Adil Khan 9 months ago
AdiKhanOfficial #FYP Ideas

Temperature profiling of an electric grid using unmanned aerial vehicle

Power transmission lines remain on maximum loading condition in hot summers. Due to this overloading, the connected grid station has severe red hot spots on the junction points in the switchyards. As a result, most of the times pitting happens and sometimes it leads to a breakdown. A grid station no

Project Title

Temperature profiling of an electric grid using unmanned aerial vehicle

Project Area of Specialization

Electrical/Electronic Engineering

Project Summary

Power transmission lines remain on maximum loading condition in hot summers. Due to this overloading, the connected grid station has severe red hot spots on the junction points in the switchyards. As a result, most of the times pitting happens and sometimes it leads to a breakdown. A grid station normally consists of two or more than two yards, so there are hundreds of critical node points for the red hot spots. The usual practice is that, in hot summers, maintenance workers note down the temperature of each junction point in the daylight using a noncontact thermal gun. During the night, the temperature of each red hot spot is noted by turning off the security lights of the yard so that the glowing point could be visible. It takes a lot of time as there are so many junctions and nodes in the form of a mesh that exist in the grid yard. An unmanned aerial vehicle (UAV) mounted temperature monitoring system is a possible solution for the thermal profiling of electric grid stations. This will not only avoid manual labor, but it will also provide fast and quick results in the digital form which can be processed by a computer.

In this project, the unmanned aerial vehicle-mounted thermal imagery circuit for the temperature profiling of an electric grid station has been proposed. The project consists of two main parts: hardware and software. The hardware part combines unmanned aerial vehicle and thermal camera circuits to capture and transmit the required data. The unmanned aerial vehicle consists of four motors spinning in the opposite direction (2 clockwise and 2 anticlockwise), controlled remotely. The thermal imagery circuit comprises of a microbolometer sensor, thermopile sensor, and a suitable thermal module using a microcontroller. The software component processes the transmitted data required to calculate the temperature of the desired point from the thermal image.  The project provides a safe, and cost-effective solution for remotely collecting the thermal profile of an electric grid switchyard in a flexible manner.

Project Objectives

The objectives of this project are:

  • Design and develop a thermal imgaing module using micro-bolometric infrared thermal sensor and micro-controller board.
  •  Mounting/connection of thermal imaging module with Unmanned Aerial Vehicle (Quad-copter).
  •  Capturing and saving the data of thermal images for further processing.
  •  Recognition and interpretation of different infrared levels of thermal image for temperature measurement.
  • Encourage the idea of substituting human workers with a UAV profiling device.

Project Implementation Method

In this project, the AMG8833 thermal sensor is used to measure the temperature of the heated nodes. It is an 8 by 8 array thermal sensor. The temperature range of this sensor is 0 to 80 degrees Celsius or 32 to 176 degrees Fahrenheit with an accuracy of plus-minus 2.5 degrees Celsius. The AMG8833 sensor is a cheap sensor that offers a 60-degree viewing field, with a 10 Hz frame rate. This thermal sensor converts the IR rays into electrical voltage and passes them to the signal conditioning unit, and shows a thermal image of an object on the display screen. In this work, this sensor is interfaced to the Raspberry Pi board.  An array of 64 individual pixels temperature is obtained from the sensor. The array is further processed for the determination of temeprature. Figure 01 shows the flow chart for the thermal imaging module. 

 Figure 01: Thermal imaging module.

Aerial thermal imaging cameras make it easy to quickly survey a large target area and detect problems with power grids. This simplifies the implementation of qualitative analysis by allowing the operator to quickly recognize heat differences in the grid equipment and identify potential deficiencies. Figure 02 shows the drone control flow chart. Figure 03 shows the working flow of the quadcopter.

Figure 02: Drone control and formation planning.

Figure 03: The working flow of the quadcopter.

We have provided schematic drawings of all the hardware. However, a brief description of the connections of the quadcopter is given below.

  • Solder the Electronic Speed Controller (ESC) pins with a quadcopter frame.
  • The VCC (red wire) of the Electronic Speed Controller (ESC) is connected to the positive terminal of the drone frame and the ground (black wire) is connected to the negative terminal of the drone frame.
  • Attache the propeller arms with the quadcopter fame through screws and nuts. 
  • Attach the brushless motor to the propeller arms.
  • Connect the wires of the electronic speed controller with a brushless motor. The VCC pin of the motor is connected to the VCC pin of the electronic speed controller. The PWM wire of the motor is connected to the PWM with the electronic speed controller and the ground wire of the electronic speed controller is connected to the motor.
  • Attach the shock absorber to the top of the frame.
  • APM 2.8 is placed on top of the shock absorber.
  • The APM 2.8 input pin (1 to 5) is connected to the receiver via a jumper wire (female to female jumper wire).
  • Connect the GPS stand to the drone body.
  • The GPS module is attached to the GPS stand.
  • Connect the GPS with the APM module.

Figure 04: Quadcopter connections

Figure 05: Quadcopter top view

Figure 06: Quadcopter mounted with thermal setup

Figure 07, Figure 08, and Figure 09 show the wiring schemes of the thermal imaging module.

Figure 07: Schematic connection 01

Figure 08: Schematic connection 02

Figure 09: Schematic connection 03

Benefits of the Project

The electric grid is an important connecting link between the distribution system and the transmission lines. In an electric grid, the switchgear directs the flow of energy and ensures the safety of the system by directly controlling the input and output power flow. Transformers are used to change the supply voltage from one level to another according to the situation. A grid station consists of multiple incoming and outgoing circuits connected to a common bus bar system, auto-transformer, current transformer (CT), and potential transformer for protection and measurement purposes.

The power transmission line is a conductor which is used to carry electricity from generating stations to the distribution substation to deliver electric energy to consumers. To transfer the electrical energy from generating stations, the generated voltages are stepped up through a transformer and carried out through the transmission line. When the electrical energy reached the substation, it steps down to a lower voltage level, which is then delivered to the distribution lines. The distribution lines, distribute the electrical energy to consumers (industries, houses, farms, etc). The structure type of the transmission system is determined by the route, existing infrastructure, and the voltage level of the electrical power.

Substations and transmission line localities remain on maximum loading condition in hot summers. Overloading in harsh conditions results in the red-hot spots of the critical nodes in the substations and transmission lines which then results in the pitting of conductors and most of the times breakdowns so timely monitoring or inspection of these nodes or critical points is required. There are hundreds of nodes present even in a substation so it takes too much time. Natural conditions and patrolling in this condition need manpower in harsh conditions, which is difficult. Thus, temperature profiling based on quadcopters is a possible option to automate the process. This will reduce manual labour and the time required for the thermal profiling of the grid. In addition, the temperature nodes are collected in digital form. The data can be processed for further analysis.

Videos links of the project:

Flying drone thermo profiling: https://drive.google.com/file/d/1WdAbUIWNY8GvsmIcrEHxmQBX6kBY8-ch/view?usp=sharing

Electric grid transformer ground thermo profiling 02: https://drive.google.com/file/d/1qYknCEZIcMtrUxAcIz05EUzrEJ43Yh0c/view?usp=sharing

Technical Details of Final Deliverable

Virtual network computing is exploited in this project for communication between UAV-mounted thermal modules and ground control. The server is installed on the UAV-mounted computer, the client installed it on the ground control computer. The connection of the two devices using the VNC is shown in Figure 10.

Figure 10: Ground control of the UAV using VNC

Results and Findings

Emissivity is a measure of the efficiency at which a surface emits thermal energy. Emissivity is essential for both calculations of heat transfer and accurate measurement of non-contact temperature.  An object having low emissivity appears dull to a thermal camera.

In the ideal case, the emissivity range is from 0 to 1, whereas in reality, the range of emissivity is from 0.01 to 0.99. It depends on the material, temperature, wavelength as well as nature of the surfaces. For example, polished metal surfaces have lower emissions but coarse metal surfaces have higher emissions. Table 01 shows the range of emissivity of different electrical materials.

Table 01: Emissivity of Electrical Equipment

Equipment

Emissivity (30 to 200oC)

PG clamp two-bolt connector

0.70 to 0.80

PG clamp three-bolt connector

0.61 to 0.75

New parts of the fuse cut-out

0.43 to 0.64

Old parts of the fuse cut-out

0.51 to 0.85

New insulators connector

0.48 to 0.58

Old insulators connector

0.43 to 0.69

Disconnecting switch

0.66 to 0.85

Aluminum conductor

0.71 to 0.79

Experimental Results

After getting the knowledge of the emissivity. The thermal setup is tested on many objects like the human body, running stove, plastic chair, and floor of the house. Some results are attached to this proposal.

Figure 11, shows the thermal image of a human body. The image is captured at a distance of less than 1 foot from the human body. The output temperature is 27 degrees Celsius.

Figure 11: Human Body Thermal Image 01

Figure 12, shows the thermal image of a human body. The image is captured at a distance of up to 4 feet from the human body. The output temperature is 26 degrees Celsius.

Figure 12: Human Body Thermal Image 02

Figure13 shows the thermal image of a human body. The image is captured at a distance of up to 7 feet from the human body. The output temperature is 25 degrees Celsius.


Figure 13: Human Body Thermal Image 03

From Figures 11, 12, and 13 it is clear that as the distance from the human body increases the ability to measure the correct temperature of the human body by AMG 8833 is reduced. For precise and accurate results, the distance of the object from AMG 8833 must be within 4 feet.

Figure 14: Running Stove Thermal Image 01 from 4 feet

Figure 15: Transformer Thermal Image 01 from 5 feet

Figure 16: Transformer Thermal Image 02 from 8 feet

Table 02 shows the output temperatures in celsius from the thermal setup.

&

Hottest point temperature Mean temperature Room temperature Standard deviation Variance
26.25 24.26 23.1 1.2

Equipment

PG clamp two-bolt connector

PG clamp three-bolt connector

New parts of the fuse cut-out

Old parts of the fuse cut-out

New insulators connector

Old insulators connector

Disconnecting switch

Aluminum conductor

Hottest point temperature

26.25

Final Deliverable of the Project

HW/SW integrated system

Core Industry

Energy

Other Industries

Security

Core Technology

Robotics

Other Technologies

Others

Sustainable Development Goals

Decent Work and Economic Growth, Industry, Innovation and Infrastructure

Required Resources

Hottest point temperature Mean temperature Room temperature Standard deviation Variance
26.25 24.26 23.1 1.2
If you need this project, please contact me on contact@adikhanofficial.com
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