acoustical signals
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Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7190
Author(s):  
Zibin Jia ◽  
Xu Zheng ◽  
Quan Zhou ◽  
Zhiyong Hao ◽  
Yi Qiu

This paper proposed a local active control method for the reduction of road noise inside a vehicle cabin. A multichannel simplified hybrid active noise control (sHANC) system was first developed and applied to the rear left seat of a large sport utility vehicle (SUV). The attenuation capability of the sHANC system was investigated through simulations, using reference signals provided by accelerometers on the suspensions and bodywork of the vehicle and microphones on the floor of cabin, respectively. It was shown that compared to the traditional feedforward system, the sHANC system using either vibrational or acoustical reference signals can produce a significant suppression of the narrowband peak noise between 75 and 80 Hz, but the system lost the control capability in a range of 100–500 Hz when the acoustic signals were used as references. To reduce the practical implementation costs while maintaining excellent reduction performance, a modified simplified hybrid ANC (msHANC) system was further proposed, in which combined vibrational and acoustical signals were used as reference signals. The off-line analyses showed that four reference accelerometers can be substituted by ten microphones without compromising attenuation performance, with 3.7 dBA overall noise reduction being achieved. The effect of delays on the reduction performance of msHANC system was also investigated. The result showed that the msHANC system was more sensitive to the delays compared to the sHANC system if using only vibrational reference signals.


2019 ◽  
Vol 27 (1) ◽  
pp. 27-30
Author(s):  
Rafael Menezes ◽  
Georgiana M. Pimentel ◽  
Ricardo S. Rosa ◽  
Alan Loures Ribeiro

AbstractRiparian forests play important roles as ecological corridors and refuge habitat for many bird populations in fragmented landscapes. This report describes the seasonal occurrence of the Lineated Woodpecker (Dryocopus lineatus) in a small riparian fragment of Atlantic Forest, northeastern Brazil. A female was recorded by its visual and acoustical signals from September to October 2014. Similar occurrences were observed in the same months over three consecutive years. Two major hypotheses regarding the woodpecker seasonal occurrence are discussed here: i) the use of the riparian fragment for breeding, evidenced by tree-cavity nests; and ii) fleeing of the bird from its natal habitat due to fire in adjacent sugarcane fields, which commonly are burned in these two months. Such recurrent events suggest that D. lineatus uses the riparian fragment as refuge habitat, highlighting the importance of these environments for bird populations that inhabit fragmented landscapes of the Brazilian Atlantic Forest.


2018 ◽  
Vol 143 (6) ◽  
pp. 3563-3573
Author(s):  
Seyed Ataollah Naghavi ◽  
Helen Czerski
Keyword(s):  

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Wei Cheng ◽  
Zhousuo Zhang ◽  
Jie Zhang ◽  
Jiantao Lu

Acoustical signals from mechanical systems reveal the operating conditions of mechanical components and thus benefit for machinery condition monitoring and fault diagnosis. However, the acoustical signals directly measured by the sensors in essential are the mixed signals of all the sources, and normally it is very difficult to be used for source identification or operating feature extraction. Therefore, this paper studies the acoustical source tracing problem using independent component analysis (ICA) and identifies the sources using correlation analysis: the measured acoustical signals are separated into independent components by independent component analysis method, and thus all the independent information of all the sources is obtained; these independent components are identified based on the prior information of the sources and correlation analysis. Therefore, all the source information contained in the measured acoustical signals can be independently separated and traced, which can provide more purer source information for condition monitoring and fault diagnosis.


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