ORCID Profile
0000-0002-4422-7800
Current Organisations
Aarhus University
,
Jordan University of Science and Technology
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Publisher: Elsevier BV
Date: 03-2020
DOI: 10.1016/J.TREE.2019.11.002
Abstract: Often perceived as environmentally benign, 'green' renewable energy technologies have ecological costs that are often overlooked, especially those occurring below the waterline. After briefly discussing the impacts of hydropower on freshwater and marine organisms, we focus this review on the impacts of marine renewable energy devices (MREDs) on underwater marine organisms, particularly offshore wind farms and marine energy converters (e.g., tidal turbines). We consider both cumulative impacts and synergistic interactions with other anthropogenic pressures, using offshore wind farms and the Taiwanese white dolphin (Sousa chinensis taiwanensis) as an ex le. While MREDs undoubtedly can help mitigate climate change, variability in the sensitivity of different species and ecosystems means that rigorous case-by-case assessments are needed to fully comprehend the consequences of MRED use.
Publisher: Hindawi Limited
Date: 04-11-2020
DOI: 10.1155/2020/8843759
Abstract: The fault detection and diagnosis (FDD) along with condition monitoring (CM) and of rotating machinery (RM) have critical importance for early diagnosis to prevent severe damage of infrastructure in industrial environments. Importantly, valuable industrial equipment needs continuous monitoring to enhance the safety, reliability, and availability and to decrease the cost of maintenance of modern industrial systems and applications. However, induction motor (IM) has been extensively used in several industrial processes because it is cheap, reliable, and robust. Rolling bearings are considered to be the main component of IM. Undoubtedly, any failure of this basic component can lead to a serious breakdown of IM and for whole industrial system. Thus, many current methods based on different techniques are employed as a fault prognosis and diagnosis of rolling elements bearing of IM. Moreover, these techniques include signal/image processing, intelligent diagnostics, data fusion, data mining, and expert systems for time and frequency as well as time-frequency domains. Artificial intelligence (AI) techniques have proven their significance in every field of digital technology. Industrial machines, automation, and processes are the net frontiers of AI adaptation. There are quite developed literatures that have been approaching the issues using signals and data processing techniques. However, the key contribution of this work is to present an extensive review of CM and FDD of the IM, especially for rolling elements bearings, based on artificial intelligent (AI) methods. This study highlights the advantages and performance limitations of each method. Finally, challenges and future trends are also highlighted.
Publisher: Acoustical Society of America (ASA)
Date: 03-2021
DOI: 10.1121/10.0003782
Abstract: Male harbor seals (Phoca vitulina) produce stereotypic underwater roars during the mating season. It remains unclear to what extent roar structures vary due to predation levels. Here, seal roars from waters with many (Iceland) and few (Denmark and Sweden) predators were compared. Most Icelandic roars included a long pulse train and a pause. Icelandic roars occurred less frequently, lasted longer (20.3 ± 6.5 s), and were recorded with lower received sound levels (98.3 ± 8.9 dB re 1 μPa root mean square) than roars from Denmark and Sweden. Local extrinsic factors may shape sound production in harbor seals more than previously reported.
No related grants have been discovered for Jakob Tougaard.