Power equipment wire tube internal joint state analysis system using in-situ visual detection

Abstract

This invention relates to a system for analyzing the internal joint status of electrical conduits using penetrating visual inspection. The system includes: a penetrating camera, which enters the conduit containing wires to perform real-time video recording of the conduit's internal environment; and an audio warning mechanism, used to play a warning audio file corresponding to the conduit's internal joint being a wire joint and not a discarded joint or a joint on other components, when a binary identifier indicating contact between wires and joints output by a deep neural network model indicates contact. This system can intelligently identify the presence of contact between wires and joints inside the conduit using multiple targeted filtered visual information based on a deep neural network model, and accordingly play the warning audio file corresponding to the conduit's internal joint being a wire joint and not a discarded joint or a joint on other components, thereby improving the safety and reliability of electrical conduit use.

Description

Technical Field

[0001] This invention relates to the field of power testing, and more specifically, to a system for analyzing the internal joint status of electrical conduits in power equipment using penetrating visual inspection. Background Technology

[0002] Image analysis is the extraction of meaningful information from images; primarily through digital image processing techniques. Image analysis tasks can range from as simple as reading a barcode label to as complex as recognizing a person from their face. Computers are indispensable for analyzing large amounts of data, for tasks requiring complex computation, or for extracting quantitative information. On the other hand, the human visual cortex is an excellent image analysis instrument, especially in extracting higher-level information, and for many applications—including medicine, security, and remote sensing—human analysts remain irreplaceable by computers. For this reason, many important image analysis tools, such as edge detectors and neural networks, are inspired by models of human visual perception. Digital image analysis, or computer image analysis, refers to the automated study of images by computers or electrical devices to obtain useful information. It involves the fields of computer or machine vision and medical imaging, and makes extensive use of pattern recognition, digital geometry, and signal processing.

[0003] However, while image analysis can be clearly applied to various specific sub-fields, some specific sub-fields still lack sufficiently effective and mature solutions. For example, there is a need for specific image analysis-based analysis of the joints inside electrical conduits that are joints on conductors rather than discarded joints or joints on other components, in order to intelligently identify whether there are illegal joints on conductors inside electrical conduits, thereby maintaining the safe operation of on-site electrical equipment. Obviously, there is currently a lack of corresponding mature technical solutions. Summary of the Invention

[0004] To address the aforementioned problems, this invention provides a system for analyzing the status of internal connectors in electrical conduits using penetrating visual inspection. This system inputs the pixel values ​​of each component pixel in a dynamically processed image of the conductor, the pixel values ​​of each component pixel in the dynamically processed image of the connector, the total number of component pixels of the conductor, and the total number of component pixels of the connector in the dynamically processed image into a deep neural network model. The deep neural network model is then run to obtain a binary identifier indicating whether the conductor and connector are in contact. Furthermore, an audible warning mechanism is introduced. When the binary identifier of whether the conductor and connector are in contact indicates that there is contact, a warning voice message is played corresponding to the connector being a conductor connector, not a discarded connector or a connector on other components. Otherwise, a notification voice message is played corresponding to the connector being a non-discarded connector or a connector on other components, thereby achieving intelligent identification and on-site alarm operation for whether there are illegal conductor connectors inside the conduit.

[0005] This invention must possess at least the following important inventive points:

[0006] First: Obtain each component pixel of the wire and the connector in the dynamic processing image, and count the total number of component pixels of the wire and the connector in the dynamic processing image to filter out the basic data for subsequent intelligent judgment.

[0007] Secondly: The pixel values ​​of each component pixel of the wire in the dynamic processing image, the pixel values ​​of each component pixel of the connector in the dynamic processing image, the total number of component pixels of the wire in the dynamic processing image, and the total number of component pixels of the connector in the dynamic processing image are input into a deep neural network model, and the deep neural network model is run to obtain the binary identifier of whether the wire and connector are in contact. The number of learning iterations of the deep neural network model is positively correlated with the signal-to-noise ratio of the dynamic processing image.

[0008] Furthermore, an audible warning mechanism is introduced. When the binary identifier of whether a wire or connector is in contact is output by the deep neural network model, indicating whether a wire or connector is in contact, a warning voice file is played corresponding to the connector inside the conduit being a connector on a wire, rather than a discarded connector or a connector on other components. Otherwise, a notification voice file is played corresponding to the connector inside the conduit being a non-discarded connector or a connector on other components, thereby realizing intelligent identification and on-site alarm operation for whether there is an illegal wire connector inside the conduit.

[0009] According to the present invention, a system for analyzing the internal joint status of electrical conduits in power equipment using penetrating visual inspection is provided, the system comprising:

[0010] An in-vehicle camera enters the interior of a conduit containing wires to perform real-time video recording of the environment inside the conduit, thereby acquiring and outputting corresponding images of the environment inside the conduit.

[0011] A smoothing filter device is installed inside the handle that fixes the probe camera and is connected to the probe camera. It is used to perform edge-preserving smoothing filtering on the received image of the environment inside the tube to obtain and output the corresponding smoothed image.

[0012] An exponential enhancement device, connected to the smoothing filter device, is used to perform image content enhancement processing based on exponential transformation on the received smoothed filter image to obtain and output a corresponding exponentially enhanced image;

[0013] A dynamic processing device, connected to the exponential enhancement device, is used to perform white balance processing based on a dynamic threshold on the received exponentially enhanced image to obtain and output a corresponding dynamically processed image.

[0014] An intelligent analysis mechanism, housed within the handle of the fixed probe camera and connected to the dynamic processing device, is used to acquire each component pixel of the wire and each component pixel of the connector in the dynamic processing image. It counts the total number of component pixels of the wire and the connector in the dynamic processing image, inputs the pixel values ​​of each component pixel of the wire and the connector in the dynamic processing image, the total number of component pixels of the wire and the connector in the dynamic processing image into a deep neural network model, and runs the deep neural network model to obtain its output binary identifier indicating whether the wire and connector are in contact. The number of learning iterations of the deep neural network model is positively correlated with the signal-to-noise ratio of the dynamic processing image.

[0015] The sound warning mechanism, connected to the intelligent analysis mechanism, is used to play a warning voice file corresponding to the fact that the internal connector of the conduit is a connector on the wire rather than a discarded connector or a connector on other parts when the binary identifier of whether the wire and connector are in contact output by the deep neural network model indicates that the wire and connector are in contact.

[0016] The process of acquiring each component pixel of the wire in the dynamic image and acquiring each component pixel of the connector in the dynamic image, and counting the total number of component pixels of the wire and the connector in the dynamic image, includes: the connector is an insulating cloth in a wrapped state, and the wire is a metal wire.

[0017] The electrical conduit internal joint status analysis system of this invention, employing in-depth visual inspection, is logically reliable and has a compact structure. By using multiple targeted filtered visual information based on a deep neural network model to intelligently identify whether there is contact between conductors and joints inside the conduit, it accordingly plays a warning voice message indicating that the internal joint is a conductor joint rather than a discarded joint or a joint on other components, thereby improving the safety and reliability of conduit use. Brief description of the attached figures

[0018] Those skilled in the art will better understand the many advantages of the present invention by referring to the accompanying drawings, wherein:

[0019] Figure 1 This is a schematic diagram of the structure of a power equipment internal connector status analysis system using in-sight vision detection according to the primary embodiment of the present invention.

[0020] Figure 2 This is a schematic diagram of a system for analyzing the internal joint status of electrical conduits in power equipment using in-sight visual inspection, according to a secondary embodiment of the present invention.

[0021] Figure 3 This is a schematic diagram of the structure of a power equipment internal connector status analysis system using in-sight vision detection according to a further embodiment of the present invention. Detailed Implementation

[0022] Figure 1 This is a schematic diagram of a system for analyzing the internal joint status of electrical conduits using penetrating visual inspection, according to a primary embodiment of the present invention. The system includes:

[0023] An in-vehicle camera enters the interior of a conduit containing wires to perform real-time video recording of the environment inside the conduit, thereby acquiring and outputting corresponding images of the environment inside the conduit.

[0024] For example, a probe-type camera, by probing into the interior of an electrical conduit with wires, performs real-time video recording of the environment inside the conduit to obtain and output corresponding images of the environment inside the conduit. This includes: the probe-type camera has a built-in embedded camera, and the embedded camera performs real-time video recording in macro shooting mode.

[0025] A smoothing filter device is installed inside the handle that fixes the probe camera and is connected to the probe camera. It is used to perform edge-preserving smoothing filtering on the received image of the environment inside the tube to obtain and output the corresponding smoothed image.

[0026] An exponential enhancement device, connected to the smoothing filter device, is used to perform image content enhancement processing based on exponential transformation on the received smoothed filter image to obtain and output a corresponding exponentially enhanced image;

[0027] A dynamic processing device, connected to the exponential enhancement device, is used to perform white balance processing based on a dynamic threshold on the received exponentially enhanced image to obtain and output a corresponding dynamically processed image.

[0028] An intelligent analysis mechanism, housed within the handle of the fixed probe camera and connected to the dynamic processing device, is used to acquire each component pixel of the wire and each component pixel of the connector in the dynamic processing image. It counts the total number of component pixels of the wire and the connector in the dynamic processing image, inputs the pixel values ​​of each component pixel of the wire and the connector in the dynamic processing image, the total number of component pixels of the wire and the connector in the dynamic processing image into a deep neural network model, and runs the deep neural network model to obtain its output binary identifier indicating whether the wire and connector are in contact. The number of learning iterations of the deep neural network model is positively correlated with the signal-to-noise ratio of the dynamic processing image.

[0029] The sound warning mechanism, connected to the intelligent analysis mechanism, is used to play a warning voice file corresponding to the fact that the internal connector of the conduit is a connector on the wire rather than a discarded connector or a connector on other parts when the binary identifier of whether the wire and connector are in contact output by the deep neural network model indicates that the wire and connector are in contact.

[0030] The process of acquiring each component pixel of the wire in the dynamic image and acquiring each component pixel of the connector in the dynamic image, and counting the total number of component pixels of the wire and the connector in the dynamic image, includes: the connector is an insulating cloth in a wrapped state, and the wire is a metal wire.

[0031] The process of obtaining each component pixel of the wire in the dynamic processing image and obtaining each component pixel of the connector in the dynamic processing image, and counting the total number of component pixels of the wire in the dynamic processing image and the total number of component pixels of the connector in the dynamic processing image, further includes: identifying the imaging area of ​​the wire in the dynamic processing image based on the color imaging features corresponding to the wire, and taking each pixel of the imaging area of ​​the wire in the dynamic processing image as each component pixel of the wire in the dynamic processing image.

[0032] The sound warning mechanism is also used to play a notification voice file corresponding to the connection inside the conduit being a non-discarded connection or a connection on other parts of the non-conductor when the binary identifier of whether the wire and connector are in contact output by the deep neural network model indicates that the wire and connector are not in contact.

[0033] Figure 2 This is a schematic diagram of a system for analyzing the internal joint status of electrical conduits in power equipment using in-sight visual inspection, according to a secondary embodiment of the present invention.

[0034] and Figure 1 different, Figure 2 The electrical conduit internal joint status analysis system for power equipment employing in-sight vision inspection may also include the following components:

[0035] The touchscreen is used to receive input information from the user for the smoothing filter, the exponential enhancement device, the dynamic processing device, and the intelligent analysis mechanism, respectively, based on the user's operation.

[0036] Figure 3 This is a schematic diagram of the structure of a power equipment internal connector status analysis system using in-sight vision detection according to a further embodiment of the present invention.

[0037] and Figure 1 different, Figure 3 The electrical conduit internal joint status analysis system for power equipment employing in-sight vision inspection may also include the following components:

[0038] A pressure detection device is installed on the housing of the smoothing filter, the exponential enhancement device, the dynamic processing device, and the intelligent analysis mechanism, and is used to measure the instantaneous pressure currently borne by the housing of any one of the smoothing filter, the exponential enhancement device, the dynamic processing device, and the intelligent analysis mechanism;

[0039] The pressure detection device is installed on the housing of the smoothing filter, the exponential enhancement device, the dynamic processing device, and the intelligent analysis mechanism. It is used to measure the instantaneous pressure currently borne by the housing of any one of the smoothing filter, the exponential enhancement device, the dynamic processing device, and the intelligent analysis mechanism. The pressure detection device has a built-in pressure analysis device, which is used to issue a pressure alarm command when the instantaneous pressure currently borne by the housing of any one of the smoothing filter, the exponential enhancement device, the dynamic processing device, and the intelligent analysis mechanism exceeds the limit.

[0040] The pressure detection device, installed on the housings of the smoothing filter, the exponential enhancement device, the dynamic processing device, and the intelligent analysis mechanism, is used to measure the instantaneous pressure currently borne by the housing of any one of the smoothing filter, the exponential enhancement device, the dynamic processing device, and the intelligent analysis mechanism. It also includes a built-in pressure analysis device that issues a pressure safety command when the instantaneous pressure received from the housings of each of the smoothing filter, the exponential enhancement device, the dynamic processing device, and the intelligent analysis mechanism is within the limit.

[0041] The pressure detection device, installed on the housings of the smoothing filter, the exponential enhancement device, the dynamic processing device, and the intelligent analysis mechanism, is used to measure the instantaneous pressure currently borne by the housings of any one of the smoothing filter, the exponential enhancement device, the dynamic processing device, and the intelligent analysis mechanism. The pressure detection device also employs multiple pressure detection units to respectively measure the instantaneous pressure currently borne by the housings of the smoothing filter, the exponential enhancement device, the dynamic processing device, and the intelligent analysis mechanism.

[0042] The pressure detection device employs multiple pressure detection units to measure the instantaneous pressure currently borne by the outer shells of the smoothing filter, the exponential enhancement device, the dynamic processing device, and the intelligent analysis mechanism, respectively. The internal structures of the multiple pressure detection units are identical.

[0043] The pressure detection device also includes multiple pressure detection units used to measure the instantaneous pressure currently borne by the shells of the smoothing filter, the exponential enhancement device, the dynamic processing device, and the intelligent analysis mechanism, respectively. Furthermore, the upper and lower limits of the pressure measurement for each of the multiple pressure detection units are equal.

[0044] Wherein, the upper limit value and lower limit value of pressure measurement of the plurality of pressure detection units are equal, including: the upper limit value of pressure measurement is greater than the lower limit value of pressure measurement;

[0045] Furthermore, the pressure detection device employs multiple pressure detection units to measure the instantaneous pressure currently borne by the housings of the smoothing filter, the exponential enhancement device, the dynamic processing device, and the intelligent analysis mechanism. Additionally, the multiple pressure detection units are respectively installed at the bottom of the top of the housings of the smoothing filter, the exponential enhancement device, the dynamic processing device, and the intelligent analysis mechanism, and are located at the center of the bottom.

[0046] In addition, in the electrical equipment conduit internal joint status analysis system using in-sight vision detection, acquiring each component pixel of the conductor in the dynamic processing image and acquiring each component pixel of the joint in the dynamic processing image, and counting the total number of component pixels of the conductor in the dynamic processing image and the total number of component pixels of the joint in the dynamic processing image, further includes: identifying the imaging area of ​​the joint in the dynamic processing image based on the color imaging features corresponding to the joint, and taking each pixel of the imaging area of ​​the joint in the dynamic processing image as each component pixel of the joint in the dynamic processing image.

[0047] While the invention has been described in considerable detail, it should be understood that those skilled in the art can modify its elements without departing from the spirit and scope of the invention. It is believed that the system of the invention and its associated advantages will be understood from the foregoing description, and it will be clear that various changes can be made to its form, structure, and component arrangement without departing from the scope and spirit of the invention or sacrificing all its substantial advantages, and no further substantial changes are provided as the forms described above are merely illustrative embodiments of the invention. The claims are intended to cover and include these changes.

Claims

1. A system for analyzing the internal joint status of electrical conduits in power equipment using penetrating visual inspection, characterized in that, The system includes: An in-vehicle camera enters the interior of a conduit containing wires to perform real-time video recording of the environment inside the conduit, thereby acquiring and outputting corresponding images of the environment inside the conduit. A smoothing filter device is installed inside the handle that fixes the probe camera and is connected to the probe camera. It is used to perform edge-preserving smoothing filtering on the received image of the environment inside the tube to obtain and output the corresponding smoothed image. An exponential enhancement device, connected to the smoothing filter device, is used to perform image content enhancement processing based on exponential transformation on the received smoothed filter image to obtain and output a corresponding exponentially enhanced image; A dynamic processing device, connected to the exponential enhancement device, is used to perform white balance processing based on a dynamic threshold on the received exponentially enhanced image to obtain and output a corresponding dynamically processed image. An intelligent analysis mechanism, housed within the handle of the fixed probe camera and connected to the dynamic processing device, is used to acquire each component pixel of the wire and each component pixel of the connector in the dynamic processing image. It counts the total number of component pixels of the wire and the connector in the dynamic processing image, inputs the pixel values ​​of each component pixel of the wire and the connector in the dynamic processing image, the total number of component pixels of the wire and the connector in the dynamic processing image into a deep neural network model, and runs the deep neural network model to obtain its output binary identifier indicating whether the wire and connector are in contact. The number of learning iterations of the deep neural network model is positively correlated with the signal-to-noise ratio of the dynamic processing image. The sound warning mechanism, connected to the intelligent analysis mechanism, is used to play a warning voice file corresponding to the fact that the internal connector of the conduit is a connector on the wire rather than a discarded connector or a connector on other parts when the binary identifier of whether the wire and connector are in contact output by the deep neural network model indicates that the wire and connector are in contact. The process of acquiring each component pixel of the wire in the dynamic processing image and acquiring each component pixel of the connector in the dynamic processing image, and counting the total number of component pixels of the wire in the dynamic processing image and the total number of component pixels of the connector in the dynamic processing image includes: the connector is an insulating cloth in a wrapped state, and the wire is a metal wire. The process of obtaining each component pixel of the wire in the dynamic processing image and obtaining each component pixel of the connector in the dynamic processing image, and counting the total number of component pixels of the wire in the dynamic processing image and the total number of component pixels of the connector in the dynamic processing image, also includes: identifying the imaging area of ​​the wire in the dynamic processing image based on the color imaging features corresponding to the wire, and taking each pixel of the imaging area of ​​the wire in the dynamic processing image as each component pixel of the wire in the dynamic processing image. Based on the color imaging features corresponding to the connector, the imaging area of ​​the connector in the dynamic processing image is identified, and each pixel of the imaging area of ​​the connector in the dynamic processing image is taken as the constituent pixel of the connector in the dynamic processing image. The sound warning mechanism is also used to play a notification voice file corresponding to the connection inside the conduit being a non-discarded connection or a connection on other parts of the non-conductor when the binary identifier of whether the wire and connector are in contact output by the deep neural network model indicates that the wire and connector are not in contact.

2. The electrical conduit internal joint status analysis system for power equipment using penetrating visual inspection as described in claim 1, characterized in that, The system also includes: The touchscreen is used to receive input information from the user for the smoothing filter, the exponential enhancement device, the dynamic processing device, and the intelligent analysis mechanism, respectively, based on the user's operation.

3. The electrical conduit internal joint status analysis system for power equipment using penetrating visual inspection as described in claim 1, characterized in that, The system also includes: A pressure detection device is installed on the housing of the smoothing filter, the exponential enhancement device, the dynamic processing device, and the intelligent analysis mechanism, and is used to measure the instantaneous pressure currently borne by the housing of any one of the smoothing filter, the exponential enhancement device, the dynamic processing device, and the intelligent analysis mechanism.

4. The electrical conduit internal joint status analysis system for power equipment using penetrating visual inspection as described in claim 3, characterized in that: A pressure detection device, installed on the housing of the smoothing filter, the exponential enhancement device, the dynamic processing device, and the intelligent analysis mechanism, is used to measure the instantaneous pressure currently borne by the housing of any one of the smoothing filter, the exponential enhancement device, the dynamic processing device, and the intelligent analysis mechanism. The pressure detection device includes a built-in pressure analysis device, used to issue a pressure alarm command when the instantaneous pressure currently borne by the housing of any one of the smoothing filter, the exponential enhancement device, the dynamic processing device, and the intelligent analysis mechanism exceeds the limit.

5. The electrical conduit internal joint status analysis system for power equipment using penetrating visual inspection as described in claim 4, characterized in that: A pressure detection device, installed on the housings of the smoothing filter, the exponential enhancement device, the dynamic processing device, and the intelligent analysis mechanism, is used to measure the instantaneous pressure currently borne by the housing of any one of the smoothing filter, the exponential enhancement device, the dynamic processing device, and the intelligent analysis mechanism. The pressure detection device also includes a built-in pressure analysis device, used to issue a pressure safety command when the received instantaneous pressure borne by the housings of each of the smoothing filter, the exponential enhancement device, the dynamic processing device, and the intelligent analysis mechanism is within limits.

6. The electrical conduit internal joint status analysis system for power equipment using penetrating visual inspection as described in claim 5, characterized in that: A pressure detection device, installed on the housing of the smoothing filter, the exponential enhancement device, the dynamic processing device, and the intelligent analysis mechanism, is used to measure the instantaneous pressure currently borne by the housing of any one of the smoothing filter, the exponential enhancement device, the dynamic processing device, and the intelligent analysis mechanism. The pressure detection device further includes: employing multiple pressure detection units to respectively measure the instantaneous pressure currently borne by the housing of the smoothing filter, the exponential enhancement device, the dynamic processing device, and the intelligent analysis mechanism.

7. The electrical conduit internal joint status analysis system for power equipment using penetrating visual inspection as described in claim 6, characterized in that, Also includes: The pressure detection device employs multiple pressure detection units to measure the instantaneous pressure currently borne by the outer shell of the smoothing filter, the exponential enhancement device, the dynamic processing device, and the intelligent analysis mechanism, respectively. The internal structure of the multiple pressure detection units is identical.

8. The electrical conduit internal joint status analysis system for power equipment using penetrating visual inspection as described in claim 7, characterized in that, Also includes: The pressure detection device employs multiple pressure detection units to measure the instantaneous pressure currently borne by the shells of the smoothing filter, the exponential enhancement device, the dynamic processing device, and the intelligent analysis mechanism, respectively. Furthermore, the upper and lower limits of the pressure measurement for each of the multiple pressure detection units are equal. Wherein, the upper limit value and lower limit value of pressure measurement of the plurality of pressure detection units are equal, including: the upper limit value of pressure measurement is greater than the lower limit value of pressure measurement; The pressure detection device employs multiple pressure detection units to measure the instantaneous pressure currently borne by the housings of the smoothing filter, the exponential enhancement device, the dynamic processing device, and the intelligent analysis mechanism. Furthermore, the multiple pressure detection units are respectively installed at the bottom of the top of the housings of the smoothing filter, the exponential enhancement device, the dynamic processing device, and the intelligent analysis mechanism, and are located at the center of the bottom.

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