Average Signal Level Research Articles

A Study of the Short-Term Stability of Energy Characteristics of the Ionospheric Radio Channel

On the basis of the results of long-term measurements on the calibrated mid-latitude highfrequency paths, it is concluded that the processes responsible for the energy characteristics of the high-frequency wave field have inertial properties. Slow (one-hour) absolute variations in the average signal and effective-noise levels in the daytime and the night-time hours do not exceed 2.0 dB. Similar variations in the average signal levels in the twilight hours after removal of the trend, which is caused by the diurnal variation in the ionospheric characteristics, are also below 2.0 dB. Analysis of the time behavior of the relative error-appearance frequency during transmission of the binary sequences with the amplitude manipulation indicates that the above frequency varies in the range 20–75% for an hour if the reception results are averaged for 20 min.

Temperature Dependence of Surface Polar State of SrTiO3 Ceramics Obtained by Piezoresponse Force Microscopy

The existence of polar state on the surface of strontium titanate ceramics was obtained by piezoresponse force microscopy (PFM) in temperature range from 8 to 295 K. This polar state is nonswitchable and relaxes fast at room temperature. This fact is attributed to charge injection from tip, which provoked the formation of oxygen vacancies in subsurface layer. Low temperature dynamics of surface piezoresponse reveals an increasing of PFM contrast at 110–130 K, associated with surface structural phase transition. Temperature dependence of the average level of piezoresponse signal exhibits two peaks due to bulk structural phase transition and coherent quantum state.

Capabilities and limitations of 3D flame measurements based on computed tomography of chemiluminescence

This work investigated the fundamental capabilities and limitations of three-dimensional (3D) combustion measurements based on computed tomography of chemiluminescence (CTC). Experimental, computational, and analytical studies were conducted to map out the fundamental relationship of several parameters important to 3D measurements, including the achievable spatial resolution, the dimension of the measurement volume, and the signal level. The spatial resolution was analyzed both from the Fourier Slice Theorem (FST) and from linear algebraic (LA) considerations, and two limits (the FST and LA limits) were obtained to predict the achievable spatial resolution in tomographic measurements. The achievable signal level and measurement volume were also analyzed under different conditions. These results suggest that it is advantageous to implement tomographic diagnostic such that the projection image fills the camera chip completely. Under such an implementation, the average signal level increases linearly with respect to the size of the measurement volume, and the spatial resolution under the LA limits degrades linearly with respect to the measurement volume if the chemiluminescence emission intensity remains constant. We expect these results to be valuable not only for CTC, but also for tomography diagnostics based on other types of signals because the mathematical formulation in this work is not specific to chemiluminescence signals.

Real-Space x-ray tomographic reconstruction of randomly oriented objects with sparse data frames

Schemes for X-ray imaging single protein molecules using new x-ray sources, like x-ray free electron lasers (XFELs), require processing many frames of data that are obtained by taking temporally short snapshots of identical molecules, each with a random and unknown orientation. Due to the small size of the molecules and short exposure times, average signal levels of much less than 1 photon/pixel/frame are expected, much too low to be processed using standard methods. One approach to process the data is to use statistical methods developed in the EMC algorithm (Loh & Elser, Phys. Rev. E, 2009) which processes the data set as a whole. In this paper we apply this method to a real-space tomographic reconstruction using sparse frames of data (below 10(-2) photons/pixel/frame) obtained by performing x-ray transmission measurements of a low-contrast, randomly-oriented object. This extends the work by Philipp et al. (Optics Express, 2012) to three dimensions and is one step closer to the single molecule reconstruction problem.

Valve Fault Diagnosis in Internal Combustion Engines Using Acoustic Emission and Artificial Neural Network

This paper presents the potential of acoustic emission (AE) technique to detect valve damage in internal combustion engines. The cylinder head of a spark-ignited engine was used as the experimental setup. The effect of three types of valve damage (clearance, semicrack, and notch) on valve leakage was investigated. The experimental results showed that AE is an effective method to detect damage and the type of damage in valves in both of the time and frequency domains. An artificial neural network was trained based on time domain analysis using AE parametric features (AErms, count, absolute AE energy, maximum signal amplitude, and average signal level). The network consisted of five, six, and five nodes in the input, hidden, and output layers, respectively. The results of the trained system showed that the AE technique could be used to identify the type of damage and its location.

Acoustic emission monitoring of wheel sets on moving trains

Recent work in acoustic emission monitoring of wheel sets on moving trains and trams using AE sensors mounted on the rails, has verified the great potential of the method in detecting geometric defects such as flat surfaces on wheel circumference. To achieve optimum results, multi-dimensional AE analysis has been performed, combining Time Driven Data (TDD), Hit Driven Data (HDD) and long waveform streams acquired simultaneously. High-frequency AE sensors proved to be adequately sensitive to flat defects, and the received AE signal level fluctuations were in agreement with the single defect rotational frequency. Combined analysis of all available types of AE data in the time and frequency domain with specialized software reveals the full potential, of the method in providing high accuracy defect detection. The present paper presents the results of AE measurements performed during train passes, with different speeds and directions, where wagons without any wheel defects and ones containing known artificial flats were moving along the rails. AE features, like signal amplitude, duration, energy, and average signal level. of AE signals are being analyzed and compared. Digital signal processing, post-test AE feature extraction and time measurements performed on acquired waveform streams that contain the total continuous acoustic emission during each pass for verification. The results clearly show repeatable indications on trains having defected wheels.

OS1814 エンジンガスケットにおけるリークの検知と挙動評価へのAE法の適用

Applicability of acoustic emission (AE) method to the diagnosis of leaks in an engine gasket was studied. Wide band type AE sensors were attached on the gasket around the cylinder, and nitrogen gas was gradually injected to the cylinder in order to occur leaks. It was demonstrated that continuous AE signals due to leaks are detected at the internal pressure exceeding a certain level. Since the average signal level (ASL) was increased according to the internal pressure, it was found that the amounts of leaks could be evaluated by the ASL. It was also found that the AE counts are preferable to detect the occurrence of leaks because of the feature that the leaks lead to significantly change of the counts. The result of wavelet transform of the leak AE signal indicates that both of the peak frequency and its intensity vary with time so that the time-frequency analysis is useful to evaluate the leak behavior.

AE Signal Fault Recognition based on Improved Lifting Wavelet Denoising and BP Neural Network

For the original acoustic emission signal noise and large amounts of data characteristics, using an improved denoising based on improved lifting Wavelet denoising method. At the same time, combined with BP neural network, is proposed based on the improved lifting wavelet and BP neural network AE signal fault recognition method, the method of AE signal de-noising processing, and then extract the denoising AE waveform signal amplitude and AE parameter signal rise time, duration and average signal level 4 characteristic parameters by the normalized, as network input, through the BP neural network intelligent identification to distinguish between different AE signals. The experimental results show that the method can improve the bearing fault recognition rate of AE signal.

Re-examine tumor-induced alterations in hemodynamic responses of BOLD fMRI: implications in presurgical brain mapping

Blood oxygenation level dependent (BOLD) fMRI is used for presurgical functional mapping of brain tumor patients. Abnormal tumor blood supply may affect hemodynamic responses and BOLD fMRI signals. To perform a multivariate and quantitative investigation of the effect of brain tumors on the hemodynamic responses and its impact on BOLD MRI signal time course, data analysis in order to better understand tumor-induced alterations in hemodynamic responses, and accurately mapping cortical regions in brain tumor patients. BOLD fMRI data from 42 glioma patients who underwent presurgical mapping of the primary motor cortex (PMC) with a block designed finger tapping paradigm were analyzed, retrospectively. Cases were divided into high grade (n = 24) and low grade (n = 18) groups based on pathology. The tumor volume and distance to the activated PMCs were measured. BOLD signal time courses from selected regions of interest (ROIs) in the PMCs of tumor affected and contralateral unaffected hemispheres were obtained from each patient. Tumor-induced changes of BOLD signal intensity and time to peak (TTP) of BOLD signal time courses were analyzed statistically. The BOLD signal intensity and TTP in the tumor-affected PMCs are altered when compared to that of the unaffected hemisphere. The average BOLD signal level is statistically significant lower in the affected PMCs. The average TTP in the affected PMCs is shorter in the high grade group, but longer in the low grade tumor group compared to the contralateral unaffected hemisphere. Degrees of alterations in BOLD signal time courses are related to both the distance to activated foci and tumor volume with the stronger effect in tumor distance to activated PMC. Alterations in BOLD signal time courses are strongly related to the tumor grade, the tumor volume, and the distance to the activated foci. Such alterations may impair accurate mapping of tumor-affected functional areas when using conventional fixed models.

Knee acoustic emission: A potential biomarker for quantitative assessment of joint ageing and degeneration

Based on a single time-point study of 34 healthy and 19 osteoarthritic knees in three different age groups (early, middle and late adulthood), this paper reports the potential of knee acoustic emission as a biomarker to monitor joint ageing and degeneration. Measurements were made of short transient high frequency acoustic emission signals generated by knee joints under stress during repeated sit–stand–sit movements along with joint angle. A statistically significant feature profile was established using a four-phase model of sit–stand–sit movements and two waveform features. The four-phase movement model is derived from joint angle measurement during repeated sit–stand–sit movements, and it consists of the ascending-acceleration and ascending-deceleration phases in the sit-to-stand movement, followed by the descending-acceleration and descending-deceleration phases in the stand-to-sit movement. The two statistically significant waveform features are extracted from AE measurement during repeated sit–stand–sit movements, and they consist of the peak magnitude value and average signal level of each AE burst. In addition to the use of bilateral plots, statistical distributions and 2D colour histograms to visualise the differences and similarities among participants, use of principal component analysis showed not only distinct data clusters corresponding to participating groups, but also an age- and disease-related trajectory progressing from the early adulthood healthy group to the late adulthood healthy group followed by the middle adulthood osteoarthritic group to the late adulthood osteoarthritic group. Furthermore, this trajectory shows increasing areas for each data cluster, with a highly compact cluster for the early adulthood healthy group at one end and a widely spread cluster for the late adulthood osteoarthritic group at the other end. From these results, a strong basis is formed for further development of knee acoustic emission as a convenient and non-invasive biomarker for quantitative assessment of joint ageing and degeneration.

Investigation of the Influence of Reflective Insulation on Indoor Reception in Rural Houses

We investigate the effects of reflective (metallic) insulation on indoor digital television (DTV) signal reception in rural houses. Simulation results indicate that under non-line-of-sight (NLOS) conditions, the presence of reflective insulation may significantly degrade indoor signal reception and cause a large variation of signal level inside a house. To predict the average signal level in domestic indoor sites, a simple empirical model that covers the DTV broadcast frequencies is proposed. Simulations also show that directional antennas may not necessarily improve indoor DTV signal reception.

Evaluation for Expansive Strain of Degraded Mortar with Damage Mechanics Model

In this study, specimens were prepared by mixing expanded polystyrene (EPS) beads with mortar to simulate degradation, and sound specimens include no beads. Measurement of acoustic emission (AE) was performed using an AE transducer. The changes in AE behavior with increase in strain were measured for a uniaxial compression test and a splitting test. The behaviors were investigated in comparison to the change in the damage variable. The AE parameters (rise time, reverberation frequency and average signal level (ASL) ) were evaluated by the average every ten seconds.

Discovering Differences in Acoustic Emission Between Healthy and Osteoarthritic Knees Using a Four-Phase Model of Sit-Stand-Sit Movements

By performing repeated sit-stand-sit movements to create stress on knee joints, short transient bursts of high frequency acoustic emission (AE) released by the knee joints were acquired from two age matched groups consisting of healthy and osteoarthritic (OA) knees, and significant differences between these two groups were discovered from the signal analysis performed. The analysis is based on a four-phase model of sit-stand-sit movements and a two-feature descriptor of AE bursts. The four phases are derived from joint angle measurement during movement, and they consist of the ascending-acceleration and ascending-deceleration phases in the sit-to-stand movement, followed by the descending-acceleration and descending-deceleration phases in the stand-to-sit movement. The two features are extracted from AE measurement during movement, and they consist of the peak magnitude value and average signal level of each AE burst. The proposed analysis method is shown to provide a high sensitivity for differentiation of the two age matched healthy and OA groups, with the most significant difference found to come from the peak magnitude value in the ascending-deceleration phase, clear quantity and strength differences in the image based visual display of their AE feature profiles due to substantially more AE bursts from OA knee joints with higher peak magnitude values and higher average signal levels, and two well separated clusters in the space formed by the principal components. These results provide ample support for further development of AE as a novel tool to facilitate dynamic integrity assessment of knee joints in clinic and home settings.

Recognition of Rub-impact Acoustic Emission Signal Based on Fuzzy Entropy

Fuzzy entropy is used to determine the uncertainty of characteristic parameters of rub-impact acoustic emission (AE) signal in the different rub-impact modes. Average signal level, amplitude, dynamic amplitude range and energies of four nodes reconstruction signals decomposition by wavelet packets are chosen as the characteristic parameters of recognition of AE signal. The membership function of each characteristic parameter belonged to different rub-impact mode based on Gaussian model is obtained from the training samples respectively. Subsequently the fuzzy relation matrix of characteristic parameters and modes is calculated with membership functions. According to different effectiveness in recognizing AE signal by the characteristic parameters, an algorithm based on fuzzy entropy is presented to calculate effectiveness coefficient. The integrated evaluate fuzzy sets is calculated with the new fuzzy relation matrix modified by effectiveness coefficient, and the mode which has the most degree of membership is chosen as the recognition results. The experiments indicate that the integrated fuzzy evaluation is effective in analysis and recognition of AE, and the differences of parameter effectiveness can be used to improve recognition efficiency.

Study on the effect of beam propagation through atmospheric turbulence on standoff nanosecond laser induced breakdown spectroscopy measurements

We report on an experimental study of the effect of atmospheric turbulence on laser induced breakdown spectroscopy (LIBS) measurements. The characteristics of the atmosphere dictate specific performance constraints to this technology. Unlike classical laboratory LIBS systems where the distance to the sample is well known and characterized, LIBS systems working at several tens of meters to the target have specific atmospheric propagation conditions that cause the quality of the LIBS signals to be affected to a significant extent. Using a new LIBS based sensor system fitted with a nanosecond laser emitting at 1064 nm, propagation effects at distances of up to 120 m were investigated. The effects observed include wander and scintillation in the outgoing laser beam and in the return atomic emission signal. Plasmas were formed on aluminium targets. Average signal levels and signal fluctuations are measured so the effect of atmospheric turbulence on LIBS measurements is quantified.

Monitoring Granulation Rate Processes Using Three PAT Tools in a Pilot-Scale Fluidized Bed

The purpose of this research was to analyze and compare the responses of three Process Analytical Technology (PAT) techniques applied simultaneously to monitor a pilot-scale fluidized bed granulation process. Real-time measurements using focused beam reflectance measurement (Lasentec FBRM) and near-infra red spectroscopy (Bruker NIR) were taken by inserting in-line probes into the fluidized bed. Non-intrusive acoustic emission measurements (Physical Acoustic AE) were performed by attaching piezoelectric sensors on the external wall of the fluidized bed. Powder samples were collected at regular intervals during the granulation process and characterized offline using laser diffraction, scanning electron microscopy, stereo-optical microscopy and loss on drying method. PAT data comprising chord length distribution and chord count (from FBRM), absorption spectra (from NIR) and average signal levels and counts (from AE) were compared with the particle properties measured using offline samples. All three PAT techniques were able to detect the three granulation regimes or rate processes (wetting and nucleation, consolidation and growth, breakage) to varying degrees of sensitivity. Being dependent on optical signals, the sensitivities of the FBRM and NIR techniques were susceptible to fouling on probe windows. The AE technique was sensitive to background fluidizing air flows and external interferences. The sensitivity, strengths and weaknesses of the PAT techniques examined may facilitate the selection of suitable PAT tools for process development and scale-up studies.

Filterscopes: Spectral line monitors for long-pulse plasma devices

A photomultiplier (PMT)-based diagnostic system for monitoring spectral lines along multiple viewchords, named the "Filterscope" [R. J. Colchin et al., Rev. Sci. Instrum. 74, 2068 (2003)], is currently in use at the DIII-D, NSTX, and CDX-U fusion plasma devices in the US, and has been installed at the KSTAR device in Korea. This diagnostic has recently been upgraded for application to long-pulse devices, such as KSTAR, EAST in China, and the future ITER in France. A new data acquisition system, employing the PXI instrumentation platform with an embedded Windows microprocessor controller, can simultaneously record up to 72 channels at 100 kHz sampling rates for plasma periods lasting up to 20 min. Based on the average signal level during an adjustable time interval (100 ms in the present DIII-D implementation), the controller digitally adjusts PMT dynode voltage throughout the course of a discharge, thereby maintaining the output signals at a level where they are neither saturated nor dominated by digitizer noise. The new system's ability to accommodate large variations in source strength, discharge to discharge and within a single discharge, has proved particularly valuable during DIII-D operations, since changes between top, bottom, and double-null divertor magnetic configurations lead to large temporal variations in signal brightness.

Highly Linear Power Tracking Doherty Amplifierfor WCDMA Repeater Applications

This letter presents a highly linear power tracking Doherty power amplifier (DPA) for wide-band code division multiple access (WCDMA) repeater system. To achieve maximum linearity without extra linearization circuits, the drain bias voltages of the carrier and peaking amplifiers as well as the gate bias voltage of the peaking amplifier are adaptively controlled using the power tracking method according to average power level of the input signal. For experimental verification, a two-way DPA has been implemented at the WCDMA band of 2.11~2.17 GHz and tested using one-tone, two-tone, and four-carrier WCDMA signals. Two-tone and WCDMA test results show the notable cancellation of the IM3 and IM5 components and the significant improvement in adjacent channel leakage ratio over a wide range of output power levels.

Behavior of Acoustic Emission of Mortar Degraded by Mixing with Expanded Polystyrene Beads

Degraded specimens were prepared by mixing expanded polystyrene (EPS) beads with mortar, and sound specimens include no beads. Measurements of compressional elastic wave velocity (Vp) and acoustic emission (AE) were performed using an AE transducer. The relationships between air content and AE parameters were investigated based on the Vp measurements. The changes in AE behavior with increase in strain were measured by a uniaxial compression test and a splitting test. The AE parameters–rise time, count, frequency, average signal level, and event count rate–were evaluated, on average, every ten seconds. The following results were obtained. (1) In the uniaxial compression test, the volumetric contraction of the degraded specimens was small. This is because large volumetric expansion of the degraded specimens occurs with increase in axial strain. (2) It is difficult to measure the degree of degradation due to increase in porosity using only one AE transducer. The degree of degradation can be evaluated qualitatively using two AE parameters (mean value of count and standard deviation of rise time). (3) It is inferred that the area of observation can be recognized as degraded by increase in cracks when the behavior of average signal level and event count rate for monotonic load is similar to that for cyclic load. (4) It is also inferred that the failure type can be determined as either extensive compression or local tension by long-term observation of reverberation frequency and rise time.

System and method for minimizing DC offset in outputs of audio power amplifiers

An amplifier system receives an input signal and generating therefrom an amplified output signal. The amplifier system is recited as comprising an input stage and an amplifier stage. The input stage is configured to receive the input signal and provide a level-shifted signal that has an average signal level that is shifted in regards a level shift value. The amplifier stage is configured to receive the level-shifted input signal from the input stage and generate therefrom the amplified output signal. The level shift value being selected to minimize a DC offset in the amplified output signal at least when the amplifier system is initially powered on. Since the amplified output signal has a minimal or zero DC offset, the amplifier system avoids generation of undesirable noises when it is initially powered on.