CN115246609A - Elevator safety prevention and control cloud platform and operation state evaluation and processing method - Google Patents
Elevator safety prevention and control cloud platform and operation state evaluation and processing method Download PDFInfo
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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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- 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
- B66B5/0018—Devices monitoring the operating condition of the elevator system
- B66B5/0025—Devices monitoring the operating condition of the elevator system for maintenance or repair
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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
- B66B5/0018—Devices monitoring the operating condition of the elevator system
- B66B5/0031—Devices monitoring the operating condition of the elevator system for safety reasons
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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
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 prevention and control website is used for a user to log in remotely, so as to access the 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 and predict faults and generate a maintenance strategy, and is used for responding to a remote prevention and control website. The elevator safety monitoring system can monitor the running state of the elevator in real time, carry out fault prediction and health management on the running state of the elevator, and solve the problems of low supervision efficiency and fault data loss existing in elevator safety prevention and control.
Description
Technical Field
The invention relates to the technical field of elevator safety prevention and control, in particular to an elevator safety prevention and control cloud platform and an operation state evaluation and processing method.
Background
The traditional maintenance mode of regular home maintenance and fault calling notification is increasingly unable to meet the requirement of the development of the era, mainly due to the following reasons: (1) the number of elevators is increased, more and more elevators are charged by maintenance personnel and supervision personnel, and the traditional supervision mode is low in efficiency; (2) the lack of daily operation detection data increases the difficulty of fault analysis and elimination, delays the timely elimination of elevator faults and increases the potential safety hazard of elevator use. (3) The existing maintenance mode cannot realize maintenance according to the conditions, and easily causes the problems of insufficient maintenance, excessive maintenance and the like.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides the elevator safety prevention and control cloud platform and the operation state evaluation and processing method, which can realize real-time monitoring of the operation state of the elevator and fault prediction and health management of the elevator, solve the problems of low supervision efficiency and fault data loss of the elevator safety prevention and control,
in order to achieve the purpose of the invention, in a first aspect, the elevator safety prevention and control cloud platform provided by the invention at least 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 prevention and control website is used for a user to remotely log in so as to access the 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 and predict faults, generate maintenance strategies and respond 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 prevention and control website to check the running condition of the elevator 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, an equipment health state unit and a safety prevention and control strategy unit, wherein the elevator fault diagnosis unit is used for analyzing original elevator data, monitoring the working state of the elevator based on the original elevator data, and judging the position and degree of the 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, a service life prediction model and a service life prediction model, wherein the life prediction model is used for inputting original elevator data into the life prediction model, predicting the performance degradation trend of important components of the elevator and comparing the performance degradation trend with a preventive maintenance threshold value so as to predict the residual life of the elevator components; the safety control strategy unit is used for establishing a maintenance scheme of the elevator based on the position and the degree of the fault sent by the elevator and the residual service life of the elevator components.
Further, the background server further comprises a fault alarm module, which is used for sending alarm information to an elevator manager when an elevator fault occurs within a preset time period and is more than a preset probability based on the elevator fault detected by the elevator fault diagnosis unit or the elevator fault predicted by the equipment health state unit.
The background server further comprises a system management module, wherein the system management module comprises a permission management submodule and an information management submodule, wherein the permission management submodule is used for dividing the user account into a system administrator account for maintaining the background server and performing permission control on other accounts, a unit administrator account for accessing the background server and an elevator maintenance maintainer account for binding elevator equipment; the information management submodule comprises an elevator basic information management submodule for managing an elevator accessed to the background server, a manufacturer information management submodule for managing an elevator manufacturer accessed to the background server, and a maintenance unit information management submodule for managing basic information of a maintenance unit participating in maintenance work.
Furthermore, the background server also comprises a real-time monitoring module, wherein the real-time monitoring module is at least used for video monitoring, equipment running state monitoring and equipment health state functions, and the video monitoring at least comprises the step of watching the internal condition of the elevator car in real time through a network camera on a remote monitoring website; the equipment running state monitoring at least comprises the real-time display of elevator running data on a remote prevention and control website; the equipment health state function at least comprises the step of scoring the health state of the elevator by combining fault prediction results of all parts of the elevator, elevator maintenance data and elevator basic operation data, so that the health state of the elevator is evaluated in real time.
Furthermore, the statistical analysis module also comprises a historical data statistical unit, and the historical data statistical unit is used for counting the historical data of the elevator and visually reflecting the use intensity and the potential high-value information of the elevator based on the statistical historical data of the elevator.
The potential high-value information is that data mining technology is used to extract some deep-level information, such as failure frequency of an elevator, fragile components and the like, so as to help improve design and optimize a spare part storage strategy.
Furthermore, the acquisition terminal at least comprises a data acquisition module, a data transmission module, an off-line analysis module and a fault alarm module, wherein the data acquisition module is used for acquiring sensor data, control cabinet data and maintenance data, and 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 off-line analysis module is used for carrying out fault diagnosis and service life prediction in an off-line state and uploading an analysis result to the background server in an on-line state; and the fault alarm module is used for sending alarm information to a manager based on the analysis result of the offline analysis module.
Furthermore, the sensor data at least comprises the relative creep amount between the traction wheel groove and the steel wire rope, the braking distance of the brake wheel during emergency stop, the three-phase current of the traction motor, the current of the door motor, the three-way acceleration of the car, the sound and the video picture of the car, the control cabinet data at least comprises the speed of the elevator, the state and the running direction of the door, and the maintenance data at least comprises a half-month check record, a quarter check record, a half-year check record, an annual check record and fault information.
Furthermore, the remote prevention and control website is also used for remotely logging in a background server based on a browser, so that the elevator equipment is uniformly managed by displaying statistical analysis results through a webpage.
The remote prevention and control website is based on a B/S (Browser/Server) architecture, a user can remotely log in a security prevention and control cloud platform to manage the equipment, a client does not need to be downloaded, and a Browser is used for directly accessing the Server.
In a third aspect, the present invention provides a method for evaluating and processing an operating state, which specifically includes:
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, forwards the verified original elevator data to an elevator fault diagnosis unit and an equipment health state unit, trains a fault diagnosis model and a service life prediction model of the equipment health state unit based on the data of the elevator fault diagnosis unit, and respectively performs fault diagnosis and service life prediction; s3, performing overall judgment on the fault diagnosis result and the service life prediction result, and comparing the judgment result with a fault standard so as to judge whether the elevator is in fault and judge the fault position and degree of the elevator; s4, if the elevator fails, sending alarm information to an elevator manager, and 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 a fault occurs within a preset time period which is greater than a preset probability, an elevator maintenance strategy is formulated, maintenance tasks are produced and pushed to an elevator manager, and otherwise, maintenance is not carried out; and S6, adding the data which do not reach the preventive maintenance threshold value into a database as normal data, temporarily storing the data which reach the preventive maintenance threshold value or the fault threshold value, waiting for the 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, and adding the data into the database for optimizing a data training fault diagnosis model or a life prediction model, otherwise discarding the data.
The invention has the beneficial effects that:
1. the remote access website of the elevator safety prevention and control cloud platform is remotely logged in through the browser, so that the running state of the elevator is remotely monitored, special client software does not need to be installed, and the threshold of monitoring and managing the elevator is reduced;
2. the running state of the elevators in the jurisdiction is monitored in real time, the health state of the elevators is intuitively mastered, more elevators can be supervised by the same number of people, and the labor intensity of elevator supervision personnel is reduced;
3. the elevator can be subjected to fault diagnosis by analyzing the acquired data, the fault position and the fault degree of the elevator are predicted, and guidance is provided for maintenance personnel to perform maintenance operation;
4. the service life of related parts of the elevator can be predicted by combining data acquired by the sensor, and the parts are maintained when reaching a preventive maintenance threshold value, so that serious consequences caused by sudden failure of the parts are avoided.
5. The method can score the detection information and the fault prediction result of each elevator, reasonably make a maintenance strategy, effectively reduce the labor intensity of maintenance personnel and really achieve 'one elevator one strategy';
6. the real-time, efficient and wide acquisition of elevator data is realized, the historical data of the elevator can be analyzed, valuable elevator information is mined, and reference is provided for elevator design and improvement.
7. The detected failure or preventive maintenance data can be used as effective data to participate in the optimization of the model of the failure diagnosis and service life prediction module after being confirmed on site by maintenance personnel, and the accuracy of model prediction can be improved.
Drawings
Fig. 1 is a schematic diagram of an elevator security control cloud platform architecture according to an embodiment of the invention;
FIG. 2 is a functional structure block diagram of an acquisition terminal according to an embodiment of the present invention;
FIG. 3 illustrates data types collected by the data collection module according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a corresponding acquisition method of acquired original elevator data according to an embodiment of the present invention;
FIG. 5 is a functional block diagram of a background server according to an embodiment of the present invention;
FIG. 6 is a functional block diagram of a real-time monitoring module according to an embodiment of the present invention;
FIG. 7 is a functional block diagram of a statistical analysis module according to an embodiment of the present invention;
fig. 8 is an account function distribution diagram of a system management module according to an embodiment of the present invention;
FIG. 9 is a functional block diagram of an information management module according to an embodiment of the present invention;
fig. 10 is a schematic diagram of a hierarchical architecture of an elevator security control cloud platform according to an embodiment of the present invention;
fig. 11 is a flow chart of an elevator running state evaluation and processing method according to an embodiment of the invention.
Detailed Description
In order to facilitate a better understanding of the invention for those skilled in the art, the invention will be described in further detail with reference to the accompanying drawings and specific examples, which are given by way of illustration only and do not limit the scope of the invention.
Example 1
As shown in fig. 1, which is a schematic view of an elevator security control cloud platform architecture according to an embodiment of the present invention, the elevator security control cloud platform will be described with reference to specific embodiments.
The elevator safety prevention and control cloud platform can comprise 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. For example: the acquisition terminal acquires original elevator data such as elevator speed, door state and running direction in the elevator control cabinet through the interface and uploads the acquired 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: the device comprises a data acquisition module, a data transmission module, an off-line analysis module and a fault warning module. Fig. 2 is a structural diagram of an acquisition terminal according to an embodiment of the present invention.
The data collected by the data collection module can be divided into three types, as shown in fig. 3, including sensor data, control cabinet data and maintenance data. The sensor data may be different depending on the type of data it is collected, and different sensors or monitoring devices may be used. As shown in fig. 4, the sensor data acquisition amount and the corresponding acquisition method are shown. For example, the three-way acceleration of the car is acquired by an acceleration sensor, and the three-phase current of the traction motor is directly measured by a current transformer. The elevator control cabinet contains a large number of parameters, i.e. control cabinet data, which are required for the operation of the equipment. Such as elevator speed, door state, direction of travel, data acquisition terminal can directly read control cabinet data through the relevant interface. The maintenance data refers to a maintenance record table filled by a maintenance worker, and comprises semi-monthly inspection, quarterly inspection, semi-annual inspection, annual inspection and fault information.
The data transmission module uploads the acquired data to the background server, and the data can be transmitted by using a wireless or wired network.
The off-line analysis module can carry out fault diagnosis and service life prediction in an off-line state, and when the network is recovered, namely in an on-line state, the engine searching module uploads analysis data and results to the background server. The fault diagnosis function is to analyze the collected original fault data by combining machine learning or artificial intelligence algorithm and judge the position and severity of the fault. The service life prediction function is used for predicting the performance degradation trend of important components of the elevator by inputting real-time data acquired during normal operation of the elevator into the service life prediction model, and comparing the performance degradation trend with a preventive maintenance threshold value to predict the residual service life of the components.
The fault warning module is used for prompting an elevator manager to process in time when the offline analysis module detects a fault, for example, prompting the manager to process in time by using a ringing mode and the like.
The background server is used for analyzing and processing the original elevator data so as to judge and predict faults and generate a maintenance strategy, and is used for responding to a remote prevention and control website. As shown in fig. 5, the functional structure block diagram of the background server is divided into five different modules according to different functions: the system comprises a data processing module, a real-time monitoring module, a statistical analysis module, a fault warning module and a system management module.
The data processing module of the background server mainly stores and forwards data, reduces the coupling degree among all functional modules of the background server, and provides data support and backup for services among the background server, the acquisition terminal and the remote login website, wherein common database systems comprise MySQL, oracle and the like.
A functional structure block diagram of a real-time monitoring module of the background server is shown in fig. 6, and comprises a video monitoring function, an equipment running state monitoring function and an equipment health state function, wherein the video monitoring function refers to that the internal condition of the elevator car is watched in real time in a remote monitoring website through a network camera; the equipment running state monitoring function means that the running data of the elevator is displayed on a remote monitoring website in real time, and comprises the current speed of the elevator, the door opening and closing condition, the stop floor and the like; the equipment health state refers to that the health state of the elevator is scored by combining information of three aspects of fault prediction results of all parts, equipment maintenance data and basic operation data, the health state of the equipment is evaluated in real time, and a supervisor can conveniently master the whole health state of the elevator.
The statistical analysis module of the background server comprises an elevator fault diagnosis unit, an equipment health state unit, a safety prevention and control strategy unit and a historical data statistical unit, and the functional structure block diagram of the statistical analysis module is shown in fig. 7.
When the elevator fault diagnosis unit analyzes the original elevator data acquired by the acquisition terminal, if the state index of the elevator is abnormal and the elevator is in an abnormal working state, the component with the fault can be reversely deduced according to the analysis module to which the corresponding abnormal state index belongs; by comparing the abnormality index value with the corresponding failure threshold value, the degree of failure can be determined.
The equipment health state unit at least comprises a life prediction model which is used for inputting real-time data acquired when the elevator normally operates by the life prediction model, predicting the performance degradation trend of important parts of the elevator, and comparing the performance degradation trend with a preventive maintenance threshold value to predict the residual life of the parts. The security prevention and control strategy unit is used for reasonably arranging maintenance intervals and force of all parts according to the real-time data analysis result of the equipment by the cloud platform, generating a maintenance task and pushing the maintenance task to maintenance personnel and supervision personnel, wherein the recovery degree of small repair, large repair and replacement strategies of the equipment parts to the equipment performance is sequentially increased. The historical data statistics refers to the statistics of historical data of the elevator, and the use intensity and potential high-value information of the elevator are visually reflected, wherein the historical data comprises the operation times, the door opening and closing times, the failure early warning times and the like of the elevator.
The fault warning module of the background server is used for sending detailed warning information to a manager for disposal through short messages and the like when the elevator fault is detected or the fault is predicted to occur with high probability in a relatively short period of time.
The system management module of the background server can be divided into an authority management submodule and an information management submodule according to different functions. The authority management submodule divides the user into a system administrator account, a unit administrator account and an elevator maintenance maintainer account according to functions, and the functions of the accounts are distributed as shown in fig. 8. The system administrator account has the highest authority, is used for maintaining a background server of the cloud platform and controls the authority of the subordinate account. The unit administrator account is owned by a unit accessing the elevator safety prevention and control cloud platform, is a secondary account of a system administrator account, can supervise an elevator in a jurisdiction in real time by logging in a remote monitoring website, and comprises the steps of checking statistical information, managing elevator equipment, monitoring the elevator in real time, alarming, and the like, and the account can not access the elevator equipment across jurisdictions. The account number of the elevator maintenance maintainer is owned by the elevator maintenance maintainer and is a secondary account number of the account number of a system manager, each elevator device can be bound with one account number of the elevator maintenance maintainer, and the maintenance maintainer can check the operation data of the elevator and register maintenance information.
The information management module can be divided into an elevator basic information management submodule, a manufacturer information management submodule and a maintenance unit information management submodule according to different information sources, and a functional structure block diagram of the information management module is shown in fig. 9. The elevator basic information management submodule is mainly used for managing the elevator accessed to the cloud platform, and has functions of elevator information detail, elevator information editing, map display and the like. The manufacturer information management submodule is mainly used for managing the basic information of the manufacturer of the access equipment, and comprises the functions of manufacturer information statistics, manufacturer information inquiry, manufacturer information editing and the like. The maintenance unit information management sub-module mainly manages basic information of the maintenance units participating in the maintenance work, and has functions of maintenance unit details, maintenance unit query, maintenance unit editing and the like.
The remote prevention and control website is based on a B/S (Browser/Server) framework, a user can remotely log in the security prevention and control cloud platform to manage the equipment, a client does not need to be downloaded, and a Browser is used for directly accessing the Server. The remote prevention and control website mainly has the advantages that data visualization is achieved, and elevator equipment in the jurisdiction are managed in a unified mode through webpage display of statistical analysis results.
Example 2
Fig. 10 is a schematic view of a hierarchical architecture of an elevator security control cloud platform according to an embodiment of the present invention, and the elevator security control cloud platform is described below with reference to a specific embodiment. The elevator security prevention and control cloud platform shown in fig. 10 is divided into five layers from bottom to top according to the flow direction of data, namely a data acquisition layer, a network layer, a data persistence layer, a service layer and an application layer, wherein the data acquisition layer uploads acquired real-time data to the data persistence layer through the network layer by using an acquisition terminal; the data persistence layer stores and forwards original data from the data acquisition layer and provides data support for service of the service layer; the service layer analyzes and processes the elevator data and provides services such as real-time monitoring, statistical analysis, fault warning, system management and the like for users; the application layer mainly utilizes a visualization technology to realize human-computer interaction, and a user remotely logs in a cloud platform system through a browser to manage the elevator.
Example 3
As shown in fig. 11, a flowchart of an operation state evaluation and processing method based on an elevator security prevention and control cloud platform is shown, and the operation state evaluation and processing method will be described in detail below with reference to the flowchart.
S1, according to a schematic diagram of an acquisition method corresponding to original elevator data shown in FIG. 4, corresponding sensors are installed at relevant parts of an elevator, and data such as relative creep amount between a traction wheel groove and a steel wire rope, braking distance of a brake wheel during emergency stop, three-phase current of a traction motor, door motor current, car three-way acceleration, car sound and the like are respectively measured by using an acquisition terminal and are transmitted to a background server;
and S2, the data processing module of the background server simply preprocesses the originally acquired data, verifies the validity of the data, and forwards the data to the corresponding elevator fault diagnosis unit and the corresponding equipment health state unit for fault diagnosis and service life prediction.
S3, performing overall judgment on the fault diagnosis result and the service life prediction result by using a related comprehensive algorithm, and comparing the judgment result with a fault standard so as to judge whether the elevator is in fault and judge the fault position and degree of the elevator;
s4, if the elevator fails, the elevator safety prevention and control cloud platform in the embodiment of the invention starts a failure alarm module to inform a supervisor of the elevator to process, and goes to S6, otherwise, goes to S5;
and S5, if the analysis result shows that the elevator is still in a normal running state at present, but the performance degradation degree of part of key components reaches a preventive maintenance threshold value and the key components are in failure in a preset time period which is greater than a preset probability, namely the key components are in failure in a short period of time in the future, a maintenance strategy of the elevator needs to be formulated, a detailed maintenance task is generated and pushed to a supervisor and a maintenance worker of the elevator, otherwise, the elevator is not maintained.
And S6, marking the data which do not reach the preventive maintenance condition as normal data, and adding the normal data into the historical database of the elevator. Data that achieves a preventive maintenance or fault condition will be temporarily stored, waiting for feedback from maintenance personnel, and if the feedback indicates that the diagnostic/prognostic results are correct, the data will be marked as preventive maintenance data or fault data and added to the elevator's historical database to optimize the fault diagnostic/prognostic model, otherwise the data will be discarded.
In conclusion, the above description is only for the preferred embodiment of the present invention and should not be construed as limiting the present invention, and any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (9)
1. An 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 remote prevention and control website is used for a user to remotely log in so as to access the 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 and predict faults, generate maintenance strategies and respond 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 prevention and control website to check the running condition of the elevator 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, an equipment health state unit and a safety prevention and control strategy unit,
the elevator fault diagnosis unit is used for analyzing original elevator data, monitoring the working state of the elevator based on the original elevator data, and judging the position and degree of the elevator fault 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, a service life prediction model and a service life prediction model, wherein the life prediction model is used for inputting original elevator data into the life prediction model, predicting the performance degradation trend of important components of the elevator and comparing the performance degradation trend with a preventive maintenance threshold value so as to predict the residual life of the elevator components;
the safety control strategy unit is used for establishing a maintenance scheme of the elevator based on the position and the degree of the fault sent by the elevator and the residual service 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, and the fault alarm module is configured to send alarm information 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 state unit to occur within a preset time period and with a probability greater than a preset probability.
3. The elevator safety prevention and control cloud platform according to claim 1, wherein the background server further comprises a system management module, the system management module comprises a permission management submodule and an information management submodule, wherein the permission management submodule is used for dividing a user account into a system administrator account for maintaining the background server and performing permission control on other accounts, a unit administrator account for accessing the background server, and an elevator maintenance maintainer account for binding elevator equipment;
the information management submodule comprises an elevator basic information management submodule for managing an elevator accessed to the background server, a manufacturer information management submodule for managing an elevator manufacturer accessed to the background server, and a maintenance unit information management submodule for managing basic information of a maintenance unit 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, the real-time monitoring module is at least used for video monitoring, equipment running state monitoring and equipment health state functions, wherein the video monitoring at least comprises real-time observation of the internal condition of the elevator car through a network camera on a remote monitoring website; the equipment running state monitoring at least comprises the real-time display of elevator running data on a remote prevention and control website; the equipment health state function at least comprises the step of scoring the health state of the elevator by combining fault prediction results of all parts of the elevator, elevator maintenance data and elevator basic operation data so as to evaluate the health state of the elevator in real time.
5. The elevator safety prevention and control cloud platform according to claim 1, wherein the statistical analysis module further comprises a historical data statistical unit, and the historical data statistical unit is used for counting historical data of the elevator and visually reflecting the use intensity and the potential high-value information of the elevator based on the statistical historical data of the elevator.
6. The elevator safety prevention and control cloud platform of claim 1, wherein the collection terminal comprises at least a data collection module, a data transmission module, an offline analysis module and a fault alarm 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 off-line analysis module is used for performing fault diagnosis and service life prediction in an off-line state and uploading an analysis result to the background server in an on-line state;
and the fault alarm module is used for sending alarm information to a manager based on the analysis result of the offline analysis module.
7. The elevator safety prevention and control cloud platform of claim 6, wherein the sensor data comprises at least relative creep amount between a traction wheel groove and a steel wire rope, braking distance of a brake wheel at emergency stop, three-phase current of a traction motor, current of a door machine, three-way acceleration of a car, car sound and video pictures;
the control cabinet data includes at least elevator speed, door status and direction of travel;
the maintenance data at least comprises a half-month inspection record, a quarter inspection record, a half-year inspection record, an annual inspection record and fault information.
8. The elevator safety prevention and control cloud platform of claim 1, wherein the remote prevention and control website is further configured to log in to a background server remotely based on a browser, so that elevator equipment is managed uniformly by displaying statistical analysis results through a webpage.
9. The method for evaluating and processing the running state of the elevator safety prevention and control cloud platform is characterized by specifically comprising the following steps of:
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, forwards the verified original elevator data to an elevator fault diagnosis unit and an equipment health state unit, trains a fault diagnosis model and a service life prediction model of the equipment health state unit based on the data of the elevator fault diagnosis unit, and respectively carries out fault diagnosis and service life prediction;
s3, performing overall judgment on the fault diagnosis result and the service life prediction result, and comparing the judgment result with a fault standard so as to judge whether the elevator is in fault and judge the fault position and degree of the elevator;
s4, if the elevator is in failure, sending alarm information to an elevator manager, and 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 a fault occurs within a preset time period which is greater than a preset probability, an elevator maintenance strategy is formulated, maintenance tasks are produced and pushed to an elevator manager, and otherwise, maintenance is not carried out;
and S6, adding the data which do not reach the preventive maintenance threshold value into a database as normal data, temporarily storing the data which reach the preventive maintenance threshold value or the fault threshold value, waiting for the 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, and adding the data into the database for optimizing a data training fault diagnosis model or a life prediction model, otherwise discarding the data.
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