CN117856455B - Intelligent regulation and control method for power equipment based on fuzzy control - Google Patents
Intelligent regulation and control method for power equipment based on fuzzy control Download PDFInfo
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Abstract
The invention relates to the technical field of control systems, in particular to an intelligent regulation and control method of power equipment based on fuzzy control, which comprises the following steps: collecting historical daily voltage data, speed data and vibration data, and constructing a historical daily voltage curve, a historical daily speed curve and a historical daily vibration curve; according to the historical daily voltage curve and the historical daily speed curve, the response degree between the voltage data and the speed data is obtained; acquiring a compensation value of a proportional gain coefficient on the same day according to the response degree between the voltage data and the speed data; acquiring a stability degree parameter of a historical daily conveyor belt system according to a historical daily vibration curve; combining the compensation value of the current day proportional gain coefficient to obtain a new proportional gain coefficient; the new conveyor system is adjusted based on the new proportional gain factor. The invention adjusts the gain coefficient of the comparative example, and finally achieves the aim of stabilizing the output of the system.
Description
Technical Field
The invention relates to the technical field of control systems, in particular to an intelligent regulation and control method for power equipment based on fuzzy control.
Background
In a power system, the intelligent regulation and control method based on fuzzy control can be used for transformer control in power equipment so as to realize effective management and regulation of electric energy; the fuzzy control method helps the transformer to realize more flexible regulation and control under different loads, power grid conditions or running states. However, since the proportional gain coefficient in the conventional fuzzy control is fixed and the power system of the power equipment is dynamically changed, the fixed proportional gain coefficient controls the power equipment to lower the stability of the system.
Disclosure of Invention
The invention provides an intelligent regulation and control method of power equipment based on fuzzy control, which aims to solve the existing problems: the proportional gain coefficient in the conventional fuzzy control is fixed, and if the power equipment is controlled by the fixed proportional gain coefficient, the stability of the system is reduced.
The intelligent regulation and control method of the power equipment based on fuzzy control adopts the following technical scheme:
The method comprises the following steps:
Collecting historical daily voltage data, historical daily speed data and historical daily vibration data, and constructing a historical daily voltage curve, a historical daily speed curve and a historical daily vibration curve;
Acquiring historical daily voltage data fluctuation characteristics and historical daily speed data fluctuation characteristics according to the voltage amplitude in the historical daily voltage curve and the speed amplitude in the historical daily speed curve; acquiring a speed characteristic difference value set and a voltage characteristic difference value set according to historical daily voltage data fluctuation characteristics and historical daily speed data fluctuation characteristics; acquiring the response degree between the voltage data and the speed data according to the speed characteristic difference value set and the voltage characteristic difference value set;
Acquiring a compensation value of a proportional gain coefficient on the same day according to the response degree between the voltage data and the speed data;
Acquiring a stability degree parameter of a historical daily conveyor belt system according to a historical daily vibration curve; according to the discrete degree of the stability degree parameter of the historical daily conveyor belt system, combining the compensation value of the current day proportional gain coefficient to obtain a new proportional gain coefficient; the conveyor system is adjusted according to the new proportional gain factor.
Preferably, the method for collecting historical daily voltage data, historical daily speed data and historical daily vibration data and constructing a historical daily voltage curve, a historical daily speed curve and a historical daily vibration curve includes the following specific steps:
the method comprises the steps of calling historical daily voltage data, historical daily speed data and historical daily vibration data collected by a voltage sensor, a speed sensor and a vibration sensor in a historical database;
for the historical first Day voltage data, time abscissa and voltage data ordinate, construct historical/>The voltage data coordinate system of the day will historically be the/>Day voltage data fills in historically/>In the voltage data coordinate system of the day, the least square method is then used for the historical/>Performing curve fitting on data points in a day voltage data coordinate system to obtain historical/>A voltage curve of days;
for the historical first Day speed data, time abscissa and speed data ordinate, construct historical/>The day's velocity data coordinate system will historically be the/>Day speed data populates historic/>In the day's velocity data coordinate system, the least square method is then used to historically/>Performing curve fitting on data points in a day speed data coordinate system to obtain historical/>A day speed profile;
for the historical first Vibration data of day, time is taken as an abscissa, vibration data is taken as an ordinate, and historical/>, is constructedThe vibration data coordinate system of the day will historically be the/>Vibration data of day is filled in historically/>In the vibration data coordinate system of the day, the least square method is then used for the historical/>Performing curve fitting on data points in a vibration data coordinate system of the day to obtain historical/>Vibration curve of day.
Preferably, the method for obtaining the historical daily voltage data fluctuation characteristic and the historical daily speed data fluctuation characteristic according to the voltage amplitude in the historical daily voltage curve and the historical daily speed amplitude in the historical daily speed curve comprises the following specific steps:
for acquisition history th Fluctuation characteristics of the voltage data of the day; according to historical/>A voltage curve of the day is obtained, and the historical/>All voltage magnitudes in the day's voltage curve, according to historical/>All voltage amplitudes in the day's voltage curve are obtained historically/>The fluctuation characteristics of the voltage data of the day are shown in the following specific calculation formula:
In the method, in the process of the invention, Representing historical/>Fluctuation characteristics of the voltage data of the day; /(I)Representing historical/>Variance of all voltage amplitudes in the daily voltage curve; /(I)Representing historical/>The number of voltage magnitudes in the voltage curve for the day; /(I)Representing historical/>First/>, in the voltage curve of the dayA plurality of voltage magnitudes; /(I)Representing historical/>Maximum voltage amplitude in the voltage curve of the day; /(I)Representing historical/>The minimum voltage amplitude in the voltage curve of the day;
for acquisition history th Fluctuation characteristics of the day speed data; according to historical/>A day's velocity profile, obtaining historical/>All speed magnitudes in the day's speed profile, according to historical/>All the speed magnitudes in the day's speed curve are obtained historically/>The fluctuation characteristics of the day speed data are as follows:
In the method, in the process of the invention, Representing historical/>Fluctuation characteristics of the day speed data; /(I)Representing historical/>Variance of all velocity magnitudes in the day's velocity profile; /(I)Representing historical/>The number of speed magnitudes in the day's speed profile; /(I)Representing historical/>First/>, in the velocity profile of the dayA respective velocity amplitude value; /(I)Representing historical/>Maximum speed amplitude in the day's speed profile; /(I)Representing historical/>The smallest speed amplitude in the day's speed profile.
Preferably, the step of obtaining the speed characteristic difference set and the voltage characteristic difference set according to the historical daily voltage data fluctuation characteristic and the historical daily speed data fluctuation characteristic comprises the following specific steps:
According to the fluctuation characteristics of the historical daily voltage data and the fluctuation characteristics of the historical daily speed data, the voltage characteristic difference value of the historical daily and the previous day and the speed characteristic difference value of the historical daily and the previous day are obtained, and the specific calculation formula is as follows:
In the method, in the process of the invention, Representing historical/>Day and history/>Difference in the speed characteristics of the day,/>Representing historical/>Number of data in the day's speed profile; /(I)Representing historical/>First/>, in the velocity profile of the dayA respective velocity amplitude value; representing historical/> First/>, in the velocity profile of the dayA respective velocity amplitude value; /(I)Representing historical/>Fluctuation characteristics of the day speed data; /(I)Representing historical/>Fluctuation characteristics of the day speed data; /(I)Representing historical/>Day and history/>Voltage characteristic difference of day; /(I)Representing historical/>Number of data in the day's voltage curve; /(I)Representing historical/>First/>, in the voltage curve of the dayA plurality of voltage magnitudes; /(I)Representing historical/>First/>, in the voltage curve of the dayA plurality of voltage magnitudes; /(I)Representing historical/>Fluctuation characteristics of the voltage data of the day; /(I)Representing historically the firstFluctuation characteristics of the voltage data of the day; /(I)Representing an absolute value operation;
the set of voltage characteristic differences of all the days and the previous day is recorded as a voltage characteristic difference set, and the set of speed characteristic differences of all the days and the previous day is recorded as a speed characteristic difference set.
Preferably, the obtaining the response degree between the voltage data and the speed data according to the speed characteristic difference value set and the voltage characteristic difference value set includes the following specific methods:
and calculating the pearson correlation coefficient between the speed characteristic difference value set and the voltage characteristic difference value set, and taking the pearson correlation coefficient between the speed characteristic difference value set and the voltage characteristic difference value set as the response degree between the voltage data and the speed data.
Preferably, the method for obtaining the compensation value of the current day proportional gain coefficient according to the response degree between the voltage data and the speed data includes the following specific steps:
firstly, the rated temperature and the rated speed of a conveyor belt are respectively recorded as And/>Next, the initial proportional gain coefficient in the fuzzy PID control is obtained and recorded as/>Then, the temperature data and the speed data of the current day are collected through a temperature sensor and a speed sensor, and the maximum temperature value in the temperature data of the current day and the maximum speed value in the speed data of the current day are respectively recorded asAnd/>Finally according to/>、/>、/>、/>、/>And the response degree between the voltage data and the speed data is used for obtaining the compensation value of the current day proportional gain coefficient.
Preferably, the obtaining the compensation value of the current day proportional gain coefficient includes the following specific calculation formula:
In the method, in the process of the invention, A compensation value representing the current day proportional gain coefficient; /(I)Representing a degree of response between the voltage data and the speed data; /(I)Representing a temperature maximum in the current day temperature data; /(I)Representing a maximum value of the speed in the current day speed data; /(I)Indicating the nominal speed of the conveyor belt; /(I)Indicating the nominal temperature of the conveyor belt; /(I)Representing an initial proportional gain coefficient in the fuzzy PID control; /(I)Representing an absolute value operation.
Preferably, the method for obtaining the stability degree parameter of the conveyor belt system every day according to the vibration curve every day in history includes the following specific steps:
for acquisition history th Stability parameters of the ceiling-based conveyor system according to historical/>The vibration curve of the day is obtained, and the first/>, historicallyThe mean value of all vibration amplitudes, the variance of all vibration amplitudes and the maximum value of all vibration amplitudes in the vibration curve of the day according to the historic/>Obtaining historical/>, wherein the average value of all vibration amplitudes, the variance of all vibration amplitudes and the maximum value of all vibration amplitudes in the vibration curve of the dayThe vibration data of the day fluctuates in characteristics.
Preferably, the acquisition history is the firstThe fluctuation characteristics of the vibration data of the day comprise the following specific calculation formulas:
In the method, in the process of the invention, Representing historical/>Stability parameters of the conveyor system; /(I)Representing historical/>Maximum vibration amplitude in the natural vibration curve; /(I)Representing historical/>The average value of all vibration amplitudes in the vibration curve of the day; representing historical/> Variance of all vibration amplitudes in the natural vibration curve; /(I)Representing an absolute value operation.
Preferably, the step of obtaining a new proportional gain coefficient according to the discrete degree of the stability degree parameter of the daily conveyor system in combination with the compensation value of the current proportional gain coefficient includes the following specific calculation formulas:
In the method, in the process of the invention, Representing a new proportional gain coefficient; /(I)Standard deviation representing a stability parameter for a historically all day conveyor belt system; /(I)Representing an initial proportional gain coefficient in the fuzzy PID control; /(I)A compensation value representing the current day proportional gain coefficient; /(I)Representing a linear normalization function.
The technical scheme of the invention has the beneficial effects that: according to the method, the relevant historical data of the power equipment are obtained, and the response degree between the data is calculated according to the historical data; obtaining a compensation value of the proportional gain value according to the response degree between the data; and then, evaluating the stability of the system according to the related historical data, and generating a new proportional gain coefficient by combining the compensation value of the proportional gain value, so that the stability of the system is improved.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flow chart of steps of an intelligent regulation and control method of electric equipment based on fuzzy control.
Detailed Description
In order to further describe the technical means and effects adopted by the invention to achieve the preset aim, the following detailed description is given below of the specific implementation, structure, characteristics and effects of the intelligent control method for the power equipment based on fuzzy control according to the invention by combining the accompanying drawings and the preferred embodiment. In the following description, different "one embodiment" or "another embodiment" means that the embodiments are not necessarily the same. Furthermore, the particular features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
The specific scheme of the intelligent power equipment regulating and controlling method based on fuzzy control provided by the invention is specifically described below with reference to the accompanying drawings.
Referring to fig. 1, a flowchart illustrating steps of a method for intelligent regulation and control of a power device based on fuzzy control according to an embodiment of the present invention is shown, where the method includes the following steps:
Step S001: the historical daily voltage data, the historical daily speed data and the historical daily vibration data are collected, and a historical daily voltage curve, a historical daily speed curve and a historical daily vibration curve are constructed.
In the power system, the intelligent regulation and control method based on fuzzy control can be used for controlling the transformer in the power equipment so as to realize effective management and regulation of electric energy, and the fuzzy control method helps the transformer to realize more flexible regulation and control under different loads, power grid conditions or running states. However, the conventional fuzzy control method is generally limited by an accurate mathematical model and complex calculation, and the uncertainty and complexity of dynamic changes of the power system can lead to performance fluctuation or instability of the fuzzy controller, so that the fuzzy control method is difficult to cope with the dynamic changes and uncertainties in the power system. Therefore, the embodiment provides an intelligent regulation and control method for power equipment based on fuzzy control.
It should be further noted that, in the industrial production system, the conveyor belt is a common power device for conveying materials, so this embodiment is described by taking intelligent control of the conveyor belt as an example; in order to realize intelligent regulation and control of the conveyor belt; it is therefore first necessary to collect historical data of the conveyor belt.
Specifically, the historical daily voltage data, the historical daily speed data and the historical daily vibration data collected by the voltage sensor, the speed sensor and the vibration sensor in the historical database are called.
It should be noted that, in this embodiment, the historical data of the conveyor belt is analyzed to realize intelligent regulation and control of the conveyor belt, and in order to better analyze the historical data, the historical data needs to be preprocessed.
In particular, for the historical firstDay voltage data, time abscissa and voltage data ordinate, construct historical/>The voltage data coordinate system of the day will historically be the/>Day voltage data fills in historically/>In the voltage data coordinate system of the day, the least square method is then used for the historical/>Performing curve fitting on data points in a day voltage data coordinate system to obtain historical/>A voltage curve of each day is obtained by the same method;
for the historical first Day speed data, time abscissa and speed data ordinate, construct historical/>The day's velocity data coordinate system will historically be the/>Day speed data populates historic/>In the day's velocity data coordinate system, the least square method is then used to historically/>Performing curve fitting on data points in a day speed data coordinate system to obtain historical/>A daily speed curve is obtained by the same method;
for the historical first Vibration data of day, time is taken as an abscissa, vibration data is taken as an ordinate, and historical/>, is constructedThe vibration data coordinate system of the day will historically be the/>Vibration data of day is filled in historically/>In the vibration data coordinate system of the day, the least square method is then used for the historical/>Performing curve fitting on data points in a vibration data coordinate system of the day to obtain historical/>A daily vibration curve is obtained by the same method;
It should be further noted that, since the specific process of performing curve fitting by using the least square method is known as a prior art, a detailed description is omitted in this embodiment, and the number of data in each of the voltage curve, the speed curve and the vibration curve is equal.
Thus, a daily voltage curve, a daily speed curve and a daily vibration curve are obtained.
Step S002: acquiring historical daily voltage data fluctuation characteristics and historical daily speed data fluctuation characteristics according to the voltage amplitude in the historical daily voltage curve and the speed amplitude in the historical daily speed curve; acquiring a speed characteristic difference value set and a voltage characteristic difference value set according to historical daily voltage data fluctuation characteristics and historical daily speed data fluctuation characteristics; and acquiring the response degree between the voltage data and the speed data according to the speed characteristic difference value set and the voltage characteristic difference value set.
It should be noted that the PID controller design in the fuzzy control method includes three important parameters, namely, a proportional gain coefficient, an integration time and a differentiation time. The proportional gain coefficient is used as an important parameter in the controller, and can control the response degree of the system to achieve the stability of the balanced system, and a larger proportional gain coefficient can apply a higher degree of control force to a larger error to quickly reduce the error. In this embodiment, the historical data of the conveyor belt is analyzed, and the gain coefficient of the comparative example is adjusted, so that the purpose of stabilizing the output of the conveyor belt is finally achieved.
It should be further noted that, in order to adjust the gain coefficient of the comparative example, it is first necessary to calculate the degree of response between the voltage data and the speed data of the apparatus, and in order to calculate the degree of response of the control system, it is first necessary to acquire the fluctuation characteristics of the voltage data of each day and the fluctuation characteristics of the speed data of each day.
Specifically, for the acquisition historyFluctuation characteristics of the voltage data of the day; according to historical/>A voltage curve of the day is obtained, and the historical/>All voltage magnitudes in the day's voltage curve, according to historical/>All voltage amplitudes in the day's voltage curve are obtained historically/>The fluctuation characteristics of the voltage data of the day are shown in the following specific calculation formula:
In the method, in the process of the invention, Representing historical/>Fluctuation characteristics of the voltage data of the day; /(I)Representing historical/>Variance of all voltage amplitudes in the daily voltage curve; /(I)Representing historical/>The number of voltage magnitudes in the voltage curve for the day; /(I)Representing historical/>First/>, in the voltage curve of the dayA plurality of voltage magnitudes; /(I)Representing historical/>Maximum voltage amplitude in the voltage curve of the day; /(I)Representing historical/>The smallest voltage amplitude in the voltage curve of the day.
It should be noted that the number of the substrates,Expressed as historical/>Variance of the voltage curve of day,/>Expressed as historical/>The average of all voltage magnitudes in the voltage curve of the day, therefore/>Can represent historical/>The change of the voltage curve of the day; /(I)Expressed as historical/>Fluctuation range of the voltage curve of the day, therefore/>Can represent historical/>Fluctuation characteristics of the voltage data of the day; i.e./>The larger the value of (2), historically the/>The higher the degree of fluctuation of the voltage data in the day.
Specifically, for the acquisition historyFluctuation characteristics of the day speed data; according to historical/>A day's velocity profile, obtaining historical/>All speed magnitudes in the day's speed profile, according to historical/>All the speed magnitudes in the day's speed curve are obtained historically/>The fluctuation characteristics of the day speed data are as follows:
In the method, in the process of the invention, Representing historical/>Fluctuation characteristics of the day speed data; /(I)Representing historical/>Variance of all velocity magnitudes in the day's velocity profile; /(I)Representing historical/>The number of speed magnitudes in the day's speed profile; /(I)Representing historical/>First/>, in the velocity profile of the dayA respective velocity amplitude value; /(I)Representing historical/>Maximum speed amplitude in the day's speed profile; /(I)Representing historical/>The smallest speed amplitude in the day's speed profile.
It should be noted that the number of the substrates,Expressed as historical/>Variance of the velocity profile of the day,/>Expressed as historical/>The average of all the velocity magnitudes in the day's velocity profile, therefore/>Can represent historical/>A change in the day's velocity profile; /(I)Expressed as historical/>Fluctuation range of the velocity profile of the day, therefore/>Can represent historical/>Fluctuation characteristics of the day speed data; i.e.The larger the value of (2), historically the/>The higher the degree of fluctuation of the day's speed data.
To this end, the fluctuation characteristics of the voltage data of each day and the fluctuation characteristics of the speed data of each day are obtained.
It should be further noted that, after obtaining the fluctuation feature of the daily voltage data and the fluctuation feature of the daily speed data, the response degree of the control system may be obtained according to the fluctuation feature of the daily voltage data and the fluctuation feature of the daily speed data.
Specifically, according to the fluctuation feature of the voltage data of each day in the history and the fluctuation feature of the speed data of each day in the history, the voltage feature difference value of each day in the history and the speed feature difference value of each day in the history are obtained, and the specific calculation formula is as follows:
In the method, in the process of the invention, Representing historical/>Day and history/>Difference in the speed characteristics of the day,/>Representing historical/>Number of data in the day's speed profile; /(I)Representing historical/>First/>, in the velocity profile of the dayA respective velocity amplitude value; representing historical/> First/>, in the velocity profile of the dayA respective velocity amplitude value; /(I)Representing historical/>Fluctuation characteristics of the day speed data; /(I)Representing historical/>Fluctuation characteristics of the day speed data; /(I)Representing historical/>Day and history/>Voltage characteristic difference of day; /(I)Representing historical/>Number of data in the day's voltage curve; /(I)Representing historical/>First/>, in the voltage curve of the dayA plurality of voltage magnitudes; /(I)Representing historical/>First/>, in the voltage curve of the dayA plurality of voltage magnitudes; /(I)Representing historical/>Fluctuation characteristics of the voltage data of the day; /(I)Representing historically the firstFluctuation characteristics of the voltage data of the day; /(I)Representing an absolute value operation;
the set of voltage characteristic differences of all the days and the previous day is recorded as a voltage characteristic difference set, and the set of speed characteristic differences of all the days and the previous day is recorded as a speed characteristic difference set.
It should be noted that the number of the substrates,Expressed as historical/>Day speed profile and history/>Mean square error between the velocity profiles of the days, and therefore/>The larger the value of (2), the description of the historical/>Day speed profile and history/>The greater the difference between the day's velocity profiles; expressed as historical/> Fluctuation characteristics of day speed data and historical/>Differences between the fluctuation characteristics of the day's velocity data; thus/>The larger the value of (2), the description of the historical/>Day speed profile and history/>The greater the difference between the day's velocity profiles, and therefore/>The larger the value of (2), the more historic/>, the descriptionDay speed profile and history/>The greater the difference between the day's velocity profiles; same principle/>The larger the value of (2), the more historic/>, the descriptionVoltage profile of day and historical/>The greater the difference between the voltage curves for the days.
It should be further noted that, if the degree of response between the voltage data and the speed data of the device is higher, the pearson correlation coefficient between the speed characteristic difference value set and the voltage characteristic difference value set is larger, so that the degree of response between the voltage data and the speed data of the device can be obtained according to the pearson correlation coefficient between the speed characteristic difference value set and the voltage characteristic difference value set.
Specifically, a pearson correlation coefficient between the speed characteristic difference value set and the voltage characteristic difference value set is calculated, and the pearson correlation coefficient between the speed characteristic difference value set and the voltage characteristic difference value set is used as the response degree between the voltage data and the speed data; since the specific calculation process of the pearson correlation coefficient is a well-known prior art, the detailed description is omitted in this embodiment
Thus, the response degree between the voltage data and the speed data of the equipment is obtained.
Step S003: and acquiring a compensation value of the current day proportional gain coefficient according to the response degree between the voltage data and the speed data.
It should be noted that, the purpose of this embodiment as an intelligent power equipment control method based on fuzzy control is to adjust the gain coefficient of the comparative example, so that the output of the power equipment is more stable finally. And step S002 is performed to obtain the response degree between the voltage data and the speed data of the equipment, and the proportional gain coefficient can be adjusted according to the response degree between the voltage data and the speed data of the equipment.
It should be further noted that, in the fuzzy PID control, when the difference between the actual value and the expected value is large, in order to make the system stability better, to achieve the purpose of effectively reducing the error and improving the control effect, it is necessary to compensate the proportional gain coefficient in the fuzzy control method. I.e. the larger the difference between the actual value and the desired value, the more the proportional gain factor needs to be increased; the compensation value of the proportional gain coefficient can thus be obtained by the difference between the actual value and the desired value.
Specifically, the rated temperature and rated speed of the conveyor belt are firstly obtained and respectively recorded asAnd/>Next, the initial proportional gain coefficient in the fuzzy PID control is obtained and recorded as/>Then, acquiring the temperature data and the speed data of the same day through a temperature sensor and a speed sensor, and acquiring the temperature maximum value in the temperature data of the same day and the speed maximum value in the speed data of the same day to be respectively recorded as/>And/>Finally according to/>、/>、/>、/>、/>And the response degree between the voltage data and the speed data, and obtaining the compensation value of the current day proportional gain coefficient, wherein the specific calculation formula is as follows:
In the method, in the process of the invention, A compensation value representing the current day proportional gain coefficient; /(I)Representing a degree of response between the voltage data and the speed data; /(I)Representing a temperature maximum in the current day temperature data; /(I)Representing a maximum value of the speed in the current day speed data; /(I)Indicating the nominal speed of the conveyor belt; /(I)Indicating the nominal temperature of the conveyor belt; /(I)Representing an initial proportional gain coefficient in the fuzzy PID control; /(I)Representing an absolute value operation.
It should be noted that the number of the substrates,Representing the degree of response between the voltage data and the speed data of the device,/>The degree of fluctuation of the conveyor belt operation is shown; in general, the higher the response in the control system, and the greater the degree of turbulence in the belt operation, the more unstable the belt operation, the greater the need to increase the proportional gain factor, i.e., the greater the compensation value for the proportional gain factor.
Thus, the compensation value of the current day proportional gain coefficient is obtained.
Step S004: acquiring a stability degree parameter of a historical daily conveyor belt system according to a historical daily vibration curve; according to the discrete degree of the stability degree parameter of the historical daily conveyor belt system, combining the compensation value of the current day proportional gain coefficient to obtain a new proportional gain coefficient; the conveyor system is adjusted according to the new proportional gain factor.
It should be noted that, the purpose of this embodiment as an intelligent power equipment control method based on fuzzy control is to adjust the gain coefficient of the comparative example, so that the output of the power equipment is more stable finally. After the compensation value of the current day proportional gain coefficient is obtained in step S003, a new proportional gain coefficient can be obtained according to the compensation value of the current day proportional gain coefficient.
It should be further noted that, in the conveyor system, the vibration data is affected by the voltage data, the speed data and the temperature data, so that the stability of the conveyor system can be directly evaluated through the vibration data, that is, the stability parameter of the conveyor system can be obtained through the vibration data,
Specifically, for the acquisition historyStability parameters of the ceiling-based conveyor system according to historical/>The vibration curve of the day is obtained, and the first/>, historicallyThe mean value of all vibration amplitudes, the variance of all vibration amplitudes and the maximum value of all vibration amplitudes in the vibration curve of the day according to the historic/>Obtaining historical/>, wherein the average value of all vibration amplitudes, the variance of all vibration amplitudes and the maximum value of all vibration amplitudes in the vibration curve of the dayThe fluctuation characteristics of the vibration data of the day are as follows:
In the method, in the process of the invention, Representing historical/>Stability parameters of the conveyor system; /(I)Representing historical/>Maximum vibration amplitude in the natural vibration curve; /(I)Representing historical/>The average value of all vibration amplitudes in the vibration curve of the day; representing historical/> Variance of all vibration amplitudes in the natural vibration curve; /(I)Representing an absolute value operation.
It should be noted that the number of the substrates,The larger the value of (2), the description of the historical/>The lower the stability of the ceiling-based conveyor system; after obtaining the stability degree parameter of the conveyor belt system every day, the proportional gain coefficient can be obtained according to the discrete degree of the stability degree parameter of the conveyor belt system every day and by combining the compensation value of the current proportional gain coefficient, and a specific calculation formula is as follows:
In the method, in the process of the invention, Representing a new proportional gain coefficient; /(I)Standard deviation representing a stability parameter for a historically all day conveyor belt system; /(I)Representing an initial proportional gain coefficient in the fuzzy PID control; /(I)A compensation value representing the current day proportional gain coefficient; /(I)Representing a linear normalization function.
It should be further noted that,The method shows the discrete degree of the stability degree parameter of the conveyor belt system every day, and the larger the discrete degree is, the more unstable the system is, namely the more the proportional gain coefficient is required to be increased, so that the parameters of the equipment are controlled by the greater control force in the fuzzy control method, the equipment can respond to the abnormal condition in the system faster and more timely, and the equipment can keep better stability.
Thus, the new proportional gain coefficient is adjusted, and the new proportional gain coefficient is used as the proportional gain coefficient in the PID control system, so that the purpose of stabilizing the output of the power equipment is achieved.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the invention, but any modifications, equivalent substitutions, improvements, etc. within the principles of the present invention should be included in the scope of the present invention.
Claims (7)
1. The intelligent regulation and control method for the power equipment based on fuzzy control is characterized by comprising the following steps of:
Collecting historical daily voltage data, historical daily speed data and historical daily vibration data, and constructing a historical daily voltage curve, a historical daily speed curve and a historical daily vibration curve;
Acquiring historical daily voltage data fluctuation characteristics and historical daily speed data fluctuation characteristics according to the voltage amplitude in the historical daily voltage curve and the speed amplitude in the historical daily speed curve; acquiring a speed characteristic difference value set and a voltage characteristic difference value set according to historical daily voltage data fluctuation characteristics and historical daily speed data fluctuation characteristics; acquiring the response degree between the voltage data and the speed data according to the speed characteristic difference value set and the voltage characteristic difference value set;
Acquiring a compensation value of a proportional gain coefficient on the same day according to the response degree between the voltage data and the speed data;
Acquiring a stability degree parameter of a historical daily conveyor belt system according to a historical daily vibration curve; according to the discrete degree of the stability degree parameter of the historical daily conveyor belt system, combining the compensation value of the current day proportional gain coefficient to obtain a new proportional gain coefficient; adjusting the conveyor belt system according to the new proportional gain coefficient;
According to the response degree between the voltage data and the speed data, the compensation value of the current day proportional gain coefficient is obtained, and the specific method comprises the following steps:
firstly, the rated temperature and the rated speed of a conveyor belt are respectively recorded as And/>Next, the initial proportional gain coefficient in the fuzzy PID control is obtained and recorded as/>Then, acquiring the temperature data and the speed data of the same day through a temperature sensor and a speed sensor, and acquiring the temperature maximum value in the temperature data of the same day and the speed maximum value in the speed data of the same day to be respectively recorded as/>And/>Finally according to/>、/>、/>、/>、/>The response degree between the voltage data and the speed data is used for obtaining the compensation value of the current day proportional gain coefficient;
The specific calculation formula for acquiring the compensation value of the current day proportional gain coefficient is as follows:
In the method, in the process of the invention, A compensation value representing the current day proportional gain coefficient; /(I)Representing a degree of response between the voltage data and the speed data; /(I)Representing a temperature maximum in the current day temperature data; /(I)Representing a maximum value of the speed in the current day speed data; /(I)Indicating the nominal speed of the conveyor belt; /(I)Indicating the nominal temperature of the conveyor belt; /(I)Representing an initial proportional gain coefficient in the fuzzy PID control; /(I)Representing an absolute value operation;
According to the discrete degree of the stability degree parameter of the daily conveyor belt system in history, the new proportional gain coefficient is obtained by combining the compensation value of the current day proportional gain coefficient, and the specific calculation formula is as follows:
In the method, in the process of the invention, Representing a new proportional gain coefficient; /(I)Standard deviation representing a stability parameter for a historically all day conveyor belt system; /(I)Representing an initial proportional gain coefficient in the fuzzy PID control; /(I)A compensation value representing the current day proportional gain coefficient; /(I)Representing a linear normalization function.
2. The intelligent regulation and control method of a power device based on fuzzy control of claim 1, wherein the steps of collecting historical daily voltage data, historical daily speed data and historical daily vibration data, and constructing a historical daily voltage curve, a historical daily speed curve and a historical daily vibration curve comprise the following specific steps:
the method comprises the steps of calling historical daily voltage data, historical daily speed data and historical daily vibration data collected by a voltage sensor, a speed sensor and a vibration sensor in a historical database;
for the historical first Day voltage data, time abscissa and voltage data ordinate, construct historical/>The voltage data coordinate system of the day will historically be the/>Day voltage data fills in historically/>In the voltage data coordinate system of the day, the least square method is then used for the historical/>Performing curve fitting on data points in a day voltage data coordinate system to obtain historical/>A voltage curve of days;
for the historical first Day speed data, time abscissa and speed data ordinate, construct historical/>The day's velocity data coordinate system will historically be the/>Day speed data populates historic/>In the day's velocity data coordinate system, the least square method is then used to historically/>Performing curve fitting on data points in a day speed data coordinate system to obtain historical/>A day speed profile;
for the historical first Vibration data of day, time is taken as an abscissa, vibration data is taken as an ordinate, and historical/>, is constructedThe vibration data coordinate system of the day will historically be the/>Vibration data of day is filled in historically/>In the vibration data coordinate system of the day, the least square method is then used for the historical/>Performing curve fitting on data points in a vibration data coordinate system of the day to obtain historical/>Vibration curve of day.
3. The intelligent regulation and control method for the power equipment based on the fuzzy control according to claim 1, wherein the method for obtaining the historical daily voltage data fluctuation characteristic and the historical daily speed data fluctuation characteristic according to the voltage amplitude in the historical daily voltage curve and the historical daily speed curve speed amplitude comprises the following specific steps:
for acquisition history th Fluctuation characteristics of the voltage data of the day; according to historical/>A voltage curve of the day is obtained, and the historical/>All voltage magnitudes in the day's voltage curve, according to historical/>All voltage amplitudes in the day's voltage curve are obtained historically/>The fluctuation characteristics of the voltage data of the day are shown in the following specific calculation formula:
In the method, in the process of the invention, Representing historical/>Fluctuation characteristics of the voltage data of the day; /(I)Representing historical/>Variance of all voltage amplitudes in the daily voltage curve; /(I)Representing historical/>The number of voltage magnitudes in the voltage curve for the day; /(I)Representing historically the firstFirst/>, in the voltage curve of the dayA plurality of voltage magnitudes; /(I)Representing historical/>Maximum voltage amplitude in the voltage curve of the day; /(I)Representing historical/>The minimum voltage amplitude in the voltage curve of the day;
for acquisition history th Fluctuation characteristics of the day speed data; according to historical/>A day's velocity profile, obtaining historical/>All speed magnitudes in the day's speed profile, according to historical/>All the speed magnitudes in the day's speed curve are obtained historically/>The fluctuation characteristics of the day speed data are as follows:
In the method, in the process of the invention, Representing historical/>Fluctuation characteristics of the day speed data; /(I)Representing historical/>Variance of all velocity magnitudes in the day's velocity profile; /(I)Representing historical/>The number of speed magnitudes in the day's speed profile; /(I)Representing historically the firstFirst/>, in the velocity profile of the dayA respective velocity amplitude value; /(I)Representing historical/>Maximum speed amplitude in the day's speed profile; /(I)Representing historical/>The smallest speed amplitude in the day's speed profile.
4. The intelligent regulation and control method for the power equipment based on the fuzzy control according to claim 1, wherein the obtaining the speed characteristic difference value set and the voltage characteristic difference value set according to the historical daily voltage data fluctuation characteristic and the historical daily speed data fluctuation characteristic comprises the following specific methods:
According to the fluctuation characteristics of the historical daily voltage data and the fluctuation characteristics of the historical daily speed data, the voltage characteristic difference value of the historical daily and the previous day and the speed characteristic difference value of the historical daily and the previous day are obtained, and the specific calculation formula is as follows:
In the method, in the process of the invention, Representing historical/>Day and history/>Difference in the speed characteristics of the day,/>Representing historical/>Number of data in the day's speed profile; /(I)Representing historical/>First/>, in the velocity profile of the dayA respective velocity amplitude value; /(I)Representing historical/>First/>, in the velocity profile of the dayA respective velocity amplitude value; /(I)Representing historical/>Fluctuation characteristics of the day speed data; /(I)Representing historical/>Fluctuation characteristics of the day speed data; /(I)Representing historical/>Day and history/>Voltage characteristic difference of day; /(I)Representing historical/>Number of data in the day's voltage curve; /(I)Representing historical/>First/>, in the voltage curve of the dayA plurality of voltage magnitudes; /(I)Representing historical/>First/>, in the voltage curve of the dayA plurality of voltage magnitudes; /(I)Representing historical/>Fluctuation characteristics of the voltage data of the day; /(I)Representing historical/>Fluctuation characteristics of the voltage data of the day; /(I)Representing an absolute value operation;
the set of voltage characteristic differences of all the days and the previous day is recorded as a voltage characteristic difference set, and the set of speed characteristic differences of all the days and the previous day is recorded as a speed characteristic difference set.
5. The intelligent regulation and control method for the power equipment based on the fuzzy control according to claim 1, wherein the response degree between the voltage data and the speed data is obtained according to the speed characteristic difference value set and the voltage characteristic difference value set, and the specific method comprises the following steps:
and calculating the pearson correlation coefficient between the speed characteristic difference value set and the voltage characteristic difference value set, and taking the pearson correlation coefficient between the speed characteristic difference value set and the voltage characteristic difference value set as the response degree between the voltage data and the speed data.
6. The intelligent regulation and control method for the power equipment based on the fuzzy control according to claim 1, wherein the method for obtaining the stability degree parameter of the historical daily conveyor belt system according to the historical daily vibration curve comprises the following specific steps:
for acquisition history th Stability parameters of the ceiling-based conveyor system according to historical/>The vibration curve of the day is obtained, and the first/>, historicallyThe mean value of all vibration amplitudes, the variance of all vibration amplitudes and the maximum value of all vibration amplitudes in the vibration curve of the day according to the historic/>Obtaining historical/>, wherein the average value of all vibration amplitudes, the variance of all vibration amplitudes and the maximum value of all vibration amplitudes in the vibration curve of the dayThe vibration data of the day fluctuates in characteristics.
7. The intelligent regulation and control method of a power device based on fuzzy control of claim 6, wherein the acquisition history is the firstThe fluctuation characteristics of the vibration data of the day comprise the following specific calculation formulas:
In the method, in the process of the invention, Representing historical/>Stability parameters of the conveyor system; /(I)Representing historical/>Maximum vibration amplitude in the natural vibration curve; /(I)Representing historical/>The average value of all vibration amplitudes in the vibration curve of the day; /(I)Representing historical/>Variance of all vibration amplitudes in the natural vibration curve; /(I)Representing an absolute value operation.
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