Beamforming Applied to Ultrasound Analysis in Detection of Bearing Defects

The bearings of rotating machinery often fail, leading to unforeseen downtime of large machines in industrial plants. Therefore, condition monitoring can be a powerful tool to aid in the quick identification of these faults and make it possible to plan maintenance before the fault becomes too drastic, reducing downtime and cost. Predictive maintenance is often based on information gathered from accelerometers. However, these sensors are contact-based, making them less attractive for use in an industrial plant and more prone to breakage. In this paper, condition monitoring based on ultrasound is researched, where non-invasive sensors are used to record the noise originating from different defects of the Machinery Fault Simulator. The acoustic data are recorded using a sparse microphone array in a lab environment. The same array was used to record real spatial noise in a fully operational plant which was later added to the acoustic data containing the different defects with a variety of Signal To Noise ratios. In this paper, we compare the classification results of the noisy acoustic data of only one microphone to the beamformed acoustic data. We do this to investigate how beamforming could improve the classification process in an ultrasound condition-monitoring application in a real industrial plant.

Traffic Noise Pollution Assessment in Major RoadJunctions of Imphal City, Manipur (India)

Noise pollution assessment was carried out in selected traffic junctions of Imphal city of Manipur, India. The noise pollution assessment was carried out using noise parameters and indices such as L10, L50, L90, Leq for selected traffic junctions during the different periods of the day, i.e., morning, noon, and evening hours. The study of equivalent noise level (Leq), noise parameters, and various noise indices have enabled the evaluation of the overall traffic noise environment of the city. The traffic noise indices such as traffic noise index (TNI), noise climate (NC), traffic noise pollution level (LNP), noise exposure index (NEI) along with day time (LD), night time (LN) average, and day-night (Ldn) noise levels were assessed for the selected traffic junctions. Moreover, spatial noise mapping was carried out using the geostatistical interpolation technique to evaluate the changes of traffic noise scenarios during the different time zones of the day. The Leq values in few traffic junctions exceeded the required noise standards. The study shows equivalent noise level ranging between 52.2–69.9 dB(A) during the morning (7–10 am), 52.4–69.3 dB(A) during noon (12 noon-2 pm), and 54.6–71.1 dB(A) during the evening (4–7 pm) hours, respectively.

Implementation of a TMS-fMRI system: A primer

Transcranial magnetic stimulation (TMS) is a non-invasive and non-pharmacological intervention, approved for the treatment of individuals diagnosed with treatment-resistant depression. This well-tolerated approach uses magnetic pulses to stimulate specific brain regions and induce changes in brain networks at multiple levels of human functioning. Combining TMS with other neuroimaging techniques, such as functional magnetic resonance imaging (fMRI), offers new insights into brain functioning, and allows to map out the causal alterations brought on by TMS interventions on neural network connectivity and behaviour. However, the implemention of concurrent TMS-fMRI brings on a number of technical challenges that must be overcome to ensure good quality of functional images. The goal of this study was thus to investigate the impact of TMS pulses in an MR-environment on the quality of BRAINO phantom images, in terms of the signal of the images, the temporal fluctuation noise, the spatial noise and the signal to fluctuation noise ratio, at the University of British Columbia (UBC) Neuroimaging facility. The results of our analyses replicated those of previous sites, and showed that the present set-up for concurrent TMS-fMRI ensures minimal noise artefact on functional images obtained through this multimodal approach. This step was a key stepping stone for future clinical trials at UBC.

Contrast adaptation improves spatial integration

The effects of contrast adaptation and contrast area summation were investigated using a contrast discrimination task. The task consisted of a target of variable size, and a pedestal with a fixed base contrast. Discrimination performance was examined for a condition in which the pedestal size was fixed, equal to the largest target size, and for a condition in which the pedestal size matched the target size and thus varied with it. Repeated performance of the task produced rapid within-session improvements for both conditions. For stimuli with a matching size of target and pedestal, the performance improved only for the larger targets, indicating the development of area summation, which was initially absent for these stimuli. However, the improvements were mostly temporary, and were not fully retained between subsequent sessions. The temporary nature of the sensitivity gains implies that they resulted, at least in part, from rapid adaptation to the stimulus contrast. We suggest that adaptation decorrelates and thus reduces the spatial noise generated by a high-contrast pedestal, leading to improved area summation and better contrast sensitivity. A decorrelation model successfully predicted our experimental results.

A dual-tube sampling technique for snowpack studies

<p>The validity of any glaciological paleo proxy used to interpret climate records is based on the level of understanding of their transfer from the atmosphere into the ice sheet and their recording in the snowpack. Large spatial noise in snow properties is observed, as the wind constantly redistributes the deposited snow at the surface routed by the local topography. To increase the signal-to-noise ratio and getting a representative estimate of snow properties with respect to the high spatial variability, a large number of snow profiles is needed. However, the classical way of obtaining profiles via snow-pits is time and energy-consuming, and thus unfavourable for large surface sampling programs. In response, we present a dual-tube technique to sample the upper metre of the snowpack at a variable depth resolution with high efficiency. The developed device is robust and avoids contact with the samples by exhibiting two tubes attached alongside each other in order to (1) contain the snow core sample and (2) to access the bottom of the sample, respectively. We demonstrate the performance of the technique through two case studies in East Antarctica where we analysed the variability of water isotopes at a 100 m and 5 km spatial scales.</p>

ACQUISITION AND PROCESSING CONSIDERATIONS FOR INFRARED IMAGES OF ROTATING TURBINE BLADES

As designers aim to increase efficiency in gas turbines for aircraft propulsion and power generation, spatially-resolved experimental measurements are needed to validate computational models and compare improvement gains of new cooling designs. Infrared (IR) thermography is one such method for obtaining spatially-resolved temperature measurements. As technological advances in thermal detectors enable faster integration times, surface temperature measurements of rotating turbine blades become possible to capture including the smallest features. This paper outlines opportunities enabled by the latest IR detector technologies for capturing spatially-resolved rotating blade temperatures, while also addressing some of the challenges of implementing IR for turbine rigs such as the one in the Steady Thermal Aero Research Turbine (START) Laboratory. This paper documents critical steps in achieving accurate measurements including calibration, integration times, spatial noise, and motion blur. From these results, recommendations are provided for achieving accurate IR measurements collected in a rotating turbine facility to study film cooling.

Speech Intelligibility and Spatial Release From Masking Improvements Using Spatial Noise Reduction Algorithms in Bimodal Cochlear Implant Users

This study investigated the speech intelligibility benefit of using two different spatial noise reduction algorithms in cochlear implant (CI) users who use a hearing aid (HA) on the contralateral side (bimodal CI users). The study controlled for head movements by using head-related impulse responses to simulate a realistic cafeteria scenario and controlled for HA and CI manufacturer differences by using the master hearing aid platform (MHA) to apply both hearing loss compensation and the noise reduction algorithms (beamformers). Ten bimodal CI users with moderate to severe hearing loss contralateral to their CI participated in the study, and data from nine listeners were included in the data analysis. The beamformers evaluated were the adaptive differential microphones (ADM) implemented independently on each side of the listener and the (binaurally implemented) minimum variance distortionless response (MVDR). For frontal speech and stationary noise from either left or right, an improvement (reduction) of the speech reception threshold of 5.4 dB and 5.5 dB was observed using the ADM, and 6.4 dB and 7.0 dB using the MVDR, respectively. As expected, no improvement was observed for either algorithm for colocated speech and noise. In a 20-talker babble noise scenario, the benefit observed was 3.5 dB for ADM and 7.5 dB for MVDR. The binaural MVDR algorithm outperformed the bilaterally applied monaural ADM. These results encourage the use of beamformer algorithms such as the ADM and MVDR by bimodal CI users in everyday life scenarios.