Crack Detection using standalone system
This project consists of the design, implementation and testing of a robotic system, supposed to move inside circular pipes, capture images, and detect the existence or non-existence of cracks. The project carries out different phases of realization, among which two are the most principal:
2025-06-28 16:30:59 - Adil Khan
Crack Detection using standalone system
Project Area of Specialization RoboticsProject SummaryThis project consists of the design, implementation and testing of a robotic system, supposed to move inside circular pipes, capture images, and detect the existence or non-existence of cracks. The project carries out different phases of realization, among which two are the most principal: Motion and kinematics, and image processing.
In order to initiate this project, research is conducted through a literature review, in which an investigation of the currently existing technologies in the market is carried out. The literature review also introduces the fields of mobile robotics, and provides a general overview of image processing.
In terms of programming, Python is used for image processing so as to capture images, analyze them, and unveil cracks had they been existent on a given image.Moreover, Edge detection technique is preferred for crack detection. Robot's motion speed is considered linear.
Project ObjectivesThe objective of this project is to design a robotic system, which will be used to find cracks inside industrial pipes, especially those which are not easily visible to the naked eye, to avoid substance leakage and major disasters. The detection process will happen either prior to the distribution of manufactured pipes, or during maintenance after the pipes have been used.
The goal is to be able to build a working prototype and test it on a real pipe, with the help of several technological tools, of background knowledge, as well as of research drawn from the literature. Such research is expected to be original in the measure where it will draw information from articles, papers, and books.
Moreover, transmission of cracks which are detected in real time should be wireless.
Design of robot should be robust.
Project Implementation Method
Image Processing Algorithm: 
Crack Detection Algorithm: 
Raspberry pi is used as a main controller because it offers required environment for image processing.
In 1965, a huge pipeline had exploded in Louisiana, USA, causing the death of more than 17 people and destroying 7 residences which were distant of about 450 feet from the disaster’s site. As the pipe was carrying gas and was judged to be “robust”, the huge impact of such a disaster was not at all previously foreseen. Had there been another type of volatile fuel in the pipe, the disaster’s magnitude could have probably tripled, entailing unprecedented damage.
The context of this study is, then, clear. The faulty judgement of cracks’ insignificance inside industrial pipes, be they micro or macro, has entailed several disastrous events across the world. Bearing in mind the dangerous leakage of volatile chemicals, or from an economic point of view, the loss of substance regardless of its nature, the detection of cracks must be taken more seriously and several measures must be put in place.
This project adopts as its motivation the intent to prevent engineering disasters at the level of industrial pipes, through the efficient detection of pipeline cracks. The methods currently employed, whether they make use of sonic vibrations or simply rely on human workforce, do not usually bring about accurate results. The switch to a system with higher reliability is certainly a better idea, notably if it married the advancements in engineering with those in computer science, to create a highly precise device, whose benefits would propagate and limit industry’s disastrous occurrences.
Moreover, this robot is capable of not only detecting cracks in pipelines but also in bridges and railway tracks.
Technical Details of Final DeliverableThis robot is robust and as new technology is preferred in its making so we are able to remove several limitations. Raspberry Pi is directly linked to the PC through Wifi to avoid wired communication.Since we have used image processing technique for crack detection so a concerned person will be able to see the image of detected crack and measure its intensity on the PC.The design of robot is capable of detecting crackings in various pipelines that are used in industry and also can be used in manufacturing firms.
Final Deliverable of the Project HW/SW integrated systemCore Industry ManufacturingOther Industries Petroleum , Others Core Technology RoboticsOther Technologies OthersSustainable Development Goals Good Health and Well-Being for People, Industry, Innovation and InfrastructureRequired Resources| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 19825 | |||
| Raspberry Pi 3 B+ | Equipment | 1 | 7400 | 7400 |
| Raspberry Pi V2 HD Camera | Equipment | 1 | 4000 | 4000 |
| HDMI cable | Equipment | 1 | 350 | 350 |
| Power supply | Equipment | 1 | 300 | 300 |
| Data Cable | Equipment | 1 | 250 | 250 |
| Memory Card 32 GB | Equipment | 1 | 1500 | 1500 |
| male to male and male to female wires | Equipment | 30 | 6 | 180 |
| Heat sink | Equipment | 2 | 125 | 250 |
| Battery | Equipment | 3 | 110 | 330 |
| PCB | Equipment | 1 | 500 | 500 |
| Dc Motors | Equipment | 2 | 500 | 1000 |
| Motor driver | Equipment | 1 | 280 | 280 |
| Buck Converter | Equipment | 1 | 360 | 360 |
| Caster wheel large | Equipment | 1 | 300 | 300 |
| Base sheet | Equipment | 2 | 250 | 500 |
| pipe | Equipment | 1 | 1000 | 1000 |
| chemical | Equipment | 1 | 150 | 150 |
| Nut bolts | Equipment | 15 | 35 | 525 |
| Base angles | Equipment | 1 | 500 | 500 |
| SMD light | Equipment | 5 | 20 | 100 |
| clumps | Equipment | 5 | 10 | 50 |