An elevator operation and maintenance management method and device based on a running scenario and a medium

Abstract

The application discloses an elevator operation and maintenance management method and device based on an operation scene, and a medium, and belongs to the field of elevator operation and maintenance management. The method comprises the following steps: collecting operation data in the operation process of an elevator, calculating the cosine similarity between a synchronous operation data vector and a standard operation data vector, and matching an elevator operation scene for the operation process of the elevator; obtaining a time period corresponding to the same elevator operation scene, and calculating the importance coefficient of different elevator operation scenes; collecting characteristic parameters of the health state of key components, and calculating the health degree; judging whether a fault occurs or not according to the corrected health degree, and starting an operation and maintenance task scheduling instruction; calculating the priority of the elevator operation and maintenance task scheduling, and performing elevator maintenance work. The device comprises a processor, a transceiver and a memory. The medium is used for storing a computer program. Task scheduling is performed based on the scene risk level and the fault prediction result, the average response time of high-risk faults is shortened, and operation and maintenance personnel are reasonably matched.

Description

Technical Field

[0001] This invention relates to the field of elevator operation and maintenance management, and specifically to an elevator operation and maintenance management method, equipment and medium based on operating scenarios. Background Technology

[0002] With the acceleration of urbanization, elevators, as an indispensable vertical transportation tool in high-rise buildings, are experiencing rapid and continuous growth in their number. Traditional elevator operation and maintenance mainly adopts a passive model of "regular maintenance + fault reporting." However, with the increase in the number of elevators, operation and maintenance management has become a major expenditure and cost for enterprises. Reasonable and efficient operation and maintenance management is also the key to ensuring the long-term and efficient operation of elevators.

[0003] In existing technologies, due to the lack of reasonable operation and maintenance management methods, over-maintenance and under-maintenance coexist. A uniform maintenance cycle cannot adapt to the actual operating intensity of different elevators, leading to over-maintenance of low-load elevators increasing costs, while under-maintenance of high-load elevators causes safety hazards. Furthermore, the varying impacts of different operating scenarios (such as morning peak heavy loads, nighttime empty loads, and renovation / transportation) on elevator component wear and failure modes are not considered. The scheduling of operation and maintenance tasks lacks dynamic assessment of scenario risk levels, resulting in untimely handling of high-risk faults and excessive resource consumption by low-risk tasks. Summary of the Invention

[0004] To address the aforementioned shortcomings of existing technologies, this invention provides an elevator operation and maintenance management method, equipment, and medium based on operational scenarios. This method deeply integrates scenario factors into elevator fault assessment, enabling precise and intelligent operation and maintenance management based on actual operational intensity and risk level.

[0005] To achieve the above-mentioned objectives, the technical solution adopted by this invention is as follows: An elevator operation and maintenance management method based on operational scenarios is provided, which includes: Step S1: Collect the operation data during the elevator operation process and preprocess it to obtain a continuous synchronous operation data vector sequence; calculate the cosine similarity between the synchronous operation data vector and the standard operation data vector based on the standard operation data vector of each elevator operation scenario, so as to match the elevator operation scenario for the elevator operation process. Step S2: Merge the same elevator operation scenarios with consecutive timestamps to obtain the time period corresponding to the same elevator operation scenario, calculate the failure rate of key components in each elevator operation scenario, and introduce the weights related to the price and maintenance time of key components to calculate the importance coefficient of different elevator operation scenarios. Step S3: Collect feature parameters reflecting the health status of each key component, calculate the health of each key component, and introduce the wear acceleration factor of key components under each elevator operation scenario to correct the health status and obtain the corrected health status. Step S4: Based on the corrected health status, calculate the comprehensive health index of the elevator, construct the covariate vector of key components in different elevator operation scenarios, calculate the risk rate of key components, determine whether key components in the elevator have malfunctioned, and initiate the operation and maintenance task scheduling instruction. Step S5: Calculate the priority of elevator maintenance task scheduling using the hazard rate and importance coefficient of key components, and match appropriate maintenance personnel according to the priority of each elevator maintenance task scheduling in the elevator maintenance management center to perform elevator maintenance work.

[0006] Furthermore, the operational data includes car vibration data, drive current, operating speed, car load, component temperature, door operator signal, number of door openings and closings, and operating time; the elevator's various operating scenarios include morning peak heavy load scenario, evening peak heavy load scenario, off-peak normal load scenario, nighttime empty load scenario, transport heavy load scenario, and fault precursor scenario.

[0007] Further, step S1 includes: Step S11: Collect elevator operation data during operation and input the operation data into the edge gateway for timestamping. t Alignment and packet loss interpolation are used to generate timestamps. t Corresponding synchronous running data vector This yields a continuous sequence of synchronized running data vectors. Step S12: Define the elevator operation scenario , k Number the elevator operation scenarios and construct each elevator operation scenario. Standard running data vector , N The amount of runtime data collected; Step S13: Calculate the synchronous running data vector With each elevator operation scenario Standard running data vector Cosine similarity between ; Step S14: Obtain the operating scenario for each type of elevator. Corresponding cosine similarity data , To synchronize the running data vector Elevator operation scenario Standard running data vector Calculate the cosine similarity between the pairs of pairs, sort them from largest to smallest, and then select the pair with the highest cosine similarity. The corresponding elevator operation scenario serves as the elevator's timestamp. t Matching elevator operation scenarios K This refers to the number of elevator operation scenarios.

[0008] Further, step S2 includes: Step S21: Based on the continuous synchronous running data vector sequence, convert the continuous timestamps... t By merging the same elevator operation scenarios, the time period corresponding to the elevator being in the same elevator operation scenario can be obtained; Step S22: Identify the key components for elevator maintenance and obtain the number of elevators operating in the same historical time period corresponding to the same elevator operation scenario. m Number of times a key component fails , m Assign numbers to key components and determine the cumulative operating time of the elevator in the same elevator operating scenario. Calculation of key components m Failure rate ; Step S23: Based on the price of each key component and the historical repair time of the malfunction Determine the weight of each key component ; Step S24: Based on the key components in different elevator operation scenarios m Failure rate and weight Calculate the importance coefficient of different elevator operation scenarios .

[0009] Further, step S3 includes: Step S31: Based on the fault-free operating time of each key component under ideal operating conditions Calculate the wear acceleration factor of key components under each elevator operation scenario. Construct the scenario loss factor matrix ; Step S32: Collect characteristic parameters reflecting the health status of each key component. According to the feature parameters Calculate the health status of each key component , u Number the feature parameters; Step S33: Introduce a loss acceleration factor Health of key components Dynamic adjustments are made to obtain the health status of key components after correction. .

[0010] Further, step S4 includes: Step S41: Based on the corrected health level Calculate the overall health index of elevators ; Step S42: Based on the importance coefficient of each key component in different elevator operating scenarios Health Construct a covariate vector based on the elevator's operating environment temperature and humidity to calculate the risk rate of critical components. ; The cumulative effective operating time after the installation of key components. This is the covariate vector after the key components are installed; Step S43: Set the hazard rate threshold for critical components ,like If the fault is found, it is determined that a critical component inside the elevator has malfunctioned, and the operation and maintenance task scheduling instruction is initiated to execute step S5; otherwise, it is determined that no critical component inside the elevator has malfunctioned.

[0011] Further, step S5 includes: Step S51: Utilize the hazard ratio of all malfunctioning critical components within the elevator. Importance coefficient of the elevator's current operating scenario Calculate the priority of elevator maintenance task scheduling ; q This is the number of the maintenance task currently initiated by the elevator maintenance management center; Step S52: Based on the elevator operation and maintenance management center's current startup... Q Each maintenance task, for Q Priority of each operation and maintenance task Sort the elevators from highest to lowest priority, and then sort them according to the qualifications of the currently available maintenance personnel in the elevator operation and maintenance management center, prioritizing the assignment of the most qualified maintenance personnel to the priority level. The biggest maintenance task is to perform elevator maintenance.

[0012] A terminal device is provided, which includes a processor, a transceiver, and a memory. The memory is used to store computer programs, and the processor is used to call and run the computer programs from the memory, and control the transceiver to perform receiving or sending actions, so that the terminal device can perform the elevator operation and maintenance management method based on the above-mentioned operating scenario.

[0013] A computer storage medium is provided for storing a computer program, the computer program including instructions for executing the above-described elevator operation and maintenance management method based on operating scenarios.

[0014] The beneficial effects of this invention are as follows: By introducing operational scenario risks and scenario depreciation factors, this invention enables the fault prediction model to adapt to the component degradation patterns under different operating conditions; it dynamically adjusts the maintenance cycle and content according to the actual elevator operating scenario and health status, avoiding over-maintenance and under-maintenance; and it performs task scheduling based on scenario risk levels and fault prediction results, thereby shortening the average response time for high-risk faults, rationally matching maintenance personnel, and improving maintenance efficiency. Attached Figure Description

[0015] Figure 1 This is a flowchart of an elevator operation and maintenance management method based on operational scenarios.

[0016] Figure 2 Construct a schematic diagram for the covariate vector.

[0017] Figure 3 This is a graph showing the growth curves of the risk rate at different operational stages. Detailed Implementation

[0018] The specific embodiments of the present invention are described below to enable those skilled in the art to understand the present invention. However, it should be understood that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, various changes are obvious as long as they are within the spirit and scope of the present invention as defined and determined by the appended claims. All inventions utilizing the concept of the present invention are protected.

[0019] like Figure 1 As shown, an elevator operation and maintenance management method based on operational scenarios includes: Step S1: Collect the operation data during the elevator operation process and preprocess it to obtain a continuous synchronous operation data vector sequence; calculate the cosine similarity between the synchronous operation data vector and the standard operation data vector based on the standard operation data vector of each elevator operation scenario, so as to match the elevator operation scenario for the elevator operation process.

[0020] Step S1 specifically includes: Step S11: Collect elevator operation data during operation and input the operation data into the edge gateway for timestamping. t Alignment and packet loss interpolation are used to generate timestamps. t Corresponding synchronous running data vector This yields a continuous sequence of synchronized running data vectors. In this embodiment, the data in the synchronized operation data vector is the operation data during the elevator operation process that is timestamped. The specific operation data includes elevator car vibration data, drive current, running speed, car load (kg), component temperature, door operator signal, number of door opening and closing times, and elevator running time collected within a set time window. The car vibration data is collected by deploying triaxial vibration sensors on the traction machine, guide rails, top and bottom of the car, with a sampling frequency of 1kHz.

[0021] This embodiment allows setting the time window to the duration required for a single floor elevator movement, ensuring accurate capture of every change in the operating scenario. The collected operating data is shown in Table 1 below: Table 1. Operational data collected during elevator operation

[0022] Step S12: Define the elevator operation scenario , k Number the elevator operation scenarios and construct each elevator operation scenario. Standard running data vector , N The amount of runtime data collected; Elevator operation and maintenance scenarios include morning peak heavy load scenarios, evening peak heavy load scenarios, off-peak normal load scenarios, nighttime empty load scenarios, transport heavy load scenarios, and fault precursor scenarios. This embodiment... N =8; Step S13: Calculate the synchronous running data vector With each elevator operation scenario Standard running data vector Cosine similarity between ; ; Step S14: Obtain the operating scenario for each type of elevator. Corresponding cosine similarity data , To synchronize the running data vector Elevator operation scenario Standard running data vector Cosine similarity between them K This embodiment addresses the number of elevator operation scenarios. K =6, and sort them from largest to smallest, taking the maximum cosine similarity. The corresponding elevator operation scenario serves as the elevator's timestamp. t Matching elevator operation scenarios.

[0023] Elevator operating scenarios represent the overall operating conditions of an elevator. Elevators operate under different conditions in different scenarios. By collecting operating data from these scenarios, we can assess whether the elevator is operating abnormally in the current scenario, thereby reflecting whether the operation of key components within the elevator is abnormal. This is because the degree of wear and tear on different key components varies under different operating scenarios. For example, heavy load scenarios during morning and evening rush hours put a strain on the traction machine and the car's load-bearing capacity. Therefore, changes or anomalies are likely to occur in car load and component temperatures (traction machine bearings, brake friction pads). By analyzing these data variation patterns, we can identify the operating scenario from which the collected operating data vectors originate.

[0024] Step S2: Merge the same elevator operation scenarios with consecutive timestamps to obtain the time period corresponding to the same elevator operation scenario, calculate the failure rate of key components in each elevator operation scenario, and introduce the weights related to the price and maintenance time of key components to calculate the importance coefficient of different elevator operation scenarios.

[0025] Step S2 specifically includes: Step S21: Based on the continuous synchronous running data vector sequence, convert the continuous timestamps... t By merging the same elevator operation scenarios, the time period corresponding to the elevator being in the same elevator operation scenario can be obtained; Step S22: Identify the key components for elevator maintenance and obtain the number of elevators operating in the same historical time period corresponding to the same elevator operation scenario. m Number of times a key component fails , m Assign numbers to key components and determine the cumulative operating time of the elevator in the same elevator operating scenario. Calculation of key components m Failure rate ; ; This embodiment selects eight components—traction machine, wire rope, guide rails, door operator, frequency converter, brake, safety gear, and buffer—as key components for elevator maintenance. The number of key components... M =8. Failure rate Indicates the elevator is on the first floor. m The key component is in the first k The failure rate during the time period corresponding to the various elevator operation scenarios.

[0026] Step S23: Based on the price of each key component and the historical repair time of the malfunction Determine the weight of each key component ; ; in, The total price of the elevator. The total historical repair time for elevator malfunctions. These are the weighted influence coefficients of price and maintenance difficulty on key components, respectively. This embodiment satisfies... Generally speaking, take ; Step S24: Based on the key components in different elevator operation scenarios m Failure rate and weight Calculate the importance coefficient of different elevator operation scenarios ; ; Importance coefficient Quantifying the risk levels of different operating scenarios provides crucial data for prioritizing elevator maintenance tasks. Importance coefficient. The larger the value, the more severe the operating conditions and the greater the load impact in the corresponding elevator operating scenario; conversely, the more stable the operating conditions and the smaller the load impact.

[0027] Step S3: Collect feature parameters reflecting the health status of each key component, calculate the health of each key component, and introduce the wear acceleration factor of key components under each elevator operation scenario to correct the health status and obtain the corrected health status.

[0028] Step S3 specifically includes: Step S31: Based on the fault-free operating time of each key component under ideal operating conditions (Ideal lifespan) Calculate the wear acceleration factor of key components under each elevator operating scenario. Construct the scenario loss factor matrix ; ; in, For the first m The key component is in the first k Mean time between failures (MTBF) under various elevator operating scenarios; Loss Acceleration Factor This reflects the differences in component degradation rates under different operating scenarios, quantifies the impact of different operating scenarios on the wear and tear of each key component, and provides a basis for dynamic health status assessment; Wear Acceleration Factor The larger the value, the faster the components wear out and fail, resulting in greater wear and tear on the components in this elevator operation scenario; conversely, the smaller the value, the less wear and tear.

[0029] Step S32: Collect characteristic parameters reflecting the health status of each key component. According to the feature parameters Calculate the health status of each key component ; ; in, U The number of characteristic parameters for each key component. u Number the feature parameters. For the first m The first key component u Normal values ​​of each feature parameter For the first m The first key component u Fault threshold of each characteristic parameter; The characteristic parameter types, normal values, and fault thresholds for the health status of each key component collected in this embodiment are shown in Table 2 below: Table 2. Characteristic parameter data of key components

[0030] Step S33: Introduce a loss acceleration factor Health of key components Dynamic adjustments are made to obtain the health status of key components after correction. ; ; in, For timestamps t In the elevator operation scenario No. m The wear acceleration factor of key components The duration of each elevator operation scenario. For the first m The basic degradation rate of key components is determined; considering the differences in component degradation rates under different operating scenarios, the static health is dynamically corrected by calculating the cumulative loss under operating scenarios through integration, so that the health can truly reflect the actual degradation state of key components.

[0031] Step S4: Based on the corrected health status, calculate the comprehensive health index of the elevator, construct the covariate vector of key components in different elevator operation scenarios, calculate the danger rate of key components, determine whether key components in the elevator have malfunctioned, and initiate the operation and maintenance task scheduling instruction.

[0032] Step S4 specifically includes: Step S41: Based on the corrected health level Calculate the overall health index of elevators ; ; Based on the health status of each key component, a weighted summation method is used to calculate the comprehensive health index. This method can comprehensively consider the health status of each key component, fully reflect the overall health level of the elevator, provide a quantitative indicator for evaluating the overall operating status of the elevator, and facilitate managers to quickly grasp the health status of the elevator.

[0033] Step S42: Based on the importance coefficient of each key component in different elevator operating scenarios Health Construct a covariate vector based on the elevator's operating environment temperature and humidity, such as... Figure 2 As shown, the risk rate of critical components is calculated. ; ; in, The cumulative effective operating time after the installation of key components. As the baseline hazard rate, The break-in period after key components are installed. Failure Mode and Condition Factors (FMCMs) are the failure mode coefficients that reflect the failure mode (FMD). This is an early-stage failure. It is a random fault. (for wear and tear failure) This is the covariate vector after the key components are installed. For the average lifespan of critical components, The vector of covariant coefficients; This invention introduces a three-parameter Weibull distribution, which can well fit the life distribution of mechanical components inside elevators. By introducing covariates (such as operating scenario factors and health status) into the hazard rate function, it can adapt to the failure patterns under different operating conditions. It significantly improves the accuracy and adaptability of fault prediction for key components and can dynamically adjust the fault identification results according to the current operating scenario and health status.

[0034] Risk rate It can also be expressed as failure rate or instantaneous failure rate. The higher the value, the higher the risk of failure occurring in the current instant; otherwise, the lower the risk of failure occurring in the current instant.

[0035] like Figure 3 As shown in the figure, this embodiment uses data collected during the operation of an elevator to calculate the relationship curve between the risk rate of key components and the cumulative effective operating time. During the break-in period, the risk rate increases slowly. After the break-in period, the risk rate increases faster and faster as the cumulative effective operating time increases.

[0036] Step S43: Set the hazard rate threshold for critical components ,like If the fault is found, it is determined that a critical component inside the elevator has malfunctioned, and the operation and maintenance task scheduling instruction is initiated to execute step S5; otherwise, it is determined that no critical component inside the elevator has malfunctioned.

[0037] Step S5: Calculate the priority of elevator maintenance task scheduling using the hazard rate and importance coefficient of key components, and match appropriate maintenance personnel according to the priority of each elevator maintenance task scheduling in the elevator maintenance management center to perform elevator maintenance work.

[0038] Step S5 specifically includes: Step S51: Utilize the hazard ratio of all malfunctioning critical components within the elevator. Importance coefficient of the elevator's current operating scenario Calculate the priority of elevator maintenance task scheduling ; ; in, q This is the current maintenance task number initiated by the elevator operation and maintenance management center. The number of critical components that malfunctioned inside the elevator; Step S52: Based on the elevator operation and maintenance management center's current startup... Q Each maintenance task, for Q Priority of each operation and maintenance task Sort the elevators from highest to lowest priority, and then sort them according to the qualifications of the currently available maintenance personnel in the elevator operation and maintenance management center, prioritizing the assignment of the most qualified maintenance personnel to the priority level. The biggest maintenance task is to perform elevator maintenance.

[0039] Maintenance personnel qualifications are selected based on their highest troubleshooting success rate, highest troubleshooting efficiency, and longest service history during past maintenance operations, with priority given to the most qualified personnel. The value indicates the urgency and difficulty of the maintenance task, ensuring the scientific arrangement of elevator maintenance management and the hierarchical handling of maintenance tasks.

[0040] A terminal device includes a processor, a transceiver, and a memory. The memory stores computer programs, and the processor retrieves and runs the computer programs from the memory, controlling the transceiver to perform receiving or sending actions, thereby enabling the terminal device to execute the elevator operation and maintenance management method based on the above-mentioned operating scenario.

[0041] A computer storage medium for storing a computer program, the computer program including instructions for executing the above-described elevator operation and maintenance management method based on operating scenarios.

[0042] This embodiment is relatively simple in its description of the device and medium embodiments, as they are basically similar to the method embodiments. For relevant details, please refer to the description of the method embodiments.

[0043] The devices, media, and methods provided in this application are one-to-one correspondences. Therefore, the devices and media also have similar beneficial effects to their corresponding methods. Since the beneficial effects of the methods have been described in detail above, the beneficial technical effects of the devices and media will not be repeated here.

[0044] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0045] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0046] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0047] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

Claims

1. An elevator operation and maintenance management method based on operational scenarios, characterized in that, include: Step S1: Collect the operation data during the elevator operation process and preprocess it to obtain a continuous synchronous operation data vector sequence; calculate the cosine similarity between the synchronous operation data vector and the standard operation data vector based on the standard operation data vector of each elevator operation scenario, so as to match the elevator operation scenario for the elevator operation process. Step S2: Merge the same elevator operation scenarios with consecutive timestamps to obtain the time period corresponding to the same elevator operation scenario, calculate the failure rate of key components in each elevator operation scenario, and introduce the weights related to the price and maintenance time of key components to calculate the importance coefficient of different elevator operation scenarios. Step S3: Collect feature parameters reflecting the health status of each key component, calculate the health of each key component, and introduce the wear acceleration factor of key components under each elevator operation scenario to correct the health status and obtain the corrected health status. Step S4: Based on the corrected health status, calculate the comprehensive health index of the elevator, construct the covariate vector of key components in different elevator operation scenarios, calculate the risk rate of key components, determine whether key components in the elevator have malfunctioned, and initiate the operation and maintenance task scheduling instruction. Step S5: Calculate the priority of elevator maintenance task scheduling using the hazard rate and importance coefficient of key components, and match appropriate maintenance personnel according to the priority of each elevator maintenance task scheduling in the elevator maintenance management center to perform elevator maintenance work.

2. The elevator operation and maintenance management method based on operational scenarios according to claim 1, characterized in that, The operational data includes car vibration data, drive current, operating speed, car load, component temperature, door operator signal, number of door openings and closings, and operating time; the elevator's various operating scenarios include morning peak heavy load scenario, evening peak heavy load scenario, off-peak normal load scenario, nighttime empty load scenario, transport heavy load scenario, and fault precursor scenario.

3. The elevator operation and maintenance management method based on operational scenarios according to claim 1, characterized in that, Step S1 includes: Step S11: Collect elevator operation data during operation and input the operation data into the edge gateway for timestamping. t Alignment and packet loss interpolation are used to generate timestamps. t Corresponding synchronous running data vector This yields a continuous sequence of synchronized running data vectors. Step S12: Define the elevator operation scenario , k Number the elevator operation scenarios and construct each elevator operation scenario. Standard running data vector , N The amount of runtime data collected; Step S13: Calculate the synchronous running data vector With each elevator operation scenario Standard running data vector Cosine similarity between ; Step S14: Obtain the operating scenario for each type of elevator. Corresponding cosine similarity data , To synchronize the running data vector Elevator operation scenario Standard running data vector Calculate the cosine similarity between the pairs of pairs, sort them from largest to smallest, and then select the pair with the highest cosine similarity. The corresponding elevator operation scenario serves as the elevator's timestamp. t Matching elevator operation scenarios K This refers to the number of elevator operation scenarios.

4. The elevator operation and maintenance management method based on operational scenarios according to claim 3, characterized in that, Step S2 includes: Step S21: Based on the continuous synchronous running data vector sequence, convert the continuous timestamps... t By merging the same elevator operation scenarios, the time period corresponding to the elevator being in the same elevator operation scenario can be obtained; Step S22: Identify the key components for elevator maintenance and obtain the number of elevators operating in the same historical time period corresponding to the same elevator operation scenario. m Number of times a key component fails , m Assign numbers to key components and determine the cumulative operating time of the elevator in the same elevator operating scenario. Calculation of key components m Failure rate ; Step S23: Based on the price of each key component and the historical repair time of the malfunction Determine the weight of each key component ; Step S24: Based on the key components in different elevator operation scenarios m Failure rate and weight Calculate the importance coefficient of different elevator operation scenarios .

5. The elevator operation and maintenance management method based on operational scenarios according to claim 4, characterized in that, Step S3 includes: Step S31: Based on the fault-free operating time of each key component under ideal operating conditions Calculate the wear acceleration factor of key components under each elevator operation scenario. Construct the scenario loss factor matrix ; Step S32: Collect characteristic parameters reflecting the health status of each key component. According to the feature parameters Calculate the health status of each key component , u Number the feature parameters; Step S33: Introduce a loss acceleration factor Health of key components Dynamic adjustments are made to obtain the health status of key components after correction. .

6. The elevator operation and maintenance management method based on operational scenarios according to claim 5, characterized in that, Step S4 includes: Step S41: Based on the corrected health level Calculate the overall health index of elevators ; Step S42: Based on the importance coefficient of each key component in different elevator operating scenarios Health Construct a covariate vector based on the elevator's operating environment temperature and humidity to calculate the risk rate of critical components. ; The cumulative effective operating time after the installation of key components. This is the covariate vector after the key components are installed; Step S43: Set the hazard rate threshold for critical components ,like If the fault is found, it is determined that a critical component inside the elevator has malfunctioned, and the operation and maintenance task scheduling instruction is initiated to execute step S5; otherwise, it is determined that no critical component inside the elevator has malfunctioned.

7. The elevator operation and maintenance management method based on operational scenarios according to claim 6, characterized in that, Step S5 includes: Step S51: Utilize the hazard ratio of all malfunctioning critical components within the elevator. Importance coefficient of the elevator's current operating scenario Calculate the priority of elevator maintenance task scheduling ; q This is the number of the maintenance task currently initiated by the elevator maintenance management center; Step S52: Based on the elevator operation and maintenance management center's current startup... Q Each maintenance task, for Q Priority of each operation and maintenance task Sort the elevators from highest to lowest priority, and then sort them according to the qualifications of the currently available maintenance personnel in the elevator operation and maintenance management center, prioritizing the assignment of the most qualified maintenance personnel to the priority level. The biggest maintenance task is to perform elevator maintenance.

8. A terminal device, characterized in that, The device includes a processor, a transceiver, and a memory. The memory stores a computer program, and the processor retrieves and runs the computer program from the memory. The processor controls the transceiver to perform receiving or sending actions, thereby enabling the terminal device to execute the elevator operation and maintenance management method based on any one of claims 1-7.

9. A computer storage medium, characterized in that, Used to store computer programs, the computer programs including instructions for executing the elevator operation and maintenance management method based on any one of claims 1-7.

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