Elevator operation button failure analysis and elimination method based on internet of things and big data

Abstract

The application discloses an elevator operation button failure analysis and elimination method based on the Internet of Things and big data, collects operation signals of elevator operation buttons by using a data acquisition device, and uploads the signals to a cloud platform after a series of processing such as data filtering, cleaning, screening and analysis, so that the function state of the elevator operation buttons is obtained by statistical calculation of the data by the cloud platform. The application records the instruction information of the elevator operation buttons by letting the data acquisition device work independently, formats the information uniformly, uploads the information to the cloud platform for statistics, calculates the statistical data, judges the actual state of the elevator operation buttons according to the calculation result, and issues corresponding work orders to the maintenance system; the application can independently monitor and judge whether the elevator operation buttons are invalid, and execute different processing according to the state, so that the invalid elevator operation buttons can be maintained in time and effectively, and the safety and reliability of elevator operation are improved.

Description

Technical Field

[0001] This invention relates to the field of elevator technology, and in particular to a method for analyzing and troubleshooting elevator operation button failures based on the Internet of Things and big data. Background Technology

[0002] Elevators have become an indispensable means of transportation in people's lives, undertaking the important tasks of passenger and freight transport. People are paying more and more attention to the safe operation of elevators, which in turn depends on the safe and reliable functioning of the operating buttons.

[0003] Currently, elevator systems are all offline, and elevator operation data cannot be obtained automatically in real time, nor can the elevator operation status be obtained immediately. Once the elevator operation buttons malfunction, repairs can only be reported in the traditional way. Specifically, if a passenger discovers a problem with the elevator button during use, the passenger reports it to the elevator management unit, which then contacts the elevator maintenance unit for repair. Only then can the maintenance unit arrange for someone to repair it.

[0004] Traditional repair methods are time-consuming, taking a long time from reporting a problem to actual repairs. If the elevator stops operating during this process, it will cause great inconvenience to passengers. If the elevator continues to operate, it will inevitably pose a great safety risk, putting passengers' personal safety at risk.

[0005] Moreover, traditional operation button failure reporting relies on passive manual discovery. It cannot autonomously detect operation button failures or abnormalities, nor can it analyze and judge whether there are potential risks of operation button failures or abnormalities, thus limiting the safety and reliability of elevator operation.

[0006] Therefore, the existing traditional methods of detecting malfunctions or abnormalities in operation buttons and reporting them for repair have problems such as long repair processes, disruption to passenger use of elevators, and significant safety hazards. Summary of the Invention

[0007] The purpose of this invention is to provide a method and analysis approach for analyzing and troubleshooting elevator control button malfunctions based on the Internet of Things and big data. This invention can automatically monitor and determine whether elevator control buttons are malfunctioning or abnormal and automatically report repairs, thereby improving the safety and reliability of elevator operation.

[0008] The technical solution of this invention: a method for analyzing and troubleshooting elevator operation buttons based on the Internet of Things and big data, comprising the following steps:

[0009] A. Collect information on elevator operation button commands;

[0010] B. Perform standardized formatting on the collected information;

[0011] C. Perform statistical analysis on the formatted data;

[0012] D. The statistically analyzed data is uploaded to the cloud platform;

[0013] E. Perform calculations based on the received data;

[0014] F. Determine the status of the elevator operation buttons based on the calculation results and provide the determination results, including normal function, abnormal function, and functional failure.

[0015] G. Send corresponding instructions to the maintenance system based on the judgment result; the maintenance system will then perform the corresponding repair or inspection work order based on the instructions.

[0016] The aforementioned method for analyzing and eliminating elevator operation button failures based on the Internet of Things and big data involves step A, which uses a data acquisition device to collect information about elevator operation button commands; the information includes at least the address code, operation time, and operation duration.

[0017] The aforementioned method for analyzing and eliminating elevator operation button failures based on the Internet of Things and big data includes, in step C, statistical data that includes at least the number of times each elevator button was operated, the operation time, and the operation duration.

[0018] The aforementioned method for analyzing and eliminating elevator operation button failures based on the Internet of Things and big data, specifically the calculations described in step E, are as follows:

[0019] E1. The number of times the buttons on each floor of the elevator are pressed is counted at a frequency of once per hour, and the result is T.

[0020] E2. Based on T obtained from E1, the number of operations on each floor button of the elevator is counted with a unit cycle as the statistical frequency, and the result is D.

[0021] E3. Based on D obtained from E2, the daily average number of operations of the buttons on each floor of the elevator is statistically analyzed with the statistical period as the statistical frequency, and the result is W.

[0022] E4. Perform calculations based on the obtained T, D, and W.

[0023] The aforementioned method for analyzing and eliminating elevator operation button failures based on the Internet of Things and big data, specifically the calculation in step E4, is as follows:

[0024] E4.1 Calculate the ratio: W / D = X;

[0025] E4.2 Calculate the difference: |W1-D|=Y, where W1 is the number of operations on the corresponding date within the statistical period.

[0026] E4.3 Compare the changing trends of the ratio and the difference; if the changing trends are consistent, the data is valid; if the changing trends are inconsistent, the data is invalid.

[0027] The aforementioned method for analyzing and eliminating elevator operation button failures based on the Internet of Things and big data, specifically the result determination mentioned in step F, is as follows:

[0028] F1. If X≤X1 and N1≥N, the function is judged to be abnormal; if X=0, the function is judged to be ineffective; X1 and N are both predetermined values, N is the predetermined number of times, and N1 is the actual number of times X≤X1; otherwise, the function is judged to be normal.

[0029] If F2, Y≤X2 and N2≥N, then the function is judged as abnormal; if Y=W1, then the function is judged as failed; X2 and N are both predetermined values, N is a predetermined number of times, and N2 is the actual number of times Y≤X2; otherwise, the function is judged as normal.

[0030] The aforementioned method for analyzing and troubleshooting elevator operation buttons based on the Internet of Things and big data, specifically step G, is as follows:

[0031] G1. When the judgment result is a functional abnormality, the cloud platform will automatically generate a checklist and send it to the maintenance system, requiring the maintenance system to check the elevator operation buttons with the functional abnormality during the most recent maintenance or inspection.

[0032] G2. When the judgment result is that the function is malfunctioning, the cloud platform will automatically generate a repair order and send it to the maintenance system, requiring the maintenance system to immediately dispatch a repair order to fix the elevator operation button with the malfunctioning function.

[0033] G3, the maintenance system will feed back the processing results to the cloud platform after the inspection or repair is completed;

[0034] G4, the cloud platform automatically learns and corrects X1, X2 and N based on the feedback from G3.

[0035] Compared with existing technologies, this invention enables the data acquisition device to work autonomously, listen to, record and analyze the instruction information of each elevator operation button on the elevator, perform unified formatting and statistical processing of the instruction information, and then upload it to the cloud platform for centralized storage and calculation. The statistical data is calculated using corresponding statistical calculation methods, and finally the actual status of the elevator operation button is judged based on the calculation results, thereby issuing the corresponding work order to the maintenance system.

[0036] Using this invention, data (instruction information) from elevator operation buttons can be automatically and in real time acquired, stored, and reported without the need for manual instruction. This results in more timely and accurate data acquisition. After acquiring the data, the cloud platform performs timely statistical calculations and can immediately determine the status of the elevator operation buttons based on the calculation results. This allows the system to directly issue corresponding maintenance or inspection work orders to the maintenance system, enabling it to arrange maintenance personnel for maintenance. Compared to the traditional method that requires manual reporting before work orders are generated and maintenance is arranged, this application offers significantly higher real-time performance.

[0037] This application can autonomously monitor and determine whether elevator operation buttons are malfunctioning, and perform different actions according to their status, ensuring timely and effective maintenance of malfunctioning elevator operation buttons, thereby improving the safety and reliability of elevator operation.

[0038] Therefore, this invention can automatically monitor and determine whether elevator operation buttons are malfunctioning or abnormal and report the problem, thereby improving the safety and reliability of elevator operation.

[0039] Furthermore, this application uses two calculation methods, ratio and difference, to calculate the functional status of elevator operation buttons, and uses the comparison of the trend changes between the ratio and the difference to judge whether the calculation result is valid, thereby ensuring that the calculation result is accurate and valid. Attached Figure Description

[0040] Figure 1 This is a flowchart illustrating the present invention;

[0041] Figure 2 This is a schematic diagram of the calculation method of the present invention. Detailed Implementation

[0042] The present invention will be further described below with reference to the accompanying drawings and embodiments, but this should not be construed as limiting the present invention.

[0043] Example. A method for analyzing and troubleshooting elevator operation buttons based on the Internet of Things and big data, such as... Figure 1 As shown, the process includes the following:

[0044] A. Collect information on elevator operation button commands;

[0045] B. Perform standardized formatting on the collected information;

[0046] C. Perform statistical analysis on the formatted data;

[0047] D. The statistically analyzed data is uploaded to the cloud platform;

[0048] E. Perform calculations based on the received data;

[0049] F. Determine the status of the elevator operation buttons based on the calculation results and provide the determination results, including normal function, abnormal function, and functional failure.

[0050] G. Send corresponding instructions to the maintenance system based on the judgment result; the maintenance system dispatches corresponding repair or inspection work orders based on the instructions.

[0051] Step A involves collecting information about elevator operation button commands using a data acquisition device. This information includes address code, operation time, operation duration, registered external call floor, registered internal call floor, door closing command, button address code, button function code, and duration.

[0052] The data acquisition equipment includes data transmission devices installed on the car top, control cabinet, or shaft, and data acquisition terminals installed in the machine room. The data transmission devices collect the operation command signals from the elevator operation buttons and transmit them to the data acquisition terminals. The data acquisition terminals then summarize the data, perform unified data formatting, and upload it to the cloud platform.

[0053] The cloud platform performs logical analysis and processing on the collected data to form preliminary intelligent algorithm logic. As the data continues to accumulate and update, the machine learns automatically to optimize the algorithm logic, ensuring that the accuracy of the calculation is infinitely close to the actual situation.

[0054] The data collected in step C includes the number of times each elevator button was pressed, the pressing time, the pressing duration, and the elevator number.

[0055] The calculation described in step E is as follows:

[0056] E1. The number of times the buttons on each floor of the elevator are pressed is counted at a frequency of once per hour, and the result is T.

[0057] E2. Based on T obtained from E1, the number of operations on each floor button of the elevator is counted with a unit cycle as the statistical frequency, and the result is D.

[0058] E3. Based on D obtained from E2, the daily average number of operations of the buttons on each floor of the elevator is statistically analyzed with the statistical period as the statistical frequency, and the result is W.

[0059] E4. Perform calculations based on the obtained T, D, and W.

[0060] The calculation described in step E4 is as follows:

[0061] E4.1 Calculate the ratio: W / D = X;

[0062] E4.2 Calculate the difference: |W1-D|=Y, where W1 is the number of operations on the corresponding date within the statistical period.

[0063] E4.3 Compare the changing trends of the ratio and the difference; if the changing trends are consistent, the data is valid; if the changing trends are inconsistent, the data is invalid.

[0064] The result determination mentioned in step F is as follows:

[0065] F1. If X≤X1 and N1≥N, the function is judged to be abnormal; if X=0, the function is judged to be ineffective; X1 and N are both predetermined values, N is the predetermined number of times, and N1 is the actual number of times X≤X1; otherwise, the function is judged to be normal.

[0066] If F2, Y≤X2 and N2≥N, then the function is judged as abnormal; if Y=W1, then the function is judged as failed; X2 and N are both predetermined values, N is a predetermined number of times, and N2 is the actual number of times Y≤X2; otherwise, the function is judged as normal.

[0067] The specific content of step G is as follows:

[0068] G1. When the judgment result is a functional abnormality, the cloud platform will automatically generate a checklist and send it to the maintenance system, requiring the maintenance system to check the elevator operation buttons with the functional abnormality during the most recent maintenance or inspection.

[0069] G2. When the judgment result is that the function is malfunctioning, the cloud platform will automatically generate a repair order and send it to the maintenance system, requiring the maintenance system to immediately dispatch a repair order to fix the elevator operation button with the malfunctioning function.

[0070] G3, the maintenance system will feed back the processing results to the cloud platform after the inspection or repair is completed;

[0071] G4, the cloud platform automatically learns and corrects X1, X2 and N based on the feedback from G3.

Claims

1. A method for elevator operation button failure analysis and exclusion based on Internet of Things and Big Data, characterized in that, The process includes the following steps: A. Collect information on elevator operation button commands; B. Perform standardized formatting on the collected information; C. Perform statistical analysis on the formatted data; D. The statistically analyzed data is uploaded to the cloud platform; E. Perform calculations based on the received data; F. Determine the status of the elevator operation buttons based on the calculation results. The determination results include normal function, abnormal function, and functional failure. G. Send corresponding instructions to the maintenance system based on the judgment result; the maintenance system will then execute the corresponding repair or inspection work order based on the instructions. The calculation described in step E is as follows: E1. The number of times the buttons on each floor of the elevator are pressed is counted at a frequency of once per hour, and the result is T. E2. Based on T obtained from E1, the number of operations on each floor button of the elevator is counted with a unit cycle as the statistical frequency, and the result is D. E3. Based on D obtained from E2, the daily average number of operations of the buttons on each floor of the elevator is statistically analyzed with the statistical period as the statistical frequency, and the result is W. E4. Perform calculations based on the obtained T, D, and W; The calculation described in step E4 is as follows: E4.1 Calculate the ratio: W / D=X; E4.2 Calculate the difference: |W1-D|=Y, where W1 is the number of operations on the corresponding date within the statistical period. E4.3 Compare the changing trends of the ratio and the difference; if the changing trends are consistent, the data is valid; if the changing trends are inconsistent, the data is invalid. The result determination mentioned in step F is as follows: F1. If X≤X1 and N1≥N, the function is judged to be abnormal; if X=0, the function is judged to be ineffective; X1 and N are both predetermined values, N is the predetermined number of times, and N1 is the actual number of times X≤X1; otherwise, the function is judged to be normal. If F2, Y≤X2 and N2≥N, then the function is judged as abnormal; if Y=W1, then the function is judged as failed; X2 and N are both predetermined values, N is a predetermined number of times, and N2 is the actual number of times Y≤X2; otherwise, the function is judged as normal.

2. The Internet of Things and Big Data based elevator operation button failure analysis exclusion method as claimed in claim 1, wherein: Step A involves acquiring information about elevator operation button commands using a data acquisition device; the information includes at least the address code, operation time, and operation duration.

3. The Internet of Things and Big Data based elevator operation button failure analysis exclusion method as claimed in claim 1, wherein: The data collected in step C includes at least the number of times each elevator button was pressed, the pressing time, and the pressing duration. 4.The IoT and big data based elevator operation button failure analysis and exclusion method according to claim 1, wherein, The specific content of step G is as follows: G1. When the judgment result is a functional abnormality, the cloud platform will automatically generate a checklist and send it to the maintenance system, requiring the maintenance system to check the elevator operation buttons with the functional abnormality during the most recent maintenance or inspection. G2. When the judgment result is that the function is malfunctioning, the cloud platform will automatically generate a repair order and send it to the maintenance system, requiring the maintenance system to immediately dispatch a repair order to fix the elevator operation button with the malfunctioning function. G3, the maintenance system will feed back the processing results to the cloud platform after the inspection or repair is completed; G4, the cloud platform automatically learns and corrects X1, X2 and N based on the feedback from G3.

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