Energy-saving control system

Abstract

The invention discloses an energy-saving control system, and belongs to the design of energy-saving control systems, and the system comprises a vacuum gauge tube which is used for collecting the vacuum degree data of an electric box in real time, and transmitting the vacuum degree data to a processing control module; the processing control module is used for collecting the operation frequency, the operation state and the alarm state of the frequency converter in real time, predicting the energy-saving operation frequency of the frequency converter in combination with the vacuum degree data, and sending an energy-saving operation frequency control instruction to the frequency converter; the frequency converter is used for connecting a vacuum pump set motor and adjusting the motor operation frequency of the vacuum pump set according to the energy-saving operation frequency control instruction; and the vacuum pump set is used for extracting gas in the electric box, so that the vacuum degree in the container reaches a preset target vacuum degree. The problem that the vacuum pump set is high in operation energy consumption is solved.

Description

Technical Field

[0001] The invention belongs to the technical field of energy-saving control system design, and in particular relates to an energy-saving control system based on a frequency converter to control the operating frequency of a pump group. Background Art

[0002] In the industrial production process, the energy consumption of the vacuum pump group of the electric box is often high, especially during the production line production. Although the existing technology can achieve energy-saving control by setting PID controllers, this method often consumes more computing resources and time, and the control effect is not ideal for some complex working conditions. Therefore, there is an urgent need for a control system that can achieve efficient energy saving under various working conditions. Summary of the invention

[0003] In view of the above-mentioned deficiencies in the prior art, the present invention provides an energy-saving control system based on a frequency converter to control the operating frequency of a pump group, which solves the problem of high energy consumption in the operation of a vacuum pump group.

[0004] In order to achieve the above-mentioned object of the invention, the technical solution adopted by the present invention is:

[0005] The present invention provides an energy-saving control system, comprising:

[0006] Vacuum gauge, used to collect the vacuum degree data of the electric box in real time and transmit it to the processing control module;

[0007] The processing control module is used to collect the operating frequency, operating status and alarm status of the inverter in real time, and predict the energy-saving operating frequency of the inverter in combination with the vacuum degree data, and send an energy-saving operating frequency control instruction to the inverter;

[0008] The frequency converter is used to connect the motor of the vacuum pump group and adjust the motor operating frequency of the vacuum pump group according to the energy-saving operating frequency control instruction;

[0009] The vacuum pump set is used to extract the gas in the electrical box so that the vacuum degree in the container reaches a preset target vacuum degree.

[0010] The beneficial effects of the present invention are as follows: an energy-saving control system provided by the present invention confirms the controllability of the frequency converter according to the collected operating frequency, operating status and alarm status of the frequency converter, and realizes accurate analysis and prediction of the vacuum factor of the motor operating frequency and the energy-saving operating frequency of the frequency converter by analyzing and processing the vacuum degree data of the electric box, thereby realizing sending an energy-saving operating frequency control instruction to the frequency converter to adjust the motor of the vacuum pump group to operate at the energy-saving operating frequency, so that the vacuum degree in the container reaches the preset target vacuum degree, and the system can greatly save the working energy consumption of the vacuum pump group; the present invention can greatly reduce the consumption of computing resources and time through the vacuum factor of the motor operating frequency, and provides a basis for timely and accurate regulation of the motor operating frequency of the vacuum pump group to reach the energy-saving operating frequency.

[0011] Furthermore, the processing control module includes:

[0012] The data receiving submodule is used to receive vacuum degree data, operating frequency, operating status and alarm status of the inverter;

[0013] The inverter identification submodule is used to determine that the inverter is an inverter to be regulated and in a normal working state according to the operating state and alarm state of the inverter;

[0014] The vacuum degree model building submodule is used to analyze and process the vacuum degree data of the electric box and build a real-time vacuum degree model;

[0015] The operating frequency optimization submodule is used to construct a motor operating frequency vacuum factor optimization model based on the real-time vacuum degree model;

[0016] The motor operating frequency control submodule is used to predict the energy-saving operating frequency of the inverter based on the motor operating frequency vacuum factor optimization model according to the particle swarm optimization method;

[0017] The control instruction sending submodule is used to send an energy-saving operation frequency control instruction to the inverter according to the energy-saving operation frequency of the inverter.

[0018] Furthermore, the vacuum degree model construction submodule includes:

[0019] The vacuum degree drop unit is used to construct the vacuum degree drop model of the electric box according to the vacuum degree data of the electric box:

[0020] ,

[0021] in, Indicates the cumulative vacuum drop of the electric box at time t, It indicates the decrease of vacuum degree of the electric box when vacuum extraction is performed at the maximum motor operating frequency, e indicates the exponential base constant, p indicates the vacuum degree increase parameter of gas molecule reflux, t0 indicates the time when the energy-saving operating frequency control instruction is sent, and s indicates the shape factor of the s-shaped curve, where s>1;

[0022] The instantaneous vacuum degree drop unit is used to derive the electric box vacuum degree drop model to obtain the electric box instantaneous vacuum degree drop model:

[0023] ,

[0024] in, Indicates the instantaneous vacuum degree drop of the electric box at time t in the mode of regulating the operating frequency of the vacuum pump group motor;

[0025] The vacuum degree reduction control unit is used to obtain the instantaneous vacuum degree reduction model of the electric box within the motor operating frequency control change window period according to the instantaneous vacuum degree reduction model of the electric box:

[0026] ,

[0027] in, It indicates the instantaneous vacuum degree drop of the electric box during the window period of the motor operating frequency control change. i indicates the i-th time the energy-saving operating frequency control instruction is sent. n indicates the total number of times the energy-saving operating frequency control instruction is sent. represents the normalized value of the motor operating frequency corresponding to the energy-saving operating frequency control command sent for the i-th time, ∈ represents the value of, where x i =1, corresponding to t i The vacuum pump group motor is used to extract the vacuum at the maximum operating frequency threshold at all times, and the vacuum degree can be reduced by B0. i =0, corresponding to t i The vacuum pump motor is not working at all times. , i and n are both positive integers, Indicates belonging to;

[0028] The real-time vacuum degree model unit is used to construct a real-time vacuum degree model based on the target vacuum degree of the electric box and the real-time vacuum degree of the electric box and the instantaneous vacuum degree drop model of the electric box within the window period of the motor operating frequency regulation change:

[0029] ,

[0030]

[0031] in, Indicates that the motor operating frequency control change window period Real-time vacuum degree of the electric box at any time, It indicates the instantaneous decrease of vacuum degree of the electric box during the window period of motor frequency regulation. Indicates the target vacuum degree of the electric box. Indicates the vacuum factor of the motor operating frequency, Indicates that the motor operating frequency control change window period The real-time vacuum degree of the electric box at the moment, k represents the vacuum pump group's exhaust rate proportional coefficient, and f represents the motor operating frequency of the vacuum pump group. Indicates that the motor operating frequency control change window period The pressure in the electric box at the moment, Indicates the original pressure in the electrical box.

[0032] The beneficial effect of adopting the above further scheme is as follows: the present invention constructs a model for the drop in vacuum degree of the electric box based on the vacuum degree data of the electric box, and by differentiating the model for the drop in vacuum degree of the electric box, the instantaneous drop in vacuum degree of the electric box can be obtained, and then by setting the window period for regulating the change in the motor operating frequency, and based on the instantaneous drop in vacuum degree at each moment within the window period for regulating the change in the motor operating frequency, the real-time vacuum degree of the electric box at each moment can be obtained, thereby providing a basis for reducing the motor energy consumption of the vacuum pump group while satisfying the condition of inverter regulation.

[0033] Furthermore, the calculation expression of the motor operating frequency vacuum factor optimization model is as follows:

[0034]

[0035] in, represents the value of the objective function for optimizing the vacuum factor of the motor operating frequency, Indicates that, Indicates the minimum vacuum degree.

[0036] The beneficial effect of adopting the above further scheme is: based on the real-time vacuum degree model, a corresponding motor operating frequency vacuum factor optimization model is constructed, which provides a basis for predicting the solution corresponding to the motor operating frequency vacuum factor optimization objective function value through the particle swarm algorithm, thereby solving the energy-saving operating frequency corresponding to the most efficient and energy-saving motor operating frequency of the vacuum pump group.

[0037] Furthermore, the motor operating frequency control submodule includes:

[0038] The particle swarm initialization unit is used to obtain a particle population matrix according to the particle swarm optimization method and the motor operating frequency vacuum factor optimization model, wherein the number of particles corresponding to the motor operating frequency vacuum factor optimization solution is preset to be n, and the number of populations composed of each particle is l, wherein a motor operating frequency vacuum factor optimization solution corresponds to the position of a particle, and during initialization, each particle is assigned a random real number (0,1);

[0039] A particle speed and position update unit is used to set a speed and position update model for each particle, and iteratively update and repair particles in a particle population matrix based on the speed and position update model;

[0040] The optimal solution updating unit substitutes the solution corresponding to the particles updated and repaired in each round of iteration into the motor operating frequency vacuum factor optimization model to obtain the motor operating frequency vacuum factor optimization objective function value corresponding to each solution, and based on the motor operating frequency vacuum factor optimization objective function value corresponding to each solution, updates the solution of each motor operating frequency vacuum factor optimization to obtain the historical optimal solution and the global optimal solution;

[0041] The optimization solution unit is used to determine whether the number of iterative updates of particles in the particle population matrix reaches a preset iterative update threshold. If so, the global optimal solution is used as the solution for optimizing the vacuum factor of the motor operating frequency;

[0042] The energy-saving operation frequency unit is used to solve the motor operation frequency of the corresponding vacuum pump group based on the vacuum factor optimization solution of the motor operation frequency, and use it as the energy-saving operation frequency of the inverter.

[0043] The beneficial effect of adopting the above-mentioned further scheme is as follows: the present invention iteratively updates the particles corresponding to the solution of the motor operating frequency vacuum factor optimization model according to the particle swarm optimization method, and after the number of iterative updates meets the preset iterative update threshold, the optimized solution of the motor operating frequency vacuum factor is obtained, thereby realizing the solution to obtain the energy-saving operating frequency of the inverter, providing a basis for saving the energy consumption of the vacuum pump group.

[0044] Furthermore, the calculation expression of the particle population matrix is ​​as follows:

[0045] ,

[0046] Where X represents the particle population matrix, Represents the position of the particle in the pth row and qth column in the particle population matrix.

[0047] Further, the particle velocity position updating unit comprises:

[0048] The particle iterative update subunit is used to set the speed and position update model of each particle, and iteratively update the particles in the particle population matrix to obtain the iterated value of each particle;

[0049] The first particle iteration subunit is used to determine whether the value after particle iteration is greater than 1. If so, set x pq The value after iteration is 1;

[0050] The second particle iteration subunit is used to determine whether the value after particle iteration is less than 0. If so, set x pq The value after iteration is 0;

[0051] The third particle iteration subunit is used to determine whether the value after particle iteration is between 0 and 1. If so, the target vacuum degree of the electric box corresponding to each particle in the current iteration and the vacuum factor of the motor operating frequency in the previous iteration are calculated respectively, where the current iteration is any iteration between the 2nd and nth iterations;

[0052] The particle repair subunit is used to determine whether the target vacuum degree of the electric box corresponding to each particle in the current iteration and the vacuum factor of the motor operating frequency in the previous iteration meet the particle repair conditions. If so, an integer j∈[1,i] is uniformly randomly selected, and the maximum gas production is of Time x j <1, assign 1 to x j , to optimize t j The maximum operating frequency of the motor is always used as the energy-saving operating frequency, where x j Indicates the normalized value of the motor operating frequency corresponding to the energy-saving operating frequency control instruction sent for the jth time.

[0053] The beneficial effect of adopting the above further scheme is: the present invention provides a method for iteratively updating and repairing the particle positions in the particle population matrix based on the speed position update model, thereby realizing the iterative update of the particle positions and ensuring the quality of the optimized solution of the vacuum factor of the motor operating frequency corresponding to the particles.

[0054] Furthermore, the calculation expression of the speed position update model is as follows:

[0055] ,

[0056] ,

[0057] in, Indicates the population The particle in The velocity at the iteration, w represents the inertia weight of the particle, Indicates the population The particle in The speed at the iteration, c1 represents the historical optimal position learning factor of the particle, represents the first random real number between 0 and 1 that follows a uniform distribution, Indicates the population Particles from the beginning to the The historical optimal position in the iteration process, Indicates the population The particle in The position at the iteration, c2 represents the global optimal position learning factor of the particle, represents a second random real number between 0 and 1 that follows a uniform distribution, Indicates the population Particles from the beginning to the The global optimal position in the iteration process is Indicates the population The particle in The position at the iteration, Indicates the population The particle in The position at the iteration.

[0058] The beneficial effect of adopting the above further scheme is: the present invention provides a calculation method for the speed position update model, which realizes learning the historical optimal position and the global optimal position of each particle update through the particle's historical optimal position learning degree factor and the particle's global optimal position learning degree factor, thereby indirectly improving the optimization efficiency of obtaining the particle's global optimal position.

[0059] Furthermore, the calculation expression of the particle repair condition is as follows:

[0060] .

[0061] The beneficial effect of adopting the above further scheme is: the present invention constructs particle repair conditions to repair the particles that do not meet the vacuum degree less than the preset target electric box vacuum degree, so as to ensure the quality of the optimized solution of the vacuum factor of the motor operating frequency.

[0062] Other advantages of the present invention will be analyzed in more detail in subsequent embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0064] Figure 1 The figure is a block diagram of an energy-saving control system in an embodiment of the present invention. DETAILED DESCRIPTION

[0065] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents the selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present invention.

[0066] like Figure 1 As shown, in one embodiment of the present invention, the present invention provides an energy-saving control system, comprising:

[0067] Vacuum gauge, used to collect the vacuum degree data of the electric box in real time and transmit it to the processing control module;

[0068] The processing control module is used to collect the operating frequency, operating status and alarm status of the inverter in real time, and predict the energy-saving operating frequency of the inverter in combination with the vacuum degree data, and send an energy-saving operating frequency control instruction to the inverter;

[0069] The processing control module comprises:

[0070] The data receiving submodule is used to receive vacuum degree data, operating frequency, operating status and alarm status of the inverter;

[0071] The inverter identification submodule is used to determine that the inverter is an inverter to be regulated and in a normal working state according to the operating status and alarm status of the inverter; in this scheme, when the operating frequency of the inverter is less than the maximum operating frequency threshold, the output power is less than the maximum load power threshold, the output current is less than the preset current threshold, the input voltage is between the minimum input voltage and the maximum input voltage, and no overheating alarm, communication fault alarm, and hardware alarms such as rectifier bridge, capacitor, resistor, etc. occur, then the inverter is an inverter to be regulated.

[0072] The vacuum degree model building submodule is used to analyze and process the vacuum degree data of the electric box and build a real-time vacuum degree model;

[0073] The vacuum degree model construction submodule includes:

[0074] The vacuum degree drop unit is used to construct the vacuum degree drop model of the electric box according to the vacuum degree data of the electric box:

[0075] ,

[0076] in, Indicates the cumulative vacuum drop of the electric box at time t, It indicates the decrease of vacuum degree of the electric box when vacuum extraction is performed at the maximum motor operating frequency, e indicates the exponential base constant, p indicates the vacuum degree increase parameter of gas molecule reflux, t0 indicates the time when the energy-saving operating frequency control instruction is sent, and s indicates the shape factor of the s-shaped curve, where s>1;

[0077] The instantaneous vacuum degree drop unit is used to derive the electric box vacuum degree drop model to obtain the electric box instantaneous vacuum degree drop model:

[0078] ,

[0079] in, Indicates the instantaneous vacuum degree drop of the electric box at time t in the mode of regulating the operating frequency of the vacuum pump group motor;

[0080] The vacuum degree reduction control unit is used to obtain the instantaneous vacuum degree reduction model of the electric box within the motor operating frequency control change window period according to the instantaneous vacuum degree reduction model of the electric box:

[0081] ,

[0082] in, It indicates the instantaneous vacuum degree drop of the electric box during the window period of the motor operating frequency control change. i indicates the i-th time the energy-saving operating frequency control instruction is sent. n indicates the total number of times the energy-saving operating frequency control instruction is sent. represents the normalized value of the motor operating frequency corresponding to the energy-saving operating frequency control command sent for the i-th time, ∈ represents the value of, where x i =1, corresponding to t i The vacuum pump group motor is used to extract the vacuum at the maximum operating frequency threshold at all times, and the vacuum degree can be reduced by B0. i =0, corresponding to t i The vacuum pump motor is not working at all times. , i and n are both positive integers, Indicates belonging to; In this scheme, the normalized value of the operating frequency is the normalized value between the minimum operating frequency and the maximum operating frequency of the motor of the vacuum pump group;

[0083] The real-time vacuum degree model unit is used to construct a real-time vacuum degree model based on the target vacuum degree of the electric box and the real-time vacuum degree of the electric box and the instantaneous vacuum degree drop model of the electric box within the window period of the motor operating frequency regulation change:

[0084] ,

[0085]

[0086] in, Indicates that the motor operating frequency control change window period Real-time vacuum degree of the electric box at any time, It indicates the instantaneous decrease of vacuum degree of the electric box during the window period of motor frequency regulation. Indicates the target vacuum degree of the electric box. Indicates the vacuum factor of the motor operating frequency, Indicates that the motor operating frequency control change window period The real-time vacuum degree of the electric box at the moment, k represents the vacuum pump group's exhaust rate proportional coefficient, and f represents the motor operating frequency of the vacuum pump group. Indicates that the motor operating frequency control change window period The pressure in the electric box at the moment, Indicates the original pressure in the electrical box.

[0087] The operating frequency optimization submodule is used to construct a motor operating frequency vacuum factor optimization model based on the real-time vacuum degree model;

[0088] The calculation expression of the motor operating frequency vacuum factor optimization model is as follows:

[0089]

[0090] in, represents the value of the objective function for optimizing the vacuum factor of the motor operating frequency, Indicates that, Indicates the minimum vacuum degree.

[0091] The process of the vacuum pump group extracting gas from the container to ensure the vacuum degree has the characteristics of large inertia, strong uncertainty and nonlinearity, so it is easy to cause vacuum extraction system oscillation. The motor operating frequency control submodule can dynamically follow the real-time vacuum degree data of the vacuum pump group to adjust the operating frequency of the vacuum pump group motor through the frequency converter.

[0092] The motor operating frequency control submodule is used to predict the energy-saving operating frequency of the inverter based on the motor operating frequency vacuum factor optimization model according to the particle swarm optimization method;

[0093] The motor operating frequency control submodule includes:

[0094] The particle swarm initialization unit is used to obtain a particle population matrix according to the particle swarm optimization method and the motor operating frequency vacuum factor optimization model, wherein the number of particles corresponding to the motor operating frequency vacuum factor optimization solution is preset to be n, and the number of populations composed of each particle is l, wherein a motor operating frequency vacuum factor optimization solution corresponds to the position of a particle, and during initialization, each particle is assigned a random real number (0,1);

[0095] The calculation expression of the particle population matrix is ​​as follows:

[0096] ,

[0097] Where X represents the particle population matrix, Represents the position of the particle in the pth row and qth column in the particle population matrix.

[0098] A particle speed and position update unit is used to set a speed and position update model for each particle, and iteratively update and repair particles in a particle population matrix based on the speed and position update model;

[0099] The particle velocity position updating unit comprises:

[0100] The particle iterative update subunit is used to set the speed and position update model of each particle, and iteratively update the particles in the particle population matrix to obtain the iterated value of each particle;

[0101] The calculation expression of the speed position update model is as follows:

[0102] ,

[0103] ,

[0104] in, Indicates the population The particle in The velocity at the iteration, w represents the inertia weight of the particle, Indicates the population The particle in The speed at the iteration, c1 represents the historical optimal position learning factor of the particle, represents the first random real number between 0 and 1 that follows a uniform distribution, Indicates the population Particles from the beginning to the The historical optimal position in the iteration process, Indicates the population The particle in The position at the iteration, c2 represents the global optimal position learning factor of the particle, represents a second random real number between 0 and 1 that follows a uniform distribution, Indicates the population Particles from the beginning to the The global optimal position in the iteration process is Indicates the population The particle in The position at the iteration, Indicates the population The particle in The position at the iteration.

[0105] The first particle iteration subunit is used to determine whether the value after particle iteration is greater than 1. If so, set x pq The value after iteration is 1;

[0106] The second particle iteration subunit is used to determine whether the value after particle iteration is less than 0. If so, set x pq The value after iteration is 0;

[0107] The third particle iteration subunit is used to determine whether the value after particle iteration is between 0 and 1. If so, the target vacuum degree of the electric box corresponding to each particle in the current iteration and the vacuum factor of the motor operating frequency in the previous iteration are calculated respectively, where the current iteration is any iteration between the 2nd and nth iterations;

[0108] The particle repair subunit is used to determine whether the target vacuum degree of the electric box corresponding to each particle in the current iteration and the vacuum factor of the motor operating frequency in the previous iteration meet the particle repair conditions. If so, an integer j∈[1,i] is uniformly randomly selected, and the maximum gas production is of Time x j <1, assign 1 to x j , to optimize t j The maximum operating frequency of the motor is always used as the energy-saving operating frequency, where x j Indicates the normalized value of the motor operating frequency corresponding to the energy-saving operating frequency control instruction sent for the jth time.

[0109] The calculation expression of the particle repair condition is as follows:

[0110] .

[0111] The optimal solution updating unit substitutes the solution corresponding to the particles updated and repaired in each round of iteration into the motor operating frequency vacuum factor optimization model to obtain the motor operating frequency vacuum factor optimization objective function value corresponding to each solution, and based on the motor operating frequency vacuum factor optimization objective function value corresponding to each solution, updates the solution of each motor operating frequency vacuum factor optimization to obtain the historical optimal solution and the global optimal solution;

[0112] The optimization solution unit is used to determine whether the number of iterative updates of particles in the particle population matrix reaches a preset iterative update threshold. If so, the global optimal solution is used as the solution for optimizing the vacuum factor of the motor operating frequency;

[0113] The energy-saving operation frequency unit is used to solve the motor operation frequency of the corresponding vacuum pump group based on the vacuum factor optimization solution of the motor operation frequency, and use it as the energy-saving operation frequency of the inverter.

[0114] The control instruction sending submodule is used to send an energy-saving operation frequency control instruction to the inverter according to the energy-saving operation frequency of the inverter.

[0115] The frequency converter is used to connect the motor of the vacuum pump group and adjust the motor operating frequency of the vacuum pump group according to the energy-saving operating frequency control instruction;

[0116] The vacuum pump set is used to extract the gas in the electrical box so that the vacuum degree in the container reaches a preset target vacuum degree.

[0117] The present invention is based on a real-time vacuum degree model, and correspondingly constructs a motor operating frequency vacuum factor optimization model. According to a particle swarm optimization method, the particles corresponding to the solution of the motor operating frequency vacuum factor optimization model are iteratively updated and optimized, thereby realizing continuous and dynamic regulation of the motor operating frequency of the inverter according to the optimized solution of the motor operating frequency vacuum factor, so that the motor of the vacuum pump group works at an energy-saving operating frequency, thereby ensuring that the vacuum degree of the electric box is at a preset target vacuum degree of the electric box, and at the same time, the energy consumption of the vacuum pump group is most efficiently and fully reduced.

[0118] In addition, in a practical example, the energy-saving control system provided by the present solution also includes a touch screen for inputting a preset target vacuum degree of the electric box to the processing control module in real time, thereby realizing timely adjustment of the target vacuum degree of the electric box according to actual requirements through manual interaction.

[0119] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. An energy-saving control system, characterized in that: include: Vacuum gauge, used to collect the vacuum degree data of the electric box in real time and transmit it to the processing control module; The processing control module is used to collect the operating frequency, operating status and alarm status of the inverter in real time, and predict the energy-saving operating frequency of the inverter in combination with the vacuum degree data, and send an energy-saving operating frequency control instruction to the inverter; The frequency converter is used to connect the motor of the vacuum pump group and adjust the motor operating frequency of the vacuum pump group according to the energy-saving operating frequency control instruction; The vacuum pump set is used to extract the gas in the electrical box so that the vacuum degree in the container reaches a preset target vacuum degree.

2. The energy-saving control system according to claim 1, characterized in that: A touch screen is also included for inputting a preset target vacuum level of the electric box into the process control module in real time.

3. The energy-saving control system according to claim 2, characterized in that: The processing control module comprises: The data receiving submodule is used to receive vacuum degree data, operating frequency, operating status and alarm status of the inverter; The inverter identification submodule is used to determine that the inverter is an inverter to be regulated and in a normal working state according to the operating state and alarm state of the inverter; The vacuum degree model building submodule is used to analyze and process the vacuum degree data of the electric box and build a real-time vacuum degree model; The operating frequency optimization submodule is used to construct a motor operating frequency vacuum factor optimization model based on the real-time vacuum degree model; The motor operating frequency control submodule is used to predict the energy-saving operating frequency of the inverter based on the motor operating frequency vacuum factor optimization model according to the particle swarm optimization method; The control instruction sending submodule is used to send an energy-saving operation frequency control instruction to the inverter according to the energy-saving operation frequency of the inverter.

4. The energy-saving control system according to claim 3, characterized in that: The vacuum degree model construction submodule includes: The vacuum degree drop unit is used to construct the vacuum degree drop model of the electric box according to the vacuum degree data of the electric box: ， in, Indicates the cumulative vacuum drop of the electric box at time t, It indicates the decrease of vacuum degree of the electric box when vacuum extraction is performed at the maximum motor operating frequency, e indicates the exponential base constant, p indicates the vacuum degree increase parameter of gas molecule reflux, t0 indicates the time when the energy-saving operating frequency control instruction is sent, and s indicates the shape factor of the s-shaped curve, where s>1; The instantaneous vacuum degree drop unit is used to derive the electric box vacuum degree drop model to obtain the electric box instantaneous vacuum degree drop model: ， in, Indicates the instantaneous vacuum degree drop of the electric box at time t in the mode of regulating the operating frequency of the vacuum pump group motor; The vacuum degree reduction control unit is used to obtain the instantaneous vacuum degree reduction model of the electric box within the motor operating frequency control change window period according to the instantaneous vacuum degree reduction model of the electric box: ， in, It indicates the instantaneous vacuum degree drop of the electric box during the window period of the motor operating frequency control change. i indicates the i-th time the energy-saving operating frequency control instruction is sent. n indicates the total number of times the energy-saving operating frequency control instruction is sent. represents the normalized value of the motor operating frequency corresponding to the energy-saving operating frequency control command sent for the i-th time, ∈ represents the value of, where x i =1, corresponding to t i The vacuum pump group motor is used to extract the vacuum at the maximum operating frequency threshold at all times, and the vacuum degree can be reduced by B0. i =0, corresponding to t i The vacuum pump motor is not working at all times. , i and n are both positive integers, Indicates belonging to; The real-time vacuum degree model unit is used to construct a real-time vacuum degree model based on the target vacuum degree of the electric box and the real-time vacuum degree of the electric box and the instantaneous vacuum degree drop model of the electric box within the window period of the motor operating frequency regulation change: ， in, Indicates that the motor operating frequency control change window period Real-time vacuum degree of the electric box at any time, It indicates the instantaneous decrease of vacuum degree of the electric box during the window period of motor frequency regulation. Indicates the target vacuum degree of the electric box. Indicates the vacuum factor of the motor operating frequency, Indicates that the motor operating frequency control change window period The real-time vacuum degree of the electric box at the moment, k represents the vacuum pump group's exhaust rate proportional coefficient, and f represents the motor operating frequency of the vacuum pump group. Indicates that the motor operating frequency control change window period The pressure in the electric box at the moment, Indicates the original pressure in the electrical box.

5. The energy-saving control system according to claim 4, characterized in that: The calculation expression of the motor operating frequency vacuum factor optimization model is as follows: in, represents the value of the objective function for optimizing the vacuum factor of the motor operating frequency, Indicates that, Indicates the minimum vacuum degree.

6. The energy-saving control system according to claim 5, characterized in that: The motor operating frequency control submodule includes: The particle swarm initialization unit is used to obtain a particle population matrix according to the particle swarm optimization method and the motor operating frequency vacuum factor optimization model, wherein the number of particles corresponding to the motor operating frequency vacuum factor optimization solution is preset to be n, and the number of populations composed of each particle is l, wherein a motor operating frequency vacuum factor optimization solution corresponds to the position of a particle, and during initialization, each particle is assigned a random real number (0,1); A particle speed and position update unit is used to set a speed and position update model for each particle, and iteratively update and repair particles in a particle population matrix based on the speed and position update model; The optimal solution updating unit substitutes the solution corresponding to the particles updated and repaired in each round of iteration into the motor operating frequency vacuum factor optimization model to obtain the motor operating frequency vacuum factor optimization objective function value corresponding to each solution, and based on the motor operating frequency vacuum factor optimization objective function value corresponding to each solution, updates the solution of each motor operating frequency vacuum factor optimization to obtain the historical optimal solution and the global optimal solution; The optimization solution unit is used to determine whether the number of iterative updates of particles in the particle population matrix reaches a preset iterative update threshold. If so, the global optimal solution is used as the solution for optimizing the vacuum factor of the motor operating frequency; The energy-saving operation frequency unit is used to solve the motor operation frequency of the corresponding vacuum pump group based on the vacuum factor optimization solution of the motor operation frequency, and use it as the energy-saving operation frequency of the inverter.

7. The energy-saving control system according to claim 6, characterized in that: The calculation expression of the particle population matrix is ​​as follows: ， Where X represents the particle population matrix, Represents the position of the particle in the pth row and qth column in the particle population matrix.

8. The energy-saving control system according to claim 7, characterized in that: The particle velocity position updating unit comprises: The particle iterative update subunit is used to set the speed and position update model of each particle, and iteratively update the particles in the particle population matrix to obtain the iterated value of each particle; The first particle iteration subunit is used to determine whether the value after particle iteration is greater than 1. If so, set x pq The value after iteration is 1; The second particle iteration subunit is used to determine whether the value after particle iteration is less than 0. If so, set x pq The value after iteration is 0; The third particle iteration subunit is used to determine whether the value after particle iteration is between 0 and 1. If so, the target vacuum degree of the electric box corresponding to each particle in the current iteration and the vacuum factor of the motor operating frequency in the previous iteration are calculated respectively, where the current iteration is any iteration between the 2nd and nth iterations; The particle repair subunit is used to determine whether the target vacuum degree of the electric box corresponding to each particle in the current iteration and the vacuum factor of the motor operating frequency in the previous iteration meet the particle repair conditions. If so, an integer j∈[1,i] is uniformly randomly selected, and the maximum gas production is of Time x j <1, assign 1 to x j , to optimize t j The maximum operating frequency of the motor is always used as the energy-saving operating frequency, where x j Indicates the normalized value of the motor operating frequency corresponding to the energy-saving operating frequency control instruction sent for the jth time.

9. The energy-saving control system according to claim 8, characterized in that: The calculation expression of the speed position update model is as follows: , , in, Indicates the population The particle in The velocity at the iteration, w represents the inertia weight of the particle, Indicates the population The particle in The speed at the iteration, c1 represents the learning degree factor of the particle's historical optimal position, represents the first random real number between 0 and 1 that follows a uniform distribution, Indicates the population Particles from the beginning to the The historical optimal position in the iteration process, Indicates the population The particle in The position at the iteration, c2 represents the global optimal position learning factor of the particle, represents a second random real number between 0 and 1 that follows a uniform distribution, Indicates the population Particles from the beginning to the The global optimal position in the iteration process is Indicates the population The particle in The position at the iteration, Indicates the population The particle in The position at the iteration.

10. The energy-saving control system according to claim 9, characterized in that: The calculation expression of the particle repair condition is as follows: 。

Images