7169results about "Elevators" patented technology

The invention relates to the technical field of elevator equipment state monitoring and fault diagnosis, and discloses an elevator traction machine running state real-time diagnosis method and system based on high-frequency sampling. According to the method, vibration (larger than or equal to 20 kHz), current (larger than or equal to 10 kHz), sound / sound emission, temperature and rotating speed signals of a traction machine are synchronously collected through a high-frequency multi-mode sensor array; capturing early weak fault transient characteristics; the edge computing unit completes data preprocessing, time synchronization, feature extraction and anomaly detection, and uploads key data to a cloud end through cloud-edge collaboration; the cloud end adopts a working condition self-adaptive strategy and a multi-modal fusion model to carry out deep diagnosis, and outputs fault types, positions and grades; and combining incremental learning and a degradation model to realize health quantification and residual life prediction. Through fusion of high-frequency data capture and an intelligent algorithm, the early fault detection capability, variable working condition adaptability and diagnosis real-time performance of the traction machine are improved, and a solution is provided for predictive maintenance of an elevator.

The invention relates to the technical field of elevator control and fault diagnosis, and discloses an elevator inverter fault pre-diagnosis and fault-tolerant control system and method based on digital twinning, and the system comprises a high-fidelity digital twinning body building module which is used for building a digital twinning body of an elevator inverter, the digital twin integrates an electric-thermal-stress coupling model, a device-level aging model, a parasitic parameter influence model and a driving circuit and protection logic model; wherein the electric-thermal-stress coupling model is used for simulating loss, junction temperature fluctuation and thermal stress circulation of a power device, and the device-level aging model is used for representing a time-varying degradation rule of device parameters. Through deep fusion of a digital twin technology, fault diagnosis and fault-tolerant control, a closed-loop system of'perception-pre-diagnosis-decision-control 'is constructed, the safety, reliability and economical efficiency of the elevator inverter are comprehensively improved, and the method has important significance in promoting transformation of the elevator industry to intelligent and unmanned maintenance.

The invention discloses a multi-elevator linkage dynamic response intelligent scheduling system and a scheduling method thereof. The scheduling method comprises the following steps: acquiring an operation rule of an elevator, constructing a historical operation database and updating the historical operation database in real time; capturing a field state in real time through a monitoring system, and generating a real-time data stream according to a time sequence; a digital twinborn model is constructed through a historical database and real-time data flow, and the elevator calling probability and the congestion risk of each floor are predicted; the elevator calling probability of each floor in the next five minutes is predicted based on a digital twinborn model, the congestion risk is calculated, a real-time demand thermodynamic diagram fusing the space-time sequence dimension is generated, and intelligent scheduling is conducted on the elevator through the thermodynamic diagram; by reducing the waiting time, the overall operation efficiency is improved, the user satisfaction is enhanced, and smoother vertical traffic experience is provided for high-rise buildings.

The application relates to the technical field of robots, and discloses a robot repositioning method and a robot, the robot repositioning method comprising the following steps: determining a current floor where the robot is located according to a test signal emitted by an elevator car at a stop floor; obtaining an environment map corresponding to the current floor; and determining the position of the robot on the current floor based on the environment map. The current floor is determined through the test signal emitted by the elevator car, the environment map corresponding to the current floor is obtained, and repositioning is completed through the environment map, so that the problem of repositioning failure of the robot when the robot is squeezed out of the elevator car is solved, and the positioning efficiency of the robot is improved.

The invention relates to an elevator fault real-time monitoring and early warning method, system and terminal, and belongs to the technical field of elevator monitoring. The monitoring and early warning method comprises the steps that multi-source sensing data of an elevator are collected, and timestamp synchronization is conducted on the multi-source sensing data; calculating a comprehensive risk value of the elevator based on the multi-source sensing data after timestamp synchronization; judging whether the comprehensive risk value is greater than a risk threshold value or not; if yes, Granger causal test is operated, an abnormal causal event is searched for from a pre-constructed causal graph, and relevant data corresponding to the abnormal causal event is packaged and sent to the elevator digital twinborn body; fault acceleration simulation is carried out in the digital twinborn body, and an abnormal root is positioned; and a health assessment report of the elevator is generated according to the simulation process data and the abnormal root. The method has the beneficial effects that the actual running state of the elevator is truly reflected, so that the running safety and reliability of the elevator are improved.

The invention discloses an elevator energy-saving control system based on a conversion module, which relates to the field of elevator control and comprises a battery module, the conversion module and an energy-saving control module, the battery module is connected with at least one elevator; the AC side of the conversion module is connected with commercial power, and the DC side of the conversion module is connected with the battery module; the energy-saving control module is connected with the battery module, and the energy-saving control module is in communication connection with the battery module and the conversion module. The stable operation of the elevator is guaranteed, the electricity utilization economical efficiency of the elevator is effectively improved, and the electricity utilization cost is reduced.

The invention discloses an information input system, comprising an operation screen which is composed of a plurality of single bodies and is used for receiving an input operation which is implemented by an input person to implement information input, and the single bodies are minimum units capable of identifying the input operation; the detection part is used for detecting the operated condition of the single body and outputting a detection result, and the detection result comprises the position information of the single body and a detection signal representing the operated condition of the single body; a processing unit for processing the detection result of the detection unit and outputting an operation point of an input operation by an input person; and a determination unit for determining input information corresponding to the operation point. The information input system can accurately register and input information for passengers at low cost.

The invention provides an elevator steel wire rope detection method and device, equipment and a storage medium, and belongs to the technical field of automatic monitoring. The method comprises the steps that electromagnetic signal data in a steel wire rope and vibration signal data of the end of the steel wire rope are obtained; performing feature extraction on the electromagnetic signal data and the vibration signal data to obtain electromagnetic noise features and vibration noise features; performing cross fusion on the electromagnetic noise feature and the vibration noise feature to obtain a first joint noise feature; performing denoising processing on the electromagnetic signal data and the vibration signal data based on the first joint noise feature to obtain denoised electromagnetic signal data and denoised vibration signal data; and performing fault prediction based on the denoised electromagnetic signal data and the denoised vibration signal data to obtain fault information of the steel wire rope. According to the elevator steel wire rope detection method and device, the equipment and the storage medium, the elevator steel wire rope fault detection precision can be improved.

The invention discloses an elevator steel wire rope detection device and method, and the device comprises the following steps: firstly, carrying out the pre-scanning of an initial magnetic field, then carrying out the magnetization of a steel wire rope through a multi-stage adjustable electromagnet, and controlling the magnetization intensity through a current; the method comprises the following steps: firstly, pre-scanning a magnetic field, then, carrying out real-time monitoring and feedback control on the magnetized magnetic field, carrying out synchronous acquisition through a multi-modal sensor, then, extracting multi-domain features, receiving a feature vector set by a model, carrying out dynamic weighting operation on the feature vector set, and finally, outputting a task. The problem that initial magnetic fields of the steel wire ropes are inconsistent can be effectively solved, data are synchronously collected through the multi-mode sensor, effective distinguishing and quantitative evaluation of different types of defects such as wire breakage, abrasion, corrosion and fatigue damage are achieved, and the defects of an existing detection mode in defect subdivision and quantification are overcome.

The invention provides an elevator intelligent operation and maintenance management method and system based on a multi-modal neural network, and relates to the technical field of operation and maintenance management. The method comprises the steps that 1, multi-source time sequence monitoring data are collected, the multi-modal neural network is constructed, the multi-source time sequence monitoring data are input into the multi-modal neural network, and the multi-source time sequence monitoring data are input into the multi-modal neural network; obtaining a vibration feature vector, an acoustic feature vector and a visual feature vector; 2, inputting the vibration feature vector, the acoustic feature vector and the visual feature vector into a cross-modal feature fusion layer in a multi-modal neural network for fusion, and generating a multi-modal joint feature vector; through multi-modal feature fusion of multi-source time sequence monitoring data, multi-dimensional health state representation modeling and fusion weight dynamic adjustment driven by data reliability evaluation, the accuracy of elevator fault diagnosis and the reasonability of maintenance decision are effectively improved, and the improvement of elevator intelligent operation and maintenance precision and efficiency is achieved.

The invention relates to the technical field of elevator group control, in particular to an elevator group control method and system based on deep learning, and the method comprises the steps: building an elevator taking behavior time sequence data set through collecting historical elevator taking behavior data and combining with an elevator calling request and the number of people waiting for an elevator obtained through image recognition; the elevator taking frequency, the elevator calling interval and the passenger number fluctuation are modeled by adopting a long-short-term memory network, passenger flow periodical characteristics in workdays, holidays and peak periods are extracted, the passenger flow of each floor in the future is predicted, and pre-scheduling deployment of idle elevators is completed in advance. In the scheduling stage, state input containing the elevator running state and predicted flow is constructed, a reinforcement learning model is introduced for strategy optimization, a reward function is constructed based on passenger waiting time, response timeout and the service completion number, a scheduling strategy is driven to continuously converge, elevator response distribution is optimized, and position presetting and path adjustment are preset. And the scheduling intelligence and the service efficiency are improved.

The invention discloses an elevator steel wire rope wear real-time monitoring system and equipment thereof, and relates to the technical field of safety monitoring, the elevator steel wire rope wear real-time monitoring system comprises an acquisition and extraction module which acquires real-time surface image data and vibration signal data of a steel wire rope through a sensor array, extracts surface damage features and vibration spectrum features by adopting an image processing algorithm, and sends the surface damage features and the vibration spectrum features to a server; fusing kernel function selection and hyperplane separation to process the preliminary wear feature set; the crack identification module is used for fusing tensile strength and corrosion resistance data in the material characteristic database according to the initial wear characteristic set, classifying potential fatigue crack types through support vector identification and crack morphological characteristics by adopting a support vector machine algorithm, and determining a fatigue crack distribution diagram; according to the elevator steel wire rope abrasion real-time monitoring system and equipment thereof, accurate abrasion evaluation and dynamic maintenance optimization are achieved, the safety of the steel wire rope is improved, and the service life of the steel wire rope is prolonged.

The present invention discloses a traction machine with dual motors and an assembly method thereof, belonging to the technical field of traction machines. The traction machine includes a traction wheel, a main rotating shaft, two supporting bodies, and two sets of motor assemblies. The two supporting bodies are respectively arranged at both ends of the traction wheel, one motor assembly is installed between the first end of the traction wheel and one of the supporting bodies, and the other motor assembly is installed between the second end of the traction wheel and the other supporting body. The two supporting bodies are respectively sleeved on both ends of the main rotating shaft, and the main rotating shaft and the supporting bodies rotate in coordination. The traction wheel is sleeved outside the main rotating shaft and fixed to the main rotating shaft. The two supporting bodies are symmetrically arranged relative to the center of the main rotating shaft, and the traction wheel is symmetrically arranged relative to the center of the main rotating shaft. When the traction machine is in operation, the forces acting on the two supporting bodies are consistent, the bearing capacity of the traction machine is more uniform, and the dynamic balance of the traction machine is achieved.

The invention relates to the technical field of elevator fault diagnosis, and discloses an elevator fault diagnosis method and system.The elevator fault diagnosis method comprises the steps that elevator operation data are collected, operation stages are divided for the elevator operation process according to the elevator operation data, and the residual error of the elevator operation data is calculated in the operation stages; based on an elevator structure, a causal chain graph reflecting the relation between components is established through fault mode analysis, and a direct upstream node set of downstream nodes in the causal chain graph serves as a parent set of the downstream nodes; in the operation stage, performing block replacement processing for keeping time sequence characteristics on an upstream node residual sequence of each edge in the causal chain graph to generate a contrast residual sequence, and calculating the propagation intensity of the edge according to the contrast residual sequence; effective propagation paths are screened according to the propagation intensity of the edges, the effective propagation paths are sorted to obtain candidate nodes, residual errors of the candidate nodes are set to be zero through virtual pinch-off, forward propagation is carried out through a semi-physical model, and fault nodes are determined in the candidate nodes based on forward propagation results.

An elevator energy-saving control system of a direct feed network relates to the technical field of elevator energy-saving control, and comprises an energy conversion module for converting kinetic energy and gravitational potential energy generated during operation of an elevator car into direct current; the control system module monitors elevator running state data and power grid parameters in real time, judges whether the elevator is in a power generation state or not according to a monitoring result, automatically starts an energy feedback mode and controls starting and stopping of energy feedback and power adjustment; the inversion grid-connected module is used for converting the direct current into alternating current, processing the generated alternating current and feeding back the electric energy in the form of the processed alternating current to a power grid; and the man-machine interaction module is used for receiving data information of the control system in real time and converting the data information into visual display content, so that a worker can master the operation condition of the system in time and deal with abnormal problems. The elevator running energy consumption is remarkably reduced, the running cost is reduced, meanwhile, the service life of equipment is prolonged, the stability of the equipment is improved, and the influence on the environment is reduced.

The invention discloses an elevator state monitoring method and device and a computer readable storage medium. The method comprises the steps that video data and audio data collected by image collection equipment in the elevator running process are obtained; performing vibration analysis on the video data to obtain time sequence vibration data, and performing abnormal sound analysis on the audio data to obtain time sequence abnormal sound data; performing weighted fusion on the time sequence vibration data and the time sequence abnormal sound data by using an attention mechanism to obtain time sequence fusion data; and the time sequence fusion data are input into a state monitoring model, the state monitoring model is used for conducting state evaluation on the time sequence fusion data, and a time sequence health score of the elevator in the running process is obtained. The technical problems that in the related technology, due to the fact that a single sensor is adopted, it is difficult to synchronously monitor possible faults of an elevator from multiple angles, the monitoring result is inaccurate, and extra hardware cost is likely to be increased are solved.

A charger assembly 10 for charging an energy storage unit associated with an elevator is provided. The charger assembly includes a first charger unit 20 mechanically coupled to an elevator column 30. The first charger unit is adapted to tap voltage from a power source. The first charger unit interconnects a first block 40 and a second block 50. The first block includes at least two slots 60 adapted to interlock with at least two projections 70 provided on the second block. The charger assembly also includes a second charger unit 80 electrically coupled with the first charger unit and mounted on a guide bracket 90 associated with a cabin of the elevator. The second charger unit includes a plurality of pins 100 adapted to receive the voltage tapped by the first charger unit to charge the energy storage unit associated with the elevator.

The invention discloses an elevator energy-saving control system, which comprises a battery module comprising Y battery packs connected in parallel, each battery pack is formed by connecting X battery cells in series, and the battery module is respectively connected with N elevators through an elevator independent interface module; the energy-saving control module is used for receiving the respective corresponding use states of the N elevators in communication connection in real time, determining the state of a battery cell in the battery module, and generating a control signal for controlling the communication state of the elevator independent interface module according to the respective corresponding use states of the N elevators and the state of the battery cell in the battery module; and the elevator independent interface module is used for receiving the control signal of the energy-saving control module and controlling connection or disconnection between the battery module and the N elevators according to the control signal, so that one or more elevators reversely charge the battery module / the battery module supplies power to one or more elevators or forbids the battery module from supplying power to any elevator. According to the system, the electricity utilization economy of the elevator is improved, and the electricity utilization cost is reduced.

The invention relates to the technical field of elevator operation and maintenance, and discloses a multi-source data fusion method and system for elevator fault localization, and the method comprises the steps: carrying out the noise filtering and data alignment of multi-source monitoring data of an elevator during operation, and obtaining a monitoring data set; performing time-frequency analysis on acceleration sensor data in the monitoring data set to obtain vibration mode characteristics; performing harmonic analysis on the motor current data to obtain current distortion characteristics; performing space-time correlation on the vibration mode characteristics, the current distortion characteristics and the safety loop state in the monitoring data set to obtain a comprehensive fault characteristic vector; according to the comprehensive fault feature vector, specific components and types when the elevator breaks down are determined, so that fault positioning information is obtained; the fault positioning information is transmitted to an elevator monitoring terminal, and the elevator is maintained according to the fault positioning information; according to the invention, the fault positioning efficiency can be improved.

The invention relates to a method for monitoring jamming or synchronism of a main engine brake of a vertical elevator, and aims to monitor and diagnose the jamming or synchronism state of the elevator brake in real time through the combination of an acceleration sensor and an electromagnetic signal. The method comprises the steps that acceleration sensors are installed on the two brake component sides of the elevator brake, vibration acceleration signals of the two brake components are collected, or the response time difference between the action vibration acceleration signals and voltage signals of the brakes on the two sides is calculated through time sequence analysis through a vibration switch with an adjustable threshold value and by means of the single-chip microcomputer technology; and the action response time difference of different brake components is determined. If the time difference exceeds the preset threshold value, it is judged that the brake is jammed or has an asynchronous fault. And finally, according to a conjoint analysis result of the vibration acceleration signal and the voltage signal, accurate diagnosis and real-time early warning of brake jamming or synchronization faults are provided. According to the method, the detection precision and response speed of elevator brake jamming or asynchronous faults can be improved, and reliable guarantee is provided for safe operation of an elevator.

The invention discloses an elevator operation and maintenance full-life-cycle fault monitoring and diagnosing method and system, and relates to the technical field of data analysis, and the method comprises the following steps: collecting fault action data of known elevator component parts, and establishing an elevator component part fault tree map; marking a historical operation process instruction of the target elevator equipment, analyzing the matching between the historical operation process instruction and the assembled building, and evaluating the current state of each component of the target elevator equipment; running data of all parts of the real-time target elevator equipment are obtained, similar fault screening is conducted on the running data and the known elevator component fault tree atlas, an undetermined fault set of all the parts of the real-time target elevator equipment is obtained, an elevator part-fault confidence coefficient function is established, and fault types of all the parts of the target elevator equipment are generated. The method has the advantages that the fault early recognition capability and the fault diagnosis accuracy are improved, the fault processing time is shortened, and the reliability of elevator equipment is improved.

The invention relates to the technical field of elevator safety monitoring, in particular to a fault early warning method based on an intelligent elevator. The fault early warning method comprises the steps that multi-dimensional operation parameters of a target elevator are obtained; multi-modal fusion is conducted on the vibration signal component, the noise signal component, the equipment static attribute data and the working condition environment data, and a health degree evaluation matrix of elevator operation is generated through a space-time attention encoder; according to the health degree evaluation matrix, a preset historical fault knowledge base is combined, the dynamic fault probability is calculated through a Bayesian inference model, and the early warning grade is generated. A historical fault knowledge base and a Bayesian inference model are further combined, a self-adaptive maintenance strategy triggered according to an early warning level from static threshold value alarm to dynamic fault probability prediction is realized, on-demand accurate maintenance is realized, and the maintenance efficiency and the resource utilization rate are improved.

The invention discloses an elevator for construction, and relates to the technical field of equipment for building construction, all guide wheels are installed on a suspension cage, all the guide wheels are located between the suspension cage and a guide rail pipe of a tower body standard knot, the guide wheels are located on the periphery of the guide rail pipe, the guide wheels are used for clamping the guide rail pipe, and a left compartment and a right compartment which are communicated with each other are arranged in the suspension cage; the left compartment and the right compartment are located on the left side and the right side of the tower body standard knot correspondingly and are symmetrically arranged, the adjusting plate is installed on the side, away from a building, of the tower body standard knot and is parallel to the construction surface of the building, and the upper end of the adjusting plate is hinged to an upper top frame at the upper end of the lifting cage. The lower end of the adjusting plate is detachably connected to a lower bottom frame at the lower end of the cage and can be adjusted and fixed at different front and back positions, so that the cage can be adjusted at different angles relative to a tower body standard knot. Construction of building inclined planes with different inclination angles can be achieved, the application range is wide, and the use safety is high.

The invention discloses an elevator energy-saving control system based on an auxiliary power supply module, which relates to the field of elevator energy-saving control and comprises a battery module, the auxiliary power supply module and an energy-saving control module, the battery module is connected with a circuit breaker, the circuit breaker is connected with at least one contactor set used for being connected with at least one elevator in a one-to-one correspondence mode, the same bypass contactor is connected between the circuit breaker and all the contactor sets, and the bypass contactor is connected with an anti-reverse diode in parallel. The mains supply and the battery module are respectively connected with the auxiliary power supply module; the auxiliary power supply module is connected with the energy-saving control module; and the energy-saving control module is respectively in communication connection with the circuit breaker, the contactor group, the bypass contactor, the battery module and the auxiliary power supply module. The charging and discharging energy balance of the battery module can be realized, and the problems of conversion electric quantity loss and high cost caused by the use of a conversion module are avoided.

The invention relates to the technical field of elevator safety monitoring, and discloses an elevator safety detection system based on vision and multi-modal data fusion, comprising: a data preprocessing module for collecting and preprocessing original multi-modal sensor data of elevator operation; the feature extraction module is used for identifying operation conditions and extracting multi-scale features for different conditions; the multi-modal fusion module is used for calculating the reliability coefficient of each modal and carrying out adaptive fusion; the anomaly detection module is used for extracting transient characteristics of working condition switching, carrying out anomaly judgment and mining an anomaly evolution trend; the sample enhancement module is used for extracting normal samples and rare fault samples, generating synthetic samples and performing quality screening; the model construction module is used for training a multi-level fault identifier and fusing a multi-modal feature library to carry out optimization learning; the intelligent early warning module is used for calculating a safety level and reasoning a fault reason and a disposal measure; accurate dynamic safety monitoring of the super high-rise building elevator under the extreme load switching working condition is achieved.

The invention discloses a telescopic elevator door knife assembly which is movably connected to a door machine hanging plate, the door knife assembly comprises a door knife bottom plate and a door knife blade, a fixing support is arranged on the door machine hanging plate, a fixing shaft is arranged at the end, away from the door machine hanging plate, of the fixing support, the fixing shaft extends towards the door knife bottom plate, and the door knife blade is arranged on the door knife bottom plate. The fixing shaft is sleeved with a telescopic spring, and the door vane bottom plate is provided with an opening allowing the fixing shaft to pass through and allowing the telescopic spring not to pass through. A rotating arm and an unlocking deflector rod are arranged on the side, back on to the telescopic spring, of the door knife assembly, a pushing and pressing part making contact with the door machine bottom plate is arranged at one end of the rotating arm, and the unlocking deflector rod is used for poking the rotating arm to enable the pushing and pressing part to extrude the door knife assembly, so that the distance between the door knife assembly and the door machine hanging plate is increased. According to the telescopic elevator door knife assembly, no matter which direction an elevator moves, the door knife blade can be prevented from colliding with the door ball, the telescopic elevator door knife assembly is suitable for an inclined elevator, and operation is safer and more reliable.

The invention discloses an elevator door motor system anomaly detection and prediction method, and relates to the technical field of elevator door motor anomaly detection.The elevator door motor system anomaly detection and prediction method comprises the steps of S1, multi-dimensional data collection, S2, operation feature extraction, S3, dynamic benchmark establishment, S4, abnormal feature recognition and S5, fault type and confidence coefficient output. According to the method, the operation cycle of the elevator door motor system is automatically divided, the defects in the prior art are overcome, a plurality of pieces of detection data in the operation cycle are accurately divided, and the value of fault prediction of the follow-up door motor system is ensured; according to the method, the dynamic reference range curve in which each characteristic parameter is associated with the operation times of the portal crane is established, so that the fault prediction accuracy of the portal crane system is improved, the false alarm rate of the portal crane system is reduced, and maintenance resources are saved to a certain extent.

The utility model discloses a traction machine rack and an elevator and belongs to the technical field of elevators, and the traction machine rack comprises a bearing assembly, a supporting assembly and a support assembly. The bearing assembly is composed of two bases arranged in parallel, a first bearing beam, a second bearing beam and a middle beam. The two ends of the first bearing beam are connected with one ends of the two bases, the two ends of the second bearing beam are connected with the other ends of the bases, the first bearing beam and the second bearing beam are arranged in parallel, and the two ends of the middle beam are connected with the ends, close to the bases, of the first bearing beam and the second bearing beam respectively. The supporting assembly comprises a first supporting beam and a second supporting beam, the two ends of the first supporting beam are connected with the first bearing beam and the middle beam respectively, and the two ends of the second supporting beam are connected with the first bearing beam and the second bearing beam respectively. The two ends of the support assembly are connected with the first supporting beam and the second supporting beam correspondingly, and a traction machine installation position is arranged on the surface of the side, away from the middle beam, of the support assembly and close to the second supporting beam. The running stability of the elevator can be improved.

The invention relates to the technical field of elevator safety monitoring, and discloses an elevator guide rail abrasion online monitoring and deep learning early warning system. The system comprises an active excitation multi-mode sensing end and a causal inference residual network analysis engine, and the analysis engine compares multi-physical field response data collected in real time with a theoretical health response signal under a current working condition based on a health response baseline model trained under a health state; the method comprises the steps that firstly, a multi-dimensional residual signal capable of separating working condition interference is generated, then, a system executes online self-calibration of a cross-modal sensor through physical constraints contained in a model, the effectiveness of the signal is judged, finally, the effective residual signal is input into a causal inference network, and the specific reason of guide rail abrasion is recognized and traced. The technical problem that the monitoring result is unreliable due to working condition interference, unknown abrasion reasons and sensor faults is solved, and high-precision, traceable and high-reliability online monitoring and early warning of elevator guide rail abrasion are achieved.

The invention relates to the technical field of elevators, in particular to an elevator traction machine vibration reconstruction method and system based on a millimeter wave radar. The method comprises the steps that in the elevator running process, echo signals of a millimeter wave radar are collected; firstly, a continuous phase sequence is obtained through echo signals; generating a rough vibration signal in a radar sight line direction according to a phase-displacement mapping relation, calculating a physical confidence coefficient, constructing a dual-channel physical prior tensor, synthesizing a three-axis reconstruction vibration signal tensor by using a PGGN physical gating generation network, and finally performing physical rationality evaluation on the three-axis reconstruction vibration signal tensor. And adjusting the gating parameters of the anisotropic physical gating unit according to the evaluation result. On the premise that a contact sensor does not need to be installed on the surface of the traction machine for a long time, physical consistency reconstruction of the three-axis vibration signals of the elevator traction machine is achieved.