Data Fusion of Eddy Current NDT Signals

Chady, Tomasz; Psuj, Grzegorz; Łopato, Przemysław

doi:10.1063/1.2902718

Cited by 4 publications

(2 citation statements)

References 5 publications

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“…Data fusion techniques combine data from multiple sensors to achieve improved accuracies and more specific inferences than could be achieved by the use of a single sensor alone (Hall and Mcmullen, 2004; Klein, 1999). Applications for multi‐sensor information fusion are wide spread, for example, monitoring of manufacturing processes, condition‐based maintenance of complex machinery (Kropas‐Hughes, 2003; Chady et al , 2008), robotics (Wang and Chen, 2007), mine detection (Steinway et al , 1998), and other military applications (Harris et al , 1998). In these applications, multi‐sensor information fusion technology provides significant advantages over single source data.…”

Section: Introductionmentioning

confidence: 99%

A study on application of multi‐sensor information fusion in pulsed GTAW

Chen

Wang

Chen

2010

Industrial Robot: An International Journal

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PurposeWelding sensor technology is the key technology in welding process, but a single sensor cannot acquire adequate information to describe welding status. This paper addresses arc sensor and sound sensor to acquire the voltage and sound information of pulsed gas tungsten arc welding (GTAW) simultaneously, and uses multi‐sensor information fusion technology to fuse the information acquired by the two sensors. The purpose of this paper is to explore the feasibility and effectiveness of multi‐sensor information fusion in pulsed GTAW.Design/methodology/approachThe weld voltage and weld sound information are first acquired by arc sensor and sound sensor, then the features of the two signals are extracted, and the features are fused by weighted mean method to predict the changes of arc length. The weights of each feature are determined by optional distribution method.FindingsThe research findings show that multi‐sensor information fusion technology can effectively utilize the information of different sensors and get better result than single sensor.Originality/valueThe arc sensor and sound sensor are first used at the same time to get information about pulsed GTAW and the fusion result shows its advantages over single sensor; this reveals that multi‐sensor fusion technology is a valuable research area in welding process.

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Section: Introductionmentioning

confidence: 99%

A study on application of multi‐sensor information fusion in pulsed GTAW

Chen

Wang

Chen

2010

Industrial Robot: An International Journal

View full text Add to dashboard Cite

show abstract

“…Information fusion techniques combine information from multiple sensors to achieve improved accuracies and more specific inferences than could be achieved by the use of a single sensor alone (Hall and McMullen, 2004; Klein, 1999). Applications of multi‐sensor information spread a wide range, such as monitoring of manufacturing processes, condition‐based maintenance of complex machinery (Kropas‐Hughes, 2003; Chady et al , 2008), robotics (Wang and Chen, 2007), mine detection (Steinway et al , 1998) and other military applications (Harris et al , 1998). During these applications, multi‐sensor information fusion technology has shown its advantages over single sensor and obtained better results.…”

Section: Introductionmentioning

confidence: 99%

Multi‐sensor information fusion in pulsed GTAW based on fuzzy measure and fuzzy integral

Chen

2010

Assembly Automation

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PurposeThe status of welding process is difficult to monitor because of the intense disturbance during the process. The purpose of this paper is to use multiple sensors to obtain information about the process from different aspects and use multi‐sensor information fusion technology to fuse the information, to obtain more precise information about the process than using a single sensor alone.Design/methodology/approachArc sensor, visual sensor, and sound sensor were used simultaneously to obtain weld current, weld voltage, weld pool's image, and weld sound about the pulsed gas tungsten‐arc welding (GTAW) process. Then special algorithms were used to extract the signal features of different information. Fuzzy measure and fuzzy integral method were used to fuse the extracted signal features to predict the penetration status about the welding process.FindingsExperiment results show that fuzzy measure and fuzzy integral method can effectively utilize the information obtained by different sensors and obtain better prediction results than a single sensor.Originality/valueArc sensor, visual sensor, and sound sensor are used in pulsed GTAW at the same time to obtain information, and fuzzy measure and fuzzy integral method are used to fuse the different features in welding process for the first time; experiment results show that multi‐sensor information can obtain better results than single sensor, this provides a new method for monitoring welding status and to control the welding process more precisely.

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Multi-sensor image fusion at signal level for improved near-surface crack detection

Heideklang

Shokouhi

2015

NDT & E International

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Data Fusion of Eddy Current NDT Signals

Cited by 4 publications

References 5 publications

A study on application of multi‐sensor information fusion in pulsed GTAW

A study on application of multi‐sensor information fusion in pulsed GTAW

Multi‐sensor information fusion in pulsed GTAW based on fuzzy measure and fuzzy integral

Multi-sensor image fusion at signal level for improved near-surface crack detection

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