Application of neuro-fuzzy techniques in oil pipeline ultrasonic nondestructive testing

Ravanbod, H.

doi:10.1016/j.ndteint.2005.03.001

Cited by 33 publications

(8 citation statements)

References 12 publications

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“…The proposed system consists of a network of miniature ultrasonic sensors embedded in a thin dielectric film that can be integrated with the pipe. Ravanbod [ 35 ] introduces fuzzy decision-based neural network algorithms for the detection and classification of corrosions in the pipeline inspection.…”

Section: Introductionmentioning

confidence: 99%

Multiple Cracks Detection in Pipeline Using Damage Index Matrix Based on Piezoceramic Transducer-Enabled Stress Wave Propagation

Kong

Zhou

et al. 2017

Sensors

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Abstract:Cracks in oil and gas pipelines cause leakage which results in property damage, environmental pollution, and even personal injury or loss of lives. In this paper, an active-sensing approach was conducted to identify the crack damage in pipeline structure using a stress wave propagation approach with piezoceramic transducers. A pipeline segment instrumented with five distributed piezoceramic transducers was used as the testing specimen in this research. Four cracks were artificially cut on the specimen, and each crack had six damage cases corresponding to different crack depths. In this way, cracks at different locations with different damage degrees were simulated. In each damage case, one piezoceramic transducer was used as an actuator to generate a stress wave to propagate along the pipeline specimen, and the other piezoceramic transducers were used as sensors to detect the wave responses. To quantitatively evaluate the crack damage status, a wavelet packet-based damage index matrix was developed. Experimental results show that the proposed method can evaluate the crack severity and estimate the crack location in the pipeline structure based on the proposed damage index matrix. The sensitivity of the proposed method decreases with increasing distance between the crack and the mounted piezoceramic transducers.

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Section: Introductionmentioning

confidence: 99%

Multiple Cracks Detection in Pipeline Using Damage Index Matrix Based on Piezoceramic Transducer-Enabled Stress Wave Propagation

Kong

Zhou

et al. 2017

Sensors

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“…Firstly, the sensors may aid in monitoring the production process, to either detect fault issues or to enhance production [ 47 , 48 ]. For example, the sensor node on a pump-jack of an oil well can gather the electric parameters, temperature, pressure and payload of this pump-jack.…”

Section: Introductionmentioning

confidence: 99%

An Effective Collaborative Mobile Weighted Clustering Schemes for Energy Balancing in Wireless Sensor Networks

Tang

Shokla

Modhawar

et al. 2016

Sensors

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Collaborative strategies for mobile sensor nodes ensure the efficiency and the robustness of data processing, while limiting the required communication bandwidth. In order to solve the problem of pipeline inspection and oil leakage monitoring, a collaborative weighted mobile sensing scheme is proposed. By adopting a weighted mobile sensing scheme, the adaptive collaborative clustering protocol can realize an even distribution of energy load among the mobile sensor nodes in each round, and make the best use of battery energy. A detailed theoretical analysis and experimental results revealed that the proposed protocol is an energy efficient collaborative strategy such that the sensor nodes can communicate with a fusion center and produce high power gain.

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“…This method is used to detect corrosion, measure dimensions and geometry and estimate the severity of the detected flaw in the test sample. [1][2][3][4] Measured ultrasonic signals don't possess the desired quality because of amalgamation, with noise and distortions due to the conditions during measurement [5]. Thus it is always necessary not only to reduce noise and deviations due to measurement conditions by pre-processing, but also to adapt the range of the processing system with the measured signal range.…”

Section: Introductionmentioning

confidence: 99%

Flaw characterization in ultrasonic non-destructive testing method using exponential modeling

Ravanbod

Karimi²,

Amindavar

2013

2013 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)

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Determining the shape, area, volume, and direction of flaws using ultrasonic imaging of metallic pieces, is a method estimating the severity of their defects. Different methods are used to process ultrasound images. Among these methods are spectral analyses, statistical, mathematical and intelligent methods. Within each of these, there are some advantages as well as limitations. Prony algorithm, which has been used as a parametric method for extracting exponential components of a signal, has several applications in signal modeling, system identification and classification. In this paper, after simulating pieces of oil pipeline, digital Wavelet transform has been used to reduce the noise of simulated images. Then the two dimensional Prony algorithm is applied to the images. After estimating the poles and residue of the signal using the Prony method, some features are extracted from these components in order to detect and classify defects. The method proposed in this paper, unlike conventional methods, will not only locate a flaw position in the image, but it can also be used to simultaneously estimate the depth and area of the defect.

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Application of neuro-fuzzy techniques in oil pipeline ultrasonic nondestructive testing

Cited by 33 publications

References 12 publications

Multiple Cracks Detection in Pipeline Using Damage Index Matrix Based on Piezoceramic Transducer-Enabled Stress Wave Propagation

Multiple Cracks Detection in Pipeline Using Damage Index Matrix Based on Piezoceramic Transducer-Enabled Stress Wave Propagation

An Effective Collaborative Mobile Weighted Clustering Schemes for Energy Balancing in Wireless Sensor Networks

Flaw characterization in ultrasonic non-destructive testing method using exponential modeling

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