Intelligent control method and system of ultra-high frequency power supply for electrostatic precipitator based on data analysis

Abstract

The invention relates to the technical field of power supply control, in particular to a method and system for intelligently controlling ultra-high frequency power supply for electrostatic precipitator based on data analysis, comprising: step 1: collecting various monitoring data of ultra-high frequency power supply control for electrostatic precipitator to obtain various parameters of analyzing ultra-high frequency power supply control performance index; step 2: analyzing various parameters of step 1 to obtain various control indexes of ultra-high frequency power supply intelligent control; step 3: comparing various control indexes obtained in step 2 with threshold values ​​respectively, triggering ultra-high frequency power supply control mechanism according to comparison results; step 4: based on the comparison results obtained in step 3, comprehensively analyzing adjustment factors of various control indexes by big data analysis technology; step 5: performing human-computer interaction on the comprehensive analysis results obtained in step 4; the invention can realize intelligent control of ultra-high frequency power supply, improve electrostatic precipitator efficiency and reduce energy consumption by real-time collection and analysis of operation data of electrostatic precipitator.

Description

Technical Field

[0001] The present invention relates to the technical field of power supply control, and in particular to a method and system for intelligently controlling a UHF power supply for an electrostatic precipitator based on data analysis. Background Art

[0002] Electrostatic precipitators are widely used in various industrial furnace dust treatment in the power, metallurgy, petrochemical, building materials, machinery, medicine and other industries due to their high dust removal efficiency and low operation and maintenance costs. As a key component of electrostatic precipitators, ultra-high frequency power supply has the advantages of high operating frequency, small size, light weight and high efficiency. In electrostatic precipitators, the application of ultra-high frequency power supply can significantly improve dust removal efficiency and reduce energy consumption. Its control method has an important influence on dust removal effect and energy consumption. The introduction of intelligent control technology provides a more advanced and flexible means for the control of power supply for electrostatic precipitators.

[0003] Most traditional high-voltage power supplies for electrostatic precipitators use industrial frequency phase-controlled power supplies to provide power for the electrostatic precipitator. They are adjusted based on fixed parameters or thresholds, and may not respond in time when the operating conditions change significantly, resulting in a decrease in the dust removal effect. They are based on constant spark rate control or ordinary spark tracking operation control. When the operating conditions change, the power supply may not be adjusted to the optimal state in time, resulting in unnecessary energy consumption.

[0004] With the continuous improvement of environmental protection standards and the requirements of energy conservation, consumption reduction and sustainable development, electrostatic precipitator technology is also constantly developing and improving. However, there are many shortcomings in the existing power supply control methods and systems for electrostatic precipitators. For example, this type of power supply has generally low operating parameters, which affects the dust removal efficiency; there are often problems such as low control accuracy, poor adaptability, and high energy consumption, which makes it difficult to meet the increasingly stringent environmental protection requirements. With the development of data analysis technology, new ideas are provided for the intelligent control of electrostatic precipitator power supplies. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, the embodiments of the present invention provide a method and system for intelligently controlling a UHF power supply for an electrostatic precipitator based on data analysis to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solution: a method for intelligently controlling a UHF power supply for electrostatic precipitator based on data analysis, comprising:

[0007] Step 1: Through sensor technology and monitoring equipment, various monitoring data of the ultra-high frequency power supply control for electrostatic precipitator are collected to obtain and analyze various parameters of the ultra-high frequency power supply control performance index;

[0008] Step 2: Analyze the parameters of step 1 through big data analysis technology to obtain various control indexes of UHF power supply intelligent control, including the electric field intensity and dust charging efficiency matching control index, the pulse frequency and energy efficiency control index, and the high-frequency power supply output and anti-corona control index;

[0009] In step 2, the electric field intensity and dust charging efficiency matching control index are obtained: first, the output voltage V_out of the ultra-high frequency power supply is monitored in real time by sensor technology to obtain the electric field intensity E at different positions in the electric field generated by the ultra-high frequency power supply; then, the particle size distribution of the dust particles for electrostatic precipitator is obtained by measuring equipment, and the average particle size d_par is calculated, and the charge cq obtained by the dust particles in the electric field is obtained; finally, the electric field intensity and dust charging efficiency matching control index η_E is obtained by big data analysis technology,

[0010] , where E_avg represents the average value of the electric field strength at different positions, CQ represents the maximum charge obtained by dust particles in the electric field, and α is the dust particle size influence coefficient;

[0011] In step 2, the pulse frequency and energy efficiency control index are obtained: first, the frequency f_pul, pulse width τ_pul and cumulative electric energy E_con consumed by the electric dust collector output by the ultra-high frequency power supply are monitored in real time by measurement technology; then, a dust concentration measurement device is installed at the inlet of the electric dust collector to obtain the inlet dust concentration in_dust and the outlet dust concentration out_dust, and the dust removal efficiency coefficient η_dust is obtained, η_dust=[(in_dust)-(out_dust)] / (out_dust); finally, the pulse frequency and energy efficiency control index η_f are obtained by big data analysis technology, , where g and b represent the influence coefficients of pulse frequency and pulse width on the energy consumption of electrostatic precipitator respectively;

[0012] In the step 2, the high-frequency power supply output and the back-corona control index are obtained: first, the waveform frequency F of the ultra-high frequency power supply output and the complete cycle of the waveform, including the high-level time t_h and the low-level time t_l of the waveform, are obtained by measuring technology; then the voltage fluctuation coefficient η_V and the current fluctuation coefficient η_I are recorded in the monitoring time period t, wherein η_V=σ_V / μ_V, σ_V and μ_V respectively represent the standard deviation of the voltage and the average voltage in the monitoring time period t, and η_I=σ_I / μ_I, σ_I and μ_I respectively represent the standard deviation of the current and the average current in the monitoring time period t; finally, the high-frequency power supply output and the back-corona control index η_d are obtained by big data analysis technology, , where H(η_dust) is the high resistivity dust collection efficiency, H(η_dust)=[H(in_dust)-H(out_dust)] / H(out_dust), H(in_dust) and H(out_dust) represent the high resistivity dust concentration at the inlet and outlet of the electrostatic precipitator, respectively, and w1 and w2 represent the weights of the voltage fluctuation coefficient and the current fluctuation coefficient, respectively;

[0013] Step 3: Compare each control index obtained in step 2 with the threshold value, and trigger the UHF power supply control mechanism according to the comparison result;

[0014] Step 4: Based on the comparison results obtained in step 3, the adjustment factors of each control index are comprehensively analyzed by big data analysis technology to obtain the comprehensive index of intelligent control of ultra-high frequency power supply for electrostatic precipitator;

[0015] Step 5: Perform human-computer interaction on the comprehensive indicators of intelligent control of ultra-high frequency power supply for electrostatic precipitator based on the comprehensive analysis results obtained in step 4.

[0016] Preferably, triggering the UHF power supply control mechanism in step 3 includes the following steps:

[0017] Step 3.1: Using big data analysis technology, substitute the electric field intensity and dust charging efficiency matching control index η_E into the formula: ; Wherein γ(η_E) represents the adjustment factor of the control index of the matching between the electric field intensity and the dust charging efficiency, η_E0 represents the threshold value, if γ(η_E)≥0, it means that the UHF power supply for the electrostatic precipitator is well controlled, otherwise the UHF power supply control mechanism is triggered to generate the UHF power supply control strategy, including adjusting the output voltage of the UHF power supply.

[0018] Preferably, triggering the UHF power supply control mechanism in step 3 includes the following steps:

[0019] Step 3.2: Using big data analysis technology, substitute the pulse frequency and energy efficiency control index η_f into the formula: ; Wherein γ(η_f) represents the adjustment factor of pulse frequency and energy consumption efficiency control index, η_f0 represents the threshold value, if γ(η_f)≥0, it means that the ultra-high frequency power supply for electrostatic precipitator is well controlled, otherwise the first mechanism of ultra-high frequency power supply control is triggered; then the dust removal efficiency coefficient η_dust is compared with the threshold value η_dust0, if η_dust is less than η_dust0, it means that the dust removal efficiency is reduced, then the second mechanism of ultra-high frequency power supply control is triggered, and based on historical data, the ultra-high frequency power supply control strategy is generated, including increasing the pulse frequency and adjusting the pulse width; finally, while maintaining the dust removal efficiency, the accumulated electric energy E_con consumed by the electrostatic precipitator is compared with the threshold value E_con0, if E_con is greater than E_con0, the third mechanism of ultra-high frequency power supply control is triggered, and based on historical data, the ultra-high frequency power supply control strategy is generated, including reducing the pulse frequency and adjusting the pulse width.

[0020] Preferably, triggering the UHF power supply control mechanism in step 3 includes the following steps:

[0021] Step 3.3: Using big data analysis technology, substitute the high-frequency power output and the back corona control index η_d into the formula: ; Wherein γ(η_d) represents the adjustment factor of high-frequency power supply output and back-corona control index, η_d0 represents the threshold value. If γ(η_d)≥0, it means that the ultra-high frequency power supply for electrostatic precipitator is well controlled. Otherwise, the ultra-high frequency power supply control mechanism is triggered. Based on historical data, the ultra-high frequency power supply control strategy is generated, including adjusting the frequency of the output waveform, adjusting the waveform duty cycle, adjusting the output voltage and current.

[0022] Preferably, the comprehensive index ECCI of intelligent control of ultra-high frequency power supply for electrostatic precipitator in step 4, ECCI=c1×γ(η_E)+c2×γ(η_f)+c3×γ(η_d), wherein c1, c2 and c3 respectively represent corresponding weights, γ(η_E) represents the adjustment factor of electric field intensity and dust charging efficiency matching control index, γ(η_f) represents the adjustment factor of pulse frequency and energy consumption efficiency control index, and γ(η_d) represents the adjustment factor of high frequency power supply output and back corona control index.

[0023] Preferably, the intelligent control system of ultra-high frequency power supply for electrostatic precipitator based on data analysis includes:

[0024] UHF power supply control data acquisition module: used to collect various monitoring data of UHF power supply control for electrostatic precipitator, obtain various parameters for analyzing UHF power supply control performance index, and transmit various parameters to UHF power supply control data analysis module;

[0025] UHF power supply control data analysis module: used to analyze various parameters of the data acquisition module, obtain various control indexes of the UHF power supply intelligent control, and transmit the various control indexes to the UHF power supply control module;

[0026] UHF power supply control module: used to compare the various control indexes obtained by the data analysis module with the threshold value, trigger the UHF power supply control mechanism according to the comparison result, and transmit the comparison result to the UHF power supply control comprehensive analysis module;

[0027] UHF power supply control comprehensive analysis module: used for comprehensive analysis of the comparison results obtained by the UHF power supply control module, and transmitting the comprehensive analysis results to the UHF power supply control human-computer interaction module;

[0028] UHF power supply control human-computer interaction module: used to transmit the comprehensive analysis results obtained by the comprehensive analysis module to the management personnel information terminal.

[0029] Technical effects and advantages of the present invention:

[0030] 1. The present invention uses big data analysis technology to monitor key parameters such as electric field strength and dust charging efficiency in real time, accurately control the output of the UHF power supply, optimize the electric field distribution, and improve the dust capture capability, thereby ensuring that the electrostatic precipitator can operate stably under various working conditions and improving the reliability and stability of the entire system;

[0031] 2. The present invention uses big data analysis technology to monitor dust removal effects and energy consumption data in real time. The system can automatically adjust the pulse frequency to achieve the best dust removal effect while reducing energy consumption. At the same time, different working conditions may be encountered during the actual operation process, and the parameters can be automatically adjusted according to the actual working conditions to ensure that the dust removal efficiency is always maintained at a high level;

[0032] 3. The present invention uses big data analysis technology to monitor and analyze the degree of back-corona phenomenon in electrostatic precipitators in real time. The UHF power supply can output flexible and adjustable waveform frequency. Managers can select appropriate frequencies to optimize the dust removal effect according to the actual needs of dust removal. By intelligently controlling the output waveform, the occurrence of back-corona phenomenon can be measured and suppressed, thereby improving the stability and efficiency of the dust collector. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 It is a schematic diagram of the overall process of the present invention.

[0034] Figure 2 It is a schematic diagram of the method flow of the present invention. DETAILED DESCRIPTION

[0035] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0036] See also Figure 1 As shown, the present invention provides an ultra-high frequency power supply intelligent control system for electrostatic precipitator based on data analysis, including: an ultra-high frequency power supply control data acquisition module, an ultra-high frequency power supply control data analysis module, an ultra-high frequency power supply control module, an ultra-high frequency power supply control comprehensive analysis module and an ultra-high frequency power supply control human-computer interaction module.

[0037] The UHF power supply control data acquisition module is connected to the UHF power supply control data analysis module, the UHF power supply control module is respectively connected to the UHF power supply control comprehensive analysis module and the UHF power supply control data analysis module, and the UHF power supply control human-computer interaction module is respectively connected to the UHF power supply control comprehensive analysis module and the UHF power supply control data analysis module.

[0038] UHF power supply control data acquisition module: used to collect various monitoring data of UHF power supply control for electrostatic precipitator, obtain various parameters for analyzing UHF power supply control performance index, and transmit various parameters to UHF power supply control data analysis module;

[0039] UHF power supply control data analysis module: used to analyze various parameters of the data acquisition module, obtain various control indexes of the UHF power supply intelligent control, and transmit the various control indexes to the UHF power supply control module;

[0040] UHF power supply control module: used to compare the various control indexes obtained by the data analysis module with the threshold value, trigger the UHF power supply control mechanism according to the comparison result, and transmit the comparison result to the UHF power supply control comprehensive analysis module;

[0041] UHF power supply control comprehensive analysis module: used for comprehensive analysis of the comparison results obtained by the UHF power supply control module, and transmitting the comprehensive analysis results to the UHF power supply control human-computer interaction module;

[0042] UHF power supply control human-computer interaction module: used to transmit the comprehensive analysis results obtained by the comprehensive analysis module to the management personnel information terminal.

[0043] See also Figure 2As shown, the method for intelligent control of ultra-high frequency power supply for electrostatic precipitator based on data analysis includes: step 1: collecting various monitoring data of ultra-high frequency power supply control for electrostatic precipitator through sensor technology and monitoring equipment, and obtaining various parameters of ultra-high frequency power supply control performance index; step 2: analyzing various parameters of step 1 through big data analysis technology, and obtaining various control indexes of ultra-high frequency power supply intelligent control, and each control index includes electric field intensity and dust charging efficiency matching control index, pulse frequency and energy consumption efficiency control index and high-frequency power supply output and back corona control index; step 3: comparing each control index obtained in step 2 with the threshold value respectively, and triggering the ultra-high frequency power supply control mechanism according to the comparison result; step 4: based on the comparison result obtained in step 3, comprehensively analyzing the adjustment factors of each control index through big data analysis technology, and obtaining the comprehensive index of ultra-high frequency power supply intelligent control for electrostatic precipitator; step 5: performing human-computer interaction on the comprehensive analysis result obtained in step 4, the comprehensive index of ultra-high frequency power supply intelligent control for electrostatic precipitator.

[0044] Step 1: Through sensor technology and monitoring equipment, various monitoring data of the ultra-high frequency power supply control for electrostatic precipitator are collected to obtain various parameters for analyzing the ultra-high frequency power supply control performance index, including administrator identity authentication information, ultra-high frequency power supply output parameters and electrostatic precipitator dust removal parameters, wherein the ultra-high frequency power supply output parameters include voltage, current, electric field strength, frequency of pulse signal, pulse width, and output waveform voltage frequency; the electrostatic precipitator dust removal parameters include the particle size of dust particles and the amount of charge obtained in the electric field, and the dust concentration at the inlet and outlet of the electrostatic precipitator;

[0045] Step 2: Analyze the parameters of step 1 through big data analysis technology to obtain various control indexes of UHF power supply intelligent control, including the electric field strength and dust charging efficiency matching control index, pulse frequency and energy efficiency control index, and high-frequency power supply output and back corona control index. The parameter analysis includes the following steps:

[0046] Step 2.1: First, the output voltage V_out of the UHF power supply is monitored in real time by sensor technology to obtain the electric field strength E at different positions in the electric field generated by the UHF power supply; then, the particle size distribution of the dust particles used for electrostatic precipitator is obtained by measuring equipment, and the average particle size d_par is calculated, and the charge cq obtained by the dust particles in the electric field is obtained; finally, the electric field strength and dust charging efficiency matching control index η_E is obtained by big data analysis technology, , where E_avg represents the average value of the electric field strength at different positions, CQ represents the maximum charge obtained by dust particles in the electric field, and α is the dust particle size influence coefficient, which is obtained based on historical data and is used to adjust the influence of particle size on charging efficiency;

[0047] What needs to be specifically explained in this embodiment is that the battery strength parameters generated by the UHF power supply and the dust particle parameters for electrostatic precipitator are analyzed, among which the electric field strength is one of the key factors determining the dust charging efficiency. By adjusting the electric field strength, the dust charging process can be optimized, thereby improving the dust charging efficiency, which means that more dust particles can obtain sufficient charge in the electric field, making it easier to be captured by the subsequent dust collecting electrode, thereby improving the dust removal effect.

[0048] Step 2.2: First, the frequency f_pul, pulse width τ_pul and cumulative electric energy E_con consumed by the electrostatic precipitator of the pulse signal output by the UHF power supply are monitored in real time through measurement technology, where the pulse width represents the duration of each pulse signal; then, a dust concentration measurement device is installed at the inlet of the electrostatic precipitator to obtain the inlet dust concentration in_dust and the outlet dust concentration out_dust, and obtain the dust removal efficiency coefficient η_dust, η_dust=[(in_dust)-(out_dust)] / (out_dust); finally, the pulse frequency and energy efficiency control index η_f are obtained through big data analysis technology. , where g and b represent the influence coefficients of pulse frequency and pulse width on the energy consumption of electrostatic precipitator, respectively, based on historical data;

[0049] What needs to be specifically explained in this embodiment is that by real-time monitoring and analysis of dust removal effect and energy consumption data, the system can automatically adjust the pulse frequency to achieve the best dust removal effect and reduce energy consumption; at the same time, pulse width is also one of the important factors affecting dust removal efficiency and energy consumption. The intelligent control system can accurately control the duration of each pulse signal to ensure that the pulse width is within an appropriate range, thereby improving dust removal efficiency and reducing energy consumption.

[0050] Step 2.3: First, the waveform frequency F output by the UHF power supply is obtained through measurement technology, as well as the complete cycle of the waveform, including the high-level time t_h and low-level time t_l of the waveform; then the voltage fluctuation coefficient η_V and the current fluctuation coefficient η_I are recorded within the monitoring time period t, where η_V=σ_V / μ_V, σ_V and μ_V represent the standard deviation of the voltage and the average voltage within the monitoring time period t, respectively, and η_I=σ_I / μ_I, σ_I and μ_I represent the standard deviation of the current and the average current within the monitoring time period t, respectively; finally, the high-frequency power supply output and the back-corona control index η_d are obtained through big data analysis technology, , where H(η_dust) is the high resistivity dust collection efficiency, H(η_dust)=[H(in_dust)-H(out_dust)] / H(out_dust), H(in_dust) and H(out_dust) represent the high resistivity dust concentration at the inlet and outlet of the electrostatic precipitator, respectively, and w1 and w2 represent the weights of the voltage fluctuation coefficient and the current fluctuation coefficient, respectively, for example, w1=0.5 and w2=0.5;

[0051] It should be specifically explained in this embodiment that high specific resistance dust refers to dust whose specific resistance value exceeds a certain threshold value. When the specific resistance value of dust is high, dust particles are not easily ionized and charged in the electric field, and therefore are difficult to be effectively captured by the electrostatic precipitator. In addition, after high specific resistance dust is deposited on the dust collecting plate, since the charge is not easily released, it is easy to form charge accumulation, and then produce local discharge phenomenon, that is, back corona. Back corona will cause the electric field strength to weaken and the dust removal efficiency to decrease. In severe cases, it may even cause the electrostatic precipitator to fail to work normally.

[0052] What needs to be specifically explained in this embodiment is that when the voltage fluctuation exceeds the normal range, it may indicate that there is an abnormality inside the electrostatic precipitator, such as the occurrence of back corona phenomenon; when the current abnormality occurs, it may also mean the existence or aggravation of the back corona phenomenon.

[0053] Step 3: Compare each control index obtained in step 2 with the threshold value, and trigger the UHF power supply control mechanism according to the comparison result, including the following steps:

[0054] Step 3.1: Using big data analysis technology, substitute the electric field intensity and dust charging efficiency matching control index η_E into the formula: ; Wherein γ(η_E) represents the adjustment factor of the electric field strength and the dust charging efficiency matching control index, η_E0 represents the threshold value, if γ(η_E)≥0, it means that the ultra-high frequency power supply for electrostatic precipitator is well controlled, otherwise the ultra-high frequency power supply control mechanism is triggered to generate the ultra-high frequency power supply control strategy, including adjusting the output voltage of the ultra-high frequency power supply to optimize the electric field strength, ensure that dust particles of different particle sizes can be efficiently charged, thereby improving the dust charging efficiency;

[0055] Step 3.2: Using big data analysis technology, substitute the pulse frequency and energy efficiency control index η_f into the formula: ; Wherein γ(η_f) represents the adjustment factor of the pulse frequency and the energy consumption efficiency control index, η_f0 represents the threshold value, if γ(η_f)≥0, it means that the ultra-high frequency power supply for the electrostatic precipitator is well controlled, otherwise the first mechanism of ultra-high frequency power supply control is triggered; then the dust removal efficiency coefficient η_dust is compared with the threshold value η_dust0, if η_dust is less than η_dust0, it means that the dust removal efficiency is reduced, then the second mechanism of ultra-high frequency power supply control is triggered, and based on historical data, an ultra-high frequency power supply control strategy is generated, including increasing the pulse frequency and adjusting the pulse width to improve the dust removal efficiency; finally, while maintaining the dust removal efficiency, the accumulated electric energy E_con consumed by the electrostatic precipitator is compared with the threshold value E_con0, if E_con is greater than E_con0, then the third mechanism of ultra-high frequency power supply control is triggered, and based on historical data, an ultra-high frequency power supply control strategy is generated, including reducing the pulse frequency and adjusting the pulse width to reduce energy consumption;

[0056] Step 3.3: Using big data analysis technology, substitute the high-frequency power output and the back corona control index η_d into the formula: ; Wherein γ(η_d) represents the adjustment factor of high-frequency power supply output and back corona control index, η_d0 represents the threshold value, if γ(η_d)≥0, it means that the ultra-high frequency power supply for electrostatic precipitator is well controlled, otherwise the ultra-high frequency power supply control mechanism is triggered, and the ultra-high frequency power supply control strategy is generated based on historical data, including adjusting the frequency of the output waveform, adjusting the waveform duty cycle, adjusting the output voltage and current, so as to suppress back corona and reduce energy consumption;

[0057] Step 4: Based on the comparison results obtained in step 3, the adjustment factors of each control index are comprehensively analyzed by big data analysis technology to obtain the comprehensive index ECCI of ultra-high frequency power supply intelligent control for electrostatic precipitator. The comprehensive analysis model is: ECCI=c1×γ(η_E)+c2×γ(η_f)+c3×γ(η_d), where c1, c2 and c3 represent the corresponding weights, γ(η_E) represents the adjustment factor of the electric field intensity and dust charging efficiency matching control index, γ(η_f) represents the adjustment factor of the pulse frequency and energy consumption efficiency control index, and γ(η_d) represents the adjustment factor of the high-frequency power supply output and the back corona control index, for example, c1=0.4, c2=0.3 and c3=0.3;

[0058] Step 5: Perform human-computer interaction on the comprehensive analysis results of step 4 for the comprehensive indicators of intelligent control of ultra-high frequency power supply for electrostatic precipitator. If the comprehensive indicators of intelligent control of ultra-high frequency power supply for electrostatic precipitator belong to the set allowable range, it means that the ultra-high frequency power supply for electrostatic precipitator is well controlled. Otherwise, the administrator is prompted to take timely measures to monitor the operating parameters of the electrostatic precipitator in real time, such as electric field strength, pulse frequency, high-frequency power supply output, etc., analyze the operating data regularly, find out the key factors affecting the dust removal efficiency, and take corresponding comprehensive control measures for ultra-high frequency power supply.

[0059] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

[0060] The above contents are merely examples and explanations of the concept of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the defined scope, they should all fall within the protection scope of the present invention.

Claims

1. An intelligent control method for ultra-high frequency power supply for electrostatic precipitator based on data analysis, characterized in that: include: Step 1: Through sensor technology and monitoring equipment, various monitoring data of the ultra-high frequency power supply control for electrostatic precipitator are collected to obtain and analyze various parameters of the ultra-high frequency power supply control performance index; Step 2: Analyze the parameters of step 1 through big data analysis technology to obtain various control indexes of UHF power supply intelligent control, including the electric field intensity and dust charging efficiency matching control index, the pulse frequency and energy efficiency control index, and the high-frequency power supply output and anti-corona control index; In step 2, the electric field intensity and dust charging efficiency matching control index are obtained: first, the output voltage V_out of the ultra-high frequency power supply is monitored in real time by sensor technology to obtain the electric field intensity E at different positions in the electric field generated by the ultra-high frequency power supply; then, the particle size distribution of the dust particles for electrostatic precipitator is obtained by measuring equipment, and the average particle size d_par is calculated, and the charge cq obtained by the dust particles in the electric field is obtained; finally, the electric field intensity and dust charging efficiency matching control index η_E is obtained by big data analysis technology, , where E_avg represents the average value of the electric field strength at different positions, CQ represents the maximum charge obtained by dust particles in the electric field, and α is the dust particle size influence coefficient; In step 2, the pulse frequency and energy efficiency control index are obtained: first, the frequency f_pul, pulse width τ_pul and cumulative electric energy E_con consumed by the electric dust collector output by the ultra-high frequency power supply are monitored in real time by measurement technology; then, a dust concentration measurement device is installed at the inlet of the electric dust collector to obtain the inlet dust concentration in_dust and the outlet dust concentration out_dust, and the dust removal efficiency coefficient η_dust is obtained, η_dust=[(in_dust)-(out_dust)] / (out_dust); finally, the pulse frequency and energy efficiency control index η_f are obtained by big data analysis technology, , where g and b represent the influence coefficients of pulse frequency and pulse width on the energy consumption of electrostatic precipitator respectively; In the step 2, the high-frequency power supply output and the back-corona control index are obtained: first, the waveform frequency F of the ultra-high frequency power supply output and the complete cycle of the waveform, including the high-level time t_h and the low-level time t_l of the waveform, are obtained by measuring technology; then the voltage fluctuation coefficient η_V and the current fluctuation coefficient η_I are recorded in the monitoring time period t, wherein η_V=σ_V / μ_V, σ_V and μ_V respectively represent the standard deviation of the voltage and the average voltage in the monitoring time period t, and η_I=σ_I / μ_I, σ_I and μ_I respectively represent the standard deviation of the current and the average current in the monitoring time period t; finally, the high-frequency power supply output and the back-corona control index η_d are obtained by big data analysis technology, , where H(η_dust) is the high resistivity dust collection efficiency, H(η_dust)=[H(in_dust)-H(out_dust)] / H(out_dust), H(in_dust) and H(out_dust) represent the high resistivity dust concentration at the inlet and outlet of the electrostatic precipitator, respectively, and w1 and w2 represent the weights of the voltage fluctuation coefficient and the current fluctuation coefficient, respectively; Step 3: Compare each control index obtained in step 2 with the threshold value, and trigger the UHF power supply control mechanism according to the comparison result; Step 4: Based on the comparison results obtained in step 3, the adjustment factors of each control index are comprehensively analyzed by big data analysis technology to obtain the comprehensive index of intelligent control of ultra-high frequency power supply for electrostatic precipitator; Step 5: Perform human-computer interaction on the comprehensive indicators of intelligent control of ultra-high frequency power supply for electrostatic precipitator based on the comprehensive analysis results obtained in step 4.

2. The intelligent control method of ultra-high frequency power supply for electrostatic precipitator based on data analysis according to claim 1 is characterized in that: Triggering the UHF power supply control mechanism in step 3 includes the following steps: Step 3.1: Using big data analysis technology, substitute the electric field intensity and dust charging efficiency matching control index η_E into the formula: ; Wherein γ(η_E) represents the adjustment factor of the control index of the matching between the electric field intensity and the dust charging efficiency, η_E0 represents the threshold value, if γ(η_E)≥0, it means that the UHF power supply for the electrostatic precipitator is well controlled, otherwise the UHF power supply control mechanism is triggered to generate the UHF power supply control strategy, including adjusting the output voltage of the UHF power supply.

3. The intelligent control method of ultra-high frequency power supply for electrostatic precipitator based on data analysis according to claim 1 is characterized in that: Triggering the UHF power supply control mechanism in step 3 includes the following steps: Step 3.2: Using big data analysis technology, substitute the pulse frequency and energy efficiency control index η_f into the formula: ; Wherein γ(η_f) represents the adjustment factor of pulse frequency and energy consumption efficiency control index, η_f0 represents the threshold value, if γ(η_f)≥0, it means that the ultra-high frequency power supply for electrostatic precipitator is well controlled, otherwise the first mechanism of ultra-high frequency power supply control is triggered; then the dust removal efficiency coefficient η_dust is compared with the threshold value η_dust0, if η_dust is less than η_dust0, it means that the dust removal efficiency is reduced, then the second mechanism of ultra-high frequency power supply control is triggered, and based on historical data, the ultra-high frequency power supply control strategy is generated, including increasing the pulse frequency and adjusting the pulse width; finally, while maintaining the dust removal efficiency, the accumulated electric energy E_con consumed by the electrostatic precipitator is compared with the threshold value E_con0, if E_con is greater than E_con0, the third mechanism of ultra-high frequency power supply control is triggered, and based on historical data, the ultra-high frequency power supply control strategy is generated, including reducing the pulse frequency and adjusting the pulse width.

4. The intelligent control method of ultra-high frequency power supply for electrostatic precipitator based on data analysis according to claim 1 is characterized in that: Triggering the UHF power supply control mechanism in step 3 includes the following steps: Step 3.3: Using big data analysis technology, substitute the high-frequency power output and the back corona control index η_d into the formula: ; Wherein γ(η_d) represents the adjustment factor of high-frequency power supply output and back-corona control index, η_d0 represents the threshold value. If γ(η_d)≥0, it means that the ultra-high frequency power supply for electrostatic precipitator is well controlled. Otherwise, the ultra-high frequency power supply control mechanism is triggered. Based on historical data, the ultra-high frequency power supply control strategy is generated, including adjusting the frequency of the output waveform, adjusting the waveform duty cycle, adjusting the output voltage and current.

5. The intelligent control method of ultra-high frequency power supply for electrostatic precipitator based on data analysis according to claim 1 is characterized in that: The comprehensive index ECCI of intelligent control of ultra-high frequency power supply for electrostatic precipitator in step 4 is ECCI=c1×γ(η_E)+c2×γ(η_f)+c3×γ(η_d), wherein c1, c2 and c3 respectively represent corresponding weights, γ(η_E) represents the adjustment factor of electric field intensity and dust charging efficiency matching control index, γ(η_f) represents the adjustment factor of pulse frequency and energy consumption efficiency control index, and γ(η_d) represents the adjustment factor of high frequency power supply output and back corona control index.

6. An intelligent control system for ultra-high frequency power supply for electrostatic precipitator based on data analysis, used for using the intelligent control method for ultra-high frequency power supply for electrostatic precipitator based on data analysis according to any one of claims 1 to 5, comprising: UHF power supply control data acquisition module: used to collect various monitoring data of UHF power supply control for electrostatic precipitator, obtain various parameters for analyzing UHF power supply control performance index, and transmit various parameters to UHF power supply control data analysis module; UHF power supply control data analysis module: used to analyze various parameters of the data acquisition module, obtain various control indexes of the UHF power supply intelligent control, and transmit the various control indexes to the UHF power supply control module; UHF power supply control module: used to compare the various control indexes obtained by the data analysis module with the threshold value, trigger the UHF power supply control mechanism according to the comparison result, and transmit the comparison result to the UHF power supply control comprehensive analysis module; UHF power supply control comprehensive analysis module: used for comprehensive analysis of the comparison results obtained by the UHF power supply control module, and transmitting the comprehensive analysis results to the UHF power supply control human-computer interaction module; UHF power supply control human-computer interaction module: used to transmit the comprehensive analysis results obtained by the comprehensive analysis module to the management personnel information terminal.

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