CN113217448B - Energy-saving control system for air blower - Google Patents
Energy-saving control system for air blower Download PDFInfo
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- F04D—NON-POSITIVE-DISPLACEMENT PUMPS
- F04D27/00—Control, e.g. regulation, of pumps, pumping installations or pumping systems specially adapted for elastic fluids
- F04D27/007—Conjoint control of two or more different functions
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
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Abstract
The invention discloses an energy-saving control system for a blower, which belongs to the technical field of blowers and comprises an air inlet adjusting module, a server, an overhaul module, an operation adjusting module, a circuit detection module and an equipment temperature monitoring module, wherein the air inlet adjusting module is used for adjusting the temperature and the humidity of air inlet of the blower; through the arrangement of the maintenance module, the problems of the air blower can be found in time and repaired in time, the excessive waste of resources caused by the increase of the burden of the air blower is avoided, and meanwhile, maintenance personnel can be reasonably dispatched to repair the air blower; through the setting of circuit detection module, can in time maintain the ageing circuit of air-blower, avoid the wasting of resources, can in time prevent the emergence of incident simultaneously, avoid causing great loss of safety.
Description
Technical Field
The invention belongs to the technical field of blowers; in particular to an energy-saving control system for a blower.
Background
The blower mainly comprises the following six parts: motor, air cleaner, air-blower body, air chamber, base, oil drip mouth. The blower eccentrically operates by a rotor offset in a cylinder, and sucks, compresses, and discharges air by changing the volume between vanes in a rotor groove. During operation, the pressure difference of the blower is used to automatically deliver the lubricant to the oil dropping nozzle and drop it into the cylinder to reduce friction and noise while keeping the gas in the cylinder from flowing back. The blower conveys medium mainly clean air, clean coal gas, sulfur dioxide and other inert gases. Other flammable, explosive, corrosive, toxic and special gases can be produced and conveyed according to requirements. Most of fans have the phenomenon that a trolley is pulled by a large horse in the using process, and the flow, pressure, temperature and the like of gas need to be regulated frequently due to changes in production, process and the like; many units still adopt the lagging mode of adjusting the opening degree of a damper or a valve to adjust the flow, the pressure, the temperature and the like of the gas. This is actually a way to artificially increase the resistance and to meet the process and operating conditions requirements for gas flow regulation at the expense of wasted electrical energy and money. The backward adjustment mode not only wastes precious energy, but also has poor adjustment precision, is difficult to meet the requirements of modern industrial production, service and the like, and has serious negative effects.
The patent with the publication number of CN207363914U discloses an energy-conserving increase control system of blower unit, this system includes a plurality of air-blowers, every air-blower includes the impeller, the spiral case, the import stator, driving motor, host computer and PLC controller, the spiral case air outlet passes through the export reducing pipe and connects air-out pipeline and blow-down pipeline respectively, export reducing pipe internal diameter increases along airflow direction, be equipped with the one-way outlet valve of taking switch sensor on the air-out pipeline, be equipped with the atmospheric valve of taking second opening sensor on the blow-down pipeline, be equipped with first opening sensor on the import stator, export reducing pipe exit is equipped with pressure transmitter, first opening sensor, second opening sensor, switch sensor, pressure transmitter, driving motor and host computer are connected the PLC controller respectively.
Compared with the prior art, the air blower energy-saving control system has the advantages that the air blower energy-saving control system is simple in energy-saving measures and low in energy-saving efficiency, energy consumption is too large for solving the problem that resources cannot be fully utilized.
Disclosure of Invention
The invention aims to provide an energy-saving control system for a blower, which solves the problems that the blower consumes too much energy and resources cannot be fully utilized.
The purpose of the invention can be realized by the following technical scheme:
an energy-saving control system for a blower comprises an air inlet adjusting module, a server, a maintenance module, an operation adjusting module, a line detection module and an equipment temperature monitoring module;
the air inlet adjusting module is used for adjusting the temperature and humidity of air inlet of the air blower, and the specific adjusting method comprises the following steps:
step a 11: acquiring historical operating data of the blower;
step a 12: establishing a neural network model, wherein the neural network model comprises an input layer, a processing layer and an output layer, neuron nodes between every two adjacent layers are connected in a single direction, the output efficiency of a blower, the operation time of the blower and the air inlet energy consumption of the blower are selected as input parameters of the neural network, and the output result of the output layer of the neural network model is the optimal air inlet temperature and humidity of the blower;
step a 13: entering a training and learning stage of a neural network, selecting d groups of parameters of known output efficiency of the blower, operation time of the blower and air inlet energy consumption of the blower as input training samples, and establishing a relation between the optimal air inlet temperature and humidity of the blower and the input parameters by the neural network through training and learning;
step a 14: entering a prediction and simulation result analysis stage of a neural network, selecting e groups of parameters of known output efficiency of the blower, operation time of the blower, air intake energy consumption of the blower and optimal air intake temperature and humidity of the blower as test samples to be input into a trained neural network model for verification, checking feasibility and accuracy of the training and learning results of the tested neural network, simulating the training results, performing inverse normalization processing by using functions after the prediction results are obtained to obtain the required prediction results, and comparing the output data with the verification data to verify the training results of the neural network model;
step a 15: inputting parameters of output efficiency of the air blower, operation time of the air blower and air intake energy consumption of the air blower according to production requirements to obtain the optimal air intake temperature and humidity of the air blower;
step a 16: acquire the temperature and the humidity that current air-blower admitted air, the temperature and the humidity that admit air with current air-blower contrast with the best temperature and humidity that admit air of air-blower, temperature and humidity that admit air when current air-blower are different with the best temperature and humidity that admit air of air-blower, generate the adjustment signal, and send the adjustment signal to the server, server control dehumidification structure that adjusts the temperature and adjusts air-blower temperature and humidity that admit air, it is whole to reach the best temperature and humidity that admit air of air-blower until air-blower temperature and humidity that admit air, it is the same with the best temperature and humidity that admit air of air-blower when the temperature and the humidity that current air-blower admits air, do not operate.
Further, the overhaul module is used for detecting and maintaining the blower, and the specific method comprises the following steps:
step a 21: acquiring the working efficiency of the normal operation of the air blower and the working efficiency of the current air blower, setting a working efficiency difference red line of the air blower, comparing the working efficiency of the normal operation of the air blower with the working efficiency of the current air blower, generating a maintenance signal when the difference between the working efficiency of the air blower and the working efficiency of the normal operation of the air blower reaches the working efficiency difference red line of the air blower, sending the maintenance signal to a server, and not operating when the difference between the working efficiency of the air blower and the working efficiency of the normal operation of the air blower is lower than the working efficiency difference red line of the air blower;
step a 22: when the server receives a maintenance signal, personal information of a maintenance worker is obtained, the personal information comprises age, gender, contact information and maintenance work age, and the maintenance worker is marked as i, wherein i is 1, 2, … … and n, and n is a positive integer;
step a 23: marking the service life of a maintenance worker as Pi;
step a 24: acquiring the working state of a maintenance worker, wherein the working state comprises an idle state and a busy state, and marking the working state of the maintenance worker as Li;
step a 25: acquiring the distance between a maintenance worker and a blower needing maintenance, and marking the distance between the maintenance worker and the blower needing maintenance as Ki; removing dimension of maintenance personnel, maintenance working age of the maintenance personnel, working state of the maintenance personnel and distance between the maintenance personnel and the blower needing to be maintained, and taking numerical value calculation;
step a 26: obtaining a priority value Qi according to a formula Qi ═ lambda ([ b1 ] Pi × [ b2 ] Li)/(b3 ] Ki +1), wherein b1, b2 and b3 are all proportional coefficients, the value range is 1< b1 ≤ 2, 0 ≤ b2 ≤ 1, 0< b3 ≤ 1, lambda is a correction factor, the value range is 0< lambda ≤ 1, when the working state of the maintenance personnel is a busy state, b2 ═ Li ═ 0, and when the working state of the maintenance personnel is an idle state, b2 ═ Li ═ 1;
step a 27: and arranging the priority values Qi in the descending order, and dispatching the maintenance personnel with the first priority values Qi for maintenance.
Further, the operation adjusting module is used for adjusting the blower according to the production plan, and the specific adjusting method comprises the following steps:
step a 31: acquiring historical operating data of the blower;
step a 32: establishing a curve of the output efficiency of the air blower and the energy consumption of the air blower, and establishing a curve of the output efficiency of the air blower and the working progress;
step a 33: synthesizing a curve of the output efficiency of the air blower and the energy consumption of the air blower and a curve of the output efficiency of the air blower and the working progress to obtain a curve of the energy consumption of the air blower, the output efficiency of the air blower and the working progress;
step a 34: and obtaining the optimal energy consumption value of the air blower according to the curve between the energy consumption of the air blower and the output efficiency and the working progress of the air blower in combination with the mathematical derivative, further obtaining the output efficiency of the air blower, and adjusting the air blower according to the output efficiency of the air blower.
Further, the line detection module is used for detecting the blower line, and the specific detection method comprises the following steps:
step a 41: acquiring a current value interval and a voltage value interval in a line of the air blower when the air blower normally operates;
step a 42: detecting a current value and a voltage value in a line of the blower in real time, comparing the detected current value with a current value interval, comparing the detected voltage value with a voltage value interval, and generating a second maintenance signal and sending the second maintenance signal to the server when the current value and the voltage value are not in the current value interval and the voltage value interval;
step a 43: setting a blower circuit temperature warning line, detecting the blower circuit temperature in real time, not operating when the blower circuit temperature is lower than the blower circuit temperature warning line, generating an alarm signal when the blower circuit temperature is higher than the blower circuit temperature warning line, and sending the alarm signal to a server;
step a 44: the server controls the power supply of the blower to be turned off and sends circuit alarm information to the client.
Further, the device temperature monitoring module is used for monitoring the temperature of each component in the blower, and the specific monitoring method comprises the following steps:
step a 51: setting temperature detection points on all parts in the blower to obtain the real-time temperature of all parts in the blower;
step a 52: establishing a coordinate system of the temperature and the time of each component in the blower, setting a temperature red line of each component in the blower, inputting the temperature red line of each component in the blower into the temperature and time coordinate system of the corresponding component, and connecting adjacent coordinate points by using a smooth curve;
step a 53: inputting the obtained temperature and detection time of each component in the blower into a temperature and time coordinate system of the corresponding component in real time;
step a 54: when the temperature of the inner part of the blower is detected to exceed the temperature red line of the inner part of the corresponding blower, generating a high-temperature warning signal, sending the high-temperature warning signal to the server, and when the temperature of the inner part of the blower is detected not to exceed the temperature red line of the inner part of the corresponding blower, not operating;
step a 55: when the server receives the high temperature warning signal, check information is transmitted to the user.
The invention has the beneficial effects that: the optimal air inlet temperature and humidity of the air blower can be obtained through the arrangement of the air inlet adjusting module, so that the air blower can ensure the optimal working efficiency, energy is greatly saved, and the waste of resources is avoided; through the arrangement of the maintenance module, the problems of the air blower can be found in time and repaired in time, the excessive waste of resources caused by the increase of the burden of the air blower is avoided, and meanwhile, maintenance personnel can be reasonably dispatched to repair the air blower; through the setting of the operation adjusting module, various factors are comprehensively considered, the use of the air blower is reasonably planned, and resources are saved to the maximum extent; due to the arrangement of the line detection module, an aged line of the air blower can be maintained in time, resource waste is avoided, safety accidents can be prevented in time, and major safety loss is avoided; through the setting of equipment temperature monitoring module, can in time discover the part overload operation in the air-blower or adjacent part friction themogenesis in the air-blower, when avoiding wasting the resource, the damage of prevention air-blower inner part brings unnecessary economic loss for the user.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic block diagram of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, an energy-saving control system for a blower includes an air intake adjusting module, a server, a maintenance module, an operation adjusting module, a line detecting module, and an equipment temperature monitoring module;
the air inlet adjusting module is used for adjusting the temperature and the humidity of air inlet of the air blower, and the specific adjusting method comprises the following steps:
step a 11: acquiring historical operating data of the blower; the historical operation data comprises a plurality of groups of data, and each group of data comprises the output efficiency of the blower, the operation time of the blower, the air inlet energy consumption of the blower, and the optimal air inlet temperature and humidity of the blower;
step a 12: establishing a neural network model, wherein the neural network model comprises an input layer, a processing layer and an output layer, neuron nodes between every two adjacent layers are connected in a single direction, the output efficiency of a blower, the operation time of the blower and the air intake energy consumption of the blower are selected as input parameters of the neural network, namely the neuron nodes of the input layer of the neural network model, and the output result of the output layer of the neural network model is the optimal air intake temperature and humidity of the blower;
step a 13: entering a training and learning stage of a neural network, selecting d groups of parameters of known output efficiency of the blower, operation time of the blower and air inlet energy consumption of the blower as input training samples, wherein d is a proportionality coefficient and is a positive integer greater than 100, and establishing the relation between the optimal air inlet temperature and humidity of the blower and the input parameters by the neural network through training and learning;
step a 14: entering a prediction and simulation result analysis stage of a neural network, selecting e groups of parameters of known output efficiency of the blower, operation time of the blower, air inlet energy consumption of the blower and optimal air inlet temperature and humidity of the blower as test samples, inputting the test samples into a trained neural network model for verification, wherein e is a proportionality coefficient and is a positive integer greater than 100, verifying feasibility and accuracy of the test neural network training and learning results, simulating the training results, performing inverse normalization processing on the prediction results by using a function to obtain required prediction results, and comparing output data with verification data to verify the training results of the neural network model;
step a 15: inputting parameters of output efficiency of the air blower, operation time of the air blower and air intake energy consumption of the air blower according to production requirements to obtain the optimal air intake temperature and humidity of the air blower;
step a 16: acquiring the temperature and humidity of current air inlet of an air blower, comparing the temperature and humidity of the current air inlet of the air blower with the optimal air inlet temperature and humidity of the air blower, generating an adjusting signal when the temperature and humidity of the current air inlet of the air blower are different from the optimal air inlet temperature and humidity of the air blower, sending the adjusting signal to a server, controlling a temperature adjusting and dehumidifying structure by the server to adjust the air inlet temperature and humidity of the air blower until the air inlet temperature and humidity of the air blower all reach the optimal air inlet temperature and humidity of the air blower, and not operating when the temperature and humidity of the current air inlet of the air blower are the same as the optimal air inlet temperature and humidity of the air blower;
the maintenance module is used for detecting and maintaining the blower, and the specific method comprises the following steps:
step a 21: acquiring the working efficiency of the normal operation of the blower and the working efficiency of the current blower, setting a blower working efficiency difference red line, summarizing that when the difference between the working efficiency of the blower and the working efficiency of the normal operation of the blower reaches a specific value according to a large amount of blower operation data, the working efficiency of the blower is poorer in economical efficiency than working energy consumption, the blower needs to be maintained, comparing the working efficiency of the normal operation of the blower with the working efficiency of the current blower, generating a maintenance signal when the difference between the working efficiency of the blower and the working efficiency of the normal operation of the blower reaches the blower working efficiency difference red line, and sending the maintenance signal to a server, when the difference between the working efficiency of the blower and the working efficiency of the normal operation of the blower is lower than the blower working efficiency difference red line, no operation is performed;
step a 22: when the server receives a maintenance signal, personal information of a maintenance worker is obtained, the personal information comprises age, gender, contact information and maintenance work age, and the maintenance worker is marked as i, wherein i is 1, 2, … … and n, and n is a positive integer;
step a 23: marking the service life of a maintenance worker as Pi;
step a 24: acquiring the working state of a maintenance worker, wherein the working state comprises an idle state and a busy state, and marking the working state of the maintenance worker as Li;
step a 25: acquiring the distance between a maintenance worker and a blower needing maintenance, and marking the distance between the maintenance worker and the blower needing maintenance as Ki; removing dimension of maintenance personnel, maintenance working age of the maintenance personnel, working state of the maintenance personnel and distance between the maintenance personnel and the blower needing to be maintained, and taking numerical value calculation;
step a 26: obtaining a priority value Qi according to a formula Qi ═ lambda ([ b1 ] Pi × [ b2 ] Li)/(b3 ] Ki +1), wherein b1, b2 and b3 are all proportional coefficients, the value range is 1< b1 ≤ 2, 0 ≤ b2 ≤ 1, 0< b3 ≤ 1, lambda is a correction factor, the value range is 0< lambda ≤ 1, when the working state of the maintenance personnel is a busy state, b2 ═ Li ═ 0, and when the working state of the maintenance personnel is an idle state, b2 ═ Li ═ 1;
step a 27: arranging the priority values Qi in a descending order, and dispatching the maintenance personnel with the first priority values Qi for maintenance;
the operation adjusting module is used for adjusting the blower according to a production plan, and the specific adjusting method comprises the following steps:
step a 31: acquiring historical operating data of the blower;
step a 32: establishing a curve of the output efficiency of the air blower and the energy consumption of the air blower, and establishing a curve of the output efficiency of the air blower and the working progress;
step a 33: synthesizing a curve of the output efficiency of the air blower and the energy consumption of the air blower and a curve of the output efficiency of the air blower and the working progress to obtain a curve of the energy consumption of the air blower, the output efficiency of the air blower and the working progress;
step a 34: obtaining an optimal energy consumption value of the air blower according to a curve and a mathematical derivative between the energy consumption of the air blower and the output efficiency and working schedule of the air blower, further obtaining the output efficiency of the air blower, and adjusting the air blower according to the output efficiency of the air blower;
the line detection module is used for detecting the line of the air blower, and the specific detection method comprises the following steps:
step a 41: acquiring a current value interval and a voltage value interval in a line of the air blower when the air blower normally operates;
step a 42: detecting a current value and a voltage value in a line of the blower in real time, comparing the detected current value with a current value interval, comparing the detected voltage value with a voltage value interval, and generating a second maintenance signal and sending the second maintenance signal to the server when the current value and the voltage value are not in the current value interval and the voltage value interval;
step a 43: setting a blower circuit temperature warning line, wherein the blower circuit temperature warning line is set by an expert according to conditions such as blower circuit quality, material and the like, so that safety accidents caused by overhigh temperature are avoided, the blower circuit temperature is detected in real time, when the blower circuit temperature is lower than the blower circuit temperature warning line, the operation is not carried out, and when the blower circuit temperature is higher than the blower circuit temperature warning line, an alarm signal is generated and sent to a server;
step a 44: the server controls the power supply of the blower to be turned off and sends circuit alarm information to the client;
the equipment temperature monitoring module is used for monitoring the temperature of each component in the blower, and the specific monitoring method comprises the following steps:
step a 51: setting temperature detection points on all parts in the blower to obtain the real-time temperature of all parts in the blower;
step a 52: establishing a coordinate system of the temperature and the time of each component in the blower, setting a temperature red line of each component in the blower, wherein the temperature red line of each component in the blower is set by an expert according to a large amount of blower use data, when the temperature of each component in the blower reaches the temperature red line, the condition that the components in the blower run in an overload mode or adjacent components in the blower generate heat through friction is indicated, the inspection is needed, the temperature red lines of each component in the blower are input into the temperature and time coordinate system of the corresponding component, and adjacent coordinate points are connected by using a smooth curve;
step a 53: inputting the obtained temperature and detection time of each component in the blower into a temperature and time coordinate system of the corresponding component in real time;
step a 54: when the temperature of the inner part of the blower is detected to exceed the temperature red line of the inner part of the corresponding blower, generating a high-temperature warning signal, sending the high-temperature warning signal to the server, and when the temperature of the inner part of the blower is detected not to exceed the temperature red line of the inner part of the corresponding blower, not operating;
step a 55: when the server receives the high-temperature warning signal, the server sends checking information to the user to prompt the user to check, and the user can turn off the air blower through remote operation.
The above formulas are all calculated by removing dimensions and taking values thereof, the formula is one closest to the real situation obtained by collecting a large amount of data and performing software simulation, and the preset parameters in the formula are set by the technical personnel in the field according to the actual situation.
When the air conditioner is used, the temperature and the humidity of air inlet of the air blower are adjusted through the air inlet adjusting module, historical operation data of the air blower are obtained, the output efficiency of the air blower, the operation time length of the air blower and the air inlet energy consumption of the air blower are selected as input parameters of a neural network, and the output result of an output layer of the neural network model is the optimal air inlet temperature and humidity of the air blower; entering a training and learning stage of the neural network, selecting d groups of parameters of known blower operation information as input training samples, and establishing the relationship between the optimal air inlet temperature and humidity of the blower and the input parameters by the neural network through training and learning; entering a prediction and simulation result analysis stage of a neural network, selecting e groups of parameters of known blower operation information as test samples, inputting the test samples into a trained neural network model for verification, checking the feasibility and accuracy of the test neural network training and learning results, simulating the training results, performing inverse normalization processing on the prediction results by using a function to obtain a required prediction result, comparing output data with verification data to verify the training result of the neural network model, and inputting parameters according to production requirements to obtain the optimal inlet air temperature and humidity of the blower; the method comprises the steps of obtaining the current air inlet temperature and humidity of an air blower, comparing the current air inlet temperature and humidity of the air blower with the optimal air inlet temperature and humidity of the air blower, generating an adjusting signal when the current air inlet temperature and humidity of the air blower are different from the optimal air inlet temperature and humidity of the air blower, sending the adjusting signal to a server, and controlling a temperature adjusting and dehumidifying structure by the server to adjust the air inlet temperature and humidity of the air blower until the air inlet temperature and humidity of the air blower all reach the optimal air inlet temperature and humidity of the air blower;
acquiring the working efficiency of the normal operation of the air blower and the working efficiency of the current air blower, setting a working efficiency difference red line of the air blower, comparing the working efficiency of the normal operation of the air blower with the working efficiency of the current air blower, generating a maintenance signal when the difference between the working efficiency of the air blower and the working efficiency of the normal operation of the air blower reaches the working efficiency difference red line of the air blower, sending the maintenance signal to a server, and dispatching maintenance personnel for maintenance; adjusting the air blower according to the production plan to obtain a curve between the energy consumption of the air blower and the output efficiency and the working progress of the air blower; obtaining an optimal energy consumption value of the air blower according to a curve and a mathematical derivative between the energy consumption of the air blower and the output efficiency and working schedule of the air blower, further obtaining the output efficiency of the air blower, and adjusting the air blower according to the output efficiency of the air blower;
acquiring a current value interval and a voltage value interval in a blower circuit when a blower normally operates, detecting the current value and the voltage value in the blower circuit in real time, comparing the detected current value with the current value interval, comparing the detected voltage value with the voltage value interval, generating a second maintenance signal when the current value and the voltage value are not in the current value interval and the voltage value interval, sending the second maintenance signal to a server, detecting the blower circuit temperature in real time, generating an alarm signal when the blower circuit temperature is higher than a blower circuit temperature warning line, sending the alarm signal to the server, controlling the blower power supply to be closed by the server, and sending circuit warning information to a client; monitoring the temperature of each part in the blower to obtain the real-time temperature of each part in the blower; inputting temperature red lines of all components in the blower into a temperature and time coordinate system of corresponding components, and connecting adjacent coordinate points by using a smooth curve; inputting the obtained temperature and detection time of each component in the blower into a temperature and time coordinate system of the corresponding component in real time; when the temperature of the inner part of the blower is detected to exceed the temperature red line of the inner part of the corresponding blower, a high-temperature warning signal is generated and sent to the server, and when the server receives the high-temperature warning signal, checking information is sent to a user.
In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means two or more unless specifically defined otherwise.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (5)
1. An energy-saving control system for a blower is characterized by comprising an air inlet adjusting module, a server, a maintenance module, an operation adjusting module, a line detection module and an equipment temperature monitoring module; the air inlet adjusting module, the overhauling module, the operation adjusting module, the line detecting module and the equipment temperature monitoring module are all in communication connection with the server;
the air inlet adjusting module is used for adjusting the temperature and humidity of air inlet of the air blower, and the specific adjusting method comprises the following steps:
step a 11: acquiring historical operating data of the blower;
step a 12: establishing a neural network model, wherein the neural network model comprises an input layer, a processing layer and an output layer, neuron nodes between every two adjacent layers are connected in a single direction, the output efficiency of a blower, the operation time of the blower and the air inlet energy consumption of the blower are selected as input parameters of the neural network, and the output result of the output layer of the neural network model is the optimal air inlet temperature and humidity of the blower;
step a 13: entering a training and learning stage of a neural network, selecting d groups of parameters of known output efficiency of the blower, operation time of the blower and air inlet energy consumption of the blower as input training samples, and establishing a relation between the optimal air inlet temperature and humidity of the blower and the input parameters by the neural network through training and learning;
step a 14: entering a prediction and simulation result analysis stage of a neural network, selecting e groups of parameters of known output efficiency of the blower, operation time of the blower, air intake energy consumption of the blower and optimal air intake temperature and humidity of the blower as test samples to be input into a trained neural network model for verification, checking feasibility and accuracy of the training and learning results of the tested neural network, simulating the training results, performing inverse normalization processing by using functions after the prediction results are obtained to obtain the required prediction results, and comparing the output data with the verification data to verify the training results of the neural network model;
step a 15: inputting parameters of output efficiency of the air blower, operation time of the air blower and air intake energy consumption of the air blower according to production requirements to obtain the optimal air intake temperature and humidity of the air blower;
step a 16: acquiring the temperature and humidity of current air inlet of an air blower, comparing the temperature and humidity of the current air inlet of the air blower with the optimal air inlet temperature and humidity of the air blower, generating an adjusting signal when the temperature and humidity of the current air inlet of the air blower are different from the optimal air inlet temperature and humidity of the air blower, sending the adjusting signal to a server, controlling a temperature adjusting and dehumidifying structure by the server to adjust the air inlet temperature and humidity of the air blower until the air inlet temperature and humidity of the air blower all reach the optimal air inlet temperature and humidity of the air blower, and not operating when the temperature and humidity of the current air inlet of the air blower are the same as the optimal air inlet temperature and humidity of the air blower;
the maintenance module is used for detecting and maintaining the blower;
the operation adjusting module is used for adjusting the blower according to the production plan;
the line detection module is used for detecting a blower line;
the equipment temperature monitoring module is used for monitoring the temperature of each component in the blower.
2. The energy-saving control system for the blower according to claim 1, wherein the inspection module performs inspection and maintenance on the blower including the steps of:
step a 21: acquiring the working efficiency of the normal operation of the air blower and the working efficiency of the current air blower, setting a working efficiency difference red line of the air blower, comparing the working efficiency of the normal operation of the air blower with the working efficiency of the current air blower, generating a maintenance signal when the difference between the working efficiency of the air blower and the working efficiency of the normal operation of the air blower reaches the working efficiency difference red line of the air blower, sending the maintenance signal to a server, and not operating when the difference between the working efficiency of the air blower and the working efficiency of the normal operation of the air blower is lower than the working efficiency difference red line of the air blower;
step a 22: when the server receives a maintenance signal, acquiring personal information of a maintenance worker, wherein the personal information comprises age, gender, contact information and maintenance work age, and marking the maintenance worker as i, wherein i =1, 2, … … and n is a positive integer;
step a 23: marking the service life of a maintenance worker as Pi;
step a 24: acquiring the working state of a maintenance worker, wherein the working state comprises an idle state and a busy state, and marking the working state of the maintenance worker as Li;
step a 25: acquiring the distance between a maintenance worker and a blower needing maintenance, and marking the distance between the maintenance worker and the blower needing maintenance as Ki; removing dimension of maintenance personnel, maintenance working age of the maintenance personnel, working state of the maintenance personnel and distance between the maintenance personnel and the blower needing to be maintained, and taking numerical value calculation;
step a 26: obtaining a priority value Qi according to a formula Qi = lambda (b1 Pi b2 Li)/(b3 Ki +1), wherein b1, b2 and b3 are all proportional coefficients, the value range is 1< b1 is less than or equal to 2, 0 is less than or equal to b2 is less than or equal to 1, 0 is less than or equal to b3 is less than or equal to 1, lambda is a correction factor, the value range is 0< lambda is less than or equal to 1, when the working state of a maintenance worker is a busy state, b2 Li =0, and when the working state of the maintenance worker is an idle state, b2 Li = 1;
step a 27: and arranging the priority values Qi in the descending order, and dispatching the maintenance personnel with the first priority values Qi for maintenance.
3. The energy-saving control system for the blower according to claim 1, wherein the method for adjusting the blower according to the production plan by the operation adjusting module comprises the following steps:
step a 31: acquiring historical operating data of the blower;
step a 32: establishing a curve of the output efficiency of the air blower and the energy consumption of the air blower, and establishing a curve of the output efficiency of the air blower and the working progress;
step a 33: synthesizing a curve of the output efficiency of the air blower and the energy consumption of the air blower and a curve of the output efficiency of the air blower and the working progress to obtain a curve of the energy consumption of the air blower, the output efficiency of the air blower and the working progress;
step a 34: and obtaining the optimal energy consumption value of the air blower according to the curve between the energy consumption of the air blower and the output efficiency and the working progress of the air blower in combination with the mathematical derivative, further obtaining the output efficiency of the air blower, and adjusting the air blower according to the output efficiency of the air blower.
4. The energy-saving control system for the blower according to claim 1, wherein the method for the line detection module to detect the line of the blower comprises the steps of:
step a 41: acquiring a current value interval and a voltage value interval in a line of the air blower when the air blower normally operates;
step a 42: detecting a current value and a voltage value in a line of the blower in real time, comparing the detected current value with a current value interval, comparing the detected voltage value with a voltage value interval, and generating a second maintenance signal and sending the second maintenance signal to the server when the current value and the voltage value are not in the current value interval and the voltage value interval;
step a 43: setting a blower circuit temperature warning line, detecting the blower circuit temperature in real time, not operating when the blower circuit temperature is lower than the blower circuit temperature warning line, generating an alarm signal when the blower circuit temperature is higher than the blower circuit temperature warning line, and sending the alarm signal to a server;
step a 44: the server controls the power supply of the blower to be turned off and sends circuit alarm information to the client.
5. The energy-saving control system for the blower according to claim 1, wherein the method for the device temperature monitoring module to monitor the temperature of each component in the blower comprises the steps of:
step a 51: setting temperature detection points on all parts in the blower to obtain the real-time temperature of all parts in the blower;
step a 52: establishing a coordinate system of the temperature and the time of each component in the blower, setting a temperature red line of each component in the blower, inputting the temperature red line of each component in the blower into the temperature and time coordinate system of the corresponding component, and connecting adjacent coordinate points by using a smooth curve;
step a 53: inputting the obtained temperature and detection time of each component in the blower into a temperature and time coordinate system of the corresponding component in real time;
step a 54: generating a high temperature warning signal when the temperature of the inner part of the blower is detected to exceed the temperature red line of the inner part of the corresponding blower, and transmitting the high temperature warning signal to the server, and not operating when the temperature of the inner part of the blower is detected not to exceed the temperature red line of the inner part of the corresponding blower;
step a 55: when the server receives the high temperature warning signal, check information is transmitted to the user.
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| CN113606111B (en) * | 2021-09-09 | 2023-02-24 | 广东鑫钻节能科技股份有限公司 | Energy-saving protection system based on air compression station and implementation method thereof |
| CN117114205B (en) * | 2023-10-23 | 2024-02-13 | 广东鑫钻节能科技股份有限公司 | Energy-saving prediction model and method for digital energy blasting station |
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Denomination of invention: An energy-saving control system for blowers Effective date of registration: 20231020 Granted publication date: 20211224 Pledgee: Guangdong Hengfu Financial Leasing Co.,Ltd. Pledgor: Guangdong xinzuan Energy Saving Technology Co.,Ltd. Registration number: Y2023980062019 |