f(x) represents the activation function; x represents the input signal; y=W*x+b Among them, y represents the output signal; w represents the weight matrix; x represents the input signal; b represents the bias vector; Among them, L represents the loss function; N represents the number of samples; K represents the number of categories; t nk Indicates the true value that the nth sample belongs to the kth category; y nk Indicates the predicted value that the nth sample belongs to the kth category.

5. The workpiece cleaning method according to claim 3, characterized in that: The support vector machine (SVM) is used to optimize and verify the output of the convolutional neural network (CNN). The support vector machine (SVM) is expressed by the following formula: Among them, w represents the weight vector; b represents the bias scalar; C represents the penalty parameter; ξ i represents the slack variable; y=w T x+b Among them, y represents the output signal; w represents the weight vector; x represents the input signal; b represents the bias scalar; y=sign(w T x+b) Wherein, sign(x) represents a sign function, which returns 1 when x>0, returns -1 when x<0, and returns 0 when x=0.

6. The workpiece cleaning method according to claim 1, characterized in that: In step 3, the parameter calculation module is used to query or calculate the cleaning parameters suitable for the workpiece in the database according to the output of the workpiece identification module, and is used to calculate the temperature, pressure and time algorithm suitable for the workpiece according to the type, size, shape and surface cleanliness of the workpiece; It is expressed using the following formula: Among them, y represents the output variable; f(x1,x2,…,x n ) represents the fuzzy inference function; x1,x2,…,x n represents the input variable; m represents the number of rules; w i represents the weight of the i-th rule; y i Represents the output of the i-th rule.

7. The workpiece cleaning method according to claim 1, characterized in that: The cleaning parameter setting module includes a database module and a communication module; the database module is used to store the cleaning parameters corresponding to workpieces of different types, sizes, shapes, and surface cleanliness, so that workpieces with the same cleaning parameters do not need to be repeatedly calculated; the database module is used to cache the cleaning parameters being cleaned; The communication module is used to send the cleaning parameters to the control module for controlling the workpiece being cleaned.

8. A workpiece cleaning system, characterized in that: It includes a hardware part, a workpiece identification module, a controller, a parameter calculation module, a cleaning parameter setting module, a cleaning liquid retrieval module, a cleaning liquid collection module, and a cleanliness detection module; the hardware part includes a conveyor belt, a spray head arranged above the conveyor belt, a collection tank arranged below the conveyor belt, a storage tank for preventing the cleaning liquid, and a manual intervention cleaning channel for transferring workpieces that exceed the maximum cleaning times at the end of the conveyor belt; The control module is used to receive inputs from various modules, control the actions of each module, and realize the coordinated operation of the entire system; The workpiece recognition module includes an image acquisition device, an image processing module, and a communication module. The image acquisition device and the control module realize two-way communication, and are used to identify the type, size, shape, and surface cleanliness characteristics of the workpiece, and send the recognition results to the control module; The parameter calculation module control module realizes two-way communication, queries or calculates the temperature, pressure and time cleaning parameters suitable for the workpiece from the database; and sends the setting results to the cleaning parameter setting module; The cleaning parameter setting module realizes two-way communication with the control module, and is used to query or calculate the cleaning parameters suitable for the workpiece from the database according to the output of the workpiece identification module: temperature, pressure, time, and send the setting results to the control module; The cleaning liquid circulation module and the control module realize two-way communication, and are used to filter, heat, pressurize the cleaning liquid, and transport the treated cleaning liquid to the liquid storage tank; The cleanliness detection module realizes two-way communication with the control module, is used to detect the contamination degree of the workpiece surface after cleaning, and sends the detection result to the control module.

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