CN110713090A - System and method for realizing real-time monitoring of abnormal state of multi-target elevator - Google Patents
System and method for realizing real-time monitoring of abnormal state of multi-target elevator Download PDFInfo
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- CN110713090A CN110713090A CN201911131618.0A CN201911131618A CN110713090A CN 110713090 A CN110713090 A CN 110713090A CN 201911131618 A CN201911131618 A CN 201911131618A CN 110713090 A CN110713090 A CN 110713090A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B5/00—Applications of checking, fault-correcting, or safety devices in elevators
- B66B5/0006—Monitoring devices or performance analysers
- B66B5/0018—Devices monitoring the operating condition of the elevator system
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
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- Medical Informatics (AREA)
- Computer Networks & Wireless Communication (AREA)
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- Indicating And Signalling Devices For Elevators (AREA)
- Maintenance And Inspection Apparatuses For Elevators (AREA)
Abstract
The invention discloses a system and a method for realizing real-time monitoring of abnormal states of a multi-target elevator, and belongs to the technical field of big data application. The system for realizing the real-time monitoring of the abnormal state of the multi-target elevator comprises a data acquisition module, a data transmission module, a data processing module, a data visualization module and an alarm module, wherein the data acquisition module is used for acquiring information data of the running state of the elevator, the data transmission module acquires the information data acquired by the data acquisition module and transmits the acquired data information to the data processing module, and the data processing module sends the analyzed result data to the data visualization module. The system for realizing the real-time monitoring of the abnormal state of the multi-target elevator can improve the throughput of the monitoring of the state data of the elevator and simultaneously reduce the delay to the millisecond level, and has good popularization and application values.
Description
Technical Field
The invention relates to the technical field of big data application, and particularly provides a system and a method for realizing real-time monitoring of abnormal states of a multi-target elevator.
Background
With the development of market economy and the continuous expansion of urban scale, the floor industry rises rapidly, and the elevator as a necessary bearing tool for going in and out of high-rise buildings gradually becomes an indispensable part of high-rise buildings such as houses, hotels, shopping malls, office buildings and the like. However, with the rapid increase of the usage amount of the elevator, the elevator is not in place in maintenance and supervision, so that elevator safety accidents happen occasionally, and the living standard and quality of residents are seriously affected. Therefore, the realization of 24-hour real-time monitoring and alarm reporting of the elevator running state becomes a problem which needs to be solved urgently by all levels of supervision departments.
The current era of big data is entered, data is changed from a traditional database into 'massive data', the data in the traditional database is only used as a processing object, and the data of a big data platform is used as a resource to analyze abnormal states, alarm thresholds and the like from the 'massive data'. The appearance of big data subverts the traditional data processing thinking and brings huge reform on the aspects of data sources, data processing modes, data thinking and the like.
The large data technology is applied in the fields of business, internet, industry and the like, the large data is also applied in elevator remote monitoring, at present, most supervision departments regularly acquire limited operation state information of elevators by means of elevator regular inspection, supervision and the like, and each elevator maintenance enterprise adopts a mechanism for safety information management of part of elevators with information acquisition capacity, so that centralized management cannot be achieved. The fault management excessively depends on manpower, and maintenance personnel cannot acquire accurate elevator fault information in real time, so that the problems of overlong processing time and the like are caused.
Disclosure of Invention
The technical task of the invention is to provide a system for realizing the real-time monitoring of the abnormal state of the multi-target elevator, which can realize the centralized storage of mass data and the processing of millisecond-level delay, improve the throughput of the monitoring of the state data of the elevator and simultaneously reduce the delay to millisecond level.
The invention further aims to provide a method for realizing the real-time monitoring of the abnormal state of the multi-target elevator.
In order to achieve the purpose, the invention provides the following technical scheme:
the utility model provides a realize system of many target elevator abnormal state real-time supervision, this system is based on flink STREAMING calculation frame, including the data acquisition module, data transmission module, data processing module, data visualization module and alarm module, the data acquisition module is used for gathering elevator running state information data, data transmission module is connected with the data acquisition module, acquire the information data that the data acquisition module gathered, and transmit the data information who acquires for data processing module, data processing module sends the result data after the analysis to data visualization module, send abnormal data to alarm module simultaneously.
The system for realizing the real-time monitoring of the abnormal state of the multi-target elevator comprises the following working procedures: the data acquisition module acquires elevator running state information data and sends the information data to the data transmission module; the data transmission module transmits the acquired elevator running state information data to the kafka distributed message processing component by using a network protocol and simultaneously transmits the information to the hdfs backup; the kafka distributed message processing component sends the information data to the data processing module, and the information data is analyzed and processed in real time; the data processing module sends the analyzed result data to the data visualization module and sends the abnormal data to the alarm module; and the alarm module informs relevant processing personnel of the alarm information at the first time according to the configured alarm rule for processing.
Preferably, the system for realizing the real-time monitoring of the abnormal state of the multi-target elevator further comprises hdfs and kafka, wherein the hdfs and the kafka are respectively connected with the data transmission module, and the data transmission module transmits the information data to the kafka distributed message processing component by using a network protocol and simultaneously transmits the information data to the hdfs.
Preferably, the information data collected by the data collection module comprises elevator position, running direction, bearing, speed and acceleration.
Preferably, the data transmission module acquires the data in real time by subscribing to the topic message of kafka.
Preferably, the data processing module submits the acquired data to the Flink cluster managed by the resource scheduling component yann to perform real-time analysis processing on the data.
A method for realizing real-time monitoring of abnormal states of a multi-target elevator comprises the following steps:
s1, the data acquisition module acquires information data of the running state of the elevator and sends the information data to the data transmission module;
s2, the data transmission module transmits the acquired elevator running state information data to the kafka distributed message processing component by using a network protocol and simultaneously transmits the information to the hdfs backup;
s3, the kafka distributed message processing component sends the information data to the data processing module, and the information data is analyzed and processed in real time;
s4, the data processing module sends the analyzed result data to the data visualization module, and sends the abnormal data to the alarm module;
and S5, the alarm module informs the processing personnel of the alarm information according to the configured alarm rule.
Preferably, the information data collected by the data collection module comprises elevator position, running direction, bearing, speed and acceleration.
Preferably, the data transmission module acquires the data in real time by subscribing to the topic message of kafka.
Preferably, the data processing module submits the acquired data to the Flink cluster managed by the resource scheduling component yann to perform real-time analysis processing on the data.
Compared with the prior art, the method for realizing the real-time monitoring of the abnormal state of the multi-target elevator has the following outstanding beneficial effects: the method for realizing the real-time monitoring of the abnormal state of the multi-target elevator can realize the centralized supervision of mass data of a plurality of elevators and the processing of millisecond-level delay, improves the throughput of elevator state data monitoring and simultaneously reduces the delay to millisecond level, and has good popularization and application values.
Drawings
Fig. 1 is a flow chart of the method for realizing the real-time monitoring of the abnormal state of the multi-target elevator.
Detailed Description
The system and method for realizing the real-time monitoring of the abnormal state of the multi-target elevator of the invention will be further described in detail with reference to the attached drawings and embodiments.
Examples
As shown in FIG. 1, the system for realizing the real-time monitoring of the abnormal state of the multi-target elevator is based on a flink streaming computing framework and comprises a data acquisition module, a data transmission module, a data processing module, a data visualization module, an alarm module, hdfs and kafka.
The data acquisition module is used for acquiring information data of the running state of the elevator, and the information data acquired by the data acquisition module comprises the position, the running direction, the bearing, the speed and the acceleration of the elevator.
The data transmission module is connected with the data acquisition module, acquires information data acquired by the data acquisition module, and transmits the acquired data information to the data processing module. And the data transmission module acquires data in real time by subscribing the theme message of kafka.
hdfs and kafka are respectively connected with the data transmission module, and the data transmission module transmits the information data to the kafka distributed message processing component by using a network protocol and simultaneously transmits the information data to hdfs.
And the data processing module sends the analyzed result data to the data visualization module and sends the abnormal data to the alarm module.
The data processing module submits the acquired data to the Flink cluster managed by the resource scheduling component yann to perform real-time analysis processing on the data.
The system for realizing the real-time monitoring of the abnormal state of the multi-target elevator comprises the following working procedures: the data acquisition module acquires elevator running state information data and sends the information data to the data transmission module; the data transmission module transmits the acquired elevator running state information data to the kafka distributed message processing component by using a network protocol and simultaneously transmits the information to the hdfs backup; the kafka distributed message processing component sends the information data to the data processing module, and the information data is analyzed and processed in real time; the data processing module sends the analyzed result data to the data visualization module and sends the abnormal data to the alarm module; and the alarm module informs relevant processing personnel of the alarm information at the first time according to the configured alarm rule for processing.
The invention discloses a method for realizing real-time monitoring of abnormal states of a multi-target elevator, which comprises the following steps of:
and S1, the data acquisition module acquires the information data of the running state of the elevator and sends the information data to the data transmission module.
The information data collected by the data collection module comprises the position, the running direction, the bearing, the speed and the acceleration of the elevator.
And S2, the data transmission module transmits the acquired elevator running state information data to the kafka distributed message processing component by using a network protocol and simultaneously transmits the information to the hdfs backup.
And the data transmission module acquires data in real time by subscribing the theme message of kafka.
And S3, sending the information data to a data processing module by the kafka distributed message processing component, and analyzing and processing the information data in real time.
And S4, the data processing module sends the analyzed result data to the data visualization module, and sends the abnormal data to the alarm module.
The data processing module submits the acquired data to the Flink cluster managed by the resource scheduling component yann to perform real-time analysis processing on the data.
And S5, the alarm module informs the processing personnel of the alarm information according to the configured alarm rule. The above-described embodiments are merely preferred embodiments of the present invention, and general changes and substitutions by those skilled in the art within the technical scope of the present invention are included in the protection scope of the present invention.
Claims (9)
1. The utility model provides a system for realize abnormal state real-time supervision of multi-target elevator which characterized in that: the system is based on a flink flow type calculation framework and comprises a data acquisition module, a data transmission module, a data processing module, a data visualization module and an alarm module, wherein the data acquisition module is used for acquiring information data of the running state of an elevator, the data transmission module is connected with the data acquisition module, information data acquired by the data acquisition module are acquired, the acquired data information is transmitted to the data processing module, the data processing module sends analyzed result data to the data visualization module, and meanwhile, abnormal data are sent to the alarm module.
2. The system for realizing real-time monitoring of the abnormal state of the multi-target elevator as claimed in claim 1, wherein: the system also comprises hdfs and kafka which are respectively connected with the data transmission module, and the data transmission module transmits the information data to the kafka distributed message processing component by using a network protocol and simultaneously transmits the information data to the hdfs.
3. The system for realizing the real-time monitoring of the abnormal state of the multi-target elevator as claimed in claim 2, wherein: the information data collected by the data collection module comprises the position, the running direction, the bearing, the speed and the acceleration of the elevator.
4. The system for realizing real-time monitoring of the abnormal state of the multi-target elevator as claimed in claim 3, wherein: and the data transmission module acquires data in real time by subscribing the theme message of kafka.
5. The system for realizing the real-time monitoring of the abnormal state of the multi-target elevator as claimed in claim 4, wherein: the data processing module submits the acquired data to the Flink cluster managed by the resource scheduling component yann to perform real-time analysis processing on the data.
6. A method for realizing real-time monitoring of abnormal states of a multi-target elevator is characterized by comprising the following steps: the method comprises the following steps:
s1, the data acquisition module acquires information data of the running state of the elevator and sends the information data to the data transmission module;
s2, the data transmission module transmits the acquired elevator running state information data to the kafka distributed message processing component by using a network protocol and simultaneously transmits the information to the hdfs backup;
s3, the kafka distributed message processing component sends the information data to the data processing module, and the information data is analyzed and processed in real time;
s4, the data processing module sends the analyzed result data to the data visualization module, and sends the abnormal data to the alarm module;
and S5, the alarm module informs the processing personnel of the alarm information according to the configured alarm rule.
7. The method for realizing the real-time monitoring of the abnormal state of the multi-target elevator as claimed in claim 6, wherein: the information data collected by the data collection module comprises the position, the running direction, the bearing, the speed and the acceleration of the elevator.
8. The method for realizing the real-time monitoring of the abnormal state of the multi-target elevator as claimed in claim 7, wherein: and the data transmission module acquires data in real time by subscribing the theme message of kafka.
9. The method for realizing the real-time monitoring of the abnormal state of the multi-target elevator as claimed in claim 8, wherein: the data processing module submits the acquired data to the Flink cluster managed by the resource scheduling component yann to perform real-time analysis processing on the data.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111517192A (en) * | 2020-03-03 | 2020-08-11 | 湖南长信畅中科技股份有限公司 | Intelligent Internet of things elevator supervision platform system |
| CN113844976A (en) * | 2021-09-10 | 2021-12-28 | 北京声智科技有限公司 | Alarm data processing method and device, computer equipment and storage medium |
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| CN108584588A (en) * | 2017-12-31 | 2018-09-28 | 浙江工业大学 | A kind of tor door faults detection method based on extensive flow data |
| JP2018167960A (en) * | 2017-03-30 | 2018-11-01 | フジテック株式会社 | Information processing device |
| KR20190049602A (en) * | 2017-10-31 | 2019-05-09 | (주)엠투엠테크 | IoT based elevator pervasive autonomous system and method |
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Patent Citations (4)
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| CN104944240A (en) * | 2015-05-19 | 2015-09-30 | 重庆大学 | Elevator equipment state monitoring system based on large data technology |
| JP2018167960A (en) * | 2017-03-30 | 2018-11-01 | フジテック株式会社 | Information processing device |
| KR20190049602A (en) * | 2017-10-31 | 2019-05-09 | (주)엠투엠테크 | IoT based elevator pervasive autonomous system and method |
| CN108584588A (en) * | 2017-12-31 | 2018-09-28 | 浙江工业大学 | A kind of tor door faults detection method based on extensive flow data |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN111517192A (en) * | 2020-03-03 | 2020-08-11 | 湖南长信畅中科技股份有限公司 | Intelligent Internet of things elevator supervision platform system |
| CN113844976A (en) * | 2021-09-10 | 2021-12-28 | 北京声智科技有限公司 | Alarm data processing method and device, computer equipment and storage medium |
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Application publication date: 20200121 |