KR102223370B1 - Apparatus for prevention of disaster of electric power equipment - Google Patents

Abstract

According to an embodiment of the present invention, provided is a power facility disaster prevention device, which comprises: a thermal imaging camera which photographs a thermal image of the interior of an enclosure equipped with power facilities; a driving unit provided in the enclosure to move the thermal imaging camera; a control unit controlling the driving unit and the thermal imaging camera; and a communication unit transmitting information on parameters including the photographed thermal image to the outside under the control of the control unit.

Description

Disaster prevention equipment for electric power facilities{APPARATUS FOR PREVENTION OF DISASTER OF ELECTRIC POWER EQUIPMENT}

The present invention relates to an electric power equipment disaster prevention system, and more particularly, to an electric power equipment disaster prevention apparatus using thermal image analysis.

Power facilities such as distribution and distribution facilities are thoroughly controlled by non-resident service personnel by installing safety fences in specific underground spaces or rooftops or outskirts where access other than the operator is not usually accessible.If the operator is not a resident employee, it is managed by non-resident service personnel. Being

The operation of the power distribution facility that controls high voltage and high power is difficult and dangerous to operate except for those who have been trained separately, so if the operator is absent during periods other than the regular inspection of the facility, it is necessary to detect an abnormal situation in the electrical system and access personnel other than the operator in the event of an emergency such as a fire. Controlled and difficult to take quick action

In the structure of power distribution facilities, various instruments, control switches, protection relays, transformers, etc. necessary for power distribution are safely installed in a metal box, and cubicle type (box type) power distribution facility panels are widely used. In addition, they are all put in a grounded metal box to protect users from electric shock disasters caused by high voltage devices and fires caused by device breakdowns.

The power distribution facility is a means of transmitting electricity received from KEPCO to the components. It uses a copper busbar and wire suitable for the power reception capacity, and is connected by bolting the components to the components.

However, since the product is standardized according to a certain design rule, the flexibility of the facility is low, and it is difficult to check the components or to determine the internal state. There are difficulties without doing it.

In addition, the heating status of components (breakers, ACB, VCB, fuses, transformers, CT, PT, relays, busbars, wires, etc.) is an important indicator for determining the point of inspection and replacement of parts and the degree of fire potential, but in real time. It is difficult to secure a high level of facility stability because monitoring is not performed.

Therefore, it is difficult for the operator to access it, and even if the inspection is performed at the site where the distribution and distribution facilities are installed, the subjective method of checking with the naked eye is not practical.

In addition, human life accidents due to electric shock accidents occur frequently during the process of inspecting the inside of the metal box, and it can be said that the loss of life and economic loss such as fire due to damage to the protection circuit is large.

Accordingly, the importance of remote monitoring or automatic failure recognition of power distribution facilities has increased.

Patent Publication 10-2002-0087924 (Publication date: November 23, 2002)

A power facility disaster prevention apparatus according to an embodiment of the present invention is for predicting a parameter change of a power facility and predicting an abnormality in the power facility.

The subject of the present application is not limited to the subject mentioned above, and another subject that is not mentioned will be clearly understood by those skilled in the art from the following description.

According to an aspect of the present invention, there is provided a thermal imaging camera for taking a thermal image of the interior of the enclosure provided with power equipment; A driving unit provided in the enclosure to move the thermal imager; A control unit for controlling the driving unit and the thermal imaging camera; And a communication unit for transmitting information on a parameter including the photographed thermal image to the outside under the control of the controller.

The electric power equipment disaster prevention apparatus according to an aspect of the present invention may further include a predictive computing apparatus for predicting the state of the electric power equipment by analyzing information on the parameter transmitted from the communication unit.

Further comprising the microphone sensor for sensing the noise of the power equipment, the information on the parameter includes the sensed noise level, and the control unit provides information on the parameter including the thermal image and the noise level By transmitting to the predictive computing device through the communication unit, the predictive computing device may analyze information on the parameter to predict the state of the power facility.

The predictive computing device derives the reference pattern of each parameter up to the first point of time through machine learning, synchronizes the reference pattern of each of the parameters, and analyzes the degree of correlation between the reference patterns of each parameter to derive a reference correlation degree. In addition, an abnormal prediction for the state of the power facility may be derived according to a result of comparing the correlation degree of each pattern of the parameters at the second time point after the first time point and the reference correlation degree.

The power facility includes one or more power components, and the control unit includes a memory unit for storing location information and photographing time of the at least one power component, and controls the driving unit according to the location information so that the thermal imager It is possible to control the thermal imaging camera to be disposed at a location corresponding to the location information, and to take a thermal image of the one or more power components at the shooting time at the disposed location.

The driving unit further includes a microphone sensor installed together with the thermal imaging camera, and the microphone sensor may sense noise generated from the at least one power component at the shooting time at the arranged position under the control of the controller. .

The power facility disaster prevention apparatus according to an embodiment of the present invention may predict a parameter change of a power facility by deriving a reference pattern of a parameter through machine learning, and perform an abnormality prediction of the power facility.

The effects of the present application are not limited to the effects mentioned above, and other effects that are not mentioned will be clearly understood by those skilled in the art from the following description.

1 shows a power equipment disaster prevention apparatus according to an embodiment of the present invention.
2 shows an example of a driving unit.
3 shows an example of power equipment.
4 shows an example of a thermal image of a power facility.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. However, the accompanying drawings are only described in order to more easily disclose the contents of the present invention, and the scope of the present invention is not limited to the scope of the accompanying drawings, and those of ordinary skill in the art can easily You will know.

In addition, terms used in the present application are only used to describe specific embodiments, and are not intended to limit the present invention. Singular expressions include plural expressions unless the context clearly indicates otherwise.

In the present application, terms such as "comprise" or "have" are intended to designate the presence of features, numbers, steps, actions, components, parts, or combinations thereof described in the specification, but one or more other features. It is to be understood that the presence or addition of elements or numbers, steps, actions, components, parts, or combinations thereof does not preclude in advance.

1 shows a power equipment disaster prevention apparatus according to an embodiment of the present invention. As shown in FIG. 1, the power equipment disaster prevention apparatus according to an embodiment of the present invention includes a thermal imaging camera 110, a driving unit 130, a control unit 150, and a communication unit 170.

The thermal imaging camera 110 takes a thermal image of the interior of the enclosure 10 equipped with the power equipment 200. The power facility 200 may be a power distribution facility, but is not limited thereto. The power facility 200 may include one or more power components. Power components may be ACB (Air Circuit Breaker), VCB (Vaccum Circuit Breaker), MOF (Metering Out Fit: instrument transformer), TR (transformer), etc., but is not limited thereto.

For example, Figure 3 shows an example of the power equipment 200, LBS (Load Breaker Switch), UVR (Under Voltage Relay), VCB, COS (Cut Out Switch), ACB, etc. may be installed, but the present invention It is not limited to the circuit and components of FIG. 3.

The driving unit 130 is provided in the enclosure 10 to move the thermal imaging camera 110. As shown in FIG. 1, the driving unit 130 may be provided on the inner side of the cover of the enclosure 10 provided with the power equipment 200. The stage 131 on which the thermal imaging camera 110 is installed can be moved vertically and horizontally. Accordingly, the thermal imaging camera 110 may take a picture of the power equipment inside the enclosure 10 to be monitored within the moving range with the thermal imaging camera.

2 shows an example of the driving unit 130. The driving unit 130 includes a stage 131, a first motor 132, a second motor 133, a first rail moving body 134, a second rail moving body 135, the first to fourth guide rails 136, 137, 138, 139), first belt 140, second belt 141, first movable pulley 142, second movable pulley 143, first fixed pulley 144, second It may include a fixed pulley (145).

In this case, the first motor 132 and the second motor 133 may be stepping motors, but are not limited to such types of motors. The first belt 140 and the second belt 141 may be timing belts, but are not limited to such belt types. In addition, the first and second moving body pulleys 142 and 143 and the first and second fixed pulleys 144 and 145 may be timing pulleys, but are not limited to such pulley types.

The first rail moving body 134 may move along the first guide rail 136, and the second rail moving body 135 may move along the second guide rail 137. In this case, the first guide rail 136 and the second guide rail 137 may be spaced apart from each other in parallel and extended in the first direction to be installed.

A first moving body pulley 142 and a second moving body pulley 143 may be provided on the first rail moving body 134 and the second rail moving body 135, respectively. The third guide rail 138 and the fourth guide rail 139 may be connected to the first rail moving body 134 and the second rail moving body 135.

In this case, the third guide rail 138 and the fourth guide rail 139 may be spaced apart from each other in parallel to extend in a second direction to be installed, and the second direction may cross perpendicularly to the first direction.

The first motor 132 may be disposed adjacent to the first guide rail 136, and the first fixed pulley 144 is disposed adjacent to the first guide rail 136 opposite the first motor 132 Can be.

The second motor 133 may be disposed adjacent to the second guide rail 137, and the second fixed pulley 145 is disposed adjacent to the second guide rail 137 opposite the second motor 133 Can be.

Accordingly, the first fixing pulley 144 and the second fixing pulley 145 may face each other along the second direction.

The first belt 140 is connected to both sides of the stage 131, a first moving body pulley 142, a first motor 132, a first fixed pulley 144, a second fixed pulley 145 and a second It may be caught on the moving body pulley 143. In addition, the second belt 141 is connected to both sides of the stage 131, the second moving body pulley 143, the second motor 133, the second fixed pulley 145, the first fixed pulley 144, 1 It may be caught on the moving body pulley 142.

The first belt 140 and the second belt 141 include a first moving body pulley 142, a first motor 132, a first fixed pulley 144, a second fixed pulley 145, and a second moving body pulley ( 143), but they can be caught apart so that they do not overlap each other.

The stage 131 can be moved along the third guide rail 138 and the fourth guide rail 139, and the third guide rail 138 and the fourth guide rail 139 are provided with the first rail moving body 134 and It is connected to the 2nd rail moving body 135. In addition, the controller 150 may control the rotation directions of the first motor 132 and the second motor 133.

Accordingly, the stage 131 may move to a position on a plane formed with the first direction and the second direction as an axis.

Meanwhile, the control unit 150 controls the driving unit 130 and the thermal imaging camera 110. For example, the controller 150 may control the rotation directions of the first motor 132 and the second motor 133. In addition, the control unit 150 may control the rotation speed of the first motor 132 and the second motor 133.

The controller 150 may control a conversion and transmission process of a thermal image captured by the thermal imaging camera 110 and a noise level, temperature, and humidity to be described later into a form suitable for transmission through the communication unit 170. .

The communication unit 170 may transmit information on a parameter including a thermal image captured under the control of the controller 150 to the outside. The communication unit 170 operates according to a communication protocol and may include hardware and software for this.

In the present invention, not only a parameter for a thermal image, but also a parameter for a noise level to be described later, a parameter for a temperature inside the enclosure 10, and a parameter for a humidity inside the enclosure 10 may be used. The parameter for the level of noise may include information on at least one of a noise level and a noise frequency.

Meanwhile, the power facility disaster prevention apparatus according to an embodiment of the present invention may further include a predictive computing device 300. The predictive computing device 300 may predict the state of the power facility 200 by analyzing information on the parameter transmitted from the communication unit 170.

To this end, the predictive computing device 300 may predict the state of the power facility 200 by analyzing information on parameters through a machine learning program.

Prediction of the state of the power facility 200 includes corona discharge, arc discharge, short, insulation deterioration, poor contact, tracking, which is a carbonization phenomenon caused by dust or moisture, etc. 200) may be a failure or malfunction, or a fire occurrence, but is not limited thereto.

In addition, the prediction computing device 300 may transmit the prediction result to the manager's terminal 400. The administrator's terminal may be a smartphone, a notebook computer, a personal computer, or a tablet PC, but is not limited thereto.

Meanwhile, the power equipment disaster prevention apparatus according to an embodiment of the present invention may further include a microphone sensor 180 for sensing noise from the power equipment 200. The information on the parameter may include the sensed noise level. That is, the present invention can use a parameter for the degree of noise.

The control unit 150 transmits information on a parameter including a thermal image and a noise level to the predictive computing device 300 through the communication unit 170, and the predictive computing device 300 analyzes the information on the parameter to provide power equipment. You can predict the state of 200.

The power equipment 200 such as a switchboard may include various power components such as circuit breakers, current transformers, transformers, control switches, relays, and the like. Vibration may occur while each power component is operating, and thus ultrasonic waves or noise in the audible range may occur in the power component.

The microphone sensor 180 generates a noise level by sensing ultrasonic waves or sound waves generated from a power component, and the controller 150 may transmit the noise level to the predictive computing device 300 through the communication unit 170.

In addition, the power equipment disaster prevention apparatus according to an embodiment of the present invention may further include a sensing unit 190 for sensing temperature and humidity inside the enclosure 10. Accordingly, the present invention transmits information on parameters including temperature and humidity inside the enclosure 10 to the predictive computing device 300 through the communication unit 170 so that the predictive computing device 300 transmits the parameters for the thermal image, It is also possible to predict the state of the power equipment 200 by simultaneously analyzing a parameter for noise level, a parameter for temperature, and a parameter for humidity.

The sensing unit 190 may sense not only temperature and humidity, but also current and voltage supplied to the power facility 200. Accordingly, information on parameters for current and voltage may be transmitted to the predictive computing device 300 through the communication unit 170.

The current and voltage supplied to the power facility 200 may be the current and voltage supplied to the power components, or may be the current and voltage supplied to the entire power facility 200.

The controller 150 may pre-process various types of data sensed by the thermal imaging camera 110, the microphone sensor 180, and the sensing unit 190 to convert into metadata, and transmit the metadata to the predictive computing device 300. .

In order to predict the state of the electric power facility 200, the predictive computing device 300 derives a reference pattern of each parameter up to the first point in time through machine learning, synchronizes the reference pattern of each parameter, and provides a reference pattern for each parameter. A reference degree of correlation can be derived by analyzing the degree of correlation between them.

The predictive computing device 300 may derive an abnormal prediction for the state of the power facility 200 according to a result of comparing the correlation degree of each pattern of the parameters of the second viewpoint after the first viewpoint and the reference correlation degree.

For example, the predictive computing device 300 derives a reference pattern of a parameter for a thermal image and a reference pattern of a parameter for a noise level, synchronizes the reference patterns, and analyzes the degree of correlation between the reference patterns. You can derive the degree.

Thereafter, the predictive computing device 300 may derive a pattern of parameters for a parameter for a thermal image transmitted in real time and a parameter for a degree of noise, and may derive a degree of correlation between these patterns. The predictive computing device 300 may derive an abnormal prediction for the state of the power equipment 200 by comparing the correlation degree and the reference correlation degree.

As another example, the predictive computing device 300 derives a reference pattern for each parameter for a thermal image, noise level, temperature, and humidity, synchronizes the reference patterns, and analyzes the correlation between reference patterns to determine the reference correlation degree. Can be derived.

Thereafter, the predictive computing device 300 may derive patterns of parameters for thermal images, noise levels, temperature and humidity transmitted in real time, and may derive correlation degrees between these patterns. The predictive computing device 300 may derive an abnormal prediction for the state of the power equipment 200 by comparing the correlation degree and the reference correlation degree.

The predictive computing device 300 may transmit information on such abnormal prediction to the administrator's terminal.

Meanwhile, the present invention can predict a future trend of a parameter through the reference pattern of each parameter described above. Such future trends may be made by the predictive computing device 300 or the control unit 150.

When future trends are made by the controller 150, the predictive computing device 300 may transmit the reference pattern of each parameter to the communication unit 170 through a network. The control unit 150 may include a memory unit (not shown), and may store a reference pattern of each parameter in the memory unit.

The control unit 150 or the prediction computing device 300 may predict a trend change by comparing a parameter measured in real time with a reference parameter and generating a prediction inflection point when the difference between the parameter measured in real time and the reference parameter is greater than a reference value.

4 shows an example of a thermal image of the power equipment 200.

The square display area of FIG. 4A indicates excessive heat generation in one of the three-phase connection wires of the bus bar, which may be due to loosening of fastening, phase imbalance, or a short circuit.

In addition, the square display area of FIG. 4B indicates that excessive heat is generated at the three-phase connection portion of a molded case circuit breaker (MCCB), which may occur due to overload or an error in selecting a wire or a circuit breaker.

Such a parameter for a thermal image can be used for the abnormal prediction and prediction inflection point described above.

Meanwhile, when the predictive computing device 300 derives an abnormal prediction, the predictive computing device 300 may output a safety control signal to the communication unit 170 through a network. The control unit 150 may stop the operation of the power facility 200 for which the abnormal prediction is derived according to the safety control signal.

Corona discharge, arc discharge, short, insulation deterioration, poor contact, tracking, which is a carbonization phenomenon caused by dust or moisture, of power equipment 200 Breakdowns, malfunctions, or fires are characterized by sudden or gradual growth to a critical point, and these phenomena are very difficult to detect in advance.

For example, in the case of corona discharge or arc discharge, abnormal sound waves are generated before the critical point, but it is difficult for the administrator to grasp it before the critical point. In addition, corona discharge or arc discharge is difficult to detect because the amount of current and discharge charge is not large in the initial stage, and if it continues, the insulation performance is deteriorated, which may cause damage or failure of the switchgear.

Since the present invention is used to predict an abnormality by analyzing a parameter for the degree of noise through machine learning, it is possible to predict an abnormality of the power equipment 200 according to various causes such as corona discharge or arc discharge.

In addition, the predictive computing device 300 receives the voltage and current parameters supplied to the power facility 200 as described above, derives a reference pattern therefor, and analyzes the degree of correlation with the reference pattern of other parameters to predict abnormality. You can do it. Accordingly, the present invention can use the voltage and current parameters supplied to the power equipment 200 in performing abnormality prediction.

Meanwhile, the control unit 150 may include a memory unit that stores location information and photographing time of one or more power components. The controller 150 may control the driving unit 130 according to the location information so that the thermal imaging camera 110 is disposed at a location corresponding to the location information. The controller 150 may control the thermal imaging camera 110 to take a thermal image of one or more power components at a shooting time at an arranged location.

Such location information and recording time may be matched with the identification code of the power component and stored, and the predictive computing device 300 may also store the identification code, location information, and photographing time of the power component.

The setting of the photographing time of each power component may also be optimized through machine learning of the predictive computing device 300. That is, the prediction computing device 300 may receive the shooting time at which the thermal image was captured from the communication unit 170, and derive a reference pattern of a parameter corresponding to the shooting time from which the abnormality prediction was derived, and The reference correlation degree can be derived by analyzing the degree of correlation between the reference pattern of the parameter and the reference pattern of other parameters. Accordingly, the predictive computing device 300 may shorten the period of thermal image capture according to a period or condition in which the frequency of derivation of an abnormality prediction increases.

Meanwhile, the power facility disaster prevention apparatus according to an embodiment of the present invention may further include a microphone sensor 180 installed together with the thermal imaging camera 110 in the driving unit 130. That is, the thermal imaging camera 110 and the microphone sensor 180 may be provided on the stage 131 of the driving unit 130.

The microphone sensor 180 may sense noise generated from one or more power components at a location arranged under the control of the controller 150 at a photographing time. In this case, the microphone sensor 180 may be a directional microphone sensor 180, and accordingly, a noise emitted from a power component installed at a corresponding position may be sensed.

Accordingly, the noise parameter of the power component in which the thermal image is photographed may be transmitted to the predictive computing device 300, and the predictive computing device 300 may determine the magnitude and size of ultrasonic waves or sound waves generated from the power component through the noise parameter of the power component. By processing at least one of the frequencies through machine learning, it is possible to accurately predict abnormalities of power components.

For example, the frequency pattern of ultrasonic waves or sound waves generated during normal operation and the frequency pattern of ultrasonic waves or sound waves generated during abnormal operation may be different for each power component, and this may be reflected in the abnormality prediction.

As described above, the embodiments according to the present invention have been looked at, and the fact that the present invention can be embodied in other specific forms without departing from its spirit or scope in addition to the above-described embodiments is understood by those of ordinary skill in the art. It is self-evident to Therefore, the above-described embodiments are to be regarded as illustrative rather than restrictive, and accordingly, the present invention is not limited to the above description and may be modified within the scope of the appended claims and their equivalents.

Thermal Imaging Camera(110)
Driving unit 130
Control unit 150
Communication Department (170)
Microphone sensor(180)
Sensing unit (190)
Electric power equipment (200)
Predictive computing device (300)

Claims (6)

A thermal imaging camera for taking a thermal image of the interior of the enclosure equipped with power equipment;
A driving unit provided in the enclosure to move the thermal imager;
A control unit for controlling the driving unit and the thermal imaging camera; And
And a communication unit for transmitting information on a parameter including the photographed thermal image to the outside under control of the control unit,
The power facility includes one or more power components,
The control unit,
And a memory unit for storing location information and photographing time of the one or more power components, and controlling the driving unit according to the location information so that the thermal imaging camera is disposed at a location corresponding to the location information, and the disposed location Controlling the thermal imaging camera to take a thermal image of the one or more power components at the shooting time,
The stage of the driving unit is provided with a microphone sensor along with the thermal imaging camera, and the stage can be moved vertically and horizontally according to the operation of the driving unit, so that the position information on the plane formed by the first direction and the second direction as an axis It can be moved to the corresponding location,
The microphone sensor is an electric power equipment disaster prevention apparatus, characterized in that for sensing the noise generated from the at least one power component at the time of the recording at the position in the arrangement under the control of the controller.
The method of claim 1,
And a predictive computing device for predicting a state of the power facility by analyzing information on the parameter transmitted from the communication unit.
The method of claim 2,
The information on the parameter includes a noise level sensed by the microphone sensor,
The control unit transmits information on the parameter including the thermal image and the noise level to the predictive computing device through the communication unit, and the predictive computing device analyzes the information on the parameter to predict the state of the power facility. Disaster prevention device for power facilities, characterized in that to be.
The method of claim 3,
The predictive computing device
The reference pattern of each parameter up to the first point in time is derived through machine learning,
Synchronizing the reference patterns of each of the parameters to analyze the correlation between the reference patterns of each of the parameters to derive a reference correlation degree,
And an abnormal prediction for the state of the power facility is derived according to a comparison result of the correlation between the pattern of each of the parameters at the second time point after the first time point and the reference correlation degree.
delete delete

Images