WO2020192281A1 - Elevator brake fault monitoring method, device and system - Google Patents
Elevator brake fault monitoring method, device and system Download PDFInfo
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- WO2020192281A1 WO2020192281A1 PCT/CN2020/074611 CN2020074611W WO2020192281A1 WO 2020192281 A1 WO2020192281 A1 WO 2020192281A1 CN 2020074611 W CN2020074611 W CN 2020074611W WO 2020192281 A1 WO2020192281 A1 WO 2020192281A1
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B5/00—Applications of checking, fault-correcting, or safety devices in elevators
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B5/00—Applications of checking, fault-correcting, or safety devices in elevators
- B66B5/02—Applications of checking, fault-correcting, or safety devices in elevators responsive to abnormal operating conditions
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/08—Locating faults in cables, transmission lines, or networks
Definitions
- This application relates to the technical field of elevators, and in particular to a method, device and system for monitoring elevator brake faults.
- the brake device is an important safety guarantee for the elevator. If there is a problem with the brake device, there is a greater safety hazard.
- a brake device (such as a brake shoe or a brake shoe) is the moving part of the brake, and the surface is a friction surface.
- the brake drum pushes the brake device, it will brake the elevator.
- the brake device will brake the elevator when the motor is powered off.
- the brake shoes will inevitably undergo certain wear or cracks.
- the brake will be abnormal, which is manifested by insufficient brake energy, and the lighter will cause If the car slides, it can cause the car to fall.
- the embodiments of the present application provide a fault monitoring method, device, equipment, and medium, which can monitor the brake device through the signal characteristic value of the acoustic emission signal, and improve the safety monitoring reliability of the elevator.
- an embodiment of the present application provides an elevator brake fault monitoring method, the method including:
- Receive acoustic emission signals which are emitted by the brake device when the elevator is braking
- the signal characteristic value includes a time domain signal characteristic value and a frequency domain signal characteristic value
- the frequency domain signal characteristic value is not within the frequency domain signal reference range, it is determined that the brake device is faulty.
- the extracting signal characteristic value includes:
- the characteristic analysis method is used to perform correlation analysis on the time domain variables of the acoustic emission signal to determine the characteristic value of the time domain signal of the acoustic emission signal;
- the time domain variables include: amplitude, energy, ring count, event, rise Time, duration and threshold voltage.
- the extracting signal characteristics includes: using a spectrum analysis method to analyze the frequency spectrum variables of the acoustic emission signal to determine the frequency domain signal characteristics of the acoustic emission signal ;
- the frequency spectrum variables include: amplitude, duration, energy, arrival time, root mean square voltage value, number of impacts, number of impacts rate and external parameters.
- the method further includes:
- the method further includes that determining the time domain signal reference range and the frequency domain signal reference range includes:
- the characteristic analysis method is used to perform correlation analysis on the time domain variables of the filtered multiple acoustic emission signals to determine the time domain signal characteristics of the multiple filtered acoustic emission signals;
- the time domain variables include: amplitude, energy, Ringing count, event, rise time, duration and threshold voltage;
- the frequency spectrum analysis method is used to perform correlation analysis on the frequency spectrum variables of the filtered multiple acoustic emission signals to determine the frequency domain signal characteristics of the multiple filtered acoustic emission signals;
- the frequency spectrum variables include: amplitude, duration, energy , Arrival time, root mean square voltage value, number of hits, rate of hits, external parameters;
- an embodiment of the present application also provides an elevator fault monitoring device, the device including:
- Acoustic emission sensor for receiving acoustic emission signals, which are emitted by the brake device when the elevator is braking;
- the control unit is configured to convert the acoustic emission signal into a voltage signal, and filter the voltage signal to extract a signal characteristic value; wherein the signal characteristic value includes a time domain signal characteristic value and a frequency domain signal characteristic value;
- the control unit is also used for judging whether the brake device is faulty according to the signal characteristic threshold;
- control unit determines that the brake device is faulty
- the control unit determines that the brake device is faulty.
- the control unit includes a first analysis subunit, and the first analysis subunit is used for adopting a characteristic analysis method to analyze the time domain variables of the acoustic emission signal. Perform correlation analysis to determine the time domain signal characteristic value of the acoustic emission signal; the time domain variables include: amplitude, energy, ringing count, event, rise time, duration, and threshold voltage.
- the control unit includes a second analysis sub-unit, and the second analysis sub-unit is used to perform a spectrum analysis method on the spectrum variables of the acoustic emission signal. Analyze and determine the frequency domain signal characteristic value of the acoustic emission signal; the frequency spectrum variables include: amplitude, duration, energy, arrival time, root mean square voltage value, number of impacts, number rate of impacts and external parameters.
- the device further includes an alarm unit configured to trigger an alarm after the control unit determines that the brake device is faulty.
- the present application also provides an elevator fault monitoring system, which includes: a brake device and the elevator fault monitoring device described above.
- the acoustic emission signal is converted into a voltage signal, and the voltage signal is processed Filtering, and then further extract the signal characteristic value from the filtered voltage signal, where the extracted signal characteristic value includes the time domain signal characteristic value and the frequency domain signal characteristic value; judge according to the time domain signal reference range and the frequency domain signal reference range Whether the brake device is faulty, wherein if the characteristic value of the time domain signal is not within the reference range of the time domain signal, it is determined that the brake device is faulty; if the characteristic value of the frequency domain signal is not within the reference range of the frequency domain signal, the brake device is determined malfunction.
- the above solution can monitor the brake device through the signal characteristic value of the acoustic emission signal, and improve the reliability of the safety monitoring of the elevator.
- Figure 1 is a schematic structural diagram of an elevator brake fault monitoring system according to an embodiment of the application.
- Figure 2 is a flowchart of a method for monitoring elevator brake faults according to an embodiment of the application
- Figure 3 is a schematic structural diagram of an elevator brake fault monitoring device according to an embodiment of the application.
- an embodiment of the present application provides an elevator fault monitoring system 100.
- the system includes a brake device 101 and an elevator fault monitoring device 300.
- the brake device 101 when the elevator is braking, the brake device 101 will emit an elastic wave and finally be transmitted to the surface of the material, causing an acoustic emission signal that can be detected by the acoustic emission sensor.
- the elastic wave transmitted in the brake device 101 will change due to the elastic impact of the above-mentioned fault, and the acoustic emission signal generated will also be changed. Changes will occur.
- the acoustic emission signal contains a wealth of collision and friction information. Unlike the vibration method, the frequency range of the acoustic emission signal is generally above 20 kHz, while the frequency of the vibration signal is generally lower. Therefore, the acoustic emission signal will not be disturbed by mechanical vibration and noise;
- the elevator fault monitoring device 300 receives the acoustic emission signal transmitted through the brake device 101, converts the acoustic emission signal into a voltage signal, filters the voltage signal, and extracts the characteristics of the signal.
- an embodiment of the present application provides a method 200 for monitoring an elevator brake fault.
- the method includes the following steps: S201, S202, and S203.
- S201 Receive acoustic emission signals, which are emitted by the brake device when the elevator is braking.
- the holding device when the holding device has cracks, wear, indentation, notch, occlusion, and poor lubrication, the surface roughness and other phenomena will cause the elastic impact of the contact surface to pass the elastic wave.
- the form is released, and the bouncing standing wave will cause a burst of acoustic emission signal, which contains information about the collision and friction between the brake device and the elevator.
- the location of the damage on the brake device and the different stress state caused the damage degree of the brake device to be different, and the characteristics of the acoustic emission signal obtained were also different.
- the frequency range of the acoustic emission signal is generally above 20kHz, and the frequency of the vibration signal is low, the acoustic emission signal will not be disturbed by the vibration signal generated by mechanical vibration.
- S202 Convert the acoustic emission signal into a voltage signal, and filter the voltage signal to extract a signal characteristic value; where the signal characteristic value includes a time domain signal characteristic value and a frequency domain signal characteristic value.
- a sensor when receiving the acoustic emission signal, can be used to receive, for example, a transducer, an acoustic emission sensor, and the sensor can be used to convert the acoustic emission signal into a voltage signal.
- the received acoustic emission The signal is a waveform in which different frequency harmonics are superimposed after multiple reflections, waveform attenuation and waveform transformation.
- the voltage signal is filtered, for example, high-pass filtering is used to eliminate noise.
- the characteristic value of the voltage signal is extracted, and the extracted signal characteristic includes the characteristic value of the time domain signal and the characteristic value of the frequency domain signal.
- the specific method for extracting the signal characteristic value includes: adopting the characteristic analysis method to perform correlation analysis on the time domain variable of the acoustic emission signal to determine the time domain signal characteristic value of the acoustic emission signal; the time domain variables include: Amplitude, energy, ring count, event, rise time, duration and threshold voltage.
- the characteristic value of the signal in the time domain can be analyzed using a characteristic analysis method to analyze the characteristic parameters of the voltage signal, such as amplitude, energy, ring count, event , Rise time, duration, and threshold voltage.
- the characteristic analysis can be a correlation graph analysis, that is, two parameters are arbitrarily selected from the above characteristic parameters for correlation analysis to obtain the time-domain characteristics and internal laws of the acoustic emission signal, and then determine the sound The time-domain signal characteristic value of the transmitted signal.
- extracting signal characteristic values includes: using a spectrum analysis method to analyze the spectrum variables of the acoustic emission signal to determine the frequency domain signal characteristics of the acoustic emission signal; the spectrum variables include: amplitude, duration, energy, Arrival time, root mean square voltage value, number of hits, rate of hits and external parameters.
- the frequency domain characteristics of the acoustic emission signal can be used to obtain the frequency domain characteristics of the acoustic emission signal, and determine the frequency domain characteristics of the acoustic emission signal value.
- S203 Determine whether the brake device is faulty according to the reference range of the time domain signal and the reference range of the frequency domain signal; among them,
- the brake device is faulty.
- the acoustic emission signal when transmitted to the sensor in the brake device that has a fault, it has certain characteristics, that is, when the brake device is in a normal state, the characteristics of the acoustic emission signal are based on the brake device. In the normal state of the device, the characteristics of the acoustic emission signal can obtain the reference range of the time domain signal and the reference range of the frequency domain signal. After determining the characteristic value of the time domain signal and the characteristic value of the frequency domain signal, the characteristic value of the time domain signal and the time domain signal The reference range is compared.
- the characteristic value of the time domain signal is not within the reference range of the time domain signal, it is determined that the brake device is faulty; the characteristic value of the commented signal is compared with the reference range of the frequency domain signal. Within the reference range of the domain signal, it is determined that the brake device is faulty.
- the specific method for determining the time domain signal reference range and the frequency domain signal reference range includes:
- Collect multiple acoustic emission signals convert multiple acoustic emission signals into multiple voltage signals, and filter multiple voltage signals;
- the characteristic analysis method is used to correlate the time domain variables of the filtered multiple acoustic emission signals to determine the time domain signal characteristics of the filtered multiple acoustic emission signals;
- the time domain variables include: amplitude, energy, ring count, Event, rise time, duration and threshold voltage;
- the spectrum analysis method is used to correlate the spectrum variables of the filtered multiple acoustic emission signals to determine the frequency domain signal characteristics of the filtered multiple acoustic emission signals;
- the spectrum variables include: amplitude, duration, energy, arrival time, Root mean square voltage value, number of hits, rate of hits, external parameters;
- the frequency domain signal reference range is determined.
- the acoustic emission signals of multiple normal brake devices are measured, and by recording the characteristics of the acoustic emission signals in the normal state, the characteristics are analyzed and set as the threshold.
- the collected multiple acoustic emission signals are converted into voltage signals and then filtered to eliminate noise.
- the characteristic analysis method is used to analyze the characteristic parameters of the voltage signal, such as amplitude, energy, ringing count, event, rise time, duration, and threshold voltage.
- the characteristic analysis can be correlation graph analysis, that is, in the above characteristic parameters Select two parameters arbitrarily to perform correlation analysis to obtain the time-domain characteristics and internal laws of the acoustic emission signal, and determine the time-domain signal reference range according to the time-domain characteristics and internal laws, that is, the time-domain signal characteristics of multiple acoustic emission signals .
- the frequency domain characteristics of multiple acoustic emission signals can be obtained, and the frequency domain signal reference range of acoustic emission signals can be determined.
- the alarm mechanism is triggered, for example, alarm information is generated and sent to the monitoring cloud platform.
- the alarm information may be a number, such as "1", that is, when the monitoring cloud platform
- the received signal is 1, which proves that the elevator brake is faulty and an alarm is issued.
- an alarm is issued, it can be alarmed by a buzzer or a reminder lamp.
- the elevator brake fault monitoring method after receiving the acoustic emission signal emitted by the brake device when braking, converts the acoustic emission signal into a voltage signal, and filters the voltage signal, and then further The signal characteristic value is extracted from the filtered voltage signal, where the extracted signal characteristic value includes the time domain signal characteristic value and the frequency domain signal characteristic value; according to the time domain signal reference range and the frequency domain signal reference range, it is judged whether the brake device is If the characteristic value of the time domain signal is not within the reference range of the time domain signal, the brake device is determined to be faulty; if the characteristic value of the frequency domain signal is not within the reference range of the frequency domain signal, it is determined that the brake device is faulty.
- the above solution can monitor the brake device through the signal characteristic value of the acoustic emission signal, and improve the reliability of the safety monitoring of the elevator.
- an embodiment of the present application also provides an elevator brake fault monitoring device 300, where the device 300 includes an acoustic emission sensor 301 and a control unit 302.
- Acoustic emission sensor 301 used to receive the acoustic emission signal generated by the brake device during elevator braking;
- the control unit 302 is configured to convert an acoustic emission signal into a voltage signal, and filter the voltage signal to extract a signal characteristic value; wherein the signal characteristic value includes a time domain signal characteristic value and a frequency domain signal characteristic value;
- the control unit 302 is also used for judging whether the brake device is faulty according to the signal characteristic threshold;
- control unit determines that the brake device is faulty
- control unit determines that the brake device is faulty.
- control unit 302 includes a first analysis subunit 3021, and the first analysis subunit 3021 is used to use a feature analysis method to perform correlation analysis on the time domain variables of the acoustic emission signal to determine the time domain signal of the acoustic emission signal Characteristic value; time domain variables include: amplitude, energy, ring count, event, rise time, duration, and threshold voltage.
- control unit 302 includes a second analysis subunit 3022, and the second analysis subunit 3022 is used to analyze the spectrum variables of the acoustic emission signal by using a spectrum analysis method to determine the frequency domain signal characteristic value of the acoustic emission signal ;
- Spectral variables include: amplitude, duration, energy, arrival time, root mean square voltage value, number of impacts, number of impacts rate and external parameters.
- the device further includes an alarm unit 303, which is used to trigger an alarm after the control unit 302 determines that the brake device is faulty.
- control unit 302 is further configured to determine the time domain signal reference range and the frequency domain signal reference range before receiving the acoustic emission signal.
- control unit 302 is further configured to determine a time domain signal reference range and a frequency domain signal reference range, including:
- Collect multiple acoustic emission signals convert multiple acoustic emission signals into multiple voltage signals, and filter multiple voltage signals;
- the characteristic analysis method is used to correlate the time domain variables of the filtered multiple acoustic emission signals to determine the time domain signal characteristics of the filtered multiple acoustic emission signals;
- the time domain variables include: amplitude, energy, ring count, Event, rise time, duration and threshold voltage;
- the spectrum analysis method is used to correlate the spectrum variables of the filtered multiple acoustic emission signals to determine the frequency domain signal characteristics of the filtered multiple acoustic emission signals;
- the spectrum variables include: amplitude, duration, energy, arrival time, Root mean square voltage value, number of hits, rate of hits, external parameters;
- the frequency domain signal reference range is determined.
- the functional blocks shown in the above structural block diagram can be implemented as hardware, software, firmware, or a combination thereof.
- hardware When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in, a function card, and so on.
- ASIC application specific integrated circuit
- the elements of this application are programs or code segments used to perform required tasks.
- the program or code segment may be stored in a machine-readable medium, or transmitted on a transmission medium or communication link through a data signal carried in a carrier wave.
- "Machine-readable medium" may include any medium that can store or transmit information.
- machine-readable media examples include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio frequency (RF) links, and so on.
- the code segment can be downloaded via a computer network such as the Internet, an intranet, etc.
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- Maintenance And Inspection Apparatuses For Elevators (AREA)
- Indicating And Signalling Devices For Elevators (AREA)
Abstract
Description
Claims (10)
- 一种电梯抱闸故障监测方法,所述方法包括:An elevator brake fault monitoring method, the method includes:接收声发射信号,所述声发射信号由抱闸装置在电梯制动时发出;Receive acoustic emission signals, which are emitted by the brake device when the elevator is braking;将所述声发射信号转换为电压信号,对所述电压信号进行滤波以提取信号特征值;其中,所述信号特征值包括时域信号特征值和频域信号特征值;Converting the acoustic emission signal into a voltage signal, and filtering the voltage signal to extract a signal characteristic value; wherein the signal characteristic value includes a time domain signal characteristic value and a frequency domain signal characteristic value;根据时域信号参考范围和频域信号参考范围,判断所述抱闸装置是否故障;其中,According to the reference range of the time domain signal and the reference range of the frequency domain signal, determine whether the brake device is malfunctioning; wherein,若所述时域信号特征值不在所述时域信号参考范围内,则确定所述抱闸装置故障;If the characteristic value of the time domain signal is not within the reference range of the time domain signal, determining that the brake device is faulty;若所述频域信号特征值不在所述频域信号参考范围内,则确定所述抱闸装置故障。If the frequency domain signal characteristic value is not within the frequency domain signal reference range, it is determined that the brake device is faulty.
- 根据权利要求1所述的方法,所述提取信号特征值包括:The method according to claim 1, wherein said extracting signal characteristic values comprises:采用特征分析法,对所述声发射信号的时域变量进行关联分析,确定所述声发射信号的时域信号特征值;所述时域变量包括:幅度、能量、振铃计数、事件、上升时间、持续时间和门槛电压。The characteristic analysis method is used to perform correlation analysis on the time domain variables of the acoustic emission signal to determine the characteristic value of the time domain signal of the acoustic emission signal; the time domain variables include: amplitude, energy, ring count, event, rise Time, duration and threshold voltage.
- 根据权利要求1所述的方法,所述提取信号特征包括:The method according to claim 1, wherein said extracting signal features comprises:采用频谱分析法,对所述声发射信号的频谱变量进行分析,确定所述声发射信号的频域信号特征;所述频谱变量包括:幅度、持续时间、能量、到达时间、均方根电压值、撞击数、撞击数率和外接参量。The spectrum analysis method is used to analyze the spectrum variables of the acoustic emission signal to determine the frequency domain signal characteristics of the acoustic emission signal; the spectrum variables include: amplitude, duration, energy, arrival time, root mean square voltage value , Impact number, impact number rate and external parameters.
- 根据权利要求1所述的方法,所述方法还包括,在接收所述声发射信号之前,确定所述时域信号参考范围和频域信号参考范围。The method according to claim 1, further comprising, before receiving the acoustic emission signal, determining the time domain signal reference range and frequency domain signal reference range.
- 根据权利要求4所述的方法,所述确定所述时域信号参考范围和频域信号参考范围,包括:The method according to claim 4, the determining the time domain signal reference range and the frequency domain signal reference range comprises:采集多个声发射信号,将所述多个声发射信号转换为多个电压信号,对所述多个电压信号进行滤波;Collecting multiple acoustic emission signals, converting the multiple acoustic emission signals into multiple voltage signals, and filtering the multiple voltage signals;采用特征分析法,对滤波后的多个声发射信号的时域变量进行关联分析,确定所述滤波后的多个声发射信号的时域信号特征;所述时域变量包括:幅度、能量、振铃计数、事件、上升时间、持续时间和门槛电压;The characteristic analysis method is used to perform correlation analysis on the time domain variables of the filtered multiple acoustic emission signals to determine the time domain signal characteristics of the multiple filtered acoustic emission signals; the time domain variables include: amplitude, energy, Ringing count, event, rise time, duration and threshold voltage;根据所述多个声发射信号的时域信号特征,确定所述时域信号参考范围;以及,Determining the time-domain signal reference range according to the time-domain signal characteristics of the multiple acoustic emission signals; and,采用频谱分析法,对滤波后的多个声发射信号的频谱变量进行关联分析,确定所述滤波后的多个声发射信号的频域信号特征;所述频谱变量包括:幅度、持续时间、能量、到达时间、均方根电压值、撞击数、撞击数率、外接参量;The frequency spectrum analysis method is used to perform correlation analysis on the frequency spectrum variables of the filtered multiple acoustic emission signals to determine the frequency domain signal characteristics of the multiple filtered acoustic emission signals; the frequency spectrum variables include: amplitude, duration, energy , Arrival time, root mean square voltage value, number of hits, rate of hits, external parameters;根据所述多个声发射信号的频域信号特征,确定所述频域信号参考范围。Determine the frequency domain signal reference range according to the frequency domain signal characteristics of the multiple acoustic emission signals.
- 一种电梯故障监测装置,所述装置包括:An elevator fault monitoring device, the device comprising:声发射传感器,用于接收声发射信号,所述声发射信号由抱闸装置在电梯制动时发出;Acoustic emission sensor, used to receive acoustic emission signals, which are emitted by the brake device when the elevator is braking;控制单元,用于将所述声发射信号转换为电压信号,对所述电压信号进行滤波以提取信号特征值;其中所述信号特征值包括时域信号特征值和频域信号特征值;The control unit is configured to convert the acoustic emission signal into a voltage signal, and filter the voltage signal to extract a signal characteristic value; wherein the signal characteristic value includes a time domain signal characteristic value and a frequency domain signal characteristic value;所述控制单元还用于根据信号特征阈值,判断所述抱闸装置是否故障;其中,The control unit is also used for judging whether the brake device is faulty according to the signal characteristic threshold; wherein,若所述时域信号特征值不在所述时域信号参考范围内,则所述控制单元确定所述抱闸装置故障;If the characteristic value of the time domain signal is not within the reference range of the time domain signal, the control unit determines that the brake device is faulty;若所述频域信号特征值不在所述频域信号参考范围内,则所述控制单元确定所述抱闸装置故障。If the frequency domain signal characteristic value is not within the frequency domain signal reference range, the control unit determines that the brake device is faulty.
- 根据权利要求6所述的装置,所述控制单元包括第一分析子单元,所述第一分析子单元用于采用特征分析法,对所述声发射信号的时域变量进行关联分析,确定所述声发射信号的时域信号特征值;所述时域变量包括:幅度、能量、振铃计数、事件、上升时间、持续时间和门槛电压。The device according to claim 6, wherein the control unit comprises a first analysis sub-unit, and the first analysis sub-unit is configured to use a characteristic analysis method to perform correlation analysis on the time-domain variables of the acoustic emission signal to determine The time-domain signal characteristic value of the acoustic emission signal; the time-domain variables include: amplitude, energy, ringing count, event, rise time, duration, and threshold voltage.
- 根据权利要求6所述的装置,所述控制单元包括第二分析子单元,所述第二分析子单元用于采用频谱分析法,对所述声发射信号的频谱变量进行分析,确定所述声发射信号的频域信号特征值;所述频谱变量包括:幅度、持续时间、能量、到达时间、均方根电压值、撞击数、撞击数率和外接参量。The device according to claim 6, wherein the control unit comprises a second analysis subunit, and the second analysis subunit is configured to use a spectrum analysis method to analyze the spectrum variables of the acoustic emission signal to determine the acoustic emission signal. The frequency domain signal characteristic value of the transmitted signal; the frequency spectrum variables include: amplitude, duration, energy, arrival time, root mean square voltage value, number of impacts, number of impacts rate and external parameters.
- 根据权利要求6所述的装置,所述装置还包括告警单元,所述告警单元用于在所述控制单元确定所述抱闸装置故障后触发报警。The device according to claim 6, further comprising an alarm unit configured to trigger an alarm after the control unit determines that the brake device is faulty.
- 一种电梯故障监测系统,所述系统包括:抱闸装置和如权利要求6-9中任一项所述的电梯故障监测装置。An elevator fault monitoring system, the system comprising: a brake device and the elevator fault monitoring device according to any one of claims 6-9.
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Citations (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2007230731A (en) * | 2006-03-01 | 2007-09-13 | Mitsubishi Electric Building Techno Service Co Ltd | Abnormality detection device of elevator |
US20100139403A1 (en) * | 2008-12-04 | 2010-06-10 | University Of Ottawa | Parameter independent detection of rotating machinery faults |
CN106219342A (en) * | 2016-08-19 | 2016-12-14 | 广州广日电梯工业有限公司 | Elevator self diagnosis based on time-frequency convert algorithm and pre-diagnostic system and method |
CN106841911A (en) * | 2016-12-20 | 2017-06-13 | 国网河北省电力公司电力科学研究院 | Transient state travelling wave signal recognition method and device during a kind of cable fault |
CN206606891U (en) * | 2016-12-23 | 2017-11-03 | 通力股份公司 | Device for elevator rope condition monitoring |
WO2018119845A1 (en) * | 2016-12-29 | 2018-07-05 | 深圳配天智能技术研究院有限公司 | State detection method and system for numerical control machine tool |
CN108439111A (en) * | 2018-02-28 | 2018-08-24 | 武汉大学 | A kind of elevator motion exception real-time detection method based on wavelet transformation |
CN108875710A (en) * | 2018-07-24 | 2018-11-23 | 杭州电子科技大学 | Elevator door speed of service estimation method based on energy threshold algorithm |
CN109941860A (en) * | 2019-03-22 | 2019-06-28 | 西人马(西安)测控科技有限公司 | Elevator internal contracting brake fault monitoring method, device and system |
Family Cites Families (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102448864B (en) * | 2010-06-16 | 2014-07-02 | Natac株式会社 | Method for monitoring damage to wire rope for elevator and device for monitoring damage to wire rope for elevator |
CN108907895A (en) * | 2018-04-13 | 2018-11-30 | 上海交通大学 | A kind of milling cutter breakage on-line monitoring method |
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Patent Citations (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2007230731A (en) * | 2006-03-01 | 2007-09-13 | Mitsubishi Electric Building Techno Service Co Ltd | Abnormality detection device of elevator |
US20100139403A1 (en) * | 2008-12-04 | 2010-06-10 | University Of Ottawa | Parameter independent detection of rotating machinery faults |
CN106219342A (en) * | 2016-08-19 | 2016-12-14 | 广州广日电梯工业有限公司 | Elevator self diagnosis based on time-frequency convert algorithm and pre-diagnostic system and method |
CN106841911A (en) * | 2016-12-20 | 2017-06-13 | 国网河北省电力公司电力科学研究院 | Transient state travelling wave signal recognition method and device during a kind of cable fault |
CN206606891U (en) * | 2016-12-23 | 2017-11-03 | 通力股份公司 | Device for elevator rope condition monitoring |
WO2018119845A1 (en) * | 2016-12-29 | 2018-07-05 | 深圳配天智能技术研究院有限公司 | State detection method and system for numerical control machine tool |
CN108439111A (en) * | 2018-02-28 | 2018-08-24 | 武汉大学 | A kind of elevator motion exception real-time detection method based on wavelet transformation |
CN108875710A (en) * | 2018-07-24 | 2018-11-23 | 杭州电子科技大学 | Elevator door speed of service estimation method based on energy threshold algorithm |
CN109941860A (en) * | 2019-03-22 | 2019-06-28 | 西人马(西安)测控科技有限公司 | Elevator internal contracting brake fault monitoring method, device and system |
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