Dominik Łuczak

Assistant Professor

Poznan University of Technology

Poland

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Dominik Łuczak is an Assistant Professor at Poznan University of Technology in Poland. His research focuses on data-driven machine fault diagnosis, particularly through the analysis of multisensor vibration data using advanced techniques such as convolutional neural networks and time-frequency image recognition. Recent publications highlight his work on improving diagnostic accuracy for rotary machines and exploring cloud-based solutions for industrial applications.

Articles (14)

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2024

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2024

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2024

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2024

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2024

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2024

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2024

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2024

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2023

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2023

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2023

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2023

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2023

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2021

Collaborators (1)

Stefan Brock

Prof.

Poznan University of Technology

POLAND

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Dominik Łuczak

Research Interests

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Articles (14)

Data-Driven Rotary Machine Fault Diagnosis Using Multisensor Vibration Data with Bandpass Filtering and Convolutional Neural Network for Signal-to-Image Recognition

Data-Driven Machine Fault Diagnosis of Multisensor Vibration Data Using Synchrosqueezed Transform and Time-Frequency Image Recognition with Convolutional Neural Network

Data-Driven Machine Fault Diagnosis of Multisensor Vibration Data Using Synchrosqueezed Transform and Time-Frequency Image Recognition with Convolutional Neural Network

Machine Fault Diagnosis through Vibration Analysis: Continuous Wavelet Transform with Complex Morlet Wavelet and Time-Frequency RGB Image Recognition via Convolutional Neural Network

Machine Fault Diagnosis through Vibration Analysis: Continuous Wavelet Transform with Complex Morlet Wavelet and Time–Frequency RGB Image Recognition via Convolutional Neural Network

Machine Fault Diagnosis through Vibration Analysis: Time Series Conversion to Grayscale and RGB Images for Recognition via Convolutional Neural Networks

Machine Fault Diagnosis through Vibration Analysis: Time Series Conversion to Grayscale and RGB Images for Recognition via Convolutional Neural Networks

Data-Driven Rotary Machine Fault Diagnosis Using Multisensor Vibration Data with Bandpass Filtering and Convolutional Neural Network for Signal-to-Image Recognition

Cloud Based Fault Diagnosis by Convolutional Neural Network as Time–Frequency RGB Image Recognition of Industrial Machine Vibration with Internet of Things Connectivity

Fault Detection and Localisation of a Three-Phase Inverter with Permanent Magnet Synchronous Motor Load Using a Convolutional Neural Network

Mechanical Vibrations Analysis in Direct Drive Using CWT with Complex Morlet Wavelet

Cloud Based Fault Diagnosis by Convolutional Neural Network as Time-Frequency RGB Image Recognition of Industrial Machine Vibration with Internet of Things Connectivity

Fault Detection and Localisation of a Three-Phase Inverter with Permanent Magnet Synchronous Motor Load Using a Convolutional Neural Network

Nonlinear Identification with Constraints in Frequency Domain of Electric Direct Drive with Multi-Resonant Mechanical Part

Collaborators (1)

Stefan Brock

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