An interactive method for predicting industrial equipment defects

Slimane, Sid Ahmed; Kebdani, Said; Bouchouicha, Benattou; Benguediab, M.; Bahram, Kaddour; Chaib, Mohammed; Sardi, N.

doi:10.1007/s00170-017-1416-5

Cited by 13 publications

(6 citation statements)

References 11 publications

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“…This process allowed us to use more and more the alloys of non-ferrous metals which offer important mechanical characteristics [9,10], it also contributed to reduce the manufacturing costs [11,12], that is why we find so important, to focus our research on how to optimize the operation at low cost, while controlling the parameters, with the best plausible configuration, which will play a crucial role in the maintenance of structures, like the speed of the tool and welding, but also the tool geometry (Fig. 2).…”

Section: Pin Jointmentioning

confidence: 99%

Optimization of Ultimate Tensile Strength with DOE Approach for Application FSW Process in the Aluminum alloys AA6061-T651 & AA7075 -T651

Chaib

Slimane

Slimane³

et al. 2021

Frattura Ed Integrità Strutturale

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As it is imperative to control the materials development processes well, in parallel, it will be necessary to constantly adapt very efficient assembly methods. Friction stir welding makes it much easier for us to fusion the aluminum alloys like AA6061-T651 and AA7075 -T651. But we noted the difficulty of containing its many parameters such as the welding speed, the rotation speed and the type of pin used during the operation to optimize mechanical properties and in particular to obtain high rupture strength with the tensile test. This why in this paper we treat carefully this process in order to define it drastically, by using the design of experiment method which is an original approach that resides in the possibility of interpretation of experimental results with a minimal effort on the experimental level whichever generates the minimization of the necessary number of experiments and allows a saving in time and in financial cost.

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Section: Pin Jointmentioning

confidence: 99%

Optimization of Ultimate Tensile Strength with DOE Approach for Application FSW Process in the Aluminum alloys AA6061-T651 & AA7075 -T651

Chaib

Slimane

Slimane³

et al. 2021

Frattura Ed Integrità Strutturale

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“…Pitting, a common and difficult-to-detect gear failure, is one of the most critical errors to prevent. Undiscovered gear pitting faults can lead to catastrophic machine failures while in use [3], [4][5].…”

Section: Introductionmentioning

confidence: 99%

Experimental study and comparative analysis of pitting fault in spur gear system

Yakeu Happi,

Tchomeni Kouejou,

Anyika Alugongo

2023

J. vibroeng.

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This paper uses a dynamic six-degree-of-freedom model that considers torsional and lateral motions to predict the impact of pitting on vibration parameters in a spur gearbox for various operating speeds and torque loads. The study examines the dynamic characteristics of a gearbox with localized pitting damage on a single gear tooth using theoretical and experimental approaches. The research analyzes the forced vibrations of a single-stage spur gear system with pitting damage, which includes variations in mesh stiffness, damping, and gear error excitation, to identify symptoms of default. The equation of motion for the rotary gearbox system is established using the Lagrangian method in tandem with Short-Time Fourier Transform (STFT) and frequency-RPM map fault diagnosis. During real-time vibration monitoring, vibration signals are captured via accelerometers and processed in both the time and frequency domains using the LabVIEW data acquisition signal processing package to extract diagnostic information. The experimental findings demonstrate how vibration analysis combined with time-frequency processing can recognize machine conditions even in harsh operational conditions. Moreover, the experimental results indicate a significant similarity with the theoretical analysis and validate the effectiveness of the RPM frequency technique-based pitting detection method, which can be an asset in gear fault monitoring.

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“…Infrared image technology quickly and automatically detects mechanical structure defects, improves detection speed and accuracy, and reduces the workload of manual detection. Timely detection and treatment of mechanical structure defects effectively extends the service life of equipment, and reduces maintenance costs and equipment replacement frequency [9][10][11][12][13][14][15][16][17][18]. It is of important research significance and broad application value to process infrared images of mechanical structures after high temperature and detect their defects, because it helps improve safety, efficiency, and reliability of equipment in various fields.…”

Section: Introductionmentioning

confidence: 99%

Mechanical Structure Defect Detection after High Temperature Based on Image Processing

Jiao¹

2023

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Mechanical structures may exhibit defects during long-time high-temperature operation. Infrared image technology quickly and automatically detects mechanical structure defects, improves detection speed and accuracy, and reduces the workload of manual detection. Although high-temperature infrared image processing method has made significant progress in detecting the defects, it still has some shortcomings. Defect features in high-temperature infrared images may not be obvious and are mixed with background information, thus making it difficult to accurately identify and extract them. Therefore, this research studied the detection method of mechanical structure defects after high temperature based on image processing. Transform domain denoising method was used to decompose the transform domains of images, which distinguished signals and noises in the images. Adaptive Contrast Enhancement (ACE) algorithm was used to enhance the images. A feature fusion imaging detection framework for infrared and optical imaging of high-temperature mechanical structures was constructed, which improved the accuracy and reliability of defect detection. Deep neural network was combined with the heuristic fusion section, which further explored deep features in the images and improved the fusion effects. The proposed fusion features were processed using binary tree classification and hierarchical classifier, which accurately identified the abnormal defect regions in the infrared images of high-temperature mechanical structures. The experimental results verified that the proposed method was effective.

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An interactive method for predicting industrial equipment defects

Cited by 13 publications

References 11 publications

Optimization of Ultimate Tensile Strength with DOE Approach for Application FSW Process in the Aluminum alloys AA6061-T651 & AA7075 -T651

Optimization of Ultimate Tensile Strength with DOE Approach for Application FSW Process in the Aluminum alloys AA6061-T651 & AA7075 -T651

Experimental study and comparative analysis of pitting fault in spur gear system

Mechanical Structure Defect Detection after High Temperature Based on Image Processing

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