scholarly journals Development of a Pipe Crawler Inspection Tool for Fossil Energy Power Plants

2021 ◽  
Author(s):  
Julie Villamil ◽  
Caique Lara ◽  
Anthony Abrahao ◽  
Aparna Arvelli ◽  
Guilherme Daldegan ◽  
...  

Fossil fuel power plants are complex systems containing multiple components that create extreme environments for the purpose of extracting usable energy. Failures in the system can lead to increased down time for the plant, reduction of power and significant cost for repairs. In the past, inspections and maintenance of the plant's superheater tubes has been predominantly manual, laborious, and extremely time consuming. This is due to the pipe's small diameter size (between 1.3 and 7.6 cm) and the coiled structure of the tubing. In addition, the tubes are often stacked close to each other, limiting access for external inspection. Detection of pipe degradation, such as increased levels of corrosion, creep, and the formation of micro-cracks is possible using standard non-destructive evaluation (NDE) methods, including ultrasonic, radiography and electromagnetic methods. However, when the access to the sub-systems is limited or the configuration of the structure is prohibitive, alternative methods are needed for deploying the NDE tools. This research effort considers a novel robotic inspection system for the evaluation of small pipes found in typical boiler superheaters that have limited access. The pipe crawler system is an internal inspection device that can potentially navigate through the entire pipe length using linear actuators to grip the walls and inch along the pipe. The modular nature of the system allows it to traverse through straight sections and multiple 90-degree and 180-degree bends. The crawler is also capable of providing visual inspections, ultrasonic thickness measurements, and generating inner diameter surface maps using LiDAR (light detection and ranging). Ultimately, the development of this robotic inspection tool can provide information regarding the structural integrity of key pipeline components in fossil fuel power plants that are not easily accessible

2021 ◽  
Vol 79 (7) ◽  
pp. 728-738
Author(s):  
Caique Lara ◽  
Julie Villamil ◽  
Anthony Abrahao ◽  
Aparna Aravelli ◽  
Guilherme Daldegan ◽  
...  

Fossil fuel power plants are complex systems containing multiple components that require periodic health monitoring. Failures in these systems can lead to increased downtime for the plant, reduction of power, and significant cost for repairs. Inspections of the plant’s superheater tubes are typically manual, laborious, and extremely time-consuming. This is due to their small diameter size (between 1.3 and 7.6 cm) and the coiled structure of the tubing. In addition, the tubes are often stacked close to each other, limiting access for external inspection. This paper presents the development and testing of an electrically powered pipe crawler that can navigate inside 5 cm diameter tubes and provide an assessment of their health. The crawler utilizes peristaltic motion within the tubes via interconnected modules for gripping and extending. The modular nature of the system allows it to traverse through straight sections and multiple 90° and 180° bends. Additional modules in the system include an ultrasonic sensor for tube thickness measurements, as well as environmental sensors, a light detecting and ranging (LiDAR) sensor, and camera. These modules utilize a gear system that allows for 360° rotation and provides a means to inspect the entire internal circumference of the tubes.


1985 ◽  
Vol 107 (4) ◽  
pp. 267-269 ◽  
Author(s):  
S. Z. Wu ◽  
D. N. Wormley ◽  
D. Rowell ◽  
P. Griffith

An evaluation of systems for control of fossil fuel power plant boiler and stack implosions has been performed using computer simulation techniques described in a companion paper. The simulations have shown that forced and induced draft fan control systems and induced draft fan bypass systems reduce the furnace pressure excursions significantly following a main fuel trip. The limitations of these systems are associated with actuator range and response time and stack pressure excursions during control actions. Preliminary study suggests that an alternative control solution may be achieved by discharging steam into the furnace after a fuel trip.


2019 ◽  
Vol 11 (9) ◽  
pp. 1117 ◽  
Author(s):  
Haopeng Zhang ◽  
Qin Deng

The frequent hazy weather with air pollution in North China has aroused wide attention in the past few years. One of the most important pollution resource is the anthropogenic emission by fossil-fuel power plants. To relieve the pollution and assist urban environment monitoring, it is necessary to continuously monitor the working status of power plants. Satellite or airborne remote sensing provides high quality data for such tasks. In this paper, we design a power plant monitoring framework based on deep learning to automatically detect the power plants and determine their working status in high resolution remote sensing images (RSIs). To this end, we collected a dataset named BUAA-FFPP60 containing RSIs of over 60 fossil-fuel power plants in the Beijing-Tianjin-Hebei region in North China, which covers about 123 km 2 of an urban area. We compared eight state-of-the-art deep learning models and comprehensively analyzed their performance on accuracy, speed, and hardware cost. Experimental results illustrate that our deep learning based framework can effectively detect the fossil-fuel power plants and determine their working status with mean average precision up to 0.8273, showing good potential for urban environment monitoring.


1971 ◽  
Vol 13 (1) ◽  
pp. 391-401 ◽  
Author(s):  
B.P. Breen ◽  
A.W. Bell ◽  
N. Bayard de Volo ◽  
F.A. Bagwell ◽  
K. Rosenthal

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