Tsai, Meng-FanMeng-FanTsaiChuang, Shu-ChunShu-ChunChuangWeng, Shih-HsienShih-HsienWengFang, Yin-YingYin-YingFangHu, Wei-ChunWei-ChunHuCHI-FANG CHEN2025-06-172025-06-172025-03-02https://www.scopus.com/record/display.uri?eid=2-s2.0-105003273721&origin=resultslisthttps://scholars.lib.ntu.edu.tw/handle/123456789/730154The expansion of offshore wind power facilities in Taiwan's western waters poses significant threats to marine cetaceans, particularly the finless porpoise (Neophocaena phocaenoides sunameri), which is the most frequently stranded cetacean in the region. Causes of stranding include fishery bycatch, environmental changes, vessel collisions, and marine engineering activities. Traditional visual surveys are ineffective for monitoring this species due to its lack of a prominent dorsal fin, limiting the collection of ecological data and the development of conservation strategies. To overcome these challenges, we developed an automated detection algorithm for high-frequency (HF) cetacean clicks using underwater passive acoustic monitoring (PAM). The first algorithm utilized a time-domain computational approach, applying a high-pass filter (>110 kHz) and a peak detection algorithm to identify click trains, incorporating the Peak Energy Algorithm (Step A). The second algorithm introduced a band-pass filter (60-192 kHz) and combined Step A with a Signal-to-Noise Ratio (SNR) calculation (Step B). Additionally, two filters were integrated into the algorithm, informed by studies conducted in the Bohai Sea, Zhangzhou, and Hainan, China, to refine click event detection. Analysis of 7.5 hours of acoustic data from the Yun-Chang Rise validated the algorithm. The first algorithm achieved a precision ratio (PR) of 78.09% and a false positive ratio (FPR) of 8.06%, with misclassifications attributed to broadband pulses or closely spaced clicks. The second algorithm, incorporating the SNR threshold, improved PR to 96.3% (+17.4%) and reduced FPR to 0.89% (-7.17%). This algorithm enables efficient HF cetacean click detection and can be integrated into firmware for real-time marine operations. It provides a promising solution to the limitations of visual surveys, enhancing acoustic pattern recognition, and supporting improved cetacean monitoring and conservation in Taiwan's waters.Automatic Detection AlgorithmClick detectionFinless porpoiseICI (Inter-Click-Interval)Passive Acoustic Monitoring (PAM)Peak Detection AlgorithmSignal to Noise Ratio[SDGs]SDG7[SDGs]SDG14conference paper10.1109/UT61067.2025.10947373