Active noise control on high frequency narrow band dental drill noise: Preliminary results

Dental drills produce a characteristic noise that is uncomfortable for patients and is also known to be harmful to dentists under prolonged exposure. It is therefore desirable to protect the patient and dentist whilst allowing two-way communication. A solution is to use a combination of the three main noise cancellation methods, namely, Passive Noise Control, Adaptive Filtering and Active Noise Control. Dental drill noise occurs at very high frequency ranges in relation to conventional ANC, typically 2kHz to 6kHz and it has a narrow band characteristic due to the direct relation of the noise to the rotational speed of the bearing. This paper presents a design of an experimental rig where first applications of ANC on dental drill noise are executed using the standard filtered reference Least Mean Square (FXLMS) algorithm. The secondary path is kept as simple as possible, due to the high frequency range of interest, and hence is chosen as the space between headphone loudspeaker and error microphone placed in the ear (input of the headphone loudspeaker and the output of the error microphone). A standard headphone loudspeaker is used for the control source and the microphone inside of an “Ear and Cheek Simulator Type 43AG” is used as the error microphone. The secondary path transfer function is obtained and preliminary results of the application of ANC are discussed

Gear wear process monitoring using acoustic signals

Airborne acoustic signals contain valuable information from machines and can be detected remotely for condition monitoring. However, the signal is often seriously contaminated by various noises from the environment as well as nearby machines. This paper presents an acoustic based method of monitoring a two stage helical gearbox, a common power transmission system used in various industries. A single microphone is employed to measure the acoustics of the gearbox under-going a run-to-failure test. To suppress the background noise and interferences from nearby ma-chines a modulation signal bispectrum (MSB) analysis is applied to the signal. It is shown that the analysis allows the meshing frequency components and the associated shaft modulating components to be captured more accurately to set up a clear monitoring trend to indicate the tooth wear of the gears under test. The results demonstrate that acoustic signals in conjunction with efficient signal processing methods provide an effective monitoring of the gear transmission process

Adaptive Noise Reduction Techniques for Airborne Acoustic Sensors

Ground and marine based acoustic arrays are currently employed in a variety of military and civilian applications for the purpose of locating and identifying sources of interest. An airborne acoustic array could perform an identical role, while providing the ability to cover a larger area and pursue a target. In order to implement such a system, steps must be taken to attenuate environmental noise that interferes with the signal of interest. In this thesis, we discuss the noise sources present in an airborne environment, present currently available methods for mitigation of these sources, and propose the use of adaptive noise cancellation techniques for removal of unwanted wind and engine noise. The least mean squares, affine projection, and extended recursive least squares algorithms are tested on recordings made aboard an airplane in-flight, and the results are presented. The algorithms provide upwards of 37dB of noise cancellation, and are able to filter the noise from a chirp with a signal to noise ratio of -20db with minimal mean square error. The experiment demonstrates that adaptive noise cancellation techniques are an effective method of suppressing unwanted acoustic noise in an airborne environment, but due to the complexity of the environment more sophisticated algorithms may be warranted

Low-Noise Energy-Efficient Sensor Interface Circuits

Today, the Internet of Things (IoT) refers to a concept of connecting any devices on network where environmental data around us is collected by sensors and shared across platforms. The IoT devices often have small form factors and limited battery capacity; they call for low-power, low-noise sensor interface circuits to achieve high resolution and long battery life. This dissertation focuses on CMOS sensor interface circuit techniques for a MEMS capacitive pressure sensor, thermopile array, and capacitive microphone. Ambient pressure is measured in the form of capacitance. This work propose two capacitance-to-digital converters (CDC): a dual-slope CDC employs an energy efficient charge subtraction and dual comparator scheme; an incremental zoom-in CDC largely reduces oversampling ratio by using 9b zoom-in SAR, significantly improving conversion energy. An infrared gesture recognition system-on-chip is then proposed. A hand emits infrared radiation, and it forms an image on a thermopile array. The signal is amplified by a low-noise instrumentation chopper amplifier, filtered by a low-power 30Hz LPF to remove out-band noise including the chopper frequency and its harmonics, and digitized by an ADC. Finally, a motion history image based DSP analyzes the waveform to detect specific hand gestures. Lastly, a microphone preamplifier represents one key challenge in enabling voice interfaces, which are expected to play a dominant role in future IoT devices. A newly proposed switched-bias preamplifier uses switched-MOSFET to reduce 1/f noise inherently.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/137061/1/chaseoh_1.pd

A low frequency dual-band operational microphone mimicking the hearing property of Ormia ochracea

This paper introduces a directional MEMS microphone designed for hearing aid applications appropriate to low frequency hearing impairment, inspired by the hearing mechanism of a fly, the female Ormia ochracea. It uses both piezoelectric and capacitive sensing schemes. In order to obtain a high sensitivity at low frequency bands, the presented microphone is designed to have two resonance frequencies below the threshold of low frequency hearing loss at approximately 2 kHz. One is around 500 Hz and the other is slightly above 2 kHz. The novel dual sensing mechanism allows for optimization of the microphone sensitivity at both frequencies, with a maximum open-circuit (excluding pre-amplification) acoustic response captured via differential piezoelectric sensing at approximately – 46 dB (V) ref. 94 dB (SPL) at the resonance frequencies. The corresponding minimum detectable sound pressure level is just below -12 dB. The comb finger capacitive sensing was employed due to a lower electrical response generated from a ground referenced single-ended output by the piezoelectric sensing at the first resonance frequency compared to the second resonance frequency. The capacitive sensing mechanism, connected to a charge amplifier, generates a -28.4 dB (V) ref. 94 dB (SPL) acoustic response when the device is excited at either of the two resonance frequencies. Due to the asymmetric geometry and the 400 µm thick substrate, the device is predicted to perform as a bi-directional microphone below 3 kHz, which is shown by the measured directional polar patterns

A 36 µW 1.1 mm2 reconfigurable analog front-end for cardiovascular and respiratory signals recording

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksThis paper presents a 1.2 V 36 µW reconfigurable analog front-end (R-AFE) as a general-purpose low-cost IC for multiple-mode biomedical signals acquisition. The R-AFE efficiently reuses a reconfigurable preamplifier, a current generator (CG), and a mixed signal processing unit, having an area of 1.1 mm2 per R-AFE while supporting five acquisition modes to record different forms of cardiovascular and respiratory signals. The R-AFE can interface with voltage-, current-, impedance-, and light-sensors and hence can measure electrocardiography (ECG), bio-impedance (BioZ), photoplethysmogram (PPG), galvanic skin response (GSR), and general-purpose analog signals. Thanks to the chopper preamplifier and the low-noise CG utilizing dynamic element matching, the R-AFE mitigates 1/f noise from both the preamplifier and the CG for improved measurement sensitivity. The IC achieves competitive performance compared to the state-of-the-art dedicated readout ICs of ECG, BioZ, GSR, and PPG, but with approximately 1.4×-5.3× smaller chip area per channel.Peer ReviewedPostprint (author's final draft

Feasible pickup from intact ossicular chain with floating piezoelectric microphone

<p>Abstract</p> <p>Objectives</p> <p>Many microphones have been developed to meet with the implantable requirement of totally implantable cochlear implant (TICI). However, a biocompatible one without destroying the intactness of the ossicular chain still remains under investigation. Such an implantable floating piezoelectric microphone (FPM) has been manufactured and shows an efficient electroacoustic performance in vitro test at our lab. We examined whether it pick up sensitively from the intact ossicular chain and postulated whether it be an optimal implantable one.</p> <p>Methods</p> <p>Animal controlled experiment: five adult cats (eight ears) were sacrificed as the model to test the electroacoustic performance of the FPM. Three groups were studied: (1) the experiment group (on malleus): the FPM glued onto the handle of the malleus of the intact ossicular chains; (2) negative control group (in vivo): the FPM only hung into the tympanic cavity; (3) positive control group (Hy-M30): a HiFi commercial microphone placed close to the site of the experiment ear. The testing speaker played pure tones orderly ranged from 0.25 to 8.0 kHz. The FPM inside the ear and the HiFi microphone simultaneously picked up acoustic vibration which recorded as .wav files to analyze.</p> <p>Results</p> <p>The FPM transformed acoustic vibration sensitively and flatly as did the in vitro test across the frequencies above 2.0 kHz, whereas inefficiently below 1.0 kHz for its overloading mass. Although the HiFi microphone presented more efficiently than the FPM did, there was no significant difference at 3.0 kHz and 8.0 kHz.</p> <p>Conclusions</p> <p>It is feasible to develop such an implantable FPM for future TICIs and TIHAs system on condition that the improvement of Micro Electromechanical System and piezoelectric ceramic material technology would be applied to reduce its weight and minimize its size.</p

A system for controlling vocal communication networks

Animal vocalizations serve a wide range of functions including territorial defense, courtship, social cohesion, begging, and vocal learning. Whereas many insights have been gained from observational studies and experiments using auditory stimulation, there is currently no technology available for the selective control of vocal communication in small animal groups. We developed a system for real-time control of vocal interactions among separately housed animals. The system is implemented on a field-programmable gate array (FPGA) and it allows imposing arbitrary communication networks among up to four animals. To minimize undesired transitive sound leakage, we adopted echo attenuation and sound squelching algorithms. In groups of three zebra finches, we restrict vocal communication in circular and in hierarchical networks and thereby mimic complex eavesdropping and middleman situations