CN116177337B - Multi-point distributed elevator monitoring system and method for abnormal passenger behaviors - Google Patents
Multi-point distributed elevator monitoring system and method for abnormal passenger behaviors Download PDFInfo
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- CN116177337B CN116177337B CN202211566964.3A CN202211566964A CN116177337B CN 116177337 B CN116177337 B CN 116177337B CN 202211566964 A CN202211566964 A CN 202211566964A CN 116177337 B CN116177337 B CN 116177337B
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 45
- 230000006399 behavior Effects 0.000 title claims abstract description 33
- 230000002159 abnormal effect Effects 0.000 title claims abstract description 23
- 238000000034 method Methods 0.000 title claims abstract description 23
- 206010000117 Abnormal behaviour Diseases 0.000 claims abstract description 20
- 238000012545 processing Methods 0.000 claims abstract description 18
- 238000007781 pre-processing Methods 0.000 claims abstract description 10
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Classifications
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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
- B66B5/0006—Monitoring devices or performance analysers
- B66B5/0012—Devices monitoring the users of the elevator system
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B1/00—Control systems of elevators in general
- B66B1/34—Details, e.g. call counting devices, data transmission from car to control system, devices giving information to the control system
- B66B1/3415—Control system configuration and the data transmission or communication within the control system
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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
- B66B5/0006—Monitoring devices or performance analysers
- B66B5/0037—Performance analysers
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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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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B50/00—Energy efficient technologies in elevators, escalators and moving walkways, e.g. energy saving or recuperation technologies
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- Indicating And Signalling Devices For Elevators (AREA)
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Abstract
The invention discloses a multipoint distributed elevator monitoring system and method for abnormal passenger behavior, wherein the system comprises the following steps: the sensor is used for monitoring the behaviors of the elevator and passengers in real time in all aspects; the data acquisition module is integrated with the sensor and is matched with the sensor to perform data acquisition and preprocessing; the controller is used for controlling the acquisition module to preprocess sensor data, and is responsible for the operation of the acquisition module, data uploading and data temporary storage; the remote data transmitter receives the data acquisition information and transmits the data acquisition information to the data intermediate station; the data intermediate station is in charge of receiving the acquisition information transmitted by the remote data transmitter and transmitting the acquisition information to the upper computer; the upper computer is arranged at the monitoring center, receives the whole acquired information, and performs secondary processing and big data storage on the data. The elevator monitoring system can monitor the elevator in an omnibearing manner in real time, so that abnormal behaviors of passengers in the elevator can be rapidly detected, behavior characteristics can be judged, normal and stable operation of the elevator can be timely ensured, and personal safety of the passengers in the elevator can be ensured.
Description
Technical Field
The invention relates to the technical field of elevators, in particular to a multipoint distributed elevator monitoring system and method for abnormal passenger behaviors.
Background
The elevator is a special vertical transportation means of high-rise buildings, the daily use of the elevator is more frequent along with the occurrence of more high-rise buildings, and the elevator accidents are gradually increased, so that the life safety of elevator passengers is ensured, and the high-level requirements on the safety operation and maintenance guarantee and treatment and risk prevention and control of the elevator are more urgent and important.
Besides the equipment faults in the running process of the elevator, the equipment faults of the elevator are accelerated by a plurality of factors, and the serious reason is that the abnormal extreme behaviors of passengers destroy the elevator car, including door scraping, jump, beating of the car wall, shouting and the like, so that the behavior conditions of the passengers in the elevator are accurately judged in real time, the method has important significance, and most of the current elevator real-time monitoring systems are incomplete in data acquisition, low in efficiency and high in packet loss rate in the data transmission process.
Disclosure of Invention
The invention aims to provide a multipoint distributed elevator monitoring system and method for abnormal behaviors of passengers, which can monitor the elevator in an omnibearing manner in real time, so that the abnormal behaviors of the passengers in the elevator can be rapidly detected, the behavior characteristics can be judged, the normal and stable running of the elevator can be timely ensured, and the personal safety of the passengers in the elevator can be ensured.
In order to achieve the above purpose, the present invention is realized by the following technical scheme:
a multipoint distributed passenger abnormal behavior elevator monitoring system comprising:
a sensor: the elevator is characterized in that the elevator is arranged on each wall surface of an elevator car and is used for monitoring the behaviors of passengers in the elevator in real time;
and a data acquisition module: the sensor is integrated with the elevator car, is arranged in the elevator car and is used for collecting, preprocessing and transmitting detection data of the sensor;
and (3) a controller: the elevator system is arranged in an elevator car and used for integrally controlling the data acquisition modules to preprocess acquired data, exchanging data information among the data acquisition modules, summarizing the data, temporarily storing the data and uploading control data information through a remote data transmitter;
remote data transmitter: the elevator system is arranged at the elevator car and is used for wirelessly transmitting the data sent by the controller to the data intermediate station;
a data intermediate station: the remote data transmitter is used for receiving the data information transmitted by the remote data transmitter and uploading the data to the upper computer; a data intermediate station is arranged at the control cabinet at the high-rise position of the elevator and at the guide rail at the bottom layer of the elevator;
the upper computer: and the monitoring center is arranged for identifying the passenger behavior by using the data uploaded by the received data intermediate station, and sending out alarm information when the passenger behavior is abnormal.
Preferably, the sensor comprises a triaxial accelerometer, a uniaxial accelerometer, a noise sensor, a microwave radar and a pyroelectric infrared sensor, wherein the triaxial accelerometer, the uniaxial accelerometer, the noise sensor, the microwave radar and the pyroelectric infrared sensor are all connected with the data acquisition module, and all the data acquisition modules are connected with the controller;
the triaxial accelerometer is arranged at the center of the bottom of the elevator car and is used for monitoring the three-way acceleration and three attitude angles of the elevator;
the single-axis accelerometers are arranged on three wall surfaces of the elevator car wall, the car door and the bottom of the car, and are used for monitoring impact acceleration values at all positions in real time;
the noise sensor is arranged in the center of the top of the elevator car and used for monitoring the sound signals in the elevator car in real time;
the microwave radar is arranged at the top of the elevator car and the car wall and is used for monitoring the respiratory rate of passengers in real time;
the pyroelectric infrared sensor is arranged at the top of the elevator car and used for monitoring infrared signals in the elevator car in real time and judging whether passengers and the number of passengers exist in the elevator car.
Preferably, the pyroelectric infrared sensor is arranged at the top of the elevator car and irradiates downwards in a cone shape, and the irradiation angle is 60-70 degrees.
Preferably, the data acquisition module comprises an operational amplifier, a sampling holder, a filter, a digital-to-analog converter and an Ethernet port which are connected in sequence; the operational amplifier is connected with the sensor, and the Ethernet port is connected with the controller.
Preferably, the controller adopts a DSP logic controller, and an external program and a data memory are arranged in the DSP logic controller, and the data memory can temporarily store collected data.
Preferably, the remote data transmitter comprises a power management module, a wireless transmission module, a singlechip controller and a surfing module; the wireless transmission module, the singlechip controller and the internet surfing module are all connected with the power management module, the wireless transmission module and the internet surfing module are both connected with the singlechip controller, the internet surfing module is connected with the controller, and the wireless transmission module is in wireless connection with the data intermediate station.
Preferably, the elevator car alarm system comprises an alarm module, wherein the alarm module is arranged in the elevator car and is connected with the controller, the upper computer sends alarm information to the controller through the data intermediate station and the remote data transmitter, and the controller alarms according to the alarm information.
The invention also provides an elevator monitoring method based on the multi-point distributed passenger abnormal behavior elevator monitoring system, which comprises the following steps:
and (3) signal acquisition: acquiring attitude angle and impact acceleration values of an elevator car, and acquiring sound signals, respiratory frequency and infrared signals of passengers in the elevator car;
and (3) signal transmission: preprocessing the acquired signals and uploading the signals;
and (3) signal processing: and processing the uploaded signals, judging whether the behaviors of the passengers are abnormal, and sending out alarm information if the behaviors of the passengers are abnormal.
Preferably, the preprocessing process of the collected signals during signal transmission comprises signal amplification, filtering and digital-to-analog conversion.
Preferably, during signal processing, the process of processing the uploaded signal and judging whether the behavior of the passenger is abnormal comprises the following steps:
fitting the uploaded signals to obtain a fitting curve;
extracting features of the fitting curve to obtain peak-to-peak values and root mean square values of the fitting curve, carrying out weighting treatment on the normalized feature values of different signals, and solving fitness functions of the different signals;
and comparing the fitness function of the same signal with a set self-adaptive threshold value, and judging whether the behavior of the passenger is abnormal or not according to a comparison result.
Preferably, the fitness function H is as follows:
wherein,and->Respectively representing the normalized root mean square value and peak-to-peak value; />The normalized energy percent value of the frequency band; omega 1 、ω 2 Respectively different weight values, and omega 1 +ω 2 =1; τ is the adaptive threshold value set.
The invention has the following beneficial effects:
according to the multi-point distributed elevator monitoring system for abnormal passenger behavior, the sensors can be used for comprehensively monitoring various parameters of the existence of passengers in the elevator, the vibration acceleration of the elevator in all directions, the respiratory rate of the passengers and the noise of the elevator and the passengers, and data transmission is carried out through a multi-level distributed data acquisition and transmission network, wireless and wired networks are combined, the monitoring range is wide, the cost performance is high, the real-time transmission capacity of data is not affected at the elevator at a high level, and the effectiveness and the stability of data transmission are improved; the monitoring system processes the real-time data twice, so that the data real-time processing and analyzing speed is improved, the system judges and early warns the abnormal behaviors of the passengers as soon as possible, and the life safety of the passengers is ensured.
Drawings
In order to more clearly illustrate the technical solution of the embodiments of the present invention, the following description will briefly explain the drawings of the embodiments.
Fig. 1 is a schematic diagram of the multi-point distributed passenger abnormal behavior elevator monitoring system of the present invention;
fig. 2 is a diagram showing an internal structure of a data acquisition module of the multi-point distributed passenger abnormal behavior elevator monitoring system according to the present invention;
fig. 3 is a block diagram of a remote data transmitter of the multi-point distributed passenger abnormal behavior elevator monitoring system of the present invention;
fig. 4 is a flow chart of data preprocessing of the acquisition module of the multi-point distributed passenger abnormal behavior elevator monitoring system of the present invention.
Detailed Description
Other advantages and effects of the present invention will become readily apparent to those skilled in the art from the following disclosure, when considered in light of the accompanying drawings, by describing embodiments of the present invention with specific embodiments thereof. The invention may be practiced or carried out in other embodiments and details within the scope and range of equivalents of the various features and advantages of the invention.
The system architecture comprises a sensor, a data acquisition module, a controller, a remote data transmitter, a data intermediate station and an upper computer; each sensor is connected with a data acquisition module, the data acquisition module is connected with a controller and is arranged at each position in the elevator car body, and the controller is further connected with a remote data transmitter and finally connected with an upper computer.
The sensor is arranged on each wall surface in the elevator car and is used for collecting the vibration data and the passenger data of the elevator car in real time, and comprises a triaxial accelerometer, a uniaxial accelerometer, a noise sensor, a microwave radar and a pyroelectric infrared sensor; the three-axis accelerometer is arranged in the center of the bottom of the elevator car, three-way acceleration and three attitude angles of the elevator are detected, the real-time inclination state of the elevator car is calculated, and the stress position and the stress condition of the elevator car can be judged according to the detection data of the three-axis accelerometer; the single-axis accelerometers are respectively arranged on each wall surface of the car, the car door and the bottom of the car, and are used for monitoring vibration acceleration values of all set positions in real time, and judging whether passengers have abnormal behaviors according to the obtained vibration acceleration values, namely judging whether the passengers have abnormal behaviors of hammer door, door scraping, wall beating and foot stamping.
The noise sensor is arranged in the center of the top of the elevator car and used for collecting noise decibels and noise frequencies in the elevator car in real time, and a two-dimensional decibel diagram of time or frequency on the abscissa can be generated according to sound signals collected by the noise sensor so as to judge whether passengers have abnormal behaviors such as quarrying or not;
the microwave radar is arranged at the top of the elevator car and the car wall and is used for sensing the movement condition of a passenger in a microwave range, collecting the respiratory rate of the passenger in real time and judging the real-time mood fluctuation and physical state condition of the passenger according to the respiratory rate of the passenger; the pyroelectric infrared sensor is arranged at the top of the elevator car and irradiates downwards in a cone shape, the irradiation angle is 60-70 degrees, the infrared imaging condition in the elevator is monitored in real time, whether passengers exist in the elevator and the number of the passengers in the elevator are judged by using the pyroelectric infrared sensor, and monitoring center monitoring staff are assisted to make more judgment. Referring to fig. 2, the data acquisition module includes an operational amplifier, a sample holder, a filter, a digital-to-analog converter, and an ethernet port connected in sequence; the filter is a low-pass filter, filters high-frequency noise signals of the elevator, and collects low-frequency vibration signals.
The sensors convert the acquired physical signals into corresponding electric signals and then output the corresponding electric signals to an operational amplifier in a data acquisition module connected with the sensors, wherein the operational amplifier is connected with the output end of the sensor and is responsible for amplifying weak electric signals of the sensors and adapting to the input range of a digital-to-analog converter; the sampling holder is connected with the output end of the operational amplifier, stores the amplified electric signal, and holds the electric signal for a certain time for conversion of the digital-to-analog converter until the next sampling time, and then takes out an analog signal value to replace the original value; the output end of the sampling holder is connected with a filter interface, the filter is responsible for filtering noise signals and high-frequency band uncorrelated signals in signals, carrying out low-pass filtering and multiple moving average filtering on digital signals, filtering high-frequency noise signals, smoothing the filtered signals, facilitating subsequent signal processing and avoiding signal overlapping and distortion, transmitting data through an Ethernet port, and temporarily storing the data through a memory of a controller. The input end of the digital-to-analog converter is connected with the output signal of the filter and is responsible for dispersing and encoding the analog data signal, converting the analog data signal into a discrete digital signal, temporarily storing the signal data through the controller and accessing the signal data into the remote data transmitter. Referring to fig. 3, the remote data transmitter includes a power management module, a wireless transmission module, a singlechip controller and a surfing module; the controller controls the data receiving and transmitting, the internet surfing module receives the collected and preprocessed sensor data, the remote data transmitter is connected to the network, the wireless transmission module is responsible for transmitting the data to the data intermediate station, and the power management module is responsible for supplying the work of each module. In addition, a remote data transmitter is installed at the top outside the elevator car and is responsible for wirelessly transmitting signal data to a data intermediate station.
The controller is arranged at the top of the car, the controller selects a DSP logic controller, a built-in power module, an external program and a data memory are arranged in the controller, the collected data is temporarily stored, the integrated control of the plurality of data collection modules carries out pretreatment on the collected data, data transmission among the modules, data summarization, data temporary storage and control data uploading through a remote data transmitter, the controller selects the DSP logic controller, the built-in power module, the external program and the data memory are arranged in the controller, and the collected data is temporarily stored.
A data intermediate station is respectively arranged at a control cabinet at the high-rise position of the elevator and a guide rail at the bottom layer of the elevator, and is used for receiving data information transmitted by a remote data transmitter, combining wireless communication with wired communication, integrating data and transmitting the data to an upper computer through a wired network; the intermediate station is respectively arranged on the top floor and the bottom floor of the elevator, and respectively receives elevator movement data at the high floor and the low floor in different receiving ranges, so that the transmission range of wireless data is greatly improved, and the reliability and the conveying volume of data transmission are improved by utilizing the stability of a wired network.
In addition, the two data intermediate stations can perform data interaction and transmission, so that the intervals of discrete data points of the real-time sensor are consistent, and the upper computer can conveniently perform secondary processing.
According to the invention, each sensor is respectively combined with a data acquisition module and a controller to be installed as a node hardware platform, is installed at different positions of an elevator car, performs sensor data acquisition and preprocessing, and uniformly transmits data to a remote data transmitter.
The upper computer is positioned at the monitoring center, software is combined with Labview to configure a software system, and a software interface mainly comprises a multi-characteristic value real-time display area, a display parameter setting area, a real-time data waveform drawing area and an alarm area;
the upper computer receives two sensor discrete data points integrated by the data intermediate station and is mainly responsible for carrying out secondary processing, characteristic value extraction and classification on vibration acceleration signals generated by the accelerometer and noise signals generated by the noise sensor: the method comprises the steps that wavelet packet noise reduction and moving average filtering combined noise reduction are carried out on a software UI interface on an upper computer, a real-time acceleration and noise signal time domain waveform graph after filtering noise reduction processing is drawn, a characteristic value display area is added in the UI interface, different characteristic values of an elevator are calculated and displayed in real time, wherein the different characteristic values comprise peak-to-peak values, root mean square values and energy value percentage values of 0-200Hz frequency bands in a frequency domain power spectral density function (PSD) corresponding to each accelerometer, then the software automatically processes and fits the characteristic values according to internal program control, and passengers in the elevator are displayed in real time in an alarm area through different set parameter threshold ranges, wherein the conditions comprise normal, foot stamping, door stamping, car wall damaging, quarrying and fight; when abnormal behaviors occur, the alarm area is displayed in red, and the alarm is given out through the loudspeaker.
The specific process of performing behavior discrimination and classification on the data by the upper computer software is as follows:
(1) The method comprises the steps of performing curve fitting on three data signals in the x direction, the y direction and the z direction of a triaxial accelerometer after preprocessing and noise reduction, three attitude angle change values and discrete points of data signals of each uniaxial accelerometer in an upper computer in real time, wherein the signals are preprocessed in the transmission process, namely signal amplification, filtering and analog-to-digital conversion, performing moving average filtering and wavelet packet filtering on the acceleration signal curves, noise reduction in combination, performing secondary processing and characteristic value acquisition on the data through upper computer software, including joint sampling on the three-axis accelerometer attitude angle curves and accelerometer signal curves in the x direction or the y direction (coordinate axis direction is perpendicular to the wall surface) at different wall surfaces, performing time domain peak-to-peak value and root mean square value extraction, performing frequency band energy value percentage extraction processing after decomposing a time domain wavelet packet to obtain characteristic value points, namely characteristic value extraction, performing time domain peak-to-peak value and root mean square value extraction on each accelerometer and each coordinate axis direction acceleration curve, performing frequency band energy occupation ratio extraction of 0-200Hz, performing weighting processing on different characteristic values, and performing weighting processing on the data after normalization, and the steps are as follows:
wherein,and->Represents the root mean square value and peak value after normalization, < >>To normalized band energy percentage value omega 1 、ω 2 Is of different weight values and omega 1 +ω 2 And (1) carrying out weight assignment objectively as much as possible, judging the transmitted information quantity by solving the information entropy of different characteristic values, and establishing objective weight.
τ is a set adaptive threshold value, corresponding characteristic values of the accelerometers at different mounting positions, and the threshold values are different in size, so that adaptive calculation is performed.
(2) Through the calculation of the fitness functions H of the different acceleration curves in (1), when the fitness functions H of the wall surface different accelerometers are calculated (wall surface) ＞τ 1 When τ is 1 The threshold value corresponding to the accelerometer curve at the wall surface shows that the wall surface has abnormal behavior, namely, a person performs wall surface hammering, and the wall surface where the wall surface occurs can be judged through the comparison of fitness functions of different wall surfaces;
(3) Similarly, when the car door H is calculated by the fitness function H (door) ＞τ 2 When τ is 2 The abnormal behavior of the passengers taking off the doors is indicated by a threshold value corresponding to an accelerometer curve at the car door;
(4) Also, when the car bottom H (Car bottom) ＞τ 3 When τ is 3 And the threshold value corresponding to the accelerometer curve at the bottom of the car is used for indicating jump and impact abnormal behaviors.
(5) The noise signal is further converted to extract a frequency domain characteristic value, and the frequency domain characteristic value is combined with a time domain peak value, so that whether the behavior of quarrying in the elevator occurs can be further judged;
(6) And the comparison of the different fitness function values H and the threshold tau is displayed on a software UI interface in real time, when H is more than tau, the interface tends to turn red, monitoring personnel are reminded through voice microphone broadcasting early warning, and finally, the monitoring personnel combine the number of passengers displayed by infrared to further evaluate and process.
The multipoint distributed abnormal passenger behavior elevator monitoring system monitors various parameters of the elevator car vibration condition, car noise index and the number of passengers in an omnibearing and real-time manner, and performs signal transmission through distributed network transmission nodes in a wired and wireless communication combination mode.
Claims (6)
1. A method for monitoring a multi-point distributed abnormal passenger behavior elevator, characterized by being performed by a multi-point distributed abnormal passenger behavior elevator monitoring system, the multi-point distributed abnormal passenger behavior elevator monitoring system comprising: a sensor: the sensors are arranged on the wall surfaces of the elevator car and are used for monitoring the behaviors of passengers in the elevator car in real time;
and a data acquisition module: the sensor is integrated with the elevator car, is arranged in the elevator car and is used for collecting, preprocessing and transmitting detection data of the sensor;
and (3) a controller: the elevator system is arranged in an elevator car and used for integrally controlling the data acquisition modules to preprocess acquired data, exchanging data information among the data acquisition modules, summarizing the data, temporarily storing the data and uploading control data information through a remote data transmitter;
remote data transmitter: the elevator system is arranged at the elevator car and is used for wirelessly transmitting the data sent by the controller to the data intermediate station;
a data intermediate station: the remote data transmitter is used for receiving the data information transmitted by the remote data transmitter and uploading the data to the upper computer; a data intermediate station is arranged at the elevator high-rise control cabinet and at the elevator bottom guide rail;
the upper computer: the monitoring center is arranged for identifying the behavior of the passenger by using the data uploaded by the received data intermediate station, and sending out alarm information when the behavior of the passenger is abnormal;
the multipoint distributed elevator monitoring method for abnormal passenger behaviors comprises the following steps:
and (3) signal acquisition: acquiring attitude angle and impact acceleration values of an elevator car, and acquiring sound signals, respiratory frequency and infrared signals of passengers in the elevator car;
and (3) signal transmission: preprocessing the acquired signals and uploading the signals;
and (3) signal processing: processing the uploaded signals, judging whether the behaviors of the passengers are abnormal, and sending out alarm information if the behaviors of the passengers are abnormal;
during signal transmission, preprocessing the acquired signals comprises signal amplification, filtering and digital-to-analog conversion;
during signal processing, the process of processing the uploaded signals and judging whether the behaviors of passengers are abnormal comprises the following steps:
fitting the uploaded signals to obtain a fitting curve;
extracting features of the fitting curve to obtain peak-to-peak values and root mean square values of the fitting curve, carrying out weighting treatment on the normalized feature values of different signals, and solving fitness functions of the different signals;
comparing the fitness function of the same signal with a set self-adaptive threshold value, and judging whether the behavior of the passenger is abnormal or not according to a comparison result;
fitness functionHThe following are provided:
wherein,and->Respectively representing the normalized root mean square value and peak-to-peak value; />The normalized energy percent value of the frequency band; />、/>Respectively different weight values, and +.>；/>Is a set adaptive threshold.
2. The multipoint distributed passenger abnormal behavior elevator monitoring method according to claim 1, wherein the sensor comprises a triaxial accelerometer, a uniaxial accelerometer, a noise sensor, a microwave radar and a pyroelectric infrared sensor, wherein the triaxial accelerometer, the uniaxial accelerometer, the noise sensor, the microwave radar and the pyroelectric infrared sensor are all connected with the data acquisition module, and all the data acquisition modules are connected with the controller;
the triaxial accelerometer is arranged at the center of the bottom of the elevator car and is used for monitoring three-way acceleration and three attitude angles of the elevator car;
the single-axis accelerometers are arranged on three wall surfaces of the elevator car wall, the car door and the bottom of the car, and are used for monitoring impact acceleration values at all positions in real time;
the noise sensor is arranged in the center of the top of the elevator car and used for monitoring the sound signals in the elevator car in real time;
the microwave radar is arranged at the top of the elevator car and the car wall and is used for monitoring the respiratory rate of passengers in real time;
the pyroelectric infrared sensor is arranged at the top of the elevator car and used for monitoring infrared signals in the elevator car in real time and judging whether passengers and the number of passengers exist in the elevator car.
3. A multipoint distributed passenger abnormal behavior elevator monitoring method according to claim 2, wherein the pyroelectric infrared sensor is installed at the top of the elevator car and irradiates downwards in a cone shape with an irradiation angle of 60 ° -70 °.
4. The method for monitoring the abnormal passenger behavior elevator according to claim 1, wherein the data acquisition module comprises an operational amplifier, a sampling holder, a filter, a digital-to-analog converter and an Ethernet port which are connected in sequence; the operational amplifier is connected with the sensor, and the Ethernet port is connected with the controller.
5. The method for monitoring the abnormal behavior of the passengers according to claim 1, wherein the controller adopts a DSP logic controller, and an external program and a data memory are arranged in the DSP logic controller, and the data memory can temporarily store collected data.
6. The method for monitoring the abnormal passenger behavior elevator according to claim 1, wherein the remote data transmitter comprises a power management module, a wireless transmission module, a singlechip controller and a surfing module; the wireless transmission module, the singlechip controller and the internet surfing module are all connected with the power management module, the wireless transmission module and the internet surfing module are both connected with the singlechip controller, the internet surfing module is connected with the controller, and the wireless transmission module is in wireless connection with the data intermediate station.
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| CN202211566964.3A CN116177337B (en) | 2022-12-07 | 2022-12-07 | Multi-point distributed elevator monitoring system and method for abnormal passenger behaviors |
| GBGB2313871.2A GB202313871D0 (en) | 2022-12-07 | 2023-09-12 | A multi point distributed elevator monitoring system and method for abnormal passenger behavior |
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| CN117236352B (en) * | 2023-09-08 | 2024-05-03 | 安徽沐达科技有限公司 | RFID sensor for vibration monitoring |
Citations (7)
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| JP2004149287A (en) * | 2002-10-31 | 2004-05-27 | Toshiba Elevator Co Ltd | Crime prevention system for elevator |
| JP2011236036A (en) * | 2010-05-12 | 2011-11-24 | Toshiba Elevator Co Ltd | Reporting system for abnormality in elevator cage |
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| JP2019172430A (en) * | 2018-03-28 | 2019-10-10 | フジテック株式会社 | elevator |
| CN114436087A (en) * | 2022-02-15 | 2022-05-06 | 浙江新再灵科技股份有限公司 | Elevator passenger door-opening detection method and system based on deep learning |
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- 2022-12-07 CN CN202211566964.3A patent/CN116177337B/en active Active
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- 2023-09-12 GB GBGB2313871.2A patent/GB202313871D0/en not_active Ceased
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| JP2004149287A (en) * | 2002-10-31 | 2004-05-27 | Toshiba Elevator Co Ltd | Crime prevention system for elevator |
| JP2011236036A (en) * | 2010-05-12 | 2011-11-24 | Toshiba Elevator Co Ltd | Reporting system for abnormality in elevator cage |
| CN105347127A (en) * | 2014-08-19 | 2016-02-24 | 三菱电机上海机电电梯有限公司 | Monitoring system and monitoring method for abnormal condition in elevator car |
| CN106608570A (en) * | 2015-10-20 | 2017-05-03 | 昆山通博电梯有限公司 | Lift abnormality early-warning, supervising and querying system |
| CN108382940A (en) * | 2018-03-16 | 2018-08-10 | 深圳市敢为特种设备物联网技术有限公司 | Lift running safety monitoring method, equipment and readable storage medium storing program for executing |
| JP2019172430A (en) * | 2018-03-28 | 2019-10-10 | フジテック株式会社 | elevator |
| CN114436087A (en) * | 2022-02-15 | 2022-05-06 | 浙江新再灵科技股份有限公司 | Elevator passenger door-opening detection method and system based on deep learning |
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| Publication number | Publication date |
|---|---|
| GB202313871D0 (en) | 2023-10-25 |
| CN116177337A (en) | 2023-05-30 |
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