CN115246609B - Elevator safety prevention and control cloud platform and running state evaluation and processing method - Google Patents

Abstract

The invention discloses an elevator safety prevention and control cloud platform and an operation state evaluation and processing method, wherein the elevator safety prevention and control cloud platform comprises an acquisition terminal, a background server and a remote prevention and control website, wherein the acquisition terminal is used for acquiring original elevator data and uploading the original elevator data to the background server; the remote control website is used for a user to remotely log in so as to access a background server and monitor the running state of the elevator; the background server is used for analyzing and processing the original elevator data so as to judge faults, predict the faults, generate maintenance strategies and respond to the remote prevention and control websites. The elevator operation state can be monitored in real time, fault prediction and health management can be carried out on the elevator operation state, and the problems of low supervision efficiency and fault data loss in elevator safety prevention and control are solved.

Description

Elevator safety control cloud platform and operation status evaluation and processing method

Technical Field

The present invention relates to the technical field of elevator safety control, and in particular to an elevator safety control cloud platform and an operating status evaluation and processing method.

Background Art

The traditional maintenance method of regular door-to-door maintenance and telephone notification when a fault occurs has become increasingly unable to adapt to the needs of the times, mainly due to the following reasons: ① The number of elevators has increased, and the number of elevators that maintenance personnel and supervisors are responsible for has increased, and the traditional supervision model is inefficient; ② The lack of daily operation test data increases the difficulty of fault analysis and troubleshooting, and also delays the timely elimination of elevator faults, increasing the safety hazards of elevator use. ③ The existing maintenance method cannot achieve maintenance according to the situation, which is easy to cause problems such as insufficient maintenance and excessive maintenance.

Summary of the invention

In order to overcome the deficiencies of the above technologies, the present invention provides an elevator safety control cloud platform and an operation status evaluation and processing method, which can realize real-time monitoring of the elevator operation status and perform fault prediction and health management on it, and solve the problems of low supervision efficiency and missing fault data in elevator safety control.

In order to achieve the purpose of the present invention, in the first aspect, an elevator safety control cloud platform proposed by the present invention at least includes an acquisition terminal, a background server and a remote control website, wherein the acquisition terminal is used to collect original elevator data and upload the original elevator data to the background server; the remote control website is used for users to log in remotely, thereby accessing the background server and monitoring the elevator operation status; the background server is used to analyze and process the original elevator data, thereby performing fault judgment, fault prediction, generating maintenance strategies, and responding to the remote control website; wherein the background server includes a data processing module for storing and forwarding original elevator data, a real-time monitoring module for responding to the remote control website to view the elevator operation status in real time, and a receiving data processing module to forward the original A statistical analysis module for elevator data; the statistical analysis module includes an elevator fault diagnosis unit, an equipment health status unit and a safety prevention and control strategy unit. The elevator fault diagnosis unit is used to analyze the original elevator data and monitor the elevator working status based on the original elevator data. If the elevator is not working properly, the location and extent of the elevator fault are determined based on the abnormal part of the monitored original elevator data; the equipment health status unit at least includes a life prediction model, which is used to input the original elevator data into the life prediction model and predict the performance degradation trend of important elevator components, and compare it with the preventive maintenance threshold, so as to predict the remaining life of the elevator components; the safety prevention and control strategy unit is used to formulate an elevator maintenance plan based on the location and extent of the elevator fault and the remaining life of the elevator components.

Furthermore, the background server also includes a fault alarm module, which is used to send an alarm message to the elevator management personnel based on the elevator fault detected by the elevator fault diagnosis unit or the elevator fault predicted by the equipment health status unit to occur with a probability greater than a preset time period.

Furthermore, the backend server also includes a system management module, which includes a permission management submodule and an information management submodule, wherein the permission management submodule is used to divide user accounts into a system administrator account for maintaining the backend server and performing permission control on other accounts, a unit administrator account for accessing the backend server, and an elevator maintenance technician account for binding elevator equipment; the information management submodule includes an elevator basic information management submodule for managing elevators accessed to the backend server, a manufacturer information management submodule for managing the manufacturers of elevators accessed to the backend server, and a maintenance unit information management submodule for managing the basic information of maintenance units involved in maintenance work.

Furthermore, the background server also includes a real-time monitoring module, which is used for at least video monitoring, equipment operation status monitoring and equipment health status functions, wherein video monitoring at least includes viewing the internal situation of the elevator car in real time on a remote monitoring website through a network camera; equipment operation status monitoring at least includes real-time display of elevator operation data on a remote prevention and control website; the equipment health status function at least includes scoring the health status of the elevator in combination with the fault prediction results of each elevator component, the elevator maintenance data and the basic operation data of the elevator, thereby evaluating the health status of the elevator in real time.

Furthermore, the statistical analysis module also includes a historical data statistical unit, which is used to collect statistics on the historical data of the elevator and intuitively reflect the usage intensity and potential high-value information of the elevator based on the statistics of the historical data of the elevator.

Among them, potential high-value information refers to the use of data mining technology to extract some deep-level information, such as the failure frequency of elevators, easily damaged parts, etc., to help improve the design and optimize the spare parts storage strategy.

Furthermore, the acquisition terminal at least includes a data acquisition module, a data transmission module, an offline analysis module and a fault alarm module. The data acquisition module is used to collect sensor data, control cabinet data and maintenance data, wherein the data acquisition module reads the control cabinet data through an interface; the data transmission module is used to upload the data collected by the data acquisition module to the background server through communication; the offline analysis module is used to perform fault diagnosis and life prediction in an offline state, and upload the analysis results to the background server in an online state; the fault alarm module is used to send alarm information to the management personnel based on the analysis results of the offline analysis module.

Furthermore, the sensor data includes at least the relative creep between the traction wheel groove and the wire rope, the braking distance of the brake wheel during emergency stop, the three-phase current of the traction motor, the door machine current, the three-way acceleration of the car, the car sound and video images, the control cabinet data includes at least the elevator speed, door status and running direction, and the maintenance data includes at least biweekly inspection records, quarterly inspection records, semi-annual inspection records, annual inspection records and fault information.

Furthermore, the remote control website is also used to remotely log in to the backend server based on the browser, so as to display the statistical analysis results through the web page and uniformly manage the elevator equipment.

The remote control website is based on the B/S (Browser/Server) architecture. Users can remotely log in to the security control cloud platform to manage the device without downloading the client and directly access the server using a browser.

In a third aspect, the present invention provides a method for evaluating and processing an operation status, which specifically includes:

S1, the acquisition terminal collects the original elevator data and uploads it to the background server; S2, the background server verifies the validity of the original elevator data, and forwards the verified original elevator data to the elevator fault diagnosis unit and the equipment health status unit, and trains the fault diagnosis model and the life prediction model of the equipment health status unit based on the data of the elevator fault diagnosis unit, and performs fault diagnosis and life prediction respectively; S3, the fault diagnosis results and life prediction results are judged as a whole, and the judgment results are compared with the fault standard to determine whether the elevator is faulty and the location and degree of the elevator fault; S4, if the elevator has failed, an alarm message is sent to the elevator manager and S6 is executed, otherwise S5 is executed; S5, if the elevator has failed, an alarm message is sent to the elevator manager and S6 is executed, otherwise S5 is executed; If the elevator is in normal operation and the performance degradation degree of any key component reaches its corresponding preventive maintenance threshold and the failure probability is greater than the preset time period, an elevator maintenance strategy is formulated, and maintenance tasks are produced and pushed to the elevator management personnel, otherwise no maintenance is performed; S6, the data that does not reach the preventive maintenance threshold is added to the database as normal data, and the data that reaches the preventive maintenance threshold or the failure threshold is temporarily saved and waits for the maintenance personnel to feedback. If the feedback result of the maintenance personnel is consistent with the temporarily saved data, the data is taken as preventive maintenance data or failure data and added to the database for optimizing data training fault diagnosis model or life prediction model, otherwise the data is discarded.

The beneficial effects of the present invention are:

1. Remotely log in to the remote access website of the elevator safety control cloud platform through a browser to remotely monitor the elevator operation status without installing special client software, thus lowering the threshold for monitoring elevators;

2. Real-time monitoring of the operating status of elevators within the jurisdiction, intuitively grasping the health status of elevators. The same number of people can supervise more elevators, while reducing the labor intensity of elevator supervisors;

3. By analyzing the collected data, the elevator fault can be diagnosed, the fault location and fault degree of the elevator can be predicted, and guidance can be provided for maintenance personnel to carry out maintenance work;

4. Combined with the data collected by sensors, the life of elevator-related components can be predicted, and maintenance can be performed when the components reach the preventive maintenance threshold to avoid sudden failure and major consequences.

5. The detection information and fault prediction results of each elevator can be scored, and a reasonable maintenance strategy can be formulated to effectively reduce the labor intensity of maintenance personnel and truly achieve "one elevator, one policy";

6. It realizes the real-time, efficient and extensive collection of elevator data, can analyze the historical data of elevators, mine valuable elevator information, and provide reference for elevator design and improvement.

7. After the detected fault or preventive maintenance data is confirmed on site by the maintenance personnel, it can be used as effective data to participate in the optimization of the model of the fault diagnosis and life prediction module, which is conducive to improving the accuracy of the model prediction.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a schematic diagram of the architecture of an elevator safety control cloud platform according to an embodiment of the present invention;

FIG2 is a functional structure block diagram of a collection terminal according to an embodiment of the present invention;

FIG3 is a diagram showing the type of data collected by a data collection module according to an embodiment of the present invention;

FIG4 is a schematic diagram of a collection method corresponding to the collected original elevator data according to an embodiment of the present invention;

FIG5 is a functional block diagram of a backend server according to an embodiment of the present invention;

FIG6 is a functional block diagram of a real-time monitoring module according to an embodiment of the present invention;

FIG7 is a functional structure diagram of a statistical analysis module according to an embodiment of the present invention;

FIG8 is a diagram showing the account function distribution of the system management module according to an embodiment of the present invention;

9 is a functional structure diagram of an information management module according to an embodiment of the present invention;

FIG10 is a schematic diagram of the hierarchical architecture of an elevator safety control cloud platform according to an embodiment of the present invention;

FIG. 11 is a flow chart of an elevator operation status evaluation and processing method according to an embodiment of the present invention.

DETAILED DESCRIPTION

In order to facilitate those skilled in the art to better understand the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. The following is only exemplary and does not limit the protection scope of the present invention.

Example 1

As shown in FIG1 , it is a schematic diagram of an elevator safety control cloud platform architecture according to an embodiment of the present invention. The elevator safety control cloud platform is described below in conjunction with specific embodiments.

The elevator safety control cloud platform can include collection terminals, background servers and remote control websites.

The acquisition terminal is used to collect original elevator data and upload the original elevator data to the background server. For example, the acquisition terminal collects original elevator data such as elevator speed, door status, and running direction in the elevator control cabinet through the interface, and uploads the collected original elevator data to the background server.

The acquisition terminal is based on a C/S (Client/Server) architecture and can be divided into four modules: a data acquisition module, a data transmission module, an offline analysis module, and a fault alarm module. As shown in FIG2 , it is a structural diagram of an acquisition terminal according to an embodiment of the present invention.

The data collected by the data acquisition module can be divided into three categories, as shown in Figure 3, including sensor data, control cabinet data and maintenance data. Sensor data can use different sensors or monitoring devices according to the different types of data collected. As shown in Figure 4, the sensor data collection volume and the corresponding collection method. For example, the acceleration sensor is used to collect the three-way acceleration of the car, and the current transformer is used to directly measure the three-phase current of the traction motor. The elevator control cabinet contains a large number of parameters required for the operation of the equipment, namely the control cabinet data. For example, the elevator speed, door status, and running direction, the data acquisition terminal can directly read the control cabinet data through the relevant interface. Maintenance data refers to the maintenance record form filled out by the maintenance personnel, including biweekly inspections, quarterly inspections, semi-annual inspections, annual inspections, and fault information.

The data transmission module uploads the collected data to the background server and can use wireless or wired network to transmit the data.

The offline analysis module can perform fault diagnosis and life prediction in an offline state. When the network is restored, that is, in an online state, it will upload the analysis data and results to the background server. Among them, the fault diagnosis function is to analyze the collected original fault data in combination with machine learning or artificial intelligence algorithms to determine the location and severity of the fault. The life prediction function is to predict the performance degradation trend of important elevator components by inputting real-time data collected during normal operation of the elevator into the life prediction model, and compare it with the preventive maintenance threshold to predict the remaining life of the components.

The fault alarm module refers to the offline analysis module that prompts the elevator management personnel to handle the problem in a timely manner when a fault is detected, for example, by ringing a bell or other means.

The backend server is used to analyze and process the original elevator data, so as to make fault judgment, fault prediction, generate maintenance strategies, and respond to remote prevention and control websites. As shown in Figure 5, it is a functional structure diagram of the backend server, which can be divided into five different modules according to its functions: data processing module, real-time monitoring module, statistical analysis module, fault alarm module and system management module.

The data processing module of the backend server mainly stores and forwards data, reduces the degree of coupling between the various functional modules of the backend server, and provides data support and backup for the services between the backend server and the collection terminal and the remote login website. Commonly used database systems include MySQL, Oracle, etc.

The functional structure diagram of the real-time monitoring module of the background server is shown in Figure 6, which includes video monitoring function, equipment operation status monitoring function and equipment health status function. The video monitoring function refers to the real-time viewing of the internal situation of the elevator car on the remote monitoring website through a network camera; the equipment operation status monitoring function refers to the real-time display of the elevator operation data on the remote monitoring website, including the current speed of the elevator, door opening and closing conditions, and stop floors; the equipment health status refers to the combination of the fault prediction results of each component, equipment maintenance data and basic operation data. The three aspects of information are scored for the health status of the elevator, and the health status of the equipment is evaluated in real time, which is convenient for supervisors to grasp the overall health status of the elevator.

The statistical analysis module of the background server includes an elevator fault diagnosis unit, an equipment health status unit, a safety prevention and control strategy unit and a historical data statistics unit. Its functional structure block diagram is shown in FIG7 .

When the elevator fault diagnosis unit analyzes the original elevator data collected by the collection terminal, if it detects that the elevator status indicator is abnormal and the elevator is in an abnormal working state, the faulty component can be inferred based on the analysis module to which the corresponding abnormal status indicator belongs; by comparing the abnormal indicator value with the corresponding fault threshold, the extent of the fault can be determined.

The equipment health status unit at least includes a life prediction model, which is used to input the real-time data collected during the normal operation of the elevator into the life prediction model, predict the performance degradation trend of important elevator components, and compare it with the preventive maintenance threshold to predict the remaining life of the components. The safety control strategy unit refers to the cloud platform, based on the results of the real-time data analysis of the equipment, reasonably arranges the maintenance intervals and intensity of each component, and generates maintenance tasks, which are pushed to maintenance personnel and supervisors. The strategies for minor repairs, major repairs and replacements of equipment parts increase the degree of recovery of equipment performance. Historical data statistics refer to the statistical historical data of the elevator, which intuitively reflects the usage intensity and potential high-value information of the elevator, including the number of elevator operations, the number of door openings and closings, the number of fault warnings, etc.

The fault alarm module of the background server means that when an elevator fault is detected or it is predicted that there is a high probability of a fault in the near future, the cloud platform will send detailed alarm information to the management personnel through text messages for disposal.

The system management module of the backend server can be divided into the authority management submodule and the information management submodule according to different functions. Among them, the authority management submodule divides users into system administrator accounts, unit administrator accounts and elevator maintenance personnel accounts according to their functions. The functional distribution of each account is shown in Figure 8. The system administrator account has the highest authority and is used to maintain the backend server of the cloud platform and control the authority of subordinate accounts. The unit administrator account is owned by the unit that accesses the elevator safety prevention and control cloud platform. It is a secondary account of the system administrator account. It can monitor the elevators in the jurisdiction in real time by logging in to the remote monitoring website, including viewing statistical information, managing elevator equipment, real-time monitoring of elevators and alarm processing. It should be noted that this account cannot access elevator equipment across jurisdictions. The elevator maintenance personnel account is owned by the elevator maintenance personnel and is a secondary account of the system administrator account. Each elevator equipment can be bound to an elevator maintenance personnel account. The maintenance personnel can view the elevator operation data and register maintenance information.

The information management module can be divided into the elevator basic information management submodule, the manufacturer information management submodule and the maintenance unit information management submodule according to the different information sources. Its functional structure diagram is shown in Figure 9. The elevator basic information management submodule is mainly used to manage elevators connected to the cloud platform, such as elevator information details, elevator information editing and map display. The manufacturer information management submodule is mainly used to manage the basic information of the manufacturer of the access equipment, such as manufacturer information statistics, manufacturer information query, manufacturer information editing and other functions. The maintenance unit information management submodule is mainly used to manage the basic information of the maintenance units involved in the maintenance work, such as maintenance unit details, maintenance unit query, maintenance unit editing and other functions.

The remote control website is based on the B/S (Browser/Server) architecture. Users can remotely log in to the security control cloud platform to manage the equipment without downloading the client. They can directly access the server using a browser. The main function of the remote control website is data visualization. It displays statistical analysis results through web pages and manages the elevator equipment in the jurisdiction in a unified manner.

Example 2

As shown in Figure 10, it is a schematic diagram of the hierarchical architecture of an elevator safety control cloud platform according to an embodiment of the present invention. The elevator safety control cloud platform is described below in conjunction with a specific embodiment. The elevator safety control cloud platform shown in Figure 10 is divided into five layers from bottom to top according to the flow of data, namely, data acquisition layer, network layer, data persistence layer, business layer and application layer. The data acquisition layer uses the acquisition terminal to upload the collected real-time data to the data persistence layer through the network layer; the data persistence layer stores and forwards the original data from the data acquisition layer, and provides data support for the business layer services; the business layer analyzes and processes the elevator data, and provides users with real-time monitoring, statistical analysis, fault alarm and system management services; the application layer mainly uses visualization technology to realize human-computer interaction, and users remotely log in to the cloud platform system through a browser to manage the elevator.

Example 3

As shown in Figure 11, this is a flow chart of the operation status evaluation and processing method based on the elevator safety control cloud platform. The operation status evaluation and processing method will be described in detail in conjunction with the flow chart.

S1, according to the schematic diagram of the collection method corresponding to the original elevator data shown in FIG4, corresponding sensors are installed at relevant parts of the elevator, and the data such as the relative creep between the traction wheel groove and the wire rope, the braking distance of the brake wheel during emergency stop, the three-phase current of the traction motor, the door machine current, the three-way acceleration of the car, and the car sound are measured by the collection terminal and uploaded to the background server;

S2, the data processing module of the background server performs simple preprocessing on the original collected data, verifies the validity of the data, and then forwards it to the corresponding elevator fault diagnosis unit and equipment health status unit for fault diagnosis and life prediction.

S3, using relevant comprehensive algorithms to make an overall evaluation of the fault diagnosis results and life prediction results, and comparing the evaluation results with the fault standard, so as to determine whether the elevator is faulty and determine the location and degree of the elevator fault;

S4, if the elevator has failed, the elevator safety prevention and control cloud platform in the embodiment of the present invention will start the fault alarm module, notify the supervisor of the elevator to handle it, and transfer to S6, otherwise transfer to S5;

S5. If the analysis results show that the elevator is still in normal operation, but the performance degradation of some key components has reached the preventive maintenance threshold, and the probability of failure within the preset time period is greater than the preset probability, that is, there is a greater probability of failure in a short period of time in the future, then it is necessary to formulate a maintenance strategy for the elevator, generate detailed maintenance tasks, and push them to the supervisor and maintenance personnel of the elevator, otherwise no maintenance will be performed.

S6, data that does not meet the preventive maintenance conditions will be marked as normal data and added to the historical database of the elevator. Data that meets the preventive maintenance or fault conditions will be temporarily stored, waiting for feedback from maintenance personnel. If the feedback results show that the diagnosis/prediction results are correct, the data will be marked as preventive maintenance data or fault data and added to the historical database of the elevator to optimize the fault diagnosis/prediction model, otherwise it will be discarded.

In short, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims (8)

1. The elevator safety prevention and control cloud platform is characterized by at least comprising an acquisition terminal, a background server and a remote prevention and control website,

The acquisition terminal is used for acquiring original elevator data and uploading the original elevator data to the background server; the original data at least comprises sensor data, control cabinet data and maintenance data, wherein the sensor data at least comprises relative creep amount between a traction sheave groove and a steel wire rope, braking distance of a braking wheel during sudden stop, three-phase current of a traction motor, door motor current, three-way acceleration of a lift car, sound of the lift car and video pictures; the control cabinet data at least comprises elevator speed, door state and running direction; the maintenance data at least comprises a semi-month check record, a quarter check record, a semi-year check record, a year check record and fault information;

the remote control website is used for a user to remotely log in so as to access a background server and monitor the running state of the elevator;

The background server is used for analyzing and processing the original elevator data so as to judge faults and predict the faults, generating maintenance strategies and responding to a remote prevention and control website;

The background server comprises a data processing module for storing and forwarding original elevator data, a real-time monitoring module for responding to a remote control website to check the elevator running condition in real time, and a statistical analysis module for receiving the original elevator data forwarded by the data processing module;

The statistical analysis module comprises an elevator fault diagnosis unit, a device health state unit and a safety prevention and control strategy unit,

The elevator fault diagnosis unit is used for analyzing the original elevator data, monitoring the working state of the elevator based on the original elevator data, and judging the position and degree of elevator fault occurrence based on the abnormal part of the monitored original elevator data if the elevator works abnormally;

the equipment health state unit at least comprises a life prediction model, is used for inputting the original elevator data into the life prediction model and predicting the performance degradation trend of important elevator components, and is compared with a preventive maintenance threshold value so as to predict the residual life of the elevator components;

The safety protection and control strategy unit is used for formulating a maintenance scheme of the elevator based on the position and degree of the fault sent by the elevator and the residual life of the elevator components.

2. The elevator safety prevention and control cloud platform of claim 1, wherein the background server further comprises a fault alarm module for sending an alarm message to an elevator manager based on an elevator fault detected by the elevator fault diagnosis unit or an elevator fault predicted by the equipment health status unit to occur within a preset time period with a probability greater than a preset probability.

3. The elevator security prevention and control cloud platform of claim 1, wherein the background server further comprises a system management module comprising a rights management sub-module and an information management sub-module, wherein the rights management sub-module is configured to divide a user account into a system administrator account for maintaining the background server and performing rights control on other accounts, a unit administrator account for accessing the background server, and an elevator maintenance attendant account for binding an elevator installation;

The information management submodule comprises an elevator basic information management submodule for managing the elevator accessed to the background server, a manufacturer information management submodule for managing manufacturers of the elevator accessed to the background server, and a maintenance unit information management submodule for managing basic information of maintenance units participating in maintenance work.

4. The elevator safety prevention and control cloud platform of claim 1, wherein the background server further comprises a real-time monitoring module at least for video monitoring, equipment running state monitoring and equipment health state functions, wherein video monitoring at least comprises real-time viewing of an elevator car interior condition at a remote monitoring website through a webcam; the equipment running state monitoring at least comprises the step of displaying elevator running data on a remote prevention and control website in real time; the equipment health status function at least comprises scoring the health status of the elevator by combining the fault prediction result of each component of the elevator, the elevator maintenance data and the elevator basic operation data, so that the health status of the elevator is estimated in real time.

5. The elevator safety prevention and control cloud platform of claim 1, wherein the statistical analysis module further comprises a historical data statistics unit for counting elevator historical data and visually reflecting the use intensity and potential high value information of the elevator based on the counted elevator historical data.

6. The elevator safety prevention and control cloud platform of claim 1, wherein the acquisition terminal comprises at least a data acquisition module, a data transmission module, an offline analysis module and a fault alert module,

The data acquisition module is used for acquiring sensor data, control cabinet data and maintenance data, wherein the data acquisition module reads the control cabinet data through an interface;

the data transmission module is used for uploading the data acquired by the data acquisition module to the background server in a communication mode;

The offline analysis module is used for carrying out fault diagnosis and life prediction in an offline state and uploading an analysis result to the background server in an online state;

The fault alarm module is used for sending alarm information to management personnel based on the analysis result of the offline analysis module.

7. The elevator security prevention and control cloud platform of claim 1, wherein the remote prevention and control website is further configured to remotely log into a background server based on a browser, thereby uniformly managing elevator equipment by displaying statistical analysis results through web pages.

8. An operation state evaluation and processing method based on the elevator safety prevention and control cloud platform according to any one of claims 1 to 7, which is characterized by comprising the following steps:

s1, an acquisition terminal acquires original elevator data and uploads the original elevator data to a background server;

S2, the background server verifies the validity of the original elevator data, and forwards the verified original elevator data to an elevator fault diagnosis unit and a device health state unit, and a fault diagnosis model and a life prediction model of the device health state unit are trained based on the data of the elevator fault diagnosis unit to respectively conduct fault diagnosis and life prediction;

S3, integrally judging the fault diagnosis result and the life prediction result, and comparing the judgment result with a fault standard so as to judge whether the elevator is faulty or not and judge the fault position and degree of the elevator;

S4, if the elevator has failed, sending alarm information to elevator management personnel, executing S6, otherwise executing S5;

s5, if the elevator is in a normal running state, the performance degradation degree of any key component reaches a corresponding preventive maintenance threshold value and fails within a preset time period more than a preset probability, an elevator maintenance strategy is formulated, maintenance tasks are produced and pushed to elevator management staff, and otherwise maintenance is not performed;

and S6, adding the data which does not reach the preventive maintenance threshold value as normal data into a database, temporarily storing the data which reaches the preventive maintenance threshold value or the fault threshold value, waiting for feedback of maintenance personnel, taking the data as preventive maintenance data or fault data if the feedback result of the maintenance personnel is consistent with the temporarily stored data, adding the data into the database for optimizing the data training fault diagnosis model or the service life prediction model, and otherwise discarding the data.