CIP automatic cleaning system of oily sludge treatment equipment

Abstract

The invention relates to the field of cleaning systems, in particular to a CIP automatic cleaning system of oily sludge treatment equipment. The technical problems that when an existing oil-containing sludge treatment equipment CIP automatic cleaning system cleans the oil-containing sludge treatment equipment, running of a CIP system needs to consume a large amount of water and energy, especially in the high-temperature cleaning stage, although the cleaning effect can be improved by increasing the concentration of a cleaning agent, the cleaning cost can be remarkably increased, and the cleaning effect is poor are solved. Therefore, the cleaning cost and the resource consumption are high; according to the technical scheme, the CIP automatic cleaning system of the oily sludge treatment equipment comprises a data acquisition module, a data analysis module, a strategy making module, an execution adjustment module and a cleaning module; the cleaning process is optimized through the intelligent control system, accurate detection of the equipment surface pollution degree, intelligent making of the cleaning strategy and real-time adjustment and optimization of the cleaning process can be achieved, and therefore energy consumption and water resource consumption are reduced while the cleaning effect is ensured.

Description

Technical Field

[0001] The invention relates to the field of cleaning systems, and in particular to a CIP automatic cleaning system for oily sludge treatment equipment. Background Art

[0002] A CIP automatic cleaning system for oily sludge treatment equipment is a system specially designed for automatic cleaning of oily sludge treatment equipment; CIP (Clean In Place) is a technology that uses cleaning fluid to circulate and clean the inside of closed pipes and equipment without disassembling the equipment; this system is widely used in food, beverage, pharmaceutical and environmental protection industries. For oily sludge treatment equipment, its high efficiency, hygiene and automation are particularly important. When the existing CIP automatic cleaning system for oily sludge treatment equipment cleans the oily sludge treatment equipment, the operation of the CIP system consumes a large amount of water and energy, especially in the high-temperature cleaning stage. Although the increase in the concentration of the cleaning agent may improve the cleaning effect, it will also significantly increase the cleaning cost, resulting in a large consumption of cleaning cost resources. Summary of the invention

[0003] In order to overcome the existing CIP automatic cleaning system of oily sludge treatment equipment, when cleaning the oily sludge treatment equipment, the operation of the CIP system consumes a lot of water and energy, especially in the high-temperature cleaning stage. Although the increase in the concentration of the cleaning agent may improve the cleaning effect, it will also significantly increase the cleaning cost, thereby leading to the problem of high cleaning cost and resource consumption.

[0004] The technical solution of the present invention is: a CIP automatic cleaning system for oily sludge treatment equipment, comprising: A data acquisition module, used to collect pollution data on the surface of the oily sludge treatment equipment using multiple sets of sensor devices, and transmit these data to the data analysis module of the intelligent control module in real time; A data analysis module is used to process and analyze the received data, calculate the quantitative index of the pollution degree, and evaluate the pollution degree of the equipment surface based on the processed data; A strategy formulation module is used to obtain pollution degree information, match and adjust the cleaning strategy according to the pollution degree information, and generate cleaning instructions with the adjusted strategy; The execution adjustment module is used to issue cleaning instructions to the cleaning module, monitor the cleaning process in real time, evaluate the cleaning effect, and repeat the execution and evaluation to meet the cleaning standards; The cleaning module is used to use multiple groups of cleaning devices to execute cleaning instructions to clean the equipment.

[0005] Preferably, the pollution data on the surface of the oily sludge treatment equipment is collected by using multiple groups of sensor devices through the data acquisition module, and the data is transmitted to the data analysis module of the intelligent control module in real time; the received data is processed and analyzed by the data analysis module, the quantitative index of the pollution degree is calculated, and the pollution degree of the equipment surface is evaluated according to the processed data; the pollution degree information is obtained through the strategy formulation module, the cleaning strategy is matched and adjusted according to the pollution degree information, and the adjusted strategy generates a cleaning instruction; the cleaning instruction is issued to the cleaning module through the execution adjustment module, and the cleaning process is monitored in real time, the cleaning effect is evaluated, and the execution and evaluation are repeated to meet the cleaning standard.

[0006] Preferably, the cleaning module includes a cleaning liquid preparation tank, a control valve, a delivery pipeline, a booster pump, a return pump, a metering pump, a temperature controller and an electrical control box; the cleaning liquid preparation tank is used to prepare the required cleaning liquid, including water, acid and alkali cleaning liquid and other chemical additives; the control valve is used to control the flow direction and flow of the cleaning liquid to ensure that the cleaning liquid can be accurately delivered to the part that needs to be cleaned, and the delivery pipeline is used to connect the cleaning liquid preparation tank, the cleaned equipment and the return pump components to form a closed cleaning circulation loop; the booster pump is used to increase the flow rate and pressure of the cleaning liquid to enhance the cleaning effect; the return pump is used to draw the cleaning liquid from the cleaning equipment back to the cleaning liquid preparation tank for regeneration; the metering pump is used to control the amount of cleaning liquid added to achieve a concentration that meets the requirements of the cleaning liquid; the temperature controller is used to monitor and adjust the temperature of the cleaning liquid to achieve the best cleaning effect; the electrical control box is used for integrated control to automatically control and monitor the cleaning process.

[0007] Preferably, the data acquisition module includes a temperature sensor, a pressure sensor and a turbidity sensor, which are used to monitor the equipment's contamination degree, cleaning fluid temperature and flow parameter data in real time, and transmit the collected relevant data to the data analysis module.

[0008] Preferably, the data acquisition module comprises the following steps when working: S101: receiving a start instruction and activating each group of sensors deployed on the device; S102: Perform sensor self-check to ensure that all sensors are in normal working condition and have no faults or damage; S103: Check whether the network connection between the sensor and the intelligent control module is stable to ensure smooth data transmission; S104: After confirmation, a start signal is sent to all sensors to activate the sensor network and start data collection; S105: The sensor network starts to collect pollution data on the surface of the equipment in real time, including key parameters such as turbidity value and temperature value; S106: During the data collection process, the collected data is preliminarily checked to remove abnormal values ​​or noise data; S107: Transmit the verified data to the data analysis module in real time.

[0009] Preferably, the data analysis module includes a data processing unit and a pollution assessment unit. The data processing unit is used to process and analyze the received data and calculate quantitative indicators of the pollution degree, such as the average turbidity value and pollution area distribution data. The pollution assessment unit is used to evaluate the pollution degree of the equipment surface based on the processed data, and determine whether cleaning is required and the priority of cleaning.

[0010] Preferably, the data analysis module comprises the following steps: S201: Preprocess the data, identify and remove outliers in the data by setting thresholds or using statistical methods; use interpolation to fill in missing parts in the data; and use filtering technology to reduce random noise in the data; S202: Integrate the cleaned data according to time series or spatial distribution to form an ordered data set, and standardize the data to ensure that data from different sources or different dimensions can be compared and analyzed on the same scale; S203: extracting key features from the integrated data set, such as average turbidity value, maximum turbidity value, and polluted area; S204: Select a corresponding mathematical model or machine learning algorithm to perform data analysis based on the characteristics of the equipment and the cleaning requirements, such as using a linear regression model to analyze the relationship between the turbidity value and the degree of contamination, and using a classification algorithm to identify the type and severity of the contaminated area; S205: Optimize the parameters of the selected model, use a cross-validation method to evaluate the model performance, and adjust the model parameters according to the evaluation results; S206: Compare and verify the model analysis results with the actual situation. If it is found that the analysis results and the actual situation have deviations outside the error range, it is necessary to re-check the data preprocessing and model building process and make corresponding adjustments; S207: According to the equipment use requirements and industry standards, set reasonable pollution degree judgment standards, including turbidity threshold and specific indicators of pollution area proportion; S208: comparing the key characteristic values ​​extracted from the data with the set pollution degree judgment standard, and judging whether the pollution degree of the equipment surface reaches or exceeds the set standard according to the comparison result; S209: Quantify the pollution level assessment results into specific values ​​or levels; S210: Output the evaluation results in the form of charts and reports.

[0011] Preferably, the strategy formulation module includes a strategy matching unit, a strategy adjustment unit and an instruction generation unit; the strategy matching unit is used to match the most corresponding cleaning strategy in a preset cleaning strategy library using an intelligent control algorithm based on the contamination level information, and the cleaning strategy library contains cleaning time, temperature, cleaning liquid type and concentration parameters corresponding to different contamination levels; the strategy adjustment unit is used to adjust the cleaning strategy using an intelligent control algorithm to achieve the best cleaning effect when the preset cleaning strategy cannot meet the current cleaning requirements or there is a better solution; the instruction generation unit is used to convert the adjusted cleaning strategy into specific cleaning instructions and send them to the execution adjustment module.

[0012] Preferably, the policy formulation module includes the following steps when working: S301: The strategy formulation module obtains the latest equipment surface contamination degree information from the data analysis module, including key data of the distribution of contaminated areas, average turbidity value, and maximum turbidity value; S302: Verify the acquired pollution degree information; if the data is found to be abnormal or missing, the abnormality handling mechanism will be triggered to re-collect the data or replace it with historical data; S303: using an intelligent control algorithm to access a preset cleaning strategy library; the cleaning strategy library contains a data set of multiple cleaning strategies, each strategy corresponding to a set of specific cleaning parameters, such as cleaning time, temperature, cleaning liquid type and concentration; S304: According to the pollution degree information, an intelligent control algorithm is used to match in the cleaning strategy library to find the cleaning strategy that best suits the current pollution condition; S305: Selecting the best cleaning strategy from the matched cleaning strategies as a guide for the current cleaning operation; S306: After the cleaning strategy is selected, the intelligent control algorithm performs further evaluation to determine whether the strategy fully meets the current cleaning requirements; S307: If it is found that the preset cleaning strategy cannot meet the current cleaning requirements or a better solution exists, the intelligent control algorithm will automatically adjust the cleaning strategy; the adjustment involves modifying the cleaning time, adjusting the temperature or concentration of the cleaning solution, or changing the type of cleaning solution; S308: verifying the adjusted cleaning strategy to ensure that it can achieve the expected cleaning effect in actual application; S309: converting the adjusted cleaning strategy into a specific cleaning instruction, wherein the cleaning instruction includes all necessary cleaning parameters such as the type of cleaning liquid, concentration, temperature, spray pressure, and cleaning time; S310: Send the cleaning instruction to the execution adjustment module.

[0013] Preferably, the execution adjustment module receives the cleaning instructions and sends the cleaning instructions to the cleaning module; the execution adjustment module includes a monitoring unit, an evaluation unit and an adjustment unit; the monitoring unit is used to monitor the degree of contamination and other relevant parameters on the surface of the equipment in real time during the cleaning process, and transmit the real-time data to the evaluation module; the evaluation unit evaluates the cleaning effect based on the real-time data, and determines whether the cleaning strategy needs to be adjusted; if the adjustment module finds that the cleaning effect does not meet expectations, it will use an intelligent control algorithm to automatically adjust the cleaning strategy, such as increasing the cleaning time, increasing the temperature or concentration of the cleaning liquid, and generate new cleaning instructions to send to related modules.

[0014] Preferably, when the adjustment module is working, the following steps are included: S401: receiving a cleaning instruction and sending the cleaning instruction to a cleaning module; S402: The cleaning module performs cleaning work according to the instruction; S403: During the cleaning process, the sensor network continuously collects pollution data and related parameters on the surface of the equipment; S404: Process and analyze the real-time data to calculate the quantitative indicators of the current cleaning effect, such as the turbidity reduction value after cleaning and the reduction of the contaminated area; S405: Compare the current cleaning effect with the preset cleaning standard to determine whether the cleaning has achieved the expected effect; S406: When the cleaning effect does not meet expectations, the intelligent control algorithm triggers the cleaning strategy adjustment mechanism; based on the real-time data and the cleaning effect evaluation results, within the preset cleaning strategy adjustment range, new cleaning strategy parameters are selected or calculated, such as increasing the cleaning time, increasing the cleaning liquid temperature or concentration; S407: converting the adjusted cleaning strategy into a new cleaning instruction and sending it to the cleaning module; S408: The cleaning module adjusts the cleaning fluid parameters according to the new instruction and continues to perform the cleaning operation; S409: The sensor continues to monitor the degree of contamination on the surface of the equipment in real time, and continuously evaluates the cleaning effect, and adjusts the cleaning strategy again as needed; this process will be repeated until the cleaning effect reaches the preset standard or the maximum cleaning time limit is reached; S410: When the cleaning effect meets the preset standard or reaches the maximum cleaning time, the system automatically stops the cleaning operation; S411: The system enters standby mode, preparing to enter the next working cycle of contamination level detection, cleaning strategy formulation, cleaning execution and adjustment process.

[0015] Beneficial effects of the present invention: 1. Compared with the existing CIP automatic cleaning system for oily sludge treatment equipment, when cleaning oily sludge treatment equipment, the operation of the CIP system consumes a lot of water and energy, especially in the high-temperature cleaning stage. Although the increase in the concentration of the cleaning agent may improve the cleaning effect, it will also significantly increase the cleaning cost, resulting in a large consumption of cleaning costs and resources. This system optimizes the cleaning process through an intelligent control system, reduces unnecessary energy and water consumption, and can achieve accurate detection of the degree of contamination on the surface of the equipment, intelligent formulation of cleaning strategies, and real-time adjustment and optimization of the cleaning process, thereby ensuring the cleaning effect while reducing energy and water consumption and reducing cleaning costs; 2. The data processing unit processes and analyzes the received data, calculates the quantitative index of the pollution degree, such as the average turbidity value and the distribution data of the pollution area, and uses the pollution assessment unit to assess the pollution degree of the equipment surface according to the processed data, and judges whether cleaning is needed and the priority of cleaning; the strategy matching unit uses the intelligent control algorithm to match the most corresponding cleaning strategy in the preset cleaning strategy library according to the pollution degree information; the strategy adjustment unit uses the intelligent control algorithm to adjust the cleaning strategy when the preset cleaning strategy cannot meet the current cleaning requirements or there is a better solution; the instruction generation unit converts the adjusted cleaning strategy into a specific cleaning instruction and sends it to the execution adjustment module; the execution adjustment module receives the cleaning instruction and sends the cleaning instruction to the cleaning module; the execution adjustment module includes a monitoring unit, an evaluation unit and an adjustment unit; the monitoring unit Used to monitor the degree of contamination and other relevant parameters on the equipment surface in real time during the cleaning process, and transmit the real-time data to the evaluation module; the evaluation unit evaluates the cleaning effect based on the real-time data and determines whether the cleaning strategy needs to be adjusted; if the adjustment module finds that the cleaning effect does not meet expectations, it will automatically adjust the cleaning strategy using an intelligent control algorithm, such as increasing the cleaning time, increasing the temperature or concentration of the cleaning liquid, and generating new cleaning instructions to send to related modules; the sensor continues to monitor the degree of contamination on the equipment surface in real time, and continuously evaluates the cleaning effect, and adjusts the cleaning strategy again as needed; this process will be repeated until the cleaning effect reaches the preset standard or the maximum cleaning time limit is reached; accurate detection of the degree of contamination on the equipment surface, intelligent formulation of cleaning strategies, and real-time adjustment and optimization of the cleaning process are achieved, thereby ensuring the cleaning effect while reducing energy and water consumption and reducing cleaning costs; 3. Receive the start command through the data acquisition module and activate the groups of sensors deployed on the equipment; ensure that all sensors are in normal working condition and without faults or damage through sensor self-test; check whether the network connection between the sensor and the intelligent control module is stable to ensure smooth data transmission; after confirmation, send a start signal to all sensors to activate the sensor network and start data collection; the sensor network begins to collect pollution data on the surface of the equipment in real time, including key parameters such as turbidity value and temperature value; during the data collection process, perform preliminary verification on the collected data to eliminate abnormal values ​​or noise data, thereby maintaining the real-time and accuracy of data collection and transmission. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 Shown is a schematic diagram of the working process of the CIP automatic cleaning system of the oily sludge treatment equipment of the present invention; Figure 2 Shown is a schematic diagram of the workflow of the adjustment module of the CIP automatic cleaning system for oily sludge treatment equipment of the present invention. DETAILED DESCRIPTION

[0017] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0018] Figure 1 to Figure 2 The present invention provides an embodiment: a CIP automatic cleaning system for oily sludge treatment equipment, comprising: A data acquisition module, used to collect pollution data on the surface of the oily sludge treatment equipment using multiple sets of sensor devices, and transmit these data to the data analysis module of the intelligent control module in real time; A data analysis module is used to process and analyze the received data, calculate the quantitative index of the pollution degree, and evaluate the pollution degree of the equipment surface based on the processed data; A strategy formulation module is used to obtain pollution degree information, match and adjust the cleaning strategy according to the pollution degree information, and generate cleaning instructions with the adjusted strategy; The execution adjustment module is used to issue cleaning instructions to the cleaning module, monitor the cleaning process in real time, evaluate the cleaning effect, and repeat the execution and evaluation to meet the cleaning standards; The cleaning module is used to use multiple groups of cleaning devices to execute cleaning instructions to clean the equipment.

[0019] Preferably, the pollution data on the surface of the oily sludge treatment equipment is collected by using multiple groups of sensor devices through the data acquisition module, and the data is transmitted to the data analysis module of the intelligent control module in real time; the received data is processed and analyzed by the data analysis module, the quantitative index of the pollution degree is calculated, and the pollution degree of the equipment surface is evaluated according to the processed data; the pollution degree information is obtained through the strategy formulation module, the cleaning strategy is matched and adjusted according to the pollution degree information, and the adjusted strategy generates a cleaning instruction; the cleaning instruction is issued to the cleaning module through the execution adjustment module, and the cleaning process is monitored in real time, the cleaning effect is evaluated, and the execution and evaluation are repeated to meet the cleaning standard.

[0020] Preferably, the cleaning module includes a cleaning liquid preparation tank, a control valve, a delivery pipeline, a booster pump, a return pump, a metering pump, a temperature controller and an electrical control box; the cleaning liquid preparation tank is used to prepare the required cleaning liquid, including water, acid and alkali cleaning liquid and other chemical additives; the control valve is used to control the flow direction and flow of the cleaning liquid to ensure that the cleaning liquid can be accurately delivered to the part that needs to be cleaned, and the delivery pipeline is used to connect the cleaning liquid preparation tank, the cleaned equipment and the return pump components to form a closed cleaning circulation loop; the booster pump is used to increase the flow rate and pressure of the cleaning liquid to enhance the cleaning effect; the return pump is used to draw the cleaning liquid from the cleaning equipment back to the cleaning liquid preparation tank for regeneration; the metering pump is used to control the amount of cleaning liquid added to achieve a concentration that meets the requirements of the cleaning liquid; the temperature controller is used to monitor and adjust the temperature of the cleaning liquid to achieve the best cleaning effect; the electrical control box is used for integrated control to automatically control and monitor the cleaning process.

[0021] Preferably, the data acquisition module includes a temperature sensor, a pressure sensor and a turbidity sensor, which are used to monitor the equipment's contamination degree, cleaning fluid temperature and flow parameter data in real time, and transmit the collected relevant data to the data analysis module.

[0022] Preferably, the data acquisition module comprises the following steps when working: S101: receiving a start instruction and activating each group of sensors deployed on the device; S102: Perform sensor self-check to ensure that all sensors are in normal working condition and have no faults or damage; S103: Check whether the network connection between the sensor and the intelligent control module is stable to ensure smooth data transmission; S104: After confirmation, a start signal is sent to all sensors to activate the sensor network and start data collection; S105: The sensor network starts to collect pollution data on the surface of the equipment in real time, including key parameters such as turbidity value and temperature value; S106: During the data collection process, the collected data is preliminarily checked to remove abnormal values ​​or noise data; S107: Transmit the verified data to the data analysis module in real time.

[0023] Preferably, the data analysis module includes a data processing unit and a pollution assessment unit. The data processing unit is used to process and analyze the received data and calculate quantitative indicators of the pollution degree, such as the average turbidity value and pollution area distribution data. The pollution assessment unit is used to evaluate the pollution degree of the equipment surface based on the processed data, and determine whether cleaning is required and the priority of cleaning.

[0024] Preferably, the data analysis module comprises the following steps: S201: Preprocess the data, identify and remove outliers in the data by setting thresholds or using statistical methods; use interpolation to fill in missing parts in the data; and use filtering technology to reduce random noise in the data; S202: Integrate the cleaned data according to time series or spatial distribution to form an ordered data set, and standardize the data to ensure that data from different sources or different dimensions can be compared and analyzed on the same scale; S203: extracting key features from the integrated data set, such as average turbidity value, maximum turbidity value, and polluted area; S204: Select a corresponding mathematical model or machine learning algorithm to perform data analysis based on the characteristics of the equipment and the cleaning requirements, such as using a linear regression model to analyze the relationship between the turbidity value and the degree of contamination, and using a classification algorithm to identify the type and severity of the contaminated area; S205: Optimize the parameters of the selected model, use a cross-validation method to evaluate the model performance, and adjust the model parameters according to the evaluation results; S206: Compare and verify the model analysis results with the actual situation. If it is found that the analysis results and the actual situation have deviations outside the error range, it is necessary to re-check the data preprocessing and model building process and make corresponding adjustments; S207: According to the equipment use requirements and industry standards, set reasonable pollution degree judgment standards, including turbidity threshold and specific indicators of pollution area proportion; S208: comparing the key characteristic values ​​extracted from the data with the set pollution degree judgment standard, and judging whether the pollution degree of the equipment surface reaches or exceeds the set standard according to the comparison result; S209: Quantify the pollution degree assessment results into specific values ​​or levels; S210: Output the evaluation results in the form of charts and reports.

[0025] Preferably, the strategy formulation module includes a strategy matching unit, a strategy adjustment unit and an instruction generation unit; the strategy matching unit is used to match the most corresponding cleaning strategy in a preset cleaning strategy library using an intelligent control algorithm based on the contamination level information, and the cleaning strategy library contains cleaning time, temperature, cleaning liquid type and concentration parameters corresponding to different contamination levels; the strategy adjustment unit is used to adjust the cleaning strategy using an intelligent control algorithm to achieve the best cleaning effect when the preset cleaning strategy cannot meet the current cleaning requirements or there is a better solution; the instruction generation unit is used to convert the adjusted cleaning strategy into specific cleaning instructions and send them to the execution adjustment module.

[0026] Preferably, the policy formulation module includes the following steps when working: S301: The strategy formulation module obtains the latest equipment surface contamination degree information from the data analysis module, including key data of the distribution of contaminated areas, average turbidity value, and maximum turbidity value; S302: Verify the acquired pollution degree information; if the data is found to be abnormal or missing, the abnormality handling mechanism will be triggered to re-collect the data or replace it with historical data; S303: using an intelligent control algorithm to access a preset cleaning strategy library; the cleaning strategy library contains a data set of multiple cleaning strategies, each strategy corresponding to a set of specific cleaning parameters, such as cleaning time, temperature, cleaning liquid type and concentration; S304: According to the pollution degree information, an intelligent control algorithm is used to match in the cleaning strategy library to find the cleaning strategy that best suits the current pollution condition; S305: Selecting the best cleaning strategy from the matched cleaning strategies as a guide for the current cleaning operation; S306: After the cleaning strategy is selected, the intelligent control algorithm performs further evaluation to determine whether the strategy fully meets the current cleaning requirements; S307: If it is found that the preset cleaning strategy cannot meet the current cleaning requirements or a better solution exists, the intelligent control algorithm will automatically adjust the cleaning strategy; the adjustment involves modifying the cleaning time, adjusting the temperature or concentration of the cleaning solution, or changing the type of cleaning solution; S308: verifying the adjusted cleaning strategy to ensure that it can achieve the expected cleaning effect in actual application; S309: converting the adjusted cleaning strategy into a specific cleaning instruction, wherein the cleaning instruction includes all necessary cleaning parameters such as the type of cleaning liquid, concentration, temperature, spray pressure, and cleaning time; S310: Send the cleaning instruction to the execution adjustment module.

[0027] Preferably, the execution adjustment module receives the cleaning instructions and sends the cleaning instructions to the cleaning module; the execution adjustment module includes a monitoring unit, an evaluation unit and an adjustment unit; the monitoring unit is used to monitor the degree of contamination and other relevant parameters on the surface of the equipment in real time during the cleaning process, and transmit the real-time data to the evaluation module; the evaluation unit evaluates the cleaning effect based on the real-time data, and determines whether the cleaning strategy needs to be adjusted; if the adjustment module finds that the cleaning effect does not meet expectations, it will use an intelligent control algorithm to automatically adjust the cleaning strategy, such as increasing the cleaning time, increasing the temperature or concentration of the cleaning liquid, and generate new cleaning instructions to send to related modules.

[0028] Preferably, when the adjustment module is working, the following steps are included: S401: receiving a cleaning instruction and sending the cleaning instruction to a cleaning module; S402: The cleaning module performs cleaning work according to the instruction; S403: During the cleaning process, the sensor network continuously collects pollution data and related parameters on the surface of the equipment; S404: Process and analyze the real-time data to calculate the quantitative indicators of the current cleaning effect, such as the turbidity reduction value after cleaning and the reduction of the contaminated area; S405: Compare the current cleaning effect with the preset cleaning standard to determine whether the cleaning has achieved the expected effect; S406: When the cleaning effect does not meet expectations, the intelligent control algorithm triggers the cleaning strategy adjustment mechanism; based on the real-time data and the cleaning effect evaluation results, within the preset cleaning strategy adjustment range, new cleaning strategy parameters are selected or calculated, such as increasing the cleaning time, increasing the cleaning liquid temperature or concentration; S407: converting the adjusted cleaning strategy into a new cleaning instruction and sending it to the cleaning module; S408: The cleaning module adjusts the cleaning fluid parameters according to the new instruction and continues to perform the cleaning operation; S409: The sensor continues to monitor the degree of contamination on the surface of the equipment in real time, and continuously evaluates the cleaning effect, and adjusts the cleaning strategy again as needed; this process will be repeated until the cleaning effect reaches the preset standard or the maximum cleaning time limit is reached; S410: When the cleaning effect meets the preset standard or reaches the maximum cleaning time, the system automatically stops the cleaning operation; S411: The system enters standby mode, preparing to enter the next working cycle of contamination level detection, cleaning strategy formulation, cleaning execution and adjustment process.

[0029] The embodiments of the present invention are described in detail above with reference to the accompanying drawings, but the present invention is not limited to the above embodiments, and various changes can be made within the knowledge scope of those skilled in the art without departing from the spirit of the present invention.

Claims

1. A CIP automatic cleaning system for oily sludge treatment equipment, characterized by: Included are: A data acquisition module, used to collect pollution data on the surface of the oily sludge treatment equipment using multiple sets of sensor devices, and transmit these data to the data analysis module of the intelligent control module in real time; A data analysis module is used to process and analyze the received data, calculate the quantitative index of the pollution degree, and evaluate the pollution degree of the equipment surface based on the processed data; A strategy formulation module is used to obtain pollution degree information, match and adjust the cleaning strategy according to the pollution degree information, and generate cleaning instructions with the adjusted strategy; The execution adjustment module is used to issue cleaning instructions to the cleaning module, monitor the cleaning process in real time, evaluate the cleaning effect, and repeat the execution and evaluation to meet the cleaning standards; The cleaning module is used to use multiple groups of cleaning devices to execute cleaning instructions to clean the equipment.

2. The CIP automatic cleaning system for oily sludge treatment equipment according to claim 1 is characterized by: The cleaning module includes a cleaning liquid preparation tank, a control valve, a delivery pipeline, a booster pump, a return pump, a metering pump, a temperature controller and an electrical control box; the cleaning liquid preparation tank is used to prepare the required cleaning liquid, including water, acid and alkali cleaning liquid; the control valve is used to control the flow direction and flow of the cleaning liquid, and the delivery pipeline is used to connect the cleaning liquid preparation tank, the cleaned equipment and the return pump components to form a closed cleaning circulation loop; the booster pump is used to increase the flow rate and pressure of the cleaning liquid; the return pump is used to draw the cleaning liquid from the cleaning equipment back to the cleaning liquid preparation tank for regeneration; the metering pump is used to control the amount of cleaning liquid added; the temperature controller is used to monitor and adjust the temperature of the cleaning liquid; the electrical control box is used for integrated control to automatically control and monitor the cleaning process.

3. The CIP automatic cleaning system for oily sludge treatment equipment according to claim 2 is characterized by: The data acquisition module includes a temperature sensor, a pressure sensor and a turbidity sensor. The temperature sensor, the pressure sensor and the turbidity sensor are used to monitor the equipment's contamination degree, cleaning fluid temperature and flow parameter data in real time, and transmit the collected relevant data to the data analysis module.

4. The CIP automatic cleaning system for oily sludge treatment equipment according to claim 3 is characterized by: When the data acquisition module is working, it includes the following steps: S101: receiving a start instruction and activating each group of sensors deployed on the device; S102: Perform sensor self-check to ensure that all sensors are in normal working condition and have no faults or damage; S103: Check whether the network connection between the sensor and the intelligent control module is stable to ensure smooth data transmission; S104: After confirmation, a start signal is sent to all sensors to activate the sensor network and start data collection; S105: The sensor network starts to collect pollution data on the surface of the equipment in real time, including key parameters such as turbidity value and temperature value; S106: During the data collection process, the collected data is preliminarily checked to remove abnormal values ​​or noise data; S107: Transmit the verified data to the data analysis module in real time.

5. The CIP automatic cleaning system for oily sludge treatment equipment according to claim 4 is characterized by: The data analysis module includes a data processing unit and a pollution assessment unit. The data processing unit is used to process and analyze the received data and calculate quantitative indicators of the pollution degree, such as the average turbidity value and pollution area distribution data. The pollution assessment unit is used to evaluate the pollution degree of the equipment surface based on the processed data and determine whether cleaning is required and the priority of cleaning.

6. The CIP automatic cleaning system for oily sludge treatment equipment according to claim 5 is characterized by: The data analysis module includes the following steps: S201: Preprocess the data, identify and remove outliers in the data by setting thresholds or using statistical methods; use interpolation to fill in missing parts in the data; and use filtering technology to reduce random noise in the data; S202: Integrate the cleaned data according to time series or spatial distribution to form an ordered data set, and standardize the data to ensure that data from different sources or different dimensions can be compared and analyzed on the same scale; S203: extracting key features from the integrated data set, such as average turbidity value, maximum turbidity value, and polluted area; S204: Select a corresponding mathematical model or machine learning algorithm to perform data analysis based on the characteristics of the equipment and the cleaning requirements, such as using a linear regression model to analyze the relationship between the turbidity value and the degree of contamination, and using a classification algorithm to identify the type and severity of the contaminated area; S205: Optimize the parameters of the selected model, use a cross-validation method to evaluate the model performance, and adjust the model parameters according to the evaluation results; S206: Compare and verify the model analysis results with the actual situation. If it is found that the analysis results and the actual situation have deviations outside the error range, it is necessary to re-check the data preprocessing and model building process and make corresponding adjustments; S207: According to the equipment use requirements and industry standards, set reasonable pollution degree judgment standards, including turbidity threshold and specific indicators of pollution area proportion; S208: comparing the key characteristic values ​​extracted from the data with the set pollution degree judgment standard, and judging whether the pollution degree of the equipment surface reaches or exceeds the set standard according to the comparison result; S209: Quantify the pollution degree assessment results into specific values ​​or levels; S210: Output the evaluation results in the form of charts and reports.

7. The CIP automatic cleaning system for oily sludge treatment equipment according to claim 6 is characterized by: The strategy formulation module includes a strategy matching unit, a strategy adjustment unit and an instruction generation unit; the strategy matching unit is used to match the most corresponding cleaning strategy in the preset cleaning strategy library according to the pollution degree information, using an intelligent control algorithm. The cleaning strategy library contains cleaning time, temperature, cleaning liquid type and concentration parameters corresponding to different pollution degrees; the strategy adjustment unit is used to adjust the cleaning strategy using an intelligent control algorithm to achieve the best cleaning effect when the preset cleaning strategy cannot meet the current cleaning requirements or there is a better solution; the instruction generation unit is used to convert the adjusted cleaning strategy into specific cleaning instructions and send them to the execution adjustment module.

8. The CIP automatic cleaning system for oily sludge treatment equipment according to claim 7 is characterized by: The strategy formulation module works by following these steps: S301: The strategy formulation module obtains the latest equipment surface contamination degree information from the data analysis module, including key data of the distribution of contaminated areas, average turbidity value, and maximum turbidity value; S302: Verify the acquired pollution degree information; if the data is found to be abnormal or missing, the abnormality handling mechanism will be triggered to re-collect the data or replace it with historical data; S303: using an intelligent control algorithm to access a preset cleaning strategy library; the cleaning strategy library contains a data set of multiple cleaning strategies, each strategy corresponding to a set of specific cleaning parameters, such as cleaning time, temperature, cleaning liquid type and concentration; S304: According to the pollution degree information, an intelligent control algorithm is used to match in the cleaning strategy library to find the cleaning strategy that best suits the current pollution condition; S305: Selecting the best cleaning strategy from the matched cleaning strategies as a guide for the current cleaning operation; S306: After the cleaning strategy is selected, the intelligent control algorithm performs further evaluation to determine whether the strategy fully meets the current cleaning requirements; S307: If it is found that the preset cleaning strategy cannot meet the current cleaning requirements or a better solution exists, the intelligent control algorithm will automatically adjust the cleaning strategy; the adjustment involves modifying the cleaning time, adjusting the temperature or concentration of the cleaning solution, or changing the type of cleaning solution; S308: verifying the adjusted cleaning strategy to ensure that it can achieve the expected cleaning effect in actual application; S309: converting the adjusted cleaning strategy into a specific cleaning instruction, wherein the cleaning instruction includes all necessary cleaning parameters such as the type of cleaning liquid, concentration, temperature, spray pressure, and cleaning time; S310: Send the cleaning instruction to the execution adjustment module.

9. The CIP automatic cleaning system for oily sludge treatment equipment according to claim 8, characterized in that: The execution and adjustment module receives the cleaning instructions and sends the cleaning instructions to the cleaning module; the execution and adjustment module includes a monitoring unit, an evaluation unit and an adjustment unit; the monitoring unit is used to monitor the degree of contamination and other relevant parameters on the surface of the equipment in real time during the cleaning process, and transmit the real-time data to the evaluation module; the evaluation unit evaluates the cleaning effect based on the real-time data and determines whether the cleaning strategy needs to be adjusted; if the adjustment module finds that the cleaning effect does not meet expectations, it will use an intelligent control algorithm to automatically adjust the cleaning strategy, such as increasing the cleaning time, increasing the temperature or concentration of the cleaning liquid, and generate new cleaning instructions to send to related modules.

10. The CIP automatic cleaning system for oily sludge treatment equipment according to claim 9, characterized in that: When the adjustment module is working, the following steps are included: S401: receiving a cleaning instruction and sending the cleaning instruction to a cleaning module; S402: The cleaning module performs cleaning work according to the instruction; S403: During the cleaning process, the sensor network continuously collects pollution data and related parameters on the surface of the equipment; S404: Process and analyze the real-time data to calculate the quantitative indicators of the current cleaning effect, such as the turbidity reduction value after cleaning and the reduction of the contaminated area; S405: Compare the current cleaning effect with the preset cleaning standard to determine whether the cleaning has achieved the expected effect; S406: When the cleaning effect does not meet expectations, the intelligent control algorithm triggers the cleaning strategy adjustment mechanism; based on the real-time data and the cleaning effect evaluation results, within the preset cleaning strategy adjustment range, new cleaning strategy parameters are selected or calculated, such as increasing the cleaning time, increasing the cleaning liquid temperature or concentration; S407: converting the adjusted cleaning strategy into a new cleaning instruction and sending it to the cleaning module; S408: The cleaning module adjusts the cleaning fluid parameters according to the new instruction and continues to perform the cleaning operation; S409: The sensor continues to monitor the degree of contamination on the surface of the equipment in real time, and continuously evaluates the cleaning effect, and adjusts the cleaning strategy again as needed; this process will be repeated until the cleaning effect reaches the preset standard or the maximum cleaning time limit is reached; S410: When the cleaning effect meets the preset standard or reaches the maximum cleaning time, the system automatically stops the cleaning operation; S411: The system enters standby mode, preparing to enter the next working cycle of contamination level detection, cleaning strategy formulation, cleaning execution and adjustment process.

Images