REMOTELY OPERATED VEHICLE FOR IDENTIFYING FRACTURES AND CORROSION IN UNDERWATER DAM STRUCTURES AND A METHOD THEREOF

Abstract

REMOTELY OPERATED VEHICLE FOR IDENTIFYING FRACTURES AND CORROSION IN UNDERWATER DAM STRUCTURES AND METHOD THEREOF ABSTRACT The present invention relates to a remotely operated vehicle for identifying fractures and corrosion in underwater dam structures, comprising: a robotic arm (1) attached at the front lower portion of the ROV; a joystick module (2) allows the operator to control the movement of the ROV and its components, including the robotic arm (3); a controller (3) connected to the joystick module (2); a plurality of sensors (4) connected to controller (3); at least two motors comprising at least six brushless direct current (BDLC) motor (5) configured to drive the robotic arm (3) and at least four servo motors (6) configured to control the movement of the robotic arm (3); an electronic speed controller (ESC) (7); at least six thrusters (8) comprising four thrusters provides forward, left, and right direction movement of ROV and other two thrusters provides upward and downward direction movement of ROV, and a camera module (9). Main Illustrative: Figure 1

Specification

Description:REMOTELY OPERATED VEHICLE FOR IDENTIFYING FRACTURES AND CORROSION IN UNDERWATER DAM STRUCTURES AND METHOD THEREOF
FIELD OF THE INVENTION
The present invention relates to a vehicle. More particularly, the present invention relates to a remotely operated vehicle (ROV) for identifying fractures and corrosion in underwater dam structures which eliminates the intervention of human deep divers and enables accurate detection and mapping of cracks and corrosion, reducing the risk of human error. Advantageously, the present invention eliminates the life risk faced by the deep divers and enhances precision.
BACKGROUND OF THE INVENTION
Dam structures are critical components of water management infrastructure, and their integrity is essential for ensuring public safety and environmental protection. However, the underwater components of these dams are susceptible to corrosion and fractures, which can have catastrophic consequences if not addressed promptly. Traditional inspection methods, such as visual inspections and acoustic testing, are often limited by their inability to detect subtle defects or monitor the structure's condition over time. This can lead to a lack of visibility into the dam's condition, making it challenging to identify potential issues before they become major problems.
Remotely operated vehicle (ROV) offers a promising solution to address these challenges. By utilizing ROVs, dam operators can gain a more comprehensive understanding of the structure's condition, including the detection of subtle defects and monitoring of the structure's condition over time. ROVs can provide high-resolution imagery and data on the dam's condition, enabling dam operators to make more informed decisions about maintenance and repair. Additionally, ROVs can be equipped with sensors and other technologies to detect changes in the structure's condition, allowing for early detection and response to potential issues. By leveraging ROV technology, dam operators can enhance the safety and reliability of their infrastructure, while also reducing costs and improving efficiency.
Some of the prior arts:
IN202441054105A discloses a to defect the corrosion in underwater infrastructures using machine learning comprising corrosion in underwater infrastructures, such as pipelines and offshore platforms, poses a significant challenge to their integrity and safety. Timely detection of corrosion is crucial to prevent structural damage and ensure the longevity of these assets. This study focuses on the development of an image processing algorithm tailored specifically for detecting corrosion in underwater environments. Underwater images captured by various means, including underwater cameras and remotely operated vehicles (ROVs), often suffer from low visibility, color distortion, and noise, making corrosion detection challenging. The proposed algorithm aims to address these challenges by employing a series of image processing techniques. Initially, preprocessing techniques are applied to enhance image quality and correct for color distortion. Then, region of interest (ROI) detection methods are used to isolate the areas of the infrastructure where corrosion is likely to occur. Subsequently, features indicative of corrosion, such as texture patterns, color properties, and shape descriptors, are extracted from the ROIs. These features are then utilized for classification, employing machine learning algorithms to differentiate between corroded and non-corroded areas. Finally, postprocessing techniques are employed to refine the results and remove false positives. The developed algorithm is intended to provide an automated and accurate solution for detecting corrosion in underwater infrastructures, thereby facilitating proactive maintenance and inspection efforts to ensure the safety and reliability of these critical assets.
CN117262161A discloses an ROV inspection method for an underwater immersion structure comprising following steps that 1, an inspection robot is arranged underwater, and posture adjustment is conducted; 2, filtering underwater interference information, and adopting a color cast correction algorithm to realize clearness processing; step 3, integrating sensor data of vision and inertial navigation to estimate the position and attitude of the ROV; 4, for a detection structure target entering the visual field of the camera, enabling the robot to approach an underwater immersion structure through a target tracking algorithm based on deep learning; and step 5, extracting geometric and texture information with defect features of the underwater immersion structure through a crack detection method based on image processing after the underwater immersion structure reaches the target at a short distance. According to the invention, underwater inspection operation can be autonomously carried out only through sensor data acquired by an IMU carried by an ROV and a camera, so that hidden dangers such as surface cracks and holes of an underwater immersion structure can be detected, the working efficiency is effectively improved, and the cost is reduced.
US10611447A discloses an autonomous underwater system for a 4D environmental monitoring comprising a multidisciplinary underwater station including onboard instrumentation, at least one autonomous modular underwater vehicle movable inside an area to be monitored along an assigned route, and at least one external instrumental modulus which can be connected the vehicle, wherein the multidisciplinary underwater station includes a docking area, an interface system, an equipping system for supplying the vehicle with instrumental moduli, and a management system.
CN108764345A discloses a underwater dam crack detection method based on local and global clustering comprising collecting an underwater dam surface image and transmitting the image to an image database, a step of preprocessing the image, initially equalizing image background illumination and enhancing a target area, a step of processing the image and equalizing the gray level of the image and then realizing image binarization by a binary threshold segmentation method, a step of extracting an image block feature and calculating a two-dimensional feature space through a cluster analysis method to obtain an image block containing a crack, a step of extracting all connected domains, taking each connected domain as a sample, extracting the features of the connected domains to form a three-dimensional feature space, and detecting the crack through the cluster analysis method, and a step of positioning the detected image containing the crack to a dam and thus determining an area where the image containing the crack is located. According to the method, the automatic detection of cracks on the surface of the dam below a water level is achieved, time and labor are saved, the cost is low, the non-destructive detection can be achieved, and the requirements of accuracy and real-time performance are satisfied.
However, the conventional system and method complicates the accurate detection of corrosion, despite preprocessing efforts to enhance image quality, and requires significant computational resources and processing time. Developing and maintaining an effective image processing algorithm for underwater corrosion detection requires significant computational resources and expertise. Continuous updates and maintenance are required to keep the algorithm effective against evolving corrosion patterns and environmental conditions. This ongoing effort adds to the operational overhead and costs associated with using the technology.
Accordingly, there is a need for an improved remotely operated vehicle (ROV) for identifying fractures and corrosion in underwater dam structures which navigates through underwater environments without human intervention, reducing the risk of human error and transmits data in real-time to enable remote monitoring and inspection.
OBJECT OF THE INVENTION
The principal object of the present invention is to provide a remotely operated vehicle (ROV) for identifying fractures and corrosion in underwater dam structures which inspects and monitor the underwater structure in real time.
Another object of the present invention is to provide an ROV for identifying fractures and corrosion in underwater dam structures which efficiently cleans or repairs cracks and corrosion.
Another object of the present invention is to provide an ROV for identifying fractures and corrosion in underwater dam structures which operates continuously for extended periods, thus allowing for thorough inspections without the limitations of human endurance.
Another object of this invention is to provide an ROV for identifying fractures and corrosion in underwater dam structures which allows for easy monitoring and analysis of the water quality.
Another object of this invention is to provide an ROV for identifying fractures and corrosion in underwater dam structures which reaches depths and areas that are difficult or impossible for human divers to access, thus ensuring comprehensive coverage of the dam structure.
SUMMARY OF THE INVENTION'
It is a primary aspect of the present invention to provide a remotely operated vehicle (ROV) for identifying fractures and corrosion in underwater dam structures, comprising: a robotic arm (1) attached at the front lower portion of the ROV; a joystick module (2) allows the operator to control the movement of the ROV and its components, including the robotic arm (3); a controller (3) connected to the joystick module (2); a plurality of sensors (4) connected to the controller (3); at least two motors comprising at least six brushless direct current (BDLC) motor (5) configured to drive the robotic arm (3) and at least four servo motors (6) configured to control the movement of the robotic arm (3); an electronic speed controller (ESC) (7); at least six thrusters (8) comprising four thrusters provides forward, left, and right direction movement of ROV and other two thrusters provides upward and downward direction movement of ROV, and a camera module (9). A 12v DC power supply is given to the controller (3) and ESC (7), from the controller (3) it equally splits and supplies the respective range of power supply to the plurality of sensors (4) and joystick module (2).
The ROV is configured to deployed into the water and descends to the desired location, the operator is configured to control the movement of the ROV using the joystick module (2), including direction, speed, and depth by using the thrusters (8) and detect the crack and corrosion, the controller (3) is configured to receive input from the joystick module (2) and sends commands to the various components of the ROV, the sensors (4) configured to provide data on various parameters, which are transmitted to the controller and displayed on a monitoring system (10), the camera module (9) provides a live video feed of the underwater environment, allowing the operator to visually inspect the dam structure,
The operator configured to control the movement of the robotic arm (3) using the joystick module (2) and perform collecting samples, taking measurements, scrubbing the walls and gates, removing any underwater waste or mud settled and resembled corrosion, thereby avoiding errors in detection and ensures accurate crack and corrosion detection. The ROV configured to use a thresholding technique (11) to map the crack and display its corresponding histogram image, thereby providing the user with a clear view of the crack and its depth and the exact coordinates and depth of the crack are then sent to the user through digital twin, thereby allowing for further analysis and action.
Another aspect of the present invention is to provide a method for working of remotely operated vehicle (ROV) for identifying fractures and corrosion in underwater dam structures, said method comprises steps of:
a. configuring the ROV to deployed into the water and descends to the desired location;
b. giving a 12v DC power supply to the controller (3) and ESC (7), from the controller (3) it equally splits and supplies the respective range of power supply to the plurality of sensors (4) and joystick module (2);
c. configuring the operator to control the movement of the ROV using the joystick module (2), including direction, speed, and depth by using the thrusters (8) and detect the crack and corrosion;
d. configuring the controller (3) to receive input from the joystick module (2) and sends commands to the various components of the ROV, the sensors (4) configured to provide data on various parameters, which are transmitted to the controller and displayed on a monitoring system (10), the camera module (9) provides a live video feed of the underwater environment, allowing the operator to visually inspect the dam structure;
e. configuring the operator to control the movement of the robotic arm (1) using the joystick module (2) and perform collecting samples, taking measurements, scrubbing the walls and gates, removing any underwater waste or mud settled and resembled corrosion, thereby avoiding errors in detection and ensures accurate crack and corrosion detection, and
f. configuring the ROV to use the thresholding technique (11) to map the crack and display its corresponding histogram image, thereby providing the user with a clear view of the crack and its depth and the exact coordinates and depth of the crack are then sent to the user through digital twin, thereby allowing for further analysis and action.
BRIEF DESCRIPTION OF THE DRAWINGS
Figure 1 is a block diagram of components used on remotely operated vehicle (ROV) for identifying fractures and corrosion in underwater dam structures according to the present invention.
Figure 2 is a flowchart of working of a remotely operated vehicle (ROV) for identifying fractures and corrosion in underwater dam structures according to the present invention.
DETAILED DESCRIPTION OF THE INVENTION
The present invention as embodied by a "a remotely operated vehicle (ROV) for identifying fractures and corrosion in underwater dam structures and method thereof" succinctly fulfils the above-mentioned need[s] in the art. The present invention has objective[s] arising because of the above-mentioned need[s], said objective[s] having been enumerated herein above.
The following description is directed to a remotely operated vehicle (ROV) for identifying fractures and corrosion in underwater dam structures and method thereof as much as the objective(s) of the present invention are enumerated, it will be obvious to a person skilled in the art that, the enumerated objective(s) are not exhaustive of the present invention in its entirety and are enclosed solely for the purpose of illustration. Further, the present invention encloses within its scope and purview, any structural alternative(s) and/or any functional equivalent(s) even though, such structural alternative(s) and/or any functional equivalent(s) are not mentioned explicitly herein or elsewhere, in the present disclosure. The present invention therefore encompasses also, any improvisation[s]/modification[s] applied to the structural alternative[s]/functional alternative[s] within its scope and purview. The present invention may be embodied in other specific form[s] without departing from the essential attributes thereof.
Furthermore, the terms and phrases used herein are not intended to be limiting, but rather are to provide an understandable description. Throughout this specification, the use of the word "comprises" and variations such as "comprises" and "comprising" may imply the inclusion of an element or elements not specifically recited.
However, the conventional system and method complicates the accurate detection of corrosion, despite preprocessing efforts to enhance image quality, and requires significant computational resources and processing time. Developing and maintaining an effective image processing algorithm for underwater corrosion detection requires significant computational resources and expertise. Continuous updates and maintenance are required to keep the algorithm effective against evolving corrosion patterns and environmental conditions. This ongoing effort adds to the operational overhead and costs associated with using the technology.
But in the case of present invention, an improved remotely operated vehicle (ROV) for identifying fractures and corrosion in underwater dam structures which navigates through underwater environments without human intervention, reducing the risk of human error and transmits data in real-time to enable remote monitoring and inspection.
Referring to Figure 1 to 2, in an embodiment of the present invention, provides an improved remotely operated vehicle (ROV) for identifying fractures and corrosion in underwater dam structures, comprising: a robotic arm (1) attached at the front lower portion of the ROV; a joystick module (2) allows the operator to control the movement of the ROV and its components, including the robotic arm (3); a controller (3) connected to the joystick module (2); a plurality of sensors (4) connected to the controller (3); at least two motors comprising at least six brushless direct current (BDLC) motor (5) configured to drive the robotic arm (3) and at least four servo motors (6) configured to control the movement of the robotic arm (3); an electronic speed controller (ESC) (7); at least six thrusters (8) comprising four thrusters provides forward, left, and right direction movement of ROV and other two thrusters provides upward and downward direction movement of ROV, and a camera module (9). A 12v DC power supply is given to the controller (3) and ESC (7), from the controller (3) it equally splits and supplies the respective range of power supply to the plurality of sensors (4) and joystick module (2),
The ROV is configured to deployed into the water and descends to the desired location, the operator is configured to control the movement of the ROV using the joystick module (2), including direction, speed, and depth by using the thrusters (8) and detect the crack and corrosion, the controller (3) is configured to receive input from the joystick module (2) and sends commands to the various components of the ROV, the sensors (4) configured to provide data on various parameters, which are transmitted to the controller and displayed on a monitoring system (10), the camera module (9) provides a live video feed of the underwater environment, allowing the operator to visually inspect the dam structure.
The operator configured to control the movement of the robotic arm (3) using the joystick module (2) and perform collecting samples, taking measurements, scrubbing the walls and gates, removing any underwater waste or mud settled and resembled corrosion, thereby avoiding errors in detection and ensures accurate crack and corrosion detection. The ROV configured to use a thresholding technique (11) to map the crack and display its corresponding histogram image, thereby providing the user with a clear view of the crack and its depth and the exact coordinates and depth of the crack are then sent to the user through digital twin, thereby allowing for further analysis and action.

In one embodiment of the present invention, the plurality of sensors (4) comprising a temperature sensor [DHT22] (4a), a potential of hydrogen [PH] sensor (4b), inertial measurement sensor [IMU] (4c), a total dissolved solids [TDS] sensor (4d), a plurality of joystick sensors (4e) and an underwater ultrasonic sensor (4f).
In one embodiment of the present invention, the camera module (9) configured to provide a live video feed of the underwater environment, thereby allowing the operator to visually inspect the dam structure.
In one embodiment of the present invention, the robotic arm is a three-degree-of-freedom (3DOF) robotic arm (1).
In one embodiment of the present invention, the four servo motors (6) provided for angular and linear position of devices such as accelerations and positioning comprising the first and second servo motors for top positing up and down movements and third and fourth servo motors used in Robotic Arm for Positioning.
In one embodiment of the present invention, the six BLDC Motors (5) comprising four BLDC motor for bottom positioning and another 2 BLDC motors for top positioning.
In one embodiment of the present invention, the controller (3) is an Arduino Mega 2560 microcontroller.
In one embodiment of the present invention, the PH Sensor (4b) configured to measures the Acidity or Alkalinity of the Water with a value between 0 to 14.
In one embodiment of the present invention, the digital twin configured to monitor the AUV's position as well as the location of the defect.
In one embodiment of the present invention, the temperature sensor [DHT22] (4a) configured to measure the Underwater Humidity and Underwater Temperature.
In one embodiment of the present invention, the underwater ultrasonic sensor (4f) configured to measure the Level Monitoring of Water.
In one embodiment of the present invention, the first Joystick Sensor configured to use X and Y Axis to Control the bottom BLDC Motor, second Joystick Sensor configured to use only X-Axis to Control the Top BLDC Motor, third Joystick Sensor configured to use only X-Axis to Control the Servo Motor and the fourth Joystick Sensor configured to use X and Y Axis to control the Robotic ARM.
In one embodiment of the present invention, the TDS sensor (4d) configured to measure the dissolved combined content of all organic and inorganic Substances in water.
In one embodiment of the present invention, the IMU sensor (4c) configured to measure the Underwater Acceleration and Gyroscopic Movements.
In one embodiment of the present invention, the BDLC motor (5) is a A2212 2200KV BLDC.
In one embodiment of the present invention, the ESC (7) is a Simonk 30A BLDC (Brushless Direct Current) Electronic Speed Controller (ESC).
In one embodiment of the present invention, the servo motor (6) is a type of electric motor.
In one embodiment of the present invention, the structure of this ROV is made up of Unplasticized Polyvinyl Chloride (UPVC).
In another embodiment of the present invention, the underwater thruster is designed in SolidWorks and it is 3D printed using SLA printing method. The thruster test experiment is performed to check the payload of the BLDC motor. A 3D model of this AUV is designed and using unity, the digital twin is created to examine the AUV's position and its navigation. Thresholding Image processing technique is used to map the crack and corroded portion in underwater.
Another embodiment of the present invention, the integration of virtual reality (VR) technology with digital twin representations of underwater structures further enhances the capabilities of inspection and maintenance systems. Digital twins provide accurate virtual replicas of physical assets, allowing for real-time monitoring and analysis of structural integrity. By combining VR interfaces with digital twins, operators can visualize sensor data overlaid onto high-fidelity models, facilitating proactive maintenance planning and optimization strategies. This integration not only improves the efficiency of inspection processes but also enables predictive maintenance, minimizing downtime and reducing the risk of costly asset failures.
Another embodiment of the present invention is to provide a method for working of remotely operated vehicle (ROV) for identifying fractures and corrosion in underwater dam structures, said method comprises steps of:
a. configuring the ROV to deployed into the water and descends to the desired location;
b. giving a 12v DC power supply to the controller (3) and ESC (7), from the controller (3) it equally splits and supplies the respective range of power supply to the plurality of sensors (4) and joystick module (2);
c. configuring the operator to control the movement of the ROV using the joystick module (2), including direction, speed, and depth by using the thrusters (8) and detect the crack and corrosion;
d. configuring the controller (3) to receive input from the joystick module (2) and sends commands to the various components of the ROV, the sensors (4) configured to provide data on various parameters, which are transmitted to the controller and displayed on a monitoring system (10), the camera module (9) provides a live video feed of the underwater environment, allowing the operator to visually inspect the dam structure;
e. configuring the operator to control the movement of the robotic arm (1) using the joystick module (2) and perform collecting samples, taking measurements, scrubbing the walls and gates, removing any underwater waste or mud settled and resembled corrosion, thereby avoiding errors in detection and ensures accurate crack and corrosion detection, and
f. configuring the ROV to use the thresholding technique (11) to map the crack and display its corresponding histogram image, thereby providing the user with a clear view of the crack and its depth and the exact coordinates and depth of the crack are then sent to the user through digital twin, thereby allowing for further analysis and action.

Another embodiment of the present invention, the digital twin of a Remotely Operated Vehicle (ROV) is created using Unity 3D and Arduino with an Inertial Measurement Unit (IMU) for underwatermotion tracking, begin by gathering components such as an Arduino board and an IMU sensor. The IMU is Set up with Arduino following its datasheet, including connecting it and installing necessary libraries for communication. Calibration is essential for accurate readings, typically performed using provided routines in IMU libraries. Arduino code is written to read IMU data, covering measurements like acceleration and gyroscope readings and the obtained data is transmitted to Unity through serial communication.
Another embodiment of the present invention, the ROV's 3D model is designed either importing from various sources or creating within Unity itself. The IMU data received from Arduino is integrated, and the digital twin's position, orientation, and motion are updated in Unity. The IMU data is utilized to animate the digital twin's movement, underwater conditions like buoyancy and currents are simulated for a realistic environment. The functionality and user experience are refined through thorough testing and iteration, thus ensure accurate transmission and processing of IMU data between Arduino and Unity.

WORKING EXAMPLE
An exemplary embodiment discloses a remotely operated vehicle (ROV) for identifying fractures and corrosion in underwater dam structures comprising configuring the ROV to deployed into the water and descends to the desired location. The operator is configured to control the movement of the ROV using the joystick module (2), including direction, speed, and depth by using the thrusters (8) and detect the crack and corrosion. The controller (3) is configured to receive input from the joystick module (2) and sends commands to the various components of the ROV. The sensors (4) are configured to provide data on various parameters, which are transmitted to the controller and displayed on a monitoring system (10). The camera module (9) is configured to provide a live video feed of the underwater environment, allowing the operator to visually inspect the dam structure. The operator is configured to control the movement of the robotic arm (1) using the joystick module (2) and perform collecting samples, taking measurements, scrubbing the walls and gates, removing any underwater waste or mud settled and resembled corrosion, thereby avoiding errors in detection and ensures accurate crack and corrosion detection. The12v DC power supply is given to the controller (3) and ESC (7), from the controller (3) it equally splits and supplies the respective range of power supply to the plurality of sensors (4) and joystick module (2),The ROV is configured to use the thresholding technique (11) to map the crack and display its corresponding histogram image, thereby providing the user with a clear view of the crack and its depth and the exact coordinates and depth of the crack are then sent to the user through digital twin, thereby allowing for further analysis and action.
3D PRINTED THRUSTER
The dimensions of the thruster are mentioned in Table 1.
S.NO DESCRIPTION DIMENSIONS
1 Thruster Weight 59 grams
2 Outer hub height 55 mm
3 Outer hub diameter 75 mm
4 Propeller diameter 30mm
5 Propeller height 40 mm
6 Propeller base diameter 30 mm
7 Propeller base height 70 mm

SENSOR:
SENSORS MIN MAX
DHT11 0°C or 32°F 50°C or 122°F
TDS 0 ppm 600 ppm
UNDERWATER ULTRASONIC 250mm 1500mm
pH 6.5 9.0

ADVANTAGE OF THE PRESENT INVENTION
The present invention relates to a remotely operated vehicle (ROV) for identifying fractures and corrosion in underwater dam structures which allows for efficient cleaning and repair of cracks and corrosion using robotic arm, reducing maintenance downtime and costs.
The present invention relates to a ROV which enables accurate detection and mapping of cracks and corrosion, reducing the risk of human error.
The present invention relates to a ROV which provides real-time data on water quality parameters, enabling timely monitoring and response to potential issues.
The present invention relates to a ROV which enables easy monitoring and analysis of water quality parameters, making it easier to identify trends and anomalies.
The present invention relates to a ROV which provides precise control over the ROV's movement, allowing for targeted inspection and maintenance.
The present invention relates to a ROV which reduces the costs associated with traditional underwater inspection methods, such as diver training and equipment costs.
The present invention relates to a ROV which access areas that are difficult or impossible to reach with traditional underwater inspection methods, such as remote or hard-to-reach areas.
The present invention relates to an integrated charging port which provides a safer, more efficient, and more reliable solution for powering various functions in agricultural vehicles. It will be apparent to a person skilled in the art that the above description is for illustrative purposes only and should not be considered as limiting. Various modifications, additions, alterations, and improvements without deviating from the spirit and the scope of the invention may be made by a person skilled in the art.
 
LIST OF NUMBERALS
(1). Robotic arm
(2). Joystick module
(3). Controller
(4). Sensors
(4a). Temperature sensor [DHT22]
(4b). Potential of hydrogen [PH] sensor
(4c). Inertial measurement sensor [IMU]
(4d). Total dissolved solids [TDS] sensor
(4e). Joystick sensors
(4f). Underwater ultrasonic sensor
(5). BDLC motor
(6). Servo motor
(7). Electronic speed controller (ESC)
(8). Thrusters
(9). Camera module
(10). Monitoring system
(11). Thresholding technique
(12). Raspberry Pi
, C , Claims:and positioning comprising the first and second servo motors for top positing up and down movements and third and fourth servo motors used in Robotic Arm for Positioning.
6. The ROV as claimed in claim 1, wherein the six BLDC Motors (5) comprising four BLDC motor for bottom positioning and another 2 BLDC motors for top positioning.
7. The ROV as claimed in claim 1, wherein the controller (3) is an Arduino Mega 2560 microcontroller.
8. The ROV as claimed in claim 1, wherein the plurality of joystick sensors comprising the first Joystick Sensor configured to use X and Y Axis to Control the bottom BLDC Motor, second Joystick Sensor configured to use only X-Axis to Control the Top BLDC Motor, third Joystick Sensor configured to use only X-Axis to Control the Servo Motor and the fourth Joystick Sensor configured to use X and Y Axis to control the Robotic ARM.
9. A method for working of remotely operated vehicle (ROV) for identifying fractures and corrosion in underwater dam structures, said method comprises steps of:
a. configuring the ROV to deployed into the water and descends to the desired location;
b. giving a 12v DC power supply to the controller (3) and ESC (7), from the controller (3) it equally splits and supplies the respective range of power supply to the plurality of sensors (4) and joystick module (2);
c. configuring the operator to control the movement of the ROV using the joystick module (2), including direction, speed, and depth by using the thrusters (8) and detect the crack and corrosion;
d. configuring the controller (3) to receive input from the joystick module (2) and sends commands to the various components of the ROV, the sensors (4) configured to provide data on various parameters, which are transmitted to the controller and displayed on a monitoring system (10), the camera module (9) provides a live video feed of the underwater environment, allowing the operator to visually inspect the dam structure;
e. configuring the operator to control the movement of the robotic arm (1) using the joystick module (2) and perform collecting samples, taking measurements, scrubbing the walls and gates, removing any underwater waste or mud settled and resembled corrosion, thereby avoiding errors in detection and ensures accurate crack and corrosion detection, and
f. configuring the ROV to use the thresholding technique (11) to map the crack and display its corresponding histogram image, thereby providing the user with a clear view of the crack and its depth and the exact coordinates and depth of the crack are then sent to the user through digital twin, thereby allowing for further analysis and action.

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