Large Noise Components Research Articles

Wavelet DE-noising and Kalman Filtering of MEMS Sensors for Autonomous Latitude Determination

Background: There is a task of autonomous determination of the position latitude of unmoved vehicles. Also, there is another task of the initial value latitude determination as a prepared operation of gimbaled and strap-down inertial navigation systems. For both cases, it is necessary to have an inertial measurement unit (IMU) with triad gyroscopes and triad accelerometers. The output signals of micromechanical gyroscopes and accelerometers have large noise components when using the IMU in the micromachined electromechanical systems (MEMS) technology. Objective: Normally to filter output signals of MEMS sensors, averaging and filtering are used. However, for Kalman filtering, it is necessary to find the exact mathematical model of the sensors and a lot of their initial random characteristics. The study of the possibility of the wavelet transform usage to filter the output signals MEMS accelerometers and gyroscopes for the latitude autonomous determination was conducted in the paper. Method: The wavelet transform approach was used to filter the output signals of MEMS accelerometers and gyroscopes in order to improve the accuracy of the autonomous position latitude determination. The autonomous latitude determination efficiency of IMU based on MEMS gyroscopes and accelerometers has been experimentally confirmed. The projections of the Earth’s angular rate and gravitational acceleration were obtained from the MEMS IMU. After that, the signals of the IMU gyroscopes and accelerometers were filtered, using the wavelet ‘Daubechies’ in decomposition, and averaged. These signals were used in a computational algorithm to determine the latitude. Results: The results showed that Unlike the well-known Kalman filter wavelet de-noising reduced calculation error by almost twice. Conclusion: Wavelet de-noising could be used for output signals filtering of micromechanical gyroscopes and accelerometers for the autonomous determination of position latitude.

Evaluation of cracking due to dynamic temperature fluctuation during plasma spraying process by laser AE method

Evaluation of cracks in the ceramic coatings is very important to insure the reliability of the coating itself and the coated materials, parts and whole systems. Laser acoustic emission (AE) method was applied to enable a non-contact and in-situ monitoring of cracks in the ceramic coating immediately after plasma spraying. In this study, originally developed Continuous Wave Memory (CWM) was used as an AE measurement system to enable the continuous waveform recording during plasma spraying process. AE signals due to cracks could be successfully distinguished from large noise components such as mechanical vibration and laser scattering during the process. The AE events during plasma spraying revealed correlation with the dynamic temperature fluctuation on the surface of the specimen which was generated by the scanning of the plasma torch. Furthermore, the larger temperature fluctuation brought higher active AE signals.

Bayesian Monte Carlo method for seismic predrill prospect assessment

Predrill assessment of the probability that a potential drilling spot holds hydrocarbons (HC) is of vital importance to any oil company. Of equally great value is the assessment of hydrocarbon volumes and distributions. We have developed a methodology that uses seismic data to find the probability that a vertical earth profile contains hydrocarbons and the probability distribution of hydrocarbon volumes. The method combines linearized amplitude variation with offset (AVO) inversion and stochastic rock models and predicts the joint probability distribution of the combined lithology and fluid for the entire profile. We use a Bayesian approach and find the solution of the inverse problem by Markov chain Monte Carlo simulation. The stochastic simulation benefits from a new and tailored simulation algorithm. The computational cost of finding the full joint probability distribution is relatively high and implies that the method is best suited to the investigation of a few potential drilling spots. We applied the method to a case with well control and to two locations in a prospect: one in the center and one at the outskirts. At the well location, we identify the two reservoir zones and obtain volumes that fit the log data. At the prospect, we obtain significant increases in HC probability and volume in the center, whereas there are decreases at the outskirts. Despite the large noise components in the data, the risked volumes in the center changed by a factor of three. We have designed an algorithm for computing the joint distribution of lithology, fluid, and elastic parameters for a full vertical profile. As opposed to what can be done with pointwise approaches, this allows us to calculate success probability and HC volumes.

Extraction of Surface Primitives from Noisy Large-Scale Point-Clouds

Abstract3D shape acquisition of large facilities, such as industrial plants and power plants, has been receiving increasing attention for simulating complicated maintenance and repair tasks. It is widely recognized that model-based planning based on 3D CAD reduces the rework of maintenance tasks to a large extent. The state-of-the-art phase-based laser scanners are very promising to efficiently capture point-clouds of large facilities; because they can produce hundreds of millions point data in several minutes. However, point data captured from the phase-based scanner tend to include large noise components and quite a lot of outliers. In addition, very large memory space is required to generate solid models by processing very large point-clouds. Therefore, it is preferable to develop techniques that can extract surface primitives, such as planes, cylinders, cones, spheres, and tori from very noisy and large-scale point-clouds. This paper introduces a robust streaming smoothing operator for extracting surf...

Standing Waves and Traveling Waves Distinguish Two Circuits in Visual Cortex

The visual cortex represents stimuli through the activity of neuronal populations. We measured the evolution of this activity in space and time by imaging voltage-sensitive dyes in cat area V1. Contrast-reversing stimuli elicit responses that oscillate at twice the stimulus frequency, indicating that signals originate mostly in complex cells. These responses stand clear of the noise, whose amplitude decreases as 1/frequency, and yield high-resolution maps of orientation preference and retinotopy. We first show how these maps are combined to yield the responses to focal, oriented stimuli. We then study the evolution of the oscillating activity in space and time. In the orientation domain, it is a standing wave. In the spatial domain, it is a traveling wave propagating at 0.2-0.5 m/s. These different dynamics indicate a fundamental distinction in the circuits underlying selectivity for position and orientation, two key stimulus attributes.

Enhanced Chemical Classification of Raman Images Using Multiresolution Wavelet Transformation

Multiresolution wavelet transformation (MWT) and block thresholding is used to effectively suppress both background and noise interference while minimally distorting Raman spectral features. The performance of MWT as a spectral pre-processing algorithm is demonstrated using both synthetic spectra and experimental hyper-spectral Raman images with large background and noise components. The results are quantified by comparing correlation coefficients of synthetic spectra with either the same or different backgrounds. The improved chemical imaging performance obtained using MWT is demonstrated by comparing principal component analysis (PCA) channel images and spectral angle mapping (SAM) classified images before and after MWT pre-processing.

Fast flaw reconstruction from 3D eddy current data

An eddy current flaw reconstruction strategy based on the minimization of nonlinear least-squares error functionals is developed for problems with arbitrary specimen, probe and defect shapes. A fast 3D forward solver is created to rapidly predict eddy current signals in the inversion shell. The high speed of the signal evaluation comes by utilizing a reaction data set constructed before performing the inversion by a finite element electromagnetic field simulator. The same pre-calculated reaction data set supports the quick evaluation of sensitivity information, thereby ensuring the efficient implementation of an optimization algorithm. This optimization algorithm combines first-order and stochastic optimization strategies and improves the reliability of the reconstruction significantly if the observed data contain large noise components. Examples with tube specimens are presented for different 3D flaw shapes.

Diagnostics of the quality of MOSFETs

The excess noise behaviour of silicided p-channel MOSFETs is investigated. Due to contact problems, generation-recombination noise spectra are observed. Analysis of the current noise spectra versus the current on a single device, showed that the generation-recombination noise was due to trapping of carriers in the source and drain contacts. An analysis of an L-array is not necessary to distinguish between channel and contact contribution. The classical geometry and current dependence of the noise is no longer valid if the noise in the series resistance is dominant. Large generation-recombination noise components, with the dependence S I ∝ I 4, point to poor device contact quality.

A 2.5D Ferrite Memory Sense Amplifier

In recent years, large-core memories have been developed that use two-wire arrays and are operated in a mode colloquially called 2.5D. The intrinsic noise problem in a 2.5D ferrite memory system is quite severe because the core signals must be sensed off an array line which is also conducting a half-select drive current. The resulting large pedestal and delta noise components, which are generated during the read cycle, severely limit the memory performance. While the delta noise can be strobed out of the sense amplifier, the pedestal noise must be eliminated by circuit techniques. To handle this noise problem, a delay and difference amplification technique is used that permits a short recovery from the pedestal noise and a corresponding increase in memory speed. The implementation of this circuit function is shown, in the final analysis, to be a relatively simple filter used in conjunction with a conventional difference amplifier and detector.

Optimum lead-controller synthesis in feedback-control systems

The phase lead network, shown in figure 1, had demonstrated its ability to improve the relative stability of linear feedback amplifiers long before it was adopted as one of the principal stabilizing networks by those interested in the newer field of servomechanisms. Its wide acceptance was based upon its simple form when dealing with d.c. signals and its ability to produce rate-type signal components without mechanical devices. When used as a synthesis tool in connection with the Nyquist plot (1)* of the loop-transfer characteristics, it allows considerable freedom in shaping the contour to conform to generally acceptable standards of performance to the limited extent with which they can be interpreted on this Nyquist plot. The major drawback of the phase-lead network is its attenuation of the signal components, an attenuation which may be readily appreciated if this network is viewed as a resistance voltage divider under static (d.c.) conditions. This sacrifice is all the more objectionable in applications where higher-frequency noise components are present and the need to maintain the signal-to-noise ratio has virtually eliminated this useful tool from systems whose inputs contain large noise components. A system controlled by a radar signal provides just such a situation.