Double-rotor engine vibration control method, device, equipment, medium and product

Abstract

The invention relates to the technical field of aero-engines, in particular to a double-rotor engine vibration control method and device, equipment, a medium and a product, and the method comprises the steps that based on a comparison result of rotor amplitude and a preset amplitude threshold value, amplitude information of a double-rotor engine is obtained, the amplitude information is quantized, and a fuzzy input quantity is obtained; calculating a fuzzy output quantity based on the fuzzy input quantity by using a membership function and a fuzzy control rule; calculating a gain coefficient variation based on the fuzzy output quantity; calculating the control positive pressure of the proportional-integral controller based on the gain coefficient variation; and performing vibration control on the rotors of the dual-rotor engine based on the control positive pressure. The fuzzy input quantity of the fuzzy controller is obtained through the amplitude information of the double-rotor engine, and after the fuzzy input quantity is applied to the master control type elastic supporting dry friction damper, the damper can change the rigidity and damping so as to control rotor vibration, and it is guaranteed that a rotor system has the optimal dynamic and static performance.

Description

Technical Field

[0001] The present disclosure relates to the technical field of aeroengines, and in particular, to a vibration control method, device, equipment, medium and product for a dual-rotor engine. Background Art

[0002] As a core component of an aircraft, the main configuration of an aeroengine is a dual-rotor system configuration with an intermediate bearing, including two rotors: a low-pressure rotor and a high-pressure rotor. However, to this day, aircraft still cannot escape the problem of vibration. To solve the vibration problem, designers have designed a new type of rotor damping and vibration reduction device that uses an elastic support based on dry friction energy dissipation, namely a main control type elastic support dry friction damper. During the operation of the rotor, the dry friction damper can simultaneously change the additional stiffness and additional damping of the rotor, which can not only provide damping for vibration reduction but also adjust the critical speed, combining the advantages of high reliability of dry friction and active control.

[0003] Although the prior art has made structural improvements to the main control type elastic support dry friction damper to make it possible to be applied to aeroengines, in terms of active control, it mostly uses the PI control method. For aeroengines operating in complex environments with variable working conditions, the traditional PI control parameters are fixed and the regulation of environmental changes is poor. When the operating environment of the aeroengine changes severely and the working conditions change drastically, the traditional proportional-integral controller (PI controller) often cannot obtain good control effects. Therefore, the existing dampers have their respective limitations when applied to aeroengines, and the control method of the main control type elastic support dry friction damper still has the above-mentioned deficiencies. Summary of the Invention

[0004] In view of the above problems, the present disclosure is proposed. The present disclosure provides a vibration control method, device, equipment, medium and product for a dual-rotor engine.

[0005] According to one aspect of the present disclosure, a vibration control method for a dual-rotor engine is provided, including:

[0006] When it is confirmed that the rotor speed of the dual-rotor engine is within the rotor control range, based on the comparison result between the rotor amplitude and a preset amplitude threshold, obtain the amplitude information of the dual-rotor engine;

[0007] Quantify the amplitude information of the dual-rotor engine to obtain a fuzzy input quantity for a fuzzy controller;

[0008] Based on the fuzzy input quantity, use the membership function and fuzzy control rules to calculate and obtain the fuzzy output quantity of the fuzzy controller;

[0009] Based on the fuzzy output quantity, calculate the change amount of the gain coefficient corresponding to the fuzzy output quantity;

[0010] Calculate the control positive pressure of the proportional-integral controller based on the change amount of the gain coefficient;

[0011] Perform vibration control on the rotor of the dual-rotor engine based on the control positive pressure.

[0012] In addition, for the dual-rotor engine vibration control method according to an aspect of the present disclosure, based on the fuzzy input quantity, using the membership function and fuzzy control rules, calculate and obtain the fuzzy output quantity of the fuzzy controller, including:

[0013] Convert the fuzzy input quantity into a fuzzy input vector using the membership function;

[0014] Based on the fuzzy control rules, perform inference on the fuzzy input vector, and calculate to obtain the fuzzy output vector of the fuzzy controller;

[0015] Based on the fuzzy output vector, obtain the fuzzy output quantity of the fuzzy controller using the membership function and fuzzy control rules.

[0016] In addition, for the dual-rotor engine vibration control method according to an aspect of the present disclosure, calculate the control positive pressure of the proportional-integral controller based on the change amount of the gain coefficient, including:

[0017] Obtain the initial gain coefficient of the proportional-integral controller;

[0018] Based on the sum of the change amount of the gain coefficient and the initial gain coefficient, obtain the gain coefficient of the proportional-integral controller;

[0019] Based on the gain coefficient, calculate the control positive pressure of the proportional-integral controller.

[0020] In addition, for the dual-rotor engine vibration control method according to an aspect of the present disclosure, the gain coefficient includes a proportional coefficient and an integral coefficient;

[0021] Based on the gain coefficient, calculate the control positive pressure of the proportional-integral controller, including:

[0022] Based on the comparison result between the rotor amplitude and the amplitude threshold, obtain the error and cumulative error of the proportional-integral controller;

[0023] Calculate the product of the proportional coefficient and the error to obtain a first product value; and calculate the product of the integral coefficient and the sum of the error and the cumulative error to obtain a second product value;

[0024] Based on the first product value and the second product value, calculate the control positive pressure of the proportional-integral controller.

[0025] In addition, for a dual-rotor engine vibration control method according to an aspect of the present disclosure, the amplitude information includes the rotor amplitude error and the error change rate, and the fuzzy input quantities include the fuzzy rotor amplitude error and the fuzzy error change rate;

[0026] Quantify the amplitude information of the dual-rotor engine to obtain fuzzy input quantities for a fuzzy controller, including:

[0027] Based on the value range of the rotor amplitude error and the value range of the error change rate, calculate the quantization factor of the rotor amplitude error and the quantization factor of the error change rate respectively;

[0028] Based on the rotor amplitude error and the quantization factor of the rotor amplitude error, calculate the fuzzy rotor amplitude error, and based on the error change rate and the quantization factor of the error change rate, calculate the fuzzy error change rate.

[0029] In addition, for a dual-rotor engine vibration control method according to an aspect of the present disclosure, perform vibration control on the rotor of the dual-rotor engine based on the control positive pressure, including:

[0030] Apply the control positive pressure to the rotor system of the dual-rotor engine through a damper, and perform vibration control on the rotor of the dual-rotor engine according to the rotor signal feedback by the vibration test signal.

[0031] According to another aspect of the present disclosure, there is provided a dual-rotor engine vibration control device, including:

[0032] An acquisition module, configured to, when it is confirmed that the rotor speed of the dual-rotor engine is within the rotor control interval, acquire the amplitude information of the dual-rotor engine based on the comparison result between the rotor amplitude and a preset amplitude threshold;

[0033] A quantization module, configured to, when it is confirmed that the rotor speed of the dual-rotor engine is within the rotor control interval, quantify the amplitude information of the dual-rotor engine to obtain fuzzy input quantities for a fuzzy controller;

[0034] A fuzzy calculation module, configured to calculate a fuzzy output quantity of the fuzzy controller based on the fuzzy input quantities by using a membership function and fuzzy control rules;

[0035] An inverse quantization module, configured to calculate the change amount of the gain coefficient corresponding to the fuzzy output quantity based on the fuzzy output quantity;

[0036] A calculation module, based on the change amount of the gain coefficient, calculates the control positive pressure of a proportional-integral controller;

[0037] A control module, configured to perform vibration control on the rotor of the dual-rotor engine based on the control positive pressure.

[0038] According to another aspect of the present disclosure, there is provided a computer device, including a memory, a processor, and a computer program stored on the memory, wherein the processor executes the computer program to implement the method of the above-mentioned aspect.

[0039] According to another aspect of the present disclosure, there is provided a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the method of the above-mentioned aspect is implemented.

[0040] According to another aspect of the present disclosure, there is provided a computer program product, including a computer program, and when the computer program is executed by a processor, the method of the above-mentioned aspect is implemented.

[0041] As will be described in detail below, a method, device, equipment, medium, and product for controlling the vibration of a dual-rotor engine according to an embodiment of the present disclosure can obtain the fuzzy input quantity of a fuzzy controller through the amplitude information of the dual-rotor engine. After applying it to the main control type elastic support dry friction damper, the dry friction damper can change the stiffness and damping to control the rotor vibration of the dual-rotor engine, ensuring that the rotor system has optimal dynamic and static performance. The control is only performed when the rotor speed of the dual-rotor engine is within the rotor control range, reducing the data processing difficulty and improving the control efficiency.

[0042] It is to be understood that both the foregoing general description and the following detailed description are exemplary and are intended to provide further explanation of the claimed technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] By describing the embodiments of the present disclosure in more detail in conjunction with the accompanying drawings, the above and other objects, features, and advantages of the present disclosure will become more apparent. The accompanying drawings are used to provide a further understanding of the embodiments of the present disclosure, and constitute a part of the specification. Together with the embodiments of the present disclosure, they are used to explain the present disclosure and do not constitute a limitation to the present disclosure. In the accompanying drawings, the same reference numerals generally represent the same components or steps.

[0044] Figure 1 It is a flowchart illustrating the application of the method for controlling the vibration of a dual-rotor engine according to an embodiment of the present disclosure.

[0045] Figure 2 It is a schematic diagram illustrating the membership function applied according to an embodiment of the present disclosure.

[0046] Figure 3 It is another flowchart illustrating the application of the method for controlling the vibration of a dual-rotor engine according to an embodiment of the present disclosure.

[0047] Figure 4It is a control logic diagram showing the vibration control method of a dual-rotor engine according to an embodiment of the present disclosure.

[0048] Figure 5 It is a schematic structural diagram showing the control structure of a dual-rotor engine according to an embodiment of the present disclosure.

[0049] Figure 6 It is a schematic structural diagram showing the structure of a vibration control device for a dual-rotor engine according to an embodiment of the present disclosure.

[0050] Figure 7 It is a schematic structural diagram showing a computer device according to an embodiment of the present disclosure.

[0051] Figure 8 It is a schematic diagram showing a computer program product according to an embodiment of the present disclosure. Detailed implementation manners

[0052] In order to make the objectives, technical solutions and advantages of the present disclosure more apparent, exemplary embodiments according to the present disclosure will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, rather than all the embodiments of the present disclosure. It should be understood that the present disclosure is not limited by the exemplary embodiments described herein.

[0053] As a core component of an aircraft, the main configuration of an aero-engine is a dual-rotor system configuration with an intermediate bearing, including two rotors, namely a low-pressure rotor and a high-pressure rotor. However, to this day, aircraft still cannot escape the problem of vibration. To solve the vibration problem, designers have designed a new type of rotor damping and vibration reduction device using an elastic support based on dry friction energy dissipation, that is, a main control type elastic support dry friction damper. During the operation of the rotor, the dry friction damper can simultaneously change the additional stiffness and additional damping of the rotor, which can not only provide damping for vibration reduction but also adjust the critical speed, combining the advantages of high reliability of dry friction and active control.

[0054] Although the prior art has made structural improvements to the main control type elastic support dry friction damper to make it possible to be applied to aero-engines, most of its active control uses the PI control method. For aero-engines operating in complex environments with variable working conditions, the traditional PI control parameters are fixed and the regulation of environmental changes is poor. When the operating environment of the aero-engine changes severely and the working conditions change drastically, the traditional proportional-integral controller (PI controller) often cannot obtain good control effects. Therefore, the existing dampers have their own limitations when applied to aero-engines, and the control method of the main control type elastic support dry friction damper still has the above-mentioned deficiencies.

[0055] As described above, a vibration control method, apparatus, device, medium, and product for a dual-rotor engine according to an embodiment of the present disclosure have been described with reference to the accompanying drawings. By obtaining the fuzzy input quantity of the fuzzy controller based on the amplitude information of the dual-rotor engine and applying it to the main control type elastic support dry friction damper, the dry friction damper can change the stiffness and damping to control the rotor vibration of the dual-rotor engine, ensuring that the rotor system has optimal dynamic and static performance. Control is only performed when the rotor speed of the dual-rotor engine is within the rotor control range, reducing the data processing difficulty and improving the control efficiency.

[0056] The fuzzy algorithm of the present disclosure has strong anti-interference ability and can adapt to different modes or harsh working conditions of the engine, enabling the engine with vibration reduction based on the main control type elastic support dry friction damper to have strong environmental adaptability.

[0057] In addition, compared with passive control, active control does not require adding hardware, thus avoiding a series of problems such as high system cost, performance degradation of system vibration suppression caused by hardware aging, and reliability and maintenance. Therefore, the active control system and method are one of the effective designs for the rotor shaft system of aeroengines, and can also be used for complex vibration suppression of the rotor shaft systems of other large rotating machinery.

[0058] To facilitate the understanding of this embodiment, a vibration control method for a dual-rotor engine disclosed in an embodiment of the present disclosure will be introduced in detail first. The execution subject of the vibration control method for a dual-rotor engine provided in the embodiment of the present disclosure is generally a computer device with certain computing capabilities. Such a computer device includes, for example: a terminal device, a server, or other processing devices. The terminal device may be a user equipment (UE), a mobile device, a user terminal, a terminal, a cellular phone, a cordless phone, a personal digital assistant (PDA), a handheld device, a computing device, a vehicle-mounted device, a wearable device, etc. In some possible implementation manners, the vibration control method for a dual-rotor engine may be implemented by a processor invoking computer-readable instructions stored in a memory.

[0059] As Figure 1 shown, it is a flowchart of the vibration control method for a dual-rotor engine provided in an embodiment of the present disclosure. The method includes S101 - S106:

[0060] S101: When it is confirmed that the rotor speed of the dual-rotor engine is within the rotor control range, based on the comparison result between the rotor amplitude and a preset amplitude threshold, obtain the amplitude information of the dual-rotor engine.

[0061] Specifically, the signal acquisition and controller can obtain the high and low pressure rotor speeds, rotor amplitudes, and amplitude information, input the sensor data into the measurement and control computer, and determine whether the rotor speed is within the rotor control range based on the speed signal. Among them, the rotor control range is generally designed according to the critical speed margin design criterion and corrected in combination with the rotor vibration control reference value.

[0062] Among them, the amplitude information includes the rotor amplitude error and the error change rate. The preset amplitude threshold is the allowable vibration amplitude set according to the rotor characteristics and the rotor safe operation criterion. When the rotor amplitude is greater than or equal to and less than the amplitude threshold, the obtained amplitude information is different.

[0063] S102: Quantify the amplitude information of the twin-rotor engine to obtain the fuzzy input quantity for the fuzzy controller.

[0064] Specifically, the fuzzy input quantity corresponds to the amplitude information and includes the fuzzy rotor amplitude error and the fuzzy error change rate. The specific steps for quantifying the amplitude information are as follows:

[0065] 1) Based on the value range of the rotor amplitude error and the value range of the error change rate, calculate the quantization factor of the rotor amplitude error and the quantization factor of the error change rate respectively. The specific formulas are as follows:

[0066]

[0067] Among them, η e represents the quantization factor of the rotor amplitude error, a represents the critical point of the value range of the rotor amplitude error, that is, the value range of the rotor amplitude error is [-a, a], η ec represents the quantization factor of the error change rate, and b represents the critical point of the value range of the error change rate, that is, the value range of the error change rate is [-b, b].

[0068] 2) Based on the rotor amplitude error and the quantization factor of the rotor amplitude error, calculate the fuzzy rotor amplitude error, and based on the error change rate and the quantization factor of the error change rate, calculate the fuzzy error change rate. The specific formulas are as follows:

[0069]

[0070] Among them, E represents the fuzzy rotor amplitude error, e represents the rotor amplitude error, EC represents the fuzzy error change rate, and ec represents the error change rate.

[0071] S103: Based on the fuzzy input quantity, use the membership function and the fuzzy control rule to calculate and obtain the fuzzy output quantity of the fuzzy controller.

[0072] Optionally, such as Figure 2As shown, the membership function adopts a triangular membership function, which is simple and easy to understand, easy to calculate and implement, can better describe the membership degree of amplitude information to the fuzzy set, and has symmetry. In some possible implementation manners, the fuzzy universe of discourse is defined as f, and seven fuzzy subsets (membership functions) are defined: negative big (NB), negative medium (NM), negative small (NS), zero (O), positive small (PS), positive medium (PM), and positive big (PB). These seven membership functions are used in the fuzzy system to describe the magnitudes of input and output quantities.

[0073] Specifically, S103 further includes the following steps 1-3:

[0074] Step 1: Use the membership function to convert the fuzzy input quantity into a fuzzy input vector.

[0075] Specifically, convert the fuzzy rotor amplitude error E into E f and convert the fuzzy error change rate EC into EC f .

[0076] Step 2: Based on the fuzzy control rules, perform inference on the fuzzy input vector and calculate to obtain the fuzzy output vector of the fuzzy controller.

[0077] Specifically, based on the fuzzy control rules in Table 1, use the centroid method to perform inference on the fuzzy input vectors E f and EC f to obtain the fuzzy output vector.

[0078] Among them, the fuzzy output vector includes the proportional coefficient fuzzy output vector and the integral coefficient fuzzy output vector

[0079] Table 1

[0080]

[0081] Table 1 is the fuzzy control rule table of the present disclosure. Take the fuzzy rotor amplitude error E and the fuzzy error change rate EC as the inputs of the fuzzy controller, and obtain the output of the fuzzy control quantity ΔK′ P and ΔK′ I . Among them, the fuzzy control rules are concepts designed based on expert experience and summarized according to experimental laws, and are expressed in the fuzzy language form of "if... then...". For example, when the sensor data of the rotor is input into the measurement and control computer, it is judged that the fuzzy rotor amplitude error E is negative big and the fuzzy error change rate EC is also negative big at this rotational speed. It can be known that the vibration amplitude of the rotor has greatly exceeded the amplitude threshold at this time and is still increasing. Then, at this time, choose to increase the proportional coefficient and the integral coefficient gain.

[0082] Step 3: Using the membership function and fuzzy control rules, based on the fuzzy output vector, obtain the fuzzy output of the fuzzy controller.

[0083] Among them, the fuzzy output is the intermediate control value, including ΔK′ P and ΔK′ I Optionally, taking ΔK′ P as an example, the calculation process of ΔK′ P is explained in detail as follows:

[0084] Suppose in the i-th fuzzy control rule, the membership degrees of E and EC to their respective input fuzzy subsets as conditions are μ i (E) and μ i (EC) respectively. Then, the ΔK′ P inferred from this rule is obtained by multiplying the centroid U i of the fuzzy subset corresponding to the conclusion by the membership degree μ i (ΔK′ P ). The formula is as follows:

[0085] ΔK′ Pi = U i μ i (ΔK′ P ) = U i μ i (E)μ i (EC)

[0086] Among them, U i represents the value range, U i ∈{-6, -4, -2, 0, 2, 4, 6}. When defuzzifying, the output ΔK′ P should be the sum of the outputs after judging all 49 rules, that is:

[0087]

[0088] Since the sum of the membership degrees for all fuzzy subsets is always 1, it can be obtained that:

[0089]

[0090] S104: Based on the fuzzy output, calculate the change amount of the gain coefficient corresponding to the fuzzy output.

[0091] Specifically, convert the fuzzy outputs ΔK′ P and ΔK′ I with the value range of the fuzzy universe of discourse into the change amounts of the gain coefficients ΔK P and ΔK I in the basic universe of discourse.

[0092] S105: Calculate the control positive pressure of the proportional-integral controller based on the change amount of the gain coefficient.

[0093] Among them, the proportional-integral controller is the PI controller. Specifically, S105 further includes the following steps 1-3:

[0094] Step 1: Obtain the initial gain coefficient of the PI controller.

[0095] The initial gain coefficient includes the initial proportional coefficient and the initial integral coefficient.

[0096] Step 2: Obtain the gain coefficient of the PI controller based on the sum of the change amount of the gain coefficient and the initial gain coefficient.

[0097] Specifically, the gain coefficient includes the proportional coefficient K P and the integral coefficient K I , and the calculation formula is as follows:

[0098] The proportional coefficient K P = initial proportional coefficient + ΔK P ;

[0099] The integral coefficient K I = initial integral coefficient + ΔK I .

[0100] Step 3: Calculate the control positive pressure of the PI controller based on the gain coefficient. The specific step process includes:

[0101] 1) Based on the comparison result between the rotor amplitude and the amplitude threshold, obtain the error and the cumulative error of the PI controller.

[0102] Among them, the error is the error of the PI controller, and the cumulative error is the cumulative value of the PI controller error over a period of time.

[0103] 2) Calculate the product of the proportional coefficient and the error to obtain the first product value; and calculate the product of the integral coefficient and the sum of the error and the cumulative error to obtain the second product value.

[0104] 3) Calculate the control positive pressure of the PI controller based on the first product value and the second product value.

[0105] Specifically, when the rotor amplitude is greater than or equal to the amplitude threshold, the obtained amplitude information is the first rotor amplitude error and the first error change rate, as well as the first error and the first cumulative error. After the calculations of S101-S105, the first proportional coefficient K P1 and the first integral coefficient K I1 are obtained. At this time, the calculation formula of the control positive pressure (unit: N) is as follows:

[0106] Control positive pressure = K P1*First error + K I1 *(First error + first cumulative error).

[0107] Similarly, when the rotor amplitude is less than the amplitude threshold, the obtained amplitude information is the second rotor amplitude error, the second error change rate, the second error, and the second cumulative error. After the calculations of S101 - S105, the second proportional coefficient K P2 and the second integral coefficient K I2 are obtained. At this time, the calculation formula for controlling the positive pressure (unit: N) is as follows:

[0108] Controlled positive pressure = K P2 *Second error + K I2 *(Second error + second cumulative error).

[0109] S106: Perform vibration control on the rotor of the dual-rotor engine based on the controlled positive pressure.

[0110] Apply the controlled positive pressure to the rotor system of the dual-rotor engine through a damper, and perform vibration control on the rotor of the dual-rotor engine according to the rotor signal feedback by the vibration test signal.

[0111] As Figure 3 shown, it is another flowchart of the dual-rotor engine vibration control method provided by the embodiment of the present disclosure. The control logic diagram is as Figure 4 shown. Among them, the control structure of the dual-rotor engine is as Figure 5 shown. The dual-rotor system with an intermediate bearing consists of a low-pressure rotor system, a high-pressure rotor system, and a fourth intermediate support. The low-pressure rotor system includes a low-pressure fan disk, a low-pressure turbine disk, a low-pressure rotor shaft, a first elastic support, a second rigid support, and a fifth elastic support. The high-pressure rotor system includes a high-pressure compressor disk, a high-pressure turbine disk, a high-pressure rotor shaft, and a third elastic support. Among them, the signal acquisition and controller can obtain the rotor speeds and relevant amplitude information of the high and low-pressure rotors, input the sensor data into the measurement and control computer, judge whether the rotor speed is within the rotor control range according to the speed signal. If so, quantify the reference amplitude with the rotor amplitude error e and the error change rate ec, input it into the fuzzy controller, and then input the controller output signal into the damper drive system to make the damper work to control the rotor.

[0112] Figure 3 The method shown includes S201 - S205:

[0113] S201: Amplitude information quantization.

[0114] First, set the rotor control range and the amplitude threshold according to the rotor characteristics. The amplitude threshold is the vibration allowable amplitude A set according to the rotor characteristics and the rotor safe operation criterion refer. The rotor control range is generally designed according to the reference critical speed margin design criterion and corrected in combination with the reference value of rotor vibration control. The amplitude threshold is the allowable vibration amplitude set according to the rotor characteristics and the rotor safe operation criterion. When the rotor amplitude is greater than or equal to and less than the amplitude threshold, the obtained amplitude information is different.

[0115] The signal acquisition and controller can obtain the rotor speed, rotor amplitude and amplitude information of the high and low pressure rotors. The amplitude information includes the rotor amplitude error e and the error change rate ec. The sensor data is input into the measurement and control computer, and it is judged whether the rotor speed is within the rotor control range according to the speed signal. When the rotor speed is within the rotor control range, the corresponding amplitude information is obtained according to the comparison result of the rotor amplitude and the amplitude threshold, and the rotor amplitude error e and the error change rate ec are quantified to obtain the fuzzy input quantities E and EC of the fuzzy controller.

[0116] S202: Fuzzification.

[0117] Through Figure 2 The shown membership function calculates the relevant membership degrees, and the fuzzy input quantities E f and EC f are respectively transformed into fuzzy input vectors E f and EC f . Through the fuzzy control rules shown in Table 1 above, the center of gravity method is used to reason about the fuzzy input vectors E and EC to obtain the fuzzy output vectors P and I . Finally, defuzzification is performed. Using the same membership function and fuzzy control rules, the fuzzy output quantities ΔK′

[0118] Taking the fuzzy output quantity ΔK′ P as an example, the calculation process of ΔK′ P is explained in detail as follows:

[0119] Suppose in the i-th fuzzy control rule, the membership degrees of E and EC to their respective input fuzzy subsets as conditions are μ i (E) and μ i (EC) respectively. Then the ΔE′ P inferred from this rule is the center of gravity U i of the conclusion corresponding fuzzy subset multiplied by the membership degree μ i (ΔK′ P ), and the formula is as follows:

[0120] ΔK′ Pi = U i μ i (ΔK′ P ) = Ui μ i (E)μ i (EC)

[0121] Among them, U i represents the value range, U i ∈{-6, -4, -2, 0, 2, 4, 6}. When defuzzification is performed, the output ΔK′ P should be the sum of the outputs after all 49 rules are judged, that is:

[0122]

[0123] Since the sum of the membership degrees for all fuzzy subsets is always 1, it can be obtained that:

[0124]

[0125] S203: Anti-quantization.

[0126] The fuzzy output ΔK′ P with the value range of the fuzzy universe of discourse and ΔK′ I are respectively converted into the change amount ΔK P of the gain coefficient in the basic universe of discourse and ΔK I .

[0127] S204: Calculate the control positive pressure.

[0128] Step 1: Obtain the initial proportional coefficient and the initial integral coefficient of the PI controller.

[0129] Step 2: Calculate the gain coefficient of the PI controller.

[0130] Specifically, the gain coefficient includes the proportional coefficient K P and the integral coefficient K I , and the calculation formula is as follows:

[0131] The proportional coefficient K P = initial proportional coefficient + ΔK P ;

[0132] The integral coefficient K I = initial integral coefficient + ΔK I .

[0133] Step 3: Based on the gain coefficient, calculate the control positive pressure of the PI controller. The specific step process includes:

[0134] 1) Based on the comparison result between the rotor amplitude and the amplitude threshold, obtain the error and the cumulative error of the PI controller.

[0135] Among them, the error is the error of the PI controller, and the cumulative error is the cumulative value of the PI controller error over a period of time.

[0136] Specifically, when the rotor amplitude is greater than or equal to the amplitude threshold, the first error and the first cumulative error are obtained; when the rotor amplitude is less than the amplitude threshold, the second error and the second cumulative error are obtained.

[0137] 2) Calculate the product of the proportionality coefficient and the error to obtain a first product value; and calculate the product of the integral coefficient and the sum of the error and the cumulative error to obtain a second product value.

[0138] 3) Calculate the control positive pressure of the PI controller based on the first product value and the second product value.

[0139] Specifically, when the rotor amplitude is greater than or equal to the amplitude threshold, the obtained amplitude information is the first rotor amplitude error and the first error change rate. After the calculations of S201 - S204, the first proportionality coefficient K P1 and the first integral coefficient K I1 are obtained. At this time, the calculation formula for the control positive pressure (unit: N) is as follows:

[0140] Control positive pressure = K P1 * First error + K I1 * (First error + First cumulative error).

[0141] Similarly, when the rotor amplitude is less than the amplitude threshold, the obtained amplitude information is the second rotor amplitude error and the second error change rate. After the calculations of S201 - S204, the second proportionality coefficient K P2 and the second integral coefficient K I2 are obtained. At this time, the calculation formula for the control positive pressure (unit: N) is as follows:

[0142] Control positive pressure = K P2 * Second error + K I2 * (Second error + Second cumulative error).

[0143] S205: System application and feedback.

[0144] Apply the control positive pressure to the rotor of the dual - rotor engine through the elastic support dry - friction damper, and perform vibration control on the rotor according to the rotor signal feedback from the vibration test signal. Then obtain the amplitude information feedback from the controlled system.

[0145] According to another aspect of the embodiments of the present disclosure, a dual - rotor engine vibration control device is provided. As Figure 6 shown, the device includes:

[0146] An acquisition module 101, configured to, when it is confirmed that the rotor speed of a dual-rotor engine is within a rotor control range, acquire amplitude information of the dual-rotor engine based on a comparison result between a rotor amplitude and a preset amplitude threshold;

[0147] A quantization module 102, configured to, when it is confirmed that the rotor speed of the dual-rotor engine is within the rotor control range, quantize the amplitude information of the dual-rotor engine to obtain a fuzzy input quantity for a fuzzy controller;

[0148] A fuzzy calculation module 103, configured to calculate a fuzzy output quantity of the fuzzy controller based on the fuzzy input quantity by using a membership function and fuzzy control rules;

[0149] An inverse quantization module 104, configured to calculate a change amount of a gain coefficient corresponding to the fuzzy output quantity based on the fuzzy output quantity;

[0150] A calculation module 105, configured to calculate a control positive pressure of a proportional-integral controller based on the change amount of the gain coefficient;

[0151] A control module 106, configured to perform vibration control on a rotor of the dual-rotor engine based on the control positive pressure.

[0152] In one or more embodiments, the fuzzy calculation module 103 is configured to:

[0153] Convert the fuzzy input quantity into a fuzzy input vector by using a membership function;

[0154] Infer the fuzzy input vector based on fuzzy control rules to calculate a fuzzy output vector of the fuzzy controller;

[0155] Obtain a fuzzy output quantity of the fuzzy controller based on the fuzzy output vector by using a membership function and fuzzy control rules.

[0156] In one or more embodiments, the calculation module 105 is configured to:

[0157] Obtain an initial gain coefficient of the proportional-integral controller;

[0158] Obtain a gain coefficient of the proportional-integral controller based on a sum of the change amount of the gain coefficient and the initial gain coefficient;

[0159] Calculate a control positive pressure of the proportional-integral controller based on the gain coefficient.

[0160] In one or more embodiments, the calculation module 105 is further configured to:

[0161] Obtain an error and an accumulated error of the proportional-integral controller based on a comparison result between the rotor amplitude and the amplitude threshold;

[0162] Calculate the product of the proportional coefficient and the error to obtain a first product value; and calculate the product of the integral coefficient and the sum of the error and the accumulated error to obtain a second product value;

[0163] Based on the first product value and the second product value, calculate the control positive pressure of the proportional-integral controller.

[0164] In one or more embodiments, the quantization module 102 is configured to:

[0165] Based on the value range of the rotor amplitude error and the value range of the error change rate, calculate the quantization factor of the rotor amplitude error and the quantization factor of the error change rate respectively;

[0166] Based on the rotor amplitude error and the quantization factor of the rotor amplitude error, calculate the fuzzy rotor amplitude error, and based on the error change rate and the quantization factor of the error change rate, calculate the fuzzy error change rate.

[0167] In one or more embodiments, the control module 106 is configured to:

[0168] Apply the control positive pressure to the rotor system of the dual-rotor engine through a damper, and perform vibration control on the rotor of the dual-rotor engine according to the rotor signal fed back by the vibration test signal.

[0169] In one or more embodiments, the dual-rotor engine vibration control device is further configured to:

[0170] Extract the rules in the rule knowledge base of the two-dimensional fuzzy controller and send them to the background server; at the same time, send the usage records of the corresponding rules and the operation data of the rotor tester after use to the background server;

[0171] Receive the comprehensive analysis result of the rules, usage records and operation data from the background server, and adjust the rules when the analysis result requires rule adjustment.

[0172] The dual-rotor engine vibration control device provided by the embodiments of the present disclosure and the dual-rotor engine vibration control method provided by the embodiments of the present disclosure are based on the same inventive concept and have the same beneficial effects as the methods adopted, run or implemented by them.

[0173] The embodiments of the present disclosure also provide a computer device to execute the above-mentioned dual-rotor engine vibration control method. Please refer to Figure 7 It shows a schematic diagram of a computer device provided by some embodiments of the present disclosure. As Figure 7As shown in the figure, the computer device 8 includes: a processor 800, a memory 801, a bus 802, and a communication interface 803. The processor 800, the communication interface 803, and the memory 801 are connected through the bus 802. A computer program that can run on the processor 800 is stored in the memory 801. When the processor 800 runs the computer program, it executes the dual-rotor engine vibration control method provided in any of the foregoing embodiments of the present disclosure.

[0174] Among them, the memory 801 may include a high-speed random access memory (RAM: Random Access Memory), and may also include a non-volatile memory, such as at least one disk memory. Through at least one communication interface 803 (which can be wired or wireless), a communication connection is realized between this device network element and at least one other network element, and the Internet, a wide area network, a local area network, a metropolitan area network, etc. can be used.

[0175] The bus 802 can be an ISA bus, a PCI bus, an EISA bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. Among them, the memory 801 is used to store a program. After receiving an execution instruction, the processor 800 executes the program. The dual-rotor engine vibration control method disclosed in any of the foregoing embodiments of the present disclosure can be applied to the processor 800 or implemented by the processor 800.

[0176] The processor 800 may be an integrated circuit chip with the ability to process signals. In the implementation process, the steps of the above method can be completed by the integrated logic circuit of the hardware in the processor 800 or the instructions in the form of software. The above-mentioned processor 800 may be a general-purpose processor, including a central processing unit (CPU for short), a network processor (NP for short), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPTA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. It can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present disclosure. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method disclosed in combination with the embodiments of the present disclosure can be directly embodied as being executed and completed by the hardware decoding processor, or executed and completed by a combination of the hardware and software modules in the decoding processor. The software module may be located in a mature storage medium in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. This storage medium is located in the memory 801, and the processor 800 reads the information in the memory 801 and combines its hardware to complete the steps of the above method.

[0177] The computer device provided by the embodiments of the present disclosure and the dual-rotor engine vibration control method provided by the embodiments of the present disclosure are based on the same inventive concept and have the same beneficial effects as the methods adopted, run, or implemented by them.

[0178] The embodiments of the present disclosure also provide a computer-readable storage medium corresponding to the dual-rotor engine vibration control method provided in the foregoing embodiments. The computer-readable storage medium is an optical disc, on which a computer program (i.e., a computer program product) is stored. When the computer program is run by a processor, it will execute the dual-rotor engine vibration control method provided in any of the foregoing embodiments.

[0179] It should be noted that examples of the computer-readable storage medium may also include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory, or other optical and magnetic storage media, which will not be elaborated here one by one.

[0180] The computer-readable storage medium provided by the above embodiments of the present disclosure and the dual-rotor engine vibration control method provided by the embodiments of the present disclosure are based on the same inventive concept and have the same beneficial effects as the methods adopted, run, or implemented by the application programs stored therein.

[0181] The embodiments of the present disclosure also provide a computer program product. Please refer to Figure 8 , the computer program product 600 carries program code, that is, computer program 601. The instructions included in the computer program 601 can be used to execute the steps of the dual-rotor engine vibration control method described in the above method embodiments. Specifically, refer to the above method embodiments, which will not be elaborated here.

[0182] Among them, the above computer program product can be specifically implemented in the form of hardware, software, or a combination thereof. In an alternative embodiment, the computer program product is specifically embodied as a computer storage medium. In another alternative embodiment, the computer program product is specifically embodied as a software product, such as a Software Development Kit (SDK), etc.

[0183] The basic principles of the present disclosure have been described above in conjunction with specific embodiments. However, it should be noted that the advantages, benefits, effects, etc. mentioned in the present disclosure are only examples and not limitations. It cannot be considered that these advantages, benefits, effects, etc. are essential for each embodiment of the present disclosure. In addition, the above specific details disclosed are only for the purposes of illustration and easy understanding, rather than limitations. The above details do not limit the present disclosure to necessarily adopt the above specific details for implementation.

[0184] The block diagrams of the devices, apparatuses, equipment, and systems involved in the present disclosure are only illustrative examples and do not intend to require or imply that they must be connected, arranged, and configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, equipment, and systems can be connected, arranged, and configured in any manner. Words such as "including", "comprising", "having", etc. are open-ended words, meaning "including but not limited to", and can be used interchangeably with each other. The words "or" and "and" used here refer to the word "and / or" and can be used interchangeably with each other, unless the context clearly indicates otherwise. The word "such as" used here refers to the phrase "such as but not limited to" and can be used interchangeably with each other.

[0185] In addition, as used herein, the "or" used in the enumeration of items starting with "at least one" indicates a separate enumeration. For example, the enumeration of "at least one of A, B, or C" means A or B or C, or AB or AC or BC, or ABC (that is, A and B and C). In addition, the term "exemplary" does not mean that the described examples are preferred or better than other examples.

[0186] It should also be noted that in the systems and methods of the present disclosure, each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent solutions of the present disclosure.

[0187] Various changes, substitutions, and alterations to the technologies described herein can be made without departing from the teachings defined by the appended claims. In addition, the scope of the claims of the present disclosure is not limited to the specific aspects of the processes, machines, manufactures, compositions of events, means, methods, and acts described above. Current or later-developed processes, machines, manufactures, compositions of events, means, methods, or acts that perform substantially the same function or achieve substantially the same result as the corresponding aspects described herein can be utilized. Accordingly, the appended claims include such processes, machines, manufactures, compositions of events, means, methods, or acts within their scope.

[0188] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of the present disclosure. Therefore, the present disclosure is not intended to be limited to the aspects shown herein, but rather to the broadest scope consistent with the principles and novel features disclosed herein.

[0189] The above description has been presented for purposes of illustration and description. Additionally, this description is not intended to limit the embodiments of the present disclosure to the forms disclosed herein. Although multiple example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and subcombinations thereof.

Claims

1. A twin-rotor engine vibration control method, characterized in that: include: When confirming that the rotor speed of the twin-rotor engine is within the rotor control range, based on the comparison result between the rotor amplitude and the preset amplitude threshold, the amplitude information of the twin-rotor engine is obtained; quantizing the amplitude information of the dual-rotor engine to obtain a fuzzy input quantity for a fuzzy controller; Based on the fuzzy input quantity, the fuzzy output quantity of the fuzzy controller is calculated by using the membership function and the fuzzy control rule; Based on the fuzzy output, calculating the gain coefficient change corresponding to the fuzzy output; Calculating the control positive pressure of the proportional-integral controller based on the gain coefficient change; Based on the controlled positive pressure, vibration control is performed on the rotor of the twin-rotor engine.

2. The twin-rotor engine vibration control method according to claim 1, characterized in that: Based on the fuzzy input, the fuzzy output of the fuzzy controller is calculated using the membership function and the fuzzy control rule, including: The fuzzy input quantity is converted into a fuzzy input vector by using a membership function; Based on the fuzzy control rules, the fuzzy input vector is inferred to obtain the fuzzy output vector of the fuzzy controller by calculation; The fuzzy output quantity of the fuzzy controller is obtained based on the fuzzy output vector by utilizing the membership function and the fuzzy control rule.

3. The twin-rotor engine vibration control method according to claim 1, characterized in that: Based on the gain coefficient change, the control positive pressure of the proportional-integral controller is calculated, including: Get the initial gain coefficient of the proportional-integral controller; Obtaining a gain coefficient of a proportional-integral controller based on the sum of the gain coefficient change and the initial gain coefficient; Based on the gain coefficient, the control positive pressure of the proportional-integral controller is calculated.

4. The twin-rotor engine vibration control method according to claim 3, characterized in that: The gain coefficient includes a proportional coefficient and an integral coefficient; Based on the gain coefficient, the control positive pressure of the proportional-integral controller is calculated, including: Based on the comparison result between the rotor amplitude and the amplitude threshold, obtaining an error and a cumulative error of a proportional-integral controller; Calculating the product of the proportional coefficient and the error to obtain a first product value; and calculating the product of the integral coefficient and the sum of the error and the accumulated error to obtain a second product value; Based on the first product value and the second product value, a control positive pressure of a proportional-integral controller is calculated.

5. The twin-rotor engine vibration control method according to claim 1, characterized in that: The amplitude information includes the rotor amplitude error and the error change rate, and the fuzzy input includes the fuzzy rotor amplitude error and the fuzzy error change rate; The amplitude information of the dual-rotor engine is quantified to obtain a fuzzy input quantity for a fuzzy controller, including: Based on the value range of the rotor amplitude error and the value range of the error change rate, respectively calculating a quantization factor of the rotor amplitude error and a quantization factor of the error change rate; A fuzzy rotor amplitude error is calculated based on the rotor amplitude error and a quantization factor of the rotor amplitude error, and a fuzzy error change rate is calculated based on the error change rate and the quantization factor of the error change rate.

6. The twin-rotor engine vibration control method according to claim 1, characterized in that: The vibration control of the rotor of the twin-rotor engine is performed based on the positive pressure control, comprising: The controlled positive pressure is applied to the rotor system of the twin-rotor engine through the damper, and the vibration of the rotor of the twin-rotor engine is controlled according to the rotor signal fed back by the vibration test signal.

7. A twin-rotor engine vibration control device, characterized in that: include: an acquisition module, configured to acquire amplitude information of the twin-rotor engine based on a comparison result between the rotor amplitude and a preset amplitude threshold value when confirming that the rotor speed of the twin-rotor engine is within the rotor control range; A quantization module, for quantizing the amplitude information of the dual-rotor engine to obtain a fuzzy input quantity for a fuzzy controller when confirming that the rotor speed of the dual-rotor engine is within the rotor control interval; A fuzzy calculation module is used to calculate the fuzzy output of the fuzzy controller based on the fuzzy input quantity using a membership function and a fuzzy control rule; A dequantization module, used for calculating a gain coefficient change amount corresponding to the fuzzy output amount based on the fuzzy output amount; A calculation module, which calculates the control positive pressure of the proportional-integral controller based on the gain coefficient change; A control module is used to perform vibration control on a rotor of a twin-rotor engine based on the control positive pressure.

8. A computer embedded device, comprising a memory, a processor and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

Images