New directions for inline inspection of automobile laser welds using non-destructive testing

Machado, Miguel A.; Rosado, Luís S.; Mendes, Nuno Alberto Marques; Miranda, Rosa Maria Mendes; Santos, Telmo G.

doi:10.1007/s00170-021-08007-0

Cited by 18 publications

(13 citation statements)

References 17 publications

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“…Membership functions enable to render a pictorial representation of a fuzzy set. 1) . Step 7: Computing the objective function…”

Section: Resultsmentioning

confidence: 99%

“…Several research works are carried out towards clustering diverse mathematical and data consisting of varied attributes. is is owing to its demand in real-time applications [1]. Cracks are surface or subsurface scissures that originate in a material.…”

Section: Introductionmentioning

confidence: 99%

“…e existing NDT techniques enable the detection of pore flaws having a diameter of 0.13 mm and porosity flaws that are submerged at a depth of 1 mm [1]. In the final solidifying of the weld pool, we have crater pipe (gas porosity).…”

Section: Introductionmentioning

confidence: 99%

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Surface Flaw Detection of Plug Valve Material Using Infrared Thermography and Weighted Local Variation Pixel-Based Fuzzy Clustering Technique

Jacintha

Karthikeyan

Sivaprakasam

2022

Advances in Materials Science and Engineering

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This study focuses on the identification and categorization of plug valve defects. We utilize a thermal fluke camera to obtain the plug valve thermal images. The thermal camera utilizes passive infrared thermography towards the identification of plug valve defects such as cracks, porosity, and internal defects. These flaws depict variation in surface temperature induced by heat flux. Infrared thermography is capable of identification of surface flaws such as cracks and subsurface flaws such as porosity. Its flaw identification range is effective only up to a certain depth in the metal. The heat flux variations are clearly visible for surface cracks and subsurface porosity. However, the heat flux shows no fluctuations for internal defects. Hence, to identify the internal defects in the metal, we opt for a combination of passive infrared thermography and dye penetrating test. In the dye penetrating test, a thinned paint is applied over the metal surface that aids in the identification of cracks, porosity, and internal defects as well. The PIT-DPT (passive infrared thermography-dye penetrating test) works in combination with weighted local variation pixel-based fuzzy clustering (WLVPBFC) to measure the depth of the defects. The defects were measured against parametric quantities such as F-value, precision, recall, accuracy, Jaccard index, TP, FP, TN, FN, FP rate, TP rate, and MCC. These parameters depict variations with regard to surface texture and extent of defect level. The PIT-DPT and WLVPBFC techniques identify metal flaws with 87.88% efficiency when evaluated against other existing algorithms.

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“…Membership functions enable to render a pictorial representation of a fuzzy set. 1) . Step 7: Computing the objective function…”

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Surface Flaw Detection of Plug Valve Material Using Infrared Thermography and Weighted Local Variation Pixel-Based Fuzzy Clustering Technique

Jacintha

Karthikeyan

Sivaprakasam

2022

Advances in Materials Science and Engineering

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“…The electrical conductivity of the materials is crucial for the design of dedicated inspection probes, so measurements were carried out. The roof panel had an electrical conductivity of 5.21 × 10 6 S/m, the side panel of 6.44 × 10 6 S/m, and the filler material of 2.03 × 10 6 S/m [10]. Figure 1b schematically illustrates the possible defects that may occur in such joints.…”

Section: Methodsmentioning

confidence: 99%

“…Eddy Current Testing (ECT) early demonstrated the ability to detect and classify defects [8], while the use of array probes, which allow enhanced throughput, was later proposed [9]. More recently, an innovative ECT inspection system was proposed for the detection of laser-brazed joints surface and sub-surface defects, operating autonomously and integrated with a robotized arm [10].…”

Section: Introductionmentioning

confidence: 99%

Multisensor Inspection of Laser-Brazed Joints in the Automotive Industry

Machado

Rosado

Mendes

et al. 2021

Sensors

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Automobile laser brazing remains a complex process whose results are affected by several process variables that may result in nonacceptable welds. A multisensory customized inspection system is proposed, with two distinct non-destructive techniques: the potential drop method and eddy current testing. New probes were designed, simulated, produced, and experimentally validated in automobile’s laser-brazed weld beads with artificially introduced defects. The numerical simulations allowed the development of a new four-point probe configuration in a non-conventional orthogonal shape demonstrating a superior performance in both simulation and experimental validation. The dedicated inspection system allowed the detection of porosities, cracks, and lack of bonding defects, demonstrating the redundancy and complementarity these two techniques provide.

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An automated nondestructive testing system for the surface of pressure pipeline welds

Zhang

Guan

et al. 2023

Journal of Field Robotics

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Pressure pipelines are widely used in hydropower generation, oil and gas transmission, and other fields. After years of operation, a pressure pipeline needs regular maintenance to ensure its safety. At present, manual detection methods are unable to meet this demand. An automatic pressure pipeline detection technology is urgently needed to achieve improved efficiency and accuracy. On the basis of the above requirements, a wall‐climbing robot is designed for automatic pressure pipe inspection and maintenance tasks. Moreover, rapid nondestructive testing of welds on the inner surface of pressure pipelines was performed, and a weld tracking function was developed for wall‐climbing robots. We propose an algorithm framework for weld recognition and centerline extraction by combining computer vision technology with traditional image processing technology using visual images. The experimental verification of the wall‐climbing robot designed in this paper and the algorithm framework for weld recognition and centerline extraction were performed based on actual pressure pipelines. The results show that the algorithm framework developed based on the wall‐climbing robot equipped with an industrial camera for pressure pipeline weld detection can achieve greatly improved efficiency, and the actual weld identification accuracy can exceed 90%, which is very meaningful for practical applications.

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New directions for inline inspection of automobile laser welds using non-destructive testing

Cited by 18 publications

References 17 publications

Surface Flaw Detection of Plug Valve Material Using Infrared Thermography and Weighted Local Variation Pixel-Based Fuzzy Clustering Technique

Surface Flaw Detection of Plug Valve Material Using Infrared Thermography and Weighted Local Variation Pixel-Based Fuzzy Clustering Technique

Multisensor Inspection of Laser-Brazed Joints in the Automotive Industry

An automated nondestructive testing system for the surface of pressure pipeline welds

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