Advances in passive acoustic detection, localization, and tracking applied to unmanned underwater vehicles

Detection, classification, localization, and tracking (DCLT) of unmanned underwater vehicles (UUVs) in the presence of shipping traffic is a critical task for passive acoustic harbor security systems. In general, vessels can be tracked by their unique acoustic signature due to machinery vibration and cavitation noise. However, cavitation noise of UUVs is considerably quieter than ships and boats, making detection significantly more challenging. In this thesis, I demonstrated that it is possible to passively track a UUV from its highfrequency motor noise using a stationary array in shallow-water experiments with passing boats. First, causes of high frequency tones were determined through direct measurements of two UUVs at a range of speeds. From this analysis, common and dominant features of noise were established: strong tones at the motor’s pulse-width modulated frequency and its harmonics. From the unique acoustic signature of the motor, I derived a high-precision, remote sensing method for estimating propeller rotation rate. In shallow-water UUV field experiments, I demonstrated that detecting a UUV from motor noise, in comparison to broadband noise from the vehicle, reduces false alarms from 45% to 8.4% for 90% true detections. Beamforming on the motor noise, in comparison to broadband noise, improved the bearing accuracy by a factor of 3.2×. Because the signal is also high-frequency, the Doppler effect on motor noise is observable and I demonstrate that range rate can be measured. Furthermore, measuring motor noise was a superior method to the “detection of envelope modulation on noise” algorithm for estimating the propeller rotation rate. Extrapolating multiple measurements from the motor signature is significant because Bearing-Doppler-RPM measurements outperform traditional bearing-Doppler target motion analysis. In the unscented Kalman filter implementation, the tracking solution accuracy for bearing, bearing rate, range, and range rate improved by a factor 2.2×, 15.8×, 3.1×, and 6.2× respectively. These findings are significant for improving UUV localization and tracking, and for informing the next-generation of quiet UUV propulsion systems.

Acoustic Signature Analysis and Sound Source Localization for a Three-Phase AC Induction Motor

As part of the recent electrification of the transportation industry, internal combustion engines are being coupled with or replaced by electric motors. This movement towards an electrified drivetrain poses new noise, vibration, and harshness (NVH) challenges related to electric motors. In this paper, the acoustic signature of an electric motor was analyzed to obtain a better understanding of the sound generated by these motors. This work provides an insight into an acoustic measurement technique that can be used to identify certain frequency bands that significantly contribute to the perceived sound. In the first part, the structural response of the motor was correlated with its acoustic spectra. Furthermore, data from acoustic and structural measurements were used to analyze the order content of the signal and identify critical contributors to the overall perceived sound. The differences between data captured by microphones in different positions around the motor helped to localize components of the overall sound. The results provide some discussion about techniques to decrease the overall sound. The technique described in this paper can be extended to fan-cooled motors that are used in vehicles such as golf carts or as auxiliary motors in electric/hybrid vehicles, as well as across a wide range of industrial applications.

Estimating Ship Underwater Radiated Noise from Onboard Vibrations

The acoustic signature of an Orca-class training vessel (Patrol Craft Training, PCT) Moose from the Royal Canadian Navy (RCN) was measured at the RCN’s Patricia Bay acoustic range on Vancouver Island, British Columbia, Canada. The acoustic range trials included accelerometer measurements on the ship hull and in the engine room and hydrophone measurements at approximately 100 m from the ship. The trials were carried out at the ship speed range of 3 to 20 knots. The test data from all the trial runs was used to derive, evaluate and validate the method of estimating ship underwater radiated noise from onboard vibrations. In the investigation, the runs were split into two sets: a training set and a testing set. A least squares approximation, AQV (average quadratic velocity) SL (source level) correlation, was then applied to the training set data to formulate a transfer function to estimate the underwater radiated noise from onboard vibrations. The AQV is calculated from accelerometer measurements (vibration levels) and SL is obtained from the hydrophone measurements. The third octave frequency band (from 10 Hz to 10 kHz) SL estimations of the testing set runs (using the transfer function and AQV) are within 1 to 3 dB of SL from the hydrophone measurements. This study demonstrates a capability of monitoring underwater radiated noise from ships using only onboard vibration levels which may be of interest for future projects relating to the reduction of shipping noise against a threshold in acoustically sensitive environments.

Acoustic signature reveals blue whales tune life history transitions to oceanographic conditions

1.Matching the timing of life history transitions with ecosystem phenology is critical for the survival of many species, especially those undertaking long-distance migrations. As a result, whether and how migratory populations adjust timing of life history transitions in response to environmental variability are important questions in ecology and conservation. Yet the flexibility and drivers of life history transitions remain largely untested for migratory marine populations, which contend with the unique spatiotemporal dynamics and sensory conditions found in marine ecosystems. 2.Here, using an acoustic signature of blue whales’ regional population-level transition from foraging to breeding migration, we document significant interannual flexibility in the timing of this life history transition (spanning roughly four months) over a continuous six-year study period. 3.We further show that timing of this transition follows the oceanographic phenology of blue whales’ foraging habitat, with a later transition from foraging to breeding migration occurring in years with an earlier onset, later peak, and greater accumulation of biological productivity. 4.These results indicate that blue whales use flexible cues, likely including individual sensing of foraging conditions and long-distance vocal signals from conspecifics, to match timing of this population-level life history transition with interannual oceanographic variability in their vast and dynamic foraging habitat. The use of flexible cues in timing a major life history transition may be key to the persistence of this endangered population facing the pressures of rapid environmental change. 5.Further, these findings extend theoretical understanding of the flexibility and drivers of population-level migration beyond insights derived primarily from group-living and terrestrial migrants, illuminating the drivers and flexibility of a life history transition in a relatively solitary marine migrant.

Numerical Study on Multiple-Blade-Rate Unsteady Propeller Forces for Underwater Vehicles

The unsteady propeller forces of an underwater vehicle were numerically simulated using computational fluid dynamics to investigate the effects of the axial location of the stern planes. A benchmark study was undertaken using a three-bladed propeller; experimental results of the nominal inflow wake profile were analyzed and the unsteady propeller forces were measured. The numerical method was applied to predict the unsteady propeller forces in the SUBOFF model’s wake by varying the axial locations of the stern planes. Several remarks were made on the primary harmonics of the hull’s wakes and blade-rate propeller forces. Introduction The hydroacoustic noise, which matches multiples of the number of propeller blades and its rotational speed, known as “blade-rate (BR) noise,” has been increasingly used to manage hydroacoustics for naval vessels. BR noise can be caused by alternating blade loads owing to fluctuations in the angle of attack of the blades because marine propellers are operated in the nonuniform wake of ships’ hulls. The unsteady blade load produces unsteady propeller forces that are transmitted via the propeller shaft and bearing, thus producing undesirable vibration and noise. Although the resultant BR noise is a common issue for marine vessels, in particular, submarines and other underwater vehicles deployed for undersea defense systems and oceanographic survey systems require strict specifications for the acoustic signature. Therefore, the unsteady propeller forces must be improved for reduced detectability, because the vehicles should be able to operate without being discovered while sonar detection technology continues to improve.

Acoustic signature identification of damage and wear mechanisms in a steel/glass sliding contact

The tribological behavior of a steel/glass ball-on-flat contact was studied by synchronizing the friction measurements with an acoustic emission device and a vision system. The results highlight two distinct friction regimes identified with low and high friction values. Their transition is characterized by a modification of acoustic emission signals. In addition, two main damage and wear mechanisms are identified: the creation and propagation of Hertzian cracks visible on the glass surface and the constitution of an interfacial layer of debris. The different accommodation mechanisms, activated successively or simultaneously, are identified for acoustic emission frequencies between 300 and 700 kHz. Eventually, this approach allows a real-time wear mechanisms identification and gives better insights about acoustic emission signals in relation to tribological systems.

On the Sequence of Unmasked Reflections in Shoebox Concert Halls

Highly appreciated concert halls have their own acoustic signature. These signatures may not often be consciously appraised by general audiences, but they have a significant impact on the appreciation of the hall. Previous research indicates that two of the most important defining elements of a hall’s acoustic signature are (i) the reflection sequence and relative reflection levels at the listener position and (ii) the perceptibility of the reflections based on perception thresholds. Early research from Sir Harold Marshall identified the importance of unmasked early reflections to enhance a concert hall’s acoustic signature. The authors see an opportunity to extend the existing research by further examining the sequence of unmasked reflections. By analysing the cross-sections of three concert halls, this manuscript quantifies potential links between a hall’s architectural form, the resultant skeletal reflections, and the properties of its acoustic signature. While doing so, the manuscript identifies potential masking reflections through visual and analytical assessment of a hall’s skeletal reflections. It is hypothesized that the “rhythm” of the reflection sequence could hold key insights into the hall’s “personality” and acoustic signature. If so, this could present new design tools and considerations for new concert halls and the diagnosis of underperformance in existing halls.

Classification of Bladder Emptying Patterns by LSTM Neural Network Trained Using Acoustic Signatures

(1) Background: Non-invasive uroflowmetry is used in clinical practice for diagnosing lower urinary tract symptoms (LUTS) and the health status of a patient. To establish a smart system for measuring the flowrate during urination without any temporospatial constraints for patients with a urinary disorder, the acoustic signatures from the uroflow of patients being treated for LUTS at a tertiary hospital were utilized. (2) Methods: Uroflowmetry data were collected for construction and verification of a long short-term memory (LSTM) deep-learning algorithm. The initial sample size comprised 34 patients; 27 patients were included in the final analysis. Uroflow sounds generated from flow impacts on a structure were analyzed by loudness and roughness parameters. (3) Results: A similar signal pattern to the clinical urological measurements was observed and applied for health diagnosis. (4) Conclusions: Consistent flowrate values were obtained by applying the uroflow sound samples from the randomly selected patients to the constructed model for validation. The flowrate predicted using the acoustic signature accurately demonstrated actual physical characteristics. This could be used for developing a new smart flowmetry device applicable in everyday life with minimal constraints from settings and enable remote diagnosis of urinary system diseases by objective continuous measurements of bladder emptying function.