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Zhao H, Zhang X, Jiang D, Gu J. Research on Rotating Machinery Fault Diagnosis Based on an Improved Eulerian Video Motion Magnification. SENSORS (BASEL, SWITZERLAND) 2023; 23:9582. [PMID: 38067955 PMCID: PMC10798371 DOI: 10.3390/s23239582] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Revised: 11/29/2023] [Accepted: 11/30/2023] [Indexed: 01/22/2024]
Abstract
Rotating machinery condition monitoring and fault diagnosis are important bases for maintenance decisions, as the vibrations generated during operation are usually imperceptible to the naked eye. Eulerian video motion magnification (EVMM) can reveal subtle changes and has been widely used in various fields such as medicine, structural analysis, and fault diagnosis, etc. However, the method has a bound relationship among three parameters: spatial wavelength, amplification factor, and displacement function, so it is necessary to adjust the parameters manually in practical applications. In this paper, on the basis of the original method, an automatic solution of spatial cutoff wavelength based on brightness is proposed. First, an input video is decomposed into image sequences, their RGB color spaces are transformed into HSV color spaces, and the Value channel image representing brightness is selected to automatically calculate the spatial cutoff frequency, and then the spatial cutoff wavelength is determined, and the motion magnification video in the specified frequency band is obtained by substituting it into the original method. Then, a publicly available video is taken as an example for simulation analysis. By comparing the time-brightness curves of the three videos (original video, motion magnification video obtained by the original method and the improved method), it is apparent that the proposed method exhibits the most significant brightness variation. Finally, taking an overhung rotor-bearing test device as the object, five conditions are set, respectively: normal, rotor unbalance, loosened anchor bolt of the bearing seat, compound fault, rotor misalignment. The proposed method is adopted to magnify the motion of the characteristic frequency bands including 1X frequency and 2X frequency. The results show that no obvious displacement is found in normal working conditions, and that the rotor unbalance fault has an overall axial shaking, the bearing seat at the loose place has an obvious vertical displacement, while the compound fault combines the both fault characteristics, and the rotor misalignment fault has an obvious axial displacement of the free-end bearing seat. The method proposed in this paper can automatically obtain the space cutoff wavelength, which solves the problem of defects arising from manually adjusting the parameters in the original method, and provides a new method for rotating machinery fault diagnosis and other fields of application.
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Affiliation(s)
- Haifeng Zhao
- School of Mechanical Science and Engineering, Northeast Petroleum University, Daqing 163318, China; (X.Z.); (D.J.); (J.G.)
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Cataldo A, Roselli I, Fioriti V, Saitta F, Colucci A, Tatì A, Ponzo FC, Ditommaso R, Mennuti C, Marzani A. Advanced Video-Based Processing for Low-Cost Damage Assessment of Buildings under Seismic Loading in Shaking Table Tests. SENSORS (BASEL, SWITZERLAND) 2023; 23:s23115303. [PMID: 37300032 DOI: 10.3390/s23115303] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/07/2023] [Revised: 05/28/2023] [Accepted: 05/31/2023] [Indexed: 06/12/2023]
Abstract
This paper explores the potential of a low-cost, advanced video-based technique for the assessment of structural damage to buildings caused by seismic loading. A low-cost, high-speed video camera was utilized for the motion magnification processing of footage of a two-story reinforced-concrete frame building subjected to shaking table tests. The damage after seismic loading was estimated by analyzing the dynamic behavior (i.e., modal parameters) and the structural deformations of the building in magnified videos. The results using the motion magnification procedure were compared for validation of the method of the damage assessment obtained through analyses of conventional accelerometric sensors and high-precision optical markers tracked using a passive 3D motion capture system. In addition, 3D laser scanning to obtain an accurate survey of the building geometry before and after the seismic tests was carried out. In particular, accelerometric recordings were also processed and analyzed using several stationary and nonstationary signal processing techniques with the aim of analyzing the linear behavior of the undamaged structure and the nonlinear structural behavior during damaging shaking table tests. The proposed procedure based on the analysis of magnified videos provided an accurate estimate of the main modal frequency and the damage location through the analysis of the modal shapes, which were confirmed using advanced analyses of the accelerometric data. Consequently, the main novelty of the study was the highlighting of a simple procedure with high potential for the extraction and analysis of modal parameters, with a special focus on the analysis of the modal shape's curvature, which provides accurate information on the location of the damage in a structure, while using a noncontact and low-cost method.
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Affiliation(s)
- Antonino Cataldo
- ENEA-Italian National Agency for New Technologies, Energy and Sustainable Economic Development, 00196 Rome, Italy
| | - Ivan Roselli
- ENEA-Italian National Agency for New Technologies, Energy and Sustainable Economic Development, 00196 Rome, Italy
| | - Vincenzo Fioriti
- ENEA-Italian National Agency for New Technologies, Energy and Sustainable Economic Development, 00196 Rome, Italy
| | - Fernando Saitta
- ENEA-Italian National Agency for New Technologies, Energy and Sustainable Economic Development, 00196 Rome, Italy
| | - Alessandro Colucci
- ENEA-Italian National Agency for New Technologies, Energy and Sustainable Economic Development, 00196 Rome, Italy
| | - Angelo Tatì
- ENEA-Italian National Agency for New Technologies, Energy and Sustainable Economic Development, 00196 Rome, Italy
| | | | - Rocco Ditommaso
- Scuola di Ingegneria, University of Basilicata, 85100 Potenza, Italy
| | - Canio Mennuti
- INAIL-Istituto Nazionale Assicurazione Contro gli Infortuni sul Lavoro, 00144 Rome, Italy
| | - Alessandro Marzani
- Dipartimento di Ingegneria Civile, Chimica, Ambientale e dei Materiali, University of Bologna, 85100 Potenza, Italy
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Fioriti V, Roselli I, Cataldo A, Forliti S, Colucci A, Baldini M, Picca A. Motion Magnification Applications for the Protection of Italian Cultural Heritage Assets. SENSORS (BASEL, SWITZERLAND) 2022; 22:s22249988. [PMID: 36560358 PMCID: PMC9784119 DOI: 10.3390/s22249988] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Revised: 12/03/2022] [Accepted: 12/16/2022] [Indexed: 06/12/2023]
Abstract
In recent years, the ENEA has introduced a novel methodology based on motion magnification (MM) into the Italian cultural heritage protection and monitoring field. It consists of a digital video signal processing technique able to amplify enormously the tiny movements recorded in conventional videos, while preserving the general topology of the acquired frames. Though the idea of such a methodology is not new, it has recently been provided with an efficient algorithm that makes possible a viable and low-cost magnification. Applications are extremely varied in almost every field of science and technology; however, we are interested in its application to the safeguarding of architectural heritage, a sector of the utmost importance for Italy. As ancient buildings can be extremely sensitive to even minimally invasive instrumentation, most common monitoring sensors can be replaced by contactless tools and methods, such as video-based techniques like MM. It offers many advantages: easy to use, contactless devices, virtual sensors, reusability of the videos, practicality, intuitive graphical results, quantitative analyses capability and low costs. These characteristics are well suited to the monitoring of large ancient monuments; on the other hand, historical sites have peculiarities of their own, requiring careful approaches, proper tools and trained personnel. Moreover, outdoor applications of MM present quite notable difficulties from a practical point of view, e.g., the dimensions of the studied objects, uncontrolled environmental conditions, spurious vibrations, lighting change/instability, etc. Here we give a general idea of the potential of MM and related issues, using some relevant in-the-field case studies in Italian heritage protection.
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HOG-SVM-Based Image Feature Classification Method for Sound Recognition of Power Equipments. ENERGIES 2022. [DOI: 10.3390/en15124449] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
In this paper, a method of power system equipment recognition based on image processing is proposed. Firstly, we carry out wavelet transform on the sound signal of power system equipment collected from the site, and obtain the wavelet coefficient–time diagram. Then, the similarity of wavelet coefficients–time images of different equipment and the same equipment in different periods is calculated, which is used as the basis of the feasibility of image recognition. Finally, we select the HOG features of the image, and classify the selected features using SVM classifier. The method proposed in this paper can accurately identify and classify power system equipment through sound signals, and is different from the traditional method of classifying sound signals directly. The advantages of image processing can be effectively utilized through image processing to avoid the limitations of sound signal processing.
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Sant’Ana WC, Lambert-Torres G, Bonaldi EL, Gama BR, Zacarias TG, Areias IADS, Arantes DDA, Assuncao FDO, Campos MM, Steiner FM. Online Frequency Response Analysis of Electric Machinery through an Active Coupling System Based on Power Electronics. SENSORS 2021; 21:s21238057. [PMID: 34884062 PMCID: PMC8659803 DOI: 10.3390/s21238057] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 11/22/2021] [Accepted: 11/29/2021] [Indexed: 11/16/2022]
Abstract
This paper presents an innovative concept for the online application of Frequency Response Analysis (FRA). FRA is a well known technique that is applied to detect damage in electric machinery. As an offline technique, the machine under testing has to be removed from service-which may cause loss of production. Experimental adaptations of FRA to online operation are usually based on the use of passive high pass coupling-which, ideally, should provide attenuation to the grid voltage, and at the same time, allow the high frequency FRA signals to be injected at the machine. In practice, however, the passive coupling results in a trade-off between the required attenuation and the useful area obtained at the FRA spectra. This paper proposes the use of an active coupling system, based on power electronics, in order to cancel the grid voltage at the terminals of FRA equipment and allow its safe connection to an energized machine. The paper presents the basic concepts of FRA and the issue of online measurements. It also presents basic concepts about power electronics converters and the operating principles of the Modular Multilevel Converter, which enables the generation of an output voltage with low THD, which is important for tracking the grid voltage with minimum error.
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Affiliation(s)
- Wilson Cesar Sant’Ana
- Gnarus Institute, Itajuba 37500-052, MG, Brazil; (G.L.-T.); (E.L.B.); (T.G.Z.); (F.d.O.A.); (M.M.C.)
- Correspondence:
| | - Germano Lambert-Torres
- Gnarus Institute, Itajuba 37500-052, MG, Brazil; (G.L.-T.); (E.L.B.); (T.G.Z.); (F.d.O.A.); (M.M.C.)
| | - Erik Leandro Bonaldi
- Gnarus Institute, Itajuba 37500-052, MG, Brazil; (G.L.-T.); (E.L.B.); (T.G.Z.); (F.d.O.A.); (M.M.C.)
| | - Bruno Reno Gama
- Pro-Reitoria de Pesquisa e Pos-Graduacao (PRPPG), Itajuba Federal University, Itajuba 37500-903, MG, Brazil; (B.R.G.); (I.A.d.S.A.); (D.d.A.A.)
| | - Tiago Goncalves Zacarias
- Gnarus Institute, Itajuba 37500-052, MG, Brazil; (G.L.-T.); (E.L.B.); (T.G.Z.); (F.d.O.A.); (M.M.C.)
| | - Isac Antonio dos Santos Areias
- Pro-Reitoria de Pesquisa e Pos-Graduacao (PRPPG), Itajuba Federal University, Itajuba 37500-903, MG, Brazil; (B.R.G.); (I.A.d.S.A.); (D.d.A.A.)
| | - Daniel de Almeida Arantes
- Pro-Reitoria de Pesquisa e Pos-Graduacao (PRPPG), Itajuba Federal University, Itajuba 37500-903, MG, Brazil; (B.R.G.); (I.A.d.S.A.); (D.d.A.A.)
| | - Frederico de Oliveira Assuncao
- Gnarus Institute, Itajuba 37500-052, MG, Brazil; (G.L.-T.); (E.L.B.); (T.G.Z.); (F.d.O.A.); (M.M.C.)
- Pro-Reitoria de Pesquisa e Pos-Graduacao (PRPPG), Itajuba Federal University, Itajuba 37500-903, MG, Brazil; (B.R.G.); (I.A.d.S.A.); (D.d.A.A.)
| | - Mateus Mendes Campos
- Gnarus Institute, Itajuba 37500-052, MG, Brazil; (G.L.-T.); (E.L.B.); (T.G.Z.); (F.d.O.A.); (M.M.C.)
- Pro-Reitoria de Pesquisa e Pos-Graduacao (PRPPG), Itajuba Federal University, Itajuba 37500-903, MG, Brazil; (B.R.G.); (I.A.d.S.A.); (D.d.A.A.)
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