CN109343427A - A kind of monitoring method and its system for belt lane - Google Patents
A kind of monitoring method and its system for belt lane Download PDFInfo
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- CN109343427A CN109343427A CN201811383521.4A CN201811383521A CN109343427A CN 109343427 A CN109343427 A CN 109343427A CN 201811383521 A CN201811383521 A CN 201811383521A CN 109343427 A CN109343427 A CN 109343427A
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
- G05B19/042—Programme control other than numerical control, i.e. in sequence controllers or logic controllers using digital processors
- G05B19/0428—Safety, monitoring
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/20—Pc systems
- G05B2219/24—Pc safety
- G05B2219/24024—Safety, surveillance
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- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Analysing Materials By The Use Of Radiation (AREA)
Abstract
The present invention relates to coal mine leather belt lane monitoring technology fields, and in particular to a kind of monitoring method and its system for belt lane.The monitoring method acquires every monitoring data in belt lane by terminal device, and the monitoring data is sent to cloud platform；The monitoring data is analyzed by cloud platform, judges whether the monitoring data exception occurs；When the monitoring data occurs abnormal; cloud platform is alarmed; even the distance of main shaft belt main entry, the gradient are big; it does not need manually to carry out inspection; it can be avoided the generation of safety accident; and it does not need to occupy the time progress inspection shut down, can guarantee the real-time running data for acquiring belt.
Description
Technical field
The present invention relates to coal mine leather belt lane monitoring technology fields, and in particular to a kind of monitoring method for belt lane and its
System.
Background technique
Belt lane is the tunnel with Belt Conveying raw coal.
The method that the existing operation data for belt lane is monitored is, in transporting equipment operation, carries out artificial
Inspection, or when transporting equipment is out of service, carry out inspection.
Inventor is in practice, it has been found that exist in the prior art following defect:
The distance of the main shaft belt main entry of Part Coal Mine, the gradient is big, such as distance is up to 670M, and the gradient is up to 26.7 °, people
When work inspection, since its gradient is big, the coal cinder transported on belt can jump out from time to time, be easy to happen danger when someone's inspection
Danger, risk is high, and when daily maintenance down, then carry out inspection, then the real-time traffic information of belt can not be understood in real time, held
Easily lead to the generation of safety accident.
Summary of the invention
In order to solve the above-mentioned technical problem, the object of the present invention is to provide a kind of monitoring method for belt lane,
Technical solution used by this method is as follows:
A kind of monitoring method for belt lane, the monitoring method include:
Every monitoring data in belt lane is acquired by terminal device, and the monitoring data is sent to cloud platform；
The monitoring data is analyzed by cloud platform, judges whether the monitoring data exception occurs；
When the monitoring data occurs abnormal, cloud platform is alarmed.
Further, the monitoring data includes one in belt operation image, temperature data, smoke data and air speed data
Kind is a variety of.
It is further, described that the monitoring data is analyzed by cloud platform, comprising the following steps:
Extract the realtime image data in the monitoring data；
The realtime image data similarity that carries out corresponding with the preset image data of cloud platform is compared, it is described default
Image data be normal operating condition when image data；
When the result that the similarity compares is less than preset threshold, it is abnormal to determine that the realtime image data occurs.
Further, the realtime image data includes belt operation image data and belt X-ray detectoscope flaw detection image
One or more of data.
Further, described that the monitoring data is analyzed by cloud platform, further comprising the steps of:
Extract the temperature data in the monitoring data；
When monitoring the temperature data as the variation of time is in lasting rising, judge the temperature data whether by
Gradually close to the preset reliability temperature threshold of cloud platform；
When the temperature data moves closer to the preset reliability temperature threshold of the cloud platform, the temperature data is determined
Occur abnormal.
On the other hand, it is another object of the present invention to provide a kind of monitoring system for belt lane, the monitoring systems
Technical solution used by uniting is as follows:
A kind of monitoring system for belt lane, the monitoring system include:
Acquisition module for acquiring every monitoring data in belt lane by terminal device, and the monitoring data is sent out
It send to cloud platform；
Analyze and determine that module judges that the monitoring data is for analyzing by cloud platform the monitoring data
No appearance is abnormal；
Alarm module, for when the monitoring data occurs abnormal, cloud platform to be alarmed.
Further, the monitoring data includes one in belt operation image, temperature data, smoke data and air speed data
Kind is a variety of.
Further, the analytical judgment module, comprising:
Image zooming-out module, for extracting the realtime image data in the monitoring data；
Image analysis module, for carrying out phase for the realtime image data is corresponding with the preset image data of cloud platform
It is compared like degree, image data when the preset image data is normal operating condition；
Image abnormity judgment module determines the reality when result for comparing in the similarity is less than preset threshold
When image data occur it is abnormal.
Further, the realtime image data includes belt operation image data and belt X-ray detectoscope flaw detection image
One or more of data.
Further, the analytical judgment module, comprising:
Data extraction module, for extracting the temperature data in the monitoring data；
Data analysis module, for when monitor the temperature data as the variation of time is in lasting rising, judgement
Whether the temperature data moves closer to the preset reliability temperature threshold of cloud platform；
Data exception judgment module, for moving closer to the preset safe temperature threshold of the cloud platform in the temperature data
When value, it is abnormal to determine that the temperature data occurs.
The invention has the following beneficial effects:
The present invention acquires every monitoring data in belt lane by terminal device, and the monitoring data is sent to cloud and is put down
Platform；The monitoring data is analyzed by cloud platform, judges whether the monitoring data exception occurs；When the monitoring number
When according to occurring abnormal, cloud platform is alarmed, even the distance of main shaft belt main entry, the gradient are big, does not need manually to carry out
Inspection, can be avoided the generation of safety accident, and not need to occupy the time progress inspection shut down, and can guarantee to acquire belt
Real-time running data.
Detailed description of the invention
Fig. 1 is a kind of method flow diagram of the monitoring method for belt lane provided by one embodiment of the present invention；
Fig. 2 is a kind of structural block diagram for monitoring system for belt lane that another embodiment of the present invention provides.
Specific embodiment
Below by specific embodiment combination attached drawing, the present invention will be described in detail, it should be noted that in the feelings not conflicted
Under condition, the feature in embodiment and embodiment in the present invention be can be combined with each other, and the scope of protection of the present invention is not limited thereto.
Referring to Fig. 1, it illustrates a kind of method flow diagram of the monitoring method for belt lane provided by the invention, it should
Monitoring method includes:
Step 101, every monitoring data in belt lane is acquired by terminal device, and the monitoring data is sent to cloud
Platform.
The terminal device can be intelligent monitoring terminal, be able to detect the necessary monitoring parameter in belt lane, the monitoring number
According to including one or more of live realtime image data, temperature data, smoke data and air speed data.
Step 102, the monitoring data is analyzed by cloud platform, it is different judges whether the monitoring data occurs
Often.
Cloud platform carries out big data analysis to the situation of change of every monitoring data, to the crucial prison for having the trend of causing danger
Control the monitoring that parameter carries out emphasis by cloud platform.
Preferably, described that the monitoring data is analyzed by cloud platform, it further include that cloud platform extracts monitoring data
In realtime image data；The realtime image data similarity that carries out corresponding with the preset image data of cloud platform is compared,
Image data when the preset image data is normal operating condition；It is less than default threshold in the result that the similarity compares
When value, it is abnormal to determine that the realtime image data occurs.For example, when running coal or protective cover shifts, institute's acquired image
There are biggish differences with normal pre-set image data for data, and after being compared the two, obtained comparison result is super
Threshold value out, cloud platform carries out automatic alarm at this time.For another example, to the flaw detection data and figure of the well head belt x-ray instrument acquired in real time
As being monitored, and the image of acquisition and data are compared with preset respective image and threshold value, when judging in belt
Wirerope when the abnormal datas such as occurring being broken, cloud platform and alarm notify corresponding personnel to verify in time, it is unnecessary to prevent
Industrial accident occur.
Preferably, described that the monitoring data is analyzed by cloud platform, it further include extracting in the monitoring data
Temperature data；When monitoring the temperature data as the variation of time is in lasting rising, judge that the temperature data is
It is no to move closer to the preset reliability temperature threshold of cloud platform；The preset safety of the cloud platform is moved closer in the temperature data
When temperature threshold, it is abnormal to determine that the temperature data occurs.
Step 103, when the monitoring data occurs abnormal, cloud platform is alarmed.
When judging abnormal data, cloud platform is alarmed, and reminds corresponding staff in time, is prevented unnecessary
Safety accident occurs.And due to the mode using automatic collection, it is close relative to what is manually acquired to adopt denseness of set
Degree is big, when monitoring data occurs abnormal, can and alarm, the speed of information transmitting is fast, and alarm rapidly, can shorten alarm
Duration.
Referring to Fig. 2, it illustrates a kind of monitoring systems for belt lane of another embodiment of the present invention offer
Mechanism block diagram, the monitoring system include acquisition module 201, analyze and determine module 202 and alarm module 203, the analytical judgment
Module 202 includes image zooming-out module 2021, image analysis module 2022 and image abnormity judgment module 2023, the analytical judgment
Module 202 further includes data extraction module 2024, data analysis module 2025 and data exception judgment module 2026.
Acquisition module 201 is used for every monitoring data by terminal device acquisition belt lane, and by the monitoring data
It is sent to cloud platform.
Preferably, the monitoring data includes one in belt operation image, temperature data, smoke data and air speed data
Kind is a variety of.
Analyze and determine that module 202 for analyzing by cloud platform the monitoring data, judges the monitoring data
Whether exception is occurred.
Alarm module 203, for when the monitoring data occurs abnormal, cloud platform to be alarmed.
Preferably, the analytical judgment module 202, including image zooming-out module 2021, image analysis module 2022 and figure
As abnormal judgment module 2023.
Image zooming-out module 2021 is used to extract the realtime image data in the monitoring data, the realtime image data
Including one or more of belt operation image data and belt X-ray detectoscope flaw detection image data.
Image analysis module 2022 be used for by the realtime image data it is corresponding with the preset image data of cloud platform into
Row similarity compares, image data when the preset image data is normal operating condition；
Image abnormity judgment module 2023 is used for when the result that the similarity compares is less than preset threshold, described in judgement
Realtime image data occurs abnormal.
Preferably, the analytical judgment module 202, including data extraction module 2024,2025 sum number of data analysis module
According to abnormal judgment module 2026.
Data extraction module 2024 is used to extract the temperature data in the monitoring data.
Data analysis module 2025 is used for when monitoring that the temperature data as the variation of time is in lasting rising, sentences
Whether the temperature data that breaks moves closer to the preset reliability temperature threshold of cloud platform.
Data exception judgment module 2026 is used to move closer to the preset safety temperature of the cloud platform in the temperature data
When spending threshold value, it is abnormal to determine that the temperature data occurs.
Finally, it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention, rather than its limitations；Although
Present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that: it still may be used
To modify the technical solutions described in the foregoing embodiments or equivalent replacement of some of the technical features；
And these are modified or replaceed, technical solution of various embodiments of the present invention that it does not separate the essence of the corresponding technical solution spirit and
Range.
Claims (10)
1. a kind of monitoring method for belt lane, which is characterized in that the monitoring method includes:
Every monitoring data in belt lane is acquired by terminal device, and the monitoring data is sent to cloud platform；
The monitoring data is analyzed by cloud platform, judges whether the monitoring data exception occurs；
When the monitoring data occurs abnormal, cloud platform is alarmed.
2. a kind of monitoring method for belt lane according to claim 1, which is characterized in that the monitoring data includes
One or more of belt operation image data, temperature data, smoke data and air speed data.
3. a kind of monitoring method for belt lane according to claim 1 or 2, which is characterized in that described flat by cloud
Platform analyzes the monitoring data, comprising the following steps:
Extract the realtime image data in the monitoring data；
The realtime image data similarity that carries out corresponding with the preset image data of cloud platform is compared, the preset figure
As data be normal operating condition when image data；
When the result that the similarity compares is less than preset threshold, it is abnormal to determine that the realtime image data occurs.
4. a kind of monitoring method for belt lane according to claim 3, which is characterized in that the realtime image data
Including one or more of belt operation image data and belt X-ray detectoscope flaw detection image data.
5. a kind of monitoring method for belt lane according to claim 1 or 2, which is characterized in that described flat by cloud
Platform analyzes the monitoring data, comprising the following steps:
Extract the temperature data in the monitoring data；
When monitoring that the temperature data as the variation of time is in lasting rising, judges whether the temperature data gradually connects
The preset reliability temperature threshold of nearly cloud platform；
When the temperature data moves closer to the preset reliability temperature threshold of the cloud platform, determine that the temperature data occurs
It is abnormal.
6. a kind of monitoring system for belt lane, which is characterized in that the monitoring system includes:
Acquisition module for acquiring every monitoring data in belt lane by terminal device, and the monitoring data is sent to
Cloud platform；
Analyze and determine that module judges whether the monitoring data goes out for analyzing by cloud platform the monitoring data
It is now abnormal；
Alarm module, for when the monitoring data occurs abnormal, cloud platform to be alarmed.
7. a kind of monitoring system for belt lane according to claim 6, which is characterized in that the monitoring data includes
One or more of belt operation image, temperature data, smoke data and air speed data.
8. a kind of monitoring system for belt lane according to claim 6 or 7, which is characterized in that the analytical judgment
Module, comprising:
Image zooming-out module, for extracting the realtime image data in the monitoring data；
Image analysis module, for carrying out similarity for the realtime image data is corresponding with the preset image data of cloud platform
It compares, image data when the preset image data is normal operating condition；
Image abnormity judgment module determines the real-time figure when result for comparing in the similarity is less than preset threshold
As exception occur in data.
9. a kind of monitoring system for belt lane according to claim 8, which is characterized in that the realtime image data
Including one or more of belt operation image data and belt X-ray detectoscope flaw detection image data.
10. a kind of monitoring system for belt lane according to claim 6 or 7, which is characterized in that the analytical judgment
Module, comprising:
Data extraction module, for extracting the temperature data in the monitoring data；
Data analysis module, for when monitoring the temperature data as the variation of time is in lasting rising, described in judgement
Whether temperature data moves closer to the preset reliability temperature threshold of cloud platform；
Data exception judgment module, for moving closer to the preset reliability temperature threshold of the cloud platform in the temperature data
When, it is abnormal to determine that the temperature data occurs.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811383521.4A CN109343427A (en) | 2018-11-20 | 2018-11-20 | A kind of monitoring method and its system for belt lane |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811383521.4A CN109343427A (en) | 2018-11-20 | 2018-11-20 | A kind of monitoring method and its system for belt lane |
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| Publication Number | Publication Date |
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| CN109343427A true CN109343427A (en) | 2019-02-15 |
Family
ID=65316635
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| CN201811383521.4A Pending CN109343427A (en) | 2018-11-20 | 2018-11-20 | A kind of monitoring method and its system for belt lane |
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Cited By (2)
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| CN109991913A (en) * | 2019-05-14 | 2019-07-09 | 广东工业大学 | A kind of monitoring system |
| CN110006469A (en) * | 2019-02-23 | 2019-07-12 | 晋能大土河热电有限公司 | A kind of coal conveyer belt crusing robot and it is operating abnormally recognition methods |
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Application publication date: 20190215 |