CN111541877A - Automatic monitoring system for substation equipment - Google Patents
Automatic monitoring system for substation equipment Download PDFInfo
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- CN111541877A CN111541877A CN202010420913.4A CN202010420913A CN111541877A CN 111541877 A CN111541877 A CN 111541877A CN 202010420913 A CN202010420913 A CN 202010420913A CN 111541877 A CN111541877 A CN 111541877A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
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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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- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B13/00—Burglar, theft or intruder alarms
- G08B13/18—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength
- G08B13/189—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems
- G08B13/194—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems
- G08B13/196—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems using television cameras
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Abstract
The invention discloses an automatic monitoring system for substation equipment, which comprises an information acquisition unit, an information conversion unit, a processing and analyzing unit and a state determination unit. The information acquisition unit is used for acquiring video state information of the substation equipment, wherein the video state information comprises environment monitoring information, moving object detection and equipment abnormal conditions; the information conversion unit is used for converting the video state information into digital map information; the processing and analyzing unit is used for processing and analyzing the digital map information to obtain a digital map curve; the state determining unit is used for evaluating the digital spectrum curve and a preset standard curve and determining the state of the substation equipment. According to the automatic monitoring system for the substation equipment, the acquired atlas is processed by processing algorithms such as atlas wavelet denoising, geometric restoration, brightness balance, contrast enhancement, atlas denoising, anti-shake deblurring and the like, the problem of unclear acquired image data is solved, and the quality of video inspection is improved.
Description
Technical Field
The invention relates to the technical field of intelligent management and control of electric power systems, in particular to an automatic monitoring system for substation equipment.
Background
With the improvement of the automation level of power grid dispatching in China, unattended operation of a transformer substation is the development trend of the current power system. In the practice of unattended operation of a transformer substation, electric power departments in various places basically realize the four-remote function (remote measurement, remote signaling, remote control and remote regulation) of electrical equipment of the transformer substation, and a large number of video monitoring systems are adopted to monitor the running condition, the environmental condition, the security condition and the like of the electrical equipment of the transformer substation, and the video monitoring systems are called as the fifth remote function in the power industry, namely remote watching. At present, the monitoring personnel utilize video monitoring system to the surveillance of unmanned on duty transformer substation, need people's eye to observe the video scene picture ceaselessly, when a plurality of displays of keeping watch on simultaneously, produce visual fatigue easily, the monitoring personnel are in this kind of operating condition for a long time, and attention drops, and the video surveillance camera machine that the transformer substation installed has tens of thousands, can't accomplish complete control comprehensively almost. In fact, the video monitoring system of the substation still does not exert the monitoring function that it should.
Disclosure of Invention
In view of the above, it is necessary to provide an automatic substation equipment monitoring system to solve the above problems.
The invention provides an automatic monitoring system of substation equipment, which comprises:
the information acquisition unit is used for acquiring video state information of the substation equipment, wherein the video state information comprises environment monitoring information, moving object detection and equipment abnormal conditions;
the information conversion unit is used for converting the video state information into digital map information;
the processing and analyzing unit is used for processing and analyzing the digital map information to obtain a digital map curve;
and the state determining unit is used for evaluating the digital spectrum curve and a preset standard curve and determining the state of the substation equipment.
Preferably, the information converting unit includes:
the map shooting module is used for shooting video state information;
the photoelectric conversion module is used for converting optical signals in the video state information into electric signals;
and the digital processing module is used for carrying out digital processing on the electric signal to obtain digital map information.
Preferably, the processing and analyzing unit comprises a map transformation module, a map enhancement module, a map restoration module, a map coding module, a map analyzing module, a map identification module and a map understanding module.
Preferably, the map transformation module is used for carrying out orthogonal transformation on the digital map information;
the orthogonal transform employs a discrete fourier transform, a discrete cosine transform, a walsh transform, a hadamard transform, or a hotelling transform.
Preferably, the atlas enhancement module uses histogram enhancement, spatial domain enhancement, frequency domain enhancement, or pseudo-color enhancement to enhance the atlas.
Preferably, the spectrum restoration module removes noise interference and blur by using inverse filtering, wiener filtering, least constrained quadratic filtering or homomorphic filtering.
Preferably, the atlas coding module employs redundancy removal coding, transform coding, wavelet transform coding, neural network coding, or model-based coding.
Preferably, the atlas analysis module obtains the digital atlas curve through edge detection, region segmentation or feature extraction means.
Preferably, the atlas identification module uses statistical, syntactic or fuzzy identification.
Preferably, the spectrum understanding module obtains a digital spectrum curve after error calibration.
Compared with the prior art, the automatic monitoring system for the substation equipment provided by the invention has the following beneficial effects:
according to the automatic monitoring system for the substation equipment, the acquired atlas is processed by processing algorithms such as atlas wavelet denoising, geometric restoration, brightness balance, contrast enhancement, atlas denoising, anti-shake deblurring and the like, the problem of unclear acquired image data is solved, and the quality of video inspection is improved.
Furthermore, based on the intelligent analysis mode of the soft measurement atlas change detection technology, the comparison analysis of various algorithms such as geometric characteristic parameters and gray characteristic parameters is carried out by utilizing the images collected by the camera on site and the object information collected historically, and the alarm of the abnormity of oil leakage, foreign matter hanging and the like of the equipment is realized.
Furthermore, by adopting a visual analysis technology of personnel behavior characteristics in a transformer substation scene, when foreign matters enter the transformer substation on the ground or in the air in a monitoring range, when a left-over object which is not easy to observe is found in a warning area, when equipment or components in the monitoring range are taken away, and strangers enter the warning area or linger around, the system can automatically give an alarm against the set behavior regulation.
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The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
Fig. 1 is a block schematic diagram of an automatic substation equipment monitoring system according to an embodiment of the present invention;
fig. 2 is a schematic flow chart of a method for automatically monitoring substation equipment according to an embodiment of the present invention.
In the figure: 100. the automatic monitoring system comprises an automatic monitoring system 110, an information acquisition unit 120, an information conversion unit 121, a map shooting module 122, a photoelectric conversion module 123, a digital processing module 130, a processing and analysis unit 131, a map transformation module 132, a map enhancement module 133, a map restoration module 134, a map coding module 135, a map analysis module 136, a map identification module 137, a map understanding module 140 and a state determination unit.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It will be understood that when an element or component is referred to as being "connected" to another element or component, it can be directly connected to the other element or component or intervening elements or components may also be present. When an element or component is referred to as being "disposed on" another element or component, it can be directly on the other element or component or intervening elements or components may also be present.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
Fig. 1 is a schematic block diagram of an automatic substation equipment monitoring system 100 provided by the present invention, where the automatic substation equipment monitoring system 100 includes an information obtaining unit 110, an information converting unit 120, a processing and analyzing unit 130, and a state determining unit 140.
Specifically, the information obtaining unit 110 is configured to obtain video status information of the substation device. The video state information comprises environment monitoring information, moving object detection and equipment abnormal conditions. The information acquisition unit 110 includes, but is not limited to, a camera and a surveillance camera.
The information conversion unit 120 is used for converting the video state information into digital map information, the video state information is image dynamic information which is directly presented to technical staff, the image dynamic information is converted into the digital map information by the information conversion unit 120, the data given by the digital map information is more objective, and the technical staff can see whether the transformer substation equipment has problems or not in a visual mode.
The processing and analyzing unit 130 is configured to process and analyze the digital map information to obtain a digital map curve, the processing and analyzing unit 130 processes the digital map information to obtain the digital map curve according to a preset processing flow, and a technician visually sees the digital map curve according to the digital map curve to find a problem.
The state determination unit 140 is configured to evaluate the digital spectrum curve and a preset standard curve, and determine a state of the substation device. And evaluating and analyzing the state of the substation equipment according to the digital spectrum curve and a preset standard curve, wherein the abnormal states possibly occur comprise security abnormity, equipment abnormity and potential safety hazards caused by severe weather.
Further, with reference to fig. 1, the information conversion unit 120 includes an image capture module 121, a photoelectric conversion module 122, and a digital processing module 123. The map shooting module 121 is used for shooting video state information, and the map shooting module 121 can be obtained by a camera; the photoelectric conversion module 122 is configured to convert an optical signal in the video status information into an electrical signal, and convert an optical signal displayed by the video status information acquired by the camera into a cable number; the digital processing module 123 is configured to perform digital processing on the electrical signal to obtain digital map information.
Further, the processing and analyzing unit 130 includes a map transforming module 131, a map enhancing module 132, a map restoring module 133, a map coding module 134, a map analyzing module 135, a map recognizing module 136, and a map understanding module 137.
The map transform module 131 performs some orthogonal transform on the original map, such as discrete fourier transform, discrete cosine transform, walsh transform, hadamard transform, hotelin transform, etc., to represent the features of the map in the transform domain, so as to perform various related processes on the map in the transform domain, especially some special processes that cannot be performed by using the spatial method.
The atlas enhancement module 132 is mainly used to highlight interesting information in the atlas and attenuate or remove unwanted information so that useful information is enhanced for target discrimination or object interpretation. The main methods of map enhancement include histogram enhancement, spatial domain enhancement, frequency domain enhancement, pseudo-color enhancement and the like.
The main purpose of the spectrum restoration module 133 is to remove noise interference and blur and restore the original view of the spectrum. The pattern noise includes random noise and coherent noise. Random noise disturbances appear as pit disturbances and coherent noise disturbances appear as moire disturbances. Blur comes from lens defocus, relative motion, atmospheric turbulence, cloud occlusion, and the like. These interferences can be removed by inverse filtering, wiener filtering, least-constrained dyadic filtering, homomorphic filtering, etc.
The map coding module 134 belongs to the field of information source coding in the information theory, and the main purpose of the map coding module is to efficiently compress map signals by utilizing the statistical characteristics of the map signals and the physiological and psychological characteristics of human vision; therefore, the data storage amount is reduced, the data amount is reduced to reduce the transmission bandwidth, and the information amount is compressed so as to facilitate the atlas analysis and the atlas identification. The main methods of map coding include redundancy removing coding, transform coding, wavelet transform coding, neural network coding, model base coding and the like.
The atlas analysis module 135 is primarily to detect and measure objects of interest in the atlas to obtain the desired objective information. The atlas analysis changes the atlas originally described by pixels into a more concise description of the target through means of edge detection, region segmentation, feature extraction and the like.
The map recognition module 136 processes the digital map by using a map recognition method. The map recognition method can be roughly classified into a statistical recognition method, a syntactic (structure) recognition method, and a fuzzy recognition method. The statistical recognition method focuses on the characteristics of the map and can be realized by a Baycs classifier, an artificial neural network and a support vector machine; syntactic recognition focuses on the structure of the map pattern and can be realized through syntactic analysis or a corresponding automaton; the fuzzy recognition method mainly introduces a fuzzy mathematical method into the map recognition, thereby simplifying the structure of the recognition system, improving the practicability and reliability of the system, and being capable of more widely and deeply simulating the ambiguity of understanding things by human brain.
The spectrum understanding module 137 obtains a digital spectrum curve through error calibration. The key point of map understanding is to further study the properties of each target in the map and the mutual relation thereof on the basis of map analysis, and obtain the understanding of the meaning of the content of the map and the explanation of the original objective scene, thereby guiding and planning the behavior. The intelligent identification, the advance discovery and the automatic alarm of abnormal behaviors in the application map of the transformer substation are realized through the map change detection based on soft measurement.
Abnormal behavior is mainly classified into the following categories:
(1) in-station fire explosion or in-station equipment failure, the flame is in the initial stage of occurrence, the flame is a process of continuous expansion and spread from scratch, and flame flames can continuously jump due to wind power, air flow, heat drive and other reasons. The physical characteristics of the flame are graphically represented as: the area of the highlight area is continuously changed, and in the continuous several frames of the atlas, the area of the highlight area is in a growing trend. In addition, a typical flame does not have a regular shape, and the edge of the flame shows an irregular curve, while interference light sources such as flashlights, incandescent lamps, and candles often have a more regular shape. Therefore, the concept of circularity is introduced, the complexity of the edge of an object is represented by the concept of circularity, the circularity is used as a characteristic for distinguishing flames and interfering a light source to identify fire flames, and the algorithm implementation is provided.
(2) Under the influence of severe weather, the performance of target segmentation, feature extraction, target identification and dynamic tracking algorithms based on complex scenes (such as changeable illumination conditions, close color of a target and a background, disorder of the background, shielding of the target by the background, change of monitoring sites and the like) is improved, the capacity and effectiveness of a static target library and a dynamic rule library are improved, the occupation of hardware operation resources is reduced, and the accuracy and the real-time performance of automatic analysis and alarm on complex targets, behaviors and events in open, complex and large-scale monitoring areas are improved; the intelligent analysis software architecture is more reasonable and efficient.
(3) The system intelligently identifies, analyzes and prompts early warning information after comparing acquired real-time video and map data with original data according to the fact that the equipment in video monitoring is obviously distorted, deformed, obviously changed in color caused by oil leakage and the like.
According to the automatic monitoring system 100 for the substation equipment, the acquired atlas is processed by processing algorithms such as atlas wavelet denoising, geometric restoration, brightness balance, contrast enhancement, atlas denoising, anti-shake deblurring and the like, the problem that acquired image data are unclear is solved, and the quality of video inspection is improved.
Furthermore, based on the intelligent analysis mode of the soft measurement atlas change detection technology, the comparison analysis of various algorithms such as geometric characteristic parameters and gray characteristic parameters is carried out by utilizing the images collected by the camera on site and the object information collected historically, and the alarm of the abnormity of oil leakage, foreign matter hanging and the like of the equipment is realized.
Furthermore, by adopting a visual analysis technology of personnel behavior characteristics in a transformer substation scene, when foreign matters enter the transformer substation on the ground or in the air in a monitoring range, when a left-over object which is not easy to observe is found in a warning area, when equipment or components in the monitoring range are taken away, and strangers enter the warning area or linger around, the system can automatically give an alarm against the set behavior regulation.
The invention also provides an automatic monitoring method of the transformer substation equipment, which comprises the following steps:
step S201, video state information of the substation equipment is obtained.
The video state information comprises environment monitoring information, moving object detection and equipment abnormal conditions.
Specifically, the information obtaining unit 110 is configured to obtain video status information of the substation device. The video state information comprises environment monitoring information, moving object detection and equipment abnormal conditions. The information acquisition unit 110 includes, but is not limited to, a camera and a surveillance camera.
Step S202, converting the video state information into digital map information.
Specifically, the information conversion unit 120 is configured to convert the video state information into digital map information, the video state information is image dynamic information directly presented to a technician, the information conversion unit 120 converts the image dynamic information into the digital map information, the data provided by the digital map information is more objective, and the technician can visually see whether a problem occurs in the substation equipment.
And step S203, processing and analyzing the digital map information to obtain a digital map curve.
Specifically, the processing and analyzing unit 130 is configured to process and analyze the digital map information to obtain a digital map curve, the processing and analyzing unit 130 processes the digital map information to obtain the digital map curve according to a preset processing flow, and a technician visually sees the digital map curve according to the digital map curve, so as to find a problem.
And step S204, evaluating the digital spectrum curve and a preset standard curve, and determining the state of the power station equipment.
Specifically, the state determination unit 140 is configured to evaluate a digital spectrum curve and a preset standard curve, and determine a state of the substation device. And evaluating and analyzing the state of the substation equipment according to the digital spectrum curve and a preset standard curve, wherein the abnormal states possibly occur comprise security abnormity, equipment abnormity and potential safety hazards caused by severe weather.
Further, step S202, converting the video status information into digital map information specifically includes an ingestion map; performing photoelectric conversion; and (6) carrying out digital processing.
Specifically, the map capturing module 121 is configured to capture video status information as a captured map, and the map capturing module 121 may be obtained by using a camera; the photoelectric conversion module 122 is configured to convert an optical signal in the video status information into an electrical signal, and convert an optical signal displayed by the video status information acquired by the camera into a cable number; the digital processing module 123 is configured to perform digital processing on the electrical signal to obtain digital map information.
Step S203, the processing and analyzing the digital map information to obtain a digital map curve includes: the method comprises the steps of map transformation, map enhancement, map restoration, map coding, map analysis, map identification and map understanding.
The atlas transformation is to carry out orthogonal transformation on the digital atlas information; the orthogonal transform employs a discrete fourier transform, a discrete cosine transform, a walsh transform, a hadamard transform, or a hotelling transform.
The map transform module 131 performs some orthogonal transform on the original map, such as discrete fourier transform, discrete cosine transform, walsh transform, hadamard transform, hotelin transform, etc., to represent the features of the map in the transform domain, so as to perform various related processes on the map in the transform domain, especially some special processes that cannot be performed by using the spatial method.
The atlas enhancement adopts histogram enhancement, spatial domain enhancement, frequency domain enhancement or pseudo-color enhancement.
The atlas enhancement module 132 is mainly used to highlight interesting information in the atlas and attenuate or remove unwanted information so that useful information is enhanced for target discrimination or object interpretation. The main methods of map enhancement include histogram enhancement, spatial domain enhancement, frequency domain enhancement, pseudo-color enhancement and the like.
And the spectrum restoration is to remove noise interference and blurring by adopting an inverse filtering method, a wiener filtering method, a minimum constraint quadratic filtering method or a homomorphic filtering method.
The main purpose of the spectrum restoration module 133 is to remove noise interference and blur and restore the original view of the spectrum. The pattern noise includes random noise and coherent noise. Random noise disturbances appear as pit disturbances and coherent noise disturbances appear as moire disturbances. Blur comes from lens defocus, relative motion, atmospheric turbulence, cloud occlusion, and the like. These interferences can be removed by inverse filtering, wiener filtering, least-constrained dyadic filtering, homomorphic filtering, etc.
The atlas coding adopts redundancy removing coding, transformation coding, wavelet transformation coding, neural network coding or model base coding.
The map coding module 134 belongs to the field of information source coding in the information theory, and the main purpose of the map coding module is to efficiently compress map signals by utilizing the statistical characteristics of the map signals and the physiological and psychological characteristics of human vision; therefore, the data storage amount is reduced, the data amount is reduced to reduce the transmission bandwidth, and the information amount is compressed so as to facilitate the atlas analysis and the atlas identification. The main methods of map coding include redundancy removing coding, transform coding, wavelet transform coding, neural network coding, model base coding and the like.
And the atlas analysis obtains a digital atlas curve through edge detection, region segmentation or feature extraction means.
The atlas analysis module 135 is primarily to detect and measure objects of interest in the atlas to obtain the desired objective information. The atlas analysis changes the atlas originally described by pixels into a more concise description of the target through means of edge detection, region segmentation, feature extraction and the like.
The atlas identification adopts a statistical identification method, a syntactic identification method or a fuzzy identification method.
The map recognition module 136 processes the digital map by using a map recognition method. The map recognition method can be roughly classified into a statistical recognition method, a syntactic (structure) recognition method, and a fuzzy recognition method. The statistical recognition method focuses on the characteristics of the map and can be realized by a Baycs classifier, an artificial neural network and a support vector machine; syntactic recognition focuses on the structure of the map pattern and can be realized through syntactic analysis or a corresponding automaton; the fuzzy recognition method mainly introduces a fuzzy mathematical method into the map recognition, thereby simplifying the structure of the recognition system, improving the practicability and reliability of the system, and being capable of more widely and deeply simulating the ambiguity of understanding things by human brain.
The spectrum understanding is that a digital spectrum curve is obtained after error calibration. The spectrum understanding module 137 obtains a digital spectrum curve through error calibration. The key point of map understanding is to further study the properties of each target in the map and the mutual relation thereof on the basis of map analysis, and obtain the understanding of the meaning of the content of the map and the explanation of the original objective scene, thereby guiding and planning the behavior. The intelligent identification, the advance discovery and the automatic alarm of abnormal behaviors in the application map of the transformer substation are realized through the map change detection based on soft measurement.
Abnormal behavior is mainly classified into the following categories:
(1) in-station fire explosion or in-station equipment failure, the flame is in the initial stage of occurrence, the flame is a process of continuous expansion and spread from scratch, and flame flames can continuously jump due to wind power, air flow, heat drive and other reasons. The physical characteristics of the flame are graphically represented as: the area of the highlight area is continuously changed, and in the continuous several frames of the atlas, the area of the highlight area is in a growing trend. In addition, a typical flame does not have a regular shape, and the edge of the flame shows an irregular curve, while interference light sources such as flashlights, incandescent lamps, and candles often have a more regular shape. Therefore, the concept of circularity is introduced, the complexity of the edge of an object is represented by the concept of circularity, the circularity is used as a characteristic for distinguishing flames and interfering a light source to identify fire flames, and the algorithm implementation is provided.
(2) Under the influence of severe weather, the performance of target segmentation, feature extraction, target identification and dynamic tracking algorithms based on complex scenes (such as changeable illumination conditions, close color of a target and a background, disorder of the background, shielding of the target by the background, change of monitoring sites and the like) is improved, the capacity and effectiveness of a static target library and a dynamic rule library are improved, the occupation of hardware operation resources is reduced, and the accuracy and the real-time performance of automatic analysis and alarm on complex targets, behaviors and events in open, complex and large-scale monitoring areas are improved; the intelligent analysis software architecture is more reasonable and efficient.
(3) The system intelligently identifies, analyzes and prompts early warning information after comparing acquired real-time video and map data with original data according to the fact that the equipment in video monitoring is obviously distorted, deformed, obviously changed in color caused by oil leakage and the like.
According to the automatic monitoring method for the substation equipment, the acquired atlas is processed by processing algorithms such as atlas wavelet denoising, geometric restoration, brightness balance, contrast enhancement, atlas denoising, anti-shake deblurring and the like, the problem that acquired image data is unclear is solved, and the quality of video inspection is improved.
Furthermore, based on the intelligent analysis mode of the soft measurement atlas change detection technology, the comparison analysis of various algorithms such as geometric characteristic parameters and gray characteristic parameters is carried out by utilizing the images collected by the camera on site and the object information collected historically, and the alarm of the abnormity of oil leakage, foreign matter hanging and the like of the equipment is realized.
Furthermore, by adopting a visual analysis technology of personnel behavior characteristics in a transformer substation scene, when foreign matters enter the transformer substation on the ground or in the air in a monitoring range, when a left-over object which is not easy to observe is found in a warning area, when equipment or components in the monitoring range are taken away, and strangers enter the warning area or linger around, the system can automatically give an alarm against the set behavior regulation.
It will be understood by those skilled in the art that all or part of the processes of the above embodiments may be implemented by hardware instructions of a computer program, and the computer program may be stored in a computer-readable storage medium, and when executed, may include processes of the embodiments of the methods described above.
In addition, functional units in the embodiments of the present invention may be integrated into the same processor, or each unit may exist alone physically, or two or more units are integrated into the same unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional module.
The integrated unit implemented in the form of a software functional unit may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium, and includes a plurality of instructions for enabling an electronic device (which may be a handheld electronic device, such as a smart phone, a laptop computer, a Personal Digital Assistant (PDA), an intelligent wearable device, or a desktop electronic device, such as a desktop computer, an intelligent television, or the like) or a Processor (Processor) to perform some steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), an optical disk, or other various media storing program codes.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned. Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. Several units or systems recited in the system claims may also be implemented by one and the same unit or system in software or hardware. The terms first, second, etc. are used to denote names, but not any particular order.
Finally, it should be noted that the above embodiments are only intended to illustrate the technical solutions of the present invention and not to limit the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (10)
1. The utility model provides a substation equipment automatic monitoring system which characterized in that: the detection system comprises:
the information acquisition unit is used for acquiring video state information of the substation equipment, wherein the video state information comprises environment monitoring information, moving object detection and equipment abnormal conditions;
the information conversion unit is used for converting the video state information into digital map information;
the processing and analyzing unit is used for processing and analyzing the digital map information to obtain a digital map curve;
and the state determining unit is used for evaluating the digital spectrum curve and a preset standard curve and determining the state of the substation equipment.
2. The substation equipment automatic monitoring system of claim 1, characterized in that:
the information conversion unit includes:
the map shooting module is used for shooting the video state information;
the photoelectric conversion module is used for converting optical signals in the video state information into electric signals;
and the digital processing module is used for carrying out digital processing on the electric signal to obtain the digital map information.
3. The substation equipment automatic monitoring system of claim 1, characterized in that:
the processing and analyzing unit comprises a map transformation module, a map enhancement module, a map restoration module, a map coding module, a map analyzing module, a map identification module and a map understanding module.
4. The substation equipment automatic monitoring system of claim 3, characterized in that:
the map transformation module is used for carrying out orthogonal transformation on the digital map information;
the orthogonal transformation adopts discrete Fourier transformation, discrete cosine transformation, Walsh transformation, Hadamard transformation or Hotelling transformation.
5. The substation equipment automatic monitoring system of claim 3, characterized in that:
the map enhancement module enhances the map by adopting histogram enhancement, spatial domain enhancement, frequency domain enhancement or pseudo-color enhancement.
6. The substation equipment automatic monitoring system of claim 3, characterized in that:
the spectrum restoration module removes noise interference and fuzziness by adopting an inverse filtering method, a wiener filtering method, a minimum constraint quadratic filtering method or a homomorphic filtering method.
7. The substation equipment automatic monitoring system of claim 3, characterized in that:
the map coding module adopts redundancy removing coding, transform coding, wavelet transform coding, neural network coding or model base coding.
8. The substation equipment automatic monitoring system of claim 3, characterized in that:
the map analysis module obtains the digital map curve through edge detection, region segmentation or feature extraction.
9. The substation equipment automatic monitoring system of claim 3, characterized in that:
the map identification module adopts a statistical identification method, a syntactic identification method or a fuzzy identification method.
10. The substation equipment automatic monitoring system of claim 3, characterized in that:
the spectrum understanding module obtains the digital spectrum curve through error calibration.
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| CN202010420913.4A CN111541877A (en) | 2020-05-18 | 2020-05-18 | Automatic monitoring system for substation equipment |
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| CN202010420913.4A CN111541877A (en) | 2020-05-18 | 2020-05-18 | Automatic monitoring system for substation equipment |
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| CN113420654A (en) * | 2021-06-22 | 2021-09-21 | 国网北京市电力公司 | Processing method and device for transformer substation state and computer readable storage medium |
| CN114022850A (en) * | 2022-01-07 | 2022-02-08 | 深圳市安软慧视科技有限公司 | Transformer substation fire monitoring method and system and related equipment |
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