CN111160272A - Intelligent image fault judgment and early warning system - Google Patents
Intelligent image fault judgment and early warning system Download PDFInfo
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- CN111160272A CN111160272A CN201911403071.5A CN201911403071A CN111160272A CN 111160272 A CN111160272 A CN 111160272A CN 201911403071 A CN201911403071 A CN 201911403071A CN 111160272 A CN111160272 A CN 111160272A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/40—Scenes; Scene-specific elements in video content
- G06V20/41—Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
- F17D—PIPE-LINE SYSTEMS; PIPE-LINES
- F17D3/00—Arrangements for supervising or controlling working operations
- F17D3/01—Arrangements for supervising or controlling working operations for controlling, signalling, or supervising the conveyance of a product
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
- F17D—PIPE-LINE SYSTEMS; PIPE-LINES
- F17D5/00—Protection or supervision of installations
- F17D5/005—Protection or supervision of installations of gas pipelines, e.g. alarm
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
- F17D—PIPE-LINE SYSTEMS; PIPE-LINES
- F17D5/00—Protection or supervision of installations
- F17D5/02—Preventing, monitoring, or locating loss
- F17D5/06—Preventing, monitoring, or locating loss using electric or acoustic means
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/40—Scenes; Scene-specific elements in video content
- G06V20/46—Extracting features or characteristics from the video content, e.g. video fingerprints, representative shots or key frames
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
Abstract
By adopting the image intelligent fault judgment and early warning system provided by the embodiment of the invention, the image intelligent fault judgment and early warning system provided by the embodiment of the invention is used for dynamically comparing and analyzing the field monitoring picture by the image intelligent analysis system by utilizing the image intelligent fault judgment and processing technology, can find the slight change of a production field in advance, early warn the abnormal condition in production in time and feed back the abnormal condition to a client.
Description
Technical Field
The invention relates to the technical field of image processing, in particular to an intelligent image fault judgment and early warning system.
Background
With the digital and information construction of natural gas transportation, the traditional divergent inspection mode is abandoned and the transition from intensive monitoring to intensive inspection is started, the centralized management of the natural gas transportation production process is gradually enhanced, and management layers at all levels also hope to timely and comprehensively know and master the operation condition and emergency of field facilities. The operation area, the metering station and the gathering and transportation station library are dispersed, the distance is long, and a large amount of personnel is needed for routing inspection and maintenance.
Through the development of many years, intelligent video analysis is gradually mature and widely applied to the field of video monitoring, and becomes the direction of the next generation of video monitoring. Perimeter intrusion detection has become a mature application of video monitoring schemes based on intelligent video analysis as a common requirement in the security field. High-definition intelligent video analysis provides advanced functions including regional intrusion, wire mixing, flame, smoke, target classification, speed detection, abandoned object, object moving detection, automatic target tracking, direction detection and the like. The system can timely give out an acousto-optic alarm to an intruder, can greatly improve the security system of the whole natural gas department, can actively alarm suspicious dangerous events, can early warn in advance and can prevent the dangerous events.
At present, the simple intelligent images with fault judgment and snapshot functions are mostly mobile detection, the natural gas transportation production scene mainly based on the monitoring of the working state and the production state of equipment is not suitable, the field monitoring requirement cannot be met, and intelligent fault judgment is imperative.
Disclosure of Invention
In order to realize early warning and monitoring on equipment or pipelines in a production state, the embodiment of the invention provides an image intelligent fault judgment and early warning system. The specific technical scheme is as follows:
the embodiment of the invention provides an image intelligent fault judgment and early warning system, which comprises:
the video acquisition module is arranged at production equipment or a production area and is used for acquiring a video to be detected; the video to be detected is a video of equipment in a working state or a video of a pipeline;
the acquisition module is used for acquiring a standard video; the standard video is a normal state video of equipment operation or a normal state video transmitted by a pipeline;
the analysis module is used for comparing the to-be-detected video with the standard video according to a preset method to obtain a comparison result, wherein the comparison result is that the equipment runs normally or abnormally and the pipeline transmits normally or abnormally;
and the monitoring module is used for acquiring the comparison result and displaying the comparison result to a worker.
Optionally, the preset method includes:
determining a first target characteristic in the video to be detected;
determining a first target feature in the standard video;
acquiring each frame of image of the video to be detected, and respectively calculating the pixel distance of the first target characteristic in each frame of image;
counting the pixel spacing of the first target features in each frame of image according to the condition that the time is an X axis and the pixel spacing is a Y axis to obtain a first change curve of the pixel spacing of each first target feature relative to the time, and calculating the slope of the first change curve to obtain a first slope;
acquiring a second change curve of the pixel pitch of the first target feature changing along with time in the standard video, and calculating the slope of the second change curve to obtain a second slope;
calculating a first rate of change of the first slope over time and a second rate of change of the second slope over time;
when the first rate of change is not greater than the second rate of change, the first target feature operates normally;
when the first rate of change is greater than the second rate of change, the first target feature operates abnormally.
Optionally, the system further comprises a background server, the background server is wirelessly connected to the monitoring module, and the background server is used for storing the comparison result.
Optionally, the system further comprises a client, the client is wirelessly connected to the background server, and the background server feeds back the comparison result to the client.
Optionally, the first characteristic is that the device or the pipeline is in a working state in the video to be detected.
Optionally, the system further comprises a power supply, and the power supply is respectively connected with the video acquisition module, the analysis module and the monitoring module.
Optionally, the power supply is an intrinsic safety type power supply.
The image intelligent fault judgment early warning system provided by the embodiment of the invention comprises a video acquisition module, an analysis module and a monitoring module, wherein the video acquisition module is arranged at production equipment or a production area and is used for acquiring a video to be detected; the video to be detected is a video of equipment in a working state or a video of a pipeline; the acquisition module is used for acquiring a standard video; the standard video is a normal state video of equipment operation or a normal state video of pipeline transmission; the analysis module is used for comparing the video to be detected with the standard video according to a preset method to obtain a comparison result, wherein the comparison result is that the equipment runs normally or abnormally and the pipeline transmits normally or abnormally; the monitoring module is used for obtaining a comparison result and displaying the comparison result to a worker, and by adopting the image intelligent fault judgment and early warning system provided by the embodiment of the invention, the image intelligent fault judgment and processing technology is utilized to carry out dynamic comparison analysis on a field monitoring picture by the image intelligent analysis system, so that the slight change of a production field can be found in advance, the abnormal condition in production can be early warned in time, and the abnormal condition can be fed back to a client.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below.
Fig. 1 is a module connection diagram of an intelligent image fault diagnosis and early warning system according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be described below with reference to the drawings in the embodiments of the present invention.
In order to realize early warning and monitoring on equipment or pipelines in a production state, the embodiment of the invention provides a block chain-based information security management method, a system and a server.
Referring to fig. 1, an embodiment of the present invention provides an image intelligent fault diagnosis and early warning system, including:
the video acquisition module is arranged at production equipment or a production area and is used for acquiring a video to be detected; the video to be detected is a video of equipment in a working state or a video of a pipeline;
the acquisition module is used for acquiring a standard video; the standard video is a normal state video of equipment operation or a normal state video transmitted by a pipeline;
the analysis module is used for comparing the to-be-detected video with the standard video according to a preset method to obtain a comparison result, wherein the comparison result is that the equipment runs normally or abnormally and the pipeline transmits normally or abnormally;
and the monitoring module is used for acquiring the comparison result and displaying the comparison result to a worker.
Specifically, the image intelligent fault judgment and early warning system provided by the embodiment of the invention comprises a video acquisition module, an analysis module and a monitoring module, wherein the video acquisition module is arranged at production equipment or a production area and is used for acquiring a video to be detected; the video to be detected is a video of equipment in a working state or a video of a pipeline; the acquisition module is used for acquiring a standard video; the standard video is a normal state video of equipment operation or a normal state video of pipeline transmission; the analysis module is used for comparing the video to be detected with the standard video according to a preset method to obtain a comparison result, wherein the comparison result is that the equipment runs normally or abnormally and the pipeline transmits normally or abnormally; the monitoring module is used for obtaining a comparison result and displaying the comparison result to a worker, and by adopting the image intelligent fault judgment and early warning system provided by the embodiment of the invention, the image intelligent fault judgment and processing technology is utilized to carry out dynamic comparison analysis on a field monitoring picture by the image intelligent analysis system, so that the slight change of a production field can be found in advance, the abnormal condition in production can be early warned in time, and the abnormal condition can be fed back to a client.
Further, the preset method comprises the following steps:
determining a first target characteristic in the video to be detected;
determining a first target feature in the standard video;
acquiring each frame of image of the video to be detected, and respectively calculating the pixel distance of the first target characteristic in each frame of image;
counting the pixel spacing of the first target features in each frame of image according to the condition that the time is an X axis and the pixel spacing is a Y axis to obtain a first change curve of the pixel spacing of each first target feature relative to the time, and calculating the slope of the first change curve to obtain a first slope;
acquiring a second change curve of the pixel pitch of the first target feature changing along with time in the standard video, and calculating the slope of the second change curve to obtain a second slope;
calculating a first rate of change of the first slope over time and a second rate of change of the second slope over time;
when the first rate of change is not greater than the second rate of change, the first target feature operates normally;
when the first rate of change is greater than the second rate of change, the first target feature operates abnormally.
The system further comprises a background server, the background server is in wireless connection with the monitoring module, and the background server is used for storing the comparison result.
The client is in wireless connection with the background server, and the background server feeds the comparison result back to the client.
Further, the first characteristic is that the equipment or the pipeline is in a working state in the video to be detected.
The system further comprises a power supply, and the power supply is respectively connected with the video acquisition module, the analysis module and the monitoring module.
Further, the power supply is an intrinsic safety type power supply.
The image intelligent fault judgment early warning system provided by the embodiment of the invention comprises a video acquisition module, an analysis module and a monitoring module, wherein the video acquisition module is arranged at production equipment or a production area and is used for acquiring a video to be detected; the video to be detected is a video of equipment in a working state or a video of a pipeline; the acquisition module is used for acquiring a standard video; the standard video is a normal state video of equipment operation or a normal state video of pipeline transmission; the analysis module is used for comparing the video to be detected with the standard video according to a preset method to obtain a comparison result, wherein the comparison result is that the equipment runs normally or abnormally and the pipeline transmits normally or abnormally; the monitoring module is used for obtaining a comparison result and displaying the comparison result to a worker, and by adopting the image intelligent fault judgment and early warning system provided by the embodiment of the invention, the image intelligent fault judgment and processing technology is utilized to carry out dynamic comparison analysis on a field monitoring picture by the image intelligent analysis system, so that the slight change of a production field can be found in advance, the abnormal condition in production can be early warned in time, and the abnormal condition can be fed back to a client.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
All the embodiments in the present specification are described in a related manner, and the same and similar parts among the embodiments may be referred to each other, and each embodiment focuses on the differences from the other embodiments. The above description is only for the preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention shall fall within the protection scope of the present invention.
Claims (7)
1. The utility model provides an image intelligence fault diagnosis early warning system which characterized in that includes:
the video acquisition module is arranged at production equipment or a production area and is used for acquiring a video to be detected; the video to be detected is a video of equipment in a working state or a video of a pipeline;
the acquisition module is used for acquiring a standard video; the standard video is a normal state video of equipment operation or a normal state video transmitted by a pipeline;
the analysis module is used for comparing the to-be-detected video with the standard video according to a preset method to obtain a comparison result, wherein the comparison result is that the equipment runs normally or abnormally and the pipeline transmits normally or abnormally;
and the monitoring module is used for acquiring the comparison result and displaying the comparison result to a worker.
2. The intelligent image fault diagnosis and early warning system according to claim 1, wherein the preset method is as follows:
determining a first target characteristic in the video to be detected;
determining a first target feature in the standard video;
acquiring each frame of image of the video to be detected, and respectively calculating the pixel distance of the first target characteristic in each frame of image;
counting the pixel spacing of the first target features in each frame of image according to the condition that the time is an X axis and the pixel spacing is a Y axis to obtain a first change curve of the pixel spacing of each first target feature relative to the time, and calculating the slope of the first change curve to obtain a first slope;
acquiring a second change curve of the pixel pitch of the first target feature changing along with time in the standard video, and calculating the slope of the second change curve to obtain a second slope;
calculating a first rate of change of the first slope over time and a second rate of change of the second slope over time;
when the first rate of change is not greater than the second rate of change, the first target feature operates normally;
when the first rate of change is greater than the second rate of change, the first target feature operates abnormally.
3. The intelligent image fault judging and early warning system according to claim 1, further comprising a background server, wherein the background server is wirelessly connected to the monitoring module, and the background server is used for storing the comparison result.
4. The intelligent image fault judging and early warning system according to claim 3, further comprising a client, wherein the client is wirelessly connected to the background server, and the background server feeds the comparison result back to the client.
5. The intelligent image fault diagnosis and early warning system according to claim 2, wherein the first characteristic is a device or a pipeline in a working state in the video to be detected.
6. The intelligent image fault judging and early warning system according to claim 1, further comprising a power supply, wherein the power supply is respectively connected to the video acquisition module, the analysis module and the monitoring module.
7. The intelligent image fault diagnosis and early warning system of claim 6, wherein the power supply is an intrinsic safety type power supply.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201911403071.5A CN111160272B (en) | 2019-12-31 | 2019-12-31 | Intelligent fault judging and early warning system for images |
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| CN201911403071.5A CN111160272B (en) | 2019-12-31 | 2019-12-31 | Intelligent fault judging and early warning system for images |
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| CN111160272A true CN111160272A (en) | 2020-05-15 |
| CN111160272B CN111160272B (en) | 2023-06-02 |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN111993438A (en) * | 2020-08-26 | 2020-11-27 | 陕西工业职业技术学院 | Intelligent robot |
| WO2023246062A1 (en) * | 2022-06-21 | 2023-12-28 | 西安热工研究院有限公司 | Intelligent video-based electric power analysis and monitoring structure, system and method, and storage medium thereof |
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| US20140043480A1 (en) * | 2011-04-18 | 2014-02-13 | Zte Corporation | Video monitoring system and method |
| CN105323565A (en) * | 2015-12-11 | 2016-02-10 | 国网浙江桐乡市供电公司 | Intelligent video fault analysis and pre-warning system of transformer substation |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| WO2023246062A1 (en) * | 2022-06-21 | 2023-12-28 | 西安热工研究院有限公司 | Intelligent video-based electric power analysis and monitoring structure, system and method, and storage medium thereof |
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| CN111160272B (en) | 2023-06-02 |
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