圈养瓶鼻海豚通讯信号分析及融合分类方法

针对圈养条件下瓶鼻海豚通讯信号（whistle）分类时混叠大量回声定位信号（click）导致分类正确率降低的问题,提出了一种基于机器学习的融合分类方法。分别提取whistle信号的时频分布特征训练随机森林分类器,梅尔时频图特征训练卷积神经网络分类器,在此基础上设计融合判决器对混叠whistle信号进行分类识别。对圈养海豚声信号采集实验数据的分类识别结果表明,融合分类方法具有更好的分类性能,对混叠whistle信号分类正确率大于94%,优于时频分布特征分类器和梅尔时频图特征分类器,能够提高混叠信号的分类能力。      

分形维数海豚哨声信号检测方法

针对海豚哨声信号自动检测的问题,提出一种基于分形维数的自适应阈值海豚哨声信号检测方法。对待检测声信号计算盒分形维数,根据得到的盒分形维数特征值,通过模糊C均值聚类自适应确定检测阈值,实现海豚哨声信号的自动检测。文中对水池录制的海豚声信号进行了数据分析,利用哨声信号盒分形维数对哨声信号段与非信号段进行检测,并与基于谱熵的方法进行对比,获得了较高的检测率以及较低的虚警率,可以适用于海豚哨声信号的自动检测与分割。     

印太瓶鼻海豚(Tursiops aduncus)通讯声信号分类及特征参数的环境差异性分析

通过长期记录室内水池环境下两只印太瓶鼻海豚通讯信号,并与海湾自然环境下同样的两只海豚所发出的通讯信号进行比较分析,从信号类型、声谱特征等方面研究生活环境变化下瓶鼻海豚通讯信号的差异性。结果表明,生活环境的差异,会改变瓶鼻海豚通讯信号。海湾自然环境下,瓶鼻海豚通讯信号以正弦型信号为主;而室内水池环境下,上扫型信号比例明显增多,而正弦型信号减少。两种环境下,瓶鼻海豚通讯信号在持续时间、拐点数、起始频率、结束频率、最小频率、最大频率等存在显著性差异(p<0.05),但信号的频率变化量相近(p=0.29)。结果为提高海豚通讯信号认知和增强海豚生物行为研究提供一定的科学参考,同时也为仿生隐蔽通信提供技术支撑。      

宽吻海豚Click信号的时频滤波检测方法

针对宽吻海豚Click信号检测提出了一种在信号时频图中基于Gabor滤波器的检测方法。该方法首先对声信号进行分段处理,计算每一段信号的时频图;然后设计Gabor滤波器,提取时频图中垂直方向的线条;对Gabor滤波处理后的时频图进行自适应阈值处理,提取时频图中能量较强的区域;最后通过连通域分析确定Click信号的位置.仿真合成不同信噪比的测试信号,本文算法在Click信号和背景噪声平均功率比为15 dB的情况下,Click信号的找全率达到了99%,错误率为0%;对实际采集的声信号进行Click信号检测,找全率为100%。本文方法预期为海豚观测和海豚生物学行为的研究提供一定的技术支持。      

时频特征的海豚发声端点检测方法研究*

为在复杂的海洋环境噪声场中检测出目标海豚的某类声信号,设计了一种基于海豚声学特征的端点检测方法。根据海洋环境中噪声能量大且分布频率范围广,而海豚声音的时频特征具有持续时间短,、频率高且集中,、发声行为持续时间长的特点,将采集到的海洋声音进行分帧,计算单帧信号短时能量、谱质心和谱质心二阶偏移率,当海豚发出声信号时,谱质心和能量相应发生突变,截取发生突变的信号实现端点检测。通过与门限法等其他常见端点检测方法进行对比,结果表明,此方法在低信噪比的海洋环境下对单一海豚的某一类声信号检测准确度更高,同时具有较强的抗干扰能力。     

基于实时主动声定位的快速测频算法

针对爆炸试验中冲击波超压传感器位置定位的问题,采用陆上实时主动声定位系统对爆炸试验中冲击波超压传感器位置进行定位。系统中对主动发出声信号频率为已知特定几种频率之一的单频信号的快速实时频率检测,提出了一种快速频率检测算法。算法充分利用信号频率为已知特定几种频率之一这一特定条件,并结合离散时间傅里叶变换(DTFT)与离散傅里叶变换(DFT)的关系以及帕塞瓦尔定理,得出快速频率检测的表达式。经实验验证和计算分析,算法检测频率精准可靠,计算量比其他快速测频算法小得多,更适用于军事紧急状态下陆上实时主动声定位中主动发声和实时定位条件下的快速测频。     

一种宽吻海豚通讯信号自动分类的方法

针对宽吻海豚通讯信号自动分类提出了一种基于句法模式识别的方法。该方法首先提取海豚通讯信号基频随时间变化的轨迹曲线,然后提取基频变化的基元序列。根据海豚通讯信号分类的标准,归纳出产生各类海豚通讯信号基频基元序列的文法。对未知类别的海豚通讯信号,提取其基频变化的基元序列,根据各类模式的文法对基元序列进行分类,进而实现海豚通讯信号的自动分类。实验结果显示本文方法的分类准确率达到了95%。本文方法预期为海豚生物学行为的声学研究提供一定的技术支持。      

海豚声纳信号的脉冲分解及特征分析

提出一种海豚声纳目标探测脉冲串信号的脉冲分解方法,在此基础上对海豚声纳脉冲信号的特征进行了分析,其中包括脉冲宽度、脉冲间隔以及脉冲的时间分辨率和频率分辨率,并采用耳蜗滤波对海豚声纳脉冲串信号的时频特征进行了分析。分析结果表明,探测目标的过程中,根据目标距离的不同,海豚会自适应调节脉冲信号的发射频率和信号形式。     

混凝土材料声发射信号的频率特征及其与强度参量的相关性试验研究

混凝土材料声发射信号频率特征与强度指标的关系是混凝土材料声发射检测技术的重要基础。通过实验,对声发射信号频率特征与混凝土强度指标的相关关系进行了探讨。研究结果表明,在较低的应力水平上,不同强度等级混凝土声发射信号大都是低频信号。而在较高应力水平时,随着强度等级的增加,声发射信号的优势频率则逐渐升高。     

北极水下声信号跨冰层变化分析

北极海冰阻碍了海水和空气两个空间的信息传输.为获得冰层对水下声信号跨冰层传输的影响,采用三维检波器在北冰洋中心区开展了水下声信号的跨冰层实验.利用水冰界面反射模型和自由冰层Lamb波模型,对水下声信号小角度(小于10°)入射冰层时测量数据进行分析,结果表明:(1)20 Hz～1 kHz声信号入射到光滑冰层时,某些频率声...     

Low frequency narrow-band calls in bottlenose dolphins (Tursiops truncatus): signal properties, function, and conservation implications

Dolphins routinely use sound for social purposes, foraging and navigating. These sounds are most commonly classified as whistles (tonal, frequency modulated, typical frequencies 5-10 kHz) or clicks (impulsed and mostly ultrasonic). However, some low frequency sounds have been documented in several species of dolphins. Low frequency sounds produced by bottlenose dolphins (Tursiops truncatus) were recorded in three locations along the Gulf of Mexico. Sounds were characterized as being tonal with low peak frequencies (mean?=?990 Hz), short duration (mean?=?0.069 s), highly harmonic, and being produced in trains. Sound duration, peak frequency and number of sounds in trains were not significantly different between Mississippi and the two West Florida sites, however, the time interval between sounds within trains in West Florida was significantly shorter than in Mississippi (t?=?-3.001, p?=?0.011). The sounds were significantly correlated with groups engaging in social activity (F=8.323, p=0.005). The peak frequencies of these sounds were below what is normally thought of as the range of good hearing in bottlenose dolphins, and are likely subject to masking by boat noise.     

Who is whistling? Localizing and identifying phonating dolphins in captivity

Acoustic communication through whistles is well developed in dolphins. However, little is known on how dolphins are using whistles because localizing the sound source is not an easy task. In the present study, the hyperbola method was used to localize the sound source using a two-hydrophone array. A combined visual and acoustic method was used to determine the identity of the whistling dolphin. In an aquarium in Mexico City where two adult bottlenose dolphins were housed we recorded 946 whistles during 22 days. We found that a dolphin was located along the calculated hyperbola for 72.9% of the whistles, but only for 60.3% of the whistles could we determine the identity of the whistling dolphin. However, sometimes it was possible to use other cues to identify the whistling dolphin. It could be the animal that performed a behavior named “observation” at the time whistling occurred or, when a whistle was only recorded on one channel, the whistling dolphin could be the animal located closest to the hydrophone that captured the whistle. Using these cues, 15.4% of the whistles were further ascribed to either dolphin to obtain an overall identification efficiency of 75.7%. Our results show that a very simple and inexpensive acoustic setup can lead to a reasonable number of identifications of the captive whistling dolphin: this is the first study to report such a high rate of whistles identified to the free swimming, captive dolphin that produced them. Therefore, we have a data set with which we can investigate how dolphins are using whistles. This method can be applied in other aquaria where a small number of dolphins is housed; though, the actual efficiency of this method will depend on how often dolphins spend time next to each other and on the reverberation conditions of the pool.     

The whistles of Hawaiian spinner dolphins

The characteristics of the whistles of Hawaiian spinner dolphins (Stenella longirostris) are considered by examining concurrently the whistle repertoire (whistle types) and the frequency of occurrence of each whistle type (whistle usage). Whistles were recorded off six islands in the Hawaiian Archipelago. In this study Hawaiian spinner dolphins emitted frequency modulated whistles that often sweep up in frequency (47% of the whistles were upsweeps). The frequency span of the fundamental component was mainly between 2 and 22 kHz (about 94% of the whistles) with an average mid-frequency of 12.9 kHz. The duration of spinner whistles was relatively short, mainly within a span of 0.05 to 1.28 s (about 94% of the whistles) with an average value of 0.49 s. The average maximum frequency of 15.9 kHz obtained by this study is consistent with the body length versus maximum frequency relationship obtained by Wang et al. (1995a) when using spinner dolphin adult body length measurements. When comparing the average values of whistle parameters obtained by this and other studies in the Island of Hawaii, statistically significant differences were found between studies. The reasons for these differences are not obvious. Some possibilities include differences in the upper frequency limit of the recording systems, different spinner groups being recorded, and observer differences in viewing spectrograms. Standardization in recording and analysis procedure is clearly needed.     

中华白海豚和东亚窄脊江豚回声定位信号分析与比较

为了增进珍稀齿鲸物种的了解和保护,对中华白海豚(Sousa chinensis)和东亚窄脊江豚(Neophocaena asiaeorientalis sunmeri)的回声定位信号特性进行了分析和比较.通过船只观测与声学监听的方式对厦门海域中华白海豚和东亚窄脊江豚的回声定位信号进行了调查,并对其声学参数进行了统计和对...     

Performance of a contour-based classification method for whistles of Mediterranean delphinids

Whistles from five delphinid species in the western Mediterranean Sea (Stenella coeruleoalba, Grampus griseus, Delphinus delphis, Tursiops truncatus, Globicephala melas) were taken from GREC sound archives. FFT contours (window size 512, Hanning, sampling frequency 44.1 kHz) were extracted with custom developed Matlab software: 277 samples of striped dolphins (Sc), 158 whistles of Risso’s dolphins (Gg), 120 of common dolphins (Dd), 76 of bottlenose dolphins (Tt), and 66 of pilot whales (Gm) were selected. Seafox software extracted 15 variables from the digitized contours, including: duration, initial, final, maximal and minimal frequency slopes, frequency range, number of frequency extrema, beginning, ending, maximal and minimal frequencies, presence of harmonics. Four of five species were significantly different (Mann-Whitney test) for average durations (respectively 0.73, 0.65, 0.47 and 0.89 s for Sc, Gg, Dd, Gm) while the average duration of bottlenose dolphins was 0.71 s. Frequency ranges (respectively 7.3, 6.3, 4.6, 3.2 and 6.3 kHz) were significantly different for all species pairs, with the exception of bottlenose and Risso’s dolphins. From a global point of view, pilot whale calls were the most distinct, with 43 significant pair-wise tests out of a total of 52, followed by the common dolphins. Risso’s dolphins were closest to other species whistles. A CART classification method achieved a global classification rate of 62.9%.     

Echolocation signals of wild dolphins

Most of our understanding of dolphin echolocation has come from studies of captive dolphins performing various echolocation tasks. Recently, measurements of echolocation signals in the wild have expanded our understanding of the characteristics of these signals in a natural setting. Measuring undistorted dolphin echolocation signals with free swimming dolphins in the field can be a challenging task. A four hydrophone array arranged in a symmetrical star pattern was used to measure the echolocation signals of four species of dolphins in the wild. Echolocation signals of the following dolphins have been measured with the symmetrical star array: white-beaked dolphins in Iceland, Atlantic spotted dolphins in the Bahamas, killer whales in British Columbia, and dusky dolphins in New Zealand. There are many common features in the echolocation signals of the different species. Most of the signals had spectra that were bimodal: two peaks, one at low frequencies and another about an octave higher in frequency. The source level of the sonar transmission varies as a function of 20logR, suggesting a form of time-varying gain but on the transmitting end of the sonar process rather than the receiving end. The results of the field work call into question the issue of whether the signals used by captive dolphins may be shaped by the task they are required to perform rather than what they would do more naturally.     

Whistles of small groups of Sotalia fluviatilis during foraging behavior in southeastern Brazil

Whistle emissions were recorded from small groups of marine tucuxi dolphins (Sotalia fluviatilis) in two beaches located in an important biological reserve in the Cananéia estuary (25 degrees 03'S, 47 degrees 58'W), southeastern Brazil. A total of 17 h of acoustic data was collected when dolphins were engaged in a specific feeding foraging activity. The amount of 3235 whistles was recorded and 40% (n=1294) were analyzed. Seven acoustic whistle parameters were determined: duration (ms), number of inflection points, start and end frequency (kHz), minimum and maximum frequency (kHz), and frequency range (kHz). Whistles with up to four inflection points were found. Whistles with no inflection points and rising frequency corresponded to 85% (n=1104) of all analyzed whistles. Whistle duration varied from 38 to 627 ms (mean=229.6+/-109.9 ms), with the start frequency varying between 1 and 16 kHz (mean=8.16+/-3.0 kHz) and the end frequency between 2 and 18 kHz (mean=14.35+/-3.0 kHz). The importance of this study requires an accurate measurement of the whistles' emissions in an unusual foraging feeding behavior situation on two beaches where several tucuxis, mostly mother-calf pairs, are frequently present. These two beaches are located in a federal and state environment Environmental Protected Area threatened by the progressive increase of tourism.     

Geographic variations in the whistles of spinner dolphins (Stenella longirostris) of the Main Hawai'ian Islands

Geographic variations in the whistles of Hawai'ian spinner dolphins are discussed by comparing 27 spinner dolphin pods recorded in waters off the Islands of Kaua'i, O'ahu, Lana'i, and Hawai'i. Three different behavioral states, the number of dolphins observed in each pod, and ten parameters extracted from each whistle contour were considered by using clustering and discriminant function analyses. The results suggest that spinner dolphin pods in the Main Hawai'ian Islands share characteristics in approximately 48% of their whistles. Spinner dolphin pods had similar whistle parameters regardless of the island, location, and date when they were sampled and the dolphins' behavioral state and pod size. The term "whistle-specific subgroup" (WSS) was used to designate whistle groups with similar whistles parameters (which could have been produced in part by the same dolphins). The emission rate of whistles was higher when spinner dolphins were socializing than when they were traveling or resting, suggesting that whistles are mainly used during close-range interactions. Spinner dolphins also seem to vary whistle duration according to their general behavioral state. Whistle duration and the number of turns and steps of a whistle may be more important in delivering information at the individual level than whistle frequency parameters.     

Discriminating features of echolocation clicks of melon-headed whales (Peponocephala electra), bottlenose dolphins (Tursiops truncatus), and Gray's spinner dolphins (Stenella longirostris longirostris)

Spectral parameters were used to discriminate between echolocation clicks produced by three dolphin species at Palmyra Atoll: melon-headed whales (Peponocephala electra), bottlenose dolphins (Tursiops truncatus) and Gray's spinner dolphins (Stenella longirostris longirostris). Single species acoustic behavior during daytime observations was recorded with a towed hydrophone array sampling at 192 and 480 kHz. Additionally, an autonomous, bottom moored High-frequency Acoustic Recording Package (HARP) collected acoustic data with a sampling rate of 200 kHz. Melon-headed whale echolocation clicks had the lowest peak and center frequencies, spinner dolphins had the highest frequencies and bottlenose dolphins were nested in between these two species. Frequency differences were significant. Temporal parameters were not well suited for classification. Feature differences were enhanced by reducing variability within a set of single clicks by calculating mean spectra for groups of clicks. Median peak frequencies of averaged clicks (group size 50) of melon-headed whales ranged between 24.4 and 29.7 kHz, of bottlenose dolphins between 26.7 and 36.7 kHz, and of spinner dolphins between 33.8 and 36.0 kHz. Discriminant function analysis showed the ability to correctly discriminate between 93% of melon-headed whales, 75% of spinner dolphins and 54% of bottlenose dolphins.