CN116717496A - Control method and system of fan of dust removal system, electronic equipment and medium - Google Patents
Control method and system of fan of dust removal system, electronic equipment and medium Download PDFInfo
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- CN116717496A CN116717496A CN202311006829.8A CN202311006829A CN116717496A CN 116717496 A CN116717496 A CN 116717496A CN 202311006829 A CN202311006829 A CN 202311006829A CN 116717496 A CN116717496 A CN 116717496A
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- 239000000428 dust Substances 0.000 title claims abstract description 287
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- 230000002068 genetic effect Effects 0.000 claims description 4
- 230000001276 controlling effect Effects 0.000 description 27
- 230000000694 effects Effects 0.000 description 16
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Classifications
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
- F04D—NON-POSITIVE-DISPLACEMENT PUMPS
- F04D27/00—Control, e.g. regulation, of pumps, pumping installations or pumping systems specially adapted for elastic fluids
- F04D27/004—Control, e.g. regulation, of pumps, pumping installations or pumping systems specially adapted for elastic fluids by varying driving speed
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B08—CLEANING
- B08B—CLEANING IN GENERAL; PREVENTION OF FOULING IN GENERAL
- B08B5/00—Cleaning by methods involving the use of air flow or gas flow
- B08B5/04—Cleaning by suction, with or without auxiliary action
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
- G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B30/00—Energy efficient heating, ventilation or air conditioning [HVAC]
- Y02B30/70—Efficient control or regulation technologies, e.g. for control of refrigerant flow, motor or heating
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Abstract
The invention provides a control method, a system, electronic equipment and a medium of a fan of a dust removal system, wherein the method comprises the following steps: and acquiring data of system state parameters representing the actual running state of the dust removal system at the current moment. According to the data of the system state parameters at the current moment, the running frequency of the fan is used as an optimization object, the energy consumption of the fan is used as the minimum target to determine the optimized objective function of the fan, the constraint condition related to the system state parameters is determined according to the operation constraint condition of the dust removal system, and the optimal running frequency of the fan corresponding to the current moment is determined according to the optimized objective function and the constraint condition and by utilizing an optimization algorithm. And adjusting the operating frequency of the fan according to the optimal operating frequency and by a preset control algorithm. According to the scheme, the optimal running frequency of the fan can be solved based on the system state parameters of the dust removal system, so that the suction air quantity of the fan is controlled, the fan sucks better air quantity, and further energy consumption and noise generated by the system are reduced.
Description
Technical Field
The invention relates to the technical field of air quantity control of fans, in particular to a control method and system of a fan of a dust removal system, electronic equipment and a medium.
Background
Along with the improvement of the national requirements on energy conservation and environmental protection, dust removal systems in industrial production are increasingly paid attention to. The dust removing system generally comprises a fan, a plurality of dust removing devices distributed in the factory building and corresponding connecting pipelines, and the working state of each dust removing device is controlled through a corresponding control valve. When a specific area in the factory building needs to be dedusted, the fan is started, and the control valve of the dedusting equipment in the area is started, so that the air can be sucked by the fan to dedust the area.
In general, a pressure sensor for measuring the pressure of gas in a pipe is provided inside a connection pipe of a dust removing system. The controller of the dust removal system can control the frequency of the fan according to the comparison result of the measurement result of the pressure sensor and the preset pressure threshold value, and then control the air quantity inhaled by the fan. For example, when the measurement result of the pressure sensor is smaller than the pressure threshold value, the air quantity of the fan is smaller, and the frequency of the fan needs to be increased to ensure the dust removal effect; when the measurement result of the pressure sensor is larger than the pressure threshold value, the air quantity of the fan is larger, and the frequency of the fan needs to be reduced to reduce energy consumption. For example, in the environmental dust removal method disclosed in patent document CN101733265B, a wind pressure sensor is additionally arranged in a dust removal main air passage, and the wind pressure sensor is arranged near an air inlet of a dust removal fan, the wind pressure sensor sends a collected wind pressure signal into a central control system in real time, the central control system compares the wind pressure signal collected by the wind pressure sensor with a standard air pressure value preset in the central control system, and the central control system outputs a variable signal to control the output frequency of the fan frequency converter according to the comparison value, so as to control the rotating speed of the dust removal fan, and further control the suction air quantity of the fan.
However, the method for controlling the suction air volume of the fan just controls the rotation speed of the dust removal fan according to the state (such as pressure) in the pipeline and the preset standard value, and has the problem of limited adjustment precision, so that the fan cannot work at the optimal frequency and cannot suck the optimal air volume. In addition, in order to ensure the dust removal effect, the air volume sucked by the fan is generally larger than the optimal air volume, which can cause the problems of higher energy consumption and larger generated noise of the fan.
Disclosure of Invention
The invention aims to solve the problems of high energy consumption and high noise of a fan caused by the fact that the fan adjusting precision of the dust removing system in the prior art is limited and the optimal air quantity cannot be sucked.
In order to solve the problems, the embodiment of the invention discloses a control method of a fan of a dust removing system, the dust removing system comprises the fan and at least one dust removing device, each dust removing device is communicated with an air inlet of the fan through a corresponding dust removing air passage, and a control valve is arranged in each dust removing air passage. The control method of the fan comprises the following steps:
s1: acquiring data of system state parameters representing the actual running state of the dust removal system at the current moment;
S2: determining an optimized objective function of the fan by taking the operating frequency of the fan as an optimized object and taking the minimum energy consumption of the fan as a target according to the data of the system state parameters at the current moment, determining a constraint condition related to the system state parameters according to the operation limiting condition of the dust removal system, and determining the optimal operating frequency of the fan corresponding to the current moment according to the optimized objective function and the constraint condition and by utilizing an optimization algorithm;
s3: and adjusting the operating frequency of the fan according to the optimal operating frequency and by a preset control algorithm.
By adopting the scheme, the actual running state of the dust removal system at the current moment is considered when the optimal running frequency is determined, so that the determined optimal running frequency is more attached to the running state of the dust removal system, and the accuracy of the optimal running frequency is improved. And moreover, the operation limiting conditions of the dust removing system are considered when the optimal operation frequency is determined, so that the problems that the dust removing system works in a limiting state and the normal use of the dust removing system is influenced due to the fact that the operation frequency is simply regulated can be avoided. In addition, the scheme can solve the optimal running frequency of the fan based on the system state parameters of the dust removal system, so that the fan runs in an optimal working state, and the inhaled air quantity of the fan is optimal in the optimal state, thereby reducing the energy consumption and the noise generated by the system on the basis of ensuring the dust removal effect and improving the working efficiency of the dust removal system.
According to another embodiment of the present invention, in the method for controlling a fan of a dust removal system disclosed in the embodiment of the present invention, in step S1, system state parameters include: the valve opening of each control valve, the dust concentration at the suction inlet of each dust removing device, the actual running frequency of the fan and the air pressure in each dust removing air passage. And, after step S1, further includes:
s1': and sequentially performing signal amplification processing, filtering processing and analog-to-digital conversion processing on the acquired data of the system state parameters.
By adopting the scheme, the acquired data is subjected to signal amplification processing, filtering processing and analog-to-digital conversion processing, so that signals with higher quality, smaller noise and convenience in subsequent processing can be obtained, an accurate basis is provided for adjusting the optimal running frequency of the fan, and the suction air volume of the fan can be kept at the optimal air volume as far as possible.
According to another specific embodiment of the invention, the constraint conditions comprise an opening constraint condition of a valve opening, a concentration constraint condition of dust concentration, a frequency constraint condition of actual operating frequency and an air pressure constraint condition of air pressure in a dust removal air passage. And, step S2 includes:
S21: determining the current total flow demand of the dust removal system according to the data of the dust concentration at the current moment, and establishing an optimization objective function by taking the running frequency of the fan as an optimization object and the minimum energy consumption of the fan as an optimization object according to the data of the current total flow demand and the valve opening at the current moment; wherein, the dust concentration and the current total flow demand are in a proportional relation;
s22: determining opening constraint conditions according to valve opening limit values of all control valves, determining concentration constraint conditions according to dust concentration targets at suction inlets of all dust removing equipment, determining frequency constraint conditions according to operation frequency limit values of fans, and determining air pressure constraint conditions according to air pressure limit values in dust removing air passages;
s23: substituting the opening constraint condition, the concentration constraint condition, the frequency constraint condition, the air pressure constraint condition and the optimization objective function into an optimization algorithm, and determining the optimal running frequency of the fan by utilizing the optimization algorithm.
By adopting the scheme, the operation frequency of the fan is taken as an optimization object, the solved optimal solution represents the optimal operation frequency of the fan, the frequency converter of the fan is directly controlled according to the optimal operation frequency, so that the air quantity sucked by the fan is the optimal air quantity, the optimal operation frequency is not required to be calculated according to other parameters, and the control efficiency and the control precision are improved. And the constraint conditions are comprehensively determined by the operation constraint conditions of the dust removal system, so that the normal operation of the dust removal system can not be influenced when the fan operates according to the determined optimal operation frequency.
According to another specific embodiment of the present invention, the method for controlling a fan of a dust removal system disclosed in the embodiment of the present invention optimizes an objective function as follows:
。
the constraint conditions are as follows:
wherein, the minimum opening of the valve is 0, and the maximum opening of the valve is 100%; the minimum dust concentration is 0 mug/m and the maximum dust concentration is 100 mug/m; the minimum frequency range of the blower is 5Hz to 10Hz, and the maximum frequency range of the blower is 45Hz to 50Hz; the minimum air pressure is 0MPa, and the maximum air pressure is 300MPa.
The optimization algorithm comprises any one of genetic algorithm, gradient descent method and particle swarm optimization algorithm.
According to another embodiment of the present invention, the method for controlling a fan of a dust removal system disclosed in the embodiment of the present invention further includes, after step S3:
s3': judging whether the data of the dust concentration corresponding to the dust removal system is in a preset concentration threshold range and whether the data of the air pressure is in a preset air pressure threshold range or not after the operation frequency of the fan is adjusted according to the optimal operation frequency;
if yes, determining the optimal running frequency of the fan corresponding to the next moment by using an optimized objective function determined according to the current total flow demand and the data of the valve opening at the current moment at the next moment after the current moment;
If not, the data of the dust concentration is collected again at the next moment, the updated total flow requirement of the dust removal system is determined again according to the data of the collected dust concentration, the running frequency of the fan is taken as an optimization object according to the updated total flow requirement and the data of the valve opening at the next moment, the optimized objective function of the fan is reestablished by taking the minimum energy consumption of the fan as the optimization object, so that the updated objective function is obtained, and the optimal running frequency of the fan is determined by utilizing an optimization algorithm according to the updated objective function and constraint conditions.
By adopting the scheme, the real-time dynamic adjustment of the optimized objective function can be realized, so that the optimal operation frequency calculated according to the optimized objective function gradually approaches to the real optimal operation frequency, the calculation accuracy of the optimal operation frequency is improved, the control accuracy of the suction air quantity of the fan is further improved, and the effects of energy conservation and consumption reduction are further achieved.
According to another specific embodiment of the invention, the method for controlling the fan of the dust removing system disclosed by the embodiment of the invention has the preset concentration threshold value ranging from 0 mug/m to 20 mug/m; the preset air pressure threshold range is less than or equal to 200MPa.
According to another embodiment of the present invention, in the method for controlling a fan of a dust removal system disclosed in the embodiment of the present invention, in step S3, the control algorithm is a feedback control algorithm. And, step S3 includes:
s31: obtaining a control model of a feedback control algorithm:
wherein,,for controlling the output of the model->For controlling the transfer function of the model +.>Is proportional gain->For the optimal operating frequency +.>Is the actual operating frequency;
s32: determining the proportional gain of the control model according to the optimal operation frequency and the actual operation frequency at the initial moment;
s33: calculating the output frequency of the control model under the actual operating frequency at the current moment according to the optimal operating frequency, the proportional gain and the actual operating frequency at the current moment;
s34: correcting the proportional gain according to the difference value between the output frequency and the optimal operating frequency to obtain an updated proportional gain;
s35: the data of the actual operating frequency is collected again at the next moment, and the output frequency of the control model under the actual operating frequency at the next moment is calculated according to the updated proportional gain, the optimal operating frequency and the data of the collected actual operating frequency;
s36: steps S34 to S35 are repeated until the output frequency of the control model is equal to the optimal operating frequency.
By adopting the scheme, the operating frequency of the fan is regulated by adopting the feedback control algorithm, so that the frequency of the motor cannot fluctuate greatly when the fan is regulated, the fan can be maintained in a stable state when the fan is sucked, the condition that the air is sucked suddenly too much or too little cannot occur, the occurrence of surging is avoided, and the stability of the system is improved.
According to another specific embodiment of the present invention, in the method for controlling a fan of a dust removal system disclosed in the embodiment of the present invention, in step S3, the control algorithm is a fuzzy control algorithm. And, step S3 includes:
s31': the valve opening, the dust concentration, the actual operating frequency and the air pressure are used as input variables of fuzzy control, input fuzzy subsets which are related to the valve opening, the dust concentration, the actual operating frequency and the air pressure are respectively defined, and the operating frequency of a fan is used as an output variable of the fuzzy control;
s32': formulating a rule base concerning input variables of the fuzzy control and output variables of the fuzzy control based on time constraints at the time of frequency adjustment;
s33': calculating a fuzzy subset of the output variables according to the rule base and the input fuzzy subset;
s34': performing defuzzification processing on the fuzzy subset of the output variable to obtain the valve opening at the current moment, the dust concentration at the current moment, the actual operating frequency at the current moment and the adjusting frequency under the air pressure at the current moment, and adjusting the operating frequency of the fan according to the adjusting frequency;
S35': judging whether the operating frequency of the fan regulated according to the regulating frequency is equal to the optimal operating frequency;
if yes, finishing the fuzzy control;
if not, updating the rule base and the input fuzzy subset according to the deviation between the adjusted running frequency of the fan and the optimal running frequency, and returning to the step S34'.
By adopting the scheme, the operation frequency of the fan is controlled by adopting the fuzzy control algorithm, so that the fan has higher convenience and robustness, and the efficiency of air quantity control is improved.
The embodiment of the invention also discloses a control system of the fan of the dust removing system, which is used for executing the control method of the fan of the dust removing system described in any embodiment. And, the control system of the fan of the dust pelletizing system includes: the acquisition module acquires data of system state parameters representing the actual running state of the dust removal system at the current moment; the control module is in communication connection with the acquisition module, acquires data of system state parameters at the current moment from the acquisition module, determines an optimization objective function of the fan by taking the running frequency of the fan as an optimization object and taking the minimum energy consumption of the fan as a target according to the data of the system state parameters, determines constraint conditions related to the system state parameters according to the running constraint conditions of the dust removal system, determines the optimal running frequency of the fan corresponding to the current moment according to the optimization objective function and the constraint conditions and by utilizing an optimization algorithm, and generates a control signal according to the optimal running frequency; the frequency adjusting module is respectively in communication connection with the control module and the fan, and adjusts the running frequency of the fan according to the control signal obtained from the control module.
According to another specific embodiment of the invention, the acquisition module comprises a data acquisition unit, a signal processing unit and a data processing unit. The device comprises a data acquisition unit, a dust collection unit and a dust collection unit, wherein the data acquisition unit comprises a valve opening sensor, a dust concentration sensor, a fan power sensor and an in-pipe pressure sensor, the valve opening sensor acquires valve opening data of a control valve, the dust concentration sensor acquires dust concentration data at a suction inlet of dust collection equipment, the fan power sensor acquires power data of a fan, the actual running frequency of the fan is calculated according to the power data, and the in-pipe pressure sensor acquires air pressure data in a dust collection air passage; the signal processing unit comprises an amplifier, a filter and an analog-to-digital converter; the amplifier acquires valve opening data, dust concentration data, actual running frequency of the fan and air pressure data from the valve opening sensor, the dust concentration sensor, the fan power sensor and the in-pipe pressure sensor respectively, and performs signal amplification processing; the filter acquires the signal subjected to the signal amplification processing from the amplifier and performs the filtering processing; the analog-to-digital converter acquires the signals subjected to the filtering processing from the filter and executes analog-to-digital conversion processing; the data processing unit comprises a data collector, a data memory, a data processor and a communication interface; the data acquisition device acquires the digital signal subjected to analog-to-digital conversion processing from the analog-to-digital converter and converts the digital signal into a machine-readable signal; the data memory acquires a machine-readable signal from the data collector and stores the machine-readable signal; the data processor acquires the machine-readable signal from the data memory and performs screening processing on the machine-readable signal; the communication interface acquires the signals subjected to screening processing from the data processor and sends the signals subjected to screening processing to the control module. And the frequency adjusting module is a frequency converter.
The embodiment of the invention also discloses an electronic device which comprises a transceiver, a processor and a memory which is in communication connection with the processor; the method comprises the steps that a transceiver obtains a task to be operated and configuration information of the task to be operated; the memory stores computer-executable instructions; the processor executes computer-executable instructions stored in the memory to implement the method of controlling the fans of the dust removal system as described in any of the embodiments above.
The embodiment of the invention also discloses a computer readable storage medium, wherein computer executing instructions are stored in the computer readable storage medium, and the computer executing instructions are used for realizing the control method of the fan of the dust removing system in any embodiment.
The beneficial effects of the invention are as follows:
according to the control method and system for the fan of the dust removal system, the optimal running frequency of the fan can be solved based on the system state parameters of the dust removal system, so that the fan runs in an optimal working state to suck better air quantity, energy consumption and noise generated by the system are reduced, and the working efficiency of the dust removal system is improved.
Drawings
Fig. 1 is a schematic structural diagram of a dust removal system according to an embodiment of the present invention;
Fig. 2 is a flow chart of a control method of a fan of a dust removal system according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a solution flow for an optimal operating frequency of a wind turbine according to an embodiment of the present invention;
FIG. 4 is a schematic flow chart of fan frequency control provided by an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a control system of a fan of a dust removal system according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Reference numerals illustrate:
1. a blower; 2. a dust removal device; 3. a dust removal air passage; 4. a control valve; 5. an acquisition module; 51. a data acquisition unit; 52. a signal processing unit; 53. a data processing unit; 6. a control module; 7. a frequency adjustment module; 121. a transceiver; 122. a processor; 123. a memory.
Detailed Description
Examples
In order to solve the problems of high energy consumption and high noise generated by a fan caused by limited fan adjustment precision and incapability of sucking the optimal air quantity in the dust removing system in the prior art, the embodiment provides a control method of the fan of the dust removing system. First, referring to fig. 1, the dust removing system includes a fan 1 and at least one dust removing device 2, each dust removing device 2 is communicated with an air inlet of the fan 1 via a corresponding dust removing air passage 3, and a control valve 4 is disposed in each dust removing air passage 3. The blower 1 sucks the gas to remove dust. The dust removing device 2 is also a dust hood arranged at each dust removing point. The dust removal air flue 3 is communicated with the fan 1 and the corresponding dust removal equipment 2, and the control valve 4 is used for controlling the opening degree of the dust removal air flue 3. When a certain dust removing point needs to remove dust, the fan 1 is opened, the control valve 4 in the corresponding dust removing air passage 3 is opened, and the dust hood can suck gas and dust at the dust removing point at the same time, so that dust removal is realized. In fact, the air intake of the fan 1 is related to its operating frequency and determines the energy consumption of the fan 1, the dust removal effect, and the noise generated by the system. How to reduce the energy consumption of the fan 1 as much as possible on the premise of ensuring the dust removal effect, so that the suction air quantity of the fan 1 reaches the optimal value, and the noise generated by the system is reduced. To achieve the above objective, the present embodiment provides a method for controlling the blower 1, that is, a method for controlling the intake air volume of the blower 1, specifically, controlling the operation frequency of the blower 1 to control the intake air volume thereof.
Further, referring to fig. 2, the method for controlling the fan of the dust removing system includes the steps of:
s1: acquiring data of system state parameters representing the actual running state of the dust removal system at the current moment;
s2: determining an optimized objective function of the fan by taking the operating frequency of the fan as an optimized object and taking the minimum energy consumption of the fan as a target according to the data of the system state parameters at the current moment, determining a constraint condition related to the system state parameters according to the operation limiting condition of the dust removal system, and determining the optimal operating frequency of the fan corresponding to the current moment according to the optimized objective function and the constraint condition and by utilizing an optimization algorithm;
s3: and adjusting the operating frequency of the fan according to the optimal operating frequency and by a preset control algorithm.
The following is a description of the above steps. When the operation frequency of the fan is to be adjusted to work in an operation state with a better suction air quantity and a low exhaustion quantity, data of parameters representing the actual operation state of the dust removing system are required to be acquired first, and because the parameter data related to the operation state may be continuously changed when the dust removing system is in operation, the data are required to be acquired in real time or in a shorter time interval, so that the current operation state of the dust removing system can be accurately represented. These parameters characterizing the actual operating state of the dust removal system are collectively referred to as system state parameters, and may be, for example, the power of the blower, the dust concentration at the dust removal point, etc. (step S1). After the data of the system state parameters are obtained, an optimization objective function is required to be determined according to the parameter data representing the actual running state of the dust removal system at the current moment. The optimized objective function is an objective function for optimizing the running frequency of the fan. Specifically, in this embodiment, since the operation frequency of the fan that reduces the power consumption as much as possible on the premise of satisfying the dust removal effect needs to be solved to enable the fan to inhale a suitable air volume, when determining the optimization objective function, the obtained data of the system state parameter is used as a data support, the operation frequency of the fan is used as an optimization object, and the minimum energy consumption of the fan is used as a target. Further, because the dust removal system needs to meet certain conditions during operation, for example, the pressure in the dust removal air flue is not too high, otherwise, the risk of pipe explosion is high; or the concentration of the dust removing point needs to meet a certain concentration limit value, and can be regarded as effective dust removal and the like. Therefore, after the optimization objective function is determined, constraint conditions are determined according to the operation constraint conditions of the dust removal system, and the constraint conditions are all constraint conditions related to system state parameters. After determining the constraint condition, the optimization objective function and the constraint condition can be used as the input of the optimization algorithm, and the optimization algorithm is utilized to output the optimal running frequency of the fan corresponding to the current time (step S2). And the optimal operating frequency of the fan output by the optimization algorithm, namely the optimal operating frequency corresponding to the fan when the dust removing system operates in the current state. If the fan runs at the frequency, the best suction air quantity can be ensured, the dust removal effect is ensured, and the fan can be in a lower power consumption state. At this time, the current operating frequency of the fan can be adjusted by using a control algorithm according to the optimal operating frequency so that the current operating frequency is gradually close to and equal to the optimal operating frequency, and further the control of the suction air quantity of the fan is realized (step S3).
The method comprises the steps of acquiring data of a system parameter state representing the actual operation state of the dust removal system at the current moment, determining the optimal operation frequency of the fan according to the acquired data, and considering the actual operation state of the dust removal system at the current moment, so that the determined optimal operation frequency is more attached to the operation state of the dust removal system, the accuracy of the optimal operation frequency is improved, and the control precision of the suction air quantity of the fan is also improved. Further, according to the data of the system state parameters, the operating frequency of the fan is used as an optimization object, the operation limiting condition of the dust removal system is used for determining constraint conditions, the operating frequency of the fan is directly used as an optimization object, the optimized output result is also the operating frequency of the fan, then the actual operating frequency of the fan is regulated according to the optimized result, the operating frequency is directly calculated, the operating frequency is regulated, the optimal air quantity inhaled by the fan can be obtained, and compared with a mode of outputting other parameters and converting the parameters into the operating frequency, the efficiency and the accuracy can be improved. And moreover, the operation limiting conditions of the dust removing system are considered when the optimal operation frequency is determined, so that the problems that the dust removing system works in a limiting state and the normal use of the dust removing system is influenced due to the fact that the operation frequency is simply regulated can be avoided. In addition, the accuracy of the optimal operating frequency can be further improved by utilizing an optimization algorithm to determine the optimal operating frequency. Furthermore, the operation frequency of the fan is adjusted according to the optimal operation frequency and by a preset control algorithm, so that the actual operation frequency of the fan is equal to the optimal operation frequency, and the fan can inhale the optimal air quantity when working at the optimal operation frequency, thereby working in a lower energy consumption state on the basis of achieving the better dust removal effect, improving the working efficiency of a dust removal system, reducing the energy consumption of the system and reducing the noise generated by the system.
Further, in the method for controlling a fan of the dust removal system according to the present invention, in step S1, the system state parameters include: the valve opening of each control valve, the dust concentration at the suction inlet of each dust removing device, the actual running frequency of the fan and the air pressure in each dust removing air passage. Specifically, the valve opening degree of each control valve may be measured via a valve opening degree sensor provided at each control valve. The dust concentration at the suction port of each dust removing apparatus can be measured via a dust concentration sensor provided at the suction port of each dust removing apparatus. The dust concentration measured here is the dust concentration after the dust removal at the dust removal point, and in order to determine whether the dust removal effect is expected, a dust concentration sensor is provided outside the suction port of each dust removal device. The actual running frequency of the fan is measured by a fan power sensor connected with the fan, and the fan power sensor can obtain the actual running frequency of the fan through calculation after obtaining the fan power because the running frequency of the fan and the power are in a linear pipeline. The air pressure in each dust removing air passage is measured by an in-pipe pressure sensor arranged in each dust removing air passage.
Further, in the method for controlling a fan of the dust removal system according to the present invention, after step S1, the method further includes:
s1': and sequentially performing signal amplification processing, filtering processing and analog-to-digital conversion processing on the acquired data of the system state parameters.
That is, step S1 only acquires the data of the system state parameters, but the data needs to be subjected to a certain data processing to be used for the subsequent optimization calculation. In this embodiment, the data is sequentially subjected to signal amplification processing, filtering processing, and analog-to-digital conversion processing by an amplifier, a filter, and an analog-to-digital converter (step S1'). The method has the steps that the data is processed, so that signals with higher quality, smaller noise and convenience for subsequent processing can be obtained, and an accurate basis is provided for adjusting the optimal running frequency of the fan.
Further, in the method for controlling the fan of the dust removal system according to the present invention, after acquiring the data of the system state parameter and performing data processing, the subsequent calculation for solving the optimal operation frequency can be performed. Referring to fig. 3, the method mainly comprises the steps of establishing an optimized objective function, defining constraint conditions, selecting an optimization algorithm according to the complexity of a official network (the complexity of a dust removal system), solving the optimal operating frequency, updating the optimal operating frequency of a fan and dynamically adjusting in real time. Specifically, the constraint conditions include an opening constraint condition of a valve opening, a concentration constraint condition of dust concentration, a frequency constraint condition of an actual operating frequency, and an air pressure constraint condition of air pressure in a dust removal air passage. More specifically, the method for updating the optimal operating frequency of the fan specifically adopts an updated optimization objective function, and the optimal operating frequency is redetermined according to the updated optimization objective function.
Still further, in the method for controlling a fan of the dust removing system according to the present invention, step S2 includes:
s21: determining the current total flow demand of the dust removal system according to the data of the dust concentration at the current moment, and establishing an optimization objective function by taking the running frequency of the fan as an optimization object and the minimum energy consumption of the fan as an optimization object according to the data of the current total flow demand and the valve opening at the current moment; wherein, the dust concentration and the current total flow demand are in a proportional relation;
s22: determining opening constraint conditions according to valve opening limit values of all control valves, determining concentration constraint conditions according to dust concentration targets at suction inlets of all dust removing equipment, determining frequency constraint conditions according to operation frequency limit values of fans, and determining air pressure constraint conditions according to air pressure limit values in dust removing air passages;
s23: substituting the opening constraint condition, the concentration constraint condition, the frequency constraint condition, the air pressure constraint condition and the optimization objective function into an optimization algorithm, and determining the optimal running frequency of the fan by utilizing the optimization algorithm.
That is, when determining the optimum operating frequency of the blower, the total flow demand of the dust removal system at the current dust concentration is first determined from the current dust concentration data. That is, the air quantity which is needed to be sucked by the fan is determined to suck dust at the dust removing point, so that the dust concentration at the dust removing point reaches the requirement. In addition, the dust concentration and the total flow demand are generally in a proportional relationship, namely, the higher the dust concentration is, the larger the air quantity required to be sucked by the fan is. And for fans, the energy consumption is related to the total flow demand and the operating frequency. In order to achieve the dust removal effect, the actual flow needs to be adjusted to be matched with the total flow demand, and the actual flow is related to the valve opening, so that the operation frequency of the fan, the valve opening and the total flow demand are used as variables of the function when the optimization objective function is established. It should be noted that, at the current time, the total flow demand and the valve opening are both constant. After determining the total flow demand and the valve opening data at the current moment, the operation frequency of the fan is taken as an optimization object, and the minimum energy consumption of the fan is taken as an optimization object to establish an optimization objective function according to the data (step S21). Specifically, the optimization objective function is:
In the optimization process, the actual operation condition of the dust removing system needs to be considered, and the hardware of the dust removing system has some operation limitation, so after the establishment of the optimization objective function is completed, constraint conditions need to be defined to meet the basic constraint conditions of the dust removing system, such as the frequency of the fan is within a predetermined range, the opening degree of the valve is within a predetermined range, and the requirement of minimum air volume is met (step S22). Specifically, the constraint conditions are:
wherein, the minimum opening of the valve is 0, and the maximum opening of the valve is 100%. That is to say the valve opening needs to be between 0 and 100%, otherwise the opening of the control valve will not be controlled.
The minimum dust concentration was 0. Mu.g/m.multidot.w, and the maximum dust concentration was 100. Mu.g/m. That is, the dust concentration is required to be in the range of 0. Mu.g/m to 100. Mu.g/m, otherwise, the dust concentration exceeding 100. Mu.g/m is regarded as a concentration which does not satisfy the dust removal requirement and does not achieve the dust removal effect.
The minimum frequency range of the blower is 5Hz to 10Hz, and the maximum frequency range of the blower is 45Hz to 50Hz. That is, the fan should be operated at a frequency ranging from 5Hz to 50Hz, for example, and excessive or insufficient frequency may cause vibration of internal components of the fan, which may cause damage to the fan.
The minimum air pressure is 0MPa, and the maximum air pressure is 300MPa. That is, the air pressure in the dust removing air passage cannot exceed 300MPa, otherwise the dust removing air passage is easy to burst.
After determining the constraint conditions, substituting each constraint condition and the optimization objective function into the selected optimization algorithm, and outputting the optimal running frequency of the fan by using the optimization algorithm (step S23). Specifically, the optimization algorithm that can be selected in this embodiment includes a genetic algorithm, a gradient descent method, a particle swarm optimization algorithm, and the like. As to what algorithm is selected, it is required to comprehensively determine according to the complexity of the dust removal system, the complexity of the variables to be solved, and the requirement of the solving speed.
More specifically, the genetic algorithm is not easy to enter the local optimal solution by mistake, the solving precision is high, but if the complexity of the calculated problem is high, the calculation time required by the calculation is longer. Therefore, the method is suitable for the conditions that the accuracy requirement on the calculation result is high, but the complexity of the system and the complexity of the problem are low, and the solving speed requirement is low. The gradient descent method has a relatively low convergence rate when approaching to the optimal solution, so that the method is suitable for the condition of low requirement on the solving speed, but the accuracy of the optimal solution determined by the gradient descent method is relatively high. The particle swarm algorithm can process the problems with comprehensive types and simpler calculation modes, and is suitable for the conditions of higher system complexity and problem complexity and higher requirement on solving speed. In this embodiment, if the optimal operating frequency needs to be calculated quickly, a particle swarm algorithm may be selected. If the optimal operating frequency needs to be calculated accurately, a genetic algorithm or gradient descent method may be selected. Because the variable required for solving the optimal running frequency is fewer, the solving problem is simpler, and the complexity of the dust removing system is not high, any one of the three algorithms can be selected as an optimization algorithm according to the calculation speed and the precision. If the variables in the optimized objective function are more, the difficulty of solving the problem is larger, and the method is more suitable for the particle swarm algorithm. The above algorithm may be selected by those skilled in the art according to actual needs, and this embodiment is not limited thereto.
The method comprises the steps that when the optimal operation frequency of the fan is determined, the total flow demand and the valve opening are used as variables, the operation frequency of the fan is used as an optimization object, the energy consumption of the fan is minimum, variables in the optimization objective function only comprise the total flow demand, the valve opening and the operation frequency, and the total flow demand and the valve opening are constant values at the current moment, so that the three variables are used as the variables of the optimization objective function, and the calculated amount is small when the optimization algorithm is used for solving. And the running frequency of the fan is taken as an optimization object, the solved optimal solution represents the optimal running frequency of the fan, the frequency converter of the fan is directly controlled according to the optimal running frequency, so that the fan can suck the optimal air quantity, the optimal running frequency is not required to be calculated according to other parameters, and the control efficiency and the control precision are improved. Further, the constraint conditions are comprehensively determined according to the operation constraint conditions of the dust removal system, so that the normal operation of the dust removal system can not be influenced when the fan operates according to the determined optimal operation frequency. In addition, the optimization algorithm is comprehensively selected according to factors such as the complexity of the dust removal system and the complexity of solving the problem, so that the efficiency and the accuracy of solving the optimal operating frequency can be further improved.
Further, in the method for controlling a fan of the dust removal system according to the present invention, in step S3, the operating frequency of the fan needs to be adjusted by using a certain control algorithm, so that the actual operating frequency of the fan is equal to the optimal operating frequency. The present embodiment provides two different control algorithms, a feedback control algorithm and a fuzzy control algorithm, respectively. Whichever control algorithm involves the steps of modeling the system, designing the controller, writing the algorithm, and controller implementation and debugging as shown in fig. 4. Specifically, the system model is established by a pointer to establish the system model of the operation of the dust removal system, and the system model mainly describes the interaction relationship among the fan, the control valve and the dust removal air passage, so that a theoretical basis is provided for the subsequent control algorithm design. Wherein the system model of the dust removal system comprises a series model of flow resistanceWherein->Flow resistance of each pipeline connected in series, +.>Is the total flow resistance after series connection; parallel model of flow resistance->The method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>Flow resistance of each pipeline in parallel, +.>Is the total flow resistance after series connection; pressure model->Wherein->For flow resistance, is->For flow rate->Is the pressure. Specifically, the controller is designed, i.e. the controller is designed according to the system model and the actual operation conditions. Next, two different control algorithms provided in the present embodiment are explained.
In a preferred embodiment according to the present invention, in step S3, the control algorithm is a feedback control algorithm. Specifically, in this embodiment, negative feedback adjustment is selected to adjust the operating frequency of the fan, so that the operating frequency of the fan is continuously close to the optimal operating frequency. The control strategy of the negative feedback regulation is to continuously reduce the difference between the actual operating frequency and the optimal operating frequency of the fan so that the difference is continuously reduced. According to the embodiment, the operation frequency of the fan is adjusted by adopting a feedback control algorithm, so that the frequency of the motor cannot be greatly fluctuated during adjustment, the fan can be maintained in a stable state during gas suction, the condition that the gas is suddenly sucked too much or too little cannot occur, the occurrence of surge is avoided, and the stability of a system is improved.
And, step S3 includes:
s31: obtaining a control model of a feedback control algorithm:
wherein,,for controlling the output of the model->For controlling the transfer function of the model +.>Is proportional gain->For the optimal operating frequency +.>Is the actual operating frequency;
s32: determining the proportional gain of the control model according to the optimal operation frequency and the actual operation frequency at the initial moment;
s33: calculating the output frequency of the control model under the actual operating frequency at the current moment according to the optimal operating frequency, the proportional gain and the actual operating frequency at the current moment;
S34: correcting the proportional gain according to the difference value between the output frequency and the optimal operating frequency to obtain an updated proportional gain;
s35: the data of the actual operating frequency is collected again at the next moment, and the output frequency of the control model under the actual operating frequency at the next moment is calculated according to the updated proportional gain, the optimal operating frequency and the data of the collected actual operating frequency;
s36: steps S34 to S35 are repeated until the output frequency of the control model is equal to the optimal operating frequency.
Specifically, it is assumed that the control model of the feedback control algorithm can be expressed as:wherein->For system output, ++>For input to the controller, +.>Is the transfer function of the system. The setting objective of the controller is to let the output of the system +.>Near desired output->. In accordance with the principles of a proportional controller, the output of the controller can be expressed as:wherein (1)>Is a proportional gain for adjusting the response strength of the controller. Input of the controller->Substituting into the system model, a closed loop transfer function can be obtained: />(step S31).
The above equation is arranged to obtain:. The above equation represents the system output +.>And (2) desired output->Transfer function relationship between the two. The appropriate proportional gain can be chosen according to the desired system behavior and performance requirements >To realize the design of the controller (step S32).
Then, the output signal of the controller is calculated according to an algorithm using the controller, and the signal is adjusted according to the predicted system behavior and the desired output (step S33).
Thereafter, the parameters of the controller or the output signals of the controller are adjusted so that the output of the system gradually approaches the desired output according to the error between the output of the actual system and the desired output (step S34 and step S35).
Thereafter, steps S34 to S35 are repeated, and model prediction, controller design, and controller adjustment are continuously performed to achieve accurate control of the system (step S36).
In another preferred embodiment according to the present invention, in step S3, the control algorithm is a fuzzy control algorithm. The fuzzy control algorithm does not need an accurate mathematical model required in the process during control, and has higher use convenience. And the fuzzy control algorithm has stronger robustness, and can solve the problems of nonlinearity, strong coupling time-varying, hysteresis and the like in the control process. The embodiment adopts a fuzzy control algorithm to control the running frequency of the fan, and has higher convenience and robustness.
And, step S3 includes:
s31': the valve opening, the dust concentration, the actual operating frequency and the air pressure are used as input variables of fuzzy control, input fuzzy subsets which are related to the valve opening, the dust concentration, the actual operating frequency and the air pressure are respectively defined, and the operating frequency of a fan is used as an output variable of the fuzzy control;
s32': formulating a rule base concerning input variables of the fuzzy control and output variables of the fuzzy control based on time constraints at the time of frequency adjustment;
s33': calculating a fuzzy subset of the output variables according to the rule base and the input fuzzy subset;
s34': performing defuzzification processing on the fuzzy subset of the output variable to obtain the valve opening at the current moment, the dust concentration at the current moment, the actual operating frequency at the current moment and the adjusting frequency under the air pressure at the current moment, and adjusting the operating frequency of the fan according to the adjusting frequency;
s35': judging whether the operating frequency of the fan regulated according to the regulating frequency is equal to the optimal operating frequency;
if yes, finishing the fuzzy control;
if not, updating the rule base and the input fuzzy subset according to the deviation between the adjusted running frequency of the fan and the optimal running frequency, and returning to the step S34'.
Specifically, in performing the fuzzy control, first, input variables and output variables of the fuzzy controller are defined (step S31'). Thereafter, a rule base of the fuzzy controller is determined to embody the relationship between the respective input variables (step S32'). Next, a fuzzy set of output variables is calculated from the rule base and the fuzzy set of input variables (step S33'). The final result is then obtained by a defuzzification process (step S34'). In addition, in the control process of the fan, a rule base and a fuzzy set of the fuzzy controller can be adjusted in real time to improve the control precision (step S35').
Further, in the method for controlling a fan of the dust removal system according to the present invention, after step S3, the method further includes:
s3': judging whether the data of the dust concentration corresponding to the dust removal system is in a preset concentration threshold range and whether the data of the air pressure is in a preset air pressure threshold range or not after the operation frequency of the fan is adjusted according to the optimal operation frequency. Wherein the preset concentration threshold ranges from 0 mug/m to 20 mug/m; for example 0 μg/m, 10 μg/m, 20 μg/m, or other concentration values within this range; the preset air pressure threshold range is less than or equal to 200MPa; for example, it may be 10 MPa, 80 MPa, 150 MPa, 200MPa, or other air pressure values within this range.
If yes, determining the optimal running frequency of the fan corresponding to the next moment by using an optimized objective function determined according to the current total flow demand and the data of the valve opening at the current moment at the next moment after the current moment;
if not, the data of the dust concentration is collected again at the next moment, the updated total flow requirement of the dust removal system is determined again according to the data of the collected dust concentration, the running frequency of the fan is taken as an optimization object according to the updated total flow requirement and the data of the valve opening at the next moment, the optimized objective function of the fan is reestablished by taking the minimum energy consumption of the fan as the optimization object, so that the updated objective function is obtained, and the optimal running frequency of the fan is determined by utilizing an optimization algorithm according to the updated objective function and constraint conditions.
Specifically, the preset concentration threshold range and the preset air pressure threshold range are ranges indicating that the dust removing system is in a preferred operation state, that is, when the fan operates at the optimal operation frequency, if concentration data at a dust removing point can be in the preset concentration threshold range and air pressure in a dust removing air passage is in the preset air pressure threshold range, the dust removing system is in the preferred operation state at the moment, correspondingly, the optimal operation frequency is also a relatively accurate optimal operation frequency, and an optimization objective function adopted when determining the optimal operation frequency is also an optimization objective function with better precision and various parameters. In this case, the optimal optimization objective function selected this time can still be used as the optimization objective function when the optimal operation frequency is determined next time, thereby improving the calculation efficiency.
However, if the fan is operated at the optimal operation frequency, the concentration of the dust removing point is not in the preset concentration threshold range, or the air pressure in the dust removing air passage is not in the preset air pressure threshold range, the dust removing system may not reach the optimal operation state at this time, and accordingly, the optimal operation frequency may not be the most accurate operation frequency, and the accuracy and various parameters of the optimization objective function adopted in determining the optimal operation frequency may not reach the optimal range yet. In this case, dust concentration data can be collected again and the total flow demand can be determined when the optimal operating frequency is determined next time, a new optimization objective function can be established according to the obtained data, and the optimal operating frequency can be solved according to the determined optimization objective function.
By the method, the optimal running frequency calculated according to the optimal objective function can be gradually approaching to the real optimal running frequency, so that the calculation accuracy of the optimal running frequency is improved, and the effects of energy conservation and consumption reduction are further achieved. That is, if the actual optimal operating frequency is 30Hz and the optimal operating frequency calculated by the current optimal objective function is 27Hz, the concentration of the dust removing point and the air pressure in the dust removing air passage may not reach the optimal range after the fan is operated at the optimal operating frequency, and at this time, the optimal objective function may be adjusted, so that the optimal operating frequency determined according to the optimal objective function is continuously approaching to 30Hz, so that the air volume inhaled by the fan reaches the optimal value, thereby further achieving the effects of energy saving and consumption reduction.
Examples
Based on the above-mentioned control method of the fan of the dust removing system, the present embodiment provides a control system of the fan of the dust removing system, for executing the control method of the fan of the dust removing system described in the above-mentioned embodiment.
Further, referring to fig. 5, the control system includes an acquisition module 5, a control module 6, and a frequency adjustment module 7. Wherein the acquisition module 5 acquires data of system state parameters representing the actual running state of the dust removal system at the current moment. The control module 6 is in communication connection with the acquisition module 5, acquires data of system state parameters at the current moment from the acquisition module 5, determines an optimization objective function of the fan by taking the operation frequency of the fan as an optimization object and taking the minimum energy consumption of the fan as a target according to the data of the system state parameters, determines constraint conditions related to the system state parameters according to operation limiting conditions of the dust removal system, determines the optimal operation frequency of the fan corresponding to the current moment according to the optimization objective function and the constraint conditions and by utilizing an optimization algorithm, and generates a control signal according to the optimal operation frequency. The frequency adjusting module 7 is respectively in communication connection with the control module 6 and the fan, and adjusts the running frequency of the fan according to the control signal obtained from the control module 6, so that the air quantity sucked by the fan reaches the optimal value.
Further, in the control system of the blower of the dust removing system according to the present invention, the acquisition module 5 includes a data acquisition unit 51, a signal processing unit 52, and a data processing unit 53. The data acquisition unit 51 includes a valve opening sensor, a dust concentration sensor, a fan power sensor, and an in-pipe pressure sensor. The dust concentration sensor acquires dust concentration data at the suction inlet of the dust removing device, the fan power sensor acquires power data of the fan, the actual running frequency of the fan is calculated according to the power data, and the in-tube pressure sensor acquires air pressure data in a dust removing air passage.
The signal processing unit 52 includes an amplifier, a filter, and an analog-to-digital converter. The amplifier acquires valve opening data, dust concentration data, actual running frequency of the fan and air pressure data from the valve opening sensor, the dust concentration sensor, the fan power sensor and the in-pipe pressure sensor respectively, and performs signal amplification processing. Specifically, the amplifier is used for amplifying the weak signal output by the sensor for subsequent processing. The filter acquires the signal subjected to the signal amplification processing from the amplifier and performs the filtering processing. Specifically, the filter is used for eliminating noise in the signal and improving the signal quality. More specifically, the filter may be an analog filter (e.g., a low-pass filter, a high-pass filter, a band-pass filter, etc.), or may be a digital filter (e.g., a moving average filter, a termination filter, etc.), and the embodiment is not particularly limited. The analog-to-digital converter acquires the filtered signal from the filter and performs analog-to-digital conversion processing. Specifically, the analog-to-digital converter converts the analog signal into a digital signal, so that the subsequent data acquisition and processing are convenient. More specifically, the accuracy and sampling rate of the analog-to-digital converter may affect the signal processing effect, and in order to ensure the subsequent signal processing effect, in this embodiment, an analog-to-digital converter with higher accuracy and higher sampling rate is selected. As for the specific model thereof, those skilled in the art can select it according to the actual circumstances.
The data processing unit 53 comprises a data collector, a data memory, a data processor, and a communication interface. The data acquisition unit acquires the digital signal after the analog-to-digital conversion processing from the analog-to-digital converter and converts the digital signal into a machine-readable signal. Specifically, the data collector is configured to receive the digital signals output by the analog-to-digital converter, and convert the signals into a data format (i.e., a machine-readable signal) recognizable by a computer. In this embodiment, the data acquisition card is used as a data acquisition device, which may be an independent hardware device, or may be a module integrated in a controller or a computer. The data memory obtains the machine-readable signal from the data collector and stores the machine-readable signal. The data processor is used for mainly processing, analyzing and calculating the data to extract useful information and provide basis for the control of a subsequent fan.
With such a structure, real-time data acquisition and processing is realized by the data acquisition unit 51, the signal processing unit 52, the data processing unit 53, and related data is transmitted to the control module 6. Thereby providing accurate basis for the frequency adjustment of the fan.
Still further, in the control system of the blower of the dust removing system according to the present application, the frequency adjusting module 7 is a frequency converter. Specifically, the frequency converter is electrically connected with the fan. That is, after the control module 6 calculates the optimal operation frequency of the fan, it sends an adjusting signal to the frequency converter to adjust the operation frequency of the fan through the regulator, thereby controlling the intake air volume of the fan.
By utilizing the control system provided by the embodiment, the optimal running frequency of the fan can be solved based on the system state parameters of the dust removal system, so that the fan runs in an optimal working state and sucks in better air quantity, the energy consumption and the noise generated by the system are reduced, and the working efficiency of the dust removal system is improved.
Examples
Based on the method for controlling the fan of the dust removal system provided by the embodiment, the embodiment provides electronic equipment.
Fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present application. Referring to fig. 6, the electronic device may include: a transceiver 121, a processor 122, a memory 123.
Processor 122 executes the computer-executable instructions stored in the memory, causing processor 122 to perform the aspects of the embodiments described above. The processor 122 may be a general-purpose processor including a central processing unit CPU, a network processor (network processor, NP), etc.; but may also be a digital signal processor DSP, an application specific integrated circuit ASIC, a field programmable gate array FPGA or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component.
Memory 123 is coupled to processor 122 via the system bus and communicates with each other, and memory 123 is configured to store computer program instructions.
The transceiver 121 may be used to acquire a task to be run and configuration information of the task to be run.
The system bus may be a peripheral component interconnect standard (peripheral component interconnect, PCI) bus or an extended industry standard architecture (extended industry standard architecture, EISA) bus, among others. The system bus may be classified into an address bus, a data bus, a control bus, and the like. For ease of illustration, the figures are shown with only one bold line, but not with only one bus or one type of bus. The transceiver is used to enable communication between the database access device and other computers (e.g., clients, read-write libraries, and read-only libraries). The memory may include random access memory (random access memory, RAM) and may also include non-volatile memory (non-volatile memory).
The electronic device provided by the embodiment of the application can be the terminal device of the embodiment.
The embodiment of the application also provides a chip for running instructions, which is used for executing the technical scheme of the control method of the fan of the dust removal system in the embodiment 1.
Examples
Based on the above-mentioned method for controlling a fan of a dust removal system, the present embodiment further provides a computer readable storage medium, where computer instructions are stored in the computer readable storage medium, and when the computer instructions run on a computer, the computer is caused to execute the technical scheme of the method for controlling a fan of a dust removal system according to the above-mentioned embodiment 1.
The embodiment of the application also provides a computer program product, which comprises a computer program, wherein the computer program is stored in a computer readable storage medium, and at least one processor can read the computer program from the computer readable storage medium, and the technical scheme of the control method of the fan of the dust removal system in the embodiment 1 can be realized when the at least one processor executes the computer program.
While the application has been shown and described with reference to certain preferred embodiments thereof, it will be understood by those skilled in the art that the foregoing is a further detailed description of the application with reference to specific embodiments, and it is not intended to limit the practice of the application to those descriptions. Various changes in form and detail may be made therein by those skilled in the art, including a few simple inferences or alternatives, without departing from the spirit and scope of the present application.
Claims (12)
1. The control method of the fan of the dust removing system is characterized in that the dust removing system comprises the fan and at least one dust removing device, each dust removing device is communicated with an air inlet of the fan through a corresponding dust removing air passage, and a control valve is arranged in each dust removing air passage; and is also provided with
The control method of the fan comprises the following steps:
s1: acquiring data of system state parameters representing the actual running state of the dust removal system at the current moment;
s2: determining an optimized objective function of the fan by taking the running frequency of the fan as an optimized object and taking the minimum energy consumption of the fan as a target according to the data of the system state parameters at the current moment, determining a constraint condition related to the system state parameters according to the running constraint condition of the dust removal system, and determining the optimal running frequency of the fan corresponding to the current moment according to the optimized objective function and the constraint condition and by utilizing an optimization algorithm;
s3: and adjusting the operating frequency of the fan according to the optimal operating frequency and by a preset control algorithm.
2. The method of controlling a fan of a dust removal system according to claim 1, wherein in the step S1, the system state parameters include:
The valve opening degree of each control valve, the dust concentration at the suction inlet of each dust removing device, the actual running frequency of the fan and the air pressure in each dust removing air passage; and is also provided with
After the step S1, the method further includes:
s1': and sequentially performing signal amplification processing, filtering processing and analog-to-digital conversion processing on the acquired data of the system state parameters.
3. The method of controlling a fan of a dust removal system according to claim 2, wherein the constraint conditions include an opening constraint condition of the valve opening, a concentration constraint condition of the dust concentration, a frequency constraint condition of the actual operating frequency, an air pressure constraint condition of an air pressure in the dust removal air passage;
the step S2 includes:
s21: determining the current total flow demand of the dust removal system according to the data of the dust concentration at the current moment, and establishing the optimization objective function by taking the running frequency of a fan as an optimization object and the minimum energy consumption of the fan as an optimization object according to the current total flow demand and the data of the valve opening at the current moment; wherein the dust concentration is in a proportional relationship with the current total flow demand;
S22: determining the opening constraint condition according to the valve opening limit value of each control valve, determining the concentration constraint condition according to the dust concentration target at the suction inlet of each dust removing device, determining the frequency constraint condition according to the running frequency limit value of the fan, and determining the air pressure constraint condition according to the air pressure limit value in the dust removing air channel;
s23: substituting the opening constraint condition, the concentration constraint condition, the frequency constraint condition, the air pressure constraint condition and the optimization objective function into the optimization algorithm, and determining the optimal running frequency of the fan by using the optimization algorithm.
4. A method of controlling a fan of a dust removal system according to claim 3, wherein the optimization objective function is:；
the constraint conditions are as follows:；
wherein the minimum opening of the valve is 0, and the maximum opening of the valve is 100%; the minimum dust concentration is 0 mug/m < w >; the minimum frequency range of the fan is 5Hz to 10Hz, and the maximum frequency range of the fan is 45Hz to 50Hz; the minimum air pressure is 0MPa, and the maximum air pressure is 300MPa;
The optimization algorithm comprises any one of a genetic algorithm, a gradient descent method and a particle swarm optimization algorithm.
5. The method for controlling a fan of a dust removing system according to claim 3 or 4, further comprising, after the step S3:
s3': judging whether the data of the dust concentration corresponding to the dust removal system is in a preset concentration threshold range or not and whether the data of the air pressure is in a preset air pressure threshold range or not after the operation frequency of the fan is adjusted according to the optimal operation frequency;
if yes, determining the optimal running frequency of the fan corresponding to the next moment by using the optimized objective function determined according to the current total flow requirement and the data of the valve opening at the current moment at the next moment after the current moment;
if not, the data of the dust concentration are collected again at the next moment, the updated total flow requirement of the dust removal system is determined again according to the collected data of the dust concentration, the running frequency of the fan is taken as an optimization object according to the updated total flow requirement and the data of the valve opening at the next moment, the optimized objective function of the fan is reestablished by taking the minimum energy consumption of the fan as the optimization object, so that the updated objective function is obtained, and the optimal running frequency of the fan is determined by utilizing the optimization algorithm according to the updated objective function and the constraint condition.
6. The method of controlling a blower of a dust removal system of claim 5, wherein the preset concentration threshold is in a range of 0 μg/m to 20 μg/m by;
the preset air pressure threshold range is less than or equal to 200MPa.
7. The method according to claim 5, wherein in the step S3, the control algorithm is a feedback control algorithm; and, the step S3 includes:
s31: obtaining a control model of the feedback control algorithm:the method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>For the output of the control model, +.>For the transfer function of the control model, +.>Is proportional gain->For the optimal operating frequency, < >>For the actual operating frequency;
s32: determining the proportional gain of the control model according to the optimal operating frequency and the actual operating frequency at the initial moment;
s33: calculating the output frequency of the control model under the actual operating frequency at the current moment according to the optimal operating frequency, the proportional gain and the actual operating frequency at the current moment;
s34: correcting the proportional gain according to the difference value between the output frequency and the optimal operating frequency to obtain an updated proportional gain;
S35: re-acquiring data of the actual operating frequency at the next moment, and calculating the output frequency of the control model at the actual operating frequency at the next moment according to the updated proportional gain, the optimal operating frequency and the re-acquired data of the actual operating frequency;
s36: repeating steps S34 to S35 until the output frequency of the control model is equal to the optimal operating frequency.
8. The method according to claim 5, wherein in the step S3, the control algorithm is a fuzzy control algorithm; and, the step S3 includes:
s31': taking the valve opening, the dust concentration, the actual operating frequency and the air pressure as input variables of fuzzy control, respectively defining the valve opening, the dust concentration, the actual operating frequency and the air pressure as input fuzzy subsets of the fuzzy control, and taking the operating frequency of the fan as output variables of the fuzzy control;
s32': formulating a rule base concerning input variables of the fuzzy control and output variables of the fuzzy control based on time constraints at the time of frequency adjustment;
S33': calculating a fuzzy subset of the output variables according to the rule base and the input fuzzy subset;
s34': performing defuzzification processing on the fuzzy subset of the output variables to obtain the valve opening at the current moment, the dust concentration at the current moment, the actual running frequency at the current moment and the adjusting frequency under the air pressure at the current moment, and adjusting the running frequency of the fan according to the adjusting frequency;
s35': judging whether the operating frequency of the fan adjusted according to the adjusting frequency is equal to the optimal operating frequency;
if yes, finishing the fuzzy control;
if not, updating the rule base and the input fuzzy subset according to the deviation between the adjusted running frequency of the fan and the optimal running frequency, and returning to the step S34'.
9. A control system of a fan of a dust removal system, characterized by performing a control method of a fan of a dust removal system according to any one of claims 1-8; and is also provided with
The control system of the fan of the dust removal system comprises:
the acquisition module acquires data of system state parameters representing the actual running state of the dust removal system at the current moment;
The control module is in communication connection with the acquisition module, acquires data of the system state parameter at the current moment from the acquisition module, determines an optimized objective function of the fan by taking the running frequency of the fan as an optimized object and taking the minimum energy consumption of the fan as a target according to the data of the system state parameter, determines a constraint condition related to the system state parameter according to the running constraint condition of the dust removal system, determines the optimal running frequency of the fan corresponding to the current moment according to the optimized objective function and the constraint condition and by utilizing an optimization algorithm, and generates a control signal according to the optimal running frequency;
the frequency adjusting module is respectively in communication connection with the control module and the fan, and adjusts the running frequency of the fan according to the control signal obtained from the control module.
10. The control system of a fan of a dust removal system of claim 9, wherein the acquisition module comprises a data acquisition unit, a signal processing unit, and a data processing unit; wherein the method comprises the steps of
The data acquisition unit comprises a valve opening sensor, a dust concentration sensor, a fan power sensor and an in-pipe pressure sensor, wherein the valve opening sensor acquires valve opening data of the control valve, the dust concentration sensor acquires dust concentration data at a suction inlet of the dust removal equipment, the fan power sensor acquires power data of the fan, the actual running frequency of the fan is calculated according to the power data, and the in-pipe pressure sensor acquires air pressure data in the dust removal air flue;
The signal processing unit comprises an amplifier, a filter and an analog-to-digital converter; the amplifier acquires the valve opening data, the dust concentration data, the actual running frequency of the fan and the air pressure data from the valve opening sensor, the dust concentration sensor, the fan power sensor and the in-pipe pressure sensor respectively, and performs signal amplification processing; the filter acquires the signal subjected to the signal amplification processing from the amplifier and performs filtering processing; the analog-to-digital converter acquires the signals subjected to the filtering processing from the filter and executes analog-to-digital conversion processing;
the data processing unit comprises a data collector, a data memory, a data processor and a communication interface; the data acquisition device acquires the digital signal subjected to the analog-to-digital conversion processing from the analog-to-digital converter and converts the digital signal into a machine-readable signal; the data memory acquires the machine-readable signal from the data collector and stores the machine-readable signal; the data processor acquires the machine-readable signal from the data memory and performs screening processing on the machine-readable signal; the communication interface acquires the signals subjected to screening processing from the data processor and sends the signals subjected to screening processing to the control module; and is also provided with
The frequency adjusting module is a frequency converter.
11. An electronic device, comprising: a transceiver, a processor, and a memory communicatively coupled to the processor;
the transceiver acquires a task to be operated and configuration information of the task to be operated;
the memory stores computer-executable instructions;
the processor executes computer-executable instructions stored in the memory to implement a method of controlling a fan of a dust removal system according to any one of claims 1-8.
12. A computer-readable storage medium, wherein computer-executable instructions are stored in the computer-readable storage medium, which when executed by a processor, are adapted to carry out a method of controlling a fan of a dust removal system according to any one of claims 1-8.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102072185A (en) * | 2011-01-27 | 2011-05-25 | 高毅夫 | Dust amount calculation optimal model-based energy-saving control method for dedusting fan |
| CN201851386U (en) * | 2010-11-18 | 2011-06-01 | 伦登风机(天津)有限公司 | Intelligent inducing fan controller |
| CN103452824A (en) * | 2013-09-06 | 2013-12-18 | 武汉理工大学 | Fan and water pump energy saving system adopting minimum power algorithm based on flow-power curve |
| WO2017047726A1 (en) * | 2015-09-18 | 2017-03-23 | 株式会社システム計装 | Dust collector control system and control method |
| KR20180080010A (en) * | 2017-01-03 | 2018-07-11 | (주)에어릭스 | Filtration and Dust Collection System and Apparatus for controlling Dust Collection System |
| JP2023029218A (en) * | 2021-08-20 | 2023-03-03 | 常州工学院 | Method and system for optimizing ventilation structure for boiler combustion |
-
2023
- 2023-08-11 CN CN202311006829.8A patent/CN116717496B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201851386U (en) * | 2010-11-18 | 2011-06-01 | 伦登风机(天津)有限公司 | Intelligent inducing fan controller |
| CN102072185A (en) * | 2011-01-27 | 2011-05-25 | 高毅夫 | Dust amount calculation optimal model-based energy-saving control method for dedusting fan |
| CN103452824A (en) * | 2013-09-06 | 2013-12-18 | 武汉理工大学 | Fan and water pump energy saving system adopting minimum power algorithm based on flow-power curve |
| WO2017047726A1 (en) * | 2015-09-18 | 2017-03-23 | 株式会社システム計装 | Dust collector control system and control method |
| KR20180080010A (en) * | 2017-01-03 | 2018-07-11 | (주)에어릭스 | Filtration and Dust Collection System and Apparatus for controlling Dust Collection System |
| JP2023029218A (en) * | 2021-08-20 | 2023-03-03 | 常州工学院 | Method and system for optimizing ventilation structure for boiler combustion |
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