KR102553453B1 - Apparatus and method of unmaned aerial vehicle for power facilities inspection monitoring - Google Patents

Abstract

The present invention relates to an unmanned diagnostic device and method for monitoring power facilities, and is provided with an autonomous flight path generation unit (100) for generating an autonomous flight path of an UAV for monitoring power facilities, and the autonomous flight path information and Based on the coordinate information of the UAV, the UAV uses an inertial navigation device to fly to the site for fault detection and to obtain monitoring information data of the power facility while allowing the UAV to maintain a safe separation distance from the power facility It includes an unmanned monitoring diagnosis unit 200 and an unmanned monitoring control unit 300 that detects a power facility failure using data received from the unmanned monitoring diagnosis unit 200.
The present invention monitors power facilities using an unmanned aerial vehicle and accurately determines whether or not there is a failure or defect in a transmission line based on objective data, thereby increasing the accuracy of diagnosis on the location of the failure and monitoring power facilities at a low cost. there is.

Description

Unmanned diagnostic device and method for power facility monitoring {APPARATUS AND METHOD OF UNMANED AERIAL VEHICLE FOR POWER FACILITIES INSPECTION MONITORING}

The present invention relates to an unmanned diagnostic device and method for monitoring power facilities, and more particularly, to an unmanned diagnostic device and method for monitoring and diagnosing power facilities using an unmanned areal vehicle (UAV). .

Among power facilities, transmission lines are installed tens of meters in the air from the ground because tens of thousands of volts [V] of high-voltage electricity flows through high-voltage lines, transmission towers, insulators, and clamps through which ultra-high voltage power is transmitted.

Accordingly, transmission lines are exposed to lightning, heavy rain, typhoons, etc., and the possibility of damage increases, and accordingly, it is necessary to perform regular inspections of transmission lines.

However, since the inspection of the transmission line involves a worker directly boarding the pylon bracket and inspecting the transmission line with the naked eye, there is a problem in that the inspection is expensive and ineffective, such as exposing the worker to danger.

In addition, since the inspection of the transmission line needs to be performed after power transmission is stopped, the time available for the operation is limited.

In addition, various monitoring facilities are installed on the steel tower, and the transmission line is estimated and monitored through the monitoring facility.

An object of the present invention is to provide an unmanned diagnostic device and method for monitoring power facilities that monitors power facilities from a remote location using an unmanned aerial vehicle and accurately diagnoses failures or defects of transmission lines based on objective data.

According to a feature of the present invention for achieving the above object, the present invention provides an autonomous flight path generation unit for generating an autonomous flight path of the UAV for monitoring a UAV capable of autonomous flight and power facilities, and the UAV. And based on the autonomous flight path information and the coordinate information of the UAV, the inertial navigation device is used to allow the UAV to fly to the site for fault detection and to maintain a safe separation distance from the power facility, It includes an unmanned monitoring diagnosis unit that acquires facility monitoring information data and an unmanned monitoring control unit that detects power facility failures using data received from the unmanned monitoring diagnosis unit.

The autonomous flight path generation unit includes a modeling unit for 3D modeling real location information of power facilities, a setting unit for setting monitoring and diagnosis location information of power facilities in the 3D modeling, and a 3D modeling unit in which monitoring and diagnosis location information of the power facilities is set. It includes an application unit that sets the autonomous flight path by adding the separation distance.

The unmanned monitoring and diagnosis unit includes a sensor for detecting a separation distance from a power facility and an UAV control unit for controlling autonomous flight of the UAV based on the signal detected by the sensor and the autonomous flight path information.

The detector includes an ultrasonic sensor emitting an ultrasonic signal, a distance measuring unit measuring a distance to an obstacle by detecting an ultrasonic signal emitted and reflected by the ultrasonic sensor, and an obstacle based on the information measured by the distance measuring unit. It includes an alarm unit that generates a warning sound to inform.

The unmanned monitoring diagnostic unit detects overheating points and corona partial discharge signals of power facilities based on monitoring information acquisition devices for acquiring thermal image information and corona information of power facilities and signals acquired by the monitoring information acquisition devices, and discharge distribution density. It includes an acquisition signal processing unit for identifying and a failure detection unit for preliminarily detecting a power facility failure by comparing the information received from the acquisition signal processing unit with a reference value.

The monitoring information acquisition device includes a CCD sensor for capturing images, a thermal image sensor for detecting thermal images, and a UV sensor for detecting corona partial discharge.

Including a mounted equipment control unit for receiving the coordinates of the power facility monitoring object from the unmanned monitoring control unit, fixing the UAV and controlling the 3-axis rotation of the monitoring information acquisition device so that the monitoring information acquisition device aims and tracks the power facility monitoring object do.

It includes an acquisition signal storage unit for storing image information of the power facility failure location previously detected by the failure detection unit together with location information, and a wireless transmission/reception unit for transmitting and receiving data signals wirelessly to and from the unmanned monitoring control unit.

The unmanned monitoring control unit compares the data signal provided from the wireless transmission/reception unit with the data signal provided from the wireless transmission/reception unit for transmitting and receiving data signals with the unmanned monitoring diagnosis unit and the set data, and confirms and detects the failure detection result in advance of power facilities. And a DB storage unit for receiving and displaying the result of the confirmation and detection of the failure location confirmation unit, displaying it to the outside and informing the user, and storing the data as a result of the confirmation and detection of the failure location confirmation unit.

The step of generating an autonomous flight path of an unmanned aerial vehicle for monitoring power facilities by an autonomous flight path creation unit, and a field for detecting a failure of the unmanned aerial vehicle by using an inertial navigation device based on the autonomous flight path information and coordinate information by an unmanned monitoring diagnostic unit. Acquiring monitoring information data of the power facility while flying and maintaining a safe distance from the power facility, and detecting a power facility failure by the unmanned monitoring control unit using data received from the unmanned monitoring diagnosis unit. include

The step of obtaining the monitoring information data of the power facility while the UAV flies to the site for fault detection and maintains a safe separation distance from the power facility, the inertial navigation device including GPS and IMU based on coordinate information location information It controls the UAV to autonomously fly by itself, and detects the separation distance between the power facility and the UAV so that the UAV maintains a safe separation distance from the power facility.

The step of obtaining monitoring information data of the power facility while allowing the UAV to fly to the site for fault detection and maintaining a safe separation distance from the power facility includes: acquiring thermal image information and corona information of the power facility; and Based on the acquired information, detecting an overheating point and a corona partial discharge signal of a power facility and determining a discharge distribution density, and detecting a failure of a power facility in advance based on whether the discharge distribution density is greater than or equal to a reference value.

The discharge distribution density is determined by converting the corona partial discharge signal distribution into a corona discharge image.

The failure occurrence location confirmation unit of the unmanned monitoring control unit compares corona information with preset failure corona waveform information, compares overheating location information with preset overheating prohibition temperature information, and confirms a result of pre-detection of the power facility failure, and the confirmation result is transmitted to the action unit so that it can be transmitted to the user.

Acquiring a faulty corona discharge signal by a UV sensor and converting the distribution of a faulty corona discharge signal into a corona discharge image, an acquisition signal processing unit figuring out the discharge distribution density in the corona discharge image, and a fault detection unit measuring the discharge distribution density The step of comparing the number of partial discharges with a reference value to determine whether there is a failure, and if it is determined that there is a failure as a result of the determination, the step of tracking where the discharge is concentrated and acquiring a high-resolution image signal using a CCD sensor, and It includes the step of receiving accurate location information of a location from an inertial navigation device including GPS and IMU, storing it in an acquisition signal storage unit based on the GPS location information, and transmitting it to an unmanned monitoring control unit.

The present invention monitors the autonomous flight movement of an unmanned aerial vehicle based on the data of the route, altitude, and speed set in advance based on the GPS location in order to monitor and diagnose the presence or absence of failure or defect of power facilities with objective numerical values, and to detect thermal imaging and corona partial discharge When a location where the image discharge distribution density (the number of partial discharges extracted from the image) exceeds the standard value is detected, a high-resolution image corresponding to the location is sent to the control unit to accurately determine whether or not there is a failure or defect in the power facility based on objective data. It is possible to monitor and diagnose power facilities by making judgments, so there is an effect of configuring a precise system for monitoring power facilities.

The present invention uses an unmanned aerial vehicle (drone) without professional technical personnel (workers), so it has high accessibility to power facilities, so it is possible to accurately monitor the location of the fault, to promote the safety of professional technical personnel, and at a lower cost than the prior art. It has the effect of monitoring power facilities.

1 is a conceptual diagram of an unmanned diagnostic device for monitoring power facilities according to the present invention.
Figure 2 is a configuration diagram of an autonomous flight path generation unit according to the present invention.
3 is a configuration diagram of an unmanned monitoring diagnostic unit according to the present invention.
Figure 4 is a conceptual diagram of an unmanned monitoring control unit according to the present invention.
5 is a conceptual diagram and an embodiment of the operation of the loading equipment control unit according to the present invention.
6 is an image embodiment in which the autonomous flight path generation unit according to the present invention 3D models the real location information of power facilities.
7 is an image embodiment in which the autonomous flight path generating unit generates an autonomous flight path including a safe separation distance according to the present invention.
8 is an embodiment of corona and thermal imaging diagnosis images according to the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

As shown in FIG. 1 , the unmanned diagnostic device for power facility monitoring (hereinafter referred to as 'unmanned diagnostic device') of the present invention detects a power facility failure using an unmanned aerial vehicle 10 capable of autonomous flight. The power facility includes a steel tower (1) and a transmission line (3). The unmanned aerial vehicle 10 may correspond to a drone, a flying robot, or an unmanned aerial vehicle.

The unmanned diagnosis device includes an autonomous flight path generator 100, an unmanned monitoring diagnosis unit 200, and an unmanned monitoring control unit 300.

The autonomous flight path generation unit 100 generates an autonomous flight path of the UAV 10 for monitoring power facilities. The autonomous flight path generating unit 100 generates flight path points of the unmanned aerial vehicle 10 so that the unmanned monitoring diagnosis unit 200 can monitor power facilities while maintaining a safe separation distance (m) from the power facilities.

As shown in FIG. 2, the autonomous flight path generator 100 includes a modeling unit 110 for 3D modeling of real location information of power facilities and a setting unit 120 for setting monitoring and diagnosis location information of power facilities in 3D modeling. ), and an application unit 130 that sets an autonomous flight path by adding a separation distance to the 3D modeling in which monitoring and diagnosis location information of power facilities is set.

For example, the autonomous flight path generation unit 100 models terrain and power transmission line information as 3D spatial information (see FIG. 6) and generates an autonomous flight path to include a safe separation distance (m) (FIG. 1 and see Figure 7).

Specifically, in the case where the power facility target is an extra-high voltage transmission tower, the modeling unit establishes an autonomous flight plan before on-site power facility monitoring and diagnosis by an unmanned diagnostic device and automatically generates and supports flight route points for an UAV capable of GPS-based automatic navigation. (110) models the information of the area where the power facility monitoring flight service is to be performed as 3D spatial information. Here, the setting unit 120 applies location-based 3D modeling of real location information of facilities that require actual monitoring and diagnosis, such as steel towers and wires, to three-dimensionally determine the connection information of transmission towers and transmission lines, and geographical and spatial positional relationships to pre-set monitoring and diagnosis location information. Next, the application unit 130 creates an autonomous flight path in advance by automatically adding a safe separation distance (m) for safe measurement of the UAV and power facilities (eg, the left and right sides of the ultra-high voltage transmission tower).

3D spatial information can determine spatial positioning as well as distance on a plane by overlaying satellite photos on a 3D digital map of the area where the transmission line monitoring flight service is to be performed. In this 3D spatial information, a 3D model of a transmission structure based on a blueprint of an actual transmission tower is applied, and flight path points can be automatically generated by three-dimensionally determining connection information and geographic and spatial positional relationships between transmission towers and transmission lines.

In other words, modeling with 3D spatial information based on the actual location information of power facilities that require actual monitoring and diagnosis, such as steel towers and wires, connection information of steel towers and transmission lines in 3D modeling, and three-dimensional judgment of geographic and spatial positional relationships to enable drones and electric power The safety separation distance (m) of the facility can be pre-selected.

The autonomous flight path generated by the autonomous flight path generator 100 is stored in the unmanned monitoring control unit 300 . The unmanned monitoring control unit 300 may wirelessly provide autonomous flight path information to the unmanned sensing diagnosis unit 200 .

The unmanned monitoring diagnosis unit 200 is provided in the UAV. The unmanned monitoring and diagnosis unit 200 controls the autonomous flight of the UAV to maintain a safe separation distance (m) from the power facility, monitors and diagnoses the power facility, and detects a failure of the power facility.

The unmanned monitoring diagnosis unit 200 uses an inertial navigation device based on autonomous flight path information and coordinate information to allow the UAV to fly to a field for fault detection. In addition, the unmanned monitoring diagnosis unit 200 acquires monitoring information data of power facilities by allowing the unmanned aerial vehicle to maintain a safe separation distance (m) from the power facilities. Monitoring information data includes thermal image information, corona information, and image information of power facilities.

As shown in FIG. 3, the unmanned monitoring diagnosis unit 200 controls the autonomous flight of the UAV based on the sensor 210 for detecting the separation distance from the power facility, the signal detected by the sensor 210, and the autonomous flight path information. It includes an UAV control unit 220 for controlling.

The unmanned monitoring diagnosis unit 200 wirelessly receives autonomous flight path information and coordinate information of the power facility monitoring object from the unmanned monitoring control unit 300, and based on the received coordinate information location, an inertial navigation device including GPS and IMU 270 Using , the UAV performs autonomous flight by itself and arrives at the site for fault detection. Here, the field corresponds to the area where power facility (transmission line) monitoring flight service is to be performed.

When the unmanned monitoring diagnosis unit 200 arrives at the site, the monitoring information acquisition device 230 is used to hover and stand by so that power facility monitoring such as detailed image acquisition is possible.

The detector 210 includes an ultrasonic sensor 211, a distance measurement unit 212, and an alarm unit 213. The ultrasonic sensor 211 emits an ultrasonic signal, and the distance measuring unit 212 detects the ultrasonic signal emitted and reflected by the ultrasonic sensor 211 to measure the distance to the obstacle and travel in a preset direction. It detects whether the safety separation distance (m) is maintained. The warning unit 213 generates a warning sound indicating that there is an obstacle based on the information measured by the distance measuring unit 212 .

The warning unit 213 serves to inform the user that there is an obstacle in the direction of the UAV by generating a warning sound through a light such as an LED mounted on the UAV 10 or a speaker. At this time, the alarm unit 213 may include a warning light and an alarm sound generating device.

In addition, the alarm unit 213 transmits information informing that there is an obstacle to the unmanned monitoring control unit 300 via the UAV control unit 220 and the wireless transmission/reception unit 290, so that a follow-up response can be taken. 320) also displays an alarm, and enables subsequent control of the UAV through the action unit 340.

In addition, the unmanned monitoring diagnosis unit 200 includes a monitoring information acquisition device 230 , an acquisition signal processing unit 240 and a failure detection unit 250 .

The monitoring information acquisition device 230 acquires thermal image information and corona information of power facilities. The surveillance information acquisition device 230 is a device mounted on an unmanned aerial vehicle, and includes a CCD sensor 231 for capturing images, a thermal image sensor 232 for detecting thermal images, and a UV sensor 233 for detecting corona partial discharge. do.

The CCD sensor 231 is a high-resolution CCD (CMOS) sensor and is intended to replace visual monitoring of power facilities. The thermal image sensor 232 measures heat generated when deterioration progresses in power facilities. The UV sensor 233 receives a corona discharge signal emitted by a partial discharge generated when deterioration progresses in a power facility. The CCD sensor 231, the thermal image sensor 232, and the UV (ultraviolet ray, Ultra Violet) sensor 233 are mounted on the UAV and can monitor and diagnose the failure or defect of the power facility with objective values.

The acquisition signal processing unit 240 detects an overheating point and a corona partial discharge signal of the power facility based on the signal acquired by the monitoring information acquisition device 230 and determines the discharge distribution density.

The acquisition signal processing unit 240 detects a corona partial discharge signal generated from an overheating point of the power facility and an abnormality of the power facility based on the signal detected by the thermal image sensor 232 and the signal detected by the UV sensor 233. In addition, the acquisition signal processing unit 240 converts the corona partial discharge signal distribution into a corona discharge image to determine the discharge distribution density. The discharge distribution density is the number of partial discharges extracted from the corona discharge image.

When corona occurs in an abnormal location in a power facility, wavelengths in the ultraviolet region are generated among various phenomena.

At this time, the UV sensor 232 detects the wavelength of ultraviolet light generated from the corona discharge and converts it into a visible light image to be used for power equipment diagnosis. Detects and amplifies UV microsignals generated artificially from abnormal points in power facilities, filters them by UV band, and amplifies UV rays tens of millions of times through signal processing through the internal photomultiplier tube (MCP, Multi Channel Plate). It can be converted into an image of visible light. At this time, the converted discharge signal distribution can be converted into a corona discharge image to determine the discharge distribution density. The acquisition signal processing unit 240 may compare the discharge distribution density with a reference value to see if a reference value or more is expressed.

The thermal image overheating point information detected by the thermal image sensor 232 includes temperature information of the overheated point and temperature information around the overheated point, and may also include relative temperature information of the overheated point. The thermal image sensor 232 may provide the acquisition signal processing unit 240 with temperature information of the overheated point, temperature information around the overheated point, and relative temperature information of the overheated point. The acquisition signal processing unit 240 transmits thermal image overheating location information, corona information, and discharge distribution density information to the failure detection unit 250 .

The failure detection unit 250 compares the information received from the acquisition signal processing unit 240 with reference data to detect a power facility failure in advance.

Specifically, the failure detection unit 250 detects a failure by comparing the corona information received from the acquisition signal processing unit 240 with the failure corona discharge waveform information secured and set in advance through a test. Thermal image overheating location information is also compared with the overheating prohibition temperature (relative temperature) information obtained through testing in advance to detect failures.

When a failure is detected by the failure detection unit 250, a high-resolution image signal is obtained through the CCD sensor 231, and accurate location information is received from the inertial navigation device including the GPS and IMU 270, and based on the GPS location information It is stored in the acquisition signal storage unit 280 and transmitted and received to the unmanned monitoring control unit 300.

In addition, the unmanned monitoring diagnosis unit 200 includes a mounted equipment control unit 260.

The mounted equipment control unit 260 receives the coordinates of the power facility monitoring object from the unmanned monitoring control unit 300 and fixes the monitoring information acquisition device 230 to the UAV so that the monitoring information acquisition device 230 aims and tracks the power facility monitoring object. and controls the 3-axis rotation of the monitoring information acquisition device 230.

The mounted equipment control unit 260 receives the coordinates of the power facility monitoring object from the unmanned monitoring control unit 300, and controls the monitoring information acquisition device 230 in three axis rotation (roll, pitch, yaw, roll, pitch, yaw) It is possible, and it should be composed of a GIMBAL device with a vibration absorption function. Accordingly, based on the received location information of the object to be monitored, the gimbal device is driven to accurately target and track, and the CCD (CMOS) sensor, thermal image sensor, and UV (ultraviolet ray, Ultra Violet) sensor It operates to acquire corona and image information.

At this time, the UAV hovers and waits so that high-resolution information can be checked in consideration of the GPS error. That is, the detailed high-resolution image information is transmitted to the unmanned monitoring controller 300 and the UAV waits while hovering so that it can be confirmed through the failure location confirmation unit 320, so that it can be corrected by manual control. .

5 illustrates the operation concept and embodiment of the UAV mounted equipment control unit.

Referring to FIG. 5, (a), a CCD (CMOS) sensor, a thermal image sensor, and a UV sensor shown in the form of a black camera can control 3-axis rotation (roll, pitch, yaw, roll, pitch, yaw), Shows an embodiment including a stabilizing function, (b) shows an embodiment with a circular enclosure in (a), and (c) and (d) show a gimbal (GIMBAL) driven by an exposed 3-axis motor. Examples are shown.

In the case of corona diagnosis, in order to increase measurement accuracy, UV ink is sprayed and marked on the object to be monitored in advance or a UV label is attached so that the monitoring information acquisition device 230 can accurately aim and track the object to be monitored. Since UV ink is a functional ink and can be detected through the UV sensor 233, a monitoring target can be additionally recognized using the UV sensor 233, enabling GPS error correction and increasing monitoring directivity.

In addition, basically, the onboard equipment control unit 260 accurately aims at the target to be monitored using the monitoring and diagnosis location information acquired by the setting unit 120 in advance when creating an autonomous flight path, thereby increasing directivity and improving monitoring and diagnosis accuracy. In the case of thermal imaging diagnosis, the setting unit 120 accurately aims the monitoring and diagnosis location information acquired in advance at the object to be monitored, thereby increasing directivity and improving monitoring and diagnosis accuracy.

In addition, the unmanned monitoring diagnosis unit 200 includes a GPS and IMU 270, an acquisition signal storage unit 280 and a wireless transmission/reception unit 290.

The GPS and IMU 270 is an inertial navigation device including GPS and IMU. The GPS and IMU 270 may determine the real position coordinate information of the UAV based on the time difference between the time sent by the GPS and the time received by the receiver. The UAV control unit 220 receives the autonomous flight path information and the coordinates of the power facility monitoring object from the unmanned monitoring control unit 300, and matches the actual location coordinate information of the UAV with the coordinates of the power facility monitoring object within an error range. It can control autonomous flight.

The UAV control unit 220 maintains a separation distance between the power facility and the UAV in real time by comparing the real-time self-location information of the UAV with the autonomous flight path information and coordinate information received from the unmanned monitoring control unit 300, and the transmission line (distribution line) It is possible to control the flight of the UAV so that it does not collide with) and transmission pylons (electric poles).

The ultrasonic sensor 211 and the distance measuring unit 212 are mounted on the UAV, and an ultrasonic signal is emitted through the ultrasonic sensor 211 to determine if there is an obstacle in the flight direction of the UAV, and the reflected ultrasonic wave is sent to the distance measuring unit 212 can detect and measure the distance to an obstacle. Obstacles may include steel towers, transmission lines, and various metal fittings installed on the steel towers and transmission lines.

If a safe separation distance (eg, 5 m) for the direction of flight of the UAV is set in advance, the UAV control unit 220 detects obstacles in the direction of the UAV flight and waits while the UAV hovers. , Through the warning unit 213, it is possible to inform the user that there is an obstacle in the UAV's flight direction through a warning sound.

Acquisition signal storage unit 280 stores the failure location information of the power facility previously detected by the failure detection unit 250 and image information of the failure location.

The information stored in the acquisition signal storage unit 280 prepares for a case where it is difficult to transmit and receive high-capacity original data due to wireless communication interruption and data wireless transmission and reception bandwidth limitations. The acquisition signal storage unit 280 may be a mass storage device such as an SSD memory. The information stored in the acquisition signal storage unit 280 can be processed and used by the user later. The acquisition signal storage unit 280 stores state information of the unmanned diagnosis device and can serve as a black box in case of an accident.

The wireless transmission/reception unit 290 transmits and receives data signals to and from the unmanned monitoring control unit 300 wirelessly. The wireless transceiver 290 transmits and receives data signals while communicating with the wireless transceiver 310 of the unmanned monitoring control unit 300.

As shown in FIG. 4 , the unmanned monitoring control unit 300 confirms and detects a power facility failure using data information received from the unmanned monitoring diagnosis unit 200 .

The unmanned monitoring control unit 300 includes a wireless transmission/reception unit 310, a failure location confirmation unit 320, an unmanned aerial vehicle and mounted equipment control unit 330, an action unit 340, and a DB storage unit 350.

The unmanned monitoring control unit 300 receives the data signal of the unmanned monitoring diagnosis unit 200 through the wireless transmission/reception unit 310 to detect a power facility failure. The wireless transmission/reception unit 310 transmits and receives data signals to and from the unmanned monitoring diagnosis unit 200 .

The failure location confirmation unit 320 compares the data signal provided from the wireless transmission/reception unit 290 of the unmanned monitoring diagnosis unit 200 with the set data to detect a power facility failure. Alternatively, the failure location confirmation unit 320 The fault detection unit 250 re-detects the result of pre-detection of the power facility failure to confirm and detect the power facility failure.

The failure location confirmation unit 320 compares the corona information of the data provided through the wireless transceivers 290 and 310 with the failure corona waveform information obtained through a preliminary test, and also obtains information on the overheated location in the thermal image through a preliminary test. The pre-detection result of the failure detection unit 250 is checked by comparing with the set overheat prohibition temperature (relative temperature) information. The result confirmed by the failure location confirmation unit 320 is transmitted to the action unit 340 via the UAV and mounted equipment control unit 330.

The action unit 340 receives the result of confirmation and detection by the failure location confirmation unit 320, displays it to the outside, and transmits it to the user. The action unit 340 may be composed of a display device or an alarm generating device that informs the user of observation information, such as a computer, and may include automatic and manual input/output interfaces such as an unmanned aerial vehicle ground control device and a mounted equipment ground control device. there is.

The action unit 340 transmits the failure detection result to the user along with the acquired location information, high-resolution image information, and a warning sound through a speaker so that the user (eg, a remote monitoring diagnostician of the action unit) can check.

In the fully autonomous flight of the UAV, the process of transmitting the failure detection result to the user by the action unit 340 is omitted. In addition, the failure detection result detected by the failure location confirmation unit 320 is stored in the DB storage unit 350 via the UAV and onboard equipment control unit 330 so that subsequent countermeasures can be taken.

The DB storage unit 350 stores data as a result of confirmation and detection by the failure location confirmation unit 320 . The DB storage unit 350 is an autonomous flight path including data obtained by modeling the actual location information of power facilities generated by the autonomous flight path generation unit 100 as 3D spatial information, location information data to be monitored and diagnosed, and the safe separation distance of the UAV. contains information The DB storage unit 350 enables the failure detection result to be displayed at a location modeled with 3D spatial information.

On the other hand, the diagnosis method using the unmanned diagnostic device for monitoring power facilities includes the steps of the autonomous flight path generation unit 100 generating an autonomous flight path for the UAV to monitor power facilities, and the unmanned monitoring diagnosis unit 200 generating the autonomous flight path Using the inertial navigation device based on information and coordinate information, the UAV flies to the site for fault detection and acquires monitoring information data of power facilities while maintaining a safe separation distance from power facilities and unmanned monitoring control unit 300 A step of detecting a power facility failure using data received from the unmanned monitoring diagnosis unit 200.

The step of generating the autonomous flight path of the UAV includes the step of 3D modeling the actual location information of power facilities, the step of setting monitoring and diagnosis location information of power facilities in 3D modeling, and the 3D modeling in which monitoring and diagnosis location information of power facilities is set. and setting an autonomous flight path by adding a separation distance to .

6 shows an image embodiment in which the autonomous flight path generator 3D models the actual location information of power facilities, and FIG. 7 shows an image embodiment in which the autonomous flight path generator generates an autonomous flight path including a safe separation distance.

As shown in FIG. 6, the autonomous flight path generation unit 100 of the unmanned diagnostic device for power facility monitoring establishes a patrol plan before the field patrol mission flight of the UAV when the target of the power facility to be monitored is an extra-high voltage transmission tower, In order to automatically generate and support flight path points for GPS-based automatic navigation UAVs, the topographical information of the area where the transmission line monitoring flight service is to be performed is modeled as 3D spatial information.

Here, as shown in FIG. 7, location-based 3D modeling is applied to actual location information of facilities that require actual monitoring and diagnosis, such as steel towers and wires, to determine the connection information and geographical and spatial positional relationships of transmission towers and transmission lines in three dimensions It is possible to select the safe separation distance between the UAV and power facilities in advance.

Thereafter, the UAV control unit 220 controls the UAV to autonomously fly by itself using an inertial navigation device including GPS and IMU based on the coordinate information and location information of the power facility monitoring object received from the unmanned monitoring control unit 300, and the sensor ( 210) detects the separation distance between the power facility and the UAV so that the UAV maintains a safe separation distance from the power facility.

Thereafter, the acquisition signal processing unit 240 acquires thermal image information and corona information of the power facility through the thermal image sensor 232 and the UV sensor 233, and based on the acquired information, overheating and corona partial discharge of the power facility Detect the signal and figure out the distribution density of the discharge. The discharge distribution density is identified by converting the corona partial discharge signal distribution into a corona discharge image.

The information identified by the acquisition signal processing unit 240 is transmitted to the failure detection unit 250 . The failure detection unit 250 detects a power facility failure in advance based on whether the discharge distribution density is expressed above a reference value.

Data information of the unmanned monitoring diagnosis unit 200 including corona information, overheating location information, and discharge distribution density information is transmitted and received to the unmanned monitoring control unit 300.

The failure location confirmation unit 320 of the unmanned monitoring control unit 300 compares the corona information with preset failure corona waveform information and compares the overheating point information with preset overheating prohibition temperature information to obtain a pre-detection result of a power facility failure. It is checked, and the result of the check is sent to the action department.

8 shows an exemplary corona and thermal diagnostic image.

In the unmanned diagnosis method for power facility monitoring of the present invention, a UV sensor detects the wavelength of ultraviolet light generated from corona discharge and converts it into a visible ray image to be used for diagnosis.

8(a) shows the distribution of the corona discharge visualization image of the power transmission line. From the corona discharge visualization image distribution, the discharge distribution and density can be grasped, and the presence or absence of abnormalities can be diagnosed. In addition, additional monitoring and diagnostic information can be obtained by tracking densely populated areas in the discharge visualization image distribution with a CCD sensor and a thermal image sensor.

8(b) shows the corona discharge visualization image distribution of the metal part connected to the power transmission line.

It is possible to diagnose the presence or absence of abnormalities by measuring the number of discharges per minute (Count rate) visualized in the corona discharge visualization image of the metal part connected to the transmission line and using a reference value. For example, in the case of (b) of FIG. 8, it is detected that discharges are currently occurring 2089 times per minute and displayed on the image. If the reference value is less than 5000 times per minute, it can be diagnosed as normal.

FIG. 8(c) shows the corona discharge visualization image distribution of the metal part connected to the power transmission line as in FIG. 8(b).

In the discharge visualization image of FIG. 8 (c), the presence or absence of abnormalities can be diagnosed by measuring the distribution and density of discharges or the number of visualized discharges per minute, and additional monitoring and diagnosis can be made by tracking the location where discharges are concentrated with a CCD sensor and a thermal image sensor. When the information is obtained, a comprehensive surveillance diagnosis image as shown in FIG. 8(d) can be obtained.

That is, if the failure corona discharge signal is acquired in advance and the data (DB) is converted into data (DB) so that the distribution of the discharge visualization image or the characteristics of the number of discharges per minute can be compared, it is possible to detect and diagnose the failure of power equipment through corona discharge.

As described above, in this embodiment, the UV sensor 233 acquires the faulty corona discharge signal and converts the faulty corona discharge signal distribution into a corona discharge image. The acquisition signal processing unit grasps the discharge distribution density in the corona discharge image. The failure detection unit identifies the number of partial discharges in the discharge distribution density and compares them with a reference value to determine whether there is a failure (abnormality).

When the failure is determined as a result of the determination by the failure detection unit 250, a location where discharge is concentrated is tracked and a high-resolution image signal is obtained using a CCD sensor. The high-resolution image signal and accurate location information of the place where discharge is concentrated are received from the inertial navigation device including GPS and IMU, stored in the acquisition signal storage unit 280 based on the GPS location information, and transmitted to the unmanned monitoring control unit 300.

In addition, the thermal image overheating point information detected by the thermal image sensor 232 is also stored in the acquisition signal storage unit 280 and transmitted to the unmanned monitoring controller 300 .

The unmanned monitoring control unit 300 receives corona information, thermal image overheating location information, discharge distribution density information, and high-resolution image signal information of a place where discharges are concentrated, and the failure detection unit 250 detects Check if the failure information is correct by re-detection.

In another embodiment, in the unmanned diagnostic device for monitoring power facilities, the monitoring information acquisition device 230 may be detachably configured to the UAV in consideration of the payload of the UAV. Only high-resolution image acquisition and corona diagnosis (e.g., UV sensor) modules are installed in the UAV, or only high-resolution image acquisition and thermal imaging diagnosis modules are installed, enabling individual utilization as a system dedicated to corona discharge diagnosis and thermal imaging diagnosis. can be configured.

The best embodiments of the present invention have been disclosed in the drawings and specifications. Here, specific terms have been used, but they are only used for the purpose of describing the present invention, and are not used to limit the scope of the present invention described in the claims. Therefore, those skilled in the art will understand that various modifications and equivalent other embodiments are possible therefrom. Therefore, the true technical scope of the present invention should be determined by the technical spirit of the appended claims.

1: steel tower 3: transmission line
10: UAV 100: autonomous flight path generation unit
200: unmanned monitoring diagnosis unit 210: detector
211: ultrasonic sensor 212: distance measuring unit
213: alarm unit 220: drone controller
230: monitoring information acquisition device 231: CCD sensor
232: thermal image sensor 233: UV sensor
240: acquisition signal processing unit 250: unattended control unit
260: load equipment control unit 270: GPS and IMU
280: acquisition signal storage unit 290: wireless transmission and reception unit
300: unmanned monitoring control unit 310: wireless transmission and reception unit
320: failure location confirmation unit 330: UAV and mounted equipment control unit
340: action unit 350: DB storage unit

Claims (16)

unmanned aerial vehicles capable of autonomous flight;
an autonomous flight path generation unit for generating an autonomous flight path of the UAV for monitoring power facilities;
It is provided in the UAV and uses an inertial navigation device based on the autonomous flight path information and the coordinate information of the UAV to allow the UAV to fly to the site for fault detection and to maintain a safe separation distance from the power facility. While, unmanned monitoring diagnosis unit for acquiring the monitoring information data of the power facility; and
An unmanned monitoring control unit for detecting a power facility failure using the data received from the unmanned monitoring diagnosis unit;
Including,
In order to convert the corona partial discharge signal distribution into a corona discharge image and compare with the reference value whether the discharge distribution density (the number of partial discharges extracted from the corona discharge image) is greater than or equal to the reference value,
The unmanned monitoring diagnosis unit
a monitoring information acquisition device for acquiring thermal image information and corona information of power facilities;
an acquisition signal processing unit that detects an overheating point and a corona partial discharge signal of a power facility on the basis of the signal acquired by the monitoring information acquisition device and determines a discharge distribution density;
a failure detection unit for preliminarily detecting a power facility failure by comparing the information received from the acquisition signal processing unit with a reference value;
an acquisition signal storage unit for storing image information of the location of a power facility failure pre-detected by the failure detection unit together with location information;
a wireless transceiver for transmitting and receiving data signals to and from the unmanned monitoring control unit wirelessly;
The data signal provided from the wireless transceiver unit is compared with the set data to confirm and detect the power facility pre-failure detection result, and the corona information of the data provided through the wireless transceiver unit is compared with the failure corona waveform information obtained through the preliminary test. a failure location check unit for confirming a result previously detected by the failure detection unit;
an action unit for receiving and displaying the result of the confirmation and detection of the failure location confirmation unit and informing the user; and
a DB storage unit for storing data as a result of the confirmation and detection of the failure location confirmation unit;
An unmanned diagnostic device for power facility monitoring that includes a. The method of claim 1,
The autonomous flight path generation unit
a modeling unit for 3D modeling real location information of power facilities;
a setting unit for setting monitoring and diagnosing location information of power facilities in the 3D modeling; and
an application unit that sets an autonomous flight path by adding a separation distance to the 3D modeling in which monitoring and diagnosis location information of the power facility is set;
An unmanned diagnostic device for monitoring power facilities, comprising: The method of claim 1,
The unmanned monitoring diagnosis unit
A sensor that detects the separation distance from the power facility; and
An UAV controller controlling autonomous flight of the UAV based on the signal detected by the sensor and the autonomous flight path information;
An unmanned diagnostic device for monitoring power facilities, comprising: The method of claim 3,
the detector is
an ultrasonic sensor that emits ultrasonic signals;
a distance measuring unit measuring a distance to an obstacle by detecting an ultrasonic signal emitted and reflected by the ultrasonic sensor; and
an alarm unit generating a warning sound indicating that there is an obstacle based on the information measured by the distance measuring unit;
An unmanned diagnostic device for monitoring power facilities, comprising: delete The method of claim 1,
The monitoring information acquisition device
CCD sensor for taking images;
a thermal image sensor that detects a thermal image; and
a UV sensor that detects corona partial discharge;
An unmanned diagnostic device for monitoring power facilities, comprising: The method of claim 6,
Including a mounted equipment control unit for receiving the coordinates of the power facility monitoring object from the unmanned monitoring control unit, fixing the UAV and controlling the 3-axis rotation of the monitoring information acquisition device so that the monitoring information acquisition device aims and tracks the power facility monitoring object An unmanned diagnostic device for power facility monitoring, characterized in that. delete delete delete delete delete delete delete delete delete

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