Speed ring parameter adjusting method and device and storage medium

Abstract

The invention discloses a speed loop parameter adjusting method and device and a storage medium. The method comprises the steps that a plurality of first parameter values are set for a proportion parameter, and a plurality of second parameter values are set for the proportion parameter; when the fixed integral parameter and the proportional parameter are sequentially adjusted to all the first parameter values, the motor is controlled to drag the lift car, so that the optimal first parameter value is found according to the vibration signal of the lift car in the vertical direction; when the optimal first parameter value is applied to the fixed proportion parameter and the integral parameter is sequentially adjusted to all the second parameter values, the motor is controlled to drag the lift car, so that the optimal second parameter value is found according to the vibration signal of the lift car in the vertical direction; the optimal second parameter value is applied to the integration parameter. According to the embodiment, a self-learning frame of the speed ring parameters is provided for the motor of the elevator, the proportion parameters and the integral parameters are optimized in a staged mode from vibration of the elevator car in the vertical direction, jolt of the elevator car during elevator running is reduced, and the elevator taking experience of a user is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of elevators, and in particular to a method, a device and a storage medium for adjusting speed loop parameters. Background Art

[0002] During the development and design phase of the elevator, the speed loop parameters of the motor are designed according to the overall specifications of the elevator, and during the testing phase of the elevator, the speed loop parameters of the motor are optimized.

[0003] However, there are certain differences between the actual load and installation of the elevator and the load and installation during the test, which makes the accuracy of the designed or tuned speed loop parameters low, resulting in more obvious bumps in the operation of some elevators, affecting the user's experience of riding the elevator. Summary of the invention

[0004] In view of this, the present invention provides a method, a device and a storage medium for adjusting speed loop parameters, so as to improve the accuracy of the speed loop parameters of an elevator motor.

[0005] A first aspect of the present invention provides a method for adjusting speed loop parameters, which is applied to an elevator, wherein the elevator is equipped with a motor for dragging a car, and the speed loop parameters of the motor include a proportional parameter and an integral parameter, and the method includes:

[0006] Setting a plurality of first parameter values ​​for the proportion parameter and setting a plurality of second parameter values ​​for the proportion parameter;

[0007] When the integral parameter is fixed and the proportional parameter is adjusted to the first parameter values ​​in sequence, the motor is controlled to drag the car respectively, so as to find the optimal first parameter value according to the vibration signal of the car in the vertical direction;

[0008] When the proportional parameter is fixed and the optimal first parameter value is applied, and the integral parameter is adjusted to each second parameter value in sequence, the motor is controlled to drag the car respectively, so as to find the optimal second parameter value according to the vibration signal of the car in the vertical direction;

[0009] An optimal second parameter value is applied to the integration parameter.

[0010] A second aspect of the present invention provides a speed loop parameter adjustment device, which is applied to an elevator, wherein the elevator is equipped with a motor for dragging a car, and the speed loop parameters of the motor include a proportional parameter and an integral parameter, and the device includes:

[0011] A parameter value setting module, used for setting a plurality of first parameter values ​​for the proportion parameter and a plurality of second parameter values ​​for the proportion parameter;

[0012] A proportional parameter optimization module, for controlling the motor to drag the car respectively when the integral parameter is fixed and the proportional parameter is adjusted to each of the first parameter values ​​in sequence, so as to find the optimal first parameter value according to the vibration signal of the car in the vertical direction;

[0013] an integral parameter optimization module, for controlling the motor to drag the car respectively when the proportional parameter is fixed and the optimal first parameter value is applied and the integral parameter is adjusted to each second parameter value in sequence, so as to find the optimal second parameter value according to the vibration signal of the car in the vertical direction;

[0014] An integral parameter application module is used to apply the optimal second parameter value to the integral parameter.

[0015] A third aspect of the present invention provides an electronic device, the electronic device comprising:

[0016] at least one processor; and

[0017] a memory communicatively connected to the at least one processor; wherein,

[0018] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for adjusting the speed loop parameters as described in the first aspect above.

[0019] A fourth aspect of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for adjusting the speed loop parameters as described in the first aspect above is implemented.

[0020] A fifth aspect of the present invention provides a computer program product, which includes a computer program. When the computer program is executed by a processor, it implements the method for adjusting the speed loop parameters as described in the first aspect above.

[0021] In this embodiment, a plurality of first parameter values ​​are set for the proportional parameter, and a plurality of second parameter values ​​are set for the proportional parameter; when the fixed integral parameter and the proportional parameter are adjusted to the first parameter values ​​in sequence, the motor is controlled to drag the car respectively, so as to find the optimal first parameter value according to the vibration signal of the car in the vertical direction; when the fixed proportional parameter applies the optimal first parameter value, and the integral parameter is adjusted to the second parameter values ​​in sequence, the motor is controlled to drag the car respectively, so as to find the optimal second parameter value according to the vibration signal of the car in the vertical direction; the optimal second parameter value is applied to the integral parameter. This embodiment provides a self-learning framework for the speed loop parameters of the elevator motor, optimizes the proportional parameter and the integral parameter in stages from the vibration of the car in the vertical direction, reduces the bumps of the car when the elevator is running, and ensures the user's experience of riding the elevator, and the automated process can reduce the requirements for engineering personnel, reduce the threshold for adjusting the speed loop parameters of the elevator motor, and shorten the debugging time, thereby effectively improving the efficiency of adjusting the speed loop parameters of the elevator motor.

[0022] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0024] Figure 1 This is a flow chart of a method for adjusting speed loop parameters provided in Embodiment 1 of the present invention.

[0025] Figure 2 It is a structural schematic diagram of a speed loop parameter adjustment device provided in Embodiment 2 of the present invention.

[0026] Figure 3 It is a structural schematic diagram of an electronic device provided in Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0027] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme 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 part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0028] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present invention described herein can cover sequential implementations other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0029] Embodiment 1

[0030] See also Figure 1 , shows a flow chart of a method for adjusting speed loop parameters provided by the first embodiment of the present invention, the method can be executed by a speed loop parameter adjustment device, the speed loop parameter adjustment device can be implemented in the form of hardware and / or software, the speed loop parameter adjustment device can be configured in an electronic device, especially an elevator controller. Figure 1 As shown, the method includes:

[0031] Step 101: setting a plurality of first parameter values ​​for a proportional parameter and a plurality of second parameter values ​​for an integral parameter.

[0032] In different types of buildings, especially high-rise buildings, there are different transportation needs for people, pets, goods, etc. Therefore, different types of elevators can be deployed in the building according to different transportation needs, such as passenger elevators, freight elevators, sightseeing elevators, etc. The method in this embodiment can be applied to various types of elevators.

[0033] This embodiment can be applied to an elevator. An elevator is a comprehensive system. Different types of elevators have different structures.

[0034] In one example, a certain type of elevator is configured with: a controller (also known as an elevator control system), external call devices distributed on each floor, a car, a motor for towing the car (also known as a traction machine), a control cabinet, a speed limiter, a door opener, a car frame, a car door, a counterweight guide rail, a car guide rail, a guide rail support, an accompanying cable, a counterweight device, a compensation chain (cable), a floor door, a guide device for the compensation chain (cable), a buffer, and the like.

[0035] In some types of elevators, the traction machine, control cabinet, speed limiter, traveling cable, etc. can be omitted.

[0036] These devices can be divided into different sets according to their functions to form various subsystems that support the operation of the elevator. The controller is connected to multiple systems of the elevator through serial ports or serial clock lines (SCL). The controller monitors each system and controls the operation of each subsystem, allowing the car to move in the shaft and reach each floor of the building.

[0037] In one example, the controller includes a door system, a frequency conversion system, a calling system and a traction system, wherein the door system is used to control the door of the elevator, the car is equipped with a car door, and the elevator lobby on each floor is provided with a hall door, and the elevator door includes a car door and a hall door of the elevator lobby on each floor, the type of the car door is the same as the type of the hall door, and they are switched at the same time (open or closed), the frequency conversion system is used to control the frequency converter, the calling system is used to control the logic of the internal call (calling the elevator in the car) and the external call (calling the elevator in the elevator lobby), and the traction system is used to control the movement of the car in the vertical direction (vertically upward or vertically downward) in the shaft.

[0038] The manager or owner of the elevator can choose whether to install an edge computing node on the elevator based on factors such as the load status of the elevator. If you choose not to install an edge computing node, the controller maintains the original control logic and does not affect the normal operation of the elevator. If you choose to install an edge computing node, you can select a suitable computing device as the edge computing node of the elevator according to your needs. The edge computing node is combined with the original controller into a new controller and redefines the control logic of the elevator.

[0039] Generally speaking, edge computing nodes are computing devices with strong computing capabilities, such as computers, servers or embedded devices. In addition, according to different intelligent services, edge computing nodes can be equipped with graphics processing units (GPUs) or embedded neural network processors (NPUs).

[0040] Edge computing nodes refer to a new business platform built at the edge of the network near the elevator, providing storage, computing, network and other resources, and sinking some key business applications to the edge of the access network to reduce the width and delay losses caused by network transmission and multi-level forwarding. The edge computing node is located between the user and the cloud (server), and is closer to the user (data source) than the traditional cloud. It has the characteristics of miniaturization, distribution and closer to the user. Massive data (such as audio data) no longer needs to be uploaded to the cloud for processing, and data processing is realized at the edge of the network, reducing request response time and network bandwidth while ensuring data security and privacy.

[0041] In addition, edge computing nodes can implement algorithm functions and model reasoning, communicate with existing controllers, and provide artificial intelligence (AI) and complex computing capabilities for existing controllers. Edge computing can also communicate with the cloud to implement algorithm functions and model updates, and transfer existing controller function calls and other functions.

[0042] In practical applications, sensor feedback can be added to the motor to form a closed-loop system. In the closed-loop system, algorithms such as PID (Proportional Integral Derivative) are used to control the speed loop. Then, the speed loop parameters of the motor include the proportional parameter P and the integral parameter I.

[0043] In this embodiment, during initial installation of the elevator, elevator failure, elevator maintenance, etc., the operation and maintenance personnel can start the speed loop self-learning mode for the elevator and automatically learn the optimal speed loop parameters based on the vibration of the car.

[0044] Generally, when the elevator is in the speed loop self-learning mode, it does not provide passenger services to the outside, that is, there are no ordinary users in the car.

[0045] In the speed loop self-learning mode, a plurality of candidate first parameter values ​​P0 are set for the proportional parameter P, and a plurality of candidate second parameter values ​​I0 are set for the integral parameter I.

[0046] Furthermore, the first interval of the proportional parameter P configuration can be queried, wherein the first interval is the range of reasonable historical fluctuations of the proportional parameter P. Searching for the optimal first parameter value P0 in the first interval can effectively converge the number of first parameter values ​​P0 and reduce the amount of optimization calculations.

[0047] In the first interval, a plurality of first parameter values ​​P0 are set for the proportional parameter P in an evenly distributed manner; wherein the evenly distributed manner refers to a preset first step length ΔP being set between two adjacent first parameter values ​​P0.

[0048] In addition, the second interval configured for the integral parameter I can be queried, wherein the second interval is the range of reasonable historical fluctuations of the integral parameter I. Searching for the optimal second parameter value I0 in the second interval can effectively converge the number of second parameter values ​​I0 and reduce the amount of optimization calculations.

[0049] In the second interval, a plurality of second parameter values ​​I0 are set for the integral parameter I in an evenly divided manner; wherein the evenly divided manner means that two adjacent second parameter values ​​I0 are spaced apart by a preset second step length ΔI.

[0050] Step 102: When the fixed integral parameter is applied to a second parameter value and the proportional parameter is adjusted to each first parameter value in sequence, the motor is controlled to drag the car respectively to find the optimal first parameter value according to the vibration signal of the car in the vertical direction.

[0051] In practical applications, the proportional parameter P and the integral parameter I are adjusted in two stages. In the first stage, the integral parameter I is fixed and unchanged, and the proportional parameter P is adjusted. In the second stage, the proportional parameter P is fixed and unchanged, and the integral parameter I is adjusted.

[0052] In the first stage, the fixed integral parameter I remains unchanged, which means that the integral parameter I is applied with a default second parameter value I0 (such as the minimum second parameter value I0, the maximum second parameter value I0, the second parameter value I0 at the middle value, etc.) and remains unchanged, and the proportional parameter P is adjusted to each first parameter value P0 in a certain order (such as from small to large, from large to small, etc.).

[0053] Each time the proportional parameter P adjusts one of the first parameter values ​​P0, the motor is controlled to run and drag the car according to the current proportional parameter P and integral parameter I. In this process, the optimal first parameter value P0 is found for the proportional parameter P based on the vibration signal of the car in the vertical direction.

[0054] To facilitate comparison of the effects of various first parameter values ​​P0, the motor usually drags the car between two designated floors in a fixed motion mode (eg, direction, speed, etc.).

[0055] In one embodiment of the present invention, step 102 may include the following steps:

[0056] Step 1021: When a second parameter value is applied to a fixed integral parameter and a first parameter value is adjusted by a proportional parameter, the motor is controlled to drag the car, and a first acceleration signal in a vertical direction is collected from the car.

[0057] When a second parameter value is applied with a fixed integral parameter and a first parameter value is adjusted with a proportional parameter, the motor can be controlled to drag the car. During this process, instruments such as the three-axis acceleration sensor in the car can be called to collect the acceleration in the vertical direction (i.e., the Z axis) of the car to obtain a first acceleration signal.

[0058] Step 1022: Filter the first acceleration signal to obtain a first vibration signal of the car in the vertical direction.

[0059] In this embodiment, the first acceleration signal is mixed with interference noise, and the user is more sensitive to the vibration of the car in the vertical direction. Therefore, for the first acceleration signal corresponding to each first parameter value, the first acceleration signal can be input into a preset filter and filtered to suppress the interference of noise and obtain the first vibration signal of the car in the vertical direction.

[0060] In a specific implementation, an algorithm such as FFT (Fast Fourier Transformation) may be used to convert the first acceleration signal from the time domain to the frequency domain to obtain the first candidate signal.

[0061] Users have different sensitivities to vibrations in different frequency bands. The vibration frequency band to which users react most strongly is 1Hz-80Hz, while the vibration frequency band to which standing users react most strongly is 4Hz-8Hz. Therefore, the first candidate signal may be subjected to band-limited filtering, acceleration and velocity conversion filtering, and high-order filtering to suppress high-frequency signals and obtain a low-frequency second candidate signal.

[0062] Furthermore, the band-limited filtering process can be divided into high-pass filtering process and low-pass filtering process.

[0063] The first candidate signal is input into a preset high-pass filter, and high-pass filtering is performed on the first candidate signal to obtain a first reference signal.

[0064] Taking a second-order Butterworth filter as an example of a high-pass filter, the high-pass filtering process is as follows:

[0065]

[0066] Among them, s is the first candidate signal, H h (s) is the first reference signal, w1 is the angular frequency, the frequency f1 corresponding to w1 (w1 = 2πf1) is a constant, such as 0.4 Hz, and Q1 is the resonant quality factor, such as

[0067] The first candidate signal is input into a low-pass filter and low-pass filtered to obtain a second reference signal.

[0068] Taking a second-order Butterworth filter as an example of a low-pass filter, the low-pass filtering process is as follows:

[0069]

[0070] Among them, s is the first candidate signal, H l(s) is the second reference signal, w2 is the angular frequency, the frequency f2 corresponding to w2 (w2 = 2πf2) is a constant, such as 100 Hz, and Q2 is the resonant quality factor, such as

[0071] The first candidate signal is input into the av conversion filter, and the first candidate signal is subjected to speed-to-speed conversion filtering to obtain a third reference signal. At this time, the third reference signal is proportional to the acceleration at a lower frequency and proportional to the speed at a higher frequency.

[0072] Exemplarily, the process of filtering the transformation between speeds is as follows:

[0073]

[0074] Among them, s is the first candidate signal, H t (s) is the third reference signal, w3 is the angular frequency, the frequency f3 corresponding to w3 (w3 = 2πf3) is a constant, such as 12.5 Hz, w4 is the angular frequency, the frequency f4 corresponding to w4 (w4 = 2πf4) is a constant, such as 12.5 Hz, Q4 is the resonance quality factor, such as K is the gain, such as 12.5.

[0075] The first candidate signal is input into a high-order filter and high-order filtering is performed on the first candidate signal to obtain a fourth reference signal, wherein the order of the high-order filter is positively correlated with the magnitude of the first acceleration signal.

[0076] Exemplarily, the process of high-order filtering is as follows:

[0077]

[0078] Among them, s is the first candidate signal, H s (s) is the fourth reference signal, w5 is the angular frequency, the frequency f5 corresponding to w5 (w5=2πf5) is a constant, such as 2.37Hz, w6 is the angular frequency, the frequency f6 corresponding to w6 (w6=2πf6) is a constant, such as 3.35Hz, Q5 is the resonance quality factor, such as 0.91, and Q6 is the resonance quality factor, such as 0.91.

[0079] The product of the first reference signal, the second reference signal, the third reference signal and the fourth reference signal is calculated to obtain a second candidate signal.

[0080] Then, the second candidate signal can be expressed as:

[0081] H(s)=H h (s)*H l (s)*H t (s)*H s(s)

[0082] Among them, H(s) is the second candidate signal, H h (s) is the first reference signal, H l (s) is the second reference signal, H t (s) is the third reference signal, H s (s) is the fourth reference signal.

[0083] At this time, an algorithm such as IFFT (Inverse Fast Fourier Transformation) can be used to convert the second candidate signal from the time domain to the frequency domain to obtain a first vibration signal of the car in the vertical direction.

[0084] Step 1023: extract the first vibration feature from each first vibration signal.

[0085] For the first vibration signals corresponding to the first parameter values, one or more features may be extracted from the first vibration signals as the first vibration features.

[0086] Exemplarily, a plurality of first peak-to-peak signals may be extracted from the first vibration signal; and a first quantile signal may be located in the plurality of first peak-to-peak signals as the first vibration feature.

[0087] The number of first peak-to-peak signals that are less than or equal to the first quantile signal and the number of first peak-to-peak signals that are greater than the first quantile signal meet a specified first ratio.

[0088] For example, if the first quantile signal is an A95 signal, it means that 95% of the first peak-to-peak signals are less than or equal to the A95 signal, and 5% of the first peak-to-peak signals are greater than the A95 signal.

[0089] Step 1024: compare the first vibration characteristics corresponding to the first parameter values ​​to find the optimal first parameter value.

[0090] In this embodiment, the first vibration characteristics corresponding to the first parameter values ​​are compared, and the first parameter value with the best first vibration characteristic is found among all the first parameters.

[0091] Exemplarily, when the first vibration characteristic is a first quantile signal, the first quantile signals of the first parameter values ​​are compared to screen out the first parameter value with the smallest first quantile signal as the optimal first parameter value. At this time, the overall vibration of the car in the vertical direction can be effectively reduced.

[0092] Of course, the above-mentioned first vibration characteristics and the method for finding the optimal first parameter value are only used as examples. When implementing this embodiment, other first vibration characteristics and the method for finding the optimal first parameter value can be set according to actual conditions. For example, when both the first peak-to-peak signal and the first quantile signal are used as the first vibration characteristics, the weighted sum of the average value of the first peak-to-peak signal and the first quantile signal can be used to obtain the first index value, and the first parameter value with the smallest first index value can be screened out as the optimal first parameter value, etc. This embodiment does not limit this. In addition, in addition to the above-mentioned first vibration characteristics and the method for finding the optimal first parameter value, those skilled in the art can also adopt other first vibration characteristics and the method for finding the optimal first parameter value according to actual needs, and this embodiment does not limit this.

[0093] Step 103, when the fixed proportion parameter applies the optimal first parameter value and the integral parameter is adjusted to each second parameter value in sequence, the motor is controlled to drag the car respectively to find the optimal second parameter value according to the vibration signal of the car in the vertical direction.

[0094] The proportional parameter in the motor speed loop parameter is applied with the optimal first parameter value, the first stage is completed, and the second stage is entered.

[0095] In the second stage, the fixed proportional parameter P remains unchanged, which means that the proportional parameter P is applied to the optimal first parameter value P0 and remains unchanged, and the integral parameter I is adjusted to each second parameter value I0 in a certain order (such as from small to large, from large to small, etc.).

[0096] Each time the integral parameter I adjusts one of the second parameter values ​​I0, the motor is controlled to run and drag the car according to the current proportional parameter P and the integral parameter I. In this process, the optimal second parameter value I0 is found for the integral parameter I based on the vibration signal of the car in the vertical direction.

[0097] To facilitate comparison of the effects of various second parameter values ​​I0, the motor usually drags the car between two designated floors in a fixed motion mode (eg, direction, speed, etc.).

[0098] In one embodiment of the present invention, step 103 may include the following steps:

[0099] Step 1031: When the fixed proportional parameter applies the optimal first parameter value and the integral parameter adjusts a second parameter value, the motor is controlled to drag the car, and a second acceleration signal in the vertical direction of the car is collected.

[0100] When the optimal first parameter value is applied with a fixed proportional parameter and a second parameter value is adjusted with an integral parameter, the motor is controlled to drag the car. During this process, instruments such as the three-axis acceleration sensor in the car can be called to collect the acceleration in the vertical direction (i.e., the Z axis) of the car to obtain a second acceleration signal.

[0101] Step 1032: Filter the second acceleration signal to obtain a second vibration signal of the car in the vertical direction.

[0102] In this embodiment, the second acceleration signal is mixed with interference noise, and the user is more sensitive to the vibration of the car in the vertical direction. Therefore, for the second acceleration signal corresponding to each second parameter value, the second acceleration signal can be input into a preset filter and filtered to suppress the interference of noise and obtain the second vibration signal of the car in the vertical direction.

[0103] In a specific implementation, an algorithm such as FFT may be used to convert the second acceleration signal from the time domain to the frequency domain to obtain the third candidate signal.

[0104] Users have different sensitivities to vibrations in different frequency bands. The vibration frequency band in which users react most strongly is 1Hz-80Hz, while the vibration frequency band in which standing users react most strongly is 4Hz-8Hz. Therefore, the third candidate signal is subjected to band-limited filtering, acceleration and velocity conversion filtering, and high-order filtering to suppress high-frequency signals and obtain a low-frequency fourth candidate signal.

[0105] Furthermore, the band-limited filtering process can be divided into high-pass filtering process and low-pass filtering process.

[0106] The third candidate signal is input into a preset high-pass filter and high-pass filtered to obtain a fifth reference signal.

[0107] Taking a second-order Butterworth filter as an example of a high-pass filter, the high-pass filtering process is as follows:

[0108]

[0109] Among them, s is the third candidate signal, H h (s) is the fifth reference signal, w1 is the angular frequency, the frequency f1 corresponding to w1 (w1 = 2πf1) is a constant, such as 0.4 Hz, and Q1 is the resonant quality factor, such as

[0110] The third candidate signal is input into a low-pass filter and low-pass filtered to obtain a sixth reference signal.

[0111] Taking a second-order Butterworth filter as an example of a low-pass filter, the low-pass filtering process is as follows:

[0112]

[0113] Among them, s is the third candidate signal, H l (s) is the sixth reference signal, w2 is the angular frequency, the frequency f2 corresponding to w2 (w2 = 2πf2) is a constant, such as 100 Hz, and Q2 is the resonance quality factor, such as

[0114] The first candidate signal is input into the av conversion filter, and the third candidate signal is subjected to speed-to-speed conversion filtering to obtain a seventh reference signal. At this time, the seventh reference signal is proportional to the acceleration at a lower frequency and proportional to the speed at a higher frequency.

[0115] Exemplarily, the process of filtering the transformation between speeds is as follows:

[0116]

[0117] Among them, s is the third candidate signal, H t (s) is the seventh reference signal, w3 is the angular frequency, the frequency f3 corresponding to w3 (w3 = 2πf3) is a constant, such as 12.5 Hz, w4 is the angular frequency, the frequency f4 corresponding to w4 (w4 = 2πf4) is a constant, such as 12.5 Hz, Q4 is the resonance quality factor, such as K is the gain, such as 12.5.

[0118] The first candidate signal is input into a high-order filter, and the third candidate signal is subjected to high-order filtering to obtain an eighth reference signal, wherein the order of the high-order filter is positively correlated with the magnitude of the second acceleration signal.

[0119] Exemplarily, the process of high-order filtering is as follows:

[0120]

[0121] Among them, s is the third candidate signal, H s (s) is the eighth reference signal, w5 is the angular frequency, the frequency f5 corresponding to w5 (w5=2πf5) is a constant, such as 2.37Hz, w6 is the angular frequency, the frequency f6 corresponding to w6 (w6=2πf6) is a constant, such as 3.35Hz, Q5 is the resonance quality factor, such as 0.91, and Q6 is the resonance quality factor, such as 0.91.

[0122] The product of the fifth reference signal, the sixth reference signal, the seventh reference signal and the eighth reference signal is calculated to obtain a fourth candidate signal.

[0123] Then, the fourth candidate signal can be expressed as:

[0124] H(s)=H h (s)*H l (s)*H t (s)*H s (s)

[0125] Among them, H(s) is the fourth candidate signal, H h (s) is the fifth reference signal, H l (s) is the sixth reference signal, H t (s) is the seventh reference signal, H s (s) is the eighth reference signal.

[0126] At this time, the fourth candidate signal can be converted from the time domain to the frequency domain using algorithms such as IFFT to obtain a second vibration signal of the car in the vertical direction.

[0127] Step 1033: extract the second vibration feature from each second vibration signal.

[0128] For the second vibration signals corresponding to the respective second parameter values, one or more features may be extracted from the respective second vibration signals as the second vibration features.

[0129] Exemplarily, a plurality of second peak-to-peak signals are extracted from the second vibration signal; and a second quantile signal is located in the plurality of second peak-to-peak signals as the second vibration feature.

[0130] The number of second peak-to-peak signals that are less than or equal to the second quantile signal and the number of first peak-to-peak signals that are greater than the second quantile signal meet a specified second ratio.

[0131] For example, if the second quantile signal is an A95 signal, it means that 95% of the second peak-to-peak signals are less than or equal to the A95 signal, and 5% of the second peak-to-peak signals are greater than the A95 signal.

[0132] Step 1034: compare the second vibration characteristics corresponding to the second parameter values ​​to find the optimal first parameter value.

[0133] In this embodiment, the second vibration characteristics corresponding to the second parameter values ​​are compared, and the second parameter value with the best performance of the second vibration characteristic is found among all the second parameters.

[0134] Exemplarily, when the second vibration characteristic is a second quantile signal, the second quantile signals of the second parameter values ​​are compared to screen out the second parameter value with the smallest second quantile signal as the optimal second parameter value. At this time, the overall vibration of the car in the vertical direction can be effectively reduced.

[0135] Of course, the above-mentioned second vibration characteristics and the method for finding the optimal second parameter value are only used as examples. When implementing this embodiment, other second vibration characteristics and the method for finding the optimal second parameter value can be set according to actual conditions. For example, when the second peak-to-peak signal and the second quantile signal are both used as the first vibration characteristics, the weighted sum of the average value of the second peak-to-peak signal and the first quantile signal can be used to obtain the second index value, and the second parameter value with the smallest second index value can be screened out as the optimal second parameter value, etc. This embodiment does not limit this. In addition, in addition to the above-mentioned second vibration characteristics and the method for finding the optimal second parameter value, those skilled in the art can also adopt other second vibration characteristics and the method for finding the optimal second parameter value according to actual needs, and this embodiment does not limit this either.

[0136] Step 104: Apply the optimal second parameter value to the integral parameter.

[0137] The second stage is completed by applying the optimal second parameter value to the integral parameter in the motor speed loop parameter.

[0138] The optimal first parameter value is used as the value of the proportional parameter, and the optimal second parameter value is used as the value of the integral parameter and stored locally to complete the self-learning of the speed loop parameters. At this time, the elevator can exit the speed loop self-learning mode.

[0139] In this embodiment, a plurality of first parameter values ​​are set for the proportional parameter, and a plurality of second parameter values ​​are set for the proportional parameter; when the fixed integral parameter and the proportional parameter are adjusted to the first parameter values ​​in sequence, the motor is controlled to drag the car respectively, so as to find the optimal first parameter value according to the vibration signal of the car in the vertical direction; when the fixed proportional parameter applies the optimal first parameter value, and the integral parameter is adjusted to the second parameter values ​​in sequence, the motor is controlled to drag the car respectively, so as to find the optimal second parameter value according to the vibration signal of the car in the vertical direction; the optimal second parameter value is applied to the integral parameter. This embodiment provides a self-learning framework for the speed loop parameters of the elevator motor, optimizes the proportional parameter and the integral parameter in stages from the vibration of the car in the vertical direction, reduces the bumps of the car when the elevator is running, and ensures the user's experience of riding the elevator, and the automated process can reduce the requirements for engineering personnel, reduce the threshold for adjusting the speed loop parameters of the elevator motor, and shorten the debugging time, thereby effectively improving the efficiency of adjusting the speed loop parameters of the elevator motor.

[0140] Embodiment 2

[0141] See also Figure 2 , showing a schematic diagram of the structure of a speed loop parameter adjustment device provided in the second embodiment of the present invention. Applied to an elevator, the elevator is equipped with a motor for dragging a car, and the speed loop parameters of the motor include a proportional parameter and an integral parameter, such as Figure 2 As shown, the device comprises:

[0142] A parameter value setting module 201, configured to set a plurality of first parameter values ​​for the proportional parameter and a plurality of second parameter values ​​for the integral parameter;

[0143] A proportional parameter optimization module 202, for controlling the motor to drag the car respectively when the integral parameter is fixed and the proportional parameter is adjusted to each of the first parameter values ​​in sequence, so as to find the optimal first parameter value according to the vibration signal of the car in the vertical direction;

[0144] An integral parameter optimization module 203, for controlling the motor to drag the car respectively when the proportional parameter is fixed and the optimal first parameter value is applied and the integral parameter is adjusted to each second parameter value in sequence, so as to find the optimal second parameter value according to the vibration signal of the car in the vertical direction;

[0145] The integral parameter application module 204 is used to apply the optimal second parameter value to the integral parameter.

[0146] In one embodiment of the present invention, the parameter value setting module 201 includes:

[0147] A first interval query module, used to query a first interval configured for the ratio parameter;

[0148] A first averaging module, used for setting a plurality of first parameter values ​​for the proportion parameter within the first interval; wherein the interval between two adjacent first parameter values ​​is a preset first step length;

[0149] A second interval query module, used to query a second interval configured for the integral parameter;

[0150] The second averaging module is used to set a plurality of second parameter values ​​for the integral parameter within the second interval; wherein a preset second step length is provided between two adjacent second parameter values.

[0151] In one embodiment of the present invention, the ratio parameter optimization module 202 includes:

[0152] A first acceleration signal acquisition module is used to control the motor to drag the car, and to acquire a first acceleration signal in a vertical direction of the car when the integral parameter is fixed and a certain second parameter value is applied and the proportional parameter adjusts a certain first parameter value;

[0153] a first vibration signal filtering module, configured to filter the first acceleration signal to obtain a first vibration signal of the car in a vertical direction;

[0154] A first vibration feature extraction module, used to extract a first vibration feature from each of the first vibration signals;

[0155] A first parameter value optimization module, used for comparing the first vibration characteristics corresponding to the first parameter values ​​to find the optimal first parameter value;

[0156] The integral parameter optimization module 203 includes:

[0157] A second acceleration signal acquisition module is used to control the motor to drag the car, and to collect a second acceleration signal in a vertical direction of the car when the proportional parameter is fixed to apply the optimal first parameter value and the integral parameter is adjusted to a certain second parameter value;

[0158] a second vibration signal filtering module, used for filtering the second acceleration signal to obtain a second vibration signal of the car in a vertical direction;

[0159] A second vibration feature extraction module, used to extract a second vibration feature from each of the second vibration signals;

[0160] The second parameter value optimization module is used to compare the second vibration characteristics corresponding to each second parameter value to find the optimal first parameter value.

[0161] In one embodiment of the present invention, the first vibration signal filtering module includes:

[0162] A first time-frequency conversion module, used for converting the first acceleration signal from the time domain to the frequency domain to obtain a first candidate signal;

[0163] A first comprehensive filtering module, used for performing band-limited filtering, acceleration and velocity conversion filtering, and high-order filtering on the first candidate signal to obtain a second candidate signal;

[0164] A first time-frequency inverse conversion module, used for converting the second candidate signal from the time domain to the frequency domain to obtain a first vibration signal of the car in the vertical direction;

[0165] The second vibration signal filtering module comprises:

[0166] A second time-frequency conversion module, used for converting the second acceleration signal from the time domain to the frequency domain to obtain a third candidate signal;

[0167] A second comprehensive filtering module is used to perform band-limited filtering, acceleration and velocity conversion filtering, and high-order filtering on the third candidate signal to obtain a fourth candidate signal;

[0168] The second time-frequency inverse conversion module is used to convert the fourth candidate signal from the time domain to the frequency domain to obtain a second vibration signal of the car in the vertical direction.

[0169] In one embodiment of the present invention, the first comprehensive filtering module includes:

[0170] A first high-pass filtering module, configured to perform high-pass filtering on the first candidate signal to obtain a first reference signal;

[0171] A first low-pass filtering module, configured to perform low-pass filtering on the first candidate signal to obtain a second reference signal;

[0172] A first transformation and filtering module, configured to perform a transformation and filtering process between speeds on the first candidate signal to obtain a third reference signal;

[0173] A first high-order filtering module, configured to perform high-order filtering on the first candidate signal to obtain a fourth reference signal;

[0174] A first filtering product module, configured to calculate the product of the first reference signal, the second reference signal, the third reference signal and the fourth reference signal to obtain a second candidate signal;

[0175] The second comprehensive filtering module comprises:

[0176] A second high-pass filtering module, used for performing high-pass filtering on the third candidate signal to obtain a fifth reference signal;

[0177] A second low-pass filtering module, used for performing low-pass filtering on the third candidate signal to obtain a sixth reference signal;

[0178] A second transformation and filtering module is used to perform a transformation and filtering process between speeds on the third candidate signal to obtain a seventh reference signal;

[0179] A second high-order filtering module, used for performing high-order filtering on the third candidate signal to obtain an eighth reference signal;

[0180] The second filtering product module is used to calculate the product of the fifth reference signal, the sixth reference signal, the seventh reference signal and the eighth reference signal to obtain a fourth candidate signal.

[0181] In one embodiment of the present invention, the first vibration feature extraction module includes:

[0182] A first peak-to-peak value signal extraction module, used to extract a plurality of first peak-to-peak value signals from the first vibration signal;

[0183] A first quantile signal locating module, used for locating a first quantile signal in the plurality of the first peak-to-peak signals as a first vibration feature;

[0184] wherein the number of the first peak-to-peak signals that are less than or equal to the first quantile signal and the number of the first peak-to-peak signals that are greater than the first quantile signal meet a specified first ratio;

[0185] The second vibration feature extraction module comprises:

[0186] A second peak-to-peak value signal extraction module, used for extracting a plurality of second peak-to-peak values ​​from the second vibration signal;

[0187] A second quantile signal locating module, used for locating a second quantile signal in the plurality of the second peak-to-peak signals as a second vibration feature;

[0188] The number of the second peak-to-peak signals that are less than or equal to the second quantile signal and the number of the first peak-to-peak signals that are greater than the second quantile signal satisfy a specified second ratio.

[0189] In one embodiment of the present invention, the first parameter value optimization module includes:

[0190] A first parameter value screening module, used for comparing the first quantile signals of the first parameter values ​​to screen out the first parameter value with the smallest first quantile signal as the optimal first parameter value;

[0191] The second parameter value optimization module includes:

[0192] The second parameter value screening module is used to compare the second quantile signals of the second parameter values ​​to screen out the second parameter value with the smallest second quantile signal as the optimal second parameter value.

[0193] The speed loop parameter adjustment device provided in the embodiment of the present invention can execute the speed loop parameter adjustment method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of executing the speed loop parameter adjustment method.

[0194] Embodiment 3

[0195] See also Figure 3 , shows a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, blade servers, mainframe computers, and other suitable computers. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0196] like Figure 3 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0197] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0198] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the method for adjusting the speed loop parameters.

[0199] In some embodiments, the method for adjusting the speed loop parameters may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the method for adjusting the speed loop parameters described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the method for adjusting the speed loop parameters in any other appropriate manner (e.g., by means of firmware).

[0200] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0201] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0202] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0203] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0204] Embodiment 4

[0205] An embodiment of the present invention further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the method for adjusting the speed loop parameters provided in any embodiment of the present invention is implemented.

[0206] In the process of implementation, the computer program product can be written in one or more programming languages ​​or a combination thereof to perform the computer program code of the present invention, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0207] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0208] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for adjusting speed loop parameters, characterized in that: Applied to an elevator, the elevator is equipped with a motor for dragging a car, the speed loop parameters of the motor include a proportional parameter and an integral parameter, and the method includes: Setting a plurality of first parameter values ​​for the proportional parameter and a plurality of second parameter values ​​for the integral parameter; When the integral parameter is fixed and the proportional parameter is adjusted to the first parameter values ​​in sequence, the motor is controlled to drag the car respectively, so as to find the optimal first parameter value according to the vibration signal of the car in the vertical direction; When the proportional parameter is fixed and the optimal first parameter value is applied, and the integral parameter is adjusted to each second parameter value in sequence, the motor is controlled to drag the car respectively, so as to find the optimal second parameter value according to the vibration signal of the car in the vertical direction; An optimal second parameter value is applied to the integration parameter.

2. The method according to claim 1, characterized in that The step of setting a plurality of first parameter values ​​for the proportional parameter and a plurality of second parameter values ​​for the integral parameter comprises: Querying a first interval configured for the ratio parameter; In the first interval, a plurality of first parameter values ​​are set for the proportion parameter; wherein the interval between two adjacent first parameter values ​​is a preset first step length; Querying a second interval configured for the integral parameter; In the second interval, a plurality of second parameter values ​​are set for the integral parameter; wherein a preset second step length is spaced between two adjacent second parameter values.

3. The method according to claim 1 or 2, characterized in that: When the integral parameter is fixed and the proportional parameter is adjusted to each of the first parameter values ​​in sequence, the motor is controlled to drag the car respectively to find the optimal first parameter value according to the vibration signal of the car in the vertical direction, including: When the integral parameter is fixed and a certain second parameter value is applied, and the proportional parameter is used to adjust a certain first parameter value, the motor is controlled to drag the car, and a first acceleration signal in a vertical direction of the car is collected; Performing filtering processing on the first acceleration signal to obtain a first vibration signal of the car in a vertical direction; extracting a first vibration feature from each of the first vibration signals; Comparing the first vibration characteristics corresponding to the first parameter values ​​to find the optimal first parameter value; When the proportional parameter is fixed and the optimal first parameter value is applied, and the integral parameter is adjusted to each second parameter value in sequence, the motor is controlled to drag the car respectively to find the optimal second parameter value according to the vibration signal of the car in the vertical direction, including: When the proportional parameter is fixed to apply the optimal first parameter value and the integral parameter is adjusted to a certain second parameter value, the motor is controlled to drag the car, and a second acceleration signal in the vertical direction of the car is collected; Performing filtering processing on the second acceleration signal to obtain a second vibration signal of the car in the vertical direction; extracting a second vibration feature from each of the second vibration signals; The second vibration characteristics corresponding to each of the second parameter values ​​are compared to find the optimal first parameter value.

4. The method according to claim 3, characterized in that: The filtering process on the first acceleration signal to obtain a first vibration signal of the car in a vertical direction includes: Converting the first acceleration signal from the time domain to the frequency domain to obtain a first candidate signal; Performing band-limited filtering, acceleration and velocity conversion filtering, and high-order filtering on the first candidate signal to obtain a second candidate signal; Convert the second candidate signal from the time domain to the frequency domain to obtain a first vibration signal of the car in the vertical direction; The filtering the second acceleration signal to obtain a second vibration signal of the car in the vertical direction includes: Converting the second acceleration signal from the time domain to the frequency domain to obtain a third candidate signal; Performing band-limited filtering, acceleration and velocity conversion filtering, and high-order filtering on the third candidate signal to obtain a fourth candidate signal; The fourth candidate signal is converted from the time domain to the frequency domain to obtain a second vibration signal of the car in the vertical direction.

5. The method according to claim 4, characterized in that The step of performing band-limited filtering, acceleration and velocity conversion filtering, and high-order filtering on the first candidate signal to obtain a second candidate signal includes: Performing high-pass filtering on the first candidate signal to obtain a first reference signal; Performing low-pass filtering on the first candidate signal to obtain a second reference signal; Performing speed-to-speed conversion filtering on the first candidate signal to obtain a third reference signal; Performing high-order filtering on the first candidate signal to obtain a fourth reference signal; Calculate the product of the first reference signal, the second reference signal, the third reference signal and the fourth reference signal to obtain a second candidate signal; The step of performing band-limited filtering, acceleration and velocity conversion filtering, and high-order filtering on the third candidate signal to obtain a fourth candidate signal includes: Performing high-pass filtering on the third candidate signal to obtain a fifth reference signal; Performing low-pass filtering on the third candidate signal to obtain a sixth reference signal; Performing speed-to-speed conversion filtering processing on the third candidate signal to obtain a seventh reference signal; Performing high-order filtering on the third candidate signal to obtain an eighth reference signal; A product of the fifth reference signal, the sixth reference signal, the seventh reference signal and the eighth reference signal is calculated to obtain a fourth candidate signal.

6. The method according to claim 3, characterized in that The extracting the first vibration feature from each of the first vibration signals comprises: extracting a plurality of first peak-to-peak signals from the first vibration signal; Locating a first quantile signal among the plurality of the first peak-to-peak signals as a first vibration feature; wherein the number of the first peak-to-peak signals that are less than or equal to the first quantile signal and the number of the first peak-to-peak signals that are greater than the first quantile signal meet a specified first ratio; The extracting the second vibration feature from each of the second vibration signals comprises: extracting a plurality of second peak-to-peak signals from the second vibration signal; Locating a second quantile signal among the plurality of the second peak-to-peak signals as a second vibration feature; The number of the second peak-to-peak signals that are less than or equal to the second quantile signal and the number of the first peak-to-peak signals that are greater than the second quantile signal satisfy a specified second ratio.

7. The method according to claim 6, characterized in that The comparing the first vibration characteristics corresponding to the first parameter values ​​to find the optimal first parameter value includes: Comparing the first quantile signals of the first parameter values ​​to select the first parameter value with the smallest first quantile signal as the optimal first parameter value; The comparing the second vibration characteristics corresponding to the respective second parameter values ​​to find the optimal first parameter value includes: The second quantile signals of the second parameter values ​​are compared to select the second parameter value with the smallest second quantile signal as the optimal second parameter value.

8. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can perform the method for adjusting the speed loop parameters according to any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for adjusting the speed loop parameters according to any one of claims 1 to 7 is implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the method for adjusting the speed loop parameters according to any one of claims 1 to 7 is implemented.

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