Search for dissertations about: "artificial neural networks damage detection"

Found 4 swedish dissertations containing the words artificial neural networks damage detection.

  2. 1. Structural Health Monitoring of Bridges : Model-free damage detection method using Machine Learning

    Author : Cláudia Neves; Raid Karoumi; John Leander; Ignacio Gonzalez; Eleni Chatzi; KTH; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Structural Health Monitoring; Machine Learning; Damage detection; Model-free based method; Artificial Neural Networks; Gaussian Process; Cost optimization; Byggvetenskap; Civil and Architectural Engineering;

    Abstract : This is probably the most appropriate time for the development of robust and reliable structural damage detection systems as aging civil engineering structures, such as bridges, are being used past their life expectancy and beyond their original design loads. Often, when a significant damage to the structure is discovered, the deterioration has already progressed far and required repair is substantial. READ MORE

  4. 2. Structural Health Monitoring of Bridges : Data-based damage detection method using Machine Learning

    Author : Ana C. Neves; Raid Karoumi; Elsa Caetano; KTH; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Structural Health Monitoring; damage detection; Machine Learning; data-based methods; Artificial Neural Networks; Value of Information; Structural Engineering and Bridges; Bro- och stålbyggnad;

    Abstract : Civil engineering structures built according to modern codes are designed for a service life of normally more than 100 years. At the same time, there is a growing pressure to keep existing aged structures in service despite the fact that they have reached the original designed lifetime, with bridges being a good example of this. READ MORE

  5. 3. Drill Failure Detection based on Sound using Artificial Intelligence

    Author : Thanh Tran; Jan Thim; Sebastian Bader; Kalle Åström; Mittuniversitetet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Convolutional neural network; machine failure detection; Mel-spectrogram; long short-term memory; sound signal processing;

    Abstract : In industry, it is crucial to be able to detect damage or abnormal behavior in machines. A machine's downtime can be minimized by detecting and repairing faulty components of the machine as early as possible. It is, however, economically inefficient and labor-intensive to detect machine fault sounds manual. READ MORE

  6. 4. Enhancing Machine Failure Detection with Artificial Intelligence and sound Analysis

    Author : Thanh Tran; Jan Lundgren; Sebastian Bader; Domenico Capriglione; Mittuniversitetet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Machine Failure Detection; Machine Learning; Deep Learning; Sound Signal Processing; Audio Augmentation;

    Abstract : The detection of damage or abnormal behavior in machines is critical in industry, as it allows faulty components to be detected and repaired as early as possible, reducing downtime and minimizing operating and personnel costs. However, manual detection of machine fault sounds is economically inefficient and labor-intensive. READ MORE