Elevator comfort intelligent adjustment method, device, equipment and storage medium

Abstract

The application discloses an elevator comfort intelligent adjustment method, device and equipment and a storage medium, and belongs to the elevator control technical field.The application detects the running state of an elevator car in real time to generate a detection signal, converts the detection signal into a communication signal, extracts features from the communication signal to generate a feature signal, performs phase compensation according to the feature signal to obtain a torque current compensation signal, and adjusts the torque of the elevator according to the torque current compensation signal.The application collects signals of the elevator to generate the detection signal, converts the detection signal into the communication signal, extracts features from the communication signal after transmission, compensates the communication signal according to the feature signal, obtains the torque current compensation signal, adjusts the torque according to the compensation result, and thus realizes the intelligent adjustment of the comfort of the elevator and improves the comfort of passengers.

Description

Technical Field

[0001] The present invention relates to the field of elevator control technology, and in particular to an elevator comfort intelligent adjustment method, device, equipment and storage medium. Background Art

[0002] Elevators, as a means of vertical transportation, are becoming increasingly widespread. As elevator system safety improves, people increasingly demand higher levels of comfort in elevator operation. Currently, elevator car-side operation relies on gyroscope-based multi-axis accelerometers to collect acceleration signals. These sensors then offline modify the control system's PI parameters based on the acceleration signal feedback. However, this only fine-tunes the PI parameters, resulting in poor adjustment of the elevator's operating status. Furthermore, the acceleration signals during actual operation are contaminated with useless information, which can easily introduce abnormal noise during elevator operation adjustments, exacerbating the deterioration of elevator car comfort.

[0003] The above content is only used to assist in understanding the technical solution of the present invention and does not constitute an admission that the above content is prior art. Summary of the Invention

[0004] The main purpose of the present invention is to provide a method, device, equipment and storage medium for intelligent adjustment of elevator comfort, aiming to solve the technical problem in the prior art that abnormal jitter in elevator operation causes poor passenger comfort.

[0005] To achieve the above object, the present invention provides an intelligent adjustment method for elevator comfort, the method comprising the following steps:

[0006] Perform real-time signal detection on the operating status of the elevator car and generate detection signals;

[0007] converting the detection signal into a communication signal;

[0008] Extracting features from the communication signal to generate a feature signal;

[0009] Phase compensation is performed according to the characteristic signal to obtain a torque current compensation signal, and torque regulation is performed on the elevator according to the torque current compensation signal.

[0010] Optionally, performing real-time signal detection on the operating status of the elevator car to generate a detection signal includes:

[0011] Perform real-time status detection on the elevator's operating status to obtain acceleration signals;

[0012] Signal processing is performed according to the acceleration signal to generate a detection signal.

[0013] Optionally, converting the detection signal into a communication signal includes:

[0014] Select a target communication method from preset communication methods, and obtain corresponding communication rules according to the target communication method;

[0015] converting the detection signal into a communication signal according to the communication rule;

[0016] The preset communication mode includes at least one of CAN communication, wireless communication, power carrier communication and serial communication.

[0017] Optionally, extracting features based on the communication signal to generate a feature signal includes:

[0018] converting the communication signal into the detection signal;

[0019] Performing signal analysis on the detection signal to generate a signal to be processed, wherein the signal analysis includes calibrating the zero drift and gain of the acceleration signal;

[0020] Feature extraction is performed based on the signal to be processed to generate a feature signal.

[0021] Optionally, extracting features based on the signal to be processed to generate a feature signal includes:

[0022] According to the characteristic frequency obtained in the self-learning model, the characteristics of the signal to be processed are extracted to generate a characteristic signal and a phase compensation value.

[0023] Optionally, performing phase compensation according to the characteristic signal to obtain a torque current compensation signal, and performing torque regulation on the elevator according to the torque current compensation signal includes:

[0024] Perform signal control according to the characteristic signal to generate a control signal;

[0025] Phase compensation is performed according to the control signal to obtain a torque current compensation signal, and torque regulation is performed on the elevator according to the torque current compensation signal.

[0026] Optionally, performing phase compensation according to the control signal to obtain a torque current compensation signal, and performing torque regulation on the elevator according to the torque current compensation signal includes:

[0027] Phase compensation is performed according to the control signal and the phase compensation value to obtain a torque current compensation signal, and torque regulation is performed on the elevator according to the torque current compensation signal.

[0028] In addition, to achieve the above-mentioned purpose, the present invention further proposes an intelligent adjustment device for elevator comfort, the intelligent adjustment device for elevator comfort comprising:

[0029] The signal acquisition module is used to perform real-time signal detection on the operating status of the elevator car and generate a detection signal;

[0030] A signal transmission module, used for converting the detection signal into a communication signal;

[0031] A system control module, configured to extract features from the communication signal and generate a feature signal;

[0032] The system control module is further used to perform phase compensation according to the characteristic signal to obtain a torque current compensation signal, and perform torque regulation on the elevator according to the torque current compensation signal.

[0033] In addition, to achieve the above-mentioned purpose, the present invention also proposes an intelligent adjustment device for elevator comfort, which includes: a memory, a processor, and an intelligent adjustment program for elevator comfort stored on the memory and runnable on the processor, wherein the intelligent adjustment program for elevator comfort is configured to implement the steps of the intelligent adjustment method for elevator comfort as described above.

[0034] In addition, to achieve the above-mentioned purpose, the present invention also proposes a storage medium, on which an elevator comfort intelligent adjustment program is stored. When the elevator comfort intelligent adjustment program is executed by a processor, the steps of the elevator comfort intelligent adjustment method as described above are implemented.

[0035] The present invention performs real-time signal detection on the operating status of the elevator car to generate a detection signal, converts the detection signal into a communication signal, extracts features based on the communication signal to generate a characteristic signal, performs phase compensation based on the characteristic signal, obtains a torque current compensation signal, and performs torque adjustment on the elevator based on the torque current compensation signal. The present invention performs signal acquisition on the elevator to generate a detection signal, converts the detection signal into a communication signal, extracts features of the communication signal after transmission, obtains a characteristic signal, compensates the communication signal, obtains a torque current compensation signal, and performs torque adjustment based on the compensation result, thereby realizing intelligent adjustment of elevator comfort and improving passenger comfort. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 1 is a schematic diagram of the structure of an intelligent elevator comfort adjustment device in a hardware operating environment according to an embodiment of the present invention;

[0037] Figure 2 This is a flow chart of the first embodiment of the intelligent adjustment method for elevator comfort of the present invention;

[0038] Figure 3 This is a flow chart of a second embodiment of the intelligent adjustment method for elevator comfort of the present invention;

[0039] Figure 4 This is a signal analysis flow diagram of an embodiment of an intelligent adjustment method for elevator comfort according to the present invention;

[0040] Figure 5 This is a structural block diagram of the first embodiment of the intelligent adjustment device for elevator comfort of the present invention.

[0041] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0042] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0043] Reference Figure 1 , Figure 1 This is a schematic diagram of the structure of an intelligent elevator comfort adjustment device in the hardware operating environment involved in an embodiment of the present invention.

[0044] like Figure 1 As shown, the intelligent elevator comfort adjustment device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and optionally the user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a wireless fidelity (Wi-Fi) interface). The memory 1005 may be a high-speed random access memory (RAM) memory or a stable non-volatile memory (NVM), such as a disk memory. The memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0045] Those skilled in the art will understand that Figure 1 The structure shown in the figure does not constitute a limitation on the intelligent elevator comfort adjustment device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0046] like Figure 1 As shown, the memory 1005 as a storage medium may include an operating system, a network communication module, a user interface module, and an elevator comfort intelligent adjustment program.

[0047] exist Figure 1 In the intelligent elevator comfort adjustment device shown, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the intelligent elevator comfort adjustment device of the present invention can be set in the intelligent elevator comfort adjustment device, and the intelligent elevator comfort adjustment device calls the intelligent elevator comfort adjustment program stored in the memory 1005 through the processor 1001 and executes the intelligent elevator comfort adjustment method provided in the embodiment of the present invention.

[0048] The embodiment of the present invention provides an intelligent adjustment method for elevator comfort. Figure 2 , Figure 2 This is a flow chart of a first embodiment of an intelligent adjustment method for elevator comfort according to the present invention.

[0049] In this embodiment, the elevator comfort intelligent adjustment method includes the following steps:

[0050] Step S10: Perform real-time signal detection on the operating status of the elevator car and generate a detection signal.

[0051] It should be noted that real-time signal detection of the elevator car's operating status and generation of a detection signal based on the detection results can be performed by a circuit including a microprocessor or a single-chip microcomputer control chip, and performing data signal detection with an acceleration sensor. The acceleration sensor can be a six-axis gyroscope accelerometer, a nine-axis gyroscope accelerometer, or other sensor with acceleration detection capabilities. The detection signal can include an acceleration signal.

[0052] Step S20: converting the detection signal into a communication signal.

[0053] It can be understood that the communication signal can be transmitted by multiple communication units, such as CAN communication unit, wireless communication unit, power carrier communication unit and serial communication unit and other communication units with signal transmission function. The required transmission method is selected according to the actual needs of signal transmission, and then the signal is transmitted by the transmission unit corresponding to the required transmission method. By converting the detection signal into a communication signal, the communication signal is sent quickly to realize wired or wireless signal transmission and ensure that there is no data loss during the data transmission process.

[0054] Step S30: extracting features from the communication signal to generate a feature signal.

[0055] It's easy to understand that after receiving a communication signal, it can be converted back into a detection signal, and features extracted from the detection signal. This feature signal can then be generated based on a self-learning model. When the elevator comfort intelligent adjustment device enters self-learning mode, it can obtain the elevator's operating status for each of its up and down runs. It then takes the acceleration signal detected by the steady-speed acceleration sensor, performs Fourier decomposition on the acceleration signal, and obtains multiple frequency signals. The frequency that meets the comfort requirement is used as the characteristic frequency, which is then used to train the self-learning model. The feature signal includes the signal with the characteristic frequency.

[0056] Step S40: performing phase compensation according to the characteristic signal to obtain a torque current compensation signal, and performing torque regulation on the elevator according to the torque current compensation signal.

[0057] It should be understood that when the elevator comfort intelligent adjustment device enters the self-learning mode, it actively sends an excitation signal of a frequency, and then compares and analyzes the detection signal fed back by the acceleration sensor with the excitation signal and performs calculation processing to obtain a phase delay compensation value, that is, a phase compensation value. The phase compensation calculation analysis is performed based on the phase compensation value and the characteristic signal to obtain a torque current compensation signal. The torque current compensation signal can be a torque current compensation value. According to the torque current compensation signal, the torque of the elevator can be adjusted, so that the elevator operation state meets the passenger comfort requirements.

[0058] This embodiment performs real-time signal detection on the operating status of the elevator car to generate a detection signal, converts the detection signal into a communication signal, extracts features from the communication signal to generate a characteristic signal, performs phase compensation based on the characteristic signal, obtains a torque-current compensation signal, and performs torque adjustment on the elevator based on the torque-current compensation signal. This embodiment collects elevator signals to generate a detection signal, converts the detection signal into a communication signal, extracts features from the communication signal after transmission, obtains a characteristic signal, compensates the communication signal, obtains a torque-current compensation signal, and performs torque adjustment based on the compensation result, thereby achieving intelligent adjustment of elevator comfort and improving passenger comfort.

[0059] refer to Figure 3 , Figure 3 This is a flow chart of a second embodiment of an intelligent adjustment method for elevator comfort according to the present invention.

[0060] Based on the first embodiment, in the intelligent adjustment method for elevator comfort in this embodiment, step S10 includes:

[0061] Step S101: Perform real-time status detection on the running status of the elevator to obtain an acceleration signal.

[0062] It should be noted that the real-time status detection of the elevator's operating status can be performed by an acceleration sensor. The acceleration sensor can be a six-axis gyroscope accelerometer, a nine-axis gyroscope accelerometer, or other sensor with acceleration detection capabilities. The acceleration sensor can detect the elevator's operating status in real time and generate an acceleration signal based on the detection results.

[0063] Step S102: performing signal processing according to the acceleration signal to generate a detection signal.

[0064] It can be understood that signal processing is performed based on the acceleration signal to generate a detection signal. The corresponding signal processing function can be performed by a circuit including a microprocessor or a single-chip microcomputer control chip. The microcontroller unit can receive the acceleration signal, amplify and filter the acceleration signal, and form a communication frame through analysis and processing, and generate a detection signal based on the communication frame.

[0065] The step S20 includes:

[0066] Step S201: selecting a target communication method from preset communication methods, and obtaining corresponding communication rules according to the target communication method.

[0067] Step S202: converting the detection signal into a communication signal according to the communication rule; wherein the preset communication method includes at least one of CAN communication, wireless communication, power carrier communication and serial communication.

[0068] It can be understood that the communication signal can be transmitted by multiple communication units, such as CAN communication unit, wireless communication unit, power carrier communication unit and serial communication unit and other communication units with signal transmission function. The communication unit corresponds to a preset communication mode, and the preset communication mode includes at least one of CAN communication, wireless communication, power carrier communication and serial communication.

[0069] It is easy to understand that according to the actual needs of signal transmission, the required transmission method, i.e., the target communication method, is selected from the preset communication methods, and then the transmission unit corresponding to the target communication method performs signal transmission. The detection signal is converted into a communication signal through the communication rules unique to the target communication method, and the communication signal is sent quickly, which can realize wired or wireless signal transmission and ensure that there is no data loss during the data transmission process.

[0070] The step S30 includes:

[0071] Step S301: converting the communication signal into the detection signal; performing signal analysis based on the detection signal to generate a signal to be processed, wherein the signal analysis includes calibration of the zero drift and gain of the acceleration signal.

[0072] It is easy to understand that there are multiple signal receiving methods for receiving transmitted communication signals, and the preset signal receiving methods for signal reception can correspond one-to-one with the preset communication methods, and in specific implementations, the preset signal receiving methods include at least one of CAN communication, wireless communication, power carrier communication and serial communication.

[0073] It is understandable that after receiving the communication signal, the communication signal can be restored to a detection signal, and the detection signal can be analyzed through the self-learning model to obtain multiple signals to be processed. The signal analysis includes calibration of the zero drift and gain of the acceleration signal. In a specific implementation, the self-learning model can be trained with multiple characteristic frequencies that meet comfort requirements. The detection signal can be processed by the self-learning model to obtain a first signal to be processed containing a first characteristic frequency and a second signal to be processed containing a second characteristic frequency, as well as a phase compensation value obtained by comparative analysis and calculation processing based on the excitation signal. The number of characteristic signals depends on the comfort quality of the current elevator operation, and usually 1 to 2 characteristic frequencies are selected for compensation.

[0074] It is easy to understand that if Figure 4 , Figure 4 This is a signal analysis flow diagram of an embodiment of the intelligent adjustment method for elevator comfort of the present invention. After the signal preprocessing subunit 3021 starts working, it can enter the self-learning mode according to the self-learning command, and input the detection signal into the trained self-learning model for signal analysis, so as to obtain the signal to be processed containing the characteristic frequency, that is, the phase compensation value, so that it can enter the subsequent analysis and processing.

[0075] Step S302: extracting features from the signal to be processed to generate a feature signal.

[0076] It is easy to understand that, in order to perform feature extraction on the signal to be processed, in a specific implementation, a filter can be used to filter the first signal to be processed containing the first characteristic frequency and the second signal to be processed containing the second characteristic frequency to filter out irrelevant signals in the signal to be processed, thereby generating characteristic signals, namely, the first characteristic signal containing the first characteristic frequency and the second characteristic signal containing the second characteristic frequency.

[0077] Furthermore, according to the characteristic frequency obtained in the self-learning model, feature extraction is performed on the signal to be processed to generate a characteristic signal and a phase compensation value.

[0078] It is easy to understand that feature extraction can use filters such as digital bandpass filters. In a specific implementation, a first bandpass filter can be used to filter a first signal to be processed containing a first characteristic frequency, and a second bandpass filter can be used to filter a second signal to be processed containing a second characteristic frequency, so as to filter out irrelevant signals in the signal to be processed, thereby generating characteristic signals, namely, a first characteristic signal containing harmonic variables of the first characteristic frequency and a second characteristic signal containing harmonic variables of the second characteristic frequency. The first characteristic signal and the second characteristic signal are both characteristic frequency signals within a certain bandwidth, usually 1 to 2 Hz.

[0079] It can be understood that the transfer function of the bandpass filter is:

[0080]

[0081] Among them, ω n is the center frequency of the bandpass filter, ξ is the damping coefficient of the bandpass filter, ω2 is the high-end cutoff frequency; ω1 is the low-end cutoff frequency.

[0082] The relationship between the damping coefficient and the high-end cutoff frequency and the low-end cutoff frequency is:

[0083]

[0084] Generally, the center frequencies of the bandpass filter are selected as characteristic frequency 1 and characteristic frequency 2, and the difference between the high-end cutoff frequency and the low-end cutoff frequency is generally selected to be 1 to 2 Hz.

[0085] The step S40 includes:

[0086] Step S401: performing signal control according to the characteristic signal to generate a control signal.

[0087] It is understandable that an adaptive regulator such as a proportional controller, a proportional-integral controller or a proportional-integral-differential controller may be used to perform signal control on the characteristic signal to generate a control signal.

[0088] Step S402: performing phase compensation according to the control signal to obtain a torque current compensation signal, and performing torque regulation on the elevator according to the torque current compensation signal.

[0089] It can be understood that phase compensation operation analysis can be performed based on the phase compensation value and the characteristic signal to obtain a torque current compensation signal. The torque current compensation signal can be a torque current compensation value. The torque of the elevator can be adjusted according to the torque current compensation signal, so that the elevator operation state meets the passenger comfort requirements.

[0090] Furthermore, phase compensation is performed based on the control signal and the phase compensation value to obtain a torque current compensation signal, and torque regulation is performed on the elevator based on the torque current compensation signal.

[0091] It is easy to understand that the phase compensation can be analyzed based on the phase compensation value and the characteristic signal. The phase compensation value is obtained based on the analysis of the excitation signal, so that the torque current compensation signal can be obtained. The torque current compensation signal can be a torque current compensation value. In a specific implementation, the first torque current compensation value can be compensated according to the first characteristic signal, and the second torque current compensation value can be compensated according to the second characteristic signal. The required torque current compensation signal is selected according to the actual comfort requirements, so as to adjust the torque of the elevator so that the elevator operation state meets the passenger comfort requirements.

[0092] This embodiment performs real-time status detection on the operating status of the elevator to obtain an acceleration signal, performs signal processing based on the acceleration signal to generate a detection signal, selects a target communication mode from preset communication modes, obtains a corresponding communication rule based on the target communication mode, and converts the detection signal into a communication signal according to the communication rule, wherein the preset communication mode includes at least one of CAN communication, wireless communication, power carrier communication and serial communication, converts the communication signal into a detection signal, performs signal analysis based on the detection signal to generate a signal to be processed, the signal analysis includes calibrating the zero drift and gain of the acceleration signal, extracts features of the signal to be processed based on the characteristic frequency obtained in the self-learning model, generates a characteristic signal and a phase compensation value, performs signal control based on the characteristic signal to generate a control signal, performs phase compensation based on the control signal and the phase compensation value to obtain a torque current compensation signal, and performs torque control on the elevator based on the torque current compensation signal, thereby realizing intelligent adjustment of elevator comfort, improving control accuracy, and further improving passenger comfort.

[0093] In addition, an embodiment of the present invention further proposes a storage medium on which an elevator comfort intelligent adjustment program is stored. When the elevator comfort intelligent adjustment program is executed by a processor, the steps of the elevator comfort intelligent adjustment method described above are implemented.

[0094] Since the storage medium adopts all the technical solutions of all the above embodiments, it has at least all the beneficial effects brought by the technical solutions of the above embodiments, which will not be described one by one here.

[0095] Reference Figure 5 , Figure 5 This is a structural block diagram of the first embodiment of the intelligent adjustment device for elevator comfort of the present invention.

[0096] like Figure 5 As shown, the intelligent adjustment device for elevator comfort proposed in an embodiment of the present invention includes:

[0097] The signal acquisition module 10 is used to perform real-time signal detection on the operating status of the elevator car and generate a detection signal.

[0098] It should be noted that real-time signal detection of the elevator car's operating status and generation of a detection signal based on the detection results can be performed by a circuit including a microprocessor or a single-chip microcomputer control chip, and performing data signal detection with an acceleration sensor. The acceleration sensor can be a six-axis gyroscope accelerometer, a nine-axis gyroscope accelerometer, or other sensor with acceleration detection capabilities. The detection signal can include an acceleration signal.

[0099] The signal transmission module 20 is used to convert the detection signal into a communication signal.

[0100] It can be understood that the communication signal can be transmitted by multiple communication units, such as CAN communication unit, wireless communication unit, power carrier communication unit and serial communication unit and other communication units with signal transmission function. The required transmission method is selected according to the actual needs of signal transmission, and then the signal is transmitted by the transmission unit corresponding to the required transmission method. By converting the detection signal into a communication signal, the communication signal is sent quickly to realize wired or wireless signal transmission and ensure that there is no data loss during the data transmission process.

[0101] The system control module 30 is used to extract features based on the communication signal and generate a feature signal.

[0102] It's easy to understand that after receiving a communication signal, it can be converted back into a detection signal, and features extracted from the detection signal. This feature signal can then be generated based on a self-learning model. When the elevator comfort intelligent adjustment device enters self-learning mode, it can obtain the elevator's operating status for each of its up and down runs. It then takes the acceleration signal detected by the steady-speed acceleration sensor, performs Fourier decomposition on the acceleration signal, and obtains multiple frequency signals. The frequency that meets the comfort requirement is used as the characteristic frequency, which is then used to train the self-learning model. The feature signal includes the signal with the characteristic frequency.

[0103] The system control module 30 is further configured to perform phase compensation according to the characteristic signal to obtain a torque current compensation signal, and perform torque regulation on the elevator according to the torque current compensation signal.

[0104] It should be understood that when the elevator comfort intelligent adjustment device enters the self-learning mode, it actively sends an excitation signal of a frequency, and then compares and analyzes the detection signal fed back by the acceleration sensor with the excitation signal and performs calculation processing to obtain a phase delay compensation value, that is, a phase compensation value. The phase compensation calculation analysis is performed based on the phase compensation value and the characteristic signal to obtain a torque current compensation signal. The torque current compensation signal can be a torque current compensation value. According to the torque current compensation signal, the torque of the elevator can be adjusted, so that the elevator operation state meets the passenger comfort requirements.

[0105] This embodiment performs real-time signal detection on the operating status of the elevator car to generate a detection signal, converts the detection signal into a communication signal, extracts features from the communication signal to generate a characteristic signal, performs phase compensation based on the characteristic signal, obtains a torque-current compensation signal, and performs torque adjustment on the elevator based on the torque-current compensation signal. This embodiment collects elevator signals to generate a detection signal, converts the detection signal into a communication signal, extracts features from the communication signal after transmission, obtains a characteristic signal, compensates the communication signal, obtains a torque-current compensation signal, and performs torque adjustment based on the compensation result, thereby achieving intelligent adjustment of elevator comfort and improving passenger comfort.

[0106] In one embodiment, the signal acquisition module 10 is further configured to perform real-time status detection on the running status of the elevator to obtain an acceleration signal; and perform signal processing according to the acceleration signal to generate a detection signal.

[0107] In one embodiment, the signal transmission module 20 is further used to select a target communication mode from preset communication modes, obtain corresponding communication rules according to the target communication mode; and convert the detection signal into a communication signal according to the communication rules; wherein the preset communication mode includes at least one of CAN communication, wireless communication, power carrier communication and serial communication.

[0108] In one embodiment, the system control module 30 is further used to convert the communication signal into the detection signal; perform signal analysis based on the detection signal to generate a signal to be processed, wherein the signal analysis includes calibration of the zero drift and gain of the acceleration signal; and perform feature extraction based on the signal to be processed to generate a feature signal.

[0109] In one embodiment, the system control module 30 is further configured to extract features of the signal to be processed based on the characteristic frequencies obtained in the self-learning model, and generate characteristic signals and phase compensation values.

[0110] In one embodiment, the system control module 30 is further used to perform signal control according to the characteristic signal to generate a control signal; perform phase compensation according to the control signal to obtain a torque current compensation signal; and perform torque regulation on the elevator according to the torque current compensation signal.

[0111] In one embodiment, the system control module 30 is further configured to perform phase compensation according to the control signal and the phase compensation value to obtain a torque current compensation signal, and perform torque regulation on the elevator according to the torque current compensation signal.

[0112] Since the intelligent adjustment device for elevator comfort adopts all the technical solutions of all the above embodiments, it has at least all the beneficial effects brought about by the technical solutions of the above embodiments, which will not be described one by one here.

[0113] It should be understood that the above is only an example and does not constitute any limitation to the technical solution of the present invention. In specific applications, those skilled in the art can make settings as needed, and the present invention does not impose any limitation on this.

[0114] It should be noted that the workflow described above is merely illustrative and does not limit the scope of protection of the present invention. In practical applications, technicians in this field can select part or all of it according to actual needs to achieve the purpose of the embodiment scheme, and no limitation is made here.

[0115] In addition, for technical details not fully described in this embodiment, reference can be made to the intelligent adjustment method for elevator comfort provided in any embodiment of the present invention, and will not be repeated here.

[0116] In addition, it should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or system comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or system. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or system comprising the element.

[0117] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0118] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, or of course by hardware, but in many cases the former is a better embodiment. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product is stored in a storage medium (such as a read-only memory (ROM) / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0119] The above are only preferred embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. An intelligent adjustment method for elevator comfort, characterized in that: The intelligent adjustment method for elevator comfort comprises: Perform real-time signal detection on the operating status of the elevator car and generate detection signals; converting the detection signal into a communication signal; Extracting features based on the communication signal, and generating a characteristic signal and a phase compensation value based on the characteristic frequency obtained in the self-learning model; Phase compensation is performed according to the characteristic signal and the phase compensation value to obtain a torque current compensation signal, and torque regulation is performed on the elevator according to the torque current compensation signal.

2. The intelligent adjustment method for elevator comfort according to claim 1, characterized in that: The real-time signal detection of the operating status of the elevator car and the generation of the detection signal include: Perform real-time status detection on the elevator's operating status to obtain acceleration signals; Signal processing is performed according to the acceleration signal to generate a detection signal.

3. The intelligent adjustment method for elevator comfort according to claim 1, characterized in that: The converting the detection signal into a communication signal comprises: Select a target communication method from preset communication methods, and obtain corresponding communication rules according to the target communication method; converting the detection signal into a communication signal according to the communication rule; The preset communication mode includes at least one of CAN communication, wireless communication, power carrier communication and serial communication.

4. The intelligent adjustment method for elevator comfort according to any one of claims 1 to 3, characterized in that: The feature extraction according to the communication signal and the generation of a feature signal and a phase compensation value according to the feature frequency obtained in the self-learning model include: converting the communication signal into the detection signal; Performing signal analysis on the detection signal to generate a signal to be processed, wherein the signal analysis includes calibrating the zero drift and gain of the acceleration signal; Feature extraction is performed based on the signal to be processed, and a characteristic signal and a phase compensation value are generated based on the characteristic frequency obtained in the self-learning model.

5. The intelligent adjustment method for elevator comfort according to claim 4, characterized in that: The performing phase compensation according to the characteristic signal and the phase compensation value to obtain a torque current compensation signal, and performing torque regulation on the elevator according to the torque current compensation signal, comprises: Perform signal control according to the characteristic signal to generate a control signal; Phase compensation is performed according to the control signal and the phase compensation value to obtain a torque current compensation signal, and torque regulation is performed on the elevator according to the torque current compensation signal.

6. An intelligent elevator comfort adjustment device, characterized in that: The intelligent adjustment device for elevator comfort comprises: The signal acquisition module is used to perform real-time signal detection on the operating status of the elevator car and generate a detection signal; A signal transmission module, used for converting the detection signal into a communication signal; A system control module, configured to extract features from the communication signal and generate a characteristic signal and a phase compensation value based on the characteristic frequency acquired in the self-learning model; The system control module is further used to perform phase compensation according to the characteristic signal and the phase compensation value to obtain a torque current compensation signal, and perform torque regulation on the elevator according to the torque current compensation signal.

7. An intelligent elevator comfort adjustment device, characterized in that: The elevator comfort intelligent adjustment device includes: a memory, a processor, and an elevator comfort intelligent adjustment program stored in the memory and executable on the processor, wherein the elevator comfort intelligent adjustment program is configured to implement the elevator comfort intelligent adjustment method according to any one of claims 1 to 5.

8. A storage medium, characterized in that: The storage medium stores an intelligent elevator comfort adjustment program, which, when executed by a processor, implements the intelligent elevator comfort adjustment method according to any one of claims 1 to 5.

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