Review of Automatic Fault Diagnosis Systems Using Audio and Vibration Signals

Henríquez, Patricia; Alonso, Jesús B.; Ferrer, Miguel A.; Travieso, Carlos M.

doi:10.1109/tsmcc.2013.2257752

Cited by 271 publications

(109 citation statements)

References 93 publications

Supporting

Mentioning

109

Contrasting

Order By: Relevance

“…Moreover, we consider GMM [34] as a representative machine learning approach within this research field, besides providing good results in similar experiments [24,25]. The birdsong recognition algorithm has been developed and tested in a Matlab environment with a synthetic dataset in order to validate the accuracy of the system.…”

Section: System Validation: Birdsong Recognition Of Botaurus Stellmentioning

confidence: 99%

An FPGA-Based WASN for Remote Real-Time Monitoring of Endangered Species: A Case Study on the Birdsong Recognition of Botaurus stellaris

Hervás

Alsina-Pagès

Álías

et al. 2017

Sensors

View full text Add to dashboard Cite

Fast environmental variations due to climate change can cause mass decline or even extinctions of species, having a dramatic impact on the future of biodiversity. During the last decade, different approaches have been proposed to track and monitor endangered species, generally based on costly semi-automatic systems that require human supervision adding limitations in coverage and time. However, the recent emergence of Wireless Acoustic Sensor Networks (WASN) has allowed non-intrusive remote monitoring of endangered species in real time through the automatic identification of the sound they emit. In this work, an FPGA-based WASN centralized architecture is proposed and validated on a simulated operation environment. The feasibility of the architecture is evaluated in a case study designed to detect the threatened Botaurus stellaris among other 19 cohabiting birds species in The Parc Natural dels Aiguamolls de l’Empordà, showing an averaged recognition accuracy of 91% over 2h 55’ of representative data. The FPGA-based feature extraction implementation allows the system to process data from 30 acoustic sensors in real time with an affordable cost. Finally, several open questions derived from this research are discussed to be considered for future works.

show abstract

Section: System Validation: Birdsong Recognition Of Botaurus Stellmentioning

confidence: 99%

An FPGA-Based WASN for Remote Real-Time Monitoring of Endangered Species: A Case Study on the Birdsong Recognition of Botaurus stellaris

Hervás

Alsina-Pagès

Álías

et al. 2017

Sensors

View full text Add to dashboard Cite

show abstract

“…The main specialties and contributions lie on three aspects: First, this study gives the dynamic response of a vertebral segment varying due to tissue removal; second, on the base of the theoretical model, the wavelet packet transform (WPT) and the adaptive linear element (ADALINE) are performed to extract the amplitude of one harmonic from the recorded vibration signal to correlate milling condition; finally, since the main challenge in vibration analysis is to reduce the influence of change in milling force, a compensation method for harmonic amplitude estimation is proposed. Wavelet transform has been used in several studies of tool condition monitoring in industrial machining applications [49]- [51]. But to the best of our knowledge, there is not an industrial monitoring method only based on one harmonic of the spindle frequency, and the reason is that such a component cannot characterize the cutting condition (such as tool wear and breakage).…”

Section: Contribution and Organization Of This Papermentioning

confidence: 99%

Vibration-Based Milling Condition Monitoring in Robot-Assisted Spine Surgery

Dai

Xue

Zhang

2015

IEEE/ASME Trans. Mechatron.

View full text Add to dashboard Cite

In order to enhance the safety of the milling operation, we develop a condition monitoring method by means of analyzing the bone vibration signal in robot-assisted spine surgery. Since the behavior of the bone being cut changes with the tissue removal, an analytical method is proposed for modeling of varying bone dynamics, and then, it is proved that the vibration amplitude of the bone indicates its status change. During the real milling process, the vibration signal of the bone is recorded by a noncontact laser displacement sensor, and we only pay attention to the harmonic component whose frequency is an integer times of the spindle frequency of the milling device. The wavelet packet transform and the adaptive linear element are performed to estimate the harmonic amplitude from the signal to correlate milling condition. Considering that the bone vibration also varies with the milling force, the relative magnitude of the force is measured from the wavelet coefficients in low-frequency subband, and subsequently, the estimated harmonic amplitude is compensated to reduce the influence of the force. The robot milling experiments in sheep spines are carried on to verify the effectiveness of the condition monitoring procedure. The experimental results are in substantial accordance with the conclusions from the dynamic model, and thus, the robot can improve the safety of the operation with the proposed method.

show abstract

“…A review of monitoring methods used in power transformers for predictive maintenance has been presented by (Bhattacharya & Dan, 2014) and recent trends of condition monitoring for fault diagnosis of equipment has been reviewed by (Wang et al, 2015). Fuzzy logic based autodiagnosis of OLTCs has been suggested by (Henriquez & Alonso, 2014;Hu, Duan, & Yong, 2015). An acoustic diagnosis system based on Dynamic Time Wrapping (DTW) is discussed in the paper (Landry & Léonard, 2008), where envelopes of testing and reference signals are compared by the testing engineers.…”

Section: Literature Review and Novelty Of Proposed Algorithmmentioning

confidence: 99%