A cloud blockchain service platform driven elevator whole life cycle management solution method

Abstract

The application relates to the technical field of elevator management, and discloses a cloud block chain service platform driven elevator whole life cycle management solution method, which comprises the following steps: constructing an elevator whole life cycle database of an elevator to be managed based on a cloud block chain and historical life cycle data; collecting and analyzing use scene information of the elevator to be managed, and determining an initial maintenance cycle of the elevator to be managed based on an analysis result; analyzing the elevator whole life cycle database to obtain historical fault data, historical maintenance data and historical performance evaluation data of the elevator to be managed, collecting real-time running data of the elevator to be managed, and determining a cycle influence factor according to the historical fault data, the historical maintenance data, the historical performance evaluation data and the real-time running data; judging and optimizing the initial maintenance cycle according to the cycle influence factor to obtain an optimized maintenance cycle. The application can accurately determine and optimize the maintenance cycle of the elevator.

Description

Technical Field

[0001] This invention relates to the field of elevator management technology, and more specifically, to a solution for elevator lifecycle management driven by a cloud blockchain service platform. Background Technology

[0002] With the accelerating pace of urbanization and the ever-expanding scale of cities, elevators, as an indispensable vertical transportation tool in modern high-rise buildings, have seen their safety performance and operational reliability become increasingly important issues of widespread concern. Traditional elevator management methods often rely primarily on manual periodic inspections and routine maintenance. This management model is not only inefficient in practice, making it difficult to respond quickly to and handle sudden malfunctions, but also, due to limited manpower, it is difficult to achieve comprehensive and meticulous management and monitoring of the entire lifecycle of elevators, from installation and use to maintenance and upgrades.

[0003] Therefore, it is necessary to design a cloud blockchain service platform-driven solution for elevator lifecycle management to address the problems existing in current technologies. Summary of the Invention

[0004] In view of this, the present invention proposes a cloud blockchain service platform-driven solution for elevator lifecycle management, which aims to solve the problem that traditional elevator management methods often rely on manual inspections and regular maintenance, which are not only inefficient but also difficult to achieve comprehensive management of the elevator's entire lifecycle.

[0005] This invention proposes a solution for elevator lifecycle management driven by a cloud blockchain service platform, including:

[0006] Identify elevators to be managed, collect historical lifecycle data of the elevators to be managed, and construct a full lifecycle database of the elevators to be managed based on cloud blockchain and the historical lifecycle data;

[0007] The usage scenario information of the elevator to be managed is collected and analyzed, and the initial maintenance cycle of the elevator to be managed is determined based on the analysis results;

[0008] The elevator lifecycle database is parsed to obtain historical fault data, historical maintenance data, and historical performance evaluation data of the elevator to be managed. Real-time operation data of the elevator to be managed is collected, and the cycle influencing factor is determined based on the historical fault data, historical maintenance data, historical performance evaluation data, and real-time operation data.

[0009] Based on the cycle impact factors, the initial maintenance cycle is determined and optimized to obtain the optimized maintenance cycle.

[0010] Furthermore, the method is characterized in that, when determining the initial maintenance cycle of the elevator to be managed based on the analysis results, it includes:

[0011] The usage scenario information is analyzed to obtain the usage scenario, usage frequency, load characteristic value and running time of the elevator to be managed;

[0012] Determine the basic maintenance cycle of the elevator to be managed based on the usage scenario;

[0013] Based on the usage frequency, determine whether to adjust the basic maintenance cycle; if so, determine the adjustment coefficient of the basic maintenance cycle based on the load characteristic value and the running time, and use the product of the adjustment coefficient and the basic maintenance cycle as the initial maintenance cycle.

[0014] Furthermore, the feature is that, when determining the basic maintenance cycle of the elevator to be managed based on the usage scenario, it includes:

[0015] The application scenarios include commercial buildings, residential communities, and public places;

[0016] When the usage scenario is the commercial building, the basic maintenance cycle is determined to be the first maintenance cycle;

[0017] When the usage scenario is the residential community, the basic maintenance cycle is determined to be the second maintenance cycle;

[0018] When the usage scenario is the public place, the basic maintenance cycle is determined to be the third maintenance cycle.

[0019] Further, the feature is that, when determining whether to adjust the basic maintenance cycle based on the usage frequency, it includes:

[0020] The usage frequency is compared with the standard usage frequency range, and the basic maintenance cycle is adjusted based on the comparison results.

[0021] If the usage frequency is within the standard usage frequency range, then it is determined that the basic maintenance cycle should be adjusted.

[0022] Otherwise, it is determined that the basic maintenance cycle will not be adjusted.

[0023] Further, the method for determining the adjustment coefficient of the basic maintenance cycle based on the load characteristic value and the operating time includes:

[0024] The load characteristic value and running time are used to construct an adjustment characteristic group. The adjustment characteristic group is compared with the historical adjustment group, and the adjustment coefficient of the basic maintenance cycle is determined based on the comparison result.

[0025] When there is a historical adjustment feature group in the historical adjustment group that is the same as the adjustment feature group, the historical adjustment coefficient corresponding to the historical adjustment feature group shall be used as the adjustment coefficient;

[0026] When there is no historical adjustment feature group in the historical adjustment group that is the same as the adjustment feature group, the adjustment coefficient of the basic maintenance cycle is determined according to the adjustment feature group.

[0027] Further, the method for determining the adjustment coefficient of the basic maintenance cycle based on the adjustment feature group includes:

[0028] A comprehensive adjustment index is calculated based on the adjustment feature group. The comprehensive adjustment index is compared with a first comprehensive adjustment index and a second comprehensive adjustment index. The adjustment coefficient of the basic maintenance cycle is determined based on the comparison result. The first comprehensive adjustment index is less than the second comprehensive adjustment index.

[0029] When the comprehensive adjustment index is less than or equal to the first comprehensive adjustment index, the adjustment coefficient is determined to be the first adjustment coefficient;

[0030] When the comprehensive adjustment index is greater than the first comprehensive adjustment index and less than the second comprehensive adjustment index, the adjustment coefficient is determined to be the second adjustment coefficient;

[0031] When the comprehensive adjustment index is greater than or equal to the second comprehensive adjustment index, the adjustment coefficient is determined to be the third adjustment coefficient;

[0032] Wherein, the first adjustment coefficient is less than the second adjustment coefficient, and the second adjustment coefficient is less than the third adjustment coefficient.

[0033] Further, the feature is that, when determining the periodic influencing factor based on the historical fault data, historical maintenance data, historical performance evaluation data, and real-time operation data, it includes:

[0034] The historical fault data, historical maintenance data, historical performance evaluation data, and real-time operation data are analyzed respectively to obtain historical fault frequency, historical maintenance duration, historical performance score, and real-time operation status value.

[0035] The cycle impact factor is calculated based on the historical fault frequency, historical maintenance duration, historical performance score, and real-time operating status value.

[0036] Further, the method is characterized in that, when determining and optimizing the initial maintenance cycle based on the said periodic impact factor to obtain the optimized maintenance cycle, it includes:

[0037] The periodic impact factor is compared with the preset periodic impact factor threshold, and the initial maintenance cycle is optimized based on the comparison result.

[0038] If the periodic impact factor is greater than the preset periodic impact factor threshold, it is determined that the initial maintenance cycle should be optimized.

[0039] Otherwise, it is determined that the initial maintenance cycle will not be optimized.

[0040] Furthermore, the method is characterized in that, when determining and optimizing the initial maintenance cycle based on the said periodic impact factor to obtain the optimized maintenance cycle, it further includes:

[0041] The cycle impact factor is compared with the first cycle impact factor and the second cycle impact factor. Based on the comparison result, the optimization coefficient of the initial maintenance cycle is determined, and the product of the optimization coefficient and the initial maintenance cycle is taken as the optimized maintenance cycle; wherein, the first cycle impact factor is smaller than the second cycle impact factor.

[0042] When the periodic influence factor is less than or equal to the first periodic influence factor, the optimization coefficient is determined to be the first optimization coefficient;

[0043] When the periodic impact factor is greater than the first periodic impact factor and less than the second periodic impact factor, the optimization coefficient is determined to be the second optimization coefficient.

[0044] When the periodic influence factor is greater than or equal to the second periodic influence factor, the optimization coefficient is determined to be the third optimization coefficient.

[0045] Furthermore, the characteristic is that the periodic influence factor is obtained by the following formula:

[0046] CIF=ω1·f+ω2·t+ω3·(1-s)+ω4·r;

[0047] Where CIF represents the periodic impact factor; f represents the normalized historical failure frequency; t represents the normalized historical total maintenance time; s represents the normalized historical performance score; r represents the normalized real-time operating status value; ω1, ω2, ω3, and ω4 all represent weighting coefficients, and ω1+ω2+ω3+ω

[0048] 4 = 1.

[0049] Compared with existing technologies, the advantages of this invention are as follows: The cloud blockchain service platform-driven elevator lifecycle management solution provided by this invention can comprehensively consider multiple dimensions such as historical elevator data, usage scenarios, and real-time operating status to accurately determine and optimize elevator maintenance cycles, thereby effectively improving elevator operational safety and reliability while reducing unnecessary maintenance costs. Through the application of cloud blockchain technology, the traceability and immutability of elevator data can also be achieved, providing strong technical support for elevator lifecycle management. Attached Figure Description

[0050] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0051] Figure 1 A flowchart illustrating the elevator lifecycle management solution driven by a cloud blockchain service platform provided in this embodiment of the invention. Detailed Implementation

[0052] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the disclosure to those skilled in the art. It should be noted that, unless otherwise specified, embodiments and features in the embodiments of the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0053] See Figure 1 As shown in some embodiments of this application, this embodiment provides a solution for elevator lifecycle management driven by a cloud blockchain service platform, including the following steps:

[0054] S100: Identify the elevator to be managed, collect the historical lifecycle data of the elevator to be managed, and construct the elevator lifecycle database of the elevator to be managed based on the cloud blockchain and the historical lifecycle data;

[0055] S200: Collect and analyze the usage scenario information of the elevator to be managed, and determine the initial maintenance cycle of the elevator to be managed based on the analysis results;

[0056] S300: Parse the elevator's full life cycle database to obtain historical fault data, historical maintenance data, and historical performance evaluation data of the elevator to be managed; collect real-time operation data of the elevator to be managed; and determine the cycle impact factor based on the historical fault data, historical maintenance data, historical performance evaluation data, and real-time operation data.

[0057] S400: Determine and optimize the initial maintenance cycle based on the cycle impact factor to obtain the optimized maintenance cycle.

[0058] In this embodiment, when constructing a full lifecycle database of elevators to be managed based on cloud blockchain and historical lifecycle data, the decentralized, transparent, and tamper-proof characteristics of cloud blockchain ensure the authenticity and integrity of the data. Simultaneously, the powerful data processing capabilities of cloud computing are utilized to efficiently store and analyze historical lifecycle data, providing reliable data support for subsequent steps.

[0059] In this embodiment, the historical lifecycle data includes basic elevator information such as model, manufacturing date, installation date, rated load, and operating speed; elevator maintenance records, including maintenance time, maintenance content, maintenance personnel, and maintenance results; elevator fault records, including fault occurrence time, fault phenomenon, fault cause, and handling measures; and elevator performance evaluation data, such as periodic performance test results and operating efficiency evaluations.

[0060] It is understood that the elevator lifecycle management solution driven by the cloud blockchain service platform provided in this embodiment can comprehensively consider multiple dimensions such as historical elevator data, usage scenarios, and real-time operating status to accurately determine and optimize elevator maintenance cycles, thereby effectively improving elevator operational safety and reliability while reducing unnecessary maintenance costs. Through the application of cloud blockchain technology, the traceability and immutability of elevator data can also be achieved, providing strong technical support for elevator lifecycle management.

[0061] Specifically, the characteristic is that, when determining the initial maintenance cycle of the elevator to be managed based on the analysis results, it includes:

[0062] The usage scenario information is analyzed to obtain the usage scenario, usage frequency, load characteristic value and running time of the elevator to be managed;

[0063] Determine the basic maintenance cycle of the elevator to be managed based on the usage scenario;

[0064] Based on the usage frequency, determine whether to adjust the basic maintenance cycle; if so, determine the adjustment coefficient of the basic maintenance cycle based on the load characteristic value and the running time, and use the product of the adjustment coefficient and the basic maintenance cycle as the initial maintenance cycle.

[0065] It is understandable that different usage scenarios, usage frequency, load characteristics, and operating durations all affect the wear and tear and failure probability of elevators. Therefore, these factors need to be comprehensively considered when determining the initial maintenance cycle. For example, elevators with high usage frequency and heavy loads may experience faster wear and tear, thus requiring a shorter maintenance cycle to ensure safe operation. Conversely, elevators with low usage frequency and light loads can have a longer maintenance cycle to reduce maintenance costs. This method allows for a more accurate determination of the initial elevator maintenance cycle, providing a reliable basis for subsequent optimization of the maintenance cycle.

[0066] Specifically, the feature is that, when determining the basic maintenance cycle of the elevator to be managed based on the usage scenario, it includes:

[0067] The application scenarios include commercial buildings, residential communities, and public places;

[0068] When the usage scenario is the commercial building, the basic maintenance cycle is determined to be the first maintenance cycle;

[0069] When the usage scenario is the residential community, the basic maintenance cycle is determined to be the second maintenance cycle;

[0070] When the usage scenario is the public place, the basic maintenance cycle is determined to be the third maintenance cycle.

[0071] It is understandable that different usage scenarios result in variations in elevator usage frequency, load requirements, and operating environments, directly impacting elevator wear and tear and failure rates. Therefore, setting different basic maintenance cycles for three typical usage scenarios—commercial buildings, residential communities, and public places—is reasonable. For commercial buildings, due to their typically high usage frequency and load requirements, elevators operate under relatively heavy loads; therefore, the first maintenance cycle should be relatively short to ensure timely maintenance and prevent potential safety hazards. For residential communities, while usage frequency may also be high, load requirements are relatively low, and the operating environment is relatively stable; therefore, the second maintenance cycle can be appropriately extended to balance maintenance costs and elevator safety. For public places, such as large transportation hubs like train stations and airports, elevator usage frequency and load requirements may fluctuate due to changes in passenger flow, and these locations place extremely high demands on elevator safety and reliability. Therefore, the third maintenance cycle needs to be set by comprehensively considering various factors to ensure safe elevator operation while avoiding unnecessary maintenance costs.

[0072] Specifically, the feature is that, when determining whether to adjust the basic maintenance cycle based on the usage frequency, it includes:

[0073] The usage frequency is compared with the standard usage frequency range, and the basic maintenance cycle is adjusted based on the comparison results.

[0074] If the usage frequency is within the standard usage frequency range, then it is determined that the basic maintenance cycle should be adjusted.

[0075] Otherwise, it is determined that the basic maintenance cycle will not be adjusted.

[0076] Understandably, usage frequency is a crucial indicator of elevator wear and tear. If an elevator's usage frequency exceeds the standard range, it indicates high operational intensity, potentially accelerating wear. Therefore, the basic maintenance cycle needs to be appropriately shortened to ensure the elevator's safety and reliability. Conversely, if the elevator's usage frequency is below the standard range, it suggests relatively low operational intensity and slower wear. In this case, the basic maintenance cycle can be appropriately extended to reduce maintenance costs. This adjustment mechanism allows for more flexible adaptation to different elevator usage scenarios, enabling precise management of maintenance cycles.

[0077] Specifically, the characteristic of determining the adjustment coefficient for the basic maintenance cycle based on the load characteristic value and the operating time includes:

[0078] The load characteristic value and running time are used to construct an adjustment characteristic group. The adjustment characteristic group is compared with the historical adjustment group, and the adjustment coefficient of the basic maintenance cycle is determined based on the comparison result.

[0079] When there is a historical adjustment feature group in the historical adjustment group that is the same as the adjustment feature group, the historical adjustment coefficient corresponding to the historical adjustment feature group shall be used as the adjustment coefficient;

[0080] When there is no historical adjustment feature group in the historical adjustment group that is the same as the adjustment feature group, the adjustment coefficient of the basic maintenance cycle is determined according to the adjustment feature group.

[0081] In this embodiment, the load characteristic value is preferably the ratio of the elevator's average load capacity to its maximum load capacity, and the running time is preferably the cumulative running time of the elevator.

[0082] Understandably, by constructing adjustment feature groups and comparing them with historical adjustment groups, the adjustment coefficients for the basic maintenance cycle can be determined quickly and accurately, thereby improving the efficiency and accuracy of maintenance cycle determination. This method makes full use of historical data, avoiding the uncertainty caused by relying solely on experience or intuitive judgment, making the determination of maintenance cycles more scientific and reasonable.

[0083] Specifically, the method for determining the adjustment coefficient of the basic maintenance cycle based on the adjustment feature group includes:

[0084] A comprehensive adjustment index is calculated based on the adjustment feature group. The comprehensive adjustment index is compared with a first comprehensive adjustment index and a second comprehensive adjustment index. The adjustment coefficient of the basic maintenance cycle is determined based on the comparison result. The first comprehensive adjustment index is less than the second comprehensive adjustment index.

[0085] When the comprehensive adjustment index is less than or equal to the first comprehensive adjustment index, the adjustment coefficient is determined to be the first adjustment coefficient;

[0086] When the comprehensive adjustment index is greater than the first comprehensive adjustment index and less than the second comprehensive adjustment index, the adjustment coefficient is determined to be the second adjustment coefficient;

[0087] When the comprehensive adjustment index is greater than or equal to the second comprehensive adjustment index, the adjustment coefficient is determined to be the third adjustment coefficient;

[0088] Wherein, the first adjustment coefficient is less than the second adjustment coefficient, and the second adjustment coefficient is less than the third adjustment coefficient.

[0089] In this embodiment, the calculation process of the comprehensive adjustment index is as follows: after normalizing the load characteristic value and running time in the adjustment characteristic group, different weights are assigned to them respectively, the weighted average value of the adjustment characteristic group is calculated according to the weights, and the weighted average value is used as the comprehensive adjustment index.

[0090] In this embodiment, the first adjustment coefficient is preferably 0.8, the second adjustment coefficient is preferably 1.05, and the third adjustment coefficient is preferably 1.2. This setting allows for more precise adjustment of the maintenance cycle based on the actual usage of the elevator, further improving the accuracy and scientific nature of the maintenance cycle.

[0091] Understandably, by setting a first and second comprehensive adjustment index as thresholds and comparing the comprehensive adjustment index with these two thresholds, the range of adjustment coefficient values ​​can be more precisely defined, thereby achieving refined adjustments to the maintenance cycle. When the comprehensive adjustment index is low, it indicates that the elevator's load characteristics and running time have a relatively small impact on the maintenance cycle; therefore, a smaller adjustment coefficient, i.e., the first adjustment coefficient, is chosen to maintain a longer maintenance cycle. When the comprehensive adjustment index is moderate, it indicates that the elevator's load characteristics and running time have a certain impact on the maintenance cycle; in this case, a moderate adjustment coefficient, i.e., the second adjustment coefficient, is chosen to balance maintenance costs and elevator safety. Conversely, when the comprehensive adjustment index is high, it indicates that the elevator's load characteristics and running time have a significant impact on the maintenance cycle; therefore, a larger adjustment coefficient, i.e., the third adjustment coefficient, is needed to shorten the maintenance cycle and ensure the safe operation of the elevator.

[0092] Specifically, the characteristic is that, when determining the periodic influencing factor based on the historical fault data, historical maintenance data, historical performance evaluation data, and real-time operation data, it includes:

[0093] The historical fault data, historical maintenance data, historical performance evaluation data, and real-time operation data are analyzed respectively to obtain historical fault frequency, historical maintenance duration, historical performance score, and real-time operation status value.

[0094] The cycle impact factor is calculated based on the historical fault frequency, historical maintenance duration, historical performance score, and real-time operating status value.

[0095] Understandably, historical failure frequency reflects how often the elevator has malfunctioned in the past and is an important indicator for assessing elevator stability and reliability. Historical maintenance time reflects the efficiency of elevator fault repair; a long maintenance time may indicate design or manufacturing defects in certain elevator components, requiring close monitoring. Historical performance score is a quantitative assessment of the elevator's periodic performance test results, providing a direct reflection of the elevator's performance status. Real-time operating status values, on the other hand, are real-time monitoring of the elevator's current operating status, including key parameters such as speed, acceleration, and vibration, which are crucial for the timely detection of potential faults.

[0096] Specifically, the method for determining and optimizing the initial maintenance cycle based on the periodic impact factor to obtain an optimized maintenance cycle includes:

[0097] The periodic impact factor is compared with the preset periodic impact factor threshold, and the initial maintenance cycle is optimized based on the comparison result.

[0098] If the periodic impact factor is greater than the preset periodic impact factor threshold, it is determined that the initial maintenance cycle should be optimized.

[0099] Otherwise, it is determined that the initial maintenance cycle will not be optimized.

[0100] Understandably, the cycle impact factor is an important indicator for measuring the urgency of elevator maintenance needs. When the cycle impact factor exceeds a preset threshold, it means that the elevator's current condition or historical performance indicates a high maintenance requirement. In this case, the initial maintenance cycle needs to be optimized to carry out maintenance work in advance and prevent potential failures from occurring.

[0101] Specifically, the method for determining and optimizing the initial maintenance cycle based on the periodic impact factor to obtain an optimized maintenance cycle further includes:

[0102] The cycle impact factor is compared with the first cycle impact factor and the second cycle impact factor. Based on the comparison result, the optimization coefficient of the initial maintenance cycle is determined, and the product of the optimization coefficient and the initial maintenance cycle is taken as the optimized maintenance cycle; wherein, the first cycle impact factor is smaller than the second cycle impact factor.

[0103] When the periodic influence factor is less than or equal to the first periodic influence factor, the optimization coefficient is determined to be the first optimization coefficient;

[0104] When the periodic impact factor is greater than the first periodic impact factor and less than the second periodic impact factor, the optimization coefficient is determined to be the second optimization coefficient.

[0105] When the periodic influence factor is greater than or equal to the second periodic influence factor, the optimization coefficient is determined to be the third optimization coefficient.

[0106] In this embodiment, the first optimization coefficient is preferably 0.85, the second optimization coefficient is preferably 0.95, and the third optimization coefficient is preferably 1.1. This setting allows for more precise adjustment of the maintenance cycle based on the periodic impact factor, ensuring timely response to elevator maintenance needs. When the periodic impact factor is low, it indicates relatively low elevator maintenance needs; in this case, a smaller optimization coefficient, i.e., the first optimization coefficient, is chosen to maintain a longer maintenance cycle and avoid unnecessary maintenance costs. When the periodic impact factor is moderate, a moderate optimization coefficient is selected.

[0107] Specifically, the characteristic is that the periodic influence factor is obtained by the following formula:

[0108] CIF=ω1·f+ω2·t+ω3·(1-s)+ω4·r;

[0109] Where CIF represents the periodic impact factor; f represents the normalized historical failure frequency; t represents the normalized historical total maintenance time; s represents the normalized historical performance score; r represents the normalized real-time operating status value; ω1, ω2, ω3, and ω4 all represent weighting coefficients, and ω1+ω2+ω3+ω

[0110] 4 = 1.

[0111] Understandably, this formula comprehensively considers four key factors: historical failure frequency, historical maintenance duration, historical performance score, and real-time operating status value, and assigns different weight coefficients to reflect their importance to the cycle impact factor. This design makes the calculation of the cycle impact factor more comprehensive and scientific, and can more accurately reflect the urgency of elevator maintenance needs. In practical applications, these weight coefficients can be adjusted according to the specific situation of the elevator and maintenance strategy to achieve more personalized maintenance cycle optimization. This method ensures that elevator maintenance work is carried out in a timely and effective manner, thereby improving elevator safety and reliability, extending elevator service life, reducing maintenance costs, and providing stronger support for the full life cycle management of elevators.

[0112] 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.

[0113] 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.

[0114] 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.

[0115] 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.

[0116] 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 solution for elevator lifecycle management driven by a cloud blockchain service platform, characterized in that, include: Identify elevators to be managed, collect historical lifecycle data of the elevators to be managed, and construct a full lifecycle database of the elevators to be managed based on cloud blockchain and the historical lifecycle data; The usage scenario information of the elevator to be managed is collected and analyzed, and the initial maintenance cycle of the elevator to be managed is determined based on the analysis results; The elevator lifecycle database is parsed to obtain historical fault data, historical maintenance data, and historical performance evaluation data of the elevator to be managed. Real-time operation data of the elevator to be managed is collected, and the cycle influencing factor is determined based on the historical fault data, historical maintenance data, historical performance evaluation data, and real-time operation data. Based on the aforementioned periodic impact factors, the initial maintenance cycle is determined and optimized to obtain an optimized maintenance cycle. When determining the initial maintenance cycle of the elevator to be managed based on the analysis results, the following are included: The usage scenario information is analyzed to obtain the usage scenario, usage frequency, load characteristic value and running time of the elevator to be managed; Determine the basic maintenance cycle of the elevator to be managed based on the usage scenario; Based on the usage frequency, determine whether to adjust the basic maintenance cycle; if so, determine the adjustment coefficient of the basic maintenance cycle based on the load characteristic value and the running time, and use the product of the adjustment coefficient and the basic maintenance cycle as the initial maintenance cycle. When determining the periodic impact factor based on the aforementioned historical fault data, historical maintenance data, historical performance evaluation data, and real-time operation data, the following are included: The historical fault data, historical maintenance data, historical performance evaluation data, and real-time operation data are analyzed respectively to obtain historical fault frequency, historical maintenance duration, historical performance score, and real-time operation status value. The cycle impact factor is calculated based on the historical fault frequency, historical maintenance duration, historical performance score, and real-time operating status value. When determining and optimizing the initial maintenance cycle based on the aforementioned periodic impact factors to obtain the optimized maintenance cycle, the following steps are included: The periodic impact factor is compared with the preset periodic impact factor threshold, and the initial maintenance cycle is optimized based on the comparison result. If the periodic impact factor is greater than the preset periodic impact factor threshold, it is determined that the initial maintenance cycle should be optimized. Otherwise, it is determined that the initial maintenance cycle will not be optimized; The periodic impact factor is obtained by the following formula: ； Wherein, CIF represents the periodic impact factor; f represents the normalized historical fault frequency; t represents the normalized historical total maintenance time; s represents the normalized historical performance score; r represents the normalized real-time operating status value; ω1, ω2, ω3 and ω4 all represent weighting coefficients, and ω1+ω2+ω3+ω4=1.

2. The solution for elevator lifecycle management driven by a cloud blockchain service platform according to claim 1, characterized in that, When determining the basic maintenance cycle of the elevator to be managed based on the aforementioned usage scenario, the following are included: The application scenarios include commercial buildings, residential communities, and public places; When the usage scenario is the commercial building, the basic maintenance cycle is determined to be the first maintenance cycle; When the usage scenario is the residential community, the basic maintenance cycle is determined to be the second maintenance cycle; When the usage scenario is the public place, the basic maintenance cycle is determined to be the third maintenance cycle.

3. The solution for elevator lifecycle management driven by a cloud blockchain service platform according to claim 2, characterized in that, When determining whether to adjust the basic maintenance cycle based on the usage frequency, the following are included: The usage frequency is compared with the standard usage frequency range, and the basic maintenance cycle is adjusted based on the comparison results. If the usage frequency is within the standard usage frequency range, then it is determined that the basic maintenance cycle will not be adjusted. Otherwise, it is determined that the basic maintenance cycle should be adjusted.

4. The elevator lifecycle management solution driven by the cloud blockchain service platform according to claim 3, characterized in that, When determining the adjustment coefficient for the basic maintenance cycle based on the load characteristic value and operating time, the following is included: The load characteristic value and running time are used to construct an adjustment characteristic group. The adjustment characteristic group is compared with the historical adjustment group, and the adjustment coefficient of the basic maintenance cycle is determined based on the comparison result. When there is a historical adjustment feature group in the historical adjustment group that is the same as the adjustment feature group, the historical adjustment coefficient corresponding to the historical adjustment feature group shall be used as the adjustment coefficient; When there is no historical adjustment feature group in the historical adjustment group that is the same as the adjustment feature group, the adjustment coefficient of the basic maintenance cycle is determined according to the adjustment feature group.

5. The solution for elevator lifecycle management driven by a cloud blockchain service platform according to claim 4, characterized in that, When determining the adjustment coefficient of the basic maintenance cycle based on the adjustment feature group, the following is included: A comprehensive adjustment index is calculated based on the adjustment feature group. The comprehensive adjustment index is compared with a first comprehensive adjustment index and a second comprehensive adjustment index. The adjustment coefficient of the basic maintenance cycle is determined based on the comparison result. The first comprehensive adjustment index is less than the second comprehensive adjustment index. When the comprehensive adjustment index is less than or equal to the first comprehensive adjustment index, the adjustment coefficient is determined to be the first adjustment coefficient; When the comprehensive adjustment index is greater than the first comprehensive adjustment index and less than the second comprehensive adjustment index, the adjustment coefficient is determined to be the second adjustment coefficient; When the comprehensive adjustment index is greater than or equal to the second comprehensive adjustment index, the adjustment coefficient is determined to be the third adjustment coefficient; Wherein, the first adjustment coefficient is less than the second adjustment coefficient, and the second adjustment coefficient is less than the third adjustment coefficient.

6. The solution for elevator lifecycle management driven by a cloud blockchain service platform according to claim 1, characterized in that, When determining and optimizing the initial maintenance cycle based on the aforementioned periodic impact factors to obtain the optimized maintenance cycle, the process further includes: The cycle impact factor is compared with the first cycle impact factor and the second cycle impact factor. Based on the comparison result, the optimization coefficient of the initial maintenance cycle is determined, and the product of the optimization coefficient and the initial maintenance cycle is taken as the optimized maintenance cycle; wherein, the first cycle impact factor is smaller than the second cycle impact factor. When the periodic influence factor is less than or equal to the first periodic influence factor, the optimization coefficient is determined to be the first optimization coefficient; When the periodic impact factor is greater than the first periodic impact factor and less than the second periodic impact factor, the optimization coefficient is determined to be the second optimization coefficient. When the periodic influence factor is greater than or equal to the second periodic influence factor, the optimization coefficient is determined to be the third optimization coefficient.

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