Method for optimizing surface discharge ozone control

Abstract

The present application relates to the technical field of ozone control, in particular to a surface discharge ozone control optimization method, comprising the following steps: collecting temperature and humidity, voltage and ozone concentration data based on a discharge device, performing proportional transformation and optimization, extracting trend characteristic factors, screening nodes and sorting according to relevance, analyzing the combined effect of electricity and temperature and humidity on ozone change, identifying a regulation and control unit, and optimizing load distribution configuration. In the present application, the temperature and humidity, electrical and ozone concentration data collected in the region are normalized, a data linkage mechanism with temperature and humidity change as the core is constructed, node response performance is dynamically sorted, periodic data changes are fused, a control process for coordinated adjustment of temperature and humidity and electrical parameters is formed, real-time adjustment of partition load and dynamic optimization of energy distribution are realized, agile response of ozone generation regulation and control and multi-region difference matching capability are brought, and the stability under ozone yield fluctuation is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of ozone control, in particular to a surface discharge ozone control optimization method. BACKGROUND

[0002] Ozone control technology relates to the process and system related to the generation and regulation of ozone, mainly including ozone generation principle, discharge mode, discharge device structure, ozone concentration monitoring and regulation, and related environmental safety management, etc., and is widely used in water treatment, air purification, industrial oxidation, etc. Among them, the traditional surface discharge ozone control optimization method refers to the method of forming a discharge channel on the surface of an insulator, adjusting the electrode structure, material properties and applied voltage parameters, etc. to change the discharge path and discharge intensity, so as to realize the control of the ozone generation process.

[0003] The prior art ignores the dynamic changes of temperature and humidity in multiple regions in the processing process, and the differences in working conditions inside and outside the region are difficult to identify, resulting in slow response of regional regulation under single parameter driving, local overload and large ozone production rate fluctuations, etc. In the environment of high humidity and high temperature, uneven working conditions, energy distribution is uneven and ozone production process is unstable due to untimely adjustment, which is difficult to adapt to the actual situation of higher requirements for differential regulation and energy consumption control. SUMMARY

[0004] In order to solve the technical problems of the prior art that ignore the dynamic changes of temperature and humidity in multiple regions in the processing process, the differences in working conditions inside and outside the region are difficult to identify, resulting in slow response of regional regulation under single parameter driving, local overload and large ozone production rate fluctuations, etc. In the environment of high humidity and high temperature, uneven working conditions, energy distribution is uneven and ozone production process is unstable due to untimely adjustment, which is difficult to adapt to the actual situation of higher requirements for differential regulation and energy consumption control, the embodiments of the present application provide a surface discharge ozone control optimization method. The technical solution is as follows:

[0005] On the one hand, a surface discharge ozone control optimization method is provided, comprising the following steps:

[0006] S1: Based on the discharge device, collect the temperature and humidity, voltage and ozone concentration data of each region, standardize the temperature and humidity by proportion, correlate the optimization parameters and ozone concentration, summarize the trend changes of each region, and obtain the node trend characteristic factor;

[0007] S2: Based on the node trend characteristic factor, calculate the temperature and humidity change rate of each monitoring point, analyze the correlation degree with the ozone concentration, screen the high correlation nodes, judge the influence intensity and perform priority sorting, and obtain the response priority sequence;

[0008] S3: Based on the response priority sequence, the electrode voltage, discharge current density and temperature and humidity data of the region with high ranking are compared, the ozone change characteristics under the linkage of multiple parameters are analyzed, the key nodes are identified, and the regulation effect distribution unit is obtained;

[0009] S4: Based on the regulation effect distribution unit, the node high-frequency voltage fluctuation is analyzed, the voltage peak amplitude change is judged, and the association of the node temperature and humidity change with the voltage anomaly is compared, the coupling offset characteristics are identified, and the coupling offset performance quantity is obtained.

[0010] On the other hand, the node trend characteristic factor includes trend intensity parameter, node association level, change direction type, the response priority sequence includes priority response level, response node number, hierarchical sorting identifier, the regulation effect distribution unit includes regulation node group, distribution weight coefficient, action category type, and the coupling offset performance quantity includes temperature and humidity offset amplitude, voltage fluctuation characteristics, coupling performance label.

[0011] On the other hand, the step of the node trend characteristic factor is:

[0012] S101: Based on the discharge device, the temperature data, humidity data, power supply voltage data and ozone concentration data of each node are analyzed, the temperature and humidity original data collected by each node are standardized, which are combined according to the node order, and the data under the same standard are compared, and the unified parameter baseline group is obtained;

[0013] S102: Based on the unified parameter baseline group, the ozone concentration change data of each node are compared, the corresponding relationship of temperature and humidity and ozone concentration data is established according to node number, the consistency of temperature and humidity change direction and ozone concentration change direction in difference time period is judged, the number of synchronous change is calculated, and the linkage trend characteristic quantity is obtained.

[0014] S103: Based on the linkage trend characteristic quantity, the nodes with consistent temperature and humidity and ozone concentration direction are screened, the frequency and fluctuation amplitude of synchronous change in each group of nodes are analyzed, the nodes are grouped according to node number, and the node trend characteristic factor is obtained.

[0015] On the other hand, the step of the response priority sequence is:

[0016] S201: Based on the node trend characteristic factor, the change rate of temperature and humidity of each monitoring node in continuous sampling period is calculated, the change direction of temperature and humidity value between adjacent time periods is judged, the amplitude of temperature change and humidity change in the same period is compared, and the change amplitude interval is obtained.

[0017] S202: Based on the change amplitude interval, analyze the synchronization between the temperature and humidity change trend and the ozone concentration change, according to the consistency of the change direction of each node temperature and humidity and ozone concentration, count the appearance frequency of the synchronous direction, and obtain the trend coupling performance degree;

[0018] S203: Based on the trend coupling performance degree, screen the nodes with high frequency of synchronous performance, sort the nodes according to the coupling performance of each node and ozone concentration change from the frequency and amplitude of synchronous performance, and obtain the response priority sequence.

[0019] On the other hand, the step of the regulation distribution unit is specifically:

[0020] S301: Based on the response priority sequence, analyze the continuous change of electrode surface voltage, discharge current density and temperature and humidity of nodes with high ranking, compare the synchronous fluctuation of each data of each node in the sampling period, judge the consistency of the fluctuation direction of each parameter, and obtain the multi-parameter change data.

[0021] S302: Based on the multi-parameter change data, analyze the relationship between the joint fluctuation of voltage, density and temperature and humidity and the response of ozone concentration, count the synchronous appearance times of ozone concentration change when the parameters are linked, analyze the influence of joint change on ozone response, and obtain the linkage influence index.

[0022] S303: Based on the linkage influence index, screen the nodes with high trend direction synchronization rate, judge the corresponding relationship between the cooperative fluctuation of each node and the ozone response performance, identify the key nodes, and obtain the regulation distribution unit.

[0023] On the other hand, the corresponding relationship between the cooperative fluctuation of each node and the ozone response performance is judged by using the formula:

[0024] ;

[0025] The cooperative response offset value is calculated, the key nodes are identified, and the regulation distribution unit is obtained, wherein, The cooperative response offset value of the node represents the temperature change of the node at time , the humidity change of the node at time , the ozone concentration change of the node at time , and the total number of time points in the calculation period.

[0026] ​​​​In another aspect, the step of coupling the offset performance quantity is specifically:

[0027] S401: Based on the regulation distribution unit, analyze the high-frequency voltage data collected by the node in the continuous period, judge the peak and valley change of voltage fluctuation in each period, compare the fluctuation amplitude and change trend between periods, and count the direction and distribution of voltage fluctuation of each node to obtain the fluctuation interval characteristic set;

[0028] S402: According to the fluctuation interval characteristic set, compare the change direction of node temperature and humidity data, analyze whether the temperature and humidity change in the same period is consistent with the voltage fluctuation, judge the fluctuation synchronization phenomenon of parameters, and count the synchronization change paragraph to obtain the synchronization response distribution quantity;

[0029] S403: According to the synchronization response distribution quantity, judge the offset trend of the combination of node temperature and humidity fluctuation and voltage change, arrange the node number and synchronization performance characteristics, analyze the relationship between the offset interval and temperature and humidity change, and obtain the coupling offset performance quantity.

[0030] In another aspect, the relationship between the offset interval and temperature and humidity change is analyzed by using the formula:

[0031] ;

[0032] The coupling offset performance quantity is obtained, wherein, represents the temperature and humidity voltage coupling offset performance quantity of the i-th node, represents the sampling number of the i-th node in the statistical period, represents the temperature data of the i-th node in the statistical period, represents the temperature average data of the i-th node in the statistical period, represents the humidity data of the i-th node in the statistical period, represents the humidity average data of the i-th node in the statistical period, represents the voltage data of the i-th node in the statistical period, represents the voltage average data of the i-th node in the statistical period.

[0033] In another aspect, the method further comprises:

[0034] ​​​​​​​​​​​S5: based on the coupling offset performance quantity, optimizing the temperature of the heat dissipation area of the associated area and the humidity of the electrode structure, combining the current density and the ozone response, analyzing the influence of temperature and humidity on load distribution, adjusting the target power, and obtaining the load distribution adjustment configuration;

[0035] The load distribution adjustment configuration includes a load adjustment configuration, a target distribution ratio, and an area adjustment identifier.

[0036] On the other hand, the steps of the load distribution adjustment configuration are specifically:

[0037] S501: based on the coupling offset performance quantity, optimizing the temperature parameter of the heat dissipation area of the surface discharge ozone device involving the area, analyzing the spatial distribution relationship between the temperature data of each node and the device heat dissipation area, adjusting the temperature distribution in the heat dissipation area, and obtaining a thermal control adjustment partition;

[0038] S502: based on the thermal control adjustment partition, adjusting the humidity of the electrode unit structure combination component, comparing the distribution before and after the humidity adjustment, judging the influence of the combination change of humidity and temperature on the discharge current density, and obtaining an energy flow characteristic factor;

[0039] S503: based on the energy flow characteristic factor, combining the ozone response data collected by the node, judging the influence of the temperature and humidity change of the area on the load distribution state of each node of the discharge device, optimizing the target area power distribution, and obtaining the load distribution adjustment configuration.

[0040] The technical scheme provided by the embodiment of the present application has at least the following beneficial effects:

[0041] By normalizing the temperature and humidity, electrical and ozone concentration data collected in the area, a data linkage mechanism with temperature and humidity change as the core is constructed, the node response performance is dynamically sorted, the periodic data change is fused, a control process for cooperatively adjusting temperature and humidity and electrical parameters is formed, the high correlation state of temperature and humidity deviation and ozone yield fluctuation of each node is actively captured, the partition load real-time adjustment and energy distribution dynamic optimization are realized, the agile response of ozone generation regulation and the multi-area difference matching ability are brought, the stability under the ozone yield fluctuation is improved, and the efficient operation and low consumption control under complex working conditions are promoted. BRIEF DESCRIPTION OF DRAWINGS

[0042] In order to more clearly illustrate the technical scheme in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0043] Figure 1is the main step flow chart of the present application;

[0044] Figure 2 is the step flow chart of S1 of the present application;

[0045] Figure 3 is the step flow chart of S2 of the present application;

[0046] Figure 4 is the step flow chart of S3 of the present application;

[0047] Figure 5 is the step flow chart of S4 of the present application;

[0048] Figure 6 is the step flow chart of S5 of the present application. DETAILED DESCRIPTION

[0049] The technical solutions in the present application will be described below with reference to the drawings.

[0050] In the embodiments of the present application, the words such as “exemplary”, “for example” are used to represent an example, illustration or description. Any embodiment or design scheme described as “exemplary” in the present application should not be interpreted as more preferred or more advantageous than other embodiments or design schemes. In fact, the word “exemplary” is intended to present the concept in a specific manner. In addition, in the embodiments of the present application, the meaning expressed by “and / or” can be both, or can be one of the two.

[0051] In the embodiments of the present application, “image” and “picture” can be used interchangeably at times. It should be pointed out that when the distinction is not emphasized, the meanings expressed are consistent. “Of”, “corresponding” and “corresponding” can be used interchangeably at times. It should be pointed out that when the distinction is not emphasized, the meanings expressed are consistent.

[0052] In the embodiments of the present application, sometimes the subscript such as W1 can be written in the form of non-subscript such as W1. When the distinction is not emphasized, the meanings expressed are consistent.

[0053] In order to make the technical problems, technical solutions and advantages to be solved by the present application more clear, the following will be described in detail with reference to the drawings and specific embodiments.

[0054] The embodiments of the present application provide a surface discharge ozone control optimization method, as shown in Figure 1 The method comprises the following steps:

[0055] S1: Based on the discharge device, analyze the temperature and humidity, power supply voltage and ozone concentration data collected in each region, adopt proportional transformation for the temperature and humidity data of each node, optimize the regulation scale of the temperature and humidity in each region, compare the optimized temperature and humidity data with the corresponding ozone concentration of the node, judge the linkage relationship of the temperature and humidity change in each region to ozone generation, calculate and summarize the trend change, and obtain the node trend characteristic factor;

[0056] S2: Based on the node trend characteristic factor, calculate the temperature and humidity change rate of each monitoring node, analyze the correlation between the temperature and humidity change trend and the ozone concentration response, screen the nodes with strong correlation between temperature and humidity change and ozone concentration yield, judge the influence of temperature and humidity of each node on ozone response, arrange them from high to low according to the correlation, select the nodes with high ranking, and obtain the response priority sequence;

[0057] S3: Based on the response priority sequence, compare the continuous changes of the electrode surface voltage, discharge current density and temperature and humidity in the region with high ranking, analyze the combined effect of temperature and humidity, current density and voltage on the change of ozone concentration, judge the influence of combined changes of temperature and humidity and electrical parameters on ozone response, identify the key nodes, and obtain the regulation effect distribution unit;

[0058] S4: Based on the regulation effect distribution unit, analyze the high-frequency voltage fluctuation data of each node, judge the change of voltage peak amplitude in the period, and analyze the humidity change by combining the node temperature data, compare the correlation between temperature and humidity fluctuation and voltage anomaly, identify the nodes with temperature and humidity coupling offset characteristics, and obtain the coupling offset performance quantity;

[0059] S5: Based on the coupling offset performance quantity, optimize the temperature parameters of the heat dissipation area of the ozone device of the surface discharge in the involved region, adjust the humidity of the electrode unit structure combination components, analyze the change of discharge current density, combine the ozone response of the node, judge the influence of temperature and humidity on the load distribution state, optimize the power distribution of the target region, and obtain the load distribution adjustment configuration.

[0060] The node trend characteristic factor includes trend intensity parameter, node correlation level, change direction type, the response priority sequence includes priority response level, response node number, hierarchical order identification, the regulation effect distribution unit includes regulation node group, distribution weight coefficient, action category type, the coupling offset performance quantity includes temperature and humidity offset amplitude, voltage fluctuation characteristics, coupling performance label, and the load distribution adjustment configuration includes load adjustment configuration, target distribution proportion, regional regulation identification.

[0061] In S1, the discharge device refers to the physical structure as a whole that performs the surface discharge reaction, usually including the electrode, insulator, shell and other components of the ozone generator, and its function is to provide controllable electrical energy input and reaction environment to make air or oxygen produce ozone under discharge conditions; the proportional conversion refers to normalizing, standardizing or scaling the temperature and humidity data collected by each monitoring node according to the same mathematical proportion standard, so as to eliminate the numerical baseline differences between different nodes and make the data comparable; the control scale refers to the range and amplitude used when adjusting temperature, humidity and other parameters, the purpose is to make the parameters of different regions reflect the control target and actual working condition changes under the unified standard; the node refers to the monitoring point set at different positions of the surface discharge device, each node can collect temperature, humidity, voltage, ozone concentration and other physical parameters in a specific area; the correlation comparison refers to the corresponding analysis of the optimized temperature and humidity data and the ozone concentration data of the same area or different nodes, through correlation analysis, trend comparison and other means, the influence of temperature and humidity changes on ozone generation is studied; the linkage relationship refers to the correlation response between temperature change, humidity change and ozone concentration change, for example, when temperature and humidity increase or decrease, the synchronous change trend of ozone generation, that is, the dynamic influence relationship between multiple parameters; the trend change refers to the change direction and amplitude of temperature, humidity and ozone concentration data within a certain monitoring period or sampling time, which is often described by statistical analysis (such as slope, growth rate, change rate, etc.).

[0062] In S2, the node with strong correlation refers to the monitoring point with high correlation coefficient between temperature and humidity change trend and ozone yield change, that is, the node whose temperature and humidity change has more sensitive influence on ozone production; the influence of temperature and humidity on ozone response refers to the degree and trend of ozone generation at a node when temperature or humidity parameters change, which is quantified by statistical and data analysis; the node in the front row refers to the node arranged from high to low according to the influence of temperature and humidity on ozone concentration after correlation calculation, that is, the node with the most significant influence, which is the area point that should be paid attention to and processed first.

[0063] In S3, the high-priority area is a number of monitoring areas (nodes) in the response priority sequence that exhibit the strongest correlation between temperature, humidity, and ozone response. The area usually has a higher value for regulation; the combined effect on ozone concentration change refers to the changes in ozone concentration under the combined action of temperature, humidity, current density, and electrode surface voltage, i.e., the combined effect of multiple parameters on ozone generation; the effect of temperature, humidity, current density, and electrode voltage on ozone response is caused by the changes in ozone generation rate and quantity, which is reflected by data analysis; the key nodes are monitoring points that can respond sharply or have a dominant effect on ozone generation under the combined changes of multiple parameters after combined action analysis, which are often the focus of subsequent regulation.

[0064] In S4, the change in voltage peak amplitude refers to the maximum and minimum fluctuation amplitude of the node voltage signal within a cycle during high-frequency monitoring, which reflects the electrical strength and the degree of change during the discharge process; the correlation of voltage abnormality refers to the correlation analysis of temperature or humidity change and voltage peak amplitude abnormality (such as abnormal increase or decrease) to determine whether temperature and humidity fluctuations are important factors affecting voltage abnormality; the temperature and humidity coupling deviation feature refers to the feature that the temperature and humidity change trends of some nodes are synchronized or cooperatively changed with the voltage fluctuation within a monitoring period, and deviate from the normal working condition state, which is used to identify abnormal nodes that need to be intervened.

[0065] In S5, the heat dissipation area of the surface discharge ozone device refers to the functional area for heat dissipation in the structure of the surface discharge ozone generator, and the temperature change of this area directly affects the stability of the discharge process and the ozone generation efficiency; the electrode unit structure combination component refers to the composite electrode assembly that bears the discharge and conduction functions in the discharge device, which can be indirectly regulated by temperature and humidity adjustment to regulate its surface state and discharge behavior; the change in discharge current density refers to the change of the current flowing through the unit area of the electrode surface over time, which is often used to represent the discharge intensity and energy distribution; the node ozone response refers to the response of ozone generation at each monitoring node under certain temperature, humidity, and electrical conditions, which is reflected by the change in sampling data; the effect on load distribution state refers to the effect of temperature and humidity parameter changes on the load distribution ratio and actual operation state of each area of the discharge device in the optimization and regulation process, which is used to realize energy distribution and efficiency adjustment.

[0066] As shown in Figure 2 , the steps of the node trend feature factor are as follows:

[0067] S101: Based on the discharge device, analyze the temperature data, humidity data, power supply voltage data, and ozone concentration data of each node, standardize the temperature and humidity raw data collected by each node, combine them in node order, and compare the data under the same standard to obtain a unified parameter baseline group;

[0068] The original temperature, humidity, power supply voltage and ozone concentration values collected by each node are read in sequence. For temperature data, the maximum and minimum temperature values of all nodes are extracted, and the difference between the original temperature of the node and the boundary value is recorded. Then, the difference is normalized according to the temperature difference between the maximum and minimum values to form a temperature standard value. Humidity data is normalized in the same way. After completion, the temperature standard value and humidity standard value of each node are combined into a group of parameter data. The data of all nodes are combined into a standardized data set in a unified format according to the arrangement order of the node number. In actual application, for example, node 1 collects temperature of 42.6 and humidity of 55%, node 2 collects temperature of 38.0 and humidity of 47%, the maximum temperature is 48.5, the minimum temperature is 36.0, the maximum humidity is 60%, and the minimum humidity is 40%. After standardization, the corresponding values of node 1 and node 2 are adjusted to dimensionless values between 0 and 1. Then, the value difference between the standardized data of each node is compared group by group. The difference is directly compared, and the adjacent nodes with a temperature and humidity difference within a certain range are marked as data consistent nodes. The upper limit of the tolerance difference is set to 0.5. If the difference of a node pair in two dimensions is less than the upper limit, it is considered to have similar data performance. On this basis, all nodes that meet the conditions are extracted to form a unified parameter baseline group, which is used as a reference for the consistency of temperature and humidity between nodes.

[0069] S102: Based on the unified parameter baseline group, compare the ozone concentration change data of each node, and establish the corresponding relationship of temperature, humidity and ozone concentration data according to the node number. Judge the consistency of the change direction of temperature and humidity and the change direction of ozone concentration in the difference period, calculate the number of synchronous changes, and obtain the linkage trend characteristic quantity;

[0070] For each node, the ozone concentration data on the continuous time sequence of the node are extracted and corresponded with the standardized temperature and humidity data of the node. The temperature change direction, humidity change direction and ozone concentration change direction in each time period are compared synchronously. The value difference between each two consecutive time points is calculated to judge whether the change trend of each parameter is rising or falling. If the three change directions are consistent, it is recorded as a linkage synchronous event. Otherwise, it is ignored. In the whole period, for example, sampling once per minute, observing for 60 minutes, a total of 60 groups of time data, if 24 times of three consistent directions occur in a node, the linkage frequency is 40%. The frequency is compared with the set threshold value, and the set judgment standard is 35%. Nodes with frequency equal to or higher than 35% are marked as trend linkage nodes. The total linkage number and total sampling number of the node are recorded. The frequency results and linkage of all nodes are summarized according to the number to form a linkage trend characteristic quantity set.

[0071] S103: Based on the linkage trend characteristic quantity, nodes with consistent direction of temperature, humidity and ozone concentration are screened, the frequency and fluctuation amplitude of synchronous change in each group of nodes are analyzed, the nodes are grouped according to node number, and node trend characteristic factor is obtained;

[0072] Nodes with frequency greater than or equal to 35% are screened into the analysis range, the temperature change value, humidity change value and corresponding ozone concentration change value of each linkage event in the node are extracted one by one, the fluctuation amplitude of each event is recorded, the average value of the fluctuation amplitude in the historical record of each node is calculated to reflect the strength of the fluctuation characteristics of the node in the linkage event. In actual sampling, for example, a node identifies 12 consistent direction events, respectively records the temperature change between 0.5 and 1.8, the humidity change between 2% RH and 6% RH, and the ozone concentration change between 4 ppb and 9 ppb. Finally, the average temperature, humidity and ozone concentration fluctuation values of each node are sorted according to the node number, and the linkage direction of the node is analyzed. If the number of positive changes is 8 and the number of negative changes is 4, the change direction of the node is positive, and the node number, frequency value, fluctuation amplitude and change direction are combined to form the node trend characteristic factor. The output is three fields of trend strength parameter, node number and change direction type, which are used for subsequent response priority sequence generation analysis.

[0073] As shown in Figure 3 , the steps of the response priority sequence are as follows:

[0074] S201: Based on the node trend characteristic factor, the change rate of temperature and humidity of each monitoring node in the continuous sampling period is calculated, the change direction of temperature and humidity value between adjacent time periods is judged, the amplitude of temperature change and humidity change in the same period is compared, and the change amplitude interval is obtained.

[0075] The temperature and humidity values of each node in the continuous sampling period are extracted, and the corresponding temperature values are read from the adjacent two time points in the time sequence order and the difference is calculated, and then divided by the time interval between the two sampling points to obtain the temperature change rate of the node in the time period. Similarly, the humidity data of the previous and next two time points are read and processed to obtain the humidity change rate. The operation is continuously performed in each node to form a set of time sequence temperature and humidity change rate lists. Under the condition that the sampling frequency is once per minute, for example, the temperature of node A at 10:00 is 42.0, and at 10:01 is 42.7, the temperature change rate is 0.7 / minute, and the humidity changes from 55.1% to 53.9% in the same time period, and the humidity change rate is-1.2% / minute. Then, it is judged that the temperature change direction between each pair of time points is rising, falling or no change. The temperature rate greater than 0 is marked as rising, less than 0 is marked as falling, and equal to 0 is marked as no change. Similarly, the humidity change direction is processed. After judging the direction, the change amplitude of temperature and humidity in each sampling period is compared, and the absolute difference is calculated. In the above example, the temperature change amplitude is 0.7, the humidity change amplitude is 1.2, and the difference between the two is 0.5. By setting the amplitude threshold interval, the change amplitude is divided into small (01), medium (12) and large (greater than 2) respectively. A set of structure-unified amplitude interval markers is formed in the multiple node data, which is used as a reference dimension of the temperature and humidity change intensity in the subsequent analysis to obtain the change amplitude interval.

[0076] S202: Based on the change amplitude interval, the synchronization between the temperature and humidity change trend and the ozone concentration change is analyzed, and according to the consistency of the change direction of the temperature and humidity and the ozone concentration of each node, the appearance frequency of the synchronous direction is counted to obtain the trend coupling performance degree.

[0077] Extract the temperature and humidity change trend of each node and the ozone concentration change value of the node in the same time period one by one, judge whether the change direction of the three parameters in the same sampling period is consistent, first judge the trend as common rising, common falling or opposite trend according to the change direction of temperature and humidity, then compare the ozone concentration change trend with it, for example, the temperature of a node rises 0.6, the humidity falls 1.3%, and the ozone concentration falls 2.1 ppb during 10:15-10:16, at this time the temperature and humidity are in opposite directions, but the ozone and humidity are both falling, and the temperature is opposite to them, not counted as synchronization; if the temperature rises 0.5, the humidity rises 1.2%, and the ozone concentration rises 4.4 ppb, then the three directions are consistent, and it is counted as a synchronous trend event, judge and count in each time period, count the total number of synchronous trend events on each node, and record the total number of sampling periods, calculate the trend synchronization frequency of the node by dividing the number of synchronizations by the total number of samples, for example, if a node appears 22 times of consistent change direction of the three in 60 samples, its trend synchronization frequency is 36.7%, and the frequency value exceeds the threshold of 35%, which is judged as a synchronous performance node, by counting the trend synchronization frequency of all nodes, a node synchronization frequency list is constructed, which marks the node number, synchronization number, total sampling number and synchronization frequency value in the list, and sets the coupling strength grade grading rules, for example, frequency below 30% is marked as low coupling, 30%-50% is medium coupling, and more than 50% is high coupling, forming a trend coupling performance degree set with grade label.

[0078] S203: Based on the trend coupling performance degree, filter the nodes with high frequency of synchronization direction performance, sort the nodes according to the coupling performance of each node and the change of ozone concentration from the frequency and amplitude of synchronization performance, and get a response priority sequence;

[0079] The frequency levels of all nodes are graded and screened, first, the node data with a frequency lower than 30% is removed, only the part with a frequency greater than or equal to 30% is reserved as a candidate set for response ranking, in the candidate node set, the trend synchronization frequency of each node and the change amplitude of ozone concentration in each synchronization event are extracted, the average of the ozone fluctuation values of all synchronization events in each node is taken as the amplitude reference basis, for example, node B has 20 synchronization events, the ozone concentration change amplitude is recorded between 3.2 ppb and 9.1 ppb, the average amplitude is 6.4 ppb, the frequency and amplitude are sorted as two dimensions, first, the synchronization frequency is arranged from high to low, the average ozone change amplitude is sorted again from high to low under the same frequency, the frequency sorting priority weight is set to 70%, the amplitude sorting weight is set to 30%, the nodes are scored and sorted by linear weighting, in this process, the synchronization frequency sorting benchmark is set to the maximum and minimum value range of the node, which is divided into five grades, the amplitude is the same, finally, the nodes are sorted and numbered according to the total score value, the node number, synchronization frequency, average ozone change amplitude, score value are output, the response priority sequence is obtained, which is used for node ranking reference when regulating resource allocation.

[0080] As shown in Figure 4 The step of regulating the distribution of the unit is specifically:

[0081] S301: Based on the response priority sequence, analyze the continuous changes of the electrode surface voltage, discharge current density and temperature and humidity of the nodes with high ranking, compare the synchronization fluctuations of each data of each node in the sampling period, judge the consistency of the fluctuation directions of each parameter, and obtain the multi-parameter change data;

[0082] According to the node ranking result, the electrode surface voltage data, the discharge current density data and the normalized temperature and humidity data in the sampling period of the node are extracted one by one, and the time sequence records of the four parameters are established in each node. Each sampling point is numbered for subsequent cycle-by-cycle comparison. In the voltage data processing, the voltage values of adjacent time points are read and the direction of voltage change is obtained. If the voltage at the next time is higher than that at the previous time, it is marked as rising, otherwise as falling. The same rule is used to determine the change direction of the current density, and the temperature and humidity data are also processed in the same way. Then, in each sampling period, it is judged whether the change directions of the four parameters are consistent. If all four parameters are rising or falling, it is marked as a full parameter synchronous event. If only three parameters are consistent, it is considered as a partial synchronous event. For example, in a sampling period, the voltage rises from 6.1kV to 6.3kV, the current density rises from 1.25mA / cm² to 1.31mA / cm², the temperature rises from 43.5 to 44.1, and the humidity drops from 48% to 46%. Since the humidity direction is opposite, this period is recorded as a three-parameter partial synchronous event. The number of four-parameter full synchronization, three-parameter partial synchronization, and double-parameter or below synchronization in the whole cycle is counted for each node. At the same time, the range of parameter change is recorded and classified, for example, the voltage change amplitude within ±0.1kV is defined as small fluctuation, 0.8 as medium fluctuation, and more than 0.8 as large fluctuation. The fluctuation level of each data is encoded and archived to obtain the multi-parameter change data.

[0083] S302: Based on the multi-parameter change data, the relationship between the combined fluctuation of voltage, density and temperature and humidity and the response of ozone concentration is analyzed, the number of synchronous occurrence of ozone concentration change when the parameters are linked is counted, the influence of combined change on ozone response is analyzed, and the linkage influence index is obtained.

[0084] The marked full synchronization events and partial synchronization events in each node cycle are extracted and compared with the ozone concentration data in the same cycle. In each cycle where the four parameters fluctuate consistently, the corresponding ozone concentration value change is read to determine whether it has changed synchronously compared with the previous cycle. If the voltage, current density, temperature and humidity rise simultaneously and the ozone concentration also rises, it is marked as a synchronous response event. If the parameters decrease and the ozone also decreases, it is also counted as a synchronous response event. If the ozone change direction is inconsistent with the above parameter direction, it is not recorded. The total number of synchronous responses of each node in all sampling cycles is counted to calculate the ozone response synchronization frequency of the node. For example, node 5 records 18 full parameter synchronization events in 60 sampling cycles, of which 12 are accompanied by synchronous fluctuation of ozone concentration, so the linkage synchronization response frequency is 66.7%. The change amplitude of the ozone concentration in the 12 events is recorded to calculate the average value to evaluate the response strength. For example, the concentration change range in the event is 5ppb to 11ppb, and the average change amplitude is 7.3ppb. The data set of linkage event number and average response amplitude is established at each node, and the interval division standard of synchronization response frequency is set. The frequency below 30% is weak linkage, the frequency between 30% and 60% is medium linkage, and the frequency above 60% is strong linkage. The linkage level, synchronization frequency and average response amplitude of each node are used as evaluation dimensions to form a linkage influence index set.

[0085] S303: Based on the linkage influence index, nodes with high trend direction synchronization rate are screened to judge the corresponding relationship between the coordinated fluctuation of each node and the ozone response performance, identify the key nodes, and obtain the regulation effect distribution unit.

[0086] The corresponding relationship between the coordinated fluctuation of each node and the ozone response performance is judged, and the formula is:

[0087] ;

[0088] The coordinated response offset value is calculated to identify the key nodes and obtain the regulation effect distribution unit, wherein, represents the coordinated response offset value of node , represents the temperature change of node at time , that is, the actual change amount divided by the difference between the maximum and minimum temperature in the monitoring cycle of the node, represents the humidity change of node at time , that is, the actual change amount divided by the difference between the maximum and minimum humidity in the monitoring cycle of the node, represents the temperature change of node at time the actual change amount divided by the difference between the maximum and minimum ozone concentration in the monitoring period of the node, representing the total number of times in the calculation period;

[0089] The cooperative response offset value refers to the overall difference and linkage between the normalized change trend of the temperature and humidity of a node and the normalized change of the ozone concentration of the same node in the monitoring period, which is used to measure the synchronization and offset of the multi-parameter (temperature, humidity, and ozone response) of the node in the dynamic process, which can help analyze and distinguish the cooperative relationship and response characteristics of different monitoring nodes under the change of multi-parameters, and facilitate the screening and identification of nodes that perform key, need to be focused on or regulated under the linkage of multi-parameters.

[0090] Selecting a node As an example, in the observation period (h), the temperature values collected by the node are 26.2, 26.8, 27.5, 28.0, 27.3, and 26.9°C, the humidity values are 45, 47, 49, 52, 50, and 46% RH, and the ozone concentration values are 0.038, 0.041, 0.045, 0.044, 0.043, and 0.040 mg / m 3 After obtaining the change amount per hour, it is normalized to obtain the normalized change values from the 2nd hour to the 6th hour as follows:

[0091] , , , , ;

[0092] The corresponding humidity normalized change values are:

[0093] , , , , ;

[0094] The corresponding ozone concentration normalized change values are:

[0095] , , , , ;

[0096] Substituting the above values into the formula:

[0097] ;

[0098] The results in the brackets at each time are calculated in turn:

[0099] 2nd hour:

[0100] ;

[0101] 3rd hour:

[0102] ;

[0103] 4th hour:

[0104] ;

[0105] 5th hour:

[0106] ;

[0107] 6th hour:

[0108] ;

[0109] Summing up the above results:

[0110] ;

[0111] Substituting into the formula:

[0112] ;

[0113] The denominator term represents the average value taken over the 5 observation intervals from time points 2 to 6. This structure places each parameter on the same scale and enables uniform summation operations, ensuring the overall calculation logic is feasible and consistent. The numerical result 0.0496 obtained is a quantitative reflection of the degree of multi-parameter coordinated deviation for the node in the current period. If this result is below the preset deviation threshold of 0.1, it can be determined that the node has a more consistent coordinated trend. The formula uses a structure that normalizes temperature, humidity, and ozone concentration and then combines addition and subtraction to obtain the average value. This structure enables the heterogeneous data from multiple sources that cannot be directly added or subtracted to be uniformly quantified without relying on algorithm models, making the results have continuous comparability and the ability to sort between nodes, thereby supporting the subsequent judgment and selection process of the regulation distribution unit.

[0114] As shown in Figure 5 , the step of coupling the deviation performance quantity is specifically:

[0115] S401: Based on the regulation distribution unit, analyze the high-frequency voltage data collected by the node in the continuous period, judge the peak and valley changes of voltage fluctuation in each period, compare the fluctuation amplitude and change trend between periods, and count the direction and distribution of voltage fluctuation of each node to obtain a fluctuation interval characteristic set;

[0116] The high-frequency voltage raw data of each node in the distribution unit within a continuous sampling period is extracted, the data sequence of all voltage sampling points within each period is read, the maximum and minimum values of the voltage within the period are identified and labeled as peak and valley values respectively, the difference between the peak and valley values is calculated to obtain the voltage fluctuation amplitude within the period, and the position difference of the maximum and minimum points within the period is recorded to determine the periodic trend of the fluctuation. The above processing procedure is repeated in a plurality of continuous periods to form a fluctuation amplitude sequence of each node in a plurality of periods. Then, the fluctuation amplitudes between periods are compared, and the difference between the fluctuation values of two adjacent periods is calculated. When the difference is positive, it indicates that the fluctuation is enhanced, when the difference is negative, it indicates that the fluctuation is weakened, and when the difference is zero, it indicates that the fluctuation trend is flat. For example, the peak-valley difference of a certain node in three consecutive periods is 0.8kV, 1.2kV and 0.9kV respectively, the fluctuation is enhanced from period 1 to period 2, and the fluctuation is weakened from period 2 to period 3. The number of times of fluctuation enhancement, weakening and flatness of each node in all periods is further counted and recorded in percentage form. In terms of voltage fluctuation amplitude, the range standard is set as follows: the fluctuation amplitude less than 0.5kV is marked as "low range", the fluctuation amplitude from 0.5kV to 1.0kV is marked as "medium range", and the fluctuation amplitude higher than 1.0kV is marked as "high range". According to the above rules, the fluctuation amplitude in each period is classified into the range type, and the fluctuation amplitude range list is formed with the node number as the index. Then, the periodic voltage fluctuation of each node is represented by structured data in combination with the fluctuation trend statistical data to form the fluctuation range characteristic set.

[0117] S402: According to the fluctuation range characteristic set, the change direction of the node temperature and humidity data is compared to analyze whether the temperature and humidity change within the same period is consistent with the voltage fluctuation, judge the fluctuation synchronization phenomenon of the parameters, and count the synchronized change paragraphs to obtain the synchronized response distribution quantity.

[0118] The direction and amplitude interval of voltage fluctuation of each node are compared cycle by cycle, the temperature and humidity data collected in the corresponding cycle are extracted, the change direction of temperature and humidity is calculated respectively, in each cycle, it is judged whether the temperature and humidity value is rising, falling or flat compared with the previous cycle, and the change direction is encoded and processed respectively, temperature rising is set to 1, falling is set to-1, flat is set to 0, and humidity is also processed in the same way. Then the change direction of temperature and humidity is compared with the direction of voltage fluctuation, if the voltage fluctuation is enhanced and the temperature and humidity rise, it is a full synchronization rising segment, if the voltage fluctuation is weakened and the temperature and humidity fall, it is a full synchronization falling segment, and the rest is a non-synchronization segment or a partial synchronization segment. After defining each synchronization type, the number of synchronization cycles of each node in all cycles is counted, and the synchronization cycle ratio is calculated by dividing the total number of synchronization cycles by the total number of sampling cycles. For example, node C has 18 full synchronization segments and 10 partial synchronization segments in 50 cycles, so the full synchronization ratio is 36% and the partial synchronization ratio is 20%. On this basis, the response judgment benchmark is set as follows: the full synchronization segment ratio exceeds 30% for medium synchronization response, exceeds 50% for strong synchronization response, and the synchronization segment number is less than 15% for weak response node. At the same time, auxiliary judgment is performed in combination with fluctuation amplitude interval and temperature and humidity change amplitude, for example, the node whose synchronization cycle number exceeds 10 times when the voltage fluctuation is in the "high interval" and the temperature fluctuation is greater than 1 and the humidity change amplitude exceeds 3% RH is identified as a high coupling strong synchronization point. The synchronization response distribution of each node is sorted and counted, and the synchronization response distribution quantity composed of synchronization cycle number, synchronization type ratio and maximum synchronization segment amplitude data is generated.

[0119] S403: According to the synchronization response distribution quantity, the offset trend of the combination of node temperature and humidity fluctuation and voltage change is judged, the node number and synchronization performance characteristics are sorted, the offset interval and temperature and humidity change relationship are analyzed, and the coupling offset performance quantity is obtained;

[0120] The relationship between the offset interval and the temperature and humidity change is analyzed, and the formula is as follows:

[0121] ;

[0122] The coupling offset performance quantity is obtained, wherein, represents the temperature and humidity voltage coupling offset performance quantity of the i-th node, represents the sampling number of the i-th node in the statistical cycle, represents the temperature data of the i-th node in the statistical cycle, represents the temperature average data of the i-th node in the statistical cycle, represents the temperature data of the i-th node in the statistical cycle, represents the temperature data of the i-th node in the statistical cycle, represents the temperature data of the i-th node in the statistical cycle, represents the temperature data of the i-th node in the statistical cycle, represents the temperature data of the i-th node in the statistical cycle, represents the temperature data of the i-th node in the statistical cycle, represents the temperature data of the i-th node in the statistical cycle, the humidity data of the node k in the monitoring period, representing the average data of the node k in the statistical period, the average data of the humidity of the node k in the statistical period, representing the average data of the node k in the statistical period, the average data of the voltage of the node k in the statistical period, representing the average data of the node k in the statistical period, the average data of the voltage of the node k in the statistical period;

[0123] The coupling offset performance refers to the synchronous fluctuation combination characteristics between the temperature, humidity and voltage data of the node k in the monitoring period and the average data of each period, and the weighted sum after absolute value processing, which reflects the comprehensive performance of the temperature and humidity changes and voltage changes of the node k in the same period deviating from the average level, and belongs to the quantitative data reflecting the amplitude and direction of the joint changes of multiple parameters.

[0124] Extract each monitoring node identified as having a synchronous offset trend, and perform classification processing on the 5 sampling data of the temperature, humidity and voltage of each node in the set statistical period. Taking node k as an example, the corresponding temperature original data is 31.2, 32.0, 30.8, 31.5, 31.7, the humidity original data is 48.3, 49.1, 47.6, 48.8, 48.5, and the voltage original data is 212.5, 213.2, 211.9, 212.8, 213.0. First, the above original temperature, humidity and voltage data are dimensionally unified by normalization method to obtain the normalized 0.44, 0.71, 0.33, 0.56, 0.61;

[0126] 0.47, 0.74, 0.36, 0.63, 0.56;

[0128] 0.39, 0.72, 0.22, 0.56, 0.67;

[0130] The corresponding average values are:

[0131] , , ;

[0132] According to the formula, each group of data from to is unfolded in turn and calculated as follows:

[0133] The first group is:​​​​​

[0134] ;

[0135] Take the absolute value as 0.05.

[0136] Group 2 is:

[0137] ;

[0138] Take the absolute value as 0.16.

[0139] Group 3 is:

[0140] ;

[0141] Take the absolute value as 0.1.

[0142] Group 4 is:

[0143] ;

[0144] Take the absolute value as 0.06.

[0145] Group 5 is:

[0146] ;

[0147] Take the absolute value as 0.07.

[0148] Sum and average the above 5 sets of data to get:

[0149] ;

[0150] This result indicates that the first The coupling offset performance value obtained by the node after normalizing the temperature, humidity, and electrical data and performing a combined difference assessment within the current monitoring period is 0.088. Combined with the offset classification criteria, if the following is set... If the offset is slight, the node is classified as a type of response-coupled node and will be uniformly labeled in the node number set. Simultaneously, the temperature and humidity fluctuation trends within its sampling period are compared. If they are synchronized with the voltage fluctuation direction, the node is included in the synchronous covariance group and classified under positive coupling characteristics, thus completing the identification and organization of the corresponding coupling offset performance. The formula constructs a combined model of temperature, humidity, and voltage difference, simultaneously considering the average differences of the three parameters. The three terms in parentheses correspond to the degree of parameter deviation. Absolute value processing is then used to eliminate offset direction interference. After summing and normalization, the comprehensive coupling offset strength of the node's physical field parameters under different sampling periods can be obtained. Indicates the first All nodes The systemically statistical coverage of group sampling, the addition item in the operation structure reflects the trend of common enhancement or weakening of temperature and humidity, the subtraction item is used to strip the voltage disturbance component, and finally the average normalization process of division forms a unified scale of offset performance results.

[0151] As shown in Figure 6 , the steps of load distribution adjustment configuration are as follows:

[0152] S501: Based on the coupling offset performance quantity, optimize the temperature parameters of the heat dissipation area of the regional surface discharge ozone device, analyze the spatial distribution relationship between the node temperature data and the device heat dissipation area, adjust the temperature distribution in the heat dissipation area, and obtain the heat control adjustment partition;

[0153] Extract the node temperature change data and its corresponding electrical fluctuation performance label, read the physical structure coordinate parameters of the heat dissipation area in the surface discharge ozone device, determine the distribution position of each node in space relative to the heat dissipation structure, and on this basis, map the node temperature measurement value to the two-dimensional plane diagram of the heat dissipation structure according to the spatial coordinates, form a thermal field distribution diagram according to the difference of the measured temperature value, and count the number of nodes and the area of the hot spot area in the heat dissipation area whose temperature is higher than 45, and judge it as a hot spot area. The area below 38 is the cold spot area, and the intermediate range is the transition area. According to the above temperature interval standard, the partition is set, the influence of the temperature of the area on the stability of the ozone generation electric parameters is comprehensively evaluated through the spatial overlap degree and the node density of the heat area, for example, if the hot spot area covers 5 high coupling nodes, and the ozone concentration abnormal fluctuation appears in 5 continuous periods, it is confirmed that the area is the key control area, then adjust the heat dissipation unit, such as increasing the air duct speed or changing the fan speed, monitor the temperature redistribution after adjustment, if the hot spot area decreases by more than 30%, and the node temperature is stable in the range of 40±1 within 3 periods, it is confirmed that the adjustment is effective, and the area is marked as a heat control adjustment partition, forming a standardized heat control adjustment partition configuration.

[0154] S502: Based on the heat control adjustment partition, adjust the humidity of the electrode unit structure combination component, combine the humidity change characteristics of each electrode structure in the environment, compare the distribution before and after the humidity adjustment, judge the influence of the combination change of humidity and temperature on the discharge current density, and obtain the energy flow characteristic factor;

[0155] Each electrode structure combination unit in the adjustment area is identified in sequence, the corresponding humidity measurement data of the environment where it is located is extracted, it is classified into edge area, middle area and heat dissipation concentrated area according to the position where the structure is located, the change range and the intra-day fluctuation frequency of humidity in each type of area are recorded, the output rate of the humidity adjustment device and the working period of the humidifying or dehumidifying device are controlled according to the adjustment target, for example, if the humidity in the edge area is lower than 40% for a long time, the target is adjusted to 45%-50% interval, the working time of the device is adjusted from 5 minutes to 7 minutes, the humidification is controlled, the stable value of the humidity after adjustment is recorded and compared with the fluctuation range before and after adjustment, if the fluctuation is converged from ±6% to ±3%, it is considered that the humidity adjustment is effective, on this basis, the discharge current density change is monitored, the change direction of the current value per unit area of the electrode and the change direction of the humidity are counted, if the current density increases after the humidity rises, it is considered that the coupling is positive, if it decreases, it is considered that the coupling is negative, the average value change amplitude of the current density before and after the adjustment of each electrode structure is calculated and analyzed in combination with the change direction of the humidity, for example, if the humidity of a certain structure rises by 3.5% and the current density increases by 0.18 mA / cm², it is classified as a high response coupling point, the humidity change amount, the current density change amount and the change direction are arranged according to the node number, and the energy flow characteristic factor is generated.

[0156] S503: Based on the energy flow characteristic factor, the influence of the change of the temperature and humidity of the region on the load distribution state of each node of the discharge device is judged in combination with the ozone response data collected by the node, the power distribution of the target region is optimized, and a load distribution adjustment configuration is obtained.

[0157] First, the current density variation of each electrode structure unit under the change of humidity and temperature is corresponded with the ozone response data of the node where the electrode structure unit is located, the ozone concentration values of each node under different environmental combination states are extracted, the synchronous situation of the node response intensity and the temperature and humidity change is judged, if the temperature is reduced by 2 and the humidity is increased by 4% after adjustment, the corresponding ozone concentration of the node is increased from 102ppb to 116ppb, then a positive enhancement response event is recorded, the number of such events is accumulated and counted for all nodes, the ozone response corresponding to different adjustment combinations is classified, the total response intensity of each node is quantitatively scored, and the influence matrix is established according to each group of temperature and humidity combination and the ozone concentration change amplitude brought by the temperature and humidity combination, on this basis, the load distribution state is analyzed, the total amount of electric power required by each node before and after adjustment is compared, the power consumption corresponding to the unit ozone generation is calculated, if the unit ozone power consumption of a certain area is reduced by more than 15% after temperature and humidity adjustment, it is determined that the load adjustment is effective, all the adjustment regions with the optimal power response are screened out, the power distribution proportion of each region is counted, and the power supply strategy is adjusted, for example, the original power proportion of a region is adjusted from 25% to 32%, and the power proportion of three regions is adjusted from 30% to 24%, to form a load distribution adjustment configuration containing the region number, the power ratio before and after adjustment, the temperature and humidity combination state and the unit power consumption of the generated capacity.

[0158] It should be understood that the term "and / or" herein merely describes an association relationship of associated objects, and indicates that there can be three relationships, for example, A and / or B can represent three cases of A existing alone, A and B existing together, and B existing alone, wherein A and B can be singular or plural. In addition, the character " / " herein generally represents an "or" relationship between the front and rear associated objects, but can also represent an "and / or" relationship, which can be understood according to the context before and after.

[0159] In the present application, "at least one" means one or more, and "a plurality of" means two or more. "At least one of the following" or the like means any combination of the items, including any combination of single item or multiple items. For example, at least one of a, b, or c can represent a, b, c, a-b, a-c, b-c, or a-b-c, wherein a, b, and c can be single or multiple.

[0160] It should be understood that in various embodiments of the present application, the size of the sequence number of the above processes does not mean the order of execution, and the execution order of the processes should be determined according to their functions and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0161] Those skilled in the art can clearly understand that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0162] Those skilled in the art can clearly understand that, for the convenience and brevity of the description, the specific working processes of the devices, apparatuses and units described above can refer to the corresponding processes in the foregoing method embodiments, which will not be repeated here.

[0163] In several embodiments provided by the present application, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely schematic, for example, the division of the units is only a logical function division, and actual implementation can have another division manner, for example, multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0164] The units described as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, that is, they can be located in one place, or can be distributed on multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment scheme.

[0165] In addition, each functional unit in each embodiment of the present application can be integrated into a processing unit, or each unit can exist physically independently, or two or more units can be integrated into one unit.

[0166] If the functions are realized in the form of software function units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application or the parts of the present application that essentially contribute to the prior art or the parts of the technical solutions can be embodied in the form of software products. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in the various embodiments of the present application. The aforementioned storage medium includes a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0167] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical range disclosed by the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for optimizing surface discharge ozone control, comprising: The method comprises: S1: based on the discharge device, collecting the temperature and humidity, voltage and ozone concentration data of each region, performing proportional standardization on the temperature and humidity, correlating the optimization parameters and the ozone concentration, summarizing the trend changes of each region, and obtaining the node trend characteristic factor; S2: based on the node trend characteristic factor, calculating the temperature and humidity change rate of each monitoring point, analyzing the correlation degree between the temperature and humidity change rate and the ozone concentration, screening high correlation nodes, judging the influence strength and performing priority sorting, and obtaining a response priority sequence; S3: based on the response priority sequence, comparing the electrode voltage, discharge current density and temperature and humidity data of the region with high priority, analyzing the ozone change characteristics under the linkage of multiple parameters, identifying the key nodes, and obtaining a regulation distribution unit; S4: based on the regulation distribution unit, analyzing the high-frequency voltage fluctuation of the node, judging the voltage peak amplitude change, combining the temperature and humidity change of the node, comparing the correlation between the temperature and humidity change and the voltage anomaly, identifying the coupling deviation characteristics, and obtaining a coupling deviation performance quantity; S5: based on the coupling deviation performance quantity, optimizing the temperature of the heat dissipation area and the humidity of the electrode structure in the correlation region, combining the current density and ozone response, analyzing the influence of temperature and humidity on load distribution, adjusting the target power, and obtaining a load distribution adjustment configuration. The load distribution adjustment configuration comprises a load adjustment configuration, a target distribution ratio and a region adjustment identifier.

2. The method of claim 1, wherein the surface discharge ozone control optimization method is characterized by, The node trend characteristic factor comprises a trend strength parameter, a node correlation level and a change direction type, the response priority sequence comprises a priority response level, a response node number and a hierarchical sorting identifier, the regulation distribution unit comprises a regulation node group, a distribution weight coefficient and an action category type, and the coupling deviation performance quantity comprises a temperature and humidity deviation amplitude, a voltage fluctuation characteristic and a coupling performance label.

3. The method of claim 1, wherein the method further comprises: The step of the node trend characteristic factor is specifically: S101: based on the discharge device, analyzing the temperature data, humidity data, power supply voltage data and ozone concentration data of each node, standardizing the temperature and humidity raw data collected by each node, combining the data in node order, comparing the data under the same standard, and obtaining a unified parameter baseline group; S102: based on the unified parameter baseline group, comparing the ozone concentration change data of each node, establishing the correspondence between the temperature and humidity and the ozone concentration data by node number, judging the consistency of the temperature and humidity change direction and the ozone concentration change direction in the difference period, calculating the number of synchronous changes, and obtaining a linkage trend characteristic quantity; S103: based on the linkage trend characteristic quantity, screening the nodes with consistent temperature and humidity and ozone concentration directions, analyzing the frequency and fluctuation amplitude of synchronous changes in each group of nodes, grouping by node number, and obtaining a node trend characteristic factor.

4. The method of claim 1, wherein the surface discharge ozone control optimization method is characterized by, The step of the response priority sequence is specifically: S201: based on the node trend characteristic factor, calculating the temperature and humidity change rate of each monitoring node in a continuous sampling period, judging the change direction of the temperature and humidity value between adjacent time periods, comparing the amplitude of temperature change and humidity change in the same period, and obtaining a change amplitude interval; S202: Based on the change amplitude interval, the synchronization between the temperature and humidity change trend and the ozone concentration change is analyzed, the occurrence frequency of the synchronization direction is counted according to the consistency of the temperature and humidity of each node and the change direction of the ozone concentration, and the trend coupling performance degree is obtained. S203: Based on the trend coupling performance degree, the nodes with high frequency of synchronization performance are screened out, and the response priority sequence is obtained by sorting the coupling performance of each node with the change of the ozone concentration from the frequency and amplitude of the synchronization performance.

5. The method of claim 1, wherein the method further comprises: The step of the regulation distribution unit is specifically: S301: Based on the response priority sequence, the continuous change of the electrode surface voltage, discharge current density and temperature and humidity of the nodes ranked in the front is analyzed, the synchronization fluctuation of each data of each node in the sampling period is compared, the consistency of the fluctuation direction of each parameter is judged, and the multi-parameter change data is obtained. S302: Based on the multi-parameter change data, the relationship between the joint fluctuation of voltage, density and temperature and humidity and the response of ozone concentration is analyzed, the synchronization occurrence times of ozone concentration change when the parameters are linked are counted, the influence of joint change on ozone response is analyzed, and the linkage influence index is obtained. S303: Based on the linkage influence index, the nodes with high synchronization rate of trend direction performance are screened out, the corresponding relationship between the coordinated fluctuation of each node and the ozone response performance is judged, the key nodes are identified, and the regulation distribution unit is obtained.

6. The method of surface discharge ozone control optimization of claim 5, wherein, The corresponding relationship between the coordinated fluctuation of each node and the ozone response performance is judged by using the formula: ； The cooperative response offset value is calculated, key nodes are identified, and a regulation effect distribution unit is obtained, wherein, representative nodes of the cooperative response offset value, representative nodes of the temperature change at time , that is, the actual change amount divided by the difference between the maximum and minimum values of the temperature in the node monitoring period, representative nodes of the humidity change at time , that is, the actual change amount divided by the difference between the maximum and minimum values of the humidity in the node monitoring period, representative nodes of the ozone concentration change at time , that is, the actual change amount divided by the difference between the maximum and minimum values of the ozone concentration in the node monitoring period, representative nodes represent the total number of times in the calculation period.

7. The method of claim 1, wherein the method further comprises: The step of the coupling offset performance quantity is specifically: S401: Based on the regulation distribution unit, the high-frequency voltage data collected by the node in the continuous period is analyzed, the peak and valley change of voltage fluctuation in each period is judged, the fluctuation amplitude and change trend between periods are compared, the direction and distribution of voltage fluctuation of each node are counted, and the fluctuation interval characteristic set is obtained. S402: According to the fluctuation interval characteristic set, the change direction of node temperature and humidity data is compared, whether the temperature and humidity change in the same period is consistent with the voltage fluctuation is analyzed, the fluctuation synchronization phenomenon of the parameters is judged, and the synchronization response distribution quantity is obtained. S403: According to the synchronization response distribution quantity, the offset trend of the combination of node temperature and humidity fluctuation and voltage change is judged, the node number and synchronization performance characteristics are sorted out, the relationship between the offset interval and temperature and humidity change is analyzed, and the coupling offset performance quantity is obtained.

8. The method of claim 7, wherein the method further comprises: The relationship between the offset interval and temperature and humidity change is analyzed by using the formula: ； The coupling offset representation is obtained, where, Representing the Temperature, humidity and voltage coupling offset of nodes. Representing the The number of times a node is sampled within the statistical period. Representing the Node number Temperature data from the second sampling, Representing the Average temperature data of the node within the statistical period. Representing the Node number Humidity data from the second sampling, Representing the Average humidity data for nodes within the statistical period. Representing the Node number Voltage data from the next sample Representing the Average voltage data of the node within the statistical period; The original temperature, humidity, and voltage data are normalized by using a normalization method to obtain normalized data , , , , and .

9. The method of wall corona ozone control optimization of claim 1, wherein, The step of the load distribution adjustment configuration is specifically: S501: Based on the coupling offset performance quantity, the temperature parameters of the heat dissipation area of the ozone device of the area along the surface discharge are optimized, the temperature data of each node and the spatial distribution relationship with the device heat dissipation area are analyzed, the temperature distribution in the heat dissipation area is adjusted, and the thermal control adjustment partition is obtained. S502: Based on the thermal control adjustment partition, the humidity of the electrode unit structure combination component is adjusted, the humidity change characteristics of each electrode structure in the environment are combined, the distribution before and after the humidity adjustment is compared, the influence of the combined change of humidity and temperature on the discharge current density is judged, and the energy flow characteristic factor is obtained. S503: Based on the energy flow characteristic factor, combined with the ozone response data collected by the nodes, the influence of the temperature and humidity changes of the region on the load distribution state of each node of the discharge device is judged, the target region power distribution is optimized, and the load distribution adjustment configuration is obtained.

Images