Elevator fault disaster cooperative monitoring and remote early warning control system and method

Abstract

The invention relates to the technical field of data analysis, and particularly discloses an elevator fault disaster cooperative monitoring remote early warning control system and method, and the system comprises a first collection module which is used for collecting the operation data of an elevator; the second acquisition module is used for acquiring state data of the elevator; the data reporting module is used for sending the operation data and the state data to the data analysis module; the data analysis module is used for analyzing the elevator use time of the users on each floor according to the historical operation data; the analysis module is further used for analyzing whether the elevator currently has operation faults or is affected by disasters according to the state data; the information notification module is used for sending use pause information to the users of the corresponding floors according to the use time of the elevator when the elevator fails in operation; and the server is also used for sending use pause information to users of the whole building when being influenced by external disasters. According to the technical scheme, elevator faults or disasters can be intelligently recognized, and directional information notification is carried out.

Description

Technical Field

[0001] The present invention relates to the field of data analysis technology, and in particular to a remote early warning control system and method for collaborative monitoring of elevator fault disasters. Background Art

[0002] As a core tool for vertical transportation in modern buildings, elevators are crucial for operational safety and reliability. With the acceleration of urbanization and the prevalence of high-rise buildings, the number of elevators has surged, increasing the risk of elevator failures or outages due to external disasters (such as fires and earthquakes). This can not only lead to safety incidents such as entrapment, but also seriously impact users' daily travel efficiency and experience.

[0003] Traditional elevator monitoring and early warning systems primarily focus on monitoring the equipment's operating status and diagnosing faults. Existing technologies typically deploy various sensors (such as vibration sensors, temperature sensors, and smoke detectors) to collect real-time elevator operating data (such as speed, direction, and door status) and status data (such as motor parameters, safety device status, and environmental information). This data is transmitted to a local or cloud platform for centralized analysis. The core goal is to identify potential internal equipment faults (such as motor overheating, brake failure, and leveling accuracy errors) or detect external disaster threats (such as excessive smoke concentrations or abnormally severe vibrations).

[0004] However, existing elevator monitoring and early warning technologies have significant shortcomings in user notification: when a fault or disaster is detected, the system often uses a simple group notification method to inform all users that the elevator has stopped operating. This lacks specificity, and many users who are not using the elevator or temporarily do not need it will also receive the notification, causing information interference. Information from users who truly need the elevator may be overwhelmed.

[0005] Therefore, there is an urgent need for an elevator fault disaster collaborative monitoring remote early warning control system and method that can intelligently identify elevator faults or disasters and provide targeted and accurate information notifications. Summary of the Invention

[0006] One of the purposes of the present invention is to provide a remote early warning control system for collaborative monitoring of elevator failures and disasters, which can intelligently identify elevator failures or disasters and provide targeted information notifications.

[0007] In order to solve the above technical problems, this application provides the following technical solutions:

[0008] Elevator fault disaster collaborative monitoring and remote early warning control system, including:

[0009] The first acquisition module is used to collect the operation data of the elevator;

[0010] The second acquisition module is used to collect elevator status data;

[0011] Data reporting module, used to send operation data and status data to the data analysis module;

[0012] The data analysis module is used to analyze the elevator usage time of users on each floor based on historical operation data; it is also used to analyze whether the elevator is currently operating at fault or affected by disasters based on status data;

[0013] The information notification module is used to send suspension information to users on the corresponding floors based on the elevator usage time when the elevator fails; it is also used to send suspension information to users in the entire building when affected by external disasters.

[0014] Furthermore, the operation data and status data are both time-stamped; the operation data includes uplink and downlink information, docking information, load information and door status information; the status data includes core system status information, safety device status information, mechanical status information, environmental monitoring information, and fault alarm information.

[0015] Furthermore, the data analysis module aligns and associates the stop information with the load information by timestamps; identifies a complete elevator riding event based on the combination of the call floor and the target floor in the stop information, and the change in the car load in the load information; performs usage time statistics based on the elevator riding event, and counts the frequency of elevator riding on each floor on different dates and hours of each month, and determines the hours when the elevator riding frequency is greater than the frequency threshold as the elevator usage time of the corresponding floor.

[0016] Furthermore, the data analysis module is further configured to determine whether the actual data complies with a preset operating rule, and if not, to determine that an operating fault currently exists;

[0017] It is also used to determine whether the smoke concentration in the environmental monitoring information exceeds the smoke threshold, and whether the vibration data in the mechanical status information exceeds the vibration threshold; if it exceeds the smoke threshold or the vibration threshold, it is determined to be affected by a disaster.

[0018] Furthermore, it also includes a remote control module, which is used to send a stop operation instruction to the corresponding elevator when an elevator operation failure occurs; and is also used to send a stop operation instruction to all elevators in the corresponding building when a disaster occurs.

[0019] Furthermore, it also includes a scheduling module for generating a maintenance work order based on an operating fault, and for matching the current work order with the corresponding historical maintenance work order, and estimating the current maintenance time based on the maintenance time of the historical maintenance work order.

[0020] Furthermore, the information notification module is also used to send suspension information to users on the corresponding floors based on the estimated maintenance time and elevator usage time. The suspension information includes the suspended elevator number and the estimated suspension time.

[0021] A second object of the present invention is to provide a method for collaborative monitoring and remote early warning control of elevator fault disasters using the above-mentioned system.

[0022] This solution deeply mines historical operating data, correlating and analyzing stop information, load changes, and timestamps to accurately identify high-frequency elevator usage patterns on different floors, across different date types, and within specific time periods. This allows the system to intelligently send suspension notifications only to users on the relevant floors who are currently in the elevator's high-frequency usage period and most dependent on it, effectively preventing information harassment from irrelevant users and ensuring that critical information reaches those most in need. In summary, this solution effectively identifies abnormal elevator conditions, accurately pushes information, and minimizes disruption to users. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 This is the logic block diagram of the remote early warning control system for collaborative monitoring of elevator failure disasters. DETAILED DESCRIPTION

[0024] The following is further described in detail through specific implementation methods:

[0025] Example 1

[0026] like Figure 1 As shown, the elevator fault disaster collaborative monitoring and remote early warning control system of this embodiment includes a first acquisition module, a second acquisition module, a data reporting module, a data analysis module and an information notification module.

[0027] The first acquisition module is used to collect elevator operation data. The operation data includes up and down information, parking information, load information and door status information;

[0028] Up and down information includes: running direction (up, down or standby), running time (the time spent on each run), number of starts and stops (the total number of starts and stops in a day), and standby time (the waiting time when the elevator stops at a floor but no one calls the elevator);

[0029] Stop information includes: the called floor (the floor on which the user pressed the call button), the target floor (the target floor pressed by the user in the elevator car), the actual stop floor (the floor where the elevator actually stopped), and the stop timestamp (the time when the elevator arrived at and left each stop floor);

[0030] Load information includes: car load (using a weighing device to monitor the weight in the car in real time), load change time (combined with the stop floor information to record weight changes);

[0031] Door status information includes: door opening and closing times (the total number of door openings and closings in a day), door opening and closing time (the time spent on each door opening and closing), and the number of door opening and closing obstructions.

[0032] The second acquisition module is used to collect elevator status data. Status data includes: core system status information, safety device status information, mechanical status information, environmental monitoring information, etc.

[0033] Core system status information includes drive system information (motor current, voltage, temperature; inverter status, output frequency / torque; brake status (open / closed), etc.), position and speed detection information (actual operating speed (whether overspeed / underspeed), leveling accuracy (docking position deviation), etc.), and door system information (door machine current, door position sensor, door safety touch panel / light curtain status, etc.).

[0034] Safety device status information includes: speed limiter status, safety clamp status, buffer status, etc.

[0035] Mechanical status information includes: vibration data (vibration amplitude and frequency of the car), noise data (operating noise level), etc.

[0036] Environmental monitoring information includes: smoke sensor data (smoke detector signals installed in the machine room, shaft, and car top),

[0037] Water immersion sensor data (water accumulation sensor signal in the shaft pit), temperature / humidity sensor data (temperature and humidity sensor signal installed on the top of the car), video surveillance data, etc.

[0038] Both operation data and status data are time stamped;

[0039] The data reporting module is used to send operation data and status data to the data analysis module.

[0040] The data analysis module is used to analyze the elevator usage time of users on each floor based on historical operation data; it is also used to analyze whether the elevator is currently experiencing operating failures or is affected by disasters based on status data.

[0041] Specifically, when analyzing elevator usage time, the data analysis module aligns and correlates the timestamps of stop information with load information. For example, an increase (entry) or decrease (exit) in load when the elevator stops and opens its doors at a certain floor can be correlated to the elevator's ridership at that floor.

[0042] Based on the combination of the called floor and the target floor, as well as the change in car load in the load information, a complete elevator ride event is identified. For example, a user presses the up button on the 5th floor (called floor = 5), the elevator reaches the 5th floor and opens its doors (stop floor = 5), the user enters the car and presses the 10th floor (target floor = 10), the elevator reaches the 10th floor and opens its doors (stop floor = 10), and the user leaves (the load decreases on the 10th floor). This identifies a "5th floor -> 10th floor" elevator ride event.

[0043] Based on elevator ride events, usage time statistics are collected. The frequency of elevator rides on different days and hours of each month for each floor is counted. Hours where the frequency exceeds a frequency threshold are considered the elevator usage time for the corresponding floor. Dates include weekdays, weekends, and holidays. In this example, the frequency threshold is 5 times.

[0044] During fault analysis, the data analysis module is used to organize and associate different types of status data in a structured manner. In this embodiment, the elevator identifier and timestamp are used as indexes.

[0045] It is also used to determine whether actual data conforms to preset operating rules. If not, it is determined that an operating fault exists. Operating rules include normal parameter ranges, normal signal states, and logical rules. For example, the traction motor temperature exceeds the upper limit of the rated operating range; the brake release / holding feedback signal is abnormal (the command does not arrive within the specified time after being issued); the elevator detects the door opening action at a non-level position, etc.

[0046] It is also used to determine whether the smoke concentration of the smoke sensor data exceeds the smoke threshold and whether the vibration data exceeds the vibration threshold; if it exceeds the smoke threshold or exceeds the vibration threshold, it is determined to be affected by the disaster.

[0047] The information notification module is used to send a suspension notification to users on the corresponding floor based on the elevator's usage time when an elevator malfunction occurs. It is also used to send a suspension notification to users throughout the building when an external disaster occurs. In this embodiment, the contact information of users on each floor is pre-stored to facilitate the transmission of the suspension notification.

[0048] The remote control module is used to send a stop operation command to the corresponding elevator when an elevator malfunction occurs; it is also used to send a stop operation command to all elevators in the corresponding building when a disaster occurs.

[0049] This embodiment also provides a method for collaborative monitoring and remote early warning control of elevator fault disasters, using the above-mentioned system.

[0050] By deeply mining historical operating data and correlating and analyzing stop information, load changes, and timestamps, this solution can accurately identify the high-frequency usage patterns (i.e., "elevator usage time") of elevators on different floors during different date types (such as weekdays and holidays) and specific time periods (such as morning and evening rush hours). This allows the system to intelligently send suspension notifications only to users on the relevant floors who are currently in the high-frequency usage period of the elevator and who rely most on it, effectively avoiding information harassment from irrelevant users and ensuring that key information reaches the groups that need it most.

[0051] In summary, this solution can effectively identify abnormal elevator conditions, accurately push information, and minimize interference to users.

[0052] Example 2

[0053] The difference between this embodiment and embodiment 1 is that this embodiment also includes a scheduling module for generating a maintenance work order based on an operating fault, and for matching the current work order with the corresponding historical maintenance work order, and estimating the current maintenance time based on the maintenance time of the historical maintenance work order.

[0054] The information notification module is also used to send suspension information to users on the corresponding floor based on the estimated maintenance time and elevator usage time. The suspension information includes the suspended elevator number and the estimated suspension time. The estimated suspension time is the estimated maintenance time.

[0055] Specifically, the scheduling module is used to record information on all historical maintenance work orders, including: fault type (such as traction motor overheating, door system abnormality, brake failure, etc.), maintenance response time (the time from fault reporting to engineer arrival), actual maintenance time (the time from the start of maintenance to the fault resolution), fault severity level (such as minor downtime, moderate functional abnormality, severe safety risk), elevator model / brand, maintenance personnel / team, etc.

[0056] The scheduling module also detects a new operational fault and extracts its characteristics. It then searches the historical maintenance work order database for other elevators with the same fault type, severity, and model, and calculates the maintenance time statistics. Fault characteristics include the faulty equipment component (e.g., brake, sensor, traction motor), fault code, or anomaly type (e.g., temperature exceeding the specified limit, signal timeout). In this embodiment, the median of the repair times of the retrieved work orders is used as the estimated maintenance time.

[0057] The solution of this embodiment automatically generates a maintenance work order after identifying an operational fault, and performs intelligent matching based on historical maintenance big data - by accurately screening past work orders with the same fault type, similar severity level and consistent elevator model, the median maintenance time is calculated as the estimated time for this maintenance, and the originally vague fault repair wait is converted into a quantifiable time expectation, fundamentally solving the user's anxiety about how long they have to wait, and then integrating the estimated maintenance time into the user notification. For example, when the system determines that a brake fault requires about 2 hours of repair, and the target floor (such as the 15th floor) is currently in the morning rush hour, the user will be clearly informed that "Passenger Elevator No. 3 is out of service and is expected to resume at 10:00." This allows users to clearly assess the impact and flexibly adjust their travel plans.

[0058] The above are only embodiments of the present invention. The invention is not limited to the fields involved in this implementation case. Common knowledge such as the known specific structures and characteristics in the scheme is not described in detail here. Ordinary technicians in the relevant field are aware of all common technical knowledge in the technical field to which the invention belongs before the application date or priority date, can obtain all existing technologies in the field, and have the ability to apply conventional experimental means before that date. Ordinary technicians in the relevant field can improve and implement this scheme in combination with their own abilities under the inspiration given by this application. Some typical known structures or known methods should not become obstacles for ordinary technicians in the relevant field to implement this application. It should be pointed out that for those skilled in the art, without departing from the structure of the present invention, several variations and improvements can be made, which should also be regarded as the scope of protection of the present invention. These will not affect the effect of the implementation of the present invention and the practicality of the patent. The scope of protection required by this application shall be based on the content of its claims, and the specific implementation methods and other records in the specification can be used to interpret the content of the claims.

Claims

1. Elevator fault disaster collaborative monitoring remote early warning control system, characterized by: include: The first acquisition module is used to collect the operation data of the elevator; The second acquisition module is used to collect elevator status data; Data reporting module, used to send operation data and status data to the data analysis module; Data analysis module, used to analyze the elevator usage time of users on each floor based on historical operation data; It is also used to analyze whether the elevator is currently experiencing operating failures or is affected by disasters based on status data; The information notification module is used to send suspension information to users on the corresponding floors based on the elevator usage time when the elevator fails; it is also used to send suspension information to users in the entire building when affected by external disasters.

2. The elevator fault disaster collaborative monitoring and remote early warning control system according to claim 1 is characterized by: The operation data and status data are both time-stamped; the operation data includes uplink and downlink information, docking information, load information and door status information; the status data includes core system status information, safety device status information, mechanical status information, environmental monitoring information and fault alarm information.

3. The elevator fault disaster collaborative monitoring and remote early warning control system according to claim 2 is characterized by: The data analysis module aligns and associates the docking information with the load information by performing time stamp alignment; Based on the combination of the elevator call floor and the target floor in the stop information, as well as the change in the car load in the load information, a complete elevator riding event is identified; based on the elevator riding event, the usage time statistics are performed, and the elevator riding frequency on each floor on different days and hours of each month is counted. The hours when the elevator riding frequency is greater than the frequency threshold are determined as the elevator usage time of the corresponding floor.

4. The elevator fault disaster collaborative monitoring and remote early warning control system according to claim 3 is characterized by: The data analysis module is also used to determine whether the actual data complies with the preset operating rules. If it does not comply with the operating rules, it is determined that there is an operating fault. It is also used to determine whether the smoke concentration in the environmental monitoring information exceeds the smoke threshold, and whether the vibration data in the mechanical status information exceeds the vibration threshold; If the smoke threshold or vibration threshold is exceeded, it is determined to be affected by the disaster.

5. The elevator fault disaster collaborative monitoring and remote early warning control system according to claim 4 is characterized by: It also includes a remote control module for sending a stop operation instruction to the corresponding elevator when an elevator operation failure occurs; It is also used to send a stop operation command to all elevators in the corresponding building when a disaster occurs.

6. The elevator fault disaster collaborative monitoring and remote early warning control system according to claim 5 is characterized by: It also includes a scheduling module for generating maintenance work orders based on operational failures, matching the current work order with the corresponding historical maintenance work order, and estimating the current maintenance time based on the maintenance time of the historical maintenance work order.

7. The elevator fault disaster collaborative monitoring and remote early warning control system according to claim 6, characterized in that: The information notification module is also used to send suspension information to users on the corresponding floors based on the estimated maintenance time and the elevator usage time. The suspension information includes the suspended elevator number and the estimated suspension time.

8. Elevator fault disaster collaborative monitoring and remote early warning control method, characterized in that: Use the system according to any one of claims 1 to 7.

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