CN112714284A - Power equipment detection method and device and mobile terminal - Google Patents

Power equipment detection method and device and mobile terminal Download PDF

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Publication number
CN112714284A
CN112714284A CN202011530560.XA CN202011530560A CN112714284A CN 112714284 A CN112714284 A CN 112714284A CN 202011530560 A CN202011530560 A CN 202011530560A CN 112714284 A CN112714284 A CN 112714284A
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CN
China
Prior art keywords
power equipment
image
detected
cloud
electric power
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Pending
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CN202011530560.XA
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Chinese (zh)
Inventor
高昆仑
陈江琦
赵婷
王博
刘思言
张希
夏卫尚
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
State Grid Corp of China SGCC
Global Energy Interconnection Research Institute
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State Grid Corp of China SGCC
Global Energy Interconnection Research Institute
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Application filed by State Grid Corp of China SGCC, Global Energy Interconnection Research Institute filed Critical State Grid Corp of China SGCC
Priority to CN202011530560.XA priority Critical patent/CN112714284A/en
Publication of CN112714284A publication Critical patent/CN112714284A/en
Pending legal-status Critical Current

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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
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00006—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment
    • H02J13/00028—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment involving the use of Internet protocols
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/06—Management of faults, events, alarms or notifications
    • H04L41/0677—Localisation of faults
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/14—Network analysis or design
    • H04L41/145—Network analysis or design involving simulating, designing, planning or modelling of a network
    • 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
    • H04L67/10—Protocols in which an application is distributed across nodes in the network
    • 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
    • Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B70/00—Technologies for an efficient end-user side electric power management and consumption
    • Y02B70/30—Systems integrating technologies related to power network operation and communication or information technologies for improving the carbon footprint of the management of residential or tertiary loads, i.e. smart grids as climate change mitigation technology in the buildings sector, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
    • 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
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S20/00—Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
    • Y04S20/20—End-user application control systems
    • Y04S20/242—Home appliances

Abstract

The invention discloses a power equipment detection method, a device and a mobile terminal, wherein the method comprises the following steps: acquiring an image of the to-be-detected power equipment; inputting an image of the to-be-detected power equipment into a power equipment analysis model, wherein the power equipment analysis model is obtained by training in advance according to image samples of a plurality of power equipment and fault image samples corresponding to the power equipment; obtaining an identification result of the image of the electric power equipment to be detected according to the electric power equipment analysis model; judging whether the identification result needs cloud identification; when the identification result needs cloud identification, sending the image of the electric power equipment to be detected to a cloud; and receiving a cloud identification result and a fault analysis result of the cloud. By implementing the method and the device, the detection of the power equipment is more comprehensive, the automatic analysis of the defects of the power equipment is realized, the fault of the power equipment can be processed in real time, and the detection efficiency of the fault of the power equipment is improved.

Description

Power equipment detection method and device and mobile terminal
Technical Field
The invention relates to the field of power equipment inspection, in particular to a power equipment detection method and device and a mobile terminal.
Background
Electric power safety is the prerequisite and the guarantee of people's daily life and national industrial production, in order to master power equipment's operation conditions, in time discovers power equipment hidden danger, ensures power equipment's safe operation, need patrol and examine power equipment usually. Relevant inspection modes, such as manual inspection, helicopter inspection, unmanned aerial vehicle inspection, robot inspection, camera monitoring and the like need to carry out troubleshooting on the acquired images of the power equipment through a manual verification mode, so that the fault detection efficiency of the power equipment is reduced.
Disclosure of Invention
Therefore, the technical problem to be solved by the present invention is to overcome the defect that the fault detection efficiency of the power equipment is reduced by performing fault troubleshooting on the power equipment in a manual verification manner in the related art, so as to provide a method, an apparatus and a mobile terminal for detecting the power equipment.
According to a first aspect, an embodiment of the present invention provides a power device detection method, including: acquiring an image of the to-be-detected power equipment; inputting the images of the electric power equipment to be detected into an electric power equipment analysis model, wherein the electric power equipment analysis model is obtained in advance according to image samples of a plurality of electric power equipment and fault image samples corresponding to the electric power equipment through training; obtaining an identification result of the to-be-detected electrical equipment image according to the electrical equipment analysis model; judging whether the identification result needs cloud identification; when the identification result needs to be subjected to cloud identification, the image of the electric power equipment to be detected is sent to a cloud; and receiving a cloud identification result and a fault analysis result of the cloud.
With reference to the first aspect, in a first implementation manner of the first aspect, the inputting the to-be-detected power equipment image to a power equipment analysis model includes: preprocessing the image of the electric power equipment to be detected according to preset processing conditions; and inputting the preprocessed image of the electric equipment to be detected into the electric equipment analysis model.
With reference to the first aspect, in a second implementation manner of the first aspect, the obtaining, according to the power equipment analysis model, an identification result of the image of the power equipment to be detected includes: based on the target sliding window, carrying out target identification on the image area of the electric power equipment to be detected corresponding to any one target sliding window by utilizing the electric power equipment analysis model; and generating a recognition result of the image of the electric power equipment to be detected according to the target recognition.
With reference to the first aspect, in a third implementation manner of the first aspect, the determining whether the identification result needs to be cloud-side identified includes: determining the target credibility corresponding to the recognition result based on the recognition result; judging whether the target reliability exceeds a preset threshold value; and when the target reliability exceeds a preset threshold value, judging that the identification result needs cloud identification.
With reference to the first aspect or the first embodiment of the first aspect, the second embodiment or the third embodiment, in a fourth embodiment of the first aspect, after the receiving the cloud end identification result and the fault analysis result of the cloud end, the method further includes: carrying out fault marking on the to-be-detected power equipment image; acquiring position information of to-be-detected electric equipment; and transmitting the image of the to-be-detected power equipment subjected to fault marking, the identification result, the fault analysis result and the position information to a power equipment management platform.
With reference to the fourth implementation manner of the first aspect, in the fifth implementation manner of the first aspect, after obtaining, according to the power equipment analysis model, a recognition result of the image of the power equipment to be detected, the method further includes: and generating an identification result of the to-be-detected power equipment image and prompt information of a fault analysis result.
With reference to the first aspect, in a sixth implementation of the first aspect, the method further includes: when the identification result does not need to be subjected to cloud identification, fault analysis is carried out according to the identification result of the to-be-detected power equipment image to obtain a fault analysis result; determining the position information of the to-be-detected power equipment based on the fault analysis result; and transmitting the image of the electric power equipment to be detected, the identification result, the fault analysis result and the position information to an electric power equipment management platform.
According to a second aspect, an embodiment of the present invention provides an electrical device detection apparatus, including: the image acquisition module is used for acquiring an image of the electric power equipment to be detected; the image input module is used for inputting the images of the to-be-detected power equipment into a power equipment analysis model, and the power equipment analysis model is obtained by training in advance according to image samples of a plurality of power equipment and fault image samples corresponding to the power equipment; the image identification module is used for obtaining an identification result of the image of the electric power equipment to be detected according to the electric power equipment analysis model; the judging module is used for judging whether the identification result needs to be subjected to cloud identification; the sending module is used for sending the image of the electric power equipment to be detected to a cloud terminal when the cloud terminal identification is needed in the identification result; and the receiving module is used for receiving the cloud identification result and the fault analysis result of the cloud.
According to a third aspect, an embodiment of the present invention provides a mobile terminal, including: the image acquisition module is used for acquiring images of the power equipment; the positioning module is used for determining the position information of the electric power equipment; a memory and a processor, the memory and the processor are communicatively connected with each other, the memory stores computer instructions, and the processor executes the computer instructions to execute the power equipment detection method in the first aspect or any embodiment of the first aspect; and the prompting module is used for prompting the processing result.
According to a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, where computer instructions are stored, and the computer instructions are configured to cause the computer to execute a method for implementing the first aspect or the power device detection method in any implementation manner of the first aspect.
The technical scheme of the invention has the following advantages:
the electric power equipment detection method provided by the invention comprises the steps of acquiring an image of electric power equipment to be detected, inputting the image of the electric power equipment to be detected into an electric power equipment analysis model, obtaining a recognition result of the image of the electric power equipment to be detected according to the electric power equipment analysis model, judging whether the recognition result needs to be subjected to cloud recognition or not, sending the image of the electric power equipment to be detected to a cloud terminal when the recognition result needs to be subjected to cloud recognition, and receiving the cloud terminal recognition result and a fault analysis result of the cloud terminal. The method enables the detection of the power equipment to be more comprehensive, realizes automatic analysis of the defects of the power equipment, can process the faults of the power equipment in real time, and improves the detection efficiency of the faults of the power equipment.
According to the power equipment detection method provided by the invention, the target reliability corresponding to the identification result is determined based on the identification result, whether the target reliability exceeds the preset threshold value or not is judged, and when the target reliability exceeds the preset threshold value, the identification result is judged to be required to be subjected to cloud identification, so that the real-time interaction between the mobile terminal and the cloud is realized.
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, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of a power equipment detection method according to an embodiment of the present invention;
fig. 2 is another flowchart of a power equipment detection method according to an embodiment of the present invention;
fig. 3 is another flowchart of a power device detection method according to an embodiment of the present invention;
fig. 4 is a block diagram of a power equipment detection apparatus according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a mobile terminal according to an embodiment of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. 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.
In addition, the technical features involved in the different embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
The embodiment provides a power device detection method, which may be used in a mobile terminal, and as shown in fig. 1, the power device detection method includes:
s11: and acquiring an image of the electric power equipment to be detected.
For example, the image of the power device to be detected can be obtained by shooting the power device to be detected through an internal or external camera of the mobile terminal. After the image to be detected is obtained by calling the camera shooting function, the image can be displayed on the mobile terminal in a preview mode, and the image of the electric power equipment to be detected is determined according to the received selection operation of the shot image; an image obtained by calling the camera by the mobile terminal can also be directly used as an image of the electric power equipment to be detected; the received image of the power equipment shot by the other shooting equipment can be used as the image of the power equipment to be detected. The acquisition mode of the image of the power equipment to be detected is not limited, and a person skilled in the art can determine the acquisition mode according to actual use needs.
S12: and inputting the images of the electric power equipment to be detected into an electric power equipment analysis model, wherein the electric power equipment analysis model is obtained by training according to the image samples of the plurality of electric power equipment and the fault image samples corresponding to the electric power equipment in advance.
Illustratively, the power equipment analysis model is trained according to a plurality of power equipment image samples obtained in advance and fault image samples corresponding to the power equipment. Training the power equipment analysis model through the plurality of power equipment image samples, so that the power equipment analysis model obtained through training can accurately identify the input power equipment in the power equipment image to be detected; through the fault image samples corresponding to the plurality of electric devices, whether the electric devices in the input images of the electric devices to be detected have faults or not can be accurately identified through the electric device analysis model obtained through training. The identification accuracy of the power equipment analysis model can be determined according to actual use requirements, and the embodiment of the application does not limit the identification accuracy.
S13: and obtaining the identification result of the image of the electric power equipment to be detected according to the electric power equipment analysis model.
Exemplarily, the image of the electrical equipment to be detected is input into the electrical equipment analysis model, and the identification result of the image of the electrical equipment to be detected is obtained according to the electrical equipment analysis model. One or more defects or faults may exist on an image of an electric power device to be detected, a plurality of identification results corresponding to the image of the electric power device to be detected can be obtained after the image of the electric power device to be detected is identified, and a fault analysis result is output according to the identification results to maintain and use the electric power device.
And S14, judging whether the identification result needs to be subjected to cloud identification.
The identification result includes the target reliability corresponding to the to-be-detected power equipment image and the category corresponding to the to-be-detected power equipment image. And judging whether the identification result needs to be subjected to cloud identification according to the type of the image corresponding to the to-be-detected power equipment and the target reliability. When it is determined that the identification result needs to be subjected to cloud identification, step S14 is executed, otherwise, other operations are executed, where the other operations may be outputting the identification result of the to-be-detected power device image, or performing fault analysis on the identification result of the to-be-detected power device image, and the like, and this is not particularly limited here.
And S15, sending the image of the electric power device to be detected to a cloud.
The cloud server is provided with a high-precision electric power equipment analysis model, and the high identification accuracy rate is high for the defects or faults of the electric power equipment. And when the identification result is determined to need cloud identification, sending the image of the electric power equipment to be detected to the cloud for defect or fault identification.
And S16, receiving the cloud identification result and the fault analysis result of the cloud.
After the cloud server inputs the image of the electric power equipment to be detected to the high-precision electric power equipment analysis model, a cloud identification result and a fault analysis result corresponding to the electric power equipment to be detected can be obtained, and the cloud can send the cloud identification result and the fault analysis result to the mobile terminal.
According to the electric power equipment detection method provided by the embodiment, the electric power equipment image to be detected is input into the electric power equipment analysis model by acquiring the electric power equipment image to be detected, the identification result of the electric power equipment image to be detected is obtained according to the electric power equipment analysis model, whether cloud identification needs to be carried out on the identification result is judged, when the identification result needs to be carried out on the cloud identification, the electric power equipment image to be detected is sent to a cloud, and the cloud identification result and the fault analysis result of the cloud are received. The method enables the power equipment to be detected more comprehensively, realizes automatic analysis of the defects of the power equipment, realizes real-time interaction between the mobile phone and the cloud, is convenient for real-time processing of the faults of the power equipment, and improves the detection efficiency of the faults of the power equipment.
The embodiment provides a power device detection method, which may be used in a mobile terminal, and as shown in fig. 2, the power device detection method includes:
s21: and acquiring an image of the electric power equipment to be detected. For a detailed description, refer to the related description of step S11 corresponding to the above embodiment, and the detailed description is omitted here.
S22: and inputting the images of the electric power equipment to be detected into an electric power equipment analysis model, wherein the electric power equipment analysis model is obtained by training according to the image samples of the plurality of electric power equipment and the fault image samples corresponding to the electric power equipment in advance.
Specifically, the step S22 may include the following steps:
s221: and preprocessing the image of the power equipment to be detected according to preset processing conditions.
For example, the mode of preprocessing the image of the to-be-detected power device may include image scaling, image flipping, image enhancement and image feature extraction of the image of the to-be-detected power device according to preset processing conditions. The image preprocessing method is not limited in the embodiment of the application, and can be determined by a person skilled in the art according to actual use requirements. The preset processing condition can be determined according to the images in the image sample used for training, and the image parameters of the image of the electric power equipment to be detected are the same as the image parameters of the image sample used for training the electric power equipment analysis model through preprocessing operation. For example, the image turning process may be to rotate the image with the target position of the image as the rotation center; the image feature extraction process may be decoding the captured image, compressing the image into a target format, such as a bitmap format; the process of image scaling may be to reset the size of the captured image; and (4) image enhancement, namely rearranging the dimensionality of the shot image to highlight the image characteristics. The images can be made to correspond to image sample parameters of the power equipment analysis model used for training in advance through the preprocessing operation.
S222: and inputting the preprocessed images of the electric equipment to be detected into an electric equipment analysis model.
For example, the power equipment analysis model may include an input buffer, an identification area, and an output buffer, but is not limited to one or more of the foregoing partitions, the input buffer continuously receives an image of the power equipment to be detected after the preprocessing operation, the identification area reads one image of the power equipment to be detected from the input buffer, identifies the power equipment in the image of the power equipment and the defects or faults of the power equipment, transmits the identification result to the output buffer, and then the output buffer feeds the result back to other equipment for subsequent processing.
S23: and obtaining the identification result of the image of the electric power equipment to be detected according to the electric power equipment analysis model.
Specifically, the step S23 may include the following steps:
and S231, based on the target sliding window, performing target identification on the to-be-detected electric power equipment image area corresponding to any target sliding window by using the electric power equipment analysis model.
The target sliding window may be rectangular or circular, and the shape and size of the target sliding window are not limited in the embodiments of the present application, and can be determined by those skilled in the art according to actual use needs. When the target sliding window is rectangular, the rectangular frame with the width of w and the height of h is adopted to traverse the image of the power equipment to be detected based on the minimum rectangular principle, so that the power equipment analysis model performs fault identification on the image corresponding to the rectangular frame. The target sliding window is arranged to traverse the to-be-detected power equipment image, so that the power equipment analysis model can perform target identification on a plurality of sub-images corresponding to the target sliding window traversing the to-be-detected power equipment image, and the accuracy of the power equipment analysis model on power equipment fault detection is improved.
And S232, generating an identification result of the image of the electric power equipment to be detected according to the target identification.
For example, the recognition result generated by performing the target recognition on each image corresponding to the target sliding window may be recorded by using a set of recognition sets, such as [ c, p, x ]c,yc,w,h]In the recognition set, "c" represents a fault category, "p" represents a target reliability, and "x" represents a target reliabilityc、yc"represents the center coordinates of the rectangular frame," w, h "represents the size of the rectangular frame.
And S24, judging whether the identification result needs to be subjected to cloud identification.
Specifically, the step S24 may include the following steps:
and S241, determining the target reliability corresponding to the recognition result based on the recognition result.
Illustratively, the target reliability is the probability of a defect or fault occurring in the image of the electrical equipment to be detected. And generating an identification set corresponding to the image of the electric equipment to be detected according to the identification result, wherein the identification result comprises the target reliability. For example, identify the set [ c, p, x [ ]c,yc,w,h]And wherein, the 'p' is the target reliability corresponding to the recognition result.
And S242, judging whether the target reliability exceeds a preset threshold value.
Illustratively, the preset threshold is a probability value of a defect or a fault occurring in the image of the to-be-detected power equipment. The preset threshold may be set to 50% according to an empirical value, may also be set to 60%, may also be set to 70%, and may of course also be set to other probability values, which is not specifically limited in this application. And comparing the target reliability with a preset threshold value, and determining whether the target reliability exceeds the preset threshold value. When the target reliability exceeds the preset threshold, step S243 is executed, otherwise, step S27 is executed.
And S243, judging that the identification result needs cloud identification.
Illustratively, when the target reliability exceeds a preset threshold, the type of the corresponding to-be-detected power equipment image is a defect type or a fault type, and the target reliability is greater than or equal to the preset threshold. At this time, it can be determined that the other result needs to be cloud-side identified.
And S25, sending the image of the electric power device to be detected to a cloud. For a detailed description, refer to the related description of step S15 corresponding to the above embodiment, and the detailed description is omitted here.
And S26, receiving the cloud identification result and the fault analysis result of the cloud. For a detailed description, refer to the related description of step S16 corresponding to the above embodiment, and the detailed description is omitted here.
And S27, performing fault analysis according to the identification result of the image of the power equipment to be detected to obtain a fault analysis result.
For example, when the target reliability does not exceed the preset threshold, it indicates that the recognition result does not need to be subjected to cloud recognition, and at this time, a recognition set formed by the recognition result may be combined with the fault description information to obtain a fault analysis result. The embodiment of the present application does not limit the expression form of the fault analysis result and the parameter category included in the fault identification set, and those skilled in the art can determine the expression form and the parameter category according to actual use requirements.
And S28, determining the position information of the to-be-detected electric equipment based on the fault analysis result.
For example, the position information of the to-be-detected power equipment corresponding to the fault analysis result may be obtained through a positioning module of the mobile terminal, or may be input through an input module of the mobile terminal, where the position information of the to-be-detected power equipment is input through the input module. The method for acquiring the position information of the power equipment to be detected is not limited, and a person skilled in the art can determine the method according to actual use needs.
And S29, transmitting the images, the recognition results, the fault analysis results and the position information of the electric equipment to be detected to the electric equipment management platform.
Exemplarily, the image and the position information of the electric power equipment to be detected, the identification result of the corresponding image and the fault analysis result of the corresponding image are transmitted to the electric power equipment management platform for storage, so that the subsequent further fault analysis and verification can be facilitated.
According to the power equipment detection method provided by the embodiment, the image of the power equipment to be detected is preprocessed, so that the image parameters of the image of the power equipment to be detected are the same as those of the image sample used for training, the preprocessed image of the power equipment to be detected is input into the power equipment analysis model, and the recognition result and the fault detection efficiency of the power equipment analysis model can be improved. The image of the power equipment to be detected is subjected to fault marking, the position information of the image is acquired, the position information of the image and the corresponding recognition and analysis result are transmitted to the power equipment management platform, and therefore technicians can conveniently determine the position of the power equipment with faults and timely maintain the power equipment with faults. The mobile terminal interacts with the cloud in real time, visual information and background information of the image of the power equipment to be detected are fused, and the identification result and the fault analysis result are displayed in real time.
The embodiment provides a power device detection method, which may be used in a mobile terminal, and as shown in fig. 3, the power device detection method includes:
s30: and acquiring an image of the electric power equipment to be detected. For a detailed description, refer to the related description of step S21 corresponding to the above embodiment, and the detailed description is omitted here.
S31: and inputting the images of the electric power equipment to be detected into an electric power equipment analysis model, wherein the electric power equipment analysis model is obtained by training according to the image samples of the plurality of electric power equipment and the fault image samples corresponding to the electric power equipment in advance. For a detailed description, refer to the related description of step S22 corresponding to the above embodiment, and the detailed description is omitted here.
S32: and obtaining the identification result of the image of the electric power equipment to be detected according to the electric power equipment analysis model. For a detailed description, refer to the related description of step S23 corresponding to the above embodiment, and the detailed description is omitted here.
And S33, judging whether the identification result needs to be subjected to cloud identification. For a detailed description, refer to the related description of step S24 corresponding to the above embodiment, and the detailed description is omitted here.
And S34, sending the image of the electric power device to be detected to a cloud. For a detailed description, refer to the related description of step S25 corresponding to the above embodiment, and the detailed description is omitted here.
And S35, receiving the cloud identification result and the fault analysis result of the cloud. For a detailed description, refer to the related description of step S26 corresponding to the above embodiment, and the detailed description is omitted here.
S36: and carrying out fault marking on the image of the power equipment to be detected.
For example, the manner of marking the fault of the image of the power equipment to be detected may be to mark the identified fault position by using a block diagram, and the shape of the block diagram may be a rectangular frame or a circular frame. The shape of the block diagram is not limited in the embodiment of the application, and can be determined by a person skilled in the art according to actual use requirements; the method for marking the fault of the image of the power equipment to be detected can also be to add a label or a character at the fault position. The method for marking the fault is not limited in the embodiment of the application, and a person skilled in the art can determine the method according to actual use needs.
S37: and acquiring the position information of the electric equipment to be detected.
For example, the position information of the to-be-detected power equipment can be obtained through a positioning module of the mobile terminal, and the position information of the to-be-detected power equipment can also be input through an input module of the mobile terminal. The method for acquiring the position information of the power equipment to be detected is not limited, and a person skilled in the art can determine the method according to actual use needs.
S38: and transmitting the image, the recognition result, the fault analysis result and the position information of the to-be-detected power equipment subjected to fault marking to a power equipment management platform.
Exemplarily, the image and the position information of the electric power equipment to be detected, the identification result of the corresponding image and the fault analysis result of the corresponding image are transmitted to the electric power equipment management platform for storage, so that the subsequent further fault analysis and verification can be facilitated.
S39: and generating an identification result of the image of the power equipment to be detected and prompt information of a fault analysis result.
Illustratively, the prompt message can be displayed on the mobile terminal in a text or video mode on the recognition result and the fault analysis result; the recognition result and the fault analysis result can also be reported to the user in a voice mode. The prompting mode of the prompting information is not limited in the embodiment of the application, and a person skilled in the art can determine the prompting mode according to actual use needs.
According to the power equipment detection method provided by the embodiment, the recognition result of the image of the power equipment to be detected and the prompt information of the fault analysis result are generated and displayed on the mobile equipment, so that the technician is prompted to find out the fault of the power equipment, analyze the fault and prompt the fault analysis result, the technician can conveniently know the running state of the power equipment in time, the mobile terminal equipment can work, and the mobile terminal equipment is easy to carry and process the fault in real time, so that different requirements of power equipment fault detection are met.
The present embodiment provides an electrical equipment detection apparatus, as shown in fig. 4, the electrical equipment detection apparatus includes:
and the image acquisition module 41 is used for acquiring an image of the electric power equipment to be detected. For a detailed description, reference is made to the corresponding related description of the above method embodiments, which is not repeated herein.
The image input module 42 is configured to input an image of the to-be-detected power device into a power device analysis model, where the power device analysis model is obtained by training in advance according to image samples of a plurality of power devices and fault image samples corresponding to the power devices. For a detailed description, reference is made to the corresponding related description of the above method embodiments, which is not repeated herein.
And the image identification module 43 is configured to obtain an identification result of the image of the to-be-detected power equipment according to the power equipment analysis model. For a detailed description, reference is made to the corresponding related description of the above method embodiments, which is not repeated herein.
And the judging module 44 is configured to judge whether the identification result needs to be cloud-identified. For a detailed description, reference is made to the corresponding related description of the above method embodiments, which is not repeated herein.
And the sending module 45 is configured to send the image of the to-be-detected power equipment to the cloud when the identification result needs cloud identification. For a detailed description, reference is made to the corresponding related description of the above method embodiments, which is not repeated herein.
The receiving module 46 is configured to receive a cloud identification result and a fault analysis result of the cloud. For a detailed description, reference is made to the corresponding related description of the above method embodiments, which is not repeated herein.
The power equipment detection device provided by the embodiment detects power equipment images through obtaining, and to detect power equipment image input to power equipment analysis model, according to power equipment analysis model, obtains the recognition result of detecting power equipment images, judges whether the recognition result needs to carry out cloud end recognition, and when the recognition result needs to carry out cloud end recognition, will detect power equipment image and send to the cloud end, receives cloud end recognition result and the failure analysis result of the cloud end. The device makes the power equipment detect more comprehensively, has realized the automatic analysis power equipment defect, has realized the real-time interaction of cell-phone and high in the clouds to carry out real-time processing to the trouble of power equipment, improved the detection efficiency of power equipment trouble.
The embodiment of the present invention further provides a mobile terminal, as shown in fig. 5, the mobile terminal includes an image acquisition module 51, a processor 52, a memory 53, a prompt module 54, and a positioning module 55.
And the image acquisition module 51 is used for acquiring the power equipment image. The image acquisition module can be a terminal camera, and other reasonable acquisition ways can also be used as the image acquisition module.
Processor 52 may be a Central Processing Unit (CPU). The Processor 52 may also be other general purpose processors, Digital Signal Processors (DSPs), Graphics Processing Units (GPUs), embedded Neural Network Processors (NPUs), or other dedicated deep learning coprocessors, Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs), or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, or any combination thereof.
The memory 53, as a non-transitory computer-readable storage medium, may be used to store non-transitory software programs, non-transitory computer-executable programs, and modules, such as program instructions/modules corresponding to the power device detection method in the embodiment of the present invention (for example, the image acquisition module 41, the image input module 42, the image recognition module 43, the judgment module 44, the transmission module 45, and the reception module 46 shown in fig. 4). The processor 52 executes various functional applications and data processing of the processor by running non-transitory software programs, instructions and modules stored in the memory 53, that is, implements the power device detection method in the above-described method embodiment.
The memory 53 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created by the processor 52, and the like. Further, the memory 53 may include high speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory 53 may optionally include memory located remotely from the processor 52, which may be connected to the processor 52 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
And a prompt module 54 for prompting the processing result. The processor 52 cooperates with the mobile terminal processing software to identify the image processing result, and the processing software may include a TensorFlow mobile terminal library, an artificial intelligence engine HIAI SDK, a neural network engine NNAPI SDK, and a neural network machine learning software Arm NN, but is not limited to one or more of the above processing software.
And the positioning module 55 is used for determining the position information of the power equipment, so that the power equipment can be more accurately positioned at the position where the defect or the fault occurs in the power equipment, and the detection efficiency is improved.
The one or more modules are stored in the memory 53 and, when executed by the processor 52, perform the power device detection method in the embodiment shown in fig. 1-3.
The method has the advantages that the image samples and the fault image samples are obtained in advance, the power equipment analysis model is obtained through training, the collected image of the power equipment to be detected is input into the power equipment analysis model, the identification result of the power equipment to be detected and the defect or fault of the power equipment to be detected are obtained, the real-time detection and fault processing of the power equipment are realized, various inspection task requirements can be met, the problem that the detection efficiency of the power equipment fault is low due to the fact that the traditional scene investigation is used for shooting, and the later manual analysis results in the power equipment fault is solved, the method can be used for automatically analyzing the power equipment defect, meanwhile, the power equipment is more comprehensive in detection, the defect or fault of the power equipment is processed in real time, and the power equipment identification.
The above-mentioned details of the mobile terminal can be understood by referring to the corresponding descriptions and effects in the embodiments shown in fig. 1 to 4, which are not described herein again.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a Flash Memory (Flash Memory), a Hard Disk (Hard Disk Drive, HDD), a Solid-State Drive (SSD), or the like; the storage medium may also comprise a combination of memories of the kind described above.
Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations fall within the scope defined by the appended claims.

Claims (10)

1. An electrical device detection method, comprising:
acquiring an image of the to-be-detected power equipment;
inputting the images of the electric power equipment to be detected into an electric power equipment analysis model, wherein the electric power equipment analysis model is obtained in advance according to image samples of a plurality of electric power equipment and fault image samples corresponding to the electric power equipment through training;
obtaining an identification result of the to-be-detected electrical equipment image according to the electrical equipment analysis model;
judging whether the identification result needs cloud identification;
when the identification result needs to be subjected to cloud identification, the image of the electric power equipment to be detected is sent to a cloud;
and receiving a cloud identification result and a fault analysis result of the cloud.
2. The method according to claim 1, wherein the inputting the to-be-detected power equipment image into a power equipment analysis model comprises:
preprocessing the image of the electric power equipment to be detected according to preset processing conditions;
and inputting the preprocessed image of the electric equipment to be detected into the electric equipment analysis model.
3. The method according to claim 1, wherein obtaining the recognition result of the image of the to-be-detected electrical equipment according to the electrical equipment analysis model comprises:
based on the target sliding window, carrying out target identification on the image area of the electric power equipment to be detected corresponding to any one target sliding window by utilizing the electric power equipment analysis model;
and generating a recognition result of the image of the electric power equipment to be detected according to the target recognition.
4. The method of claim 1, wherein the determining whether cloud recognition is required for the recognition result comprises:
determining the target credibility corresponding to the recognition result based on the recognition result;
judging whether the target reliability exceeds a preset threshold value;
and when the target reliability exceeds a preset threshold value, judging that the identification result needs cloud identification.
5. The method according to any one of claims 1-4, wherein after the receiving the cloud identification results and the failure analysis results of the cloud, the method further comprises:
carrying out fault marking on the to-be-detected power equipment image;
acquiring position information of to-be-detected electric equipment;
and transmitting the image of the to-be-detected power equipment subjected to fault marking, the identification result, the fault analysis result and the position information to a power equipment management platform.
6. The method according to claim 5, wherein after obtaining the recognition result of the image of the to-be-detected electrical equipment according to the electrical equipment analysis model, the method further comprises:
and generating an identification result of the to-be-detected power equipment image and prompt information of a fault analysis result.
7. The method of claim 5, further comprising:
when the identification result does not need to be subjected to cloud identification, fault analysis is carried out according to the identification result of the to-be-detected power equipment image to obtain a fault analysis result;
determining the position information of the to-be-detected power equipment based on the fault analysis result;
and transmitting the image of the electric power equipment to be detected, the identification result, the fault analysis result and the position information to an electric power equipment management platform.
8. An electrical equipment detection device, comprising:
the image acquisition module is used for acquiring an image of the electric power equipment to be detected;
the image input module is used for inputting the images of the to-be-detected power equipment into a power equipment analysis model, and the power equipment analysis model is obtained by training in advance according to image samples of a plurality of power equipment and fault image samples corresponding to the power equipment;
the image identification module is used for obtaining an identification result of the image of the electric power equipment to be detected according to the electric power equipment analysis model;
the judging module is used for judging whether the identification result needs to be subjected to cloud identification;
the sending module is used for sending the image of the electric power equipment to be detected to a cloud terminal when the cloud terminal identification is needed in the identification result;
and the receiving module is used for receiving the cloud identification result and the fault analysis result of the cloud.
9. A mobile terminal, comprising:
the image acquisition module is used for acquiring images of the power equipment;
the positioning module is used for determining the position information of the electric power equipment;
a memory and a processor, wherein the memory and the processor are communicatively connected with each other, the memory stores computer instructions, and the processor executes the computer instructions to execute the power equipment detection method according to any one of claims 1 to 7;
and the prompting module is used for prompting the processing result.
10. A computer-readable storage medium storing computer instructions for causing a computer to perform the power device detection method according to any one of claims 1 to 7.
CN202011530560.XA 2020-12-22 2020-12-22 Power equipment detection method and device and mobile terminal Pending CN112714284A (en)

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