An elevator whole life cycle quality and safety tracing system
By installing sensor arrays on elevators and combining them with blockchain technology, quality and safety traceability throughout the entire lifecycle of elevators can be achieved, solving the problems of data dispersion and real-time fault detection, and improving the intelligence and reliability of elevator safety management.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SHANDONG TIWANG INFORMATION TECHNOLOGY CO LTD
- Filing Date
- 2025-07-23
- Publication Date
- 2026-07-31
AI Technical Summary
In traditional elevator safety management, data is scattered and lacks a unified and reliable data carrier, making it difficult to trace quality throughout the entire life cycle and to detect potential faults in real time, resulting in insufficient accident prevention capabilities.
A sensor array is used to collect elevator operation data in real time. Combined with blockchain technology, hash processing and on-chain storage are performed to generate a quality and safety record of the entire life cycle of the elevator. The data is then managed and monitored in real time through a visual traceability and early warning response module.
It enables quality and safety traceability throughout the entire life cycle of elevators, improves the reliability and intelligence level of safety management, ensures that data is tamper-proof, supports transparent supervision throughout the entire process, and reduces the accident rate.
Smart Images
Figure CN120987156B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of elevator safety management technology, and in particular to an elevator full life cycle quality and safety traceability system. Background Technology
[0002] With the acceleration of urbanization and the continuous growth of elevator ownership, the safe operation and quality supervision of elevators face severe challenges. Traditional elevator safety management suffers from the following prominent problems: data from elevator manufacturing, installation, maintenance, and use are scattered, lacking a unified and reliable data carrier, making it difficult to trace quality throughout the entire lifecycle. Traditional centralized storage methods are susceptible to human intervention, and critical data (such as maintenance records and fault information) may be tampered with or lost. Reliance on manual inspections and periodic maintenance makes it difficult to detect potential elevator faults in real time, resulting in insufficient accident prevention capabilities. Once a safety accident occurs, the fragmented data and lack of credibility make it difficult to quickly identify the responsible party.
[0003] While existing technologies like the Internet of Things (IoT) can collect elevator operation data, they lack a reliable data storage mechanism. Blockchain technology, while ensuring data security, is not deeply integrated with the actual operation of elevators. Therefore, there is an urgent need for a system that integrates real-time IoT sensing with reliable blockchain traceability to achieve decentralized management and security early warning of elevator data throughout its entire lifecycle. Summary of the Invention
[0004] The purpose of this invention is to provide an elevator full life cycle quality and safety traceability system, which aims to solve the above-mentioned problems.
[0005] This invention provides an elevator lifecycle quality and safety traceability system, comprising:
[0006] The sensor deployment module is configured to install a sensor array and communication components on each elevator.
[0007] The data acquisition module is configured to receive elevator operation data and elevator maintenance data collected by the sensor array through a communication component. The elevator operation data includes the number of runs, load capacity, running speed, vibration frequency, temperature value, and humidity value.
[0008] The data analysis module is configured to analyze the elevator operation data and elevator maintenance data, determine the elevator's operating mode, and determine whether there are potential faults in the elevator. If there are potential faults, a maintenance early warning notification is generated.
[0009] The on-chain storage module is configured to perform hash processing on the operating mode and maintenance warning notification, and store the elevator basic information on the chain to generate a quality and safety record of the entire life cycle of the elevator.
[0010] The visual traceability module is configured to allow visual access to the elevator's entire lifecycle quality and safety records based on user permissions.
[0011] The early warning response module is configured to monitor the user's access process and issue early warning responses based on the user's access process.
[0012] Preferably, the sensor array includes:
[0013] Load sensors are used to detect the load weight each time the elevator runs.
[0014] A speed sensor is used to detect the elevator's operating speed each time it runs.
[0015] Vibration sensors are used to detect the vibration frequency during each elevator operation.
[0016] Temperature sensor is used to detect the temperature value of the control cabinet each time the elevator runs;
[0017] A humidity sensor is used to detect the humidity level inside the elevator each time it runs.
[0018] Preferably, the elevator maintenance data includes: maintenance time, number of maintenance operations, fault type, and corresponding fault data.
[0019] Preferably, the data analysis module analyzes the elevator operation data and elevator maintenance data to determine the elevator's operating mode, including:
[0020] Baselines for the number of runs, load capacity, and operating speed are set.
[0021] Determine the frequency fluctuation value of the vibration frequency, the temperature fluctuation value of the temperature value, and the humidity fluctuation value of the humidity value;
[0022] The elevator's operating mode is determined by comparing the number of runs with the baseline number of runs, the load capacity with the baseline load capacity, and the operating speed with the baseline operating speed, based on the frequency fluctuation value, temperature fluctuation value, humidity fluctuation value, and the comparison results.
[0023] Preferably, the data analysis module determines the elevator's operating mode based on frequency fluctuation values, temperature fluctuation values, humidity fluctuation values, and comparison results, including:
[0024] If the number of runs is less than the baseline number of runs, the load capacity is less than the baseline load capacity, and the running speed is less than the baseline running speed, then the elevator's operating mode is determined based on the frequency fluctuation value, temperature fluctuation value, and humidity fluctuation value; if the frequency fluctuation value, temperature fluctuation value, and humidity fluctuation value are all within acceptable ranges, then the elevator is determined to be in normal mode; if one or more of the frequency fluctuation value, temperature fluctuation value, and humidity fluctuation value are outside acceptable ranges, then the elevator is determined to be in abnormal mode.
[0025] If the number of runs exceeds 130% of the baseline number of runs, and / or the load exceeds 130% of the baseline load, and / or the running speed exceeds 130% of the baseline running speed, then the elevator's operating mode is determined based on the frequency fluctuation value, temperature fluctuation value, and humidity fluctuation value; if the frequency fluctuation value, temperature fluctuation value, and humidity fluctuation value are all within acceptable ranges, then the elevator is determined to be in peak mode; if one or more of the frequency fluctuation value, temperature fluctuation value, and humidity fluctuation value are outside acceptable ranges, then the elevator is determined to be in abnormal mode.
[0026] Preferably, the data analysis module analyzes the elevator operation data and elevator maintenance data to determine the elevator's operating mode, and further includes:
[0027] A minimum number of runs is preset, and the minimum number of runs is less than the baseline number of runs;
[0028] The number of runs is compared with the minimum number of runs. If the number of runs is less than or equal to the minimum number of runs, the elevator is determined to be in energy-saving mode.
[0029] Preferably, the data analysis module determines whether the elevator has a potential malfunction. If a potential malfunction exists, a maintenance early warning notification is generated, including:
[0030] When the elevator is determined to be in an abnormal mode, it is determined that there is a potential malfunction in the elevator, and a maintenance warning notification is generated based on the elevator operation data and elevator maintenance data.
[0031] The elevator operation data is matched with the fault data corresponding to the fault type, and the fault type when the elevator is in an abnormal mode is determined based on the matching result.
[0032] If the elevator operation data and the fault data do not match, the fault type in the elevator abnormal mode is determined based on the frequency fluctuation value, temperature fluctuation value, and humidity fluctuation value.
[0033] If the frequency fluctuation value is outside the acceptable range, the fault type is determined to be guide rail wear or traction wheel failure;
[0034] If the temperature fluctuation value is outside the acceptable range, the fault type is determined to be motor overheating or heat dissipation failure;
[0035] If the humidity fluctuation value is outside the acceptable range, the fault type is determined to be a moisture-induced electrical component fault.
[0036] A maintenance warning notification is generated based on the identified fault type. The maintenance warning notification includes the identified fault type and elevator operation data.
[0037] Preferably, the on-chain storage module performs hash processing on the operating mode and maintenance warning notification, and stores the elevator's basic information on the chain to generate a full lifecycle quality and safety record for the elevator, including:
[0038] The elevator's basic information includes the elevator ID, elevator model, and elevator installation date;
[0039] The operating mode and maintenance warning notification are hashed to generate hash values;
[0040] The hash value is bound to the elevator ID, and the elevator operation data is also bound to the elevator ID, and stored as a full life cycle quality and safety record of the elevator on the blockchain;
[0041] Each elevator's entire lifecycle quality and safety record on each blockchain is timestamped.
[0042] Preferably, the visualization traceability module provides visualized access to the elevator's entire lifecycle quality and safety records based on user permissions, including:
[0043] Obtain user permissions and determine the scope of records that the user can access based on those permissions;
[0044] Obtain the elevator's full lifecycle quality and safety records requested by the user. If the elevator's full lifecycle quality and safety records requested by the user are within the range of records that the user can access, then allow the user to access them.
[0045] If the elevator's full lifecycle quality and safety records requested by the user are not within the scope of records that the user can access, then the user's access will be denied.
[0046] Preferably, the early warning response module monitors the user's access process and issues an early warning response based on the user's access process, including:
[0047] Obtain user permissions and determine the editable scope of the user based on those permissions;
[0048] The system acquires the user's access process, analyzes the access process, determines the user's request to edit records, and if the request to edit records are within the user's editable range, no warning response is issued.
[0049] If the requested edit record is not within the user's editable scope, an early warning response will be issued.
[0050] Compared with existing technologies, the beneficial effects of this invention are that it significantly improves the reliability and intelligence level of elevator safety management through the deep integration of the Internet of Things and blockchain. By using blockchain hashing and on-chain storage, it ensures that elevator operation data, maintenance records, and other information throughout their entire lifecycle are tamper-proof, forming a traceable "digital archive." Data anchoring is achieved based on the elevator's unique identifier (such as an equipment ID), supporting transparent supervision throughout the entire process from manufacturing to scrapping. A sensor array collects key parameters such as vibration frequency and temperature in real time, and combined with intelligent analysis, it predicts potential faults and generates maintenance warnings in advance. Maintenance records are automatically uploaded to the blockchain, avoiding human error or omissions, and improving maintenance efficiency and quality. Blockchain encryption technology prevents data leakage, and sensitive information (such as user identity) is accessed hierarchically through permission management. The warning response module monitors access behavior, and abnormal operations trigger audit trails, ensuring system security. This invention, through collaborative technological innovation, reduces the accident rate and improves the level of public safety. Attached Figure Description
[0051] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.
[0052] Figure 1 This is a functional block diagram of an elevator full life cycle quality and safety traceability system according to the present invention. Detailed Implementation
[0053] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.
[0054] like Figure 1 As shown, this invention provides an elevator full lifecycle quality and safety traceability system, including:
[0055] The sensor deployment module is configured to install sensor arrays and communication components on each elevator.
[0056] The data acquisition module is configured to receive elevator operation data and elevator maintenance data collected by the sensor array through a communication component. The elevator operation data includes the number of runs, load capacity, running speed, vibration frequency, temperature value, and humidity value.
[0057] The data analysis module is configured to analyze the elevator operation data and elevator maintenance data, determine the elevator's operating mode, and determine whether there are potential faults in the elevator. If there are potential faults, a maintenance warning notification is generated.
[0058] The on-chain storage module is configured to perform hash processing on the operating mode and maintenance warning notifications, and store them on the chain according to the elevator's basic information to generate a quality and safety record for the entire life cycle of the elevator.
[0059] The visualization traceability module is configured to allow visual access to the elevator's entire lifecycle quality and safety records based on user permissions.
[0060] The early warning response module is configured to monitor the user's access process and issue early warning responses based on the user's access process.
[0061] This invention enables quality and safety traceability throughout the entire lifecycle of elevators, improving the efficiency and accuracy of elevator safety management. Through a sensor deployment module, the system can acquire elevator operation and maintenance data in real time, providing a reliable foundation for data analysis. The data analysis module can intelligently identify elevator operating modes, promptly detect potential faults, and remind relevant personnel to handle them through maintenance early warning notifications, effectively preventing elevator safety accidents. The on-chain storage module utilizes blockchain technology to ensure the immutability and traceability of elevator quality and safety records throughout their entire lifecycle, providing strong technical support for elevator safety management. The visual traceability module allows users to easily view elevator quality and safety records, improving information transparency. The early warning response module can monitor the user's access process in real time, ensuring the safe and stable operation of the system.
[0062] In some embodiments of this application, the sensor array includes: a load sensor for detecting the load weight each time the elevator runs; a speed sensor for detecting the running speed each time the elevator runs; a vibration sensor for detecting the vibration frequency each time the elevator runs; a temperature sensor for detecting the temperature value of the control cabinet each time the elevator runs; and a humidity sensor for detecting the humidity value inside the elevator each time the elevator runs.
[0063] Understandably, through a finely segmented sensor array, the system can more accurately acquire various key parameters during elevator operation. Load sensors ensure accurate monitoring of the elevator's load capacity, helping to prevent safety hazards caused by overloading. Speed sensors track the elevator's operating speed in real time; if an abnormal speed occurs, the system can respond quickly to avoid the risk of overspeeding. Vibration sensors meticulously monitor vibrations during elevator operation, helping to detect wear or malfunctions of mechanical components early. Temperature sensors monitor the temperature of the control cabinet, preventing equipment damage or fire risks due to overheating. Humidity sensors monitor the humidity environment inside the elevator, providing a more comfortable riding experience for passengers and also helping to maintain the normal operation of the elevator's electronic components.
[0064] In some embodiments of this application, the elevator maintenance data includes: maintenance time, number of maintenance operations, fault type, and corresponding fault data.
[0065] Understandably, by recording detailed elevator maintenance data, the system can comprehensively track the elevator's maintenance history. Recording maintenance times helps in developing and implementing regular maintenance plans, ensuring timely elevator upkeep. Statistics on maintenance frequency reflect the elevator's usage intensity and maintenance frequency, providing crucial information for assessing its lifespan and performance. Recording fault types and corresponding fault data enables maintenance personnel to quickly identify and resolve elevator malfunctions, reducing downtime and improving operational efficiency.
[0066] In some embodiments of this application, the data analysis module analyzes the elevator operation data and elevator maintenance data to determine the elevator's operating mode, including: setting a baseline for the number of runs, a baseline for the load capacity, and a baseline for the operating speed; determining the frequency fluctuation value of the vibration frequency, the temperature fluctuation value of the temperature value, and the humidity fluctuation value of the humidity value; comparing the number of runs with the baseline for the number of runs, comparing the load capacity with the baseline for the load capacity, and comparing the operating speed with the baseline for the operating speed; and determining the elevator's operating mode based on the frequency fluctuation value, the temperature fluctuation value, the humidity fluctuation value, and the comparison results.
[0067] Understandably, through in-depth analysis of elevator operation and maintenance data by the data analysis module, the system can intelligently identify the elevator's operating mode. Setting baselines for the number of runs, load capacity, and operating speed provides reference standards for assessing the elevator's normal operating status. Simultaneously, by monitoring fluctuations in vibration frequency, temperature, and humidity, the system can detect subtle changes during elevator operation; these changes are often early signals of potential malfunctions. By comparing actual operating data with baseline data and analyzing fluctuation values, the system can accurately determine whether the elevator is currently in a normal, abnormal, or faulty state, thus providing timely warnings and preventing accidents.
[0068] In some embodiments of this application, the data analysis module determines the elevator's operating mode based on frequency fluctuation values, temperature fluctuation values, humidity fluctuation values, and comparison results, including: if the number of runs is less than the baseline number of runs, the load capacity is less than the baseline load capacity, and the operating speed is less than the baseline operating speed, then the elevator's operating mode is determined based on the frequency fluctuation values, temperature fluctuation values, and humidity fluctuation values; if the frequency fluctuation values, temperature fluctuation values, and humidity fluctuation values are all within acceptable ranges, then the elevator is determined to be in normal mode; if one or more of the frequency fluctuation values, temperature fluctuation values, and humidity fluctuation values are outside the acceptable ranges... If the frequency fluctuation, temperature fluctuation, and humidity fluctuation are all within acceptable ranges, the elevator is determined to be in abnormal mode. If the number of runs is greater than 130% of the baseline number of runs, and / or the load is greater than 130% of the baseline load, and / or the running speed is greater than 130% of the baseline running speed, the elevator's operating mode is determined based on the frequency fluctuation, temperature fluctuation, and humidity fluctuation values. If the frequency fluctuation, temperature fluctuation, and humidity fluctuation values are all within acceptable ranges, the elevator is determined to be in peak mode. If one or more of the frequency fluctuation, temperature fluctuation, and humidity fluctuation values are outside acceptable ranges, the elevator is determined to be in abnormal mode. Otherwise, it is in normal mode.
[0069] Understandably, through more refined data comparison and fluctuation value analysis, the system can more accurately determine the elevator's status under different loads and operating conditions. When the elevator's number of trips, load capacity, and operating speed are all below the baseline, if the fluctuation values of frequency, temperature, and humidity remain within the preset acceptable range, the system can determine that the elevator is in a normal, low-load operating mode. This is very useful for assessing the elevator's operating status during off-peak hours. Conversely, if these fluctuation values are abnormal, even if the elevator is in a low-load state, the system can promptly identify potential problems and prevent minor faults from escalating into serious accidents.
[0070] When the number of elevator runs, load capacity, or operating speed exceeds 130% of the baseline, the system considers it a peak or high-load condition. In this situation, if the fluctuations in frequency, temperature, and humidity remain within acceptable ranges, the system determines that the elevator is in peak mode, which is a state where the elevator is operating normally but under a higher load. However, if these fluctuations exceed acceptable ranges, the system immediately classifies the elevator as being in an abnormal mode, indicating a potential risk of overload or excessive wear, requiring immediate inspection and maintenance.
[0071] In some embodiments of this application, the data analysis module analyzes the elevator operation data and elevator maintenance data to determine the elevator's operating mode, and further includes: setting a minimum limit for the number of operations, the minimum limit for the number of operations being less than the baseline for the number of operations; comparing the number of operations with the minimum limit for the number of operations, and if the number of operations is less than or equal to the minimum limit for the number of operations, then determining that the elevator is in energy-saving mode.
[0072] Understandably, by introducing the concept of a minimum number of elevator runs, the system can further refine the identification of elevator operating modes. When the number of elevator runs falls below this minimum, it means that the elevator is used very infrequently and may be idle for extended periods. In this case, the system identifies the elevator as being in energy-saving mode, which is significant for reducing energy consumption and lowering operating costs. Setting an energy-saving mode not only reflects the rational use of resources but also aligns with current green and environmentally friendly development principles.
[0073] Furthermore, comparing the number of runs with the minimum required number of runs helps the system more accurately determine the elevator's idle status, allowing for appropriate management measures to be taken. For example, in energy-saving mode, the system can automatically adjust elevator operating parameters, such as reducing operating speed and lighting, to further reduce energy consumption. Simultaneously, the system can send reminders to management personnel, suggesting regular inspections and maintenance of elevators that have been idle for extended periods to ensure they are in good working order.
[0074] In some embodiments of this application, the data analysis module determines whether the elevator has a potential fault. If a potential fault exists, a maintenance warning notification is generated, including: when the elevator is determined to be in an abnormal mode, determining that the elevator has a potential fault, and generating a maintenance warning notification based on the elevator operation data and elevator maintenance data; matching the elevator operation data with the fault data corresponding to the fault type, and determining the fault type in the elevator abnormal mode based on the matching result; if the elevator operation data and the fault data do not match, determining the fault type in the elevator abnormal mode based on the frequency fluctuation value, temperature fluctuation value, and humidity fluctuation value; if the frequency fluctuation value is not within the acceptable range, determining the fault type as guide rail wear or traction sheave fault; if the temperature fluctuation value is not within the acceptable range, determining the fault type as motor overheating or heat dissipation fault; if the humidity fluctuation value is not within the acceptable range, determining the fault type as electrical component moisture fault; generating a maintenance warning notification based on the determined fault type, the maintenance warning notification including the determined fault type and elevator operation data.
[0075] Understandably, by comprehensively analyzing elevator operating and maintenance data, the system can accurately identify potential elevator malfunctions and generate timely maintenance warnings when necessary. This function not only improves the accuracy and efficiency of elevator malfunction identification but also provides strong support for preventative elevator maintenance. When an elevator enters an abnormal mode, the system can respond quickly, determine the presence of potential malfunctions, and identify the specific malfunction type based on the matching results of operating and malfunction data. If the data does not match, the system will further analyze fluctuations in frequency, temperature, and humidity to more comprehensively diagnose the elevator's malfunction. This meticulous malfunction identification method ensures the accuracy and relevance of maintenance warnings, enabling managers to quickly take effective measures to prevent further deterioration of the malfunction and ensure the safe operation of the elevator.
[0076] In some embodiments of this application, the on-chain storage module performs hash processing on the operating mode and maintenance warning notification, and stores them on-chain according to the elevator's basic information to generate a full lifecycle quality and safety record for the elevator. This includes: the elevator's basic information including elevator ID, elevator model, and elevator installation date; hash processing on the operating mode and maintenance warning notification to generate a hash value; binding the hash value to the elevator ID, and binding the elevator operating data to the elevator ID, storing these as a full lifecycle quality and safety record for the elevator on the blockchain; wherein each full lifecycle quality and safety record for the elevator on each blockchain is timestamped.
[0077] Understandably, hashing elevator operation modes and maintenance warning notifications through an on-chain storage module ensures data immutability and security. A hash value, as a unique digital fingerprint, can uniquely identify each piece of data, making any data alteration easily detectable. Binding hash values to elevator IDs not only achieves precise data association but also facilitates rapid retrieval and querying when needed. Simultaneously, binding elevator operation data to elevator IDs and storing it as a complete lifecycle quality and safety record on the blockchain provides comprehensive data support for the full lifecycle management of elevators. This storage method not only improves the efficiency and accuracy of data management but also provides a reliable basis for elevator quality and safety traceability.
[0078] In some embodiments of this application, the visualization traceability module performs visual access to the elevator's entire lifecycle quality and safety records based on user permissions, including: obtaining user permissions and determining the range of records accessible to the user based on user permissions; obtaining the elevator's entire lifecycle quality and safety records that the user requests to access; if the elevator's entire lifecycle quality and safety records that the user requests to access are within the range of records accessible to the user, then allowing the user to access them; if the elevator's entire lifecycle quality and safety records that the user requests to access are not within the range of records accessible to the user, then denying the user access.
[0079] Understandably, the visual traceability module enables authorized access to elevator quality and safety records throughout their entire lifecycle, effectively protecting data security and avoiding potential risks from unauthorized access. Users can only access records within their authorized scope, which not only enhances data confidentiality but also makes data management and use more standardized.
[0080] In some embodiments of this application, the early warning response module monitors the user's access process and issues an early warning response based on the user's access process, including: obtaining user permissions and determining the user's editable range based on the user permissions; obtaining the user's access process, analyzing the access process, determining the user's request to edit records, and if the request to edit records are within the user's editable range, then no early warning response is issued; if the request to edit records are not within the user's editable range, then an early warning response is issued.
[0081] Understandably, the early warning response module enables real-time monitoring and intelligent early warning of user access processes, further enhancing system security. When a user attempts to edit a record beyond their authorized scope, the system immediately issues an early warning, effectively preventing unauthorized data tampering or misoperation and ensuring the integrity and authenticity of elevator quality and safety records throughout their entire lifecycle.
[0082] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program goods. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program goods 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.
[0083] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program goods according to embodiments of this application. 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... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.
[0084] 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.
[0085] 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.
[0086] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.
Claims
1. A quality and safety traceability system for the entire life cycle of an elevator, characterized in that, include: The sensor deployment module is configured to install a sensor array and communication components on each elevator; The sensor array includes: a load sensor for detecting the load weight during each elevator operation; a speed sensor for detecting the operating speed during each elevator operation; a vibration sensor for detecting the vibration frequency during each elevator operation; a temperature sensor for detecting the temperature value of the control cabinet during each elevator operation; and a humidity sensor for detecting the humidity value inside the elevator during each elevator operation. The data acquisition module is configured to receive elevator operation data and elevator maintenance data collected by the sensor array via a communication component. The elevator operation data includes the number of runs, load capacity, running speed, vibration frequency, temperature value, and humidity value. The elevator maintenance data includes maintenance time, maintenance frequency, fault type, and corresponding fault data. The data analysis module is configured to analyze the elevator operation data and elevator maintenance data, determine the elevator's operating mode, and determine whether there are potential faults in the elevator. If there are potential faults, a maintenance early warning notification is generated. The on-chain storage module is configured to perform hash processing on the operating mode and maintenance warning notification, and store the elevator basic information on the chain to generate a quality and safety record of the entire life cycle of the elevator. The visual traceability module is configured to allow visual access to the elevator's entire lifecycle quality and safety records based on user permissions. The early warning response module is configured to monitor the user's access process and issue early warning responses based on the user's access process. The data analysis module analyzes the elevator operation data and elevator maintenance data to determine the elevator's operating mode, including: The data analysis module is configured with baselines for the number of runs, load capacity, and running speed. Determine the frequency fluctuation value of the vibration frequency, the temperature fluctuation value of the temperature value, and the humidity fluctuation value of the humidity value; The number of runs is compared with the baseline number of runs, the load capacity is compared with the baseline load capacity, and the running speed is compared with the baseline running speed. The elevator's operating mode is determined based on the frequency fluctuation value, temperature fluctuation value, humidity fluctuation value, and the comparison results. The data analysis module determines the elevator's operating mode based on frequency fluctuation values, temperature fluctuation values, humidity fluctuation values, and comparison results, including: If the number of runs is less than the baseline number of runs, the load capacity is less than the baseline load capacity, and the running speed is less than the baseline running speed, then the elevator's operating mode is determined based on the frequency fluctuation value, temperature fluctuation value, and humidity fluctuation value; if the frequency fluctuation value, temperature fluctuation value, and humidity fluctuation value are all within acceptable ranges, then the elevator is determined to be in normal mode; if one or more of the frequency fluctuation value, temperature fluctuation value, and humidity fluctuation value are outside acceptable ranges, then the elevator is determined to be in abnormal mode. If the number of runs exceeds 130% of the baseline number of runs, and / or the load exceeds 130% of the baseline load, and / or the running speed exceeds 130% of the baseline running speed, then the elevator's operating mode is determined based on the frequency fluctuation value, temperature fluctuation value, and humidity fluctuation value; if the frequency fluctuation value, temperature fluctuation value, and humidity fluctuation value are all within acceptable ranges, then the elevator is determined to be in peak mode; if one or more of the frequency fluctuation value, temperature fluctuation value, and humidity fluctuation value are outside acceptable ranges, then the elevator is determined to be in abnormal mode.
2. The elevator full life cycle quality and safety traceability system according to claim 1, characterized in that, The data analysis module analyzes the elevator operation data and elevator maintenance data to determine the elevator's operating mode, and also includes: A minimum number of runs is preset, and the minimum number of runs is less than the baseline number of runs; The number of runs is compared with the minimum number of runs. If the number of runs is less than or equal to the minimum number of runs, the elevator is determined to be in energy-saving mode.
3. The elevator full life cycle quality and safety traceability system according to claim 2, characterized in that, The data analysis module determines whether there are potential malfunctions in the elevator. If a potential malfunction is found, a maintenance warning notification is generated, including: When the elevator is determined to be in an abnormal mode, it is determined that there is a potential malfunction in the elevator, and a maintenance warning notification is generated based on the elevator operation data and elevator maintenance data. The elevator operation data is matched with the fault data corresponding to the fault type, and the fault type when the elevator is in an abnormal mode is determined based on the matching result. If the elevator operation data and the fault data do not match, the fault type in the elevator abnormal mode is determined based on the frequency fluctuation value, temperature fluctuation value, and humidity fluctuation value. If the frequency fluctuation value is outside the acceptable range, the fault type is determined to be guide rail wear or traction wheel failure; If the temperature fluctuation value is outside the acceptable range, the fault type is determined to be motor overheating or heat dissipation failure. If the humidity fluctuation value is outside the acceptable range, the fault type is determined to be a moisture-induced electrical component fault. A maintenance warning notification is generated based on the identified fault type. The maintenance warning notification includes the identified fault type and elevator operation data.
4. The elevator full life cycle quality and safety traceability system according to claim 3, characterized in that, The on-chain storage module performs hash processing on the operating mode and maintenance warning notifications, and stores them on-chain based on the elevator's basic information to generate a full lifecycle quality and safety record for the elevator, including: The elevator's basic information includes the elevator ID, elevator model, and elevator installation date; The operating mode and maintenance warning notification are hashed to generate hash values; The hash value is bound to the elevator ID, and the elevator operation data is also bound to the elevator ID, and stored as a full life cycle quality and safety record of the elevator on the blockchain; Each elevator's entire lifecycle quality and safety record on each blockchain is timestamped.
5. The elevator full life cycle quality and safety traceability system according to claim 4, characterized in that, The visualization traceability module allows for visualized access to the elevator's entire lifecycle quality and safety records based on user permissions, including: Obtain user permissions and determine the scope of records that the user can access based on those permissions; Access the elevator's full lifecycle quality and safety records requested by the user. If the elevator's full lifecycle quality and safety records requested by the user are within the range of records that the user can access, then allow the user to access them. If the elevator's full lifecycle quality and safety records requested by the user are not within the scope of records that the user can access, then the user's access will be denied.
6. The elevator full life cycle quality and safety traceability system according to claim 5, characterized in that, The early warning response module monitors the user's access process and issues early warning responses based on the user's access process, including: Obtain user permissions and determine the editable scope of the user based on those permissions; The system acquires the user's access process, analyzes the access process, determines the user's request to edit records, and if the request to edit records are within the user's editable range, no warning response is issued. If the requested edit record is not within the user's editable scope, an early warning response will be issued.