AI-based self-diagnosis system for building electrical equipment

Abstract

The present invention relates to an AI-based self-diagnosis system for building electrical equipment that enables the detection of deterioration of electrical equipment, which is essential for a building to be utilized according to its purpose, and enables diagnosis of damage or failure optimized for the building, thereby ensuring overall maintenance and management efficiency of the building, and also enables early identification of defects and prediction of future repair timing, thereby providing clear basis data for repair and maintenance plans and promoting sustainable building management. The system comprises: a detection unit (100) capable of detecting insulation deterioration by collecting ultrasonic signals and generating a system capable of determining and predicting the occurrence of insulation damage by detecting positional displacement of a structure; a self-diagnosis unit (200) capable of generating diagnostic data that serves as a basis for predicting discharge, structural stability, and maintenance status of electrical equipment based on the ultrasonics and structural displacement collected through the detection unit (100); and a data communication management unit (300) capable of receiving, classifying, and storing each detection data and diagnostic data from the detection unit (100) and the self-diagnosis unit (200), and enabling real-time linkage with a terminal unit (400). It is composed of a terminal unit (400) that enables real-time monitoring of the detection unit (100) via a data communication management unit (300) and allows the diagnosis data of the self-diagnosis unit (200) to be visually output.

Description

Technology Field

[0001] The present invention relates to a self-diagnosis system for electrical equipment in buildings, and more specifically, to an AI-based self-diagnosis system for electrical equipment in buildings that enables the diagnosis of damage or breakage optimized for the building while detecting deterioration of electrical equipment that is essential for a building to be utilized according to its purpose, thereby ensuring overall maintenance and management efficiency of the building, and also enables the early identification of defects and the prediction of future repair timing, thereby providing clear supporting data for repair and maintenance plans and promoting sustainable building management. Background Technology

[0003] According to generally known domestic fire statistics, more than 30,000 fires occur annually, and it is known that over 30% of them are caused by electricity, indicating that electrical fires are frequent. Electrical fires can occur not only in electrically vulnerable facilities but also in all facilities that use electricity, such as water and sewage treatment facilities, traditional markets with aging electrical equipment, and large buildings.

[0004] In particular, since electrical fires in places with high power consumption, such as factories or large shopping malls, can cause massive property damage and loss of life, there has always been an urgent need for fire prevention systems.

[0006] In Korea, the most active fire prevention measure was to install earth leakage circuit breakers to prevent fires caused by short circuits or leakage currents, which are the main causes of electrical fires. However, since electrical lines are often concealed inside the walls of buildings, it was difficult to completely prevent short circuits or leakage currents in the electrical lines.

[0008] For example, the technical concept regarding a 'self-diagnostic automatic control device' is disclosed in Registered Patent Publication No. 10-2406874.

[0009] The technical concept is characterized by providing an automatic control device capable of self-diagnosis that enables rapid response by displaying a response method corresponding to the data in the display unit from the self-diagnosis unit in the event of a wire break or a relay coil failure.

[0011] Furthermore, there is a need for technology capable of detecting and diagnosing defects in electrical facilities caused not only by the electrical equipment itself but also by issues arising from the building. Prior art literature

[0013] Registered Patent Publication No. 10-2406874 (Date of publication: June 10, 2022) The problem to be solved

[0014] The present invention was created to more actively resolve the aforementioned problems, and its main purpose is to provide an AI-based self-diagnosis system for building electrical facilities that can secure overall maintenance and management efficiency by detecting the deterioration of electrical facilities, which are essential for a building to be utilized according to its purpose, and enabling damage or failure diagnosis optimized for the building.

[0016] In addition, another objective of the present invention is to provide an AI-based self-diagnosis system for building electrical facilities that enables sustainable building management by identifying defects early and predicting future repair timing, thereby providing clear supporting data for repair and maintenance plans. means of solving the problem

[0018] To achieve the above-mentioned problem, the AI-based self-diagnosis system for building electrical facilities proposed by the present invention is as follows.

[0020] The present invention is characterized by being configured to facilitate the lifespan of insulation and the maintenance, management, and repair of electrical equipment installed in a building based on changes in ultrasonic waves and structural displacement, comprising: a sensing unit (100) capable of detecting insulation degradation by collecting ultrasonic signals and detecting positional displacement of a structure to determine and predict the occurrence of insulation damage; a self-diagnosis unit (200) capable of generating diagnostic data that serves as a basis for predicting discharge, structural stability, and maintenance status of electrical equipment based on ultrasonic waves and structural displacement collected through the sensing unit (100); a data communication management unit (300) capable of receiving, classifying, and storing each sensing data and diagnostic data from the sensing unit (100) and the self-diagnosis unit (200), and enabling real-time linkage with a terminal unit (400); and a terminal unit (400) capable of real-time monitoring of the sensing unit (100) via the data communication management unit (300) and visually outputting diagnostic data from the self-diagnosis unit (200).

[0022] The above detection unit (100) is characterized by including: an ultrasonic sensor unit (110) that detects an ultrasonic signal to determine whether the insulation is deteriorating and generates sound wave data; and a displacement sensing unit (120) that is positioned in a structure supporting the electrical equipment and detects the positional displacement of the structure itself and generates displacement data, thereby determining a discharge caused by the deterioration of the insulation due to ultrasound and detecting positional displacement caused by natural disasters or deterioration at a fixed position of the electrical equipment, thereby enabling the establishment of a maintenance plan for the electrical equipment.

[0024] The above self-diagnosis unit (200) may include: a discharge determination unit (210) that determines whether an insulator is discharged and the location of the discharge by analyzing an ultrasonic signal collected by a detection unit (100); a displacement determination unit (220) that calculates a displacement difference based on the positional displacement collected by the detection unit (100); and a diagnosis data generation unit (230) that generates diagnosis data based on whether the discharge is discharged or the displacement difference of the discharge determination unit (210) and the displacement determination unit (220).

[0026] The present invention may further include the following configurations.

[0028] The above data communication management unit (300) includes: a database unit (310) that stores and manages ultrasonic signals and position displacements collected by the detection unit (100) and diagnostic data of the self-diagnosis unit (200); and a data communication unit (320) that interconnects the terminal unit (400) and the detection unit (100) and transmits the ultrasonic signals and position displacements collected by the detection unit (100) to the terminal unit (400) based on a selection signal or diagnostic data input from the terminal unit (400).

[0030] The above terminal unit (400) further includes: a screen unit (410) configured to visually output ultrasonic signals and position displacement transmitted via a data communication unit (320); and an input unit (420) configured to enable the operation of the detection unit (100) and the management of the database unit (310) by enabling a separate selection signal to be input via the data communication unit (320).

[0032] The above displacement sensing unit (120) is characterized by further including a first sensor unit (121) positioned on the upper side centered on the electrical equipment; and a second sensor unit (122) positioned on one side opposite to the first sensor unit, thereby enabling the establishment of a maintenance plan for the electrical equipment based on the positional displacement of the first sensor unit (121) and the second sensor unit (122).

[0034] The above discharge determination unit (210) further includes: a phase learning unit (211) that learns the phase of the ultrasonic waves generated during discharge; a phase analysis unit (212) that compares and analyzes the learned phase with the phase of the ultrasonic signal collected by the detection unit (100); and a zone discharge determination unit (213) that determines the cause of discharge of the insulating material based on the phase analyzed by the phase analysis unit (212).

[0036] The above diagnostic data generation unit (230) further includes: a discharge location calculation unit (231) configured to specify the discharge location when the discharge is determined by the discharge determination unit (210); a displacement source specification unit (232) that specifies the first sensor unit (121) to the second sensor unit (122) that caused the displacement difference based on the displacement difference calculation value through the displacement repair determination unit (220); and a diagnostic transmission unit (233) that transmits the location of the discharged and the specified first sensor unit or second sensor unit based on the discharge status and the displacement difference calculation value so that it can be verified at the terminal unit (400).

[0038] The above database unit (310) further includes: a first database unit (311) that classifies and stores ultrasonic signals and position displacements collected by the detection unit (100); a second database unit (312) that stores and manages diagnostic data of the self-diagnosis unit (200); and a third database unit (313) that stores and manages pre-learning data on the causes of ultrasonic generation by phase and classifies the ultrasonic signals of the first database unit (311) as learning data. The discharge determination unit (210) is characterized by being able to determine the causes of ultrasonic generation by phase based on the pre-learning data of the third database unit (313), and by enabling optimized determination based on the learning data. Effects of the invention

[0040] According to the present invention, which is configured as described above, it is possible to detect deterioration of electrical facilities that are essential for a building to be utilized according to its purpose, and to diagnose damage or breakage optimized for the building, thereby ensuring overall maintenance and management efficiency of the building.

[0042] In addition, by identifying defects early and making it possible to predict future repair timing, clear supporting data can be prepared for repair and maintenance plans, thereby enabling sustainable building management. Brief explanation of the drawing

[0044] FIG. 1 is a schematic diagram of the AI-based building electrical equipment self-diagnosis system of the present invention. FIG. 2 is a block diagram of the AI-based building electrical equipment self-diagnosis system of the present invention. FIG. 3 is an embodiment of the first and second sensor units (121, 122) of the AI-based building electrical equipment self-diagnosis system of the present invention. FIG. 4 is another embodiment of the AI-based building electrical equipment self-diagnosis system of the present invention. Specific details for implementing the invention

[0045] First, the advantages and features of the present invention and the methods for achieving them will become clear by referring to the embodiments described below in detail together with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below, but can be implemented in various different forms. These embodiments are provided merely to ensure that the disclosure of the present invention is complete and to fully inform those skilled in the art of the scope of the invention, and the present invention is defined only by the scope of the claims. Furthermore, throughout the entire specification, the same reference numerals refer to the same components.

[0047] It should be noted that the present invention relates to an AI-based self-diagnosis system for building electrical equipment that enables the detection of deterioration of electrical equipment, which is essential for a building to be utilized according to its purpose, and enables diagnosis of damage or failure optimized for the building, thereby ensuring overall maintenance and management efficiency of the building, as well as early identification of defects and the prediction of future repair timing, and thus provides clear supporting data for repair and maintenance plans, thereby aiming for sustainable building management.

[0049] Throughout the specification, when it is stated that a part is "connected" to another part, this includes not only cases where it is "directly connected," but also cases where it is "electrically connected" with other components interposed between them. Furthermore, when it is stated that a part "includes" a certain component, this means that, unless specifically stated otherwise, it does not exclude other components but may include additional components.

[0050] In addition, the present invention lists systemic configurations, wherein the name of '...part' may be composed of hardware or a combination of hardware and software, and may also refer to a device that includes functions.

[0052] Hereinafter, the structure and effects of the present invention will be described collectively.

[0054] Before describing the invention, since electric lines are often concealed inside the walls (1) of buildings, constant monitoring of defects in the electric lines is required. In the case of large-scale facilities, personnel are deployed to manage them, but there are clear limitations in that this cannot be definitively considered to be significant in terms of efficiency and effectiveness.

[0056] In order to improve such conventional inefficient environments and further reduce social costs by protecting lives, the present invention may be composed of a sensing unit (100); a self-diagnosis unit (200); a data communication management unit (300); and a terminal unit (400).

[0058] Specifically, as illustrated in FIGS. 1 and 2, the present invention is characterized by being configured to enable the lifespan of an insulator and the maintenance, management, and repair of electrical equipment installed in a building based on changes in ultrasonic waves and structural displacement, comprising: a sensing unit (100) capable of detecting the deterioration of an insulator by collecting ultrasonic signals and capable of detecting positional displacement of a structure to enable the determination and prediction of damage to the insulator; a self-diagnosis unit (200) capable of generating diagnostic data that serves as a basis for predicting discharge, structural stability, and maintenance of electrical equipment based on ultrasonic waves and structural displacement collected through the sensing unit (100); a data communication management unit (300) capable of receiving, classifying, and storing each sensing data and diagnostic data from the sensing unit (100) and the self-diagnosis unit (200), and enabling real-time linkage with a terminal unit (400); and a terminal unit (400) capable of real-time monitoring of the sensing unit (100) via the data communication management unit (300) and enabling the visual output of diagnostic data from the self-diagnosis unit (200).

[0060] The above-mentioned detection unit (100) enables the detection of a sound generated by an ultrasonic sensor that can identify defects in electrical equipment (wires, switchboards) in a wavelength range that is inaudible to the human body. Based on the amplitude, shape, intensity, etc. of the wavelength of the detected simple ultrasonic sound (WAV), cracks, poor contact of insulators, and erosion of wires can be identified.

[0061] In addition, switchboards, transformers, and circuit breakers are formed on one side of the building, and by collecting positional displacement of the building structure to predict in advance the safety of the facilities and defects in the electrical lines connected to them, it is possible to prepare for natural disasters.

[0062] The self-diagnosis unit (200) above generates diagnostic data based on ultrasonic detection and position displacement of the detection unit (100). The diagnostic data may be specific data regarding the occurrence of cracks in electrical equipment, poor contact of insulators, or erosion of wires, or position displacement values ​​due to natural disasters in building structures, in other words, subsidence or cracks in the structure, etc.

[0063] In particular, in the case of ultrasound, different sounds may be generated depending on the material, and a pre-training process can be further performed through a machine learning-based algorithm to optimize it for the building in question. The pre-training data includes information (data) such as cracks, poor contact of insulators, and erosion of wires according to the amplitude, shape, and intensity of the wavelength of the ultrasonic sound (WAV).

[0064] The above data communication management unit (300) stores and manages ultrasonic signals and position displacements collected by the detection unit (100) and diagnostic data of the self-diagnosis unit (200), interconnects the terminal unit (400) and the detection unit (100), and transmits the ultrasonic signals and position displacements collected by the detection unit (100) to the terminal unit (400) based on selection signals or diagnostic data input from the terminal unit (400), thereby enabling the user (manager) of the terminal unit (400) to identify defects that have occurred in the electrical equipment of the building where the detection unit (100) is installed.

[0065] The above terminal unit (400) may be a PC or portable terminal equipped with a separate input means, which may further include a screen for visually displaying diagnostic data of the self-diagnosis unit (200), and may be capable of real-time monitoring of the detection unit (100) via the data communication management unit (300) as a management department or manager of a building in which the present invention is installed. At this time, it may be configured to select whether to operate the detection unit (100) by receiving data from the data communication management unit (300) or transmitting an input signal through the input means, and for this purpose, it may be a device connected to a mobile communication network or a separate internet network.

[0066] Thus, the present invention ensures the safety of electrical lines concealed inside walls and switchboards and circuit breakers fixed to building structures, enables constant monitoring without separate management personnel, and allows for the management of the entire building based on positional displacement of the building structure rather than focusing on electrical facilities for the operation of the building.

[0068] To this end, the present invention further includes the following configuration.

[0070] The above detection unit (100) includes: an ultrasonic sensor unit (110) that detects an ultrasonic signal to determine whether the insulation material is deteriorated and generates sound wave data; and a displacement sensing unit (120) that is positioned in a structure supporting the electrical equipment and detects the positional displacement of the structure itself and generates displacement data.

[0071] The above ultrasonic sensor unit (110) can acquire an ultrasonic signal through a digital MEMS microphone array of an ultrasonic camera. It is obvious that band-pass filtering, etc., can be performed to remove external noise and disturbance signals from the measurement of such ultrasonic signals and to perform signal processing.

[0072] In addition, the collected ultrasonic signals can be visually displayed by predicting the sound field propagating in three-dimensional space-time—namely, sound pressure, particle velocity, and acoustic energy—through sound field visualization technology, thereby enabling tracking of the location of the noise source and the radiation path of the sound field. For sound field visualization, a beamforming technique can be further performed to correct for time delays in each ultrasonic signal and sum them to form a delayed sum beam.

[0073] The above displacement sensing unit (120) further comprises a first sensor unit (121) positioned on the upper side centered on the electrical equipment; and a second sensor unit (122) positioned on the lower side opposite to the second sensor unit, thereby enabling the establishment of a maintenance plan for the electrical equipment based on the positional displacement of the second sensor unit (121) and the second sensor unit (122).

[0074] For example, as illustrated in FIG. 3, the first sensor unit (121) may be positioned on the upper part of a building (which can be represented as a structure) (1) on which a power distribution board (10) is placed, and the second sensor unit (122) may be positioned on the lower part of the same structure to detect displacement of the structure due to unforeseen disasters caused by ground erosion, earthquakes, or vibrations. Additionally, the first sensor unit (121) may be positioned on a structure containing a power distribution board, and the second sensor unit (122) may be positioned on another structure opposite to that structure, thereby enabling detection of erosion or displacement of several structures supporting the building.

[0075] Specifically, the first sensor unit (121) and the second sensor unit (122) are coupled to each other while positioned on the same horizontal or vertical line, and detection of any positional displacement can be performed.

[0076] Through the above ultrasonic sensor unit (110) and displacement sensing unit (120), discharge caused by deterioration of insulation material due to ultrasonic waves can be identified and position displacement caused by natural disasters or deterioration can be detected at a fixed position of the electrical equipment, and the user can diagnose the risk of electrical equipment not only by concealed electrical lines but also by direct position displacement of buildings, thereby enabling the establishment of a maintenance plan for the electrical equipment.

[0077] In addition, the aforementioned ultrasonic sensor unit and displacement sensor unit can be configured so that their operation can be controlled by the terminal unit (400), which implies the use of IoT technology.

[0079] As illustrated in FIG. 4, the self-diagnosis unit (200) may include: a discharge determination unit (210) that determines whether an insulator is discharged and the location of the discharge by analyzing an ultrasonic signal collected by a detection unit (100); a displacement determination unit (220) that calculates a displacement difference based on the positional displacement collected by the detection unit (100); and a diagnosis data generation unit (230) that generates diagnosis data based on whether the discharge is discharged or the displacement difference of the discharge determination unit (210) and the displacement determination unit (220).

[0080] The discharge determination unit (210) can make it possible to track the location of the noise source and the radiation path of the sound field by predicting and visually displaying the sound field propagating in three-dimensional space-time, namely sound pressure, particle velocity, and acoustic energy, through sound field visualization technology using the collected ultrasonic signal. That is, the ultrasonic generation location and radiation path are determined by visualizing the sound wave data, which is the ultrasonic signal collected by the ultrasonic sensor unit (110). To this end, the beam power level of a virtual plane point can be programmed to be calculated using a beamforming technique.

[0081] The above displacement determination unit (220) means that it is configured to be able to calculate the displacement difference, that is, the difference in distance from the initially set position of the second sensor unit (121) or the second sensor unit (122), based on the position displacement and change of the first sensor unit (121) and the second sensor unit (122).

[0082] The above diagnostic data generation unit (230) generates diagnostic data based on the respective data determined by the discharge determination unit (210) and the displacement determination unit (220). This diagnostic data refers to data regarding ground subsidence of a building structure or structural bending phenomena that can be inferred or predicted by the presence or absence of discharge, the location of the discharge, and the positional displacement, and may include data that is converted into visual data that can be visually verified by an administrator (user) operating the terminal unit (400). That is, the administrator (user) can establish a maintenance plan for the entire building based on the positional displacement or the presence or absence of discharge indicated in the diagnostic data.

[0083] The above diagnostic data generation unit (230) further includes: a discharge location calculation unit (231) configured to specify the discharge location when the discharge is determined by the discharge determination unit (210); a displacement source specification unit (232) that specifies the first sensor unit (121) to the second sensor unit (122) that caused the displacement difference based on the displacement difference calculation value through the displacement determination unit (220); and a diagnostic transmission unit (233) that transmits the location of the discharged and the specified first sensor unit or second sensor unit based on the discharge status and the displacement difference calculation value so that it can be verified at the terminal unit (400).

[0084] In particular, the variable selection unit (232) selects the sensor unit among the first sensor unit (121) to the second sensor unit (122) where position variation has occurred, and in advance, identifiable numbers, etc. may be set in the first sensor unit and the second sensor unit.

[0085] This self-diagnosis unit (200) suggests that it includes artificial intelligence programming employing a machine learning algorithm.

[0087] The above data communication management unit (300) includes: a database unit (310) that stores and manages ultrasonic signals and position displacements collected by the detection unit (100) and diagnostic data of the self-diagnosis unit (200); and a data communication unit (320) that interconnects the terminal unit (400) and the detection unit (100) and transmits the ultrasonic signals and position displacements collected by the detection unit (100) to the terminal unit (400) based on a selection signal or diagnostic data input from the terminal unit (400).

[0088] The above database unit (310) further includes: a first database unit (311) that classifies and stores ultrasonic signals and position displacements collected by the detection unit (100); a second database unit (312) that stores and manages diagnostic data of the self-diagnosis unit (200); and a third database unit (313) that stores and manages pre-learning data on the causes of ultrasonic generation by phase and classifies the ultrasonic signals of the first database unit (311) as learning data. The discharge determination unit (210) is characterized by being able to determine the causes of ultrasonic generation by phase based on the pre-learning data of the third database unit (313), and by enabling optimized determination based on the learning data.

[0090] The above terminal unit (400) further includes: a screen unit (410) configured to visually output ultrasonic signals and position displacement transmitted via a data communication unit (320); and an input unit (420) configured to enable the operation of the detection unit (100) and the management of the database unit (310) by enabling a separate selection signal to be input via the data communication unit (320).

[0092] The present invention may further include the following configurations.

[0094] As illustrated in FIG. 4, the discharge determination unit (210) further includes: a phase learning unit (211) that learns the phase of the ultrasonic waves generated during discharge; a phase analysis unit (212) that compares and analyzes the learned phase with the phase of the ultrasonic signal collected by the detection unit (100); and a zone discharge determination unit (213) that determines the cause of discharge of the insulating material based on the phase analyzed by the phase analysis unit (212).

[0095] The above phase learning unit (211) can continuously learn the phase of ultrasonic waves that occur differently depending on the equipment of each electrical facility and the structure of the building, thereby improving the accuracy of capturing discharge sounds generated from electrical facilities within the building to which the present invention is applied, and at the same time enabling optimized diagnosis of the building.

[0096] The above phase analysis unit (212) can extract suspected partial discharge pulses from the envelope of the ultrasonic signal, generate a pattern in a window divided by a predetermined period of power frequency, and then analyze this pattern with the ultrasonic pattern generated by the cause. Specifically, it can accumulate signals (suspected pulses) that are repeated every 1 cycle of power frequency and generate a pattern based on this.

[0097] Based on these analysis results, the zone discharge determination unit (231) can perform the process of identifying the cause.

[0098] In this case, it can be said that a suspected pulse may be defined from the envelope extracted through the Hilbert transform, etc., for the AC component ultrasonic signal measured by a MEMS sensor.

[0100] According to the present invention as described above, it is possible to detect deterioration of electrical facilities that are essential for a building to be utilized according to its purpose, and to diagnose damage or breakage optimized for the building, thereby ensuring overall maintenance and management efficiency of the building.

[0101] In addition, by identifying defects early and making it possible to predict future repair timing, clear supporting data can be prepared for repair and maintenance plans, thereby enabling sustainable building management.

[0103] To explain the above functions, effects, configurations, and operations, reference has been made to an exemplary embodiment illustrated in the drawings, but this is merely illustrative and should be made clear to those skilled in the art that various modifications and equivalent alternative embodiments are possible therefrom. Accordingly, the true scope of technical protection of the present invention should be interpreted by the appended claims, and all technical ideas within an equivalent scope should be interpreted as being included within the scope of rights of the present invention. Explanation of the symbols

[0105] 100 : Detection unit 110 : Ultrasonic sensor unit 120: Displacement sensing unit 121: First sensor unit 122 : 2nd Sensor Unit 200 : Self-Diagnosis Unit 210: Discharge Discrimination Unit 211: Phase Learning Unit 212: Phase Analysis Unit 213: Zone Discharge Discrimination Unit 220: Displacement determination unit 230: Diagnostic data generation unit 300: Data Communications Management Department 310: Database Department 320 : Data Communication Unit 400 : Terminal Unit 410 : Screen section 420 : Input section

Claims

Claim 1 In an AI-based self-diagnosis system for building electrical equipment, the sensing unit (100) is capable of detecting insulation degradation by collecting ultrasonic signals and detecting positional displacement of a structure to determine and predict the occurrence of insulation damage; the self-diagnosis unit (200) is capable of generating diagnostic data that serves as a basis for predicting discharge, structural stability, and maintenance status of electrical equipment based on the ultrasonic signals and structural displacement collected through the sensing unit; the data communication management unit (300) is capable of receiving, classifying, and storing each of the sensing data and diagnostic data from the sensing unit and the self-diagnosis unit, and is capable of real-time linkage with a terminal unit (400); and the terminal unit (400) is capable of real-time monitoring of the sensing unit via the data communication management unit and visually outputting the diagnostic data from the self-diagnosis unit. In this system, the sensing unit (100) is formed by an ultrasonic sensor unit (110) that detects ultrasonic signals to determine whether insulation degradation has occurred and generates sound wave data, and a displacement sensing unit (120) that is disposed on a structure supporting electrical equipment and detects positional displacement of the structure itself and generates displacement data. The self-diagnosis unit (200) includes a discharge determination unit (210) that determines whether there is a discharge and the location of the discharge by analyzing ultrasonic signals collected by the detection unit (100); a displacement determination unit (220) that calculates a displacement difference based on the location of the displacement collected by the detection unit (100); and a diagnosis data generation unit (230) that generates diagnosis data based on the discharge determination unit and the displacement difference. The data communication management unit (300) includes a database unit (310) that stores and manages ultrasonic signals collected by the detection unit (100), location displacement, and diagnosis data of the self-diagnosis unit (200).The device includes a terminal unit (400) and a detection unit (100) that mutually link the terminal unit (400) and the detection unit (100), and a data communication unit (320) that transmits ultrasonic signals and position displacements collected by the detection unit (100) to the terminal unit (400) based on selection signals or diagnostic data input from the terminal unit (400); and the terminal unit (400) further includes a screen unit (410) configured to visually output ultrasonic signals and position displacements transmitted via the data communication unit (320), and an input unit (420) that enables the operation of the detection unit (100) and the management of the database unit (310) by allowing a separate selection signal to be input via the data communication unit (320); wherein the displacement sensing unit (120) is divided into a first sensor unit (121) positioned on the upper part of a structure on which a power distribution board (10) is placed, and a second sensor unit (122) positioned on the lower part of the same vertical line of the same structure on which the first sensor unit is placed, or positioned at a set location of another structure. It is formed to enable the detection of positional displacement of a single structure or the identification of erosion or positional displacement of several structures, and the discharge determination unit (210) further includes: a phase learning unit (211) that learns the phase of the ultrasonic waves generated during discharge; a phase analysis unit (212) that compares and analyzes the learned phase with the phase of the ultrasonic signal collected by the detection unit (100); and a zone discharge determination unit (213) that determines the cause of discharge of an insulating material based on the phase analyzed by the phase analysis unit (212); and the diagnostic data generation unit (230) further includes: a discharge location calculation unit (231) that enables the determination of the discharge location when discharge is determined by the discharge determination unit (210); a displacement source determination unit (232) that determines the first sensor unit (121) to the second sensor unit (122) that caused the displacement difference based on the displacement difference calculation value through the displacement repair determination unit (220); and the discharge and the determined based on the discharge status and the displacement difference calculation value. A diagnostic transmission unit (233) that transmits the location of the first sensor unit or the second sensor unit so that it can be verified at the terminal unit (400); further comprising the database unit (310);The AI-based building electrical equipment self-diagnosis system further comprises: a first database unit (311) that classifies and stores ultrasonic signals and position displacements collected by a detection unit (100); a second database unit (312) that stores and manages diagnostic data of a self-diagnosis unit (200); and a third database unit (313) that stores and manages pre-learning data on the causes of ultrasonic generation by ultrasonic phase and classifies the ultrasonic signals of the first database unit (311) as learning data; and enables the discharge discrimination unit (210) to determine the causes of ultrasonic generation by ultrasonic phase based on the pre-learning data of the third database unit (313), while enabling optimized determination based on the learning data. Claim 2 delete Claim 3 delete

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