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Abstract

The present work focuses on a first study for a piezoelectric harvesting system, finalized to the obtaining of electrical energy from the kinetic energy of rainy precipitation, a renewable energy source not really considered until now. The system, after the realization, can be collocated on the roof of an house, configuring a “Piezo Roof Harvesting System”. After presenting a state of art of the harvesting systems from environmental energy, linked to vibrations, using piezoelectric structures, and of piezoelectric harvesting systems functioning with rain, the authors propose an analysis of the fundamental features of rainy precipitations for the definition of the harvesting system. Then, four key patterns for the realization of a piezoelectric energy harvesting system are discussed and analysed, arriving to the choice of a cantilever beam scheme, in which the piezoelectric material works in 31 mode. An electro-mechanical model for the simulation of performance of the unit for the energetic conversion, composed of three blocks, is proposed. The model is used for a simulation campaign to perform the final choice of the more suitable piezoelectric unit, available on the market, which will be adopted for the realization of the “Piezo Roof Harvesting System”.

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Authors and Affiliations

Romeo di Leo
1
Massimo Viscardi
1
Francesco Paolo Tuccinardi
2
Michele Visone
3

  1. Department of Industrial Engineering – Aerospace section, University of Naples “Federico II”, Italy
  2. Promete S.r.l., Naples, Italy
  3. Blue Design S.r.l., Naples, Italy
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Abstract

The paper presents the novel concept of the magnetoelectric sensor constructed using the amorphous glass ribbon. Its output characteristics (voltage pattern), conditions of work and experimental results are presented. The novel construction allows for minimizing the demagnetizing field in the core of the sensor and linearization of the characteristics between the magnetic field and obtained voltage. Conducted experiments were aimed at determining the sensor operation in the presence of the constant magnetic field (HDC). The main concern of the tests was to verify the linear dependency between the HDC value and the amplitude of the output voltage. Next, the computer model representing the sensor behavior in the constant magnetic field is described. The model implements the parameter identification task based on the regression algorithms. The presented work shows that the proposed device can be used to measure the weak magnetic field and the dependency between the output signal amplitudes and the constant component in the measured magnetic field is approximately linear. This enables measurements of even weak fields.
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Authors and Affiliations

Karol Kuczynski
1
ORCID: ORCID
Piotr Bilski
1
ORCID: ORCID
Adrian Bilski
2
ORCID: ORCID
Jerzy Szymanski
3
ORCID: ORCID

  1. Warsaw University of Technology, Faculty of Electronics and Information Technology, Institute of Radioelectronics and Multimedia Technology, Poland
  2. Warsaw University of Life Sciences, Poland
  3. Kazimierz Pulaski University of Technology and Humanities in Radom, Faculty of Transport, Electrical Engineering and Computer Science, Poland
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Abstract

This study aims to evaluate the effectiveness of machine learning (ML) models in predicting concrete damage using electromechanical impedance (EMI) data. From numerous experimental evidence, the damaged mortar sample with surface-mounted piezoelectric (PZT) material connected to the EMI response was assessed. This work involved the different ML models to identify the accurate model for concrete damage detection using EMI data. Each model was evaluated with evaluation metrics with the prediction/true class and each class was classified into three levels for testing and trained data. Experimental findings indicate that as damage to the structure increases, the responsiveness of PZT decreases. Therefore, we examined the ability of ML models trained on existing experimental data to predict concrete damage using the EMI data. The current work successfully identified the approximately close ML models for predicting damage detection in mortar samples. The proposed ML models not only streamline the identification of key input parameters with models but also offer cost-saving benefits by reducing the need for multiple trials in experiments. Lastly, the results demonstrate the capability of the model to produce precise predictions.
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Authors and Affiliations

Asraar Anjum
1
Meftah Hrairi
1
ORCID: ORCID
Abdul Aabid
2
ORCID: ORCID
Norfazrina Yatim
1
ORCID: ORCID
Maisarah Ali
3

  1. Department of Mechanical and Aerospace Engineering, Faculty of Engineering, International Islamic University Malaysia,P.O. Box 10, 50728, Kuala Lumpur, Malaysia
  2. Department of Engineering Management, College of Engineering, Prince Sultan University, PO BOX 66833, Riyadh 11586, Saudi Arabia
  3. Department of Civil Engineering, Faculty of Engineering, International Islamic University Malaysia, P.O. Box 10, 50728, Kuala Lumpur, Malaysia
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Abstract

The paper presents the analysis of the magnetic sensor’s applicability to the energy harvesting operations. The general scheme and technical advancement of the energy extraction from the electric vehicle (such as a tram or a train) is presented. The proposed methodology of applying the magnetic sensor to the energy harvesting is provided. The experimental scheme for the sensor characteristics and measurement results is discussed. Conclusions and future prospects regarding the practical implementation of the energy harvesting system are provided.

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Authors and Affiliations

Karol Kuczynski
ORCID: ORCID
Adrian Bilski
ORCID: ORCID
Piotr Bilski
ORCID: ORCID
Jerzy Szymanski
ORCID: ORCID

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