A self-adaptive vibration isolation control method for a phase separation closed bus

Abstract

The application discloses a self-adaptive vibration isolation control method for a phase-separated closed bus, and is characterized in that an equivalent fourteen-degree-of-freedom vibration isolation system dynamic model is established in combination with the internal structure of the phase-separated closed bus and the phase interval installation mode of a magneto-rheological elastomer vibration isolator; after input and output variables of the dynamic model are determined, a fuzzy controller is designed, the input variables are fuzzed, fuzzy rules are formulated, and output variables are obtained after defuzzification; and the quantization factor parameters of the fuzzy controller are determined, the calculated control current is output to the magneto-rheological elastomer vibration isolator, and the stiffness and damping of the vibration isolator are changed. The self-adaptive vibration isolation control method can fully exert the mechanical characteristics of variable stiffness and variable damping of the magneto-rheological elastomer vibration isolator, efficiently suppress the vibration generated under normal working and short-circuit current conditions of the phase-separated closed bus, and has important practical significance for ensuring the safety of equipment and the stability of a power system.

Description

Technical Field

[0001] This invention relates to vibration isolation control technology for power equipment, and in particular to an adaptive vibration isolation control method for isolated phase closed busbars. Background Technology

[0002] As a crucial device for current and power transmission between equipment in pumped-storage power plants and substations, the performance of isolated-phase busbars is closely related to the safe and stable operation of the pumped-storage power plant and the entire power system. Under normal operating conditions, although the vibration amplitude of each component in the isolated-phase busbar is small, prolonged micro-vibrations can lead to insulator loosening and subsequent faults. Furthermore, when a short-circuit fault occurs in the isolated-phase busbar, the large short-circuit current generates enormous electrodynamic forces, causing severe vibrations and ultimately damaging the equipment, jeopardizing power system safety. Besides short-circuit faults, when electrical equipment experiences poor heat dissipation or severe wear during operation, the connected isolated-phase busbar will continuously heat up and eventually burn out. When pumps in pumped-storage power plants pump water, the impact of the water flow or the seismic impact during earthquakes can also cause vibrations in the isolated-phase busbar, leading to partial discharge corrosion of the insulators and gradual damage. Considering the hazards of vibration to isolated-phase busbars and the power system, it is necessary to conduct vibration isolation research on isolated-phase busbars.

[0003] Vibration isolation of isolated-phase enclosed busbars essentially isolates the vibration patterns of various components under complex excitation. Current passive vibration isolation methods, which improve processes, design reasonable stiffness, and add passive vibration isolation pads, are limited to isolated-phase enclosed busbars of specific dimensions and operating conditions. They cannot adaptively isolate vibrations based on the complex vibration characteristics under different operating conditions, and passive vibration isolation pads will eventually wear out with long-term use, thus their isolation efficiency needs improvement. Furthermore, while active vibration isolation methods, such as installing adjustable stiffness and damping air spring vibration isolators at the bottom of the steel frame, can achieve adaptive vibration isolation, the isolators operate continuously, resulting in energy waste, high energy consumption, complex structure, and high cost. Summary of the Invention

[0004] The purpose of this invention is to solve the above problems and provide an adaptive vibration isolation control method for isolated closed busbars. Starting from the internal structure and vibration characteristics of isolated closed busbars, and combining magnetorheological elastomer vibration isolators and fuzzy control strategies, an adaptive vibration isolation control system for isolated closed busbars that takes into account the internal structure is established.

[0005] The above-mentioned technical problem of the present invention is mainly solved by the following technical solution: an adaptive vibration isolation control method for a phase-separated enclosed busbar, characterized by comprising the following steps:

[0006] Step 1: Establish an equivalent 14-degree-of-freedom vibration isolation system dynamic model by combining the internal structure of the phase-separated enclosed busbar and the phase-to-phase installation method of the magnetorheological elastomer vibration isolator.

[0007] Step two: After determining the input and output variables of the dynamic model, design a fuzzy controller, fuzzify the input variables, formulate fuzzy rules, and then defuzzify to obtain the output variables.

[0008] Step 3: Determine the quantization factor parameters of the fuzzy controller, and output the calculated control current to the magnetorheological elastomer isolator to change the stiffness and damping of the isolator, thereby achieving the isolation effect of the phase-separated closed busbar.

[0009] The aforementioned adaptive vibration isolation control method for isolated phase enclosed busbars is characterized in that: in step one, the isolated phase enclosed busbars consider the shells and conductors of phases A, B, and C, with equivalent masses corresponding to m respectively. A1 m A2 m B1 m B2 m C1 and m C2 The magnetorheological elastomer vibration isolator considers its initial stiffness and variable stiffness and damping. The equivalent initial stiffness, variable stiffness and damping are k4, k, and k, respectively. x and c x The horizontal motion equations of the established fourteen-degree-of-freedom vibration isolation system dynamic model are defined as follows:

[0010]

[0011] The equation of motion in the vertical direction is defined as:

[0012]

[0013]

[0014]

[0015] Where F wk1 F wk2 F wk3 These represent the interphase forces of phases A, B, and C, respectively; m1 is the equivalent mass of the bottom steel frame structure; k1 and c1 represent the equivalent stiffness and damping between the shell and the conductor, respectively; k2 represents the equivalent stiffness between the shell and the supporting structure; k3 represents the equivalent stiffness between the steel frame structure and the ground; k4 and k5 represent the equivalent initial constant stiffness of the phase isolators; k x and c x X1 represents the equivalent variable stiffness and damping of the vibration isolator; X2 and X3 represent the vertical displacements of the steel frame structure, the shell, and the conductor, respectively; and X4, X5, and X6 represent the horizontal displacements of phase A, phase B, and phase C, respectively.

[0016] The aforementioned adaptive vibration isolation control method for a phase-separated enclosed busbar is characterized in that, in step two, the input variables correspond to the horizontal and vertical displacements of each phase, and the output variable is the control current of the magnetorheological isolator.

[0017] The aforementioned adaptive vibration isolation control method for isolated closed busbars is characterized in that the relationship between the equivalent parameters of the magnetorheological isolator and the control current I is as follows:

[0018]

[0019] Where f y This is the damping force after the vibration isolator yields.

[0020] The aforementioned adaptive vibration isolation control method for isolated closed busbars is characterized by the following fuzzy rule formulation: the input membership degree and output membership degree adopted by the fuzzy control are discretized by the fuzzy subsets of the input variable displacement difference and relative velocity as: negative large (NB), negative small (NS), zero (ZE), positive small (PS) and positive large (PB), and the fuzzy subsets of the output variable current are discretized as: zero (ZE), small (S), medium small (SM), medium (M), medium large (BM) and large (B), and the membership function adopts Gaussian type.

[0021] The aforementioned adaptive vibration isolation control method for isolated phase closed busbars is characterized in that the specific current values ​​obtained through fuzzy processing are defuzzified to obtain fuzzy decision results.

[0022] Compared with existing technologies, the beneficial effects of this invention are as follows: the adaptive vibration isolation control strategy has significant practical implications for efficiently suppressing the vibration of isolated closed busbars under different operating conditions. An adaptive vibration isolation control method for isolated closed busbars considering the internal structure is proposed. Starting from the internal structure of the isolated closed busbar, and combining the mechanical characteristics of the magnetorheological elastomer isolator, which allows for rapid changes in stiffness and damping under different magnetic field environments, a 14-degree-of-freedom vibration isolation system dynamic model is established. Addressing the complex excitation forms during the operation of the isolated closed busbar, the control current of the isolator is calculated using a fuzzy control algorithm, thereby changing the stiffness and damping of the isolator. This fully utilizes the variable stiffness and variable damping mechanical characteristics of the magnetorheological elastomer isolator, effectively suppressing the vibration generated by the isolated closed busbar under normal operation and short-circuit current conditions. It can effectively reduce the vibration displacement and acceleration of the isolated closed busbar under normal operating conditions and short-circuit faults, significantly improving the vibration problem of the isolated closed busbar. Attached Figure Description

[0023] Figure 1 This is a flowchart of an adaptive vibration isolation control method for a phase-separated enclosed busbar according to the present invention.

[0024] Figure 2 This is a schematic diagram of the dynamic model of a fourteen-degree-of-freedom vibration isolation system considering the internal structure of a phase-separated enclosed busbar according to the present invention.

[0025] Figure 3 This is a flowchart of the fuzzy control algorithm of the present invention.

[0026] Figure 4 This is the membership function graph of the input variables in this invention.

[0027] Figure 5 This is the membership function graph of the output variables of this invention.

[0028] Figure 6 This is a diagram of the decision-making results of fuzzy rule reasoning.

[0029] Figure 7 It is a graph showing the changes in the equivalent stiffness and damping of the vibration isolator with the control current. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of the present invention clearer, the technical solutions of the present invention will be further described in detail below through embodiments and in conjunction with the accompanying drawings.

[0031] This embodiment presents an adaptive vibration isolation control method for isolated closed busbars, such as... Figure 1 As shown, it includes the following steps:

[0032] Step 1: Establish an equivalent 14-degree-of-freedom vibration isolation system dynamic model by combining the shell, conductor, etc. of each phase in the internal structure of the phase-separated enclosed busbar, as well as the phase-to-phase installation method of the magnetorheological elastomer vibration isolators between the shells of each phase.

[0033] The outer shell and conductors are replaced by equivalent mass, and the magnetorheological elastomer vibration isolator is replaced by initial stiffness, variable stiffness, and damping, as follows: Figure 2 As shown, the isolated phase busbar considers the outer casing and conductors of phases A, B, and C, with equivalent masses corresponding to m respectively. A1 m A2 m B1 m B2 m C1 and m C2 The magnetorheological elastomer vibration isolator considers its initial stiffness and variable stiffness and damping. The equivalent initial stiffness, variable stiffness and damping are k4, k, and k, respectively. x and c x .

[0034] Based on the displacements caused by the horizontal and vertical forces acting on the isolated closed busbar during actual operation, the dynamic model of the fourteen-degree-of-freedom system establishes the equations of motion for the horizontal and vertical directions as follows:

[0035]

[0036]

[0037]

[0038]

[0039] Where: m A1 m A2 m B1 m B2 m C1 and m C2 Let m1 represent the equivalent mass of the A-phase shell and conductor, the B-phase shell and conductor, and the C-phase shell and conductor, respectively; m1 is the equivalent mass of the bottom steel frame structure; k1 and c1 represent the equivalent stiffness and damping between the shell and conductor, respectively; k2 represents the equivalent stiffness between the shell and the supporting structure; k3 represents the equivalent stiffness between the steel frame structure and the ground; k4 and k5 represent the equivalent initial constant stiffness of the phase isolators; k... x and c x X1 represents the equivalent variable stiffness and damping of the MRE vibration isolator; X2 and X3 represent the vertical displacements of the steel frame structure, shell, and conductor, respectively; and X4, X5, and X6 represent the horizontal displacements of phase A, phase B, and phase C, respectively.

[0040] The equivalent model of the magnetorheological elastic vibration isolator uses the improved Bingham model, and the expression for the output force is as follows:

[0041]

[0042] Where f y This represents the damping force after the isolator yields. The relationship between the equivalent parameters of the magnetorheological isolator and the control current I in the improved Bingham model is as follows:

[0043]

[0044] Step two involves designing a fuzzy controller after determining the input and output variables of the dynamic model. The input variables are fuzzified, and after establishing fuzzy rules, the fuzziness is resolved to obtain the output variables. The input variables correspond to the horizontal and vertical displacements of each phase, respectively, and the output variable is the control current of the magnetorheological isolator.

[0045] First, design a fuzzy control strategy, such as... Figure 3The fuzzy control algorithm shown defines the inputs of the dynamic model as the displacements and velocities of each phase conductor and the shell due to vibration, and the output variable as the control current of the magnetorheological elastomer isolator. Then, the fuzzy subsets of the input variables, displacement difference and relative velocity, are discretized as: negative large (NB), negative small (NS), zero (ZE), positive small (PS), and positive large (PB). The fuzzy subsets of the output variable, current, are discretized as: zero (ZE), small (S), medium small (SM), medium (M), medium large (BM), and large (B). The membership functions are all Gaussian, such as... Figure 4 , Figure 5 As shown. The specific current values ​​obtained through fuzzy processing are then defuzzified to obtain the fuzzy decision results, outputting the curves showing the correspondence between the control current and the input displacement and velocity, as shown. Figure 6 As shown.

[0046] Step 3: Determine the quantization factor parameter k of the fuzzy controller. e k c The quantization factors for relative displacement, relative velocity, and control current, ki and , respectively, are used to determine these parameters. The determination of these parameters requires considering the relative weights of masses in the corresponding dynamic equations, and adjusting the quantization factors to ensure that the maximum peak value of the input signal is within the input domain of the fuzzy controller. The control current calculated by the fuzzy controller is output to the magnetorheological elastomer isolator, changing its stiffness and damping, thereby achieving the isolation effect of the isolated busbar. The curves showing the variation of the isolator's equivalent stiffness and damping with the control current are shown below. Figure 7 .

[0047] The above embodiments are illustrative of some embodiments of the present invention and are not intended to limit the present invention. Based on the spirit of the present invention, any simple modifications to the present invention made by those skilled in the art without departing from the principles of the present technical solution and without creative effort shall fall within the protection scope of the present invention.

Claims

1. An adaptive vibration isolation control method for isolated phase closed busbars, characterized in that, Includes the following steps: Step 1: Establish an equivalent 14-degree-of-freedom vibration isolation system dynamic model by combining the internal structure of the phase-separated enclosed busbar and the phase-to-phase installation method of the magnetorheological elastomer vibration isolator; Step 2: After determining the input and output variables of the dynamic model, design a fuzzy controller, fuzzify the input variables, formulate fuzzy rules, and then defuzzify to obtain the output variables. Step 3: Determine the quantization factor parameters of the fuzzy controller, and output the calculated control current to the magnetorheological elastomer vibration isolator to change the stiffness and damping of the vibration isolator, thereby achieving the vibration isolation effect of the phase-separated closed busbar. In step one, the phase-separated enclosed busbar considers the outer casing and conductors of phases A, B, and C, with equivalent masses corresponding to m respectively. A1 m A2 m B1 m B2 m C1 and m C2 The magnetorheological elastomer vibration isolator considers its initial stiffness and variable stiffness and damping. The equivalent initial stiffness, variable stiffness and damping are k4, k, and k, respectively. x and c x The horizontal motion equations of the established fourteen-degree-of-freedom vibration isolation system dynamic model are defined as follows: The equation of motion in the vertical direction is defined as: Where F wk1 F wk2 F wk3 These represent the interphase forces of phases A, B, and C, respectively; m1 is the equivalent mass of the bottom steel frame structure; k1 and c1 represent the equivalent stiffness and damping between the shell and the conductor, respectively; k2 represents the equivalent stiffness between the shell and the supporting structure; k3 represents the equivalent stiffness between the steel frame structure and the ground; k4 and k5 represent the equivalent initial constant stiffness of the phase isolators; k x and c x X1 represents the equivalent variable stiffness and damping of the vibration isolator; X2 and X3 represent the vertical displacements of the steel frame structure, the shell, and the conductor, respectively; and X4, X5, and X6 represent the horizontal displacements of phase A, phase B, and phase C, respectively.

2. The adaptive vibration isolation control method for a phase-separated enclosed busbar according to claim 1, characterized in that, In step two, the input variables correspond to the horizontal and vertical displacements of each phase, respectively, and the output variable is the control current of the magnetorheological isolator.

3. The adaptive vibration isolation control method for a phase-separated enclosed busbar according to claim 1, characterized in that, The relationship between the equivalent parameters of the magnetorheological vibration isolator and the control current I is as follows: in This is the damping force after the vibration isolator yields.

4. The adaptive vibration isolation control method for a phase-separated enclosed busbar according to claim 1 or 2, characterized in that, The fuzzy rules are formulated as follows: the input membership degree and output membership degree adopted by fuzzy control are discretized by the input variable displacement difference and relative velocity fuzzy subsets as: negative large (NB), negative small (NS), zero (ZE), positive small (PS) and positive large (PB), and the output variable current fuzzy subsets are discretized as: zero (ZE), small (S), medium small (SM), medium (M), medium large (BM) and large (B). The membership function adopts Gaussian type.

5. The adaptive vibration isolation control method for a phase-separated enclosed busbar according to claim 4, characterized in that, The specific current values ​​obtained through fuzzy processing are then defuzzified to obtain fuzzy decision results.

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