Acoustic Diagnostics Applications in the Study of the Oscillation Combustion in Lean Premixed Pre-Evaporation Combustor

The paper presents an experimental investigation of the thermoacoustic oscillations detection in a lean premixed pre-evaporation (LPP) combustor using acoustic signals. The LPP model combustion chamber oscillation combustion test platform was designed and built, and the combustion chamber oscillation combustion conditions of the sound - pressure - thermal parameters contrast experiment was complete. In this experiment, the thermal parameters signal, the acoustic signal and the dynamic pressure signal were collected under the oscillation state and the transition state (ignition condition, stable to the oscillation combustion condition, the oscillation to the stable combustion condition and the flameout condition), and been analyzed comparatively. The experimental result shows that the acoustic signal and pressure signal can reflect the changing of the main frequency in the combustion chamber. That is, at the same inlet air flow, the main frequency of the combustion chamber is proportional to the thermal load, while at the same fuel flow, the main frequency of the combustion chamber does not change with the changing of air flow. In addition, the frequency multiplication of the acoustic signal is more obvious than the pressure signal’s, which show that the interference of the acoustic signal is less, it can clearly reflect the thermoacoustic oscillation in the combustion chamber. In the transition state, the pulse energy of the acoustic signal is obviously increased after ignition. The main frequency energy increases when the working condition begins to change in the stable to the oscillation combustion condition. The main frequency energy decreases when the working condition begins to change in the oscillation to the stable combustion condition. During the flameout condition, the oscillating energy begins to decay from the high frequency region. For the acoustic signal is less disturbed than the pressure signal and it can obtained the same result with the pressure signal in the oscillation state and the transition state, it can replace the pressure signal in the thermoacoustic coupling oscillation analysis of the lean premixed pre-evaporation combustor the lean premixed pre-evaporation combustor.

Development of an Analytical Model for Beams With Two Dimples in Opposing Direction

Structures such as beams and plates can produce unwanted noise and vibration. An emerging technique can reduce noise and vibration without any additional weight or cost. This method focuses on creating two dimples in the same and opposite direction on a beam’s surface where the effect of dimples on its natural frequencies is the problem of interest. The change in the natural frequency between both cases have a different trend. The strategic approach to calculate natural frequencies is as follows: first, a boundary value model (BVM) is developed for a beam with two dimples and subject to various boundary conditions using Hamilton’s Variational Principle. Differential equations describing the motion of each segment are presented. Beam natural frequencies and mode shapes are obtained using a numerical solution of the differential equations. A finite element method (FEM) is used to model the dimpled beam and verify the natural frequencies of the BVM. Both methods are also validated experimentally. The experimental results show a good agreement with the BVM and FEM results. A fixed-fixed beam with two dimples in the same and opposite direction is considered as an example in order to compute its natural frequencies and mode shapes. The effect of dimple locations and angles on the natural frequencies are investigated. The natural frequencies of each case represent a greater sensitivity to change in dimple angle for dimples placed at high modal strain energy regions of a uniform beam.

Acoustic Pressure Fields Generated With a High Frequency Acoustic Levitator

Acoustic levitation is an advantageous particle positioning mechanism currently employed for applications of x-ray spectroscopy and micro-material manufacturing[1], [2]. By levitating a particle using only acoustic pressure waves, one eliminates the need for a container or other physical structure which may contaminate the specimen. Unfortunately, the pressure field generated by a standing acoustic wave is susceptible to periodic instabilities, and a particle that is levitated in this field tends to vibrate. The amplitude of the vibration is largest in the directions that are orthogonal to the axis in which the acoustic wave is generated. Therefore, by generating additional acoustic waves in each orthogonal axis, the vibration amplitude of the levitated particle is significantly reduced. The authors have shown this phenomenon to be true in a previous study[3]. In this paper, the authors explore the details of the pressure field that is generated with the device. A single degree-of-freedom relationship is developed between the acoustic field pressure, the location of the levitated particle, and the mechanical vibration needed to produce levitation. In order to levitate a 100 micrometer diameter water droplet at 55 kilohertz, the calculations suggest that the transducer must achieve an average surface vibration amplitude of at least 6.43 micrometers. This mechanical vibration must produce a root means-squared pressure amplitude of 933 Pascal. Under these conditions, the particle will levitate approximately 0.4 millimeters below a zero pressure node. To validate the use of the single degree of freedom relationships and to explore the acoustic field for one, two, and three-axis levitation, the authors designed and prototyped an acoustic levitator capable of generating standing waves in three orthogonal directions. Using a simple electrical control circuit, the acoustic wave transducers of each axis can be turned on individually or simultaneously. An experiment was developed to measure the pressure of the acoustic field using a microphone. Preliminary pressure magnitude results were measured for one-axis levitation along the center of the vertical axis of the levitator. The measurements suggest that the theoretical development provides a valid first approximation for the pressure magnitude and required mechanical vibration amplitude.

Non-Model-Based Multiple Damage Identification of Beams Under Spatially Dense Vibration Measurement

An effective non-model-based multiple damage identification method for beams by using a continuously scanning laser Doppler vibrometer (CSLDV) system is presented. Velocity response of a beam along a scan line under sinusoidal excitation is measured by the CSLDV system and a spatially dense operating deflection shape (ODS) of the beam along the scan line is obtained by the demodulation method from velocity response. The ODS of an associated undamaged beam is obtained by using a polynomial with a proper order to fit the ODS from the demodulation method. The curvature of an ODS (CODS) is used to identify abnormality induced by multiple damage. A curvature damage index (CDI) using differences between CODSs associated with ODSs that are obtained by the demodulation method and the polynomial fit is proposed to identify multiple damage. An auxiliary CDI obtained by averaging CDIs at different excitation frequencies is defined to further assist identification of multiple damage. Experiments on three beams with three damage on each beam in the form of three small cuts are conducted. Widths and depths of the three damage are varied from 3 mm to 9 mm with an increment of 3 mm and from 5% of thickness reduction to 15% with an increment of 5%, respectively, and their effects on ODSs, CODSs, and CDIs are investigated. Three frequencies close to natural frequencies of the beams and one randomly selected frequency that is not close to any natural frequencies of the beams are used as sinusoidal excitation frequencies. Each damage is successfully identified near regions with consistently high values of CDIs at different excitation frequencies when the damage is not close to a nodal point of an ODS. The three damage on each beam is successfully identified with the auxiliary CDI by obvious peaks at locations of the three damage.

Identification and Ranking of Noise Sources on a Jumbo Drill Machine During Operation

Noise-induced hearing loss (NIHL) is the second most prevalent illness in the mining industry. According to a study conducted by the National Institute for Occupational Safety and Health (NIOSH), in which over 42,000 audiograms from metal/nonmetal miners were analyzed, approximately 70% of miners have hearing impairment as compared to 9% of non-occupationally noise-exposed workers. One of the machines used extensively in metal/nonmetal mines responsible for high noise exposure levels of its operators is the jumbo drill, used to drill holes at the mines for blasting purposes. In this context, NIOSH is conducting research to develop engineering noise controls for jumbo drills that would reduce the prevalence of hearing loss among operators of this equipment. The first step of the noise control development process consists of identifying and ranking dominant noise sources present during operation of the jumbo drill. To this end, a noise study was conducted at NIOSH’s laboratories in which a microphone phased array system was used to identify dominant noise sources, and the transfer path analysis method was used to rank these sources based on their contribution to the operator location. Results showed that the drill string and the drilling mechanism — known as the drifter — are the dominant sound-radiating components in the operation of the jumbo drill.

Sound Source Separation Using Spectrogram Analysis by Neural Networks

The performance of neural networks has been dramatically improved since the method called “deep leaning” was developed around 2006[1][2]. Mainly, neural networks have been used for classification problems such as visual pattern recognition and speech recognition. However, there are not so many studies of sound source separation using neural networks. To apply neural networks to separation problems, separation problems require to be transformed into classification problems. To realize it, we referred to spectrogram analysis by specialists. Specialists can separate each source signal from the spectrogram of mixed signals by focusing on each local area of the spectrogram. In this study, we developed a novel method for sound source separation using spectrogram analysis by neural networks. As a result of the simulation, we successfully separated male and female voices from their mixed sound. The proposed method is superior to conventional methods in separation problems with sound reflection on walls and convolutional mixture which includes the difference of traveling time from a sound source to microphones because the method does not require to identify the mixture process in space.

Participatory Noise Mapping: Harnessing the Potential of Smartphones Through the Development of a Dedicated Citizen-Science Platform

This paper presents results of an ongoing project which aims to develop a purpose-built platform for using smart phones as alternative to sound level meters for citizen-science based environment noise assessment. In order to manage and control environmental noise effectively, the extent of the problem must first be quantified. Across the world, strategic noise maps are used to assess the impact of environmental noise in cities. Traditionally, these maps are developed using predictive techniques, but some authors have advocated the use of noise measurements to develop more reliable and robust noise maps. If adopted correctly, smartphones have the capability to revolutionize the manner in which environmental noise assessments are performed. The development of smartphone technology, and its impact on environmental noise studies, has recently begun to receive attention in the academic literature. Recent research has assessed the capability of existing smartphone applications (apps) to be utilized as an alternative low-cost solution to traditional noise monitoring. Results show that the accuracy of current noise measurement apps varies widely relative to pre-specified reference levels. The high degree of measurement variability associated with such apps renders their robustness questionable in their current state. Further work is required to assess how smartphones with mobile apps may be used in the field and what limitations may be associated with their use. To over come the above issues, this project is developing a platform specifically for citizen science noise assessment. The platform consists of a smartphone app that acquires a sound signal and transfers the data to a server via a web based API for post processing purposes. This then returns key information to the user, as well as logging the data for use in a massive noise mapping study. The structure of the proposed platform maintains a clear separation between client (phone) and server. This approach will allow implementation of future open source client side apps for both Android and iOS operating systems.

Development of an Instrumented Drill String for Measuring Drilling Forces

The National Institute for Occupational Safety and Health (NIOSH) Pittsburgh Mining Research Division (PMRD) conducts a wide variety of mining-related health and safety research. As part of this research, PMRD’s Workplace Health Branch maintains a Noise Control Team tasked with developing noise controls to reduce future incidences of noise-induced hearing loss (NIHL) among the nation’s mining workforce. A noise control project that PMRD is currently investigating is the development of noise controls to reduce the noise emissions from jumbo drills. Operators of jumbo drills are frequently overexposed to noise, putting them at risk of NIHL. A key contributor to the noise at the operator location is the noise radiated from the jumbo drill string, or drill rod. Jumbo drilling is rotary-percussive in nature, and the drill string is mechanically excited by the cutting of the media as well as by a percussive hammer. These excitations travel from the bit/rock interface and from the drifter hammer into the drill string, vibrating the structure and causing it to radiate noise. The development of an instrumented drill string will allow NIOSH to quantify the forces within the drill string during drilling, providing critical information for the development of jumbo drill noise controls.

Structural Acoustic Physics Based Modeling of Curved Composite Shells

Understanding sound wave propagation through a curved shell geometry is essential for a wide variety of underwater applications. The objective of this study was to use physics-based modeling (PBM) to investigate wave propagations through curved shells that are subjected to acoustic excitation. An improved understanding of the absorption and reflection properties of materials, such as fiber-reinforced polymer (FRP) composites, will enhance the design methods for a variety of Navy products such as acoustic sensors, acoustic windows, and unmanned underwater vehicles. The research documented in this report investigates the reflection and transmission coefficients of both flat plates and curved shells for steel and composite materials. Results show that the finite element computational models accurately match analytical calculations, and that the composite material studied in this report has more desirable reflection and absorption properties than steel for typical Navy applications. This research also explores the use of coupled Eulerian-Lagrangian (CEL) and smoothed particle hydrodynamics (SPH) modeling approaches in place of the current, traditional Lagrangian approach. Unfortunately, these approaches were found to be unsuitable for the type of acoustic analyses performed throughout this research. However, results from the traditional Lagrangian approach confirmed the validity of current modeling techniques and allowed for the study of the acoustic properties of various geometries and materials. This can help drive future research on composite material applications and enhance design methods for future Navy products.

Frequency Band Selection Based on a New Indicator: Accuracy Rate

Local defects in rotating machinery give rise to periodic impulses in vibrations. In order to acquire the information of these faults, various diagnostic methods have been proposed in the past decades. Most methods used the squared envelope spectrum (i.e., the spectrum of the squared envelope) as the final diagnostic tool, but different preprocessing steps were used before obtaining the envelope signal. The key problem is to obtain the center frequency and bandwidth of the fault signal, then analyze the envelope (squared envelope spectrum) of the band-pass filtered signal. The framework of accuracy rate method was proposed by means of cross validation of the nearest neighbor classifier in this paper: a) obtain the piecewise signal through original signal segmentation; b) calculate the feature of each piecewise signal; c) then an accuracy rate is calculated based on cross validation of the nearest neighbor classifier; and d) repeat the above steps in different frequency band, then find a frequency band with the maximum accuracy rate. Through this algorithm, we can obtain a fault frequency band, and then we can find out the type of the fault by the spectrum of the squared envelope. At the end of this paper, the proposed method is validated by two examples and compared with the other two diagnostic methods: conventional envelope analysis and Fast kurtogram. Through the comparison of results, the validity and superiority of this method has been proved.