Intelligent adjustment control method and system for coating air conditioner, electronic equipment and storage medium

Abstract

The invention discloses an intelligent adjustment control method for a painting air conditioner, and relates to the field of automobile painting environment control, and the method comprises the steps that multi-dimensional sensor data and a system operation state are obtained, and multi-dimensional sensors are deployed in all process sections of a painting air conditioner in a painting workshop; preprocessing and analyzing the multi-dimensional sensor data to obtain stable operation data of each process section; the stable operation data comprises temperature data and relative humidity data; obtaining an operation mode according to the stable operation data of each process section in combination with the enthalpy humidity; generating a control logic based on the operation mode; the control logic comprises a local mode and a remote mode; the control logic is switched according to a system operation state; when the control logic is switched to the local mode, compensation and filtering are carried out, and system operation is corrected. Through seasonal mode judgment logic based on the enthalpy value and the moisture content, the corresponding function section is accurately started, invalid equipment operation is avoided, and redundant energy consumption is directly reduced.

Description

TECHNICAL FIELD

[0001] The application relates to the field of automobile painting environment control, in particular to a painting air conditioner intelligent regulation control method, a painting air conditioner intelligent regulation control system, an electronic device and a storage medium. BACKGROUND

[0002] In the whole vehicle manufacturing process of commercial vehicles, the painting process is a key link. It is not only related to the appearance quality of the vehicle, such as the uniformity of the color, the gloss and flatness of the paint surface, etc., which directly affect the purchase willingness of the user. Moreover, the painting layer also provides important protection function for the vehicle, which can effectively prevent the corrosion of the vehicle body metal parts from external environmental factors (such as moisture, salt, ultraviolet rays, acid rain, etc.), thereby prolonging the service life of the vehicle.

[0003] At present, the mainstream painting process of commercial vehicles is 3C2B, which includes three times of painting of primer, topcoat and clear coat, and two times of drying process. The main process of primer spraying is pretreatment and electrophoresis, which ensures the cleanliness of the vehicle body and the uniform adhesion of the primer. After electrophoresis, one-time drying is carried out, and then topcoat and clear coat spraying and drying are carried out. The requirements for temperature and humidity in the whole process are extremely strict. The traditional equipment control is to control the air conditioner, cold and hot water valves and drying furnace equipment by PID algorithm to realize accurate control of temperature and humidity, and to manufacture products meeting the process technical requirements.

[0004] The whole vehicle manufacturing process needs to consume industrial water, electricity, natural gas, compressed air and other energy sources. The painting process is the largest energy consumption link in the whole vehicle manufacturing process, and the energy cost accounts for more than 70%. The paint spraying room is the largest energy consumption equipment in the vehicle painting workshop, accounting for about 50% of the total energy consumption of the painting workshop, and the air conditioning energy consumption accounts for about 40% of the energy consumption of the paint spraying room. The traditional PID algorithm control has time lag, has great delay when the season and climate change, and still needs manual intervention adjustment. When the production environment changes and the production operation plan is adjusted, relying on the traditional PID control will cause great energy consumption redundancy. SUMMARY

[0005] The application aims to provide a painting air conditioner intelligent regulation control method, a painting air conditioner intelligent regulation control system, an electronic device and a storage medium. The technical problem of time lag of the traditional control algorithm and great energy consumption redundancy is solved, the adaptive adjustment of the control parameters is realized according to the real-time external environmental factors, the consumption of water, electricity and gas is reduced, and the operating cost of the enterprise is reduced.

[0006] The application provides the following solutions:

[0007] According to one aspect of the application, a painting air conditioner intelligent regulation control method is provided, which comprises the following steps:

[0008] Obtain multi-dimensional sensor data and system running state, the multi-dimensional sensor is deployed in each process section of the spray paint air conditioner in the coating workshop;

[0009] Preprocess and analyze the multi-dimensional sensor data to obtain stable running data of each process section; the stable running data includes temperature data and relative humidity data;

[0010] According to the stable running data of each process section, obtain the running mode combined with enthalpy and humidity;

[0011] Generate control logic based on the running mode;

[0012] The control logic includes local mode and remote mode;

[0013] The control logic is switched according to the system running state;

[0014] When the control logic is switched to the local mode, compensation and filtering are performed to correct the system running.

[0015] Further, it includes:

[0016] The preprocessing and analysis include: using k-mean clustering algorithm to exclude abnormal data and extract stable threshold;

[0017] The clustering method is specifically:

[0018] ;

[0019] Wherein, k is the number of cluster, involving 4 different control areas, one terminal detection area, so k=5; x is the data in the ith cluster , is the cluster centroid; is the clustering objective function; is the index of the cluster; is the ith cluster; is the data point of the ith cluster ; ; The representative is the centroid of the ith cluster, which is the mean vector of all data points in the cluster;

[0020] Further, Use Euclidean distance calculation:

[0021] ;

[0022] Wherein, is the Euclidean distance from the data point to the cluster centroid ; ​is a data point to be calculated distance; is the centroid of the cluster; is the dimension representing data; is the index of the dimension.

[0023] Further comprising:

[0024] The control logic switches according to the system running state, comprising: according to the heartbeat signal, the switching of the control logic is executed.

[0025] Further comprising:

[0026] According to the stable running data of each process section, combined with enthalpy humidity, the running mode comprises:

[0027] The collected temperature data is converted into Kelvin temperature data;

[0028] According to the Kelvin temperature data, the exponential parameter of the water vapor saturation vapor pressure is calculated;

[0029] According to the exponential parameter of the water vapor saturation vapor pressure, the saturation vapor pressure of the water vapor is calculated;

[0030] According to the collected relative humidity data and the saturation vapor pressure, the partial pressure of the water vapor is calculated;

[0031] According to the saturation vapor pressure and the partial pressure of the water vapor, the moisture content data is calculated;

[0032] According to the moisture content data, combined with the running data, the enthalpy value data is generated;

[0033] According to the enthalpy value data, the running mode is obtained;

[0034] The running mode comprises: summer, winter or spring and autumn mode;

[0035] Further comprising:

[0036] The compensation and filtering comprises: in the PID running, the integral and differential cumulative values need to be re-adjusted; Specifically: ;

[0037] Wherein, The cumulative error during the algorithm running is incorporated into the integral term; The integral term of the PID controller; The integral gain; The term from the first sampling time to the The cumulative value of the term from the first sampling time to the The error of the current time;

[0038] ;

[0039] Wherein, is a derivative term of the PID controller; is a derivative gain; is a rate of error change;

[0040] Further,

[0041] ;

[0042] When responding to the switching signal, the initial is:

[0043] ;

[0044] wherein, is a time of a control cycle, is a filter coefficient, and is 0.091, is a mode switching initial time, is an error value of a previous time, is a rate of error change after low-pass filtering of a previous time.

[0045] Further, comprising:

[0046] The multi-dimensional sensor is arranged in each process section of the paint spraying air conditioner in the painting workshop, including a mixed air section, a preheating section, a filtering section, a surface cooling section, a heating section, a humidifying section, a fan section and a air supply section.

[0047] Further, comprising:

[0048] When the control logic is switched, the running mode parameters, sensor data and control output values at the switching time are recorded synchronously to generate a switching log.

[0049] According to two aspects of the present application, an intelligent adjustment control system for a painting air conditioner is provided, comprising:

[0050] a multi-dimensional sensor module, a data processing module, a mode determination module, a control logic module, a mode switching module and a compensation correction module;

[0051] The multi-dimensional sensor module is arranged in each process section of the paint spraying air conditioner in the painting workshop, and is used for collecting sensor data and system running state data.

[0052] The data processing module is in communication connection with the multi-dimensional sensor module, is used for pre-processing and analyzing the sensor data, and outputs stable running data of each process section.

[0053] The mode determination module is in communication connection with the data processing module, is used for determining a running mode according to the stable running data and the enthalpy-humidity calculation result.

[0054] A control logic module, in communication connection with the mode determination module, is configured to generate control logic based on the operation mode, wherein the control logic comprises a local mode and a remote mode;

[0055] A mode switching module, in connection with the control logic module and the multi-dimensional sensor module, is configured to switch the control logic between the local mode and the remote mode according to the system operation state;

[0056] A compensation correction module, in connection with the mode switching module, is configured to correct the system operation by compensation and filtering when the control logic is switched to the local mode.

[0057] According to the three aspects of the present application, an electronic device is provided, comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory are in communication with each other through the communication bus.

[0058] The memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the coating air conditioner intelligent adjustment control method.

[0059] According to the four aspects of the present application, a computer readable storage medium is provided, which stores a computer program executable by an electronic device, and when the computer program is executed on the electronic device, the electronic device executes the steps of the coating air conditioner intelligent adjustment control method.

[0060] Compared with the prior art, the present application has the following advantages:

[0061] The present application can accurately start the corresponding function segment based on the seasonal mode judgment logic based on enthalpy and humidity content, avoid invalid device operation, and directly reduce redundant energy consumption.

[0062] The present application can filter the temperature and humidity relationship in the stable operation state through k-mean clustering, accurately control the valve opening degree based on temperature difference, and reduce energy waste.

[0063] The present application can parallel the PLC and intelligent algorithm double control system, the local PID mode can guarantee the safety of basic control, and the remote mode can support the accurate adjustment of intelligent algorithm.

[0064] The present application can avoid the instantaneous switching of the valve or the loss of control of temperature and humidity during switching through integral deviation compensation and differential low-pass filtering, and can realize smooth transition of the actuator after optimization, thereby guaranteeing the stability of process parameters.

[0065] The present application can realize the switching of the system by collecting the heartbeat signal, thereby increasing the stability of the system. BRIEF DESCRIPTION OF DRAWINGS

[0066] In order to more clearly illustrate the technical solutions in the specific embodiments of the present application or the prior art, the drawings required to be used in the specific embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative effort on the basis of these drawings.

[0067] Figure 1 is a flow chart of a coating air conditioner intelligent regulation control method provided by one or more embodiments of the present application.

[0068] Figure 2 is a structural diagram of a coating air conditioner intelligent regulation control system provided by one or more embodiments of the present application.

[0069] Figure 3 is a sensor type table required to be deployed in each process section of a coating process according to one specific embodiment of the present application.

[0070] Figure 4 is a seasonal climate area division diagram based on an enthalpy humidity chart according to one specific embodiment of the present application.

[0071] Figure 5 is a seasonal climate area division diagram of air state points of each key link based on an enthalpy humidity chart according to one specific embodiment of the present application.

[0072] Figure 6 is a flow chart of control mode switching and execution logic of a coating air conditioner control system according to one specific embodiment of the present application.

[0073] Figure 7 is a PLC logic ladder diagram of a coating air conditioner control system according to one specific embodiment of the present application.

[0074] Figure 8 is a PLC logic ladder diagram of a coating air conditioner control system according to one specific embodiment of the present application.

[0075] Figure 9 is a PLC logic ladder diagram of a coating air conditioner control system according to one specific embodiment of the present application.

[0076] Figure 10 is a structural block diagram of an electronic device of a coating air conditioner intelligent regulation control method provided by one or more embodiments of the present application. DETAILED DESCRIPTION

[0077] The technical solutions of the present application will be described clearly and completely below in conjunction with the drawings. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0078] Figure 1 is a flowchart of a coating air conditioner intelligent regulation control method provided by one or more embodiments of the present application.

[0079] As shown in Figure 1 , the method comprises the following steps:

[0080] Step S1, acquiring multi-dimensional sensor data and system running state, the multi-dimensional sensor being deployed at each process section of a paint spraying air conditioner in a coating workshop;

[0081] Specifically, sensors are installed in each section of the production line body, and the sensors include temperature and humidity sensors, water flow sensors, water temperature sensors, valve opening degree sensors, energy sensors, humidification pump frequency sensors, and fan frequency sensors of each process section, so as to realize device control through monitoring of the signals of the above-mentioned sensors.

[0082] Step S2, pre-processing and analyzing the multi-dimensional sensor data to acquire stable running data of each process section; the stable running data includes temperature data and relative humidity data;

[0083] Specifically, in the clustering, the data in the stable running state is first segmented, the data is preliminarily screened according to every 2 hours, and is screened according to the k-mean method, and the characteristics of each section are presented according to the clustering result. In this process, abnormal data can be well eliminated, and then the data relationship in the stable state of each section is obtained.

[0084] Step S3, acquiring a running mode according to the stable running data of each process section and in combination with enthalpy humidity;

[0085] Specifically, the running mode judgment logic judges the enthalpy value through collection of the external temperature and humidity,

[0086] and then judges the current running mode, and controls the start of part of the devices through the running mode judgment result.

[0087] Specifically, after the fan is started, the current running mode of the air conditioner needs to be judged according to the current climate parameters of the outside world.

[0088] Step S4, generating a control logic based on the running mode;

[0089] The control logic includes a local mode and a remote mode.

[0090] Specifically, according to the operation mode, the fresh air conditioner operation can be divided into: winter mode, spring and autumn mode, summer mode; the circulating air conditioner is affected by the outlet temperature and humidity of fresh air, but it does not have an operation mode. The required operation function section of the fresh air conditioner in each season operation mode is as follows:

[0091] Summer mode: cooling section, secondary heating. Among them, the cooling section is responsible for cooling the outside air with high temperature, and at the same time, it plays a dehumidification effect, and the secondary heating is responsible for reheating the cooled air. Due to high temperature and high humidity in summer, the humidifying pump is usually not started.

[0092] Spring and autumn mode: cooling section, humidifying section. Among them, the cooling is responsible for cooling the outside air, and in the case of high humidity, it needs to have a dehumidification function, and the humidifying section is responsible for humidifying the low humidity air to the standard value.

[0093] Winter mode: one-stage heating, humidifying section. Among them, one-stage heating is responsible for directly heating the outside air with low temperature, and the humidifying section is responsible for humidifying the dry air in winter.

[0094] Step S5, the control logic switches according to the system operation state;

[0095] Specifically, according to the two parallel operation systems, the system is isolated by setting the remote start method, and the PID mode is only run in the local mode. The control system issues control instructions to the PLC, and in order to ensure safety, the highest authority is set in the local mode. In the local mode, the remote mode does not run any operation and cannot be switched back to the remote mode.

[0096] In the remote mode, the control system can execute the algorithm, that is, the MPC mode, or can be switched to the PID control system according to the actual demand on the spot. The two systems cannot run in parallel.

[0097] Step S6, when the control logic is switched to the local mode, compensation and filtering are performed to correct the system operation.

[0098] Specifically, after the operation system is switched, the valve exists instantaneous closing or opening phenomenon, which leads to uncontrollable temperature and humidity. The recovery process is relatively long, which leads to that any switching cannot be performed in the normal production process, and there is a great production hidden danger. After the integral and differential compensation, the algorithm switching can realize smooth transition of the air conditioner executor.

[0099] Further, it includes:

[0100] The preprocessing and analysis include: using the k-mean clustering algorithm to remove outliers and extract stable threshold values from the collected data;

[0101] The clustering method is specifically:

[0102] ;

[0103] where k is the number of clusters, involving 4 different control regions, one terminal detection region, so k = 5; x is the data in the i-th cluster, is the centroid of the cluster; is the clustering objective function; is the index of the cluster; is the i-th cluster; is the data point of the i-th cluster is the data point of the i-th cluster is the data point of the i-th cluster is the centroid of the i-th cluster, which is the mean vector of all data points in the cluster;

[0104] Further, using the Euclidean distance calculation:

[0105] ;

[0106] where, is the Euclidean distance from the data point to the cluster centroid ; is the data point to be calculated; is the centroid of the cluster; is the dimension of the data; is the index of the dimension.

[0107] Specifically, after k-means clustering screening, it is found that the temperature and humidity of each section have a numerical relationship in the stable running state, so the temperature difference control valve opening can be used in the control to achieve more accurate control. In the clustering, the data in the stable running state is first segmented, and the data is preliminarily screened every 2 hours, and then clustered in the above manner. It can be found that the clustering results show the characteristics of each section, and in this process, abnormal data can be well eliminated, and the data relationship in the stable state of each section is obtained.

[0108] Referring to Figure 5 , according to the data distribution, the present application concludes that if each functional section does not work, such as the heating section does not supply water temporarily, and only relies on space heat dissipation, then the temperature difference between two adjacent functional sections does not exceed 2℃, and the relative humidity difference is 1%-3%; if there is a working state, in order to maintain the process parameters stable at the outlet, according to the data analysis results, the outlet of each section should at least meet:

[0109] the heating temperature of the first section in winter is maintained at 40℃-47℃; and the relative humidity is maintained at 38%-45% after humidification;

[0110] ​​Spring and autumn mode table cold 18-20℃; after humidification, the relative humidity is maintained at 40%-52%;

[0111] Summer mode two section outlet maintained at 31-38℃ interval.

[0112] The air-conditioning cabin outlet temperature and humidity sensor is used to directly evaluate the outlet temperature and humidity, according to the above data analysis process, the stable running state, the moisture content deviation should not be less than 1g / kg, otherwise the system gives an alarm.

[0113] The circulating air conditioner only has a humidification section and a table cooling section, in addition to the inlet and outlet positions of the air-conditioning cabin, temperature and humidity sensors are installed after humidification and table cooling. Since there is no seasonal mode for the humidification pump, according to the above data analysis method, the stable running state can be obtained, otherwise the system needs to be alarmed:

[0114] The temperature after the humidification pump section needs to be maintained at 18-19℃, and the humidity can be maintained at 85%-88% during operation;

[0115] The temperature after table cooling needs to be maintained at 17-18.5℃ during operation, and the humidity needs to be maintained at 74%-80%.

[0116] Further, comprising:

[0117] The control logic switches according to the system running state, including: executing the switching of the control logic according to the heartbeat signal.

[0118] Specifically, according to the periodic signal actively sent by the system key component, it is judged whether the corresponding component is in a normal running state, when signal loss, format exception, state code exception and frequency exception occur, it is judged that the corresponding component is in an abnormal running state, and the problem source can be located through the exception type.

[0119] Further, comprising:

[0120] According to the stable running data of each process section, combined with enthalpy and humidity, the running mode includes:

[0121] Step A1, converting the collected temperature data into Kelvin temperature data;

[0122] Step A2, calculating the exponential parameter of water vapor saturation vapor pressure according to the Kelvin temperature data;

[0123] Step A3, calculating the saturation vapor pressure of water vapor according to the exponential parameter of water vapor saturation vapor pressure;

[0124] Step A4, calculating the partial pressure of water vapor according to the collected relative humidity data and the saturation vapor pressure;

[0125] Step A5, calculating the moisture content data according to the saturation vapor pressure and the partial pressure of water vapor;

[0126] Step A6: Based on the moisture content data and combined with the operating data, generate enthalpy data;

[0127] Step A7: Obtain the operating mode based on the enthalpy data;

[0128] Operating modes include: summer, winter, or spring / autumn mode;

[0129] Specifically, the enthalpy and humidity are calculated using the following method:

[0130] Moisture content:

[0131]

[0132]

[0133]

[0134] Where ps is the saturated vapor pressure of water vapor (Pa), pd is the partial pressure of water vapor (Pa), T is the input temperature in degrees Celsius (°C), and equation (1) converts the temperature into Kelvin (K); H is the relative humidity collected by the sensor, and finally the moisture content is output. The unit is g / kg.

[0135] The enthalpy value is calculated as follows:

[0136]

[0137] Where T is the dry-bulb temperature (°C) collected by the sensor, M is the moisture content calculated by equation (4), and the output enthalpy value is... Unit: kJ / kg.

[0138] The specific method is as follows: due to the air circulation inside the original cabin, the temperature and humidity inside the cabin before the primary filtration can better reflect the internal conditions of the cabin, while the external sensors can better reflect the external weather conditions, but are easily affected by extreme weather, resulting in inaccurate measurements.

[0139] Therefore, considering both the temperature and humidity before adding the primary filter, the process is as follows:

[0140] Step 1: Calculate the moisture content before primary filtration using the formula, and compare it with the moisture content at the air inlet. If the difference in moisture content is greater than 5, an alarm will be triggered.

[0141] Step 2: Determine if the machine is on. If it is on and the moisture content difference is greater than 5, then continue to determine if it is winter. If so, use the inlet temperature and humidity as the inlet standard; otherwise, use the temperature and humidity before the primary filter as the standard.

[0142] Step 3: Under normal operating conditions, if it is summer mode, use the one with higher humidity as the standard for calculation;

[0143] Step 4: Under normal operating conditions, if it is the spring / autumn mode, use the lower humidity content as the standard for calculation.

[0144] Furthermore, including:

[0145] Compensation and filtering include: readjusting the integral and derivative cumulative values ​​during PID operation; specifically: ;

[0146] in, The cumulative error during the algorithm's execution is incorporated into the integration term; This is the integral term of the PID controller; For integral gain; To analyze data from the first sampling time to the second sampling time... The items at each sampling time are accumulated; This represents the error at the current moment;

[0147] ;

[0148] in, This is the derivative term of the PID controller; This is the differential gain; The rate of change of error;

[0149] Furthermore,

[0150] ;

[0151] When responding to the switching signal, initially for:

[0152] ;

[0153] in, To control the cycle time, This is the filter coefficient, with a value of 0.091. At the initial moment of mode switching, This represents the error value from the previous moment. This represents the rate of change of error after low-pass filtering at the previous moment.

[0154] Specifically, in automatic mode, the PID controller follows the PID algorithm to automatically adjust the output to ensure the process feedback value follows the setpoint and remains stable. This is an automatic closed-loop control system. Operators can change the setpoint value according to the requirements of the on-site process. PID control follows the formula:

[0155]

[0156] Where Kp represents the proportional gain, Ki represents the integral gain, Kd represents the derivative gain, and e(t) represents the error, which is the deviation between the actual process value and the set value. When running the above formula in a PLC, discretization processing is required.

[0157]

[0158] The first part is the proportional term, which is used to compensate for the difference between the proportional term and the set value; the second part is the integral term, which is used to eliminate steady-state error; and the third part is the derivative term, which is used to respond to the rate of change of the system deviation and avoid oscillations caused by the proportional term changing too quickly.

[0159] The disturbance-free switching control of the mode switching mainly includes changing the mode of the PID parameter block and adjusting the parameter input method of the PID. In the original operating mode, when the control mode is switched, the algorithm and PID also run synchronously. At this time, the temperature and humidity sample values ​​obtained by the algorithm are all values ​​adjusted by the PID, which causes the sample training results to be biased. However, when the algorithm switches to PID, the PID will accumulate the proportional, integral and derivative components again, which causes the adjustment delay. The calculation of the proportional term does not involve the time dimension. The algorithm and PID are no different. According to equation (7), the role of integral and derivative needs to consider the accumulation of error over a period of time. If the accumulation starts again every time the switch is made, and there are problems such as steady-state temperature difference and oscillation during the switching process, the integral and derivative terms cannot be used. Therefore, it is necessary to readjust the accumulated values ​​of integral and derivative during PID operation.

[0160]

[0161]

[0162] in The accumulated error during algorithm execution is incorporated into the integral term to compensate for it. However, since the differential term's calculation process considers the difference between the previous and current time points, a low-pass filter is used during compensation to prevent excessively rapid changes in the rate of change from the previous time point. This filter is continuously accumulated for 10 minutes to supplement the deficiencies in the differential term during switching. The specific calculation method is as follows:

[0163]

[0164] In the formula The filter coefficient is set to 0.091 in this invention. When the switching signal is initially... for:

[0165]

[0166] in To control the cycle time, an intermediate variable was designed. During switching, the algorithm calculates the variable value and assigns it to the PLC's PID parameters. Verification showed that before seamless switching, the valve experienced momentary closure or widening after switching to PID, leading to temperature and humidity malfunction. Furthermore, the recovery process was lengthy, preventing any switching during normal production and posing a significant production hazard. After integral and derivative adjustments, the algorithm achieves a smooth transition between actuators in each section of the air conditioner during switching.

[0167] Furthermore, including:

[0168] Multi-dimensional sensors are deployed in various process sections of the painting workshop's air conditioning system, including: air mixing section, preheating section, filtration section, surface cooling section, heating section, humidification section, fan section, and air supply section.

[0169] Furthermore, including:

[0170] When the control logic switches, the operating mode parameters, sensor data and control output values ​​at the time of switching are recorded synchronously to generate a switching log.

[0171] Specifically, when the system subsequently experiences control anomalies (such as uncontrolled temperature and humidity, or malfunctioning actuators), the switching log can provide a crucial snapshot of the switching moment. By comparing the differences in parameters and states before and after the switching, the root cause of the problem can be quickly identified: whether it is an error in parameter transmission during the switching process or a mismatch between the control logic and the operating conditions after the switching, significantly shortening troubleshooting time and improving system operation and maintenance efficiency.

[0172] Figure 2 This is a structural diagram of an intelligent adjustment and control system for coating air conditioning provided in one or more embodiments of the present invention.

[0173] like Figure 2 As shown, it includes:

[0174] Multi-dimensional sensor module, data processing module, mode determination module, control logic module, mode switching module, and compensation and correction module;

[0175] Multi-dimensional sensor modules are deployed in various process sections of the air conditioning system in the painting workshop to collect sensor data and system operating status data.

[0176] The data processing module is used to communicate with the multi-dimensional sensor module, preprocess and analyze the sensor data, and output stable operating data of each process segment.

[0177] The mode determination module is used to communicate with the data processing module and to determine the operating mode based on the stable operating data and the enthalpy and humidity calculation results.

[0178] A control logic module, which is communicatively connected to the mode determination module, is used to generate control logic based on the operating mode, the control logic including local mode and remote mode;

[0179] The mode switching module is connected to the control logic module and the multi-dimensional sensor module respectively, and is used to control the control logic to switch between local mode and remote mode according to the system operating status.

[0180] The compensation and correction module, connected to the mode switching module, is used to correct the system operation through compensation and filtering when the control logic is switched to local mode.

[0181] It is worth noting that although only some basic functional modules are disclosed in this embodiment, it does not mean that the composition of this system is limited to the above-mentioned basic functional modules. On the contrary, what this embodiment intends to express is that, based on the above-mentioned basic functional modules, those skilled in the art can arbitrarily add one or more functional modules in combination with existing technology to form an infinite number of embodiments or technical solutions. That is to say, this system is open rather than closed. The fact that this embodiment only discloses a few basic functional modules does not mean that the scope of protection of the claims of this invention is limited to the disclosed basic functional modules. At the same time, for the convenience of description, the above device is described separately according to its functions as various units and modules. Of course, in implementing this invention, the functions of each unit and module can be implemented in one or more software and / or hardware.

[0182] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0183] Figure 3 This is a table of sensor types that need to be deployed in each process segment of the coating process according to a specific embodiment of the present invention.

[0184] like Figure 3 As shown, a hardware deployment scheme is provided, which mainly includes installing temperature and humidity sensors, valve opening sensors, flow meters, equipment vibration frequency sensors and other sensing devices in each process section of the air conditioning system, namely mixing, preheating, filtering, surface cooling, heating, humidification and air supply sections. The newly added and modified equipment is connected to the data acquisition platform to accumulate a large amount of production process data and provide data support for intelligent algorithms.

[0185] Figure 4 This is a seasonal climate zone division map based on enthalpy-humidity chart, which is a specific embodiment of the present invention.

[0186] Combination Figure 4 Implement logic modification of the PLC control program, based on Figure 3 Real-time data from various sensors is used to calculate the current seasonal mode of the air conditioner, and feedback is generated with the algorithm for continuous adjustment and optimization. The specific judgment method and related equipment control principles are as follows:

[0187] 1. Determine if the current mode is summer mode. The determination method is that if the outside humidity is greater than or equal to the set humidity, it means that dehumidification is required, and therefore it is determined to be summer mode. Only in summer mode will the air conditioner have a dehumidification function and the surface cooling and secondary heating equipment will be activated.

[0188] 2. Determine if it is winter mode: If the ambient humidity is less than the set humidity and the ambient enthalpy is less than the lower limit of enthalpy, it means that heating and humidification are required. Therefore, it is determined to be winter mode, and the heating and humidification sections of the equipment will operate.

[0189] 3. Determine if it is in spring / autumn mode: If the ambient humidity is less than the set humidity and the ambient enthalpy is greater than the lower limit of enthalpy, it means that humidification is required and cooling may be necessary. The surface cooling section and humidification section equipment should be turned on.

[0190] 4. If the last startup had an automatically selected mode, the fan will temporarily run in the mode it was in before the last shutdown after startup. After 30 seconds, the mode will be changed based on external conditions. If necessary, the mode will be changed automatically.

[0191] 5. When the air conditioner is in manual mode, it will operate according to the seasonal mode selected manually, and the corresponding function segments will be manually activated.

[0192] Figure 6 This is a flowchart of the control mode switching and execution logic of a coating air conditioning control system according to a specific embodiment of the present invention.

[0193] like Figure 6 As shown, it includes:

[0194] A new multi-dimensional sensor is embedded in the new system, which effectively supports algorithm operation. For security reasons, two parallel operating systems are designed, and remote start is used to isolate the systems. In local mode, only the PID control system runs, sending control commands to the PLC. To ensure safety, the highest privilege level is set in local mode; in local mode, the remote mode does not run or perform any operations, and it is impossible to switch back to remote mode.

[0195] In remote mode, the control system can execute the algorithm (MPC mode) or switch to PID control system operation according to actual on-site needs. The two systems cannot run in parallel. This invention redesigns and rewrites the PLC program to address this issue. The original PLC can operate normally based on the existing sensors, but after switching to the algorithm control system, the original equipment control logic is disconnected. The execution logic is as follows:

[0196] like Figure 7 , 8 As shown:

[0197] Taking a paint-coated fresh air conditioner as an example, after the device starts up, it needs to determine the current seasonal mode. After receiving the signal for determining the seasonal mode, a program for the judgment logic is written based on the principle of starting the device in different seasons, and then the device outputs a signal. For example, there is a cooling signal output only in spring / autumn and summer modes, a first-stage heating output only in winter mode, and a second-stage heating output signal only in winter and summer modes, etc.

[0198] In actual operation, due to on-site operations or system data transmission issues, there may be a need to switch in remote mode. Air conditioning control systems require high control precision, and control fluctuations should be minimized during system switching. Therefore, this invention designs a bumpless switching method between algorithms and PID control. This method achieves a smooth control transition by compensating for differential deviations during switching.

[0199] As attached Figure 9 As shown:

[0200] After receiving the signal that the current process section of the equipment is allowed to output, when switching from PID to algorithm, the PID function block is reset, and the algorithm takes over the currently generated integral quantity as input to continue control. However, when switching from algorithm mode to PID control, because the integral accumulation is cleared to zero upon reset in traditional PID operation mode, the PID controller will start controlling and adjusting the output from 0 again, causing fluctuations in control parameters and a large control time delay. By changing the control mode and input parameters of the PID controller, when switching algorithms, the algorithm inputs the cumulative value of the integral quantity to the PID controller through manual input points and maintains this for ten minutes to achieve a stable switching of control modes.

[0201] In one embodiment,

[0202] Combination Figure 3This embodiment provides a hardware deployment scheme, which mainly includes installing temperature and humidity sensors, valve opening sensors, flow meters, equipment vibration frequency sensors and other sensing devices in each process section of the air conditioning system, namely mixing, preheating, filtering, surface cooling, heating, humidification and air supply sections. The newly added and modified equipment is connected to the data acquisition platform to accumulate a large amount of production process data and provide data support for intelligent algorithms.

[0203] In one embodiment:

[0204] Combination Figure 4 The logic of the PLC control program is modified. Based on the real-time data from various sensors in the previous embodiment, the seasonal mode of the current air conditioner is determined through formula calculation, and feedback is generated with the algorithm for continuous adjustment and optimization. The specific determination method and related equipment control principles are as follows:

[0205] 1. Determine if the current mode is summer mode. The determination method is that if the outside humidity is greater than or equal to the set humidity, it means that dehumidification is required, and therefore it is determined to be summer mode. Only in summer mode will the air conditioner have a dehumidification function and the surface cooling and secondary heating equipment will be activated.

[0206] 2. Determine if it is winter mode: If the ambient humidity is less than the set humidity and the ambient enthalpy is less than the lower limit of enthalpy, it means that heating and humidification are required. Therefore, it is determined to be winter mode, and the heating and humidification sections of the equipment will operate.

[0207] 3. Determine if it is in spring / autumn mode: If the ambient humidity is less than the set humidity and the ambient enthalpy is greater than the lower limit of enthalpy, it means that humidification is required and cooling may be necessary. The surface cooling section and humidification section equipment should be turned on.

[0208] 4. If an automatic mode was selected during the last startup, the fan will temporarily run in the mode it was in before the last shutdown after startup. After 30 seconds, the mode will be changed based on external conditions. If necessary, the mode will be changed automatically.

[0209] 5. When the air conditioner is in manual mode, it will operate according to the seasonal mode selected manually, and the corresponding function segments will be manually activated.

[0210] In one embodiment:

[0211] Combination Figure 7 Based on real-time parameters such as ambient temperature and humidity, the system determines the seasonal mode of the air conditioner, providing input for subsequent control signal transmission.

[0212] Combination Figure 8When the control mode switches from PID to intelligent algorithm mode, and conditions such as equipment operation, temperature, algorithm access, and seasonal mode judgment are met, a signal is given that the valve can be remotely controlled, and then a signal is given that each process section can output. The output signal and the algorithm mode operation signal are connected in series as the signal input for the PID controller to stop working, thereby turning off the PID controller. At this time, the algorithm will take over all the parameters of the PID controller to continue to control and regulate.

[0213] In one embodiment:

[0214] Combination Figure 9 The improvement of the seamless switching mode mainly consists of the following: 1. Switching the working mode of the PID controller. In the original working mode, the PID controller always worked, and the temperature and humidity sample values ​​obtained by the intelligent control algorithm were all output values ​​adjusted by the PID controller. This would cause the sample training model of the algorithm to be all optimized output values, and the operation of the entire algorithm would be deviated. After changing the operating mode, the algorithm and the PID controller run independently, ensuring the accuracy of the algorithm training samples. During the training and verification process of the new samples, it was found that when the mode switching occurred, that is, when switching from the algorithm mode to the PID control mode, the air conditioner parameter control fluctuated greatly, and the PID controller would clear the current integral quantity to zero, causing the output valve to close and restart the adjustment control. This step required a lot of time to bring the temperature and humidity parameters back to normal. To address this issue, the control logic for mode switching was further optimized. In the manual mode of the PID controller, the normally closed signal of the algorithm mode and the normally open signal of the remote mode were connected in series, and the connection was made by delay. When the algorithm switches to PID, the current integral quantity is input to the PID controller in the form of this manual signal. After 10 minutes, the PID enters the automatic mode, realizing a smooth transition of the entire switching process and reducing control fluctuations.

[0215] Figure 10 This is an electronic device structural block diagram of an automotive paint spraying air conditioning predictive control method provided by one or more embodiments of the present invention.

[0216] like Figure 10 As shown, this application provides an electronic device, including: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus;

[0217] The memory stores a computer program, which, when executed by the processor, causes the processor to perform the steps of a smart adjustment and control method for coating air conditioning.

[0218] This application also provides a computer-readable storage medium storing a computer program executable by an electronic device, which, when run on the electronic device, causes the electronic device to perform the steps of a coating air conditioning intelligent adjustment and control method.

[0219] For the sake of simplicity, the method embodiments are described as a series of actions. However, those skilled in the art should understand that the embodiments of the present invention are not limited to the described order of actions, because according to the embodiments of the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions involved are not necessarily essential to the embodiments of the present invention.

[0220] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in various embodiments or some parts of the embodiments of this application.

[0221] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for intelligent adjustment and control of air conditioning in coating processes, characterized in that, include: Acquire multi-dimensional sensor data and system operating status; the multi-dimensional sensors are deployed in various process sections of the painting workshop's air conditioning system. The multi-dimensional sensor data is preprocessed and analyzed to obtain stable operating data for each process segment; The stable operating data includes: temperature data and relative humidity data; Based on the stable operating data of each process segment, combined with enthalpy and humidity, the operating mode is obtained; Based on the operating mode, generate control logic; The control logic includes: local mode and remote mode; The control logic switches according to the system's operating state; When the control logic switches to local mode, compensation and filtering are performed to correct the system operation.

2. The intelligent adjustment and control method for coating air conditioning according to claim 1, characterized in that, The preprocessing and analysis include: using the k-means clustering algorithm to remove anomalies and extract stable thresholds from the collected data; The clustering method is specifically as follows: ； in, The number of clusters involves four different control regions and one terminal detection region. =5; For the first Cluster The data in It is the centroid of the cluster; It is the clustering objective function; It is the cluster index; It is the first A cluster; It indicates that it is the first Cluster Data points; The representative is the centroid of the i-th cluster, and the mean vector of all data points in that cluster; Furthermore, Calculated using Euclidean distance: ； in, Data points to cluster centroid The Euclidean distance; These are the data points whose distances are to be calculated; It is the centroid of the cluster; It represents the dimension of the data; It is a dimension index.

3. The intelligent adjustment and control method for coating air conditioning according to claim 1, characterized in that, The control logic switching based on the system operating state includes: switching the control logic based on the heartbeat signal.

4. The intelligent adjustment and control method for coating air conditioning according to claim 3, characterized in that, The process of obtaining the operating mode based on the stable operating data of each process segment, combined with enthalpy and humidity, includes the following steps: Convert the collected temperature data into Kelvin temperature data; Calculate the exponential parameter of the saturated vapor pressure of water vapor based on Kelvin temperature data; Calculate the saturated vapor pressure of water vapor based on the exponential parameter of the saturated vapor pressure of water vapor; Calculate the partial pressure of water vapor based on the collected relative humidity data and saturated vapor pressure; Calculate the moisture content data based on the saturated vapor pressure and the partial pressure of water vapor; Based on the moisture content data and combined with the operational data, enthalpy data is generated. Obtain the operating mode based on the enthalpy data; The operating modes include: summer, winter, or spring / autumn modes.

5. The intelligent adjustment and control method for coating air conditioning according to claim 1, characterized in that, The compensation and filtering include: readjusting the integral and derivative cumulative values ​​during PID operation; specifically: ; in, The cumulative error during the algorithm's execution is incorporated into the integration term; This is the integral term of the PID controller; For integral gain; To analyze data from the first sampling time to the second sampling time... The items at each sampling time are accumulated; This represents the error at the current moment; ； in, This is the derivative term of the PID controller; This is the differential gain; The rate of change of error; ； When responding to the switching signal, initially for: ； in, To control the cycle time, This is the filter coefficient, with a value of 0.

091. At the initial moment of mode switching, This represents the error value from the previous moment. This represents the rate of change of error after low-pass filtering at the previous moment.

6. The intelligent adjustment and control method for coating air conditioning according to claim 1, characterized in that, The multi-dimensional sensors are deployed in various process sections of the painting workshop's air conditioning system, including: air mixing section, preheating section, filtration section, surface cooling section, heating section, humidification section, fan section, and air supply section.

7. The intelligent adjustment and control method for coating air conditioning according to claim 1, characterized in that, When the control logic switches, the operating mode parameters, sensor data and control output values ​​at the time of switching are recorded synchronously to generate a switching log.

8. A smart adjustment and control system for coating air conditioning, characterized in that, include: Multi-dimensional sensor module, data processing module, mode determination module, control logic module, mode switching module, and compensation and correction module; Multi-dimensional sensor modules are deployed in various process sections of the air conditioning system in the painting workshop to collect sensor data and system operating status data. The data processing module is used to communicate with the multi-dimensional sensor module, preprocess and analyze the sensor data, and output stable operating data of each process segment. The mode determination module is used to communicate with the data processing module and to determine the operating mode based on the stable operating data and the enthalpy and humidity calculation results. A control logic module, which is communicatively connected to the mode determination module, is used to generate control logic based on the operating mode, the control logic including local mode and remote mode; The mode switching module is connected to the control logic module and the multi-dimensional sensor module respectively, and is used to control the control logic to switch between local mode and remote mode according to the system operating status. The compensation and correction module, connected to the mode switching module, is used to correct the system operation through compensation and filtering when the control logic is switched to local mode.

9. An electronic device, characterized in that, include: The processor, communication interface, memory, and communication bus are connected, with the processor, communication interface, and memory communicating with each other via the communication bus. The memory stores a computer program, which, when executed by the processor, causes the processor to perform the steps of the intelligent adjustment and control method for coating air conditioning as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, It stores a computer program that can be executed by an electronic device, which, when run on the electronic device, causes the electronic device to perform the steps of the intelligent adjustment and control method for coating air conditioning as described in any one of claims 1-7.

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