Cross-correlation Signal Processing Research Articles

Wavelet Cross-Correlation Signal Processing for Two-Phase Flow Control System in Oil Well Production

An algorithm based on continuous measurement of multiphase flows of oil well production has been designed to improve the efficiency of the technical control of oil production processes in the field. Separation-free, non-contact measurement of multiphase flows of oil well products allows increasing the efficiency of managing oil production processes in the field. Monitoring the current density using radioisotope measuring transducers (RMTs) allows obtaining information about the structure of the flow in the form of the distribution of gas inclusions and the speed of movement of liquid and gas in a two-phase flow. Fluid velocity measurement is based on digital processing of RMT signals, applying a continuous or discrete undecimated wavelet transform to them, and assessing the cross-correlation of wavelet coefficients in individual subspaces of the wavelet decomposition. The cross-correlation coefficients of two RMT signals located at a base distance, calculated in the subspaces of the wavelet decomposition, characterize the speed of movement of gas bubbles of different sizes in a vertical pipe. The measurement assumes that the velocity of the liquid phase of the oil flow in a vertical pipe mainly corresponds to the velocity of small bubbles. This speed should be determined by the maximum cross-correlation of wavelet coefficients in the corresponding decomposition subspace. Computer modeling made it possible to evaluate the characteristics of the algorithm for controlling the speed of liquid movement in the gas–liquid flow of oil well products and determine the mass flow rate of the liquid and the relative value of the gas content. The implementation of the algorithm in a multi-channel version of the device allows monitoring an entire cluster of wells in the field.

Photoacoustic method for measuring the elasticity of polydimethylsiloxane at various mixing ratios

Measuring elasticity without physical contact is challenging, as current methods often require deconstruction of the test sample. This study addresses this challenge by proposing and testing a photoacoustic effect-based method for measuring the elasticity of polydimethylsiloxane (PDMS) at various mixing ratios, which may be applied on the wide range of applications such as biomedical and optical fields. A dual-light laser source of the photoacoustic (PA) system is designed, employing cross-correlation signal processing techniques. The platform systems and a mathematical model for performing PDMS elasticity measurements are constructed. During elasticity detection, photoacoustic signal features, influenced by hardness and shapes, are analyzed using cross-correlation calculations and phase difference detection. Results from phantom tests demonstrate the potential of predicting Young's modulus using the cross-correlation method, aligning with the American Society for Testing and Materials (ASTM) standard samples. However, accuracy may be affected by mixed materials and short tubes. Normalization or calibration of signals is suggested for aligning with Young's coefficient.

Improved Extraction of Second-Order Material Constants for Current Generation Y-Grown La₃Ga5.5Nb0.5O₁₄ (LGN) Crystal.

With higher demand for sensor development, piezoelectric materials with advanced performance and wide availability draw more attention today. Accurate second-order material constants are necessary for modeling and mechanical design of sensors that make use of langanite (La3Ga5.5Nb0.5O14, LGN) crystals. We report here on room temperature LGN bulk acoustic wave (BAW) velocities obtained with reduced uncertainties using ultrasound measurements and taking advantage of the cross correlation signal processing technique, and a full set of LGN material constants extracted from the BAW velocity results. Our results compare favorably with prior results assessed as using a reliable measurement technique, and differ in expected fashion from other results based on techniques that do not address a known weakness in the measurement technique.

Three-dimensional thermophotonic image optimization modalities of truncated correlation photothermal coherence tomography.

Truncated correlation photothermal coherence tomography (TC-PCT) is a pulse-compression, matched-filter-based photothermal diffusion-wave imaging modality with a proven track record in non-destructive evaluation of biomedical, dental, art-object and industrial applications. This is a study of the effect thermal transient truncation plays in the TC-PCT algorithm. It introduces a new phase channel which was coined the name Linear Iso Phase (LIOP) and improves the conventional TC-PCT phase by redevising its matched-filter sampling scheme and removing the effect of circular aliasing artifacts introduced in the frequency-domain-transformed cross-correlation (CC) calculations. A previously introduced computationally simplified adaptation to TC-PCT based on conventional CC signal processing, named enhanced truncated correlation photothermal coherence tomography (eTC-PCT), which does not utilize thermal transient truncation is also investigated: The TC-PCT and eTC-PCT algorithms and the LIOP channel are used to produce three-dimensional reconstructions of a complex multi-layered marquetry art sample and a tooth with a bacterial-induced lesion.

Cross-correlation method for noise measurements of photodetectors used for laser absorption spectroscopy

The paper presents noise measurements of low-resistance photon detectors with a specially developed system. These measurements are significant for many applications. This issue is particularly critical for laser absorption spectroscopy systems to detect trace amounts of gases. In these systems, the detection limit is determined by noise origins, e.g., light source, background, and detector noise and its readout electronics. The use of some specially designed components of the system (low-noise - 3.6 × 10<sub>-19</sub> V<sub>2</sub>/Hz for f >1 kHz) cross-correlation signal processing provides to obtain a measuring floor noise below 10<sub>-18</sub> V<sub>2</sub>/Hz for f > 10 Hz and below 10<sub>-19</sub> V<sub>2</sub>/Hz for f > 1 kHz after ten minutes’ analysis. Measurements of some reference resistors have verified the system’s performance. Finally, the system was also applied to determine the spectral noise density of the II -Type SuperLattice photodetector made of InAs / InAsSb.

Embedded Ceramic-Based Passive Wireless Sensors for Harsh-Environment Applications

Recent advancements in high temperature systems such as gasifiers, molten slag furnaces, super-heated steam turbines, and energy harvesting systems require in-situ temperature monitoring. Conventional temperature sensors such as thermocouples, thermistors, and resistance temperature devices (RTDs) are limited to such applications due to poor reliability. Additionally, these sensors require one end of the device to be maintained in a relatively cold junction which limits the integration with the sophisticated modern high temperature systems. To mitigate these issues, research has been focused on adapting wireless technology for measuring temperature in harsh environments where a conventional temperature sensor cannot be integrated with the system. Initially, research was focused heavily on fiber optics sensor systems, surface acoustic wave (SAW) sensors, laser interferometers, and infra-red sensors. However, these sensor systems have limited lifespan, poor reliability due to reactions taking place at the hot junction, and integration of the sensor with the high temperature system is challenging due to sophisticated design of the furnaces, gasifiers, or turbine blades. In order to mitigate these issues, research has been focused on adapting radio-frequency (RF) technology for high temperature systems. The objective of this work was to design and fabricate inductor-capacitor (LC) resonator based wireless sensors to monitor temperature systems above 500oC.The two-dimensional (planar) LC resonator sensors were designed using the ANSYS Maxwell simulation package. The inductor design was based upon a fifteen-turn coil. The coil geometry was based on a width of 0.15 mm and a spacing of 0.15 mm spacing between the turns. The outer diameter was ~20 mm and the inner diameter was near ~10 mm. The capacitor was based on an interdigitated capacitor (IDC) which could be easily printed onto a ceramic substrate, which would act as the dielectric. The common substrate used in this work was alumina (Al2O3) or yttrium-stabilized zirconia (YSZ). The LC circuit patterns were printed onto alumina or zirconia substrates using inks containing semi-conducting ceramic particles. A few different semi-conducting ceramic compositions were evaluated in this work. One example composition was the La2NiO4 (LN) composition, which displays relatively good high-temperature stability and high electrical conductivity in the range from >40 S/cm at temperatures above 450⁰C. The ceramic powder compositions were synthesized using a conventional solid-state reaction route by mixed the stoichiometric constituents by attrition-milling using zirconia media in ethanol. The resultant slurry was dried and calcined >1000°C for 4 h. X-ray diffraction (XRD) analysis was performed using Panalytical X-ray diffractometer to confirm single phase formation. The circuit patterns were fabricated by using a micro-casting process. Conventional photolithography was used to pattern the photoresist onto the ceramic substrates. The patterned photoresist acted as the molds to deposit the ceramic inks to form the desired LC patterns. The micro-casted patterns were dried and then fired in a muffle furnace to ~1200oC to densify the patterns and bond them to the ceramic substrates. During the firing process, the photoresist would be removed in situ through a basic pyrolysis mechanism. For initial testing in this work, platinum (Pt) interconnects connected to the contact pads were made using Pt ink and further connected to Pt wires to connect to the electrical analysis equipment. Figure 1 shows a magnified optical microscopy picture of a section of the inductor pattern, which shows the level of resolution of the ceramic pattern. The sensors were tested within a high temperature muffle furnace in air. Initial tests used matching sensors placed parallel to each other within the furnace. One sensor was attached using the Pt wires to a signal generator (HP E4433B, USA) to act as the interrogator. The second sensor was hard-wired to a signal analyzer (Tektronix RSA306B, USA). The sensors were characterized at 500 – 1000oC in an ambient atmosphere with an RF signal ranging from 10 – 80 MHz at 2 MHz/sec sweep rate. The sensors showed a sensitivity of 0.2 kHz/oC. Two signal processing methods were implemented in algorithm form (within MATLAB) to estimate the temperature given the frequency response of the sensor. The methods evaluated were the cross-correlation and minimization of absolute error methods. In addition to these two signal processing methods, a split window technique for analyzing the temperature/frequency correlation was used. The cross-correlation signal processing method showed the best fitting for the initial sensor testing. The first set of sensors based on the LN compositions demonstrated sensitivities ~0.2 kHz/oC up to 1000°C. The work will further discuss the results from all sensor compositions and geometries. In addition, the investigation of cyclic stability and repeatability analysis will also be discussed in the presentation. Figure 1

New signal processing approach for structural health monitoring in noisy environments based on impedance measurements

The electro-mechanical impedance (EMI) technique is one of the most promising structural health monitoring (SHM) approaches for material damage detection, which is based on impedance measurements of low-cost piezoelectric transducers. However, numerous practical issues such as signal noise effects caused by environmental conditions can alter signal measurements and limit the capabilities of the EMI technique when the characterization of damage is performed using conventional basic indices. Therefore, this paper proposes a new index for structure feature extraction based on the cross-correlation signal processing technique that can be applied in real noisy environment. The proposed index was evaluated in the frequency domain, where the damage detection is performed directly on the electrical impedance measurements of the transducer, as well as on the time domain, which is based on the wavelet transform applied to the transducer response signal. Experimental tests were carried out on a damaged aluminium structure subject to various signal noise levels. Experimental results revealed that the proposed approach for material feature extraction under noisy environments proved to be effective for detecting damage, thus enhancing the reliability and expanding the applicability of the EMI technique.

Cross-Correlation Signal Processing for Axion and WISP Dark Matter Searches.

The search for dark matter is of fundamental importance to our understanding of the universe. Weakly interacting slim particles (WISPs) such as axions and hidden sector photons are well-motivated candidates for the dark matter. Some of the most sensitive and mature experiments to detect WISPs rely on microwave cavities, and the detection of weak photon signals. It is often suggested to power combine multiple cavities, which creates a host of technical concerns. We outline a scheme based on cross correlation for power combining cavities and increasing the signal-to-noise ratio of a candidate WISP signal.

Comparative evaluation of in situ stress monitoring with Rayleigh waves

The in situ monitoring of stresses provides a crucial input for residual life prognosis and is an integral part of structural health monitoring systems. Stress monitoring is generally achieved by utilising the acoustoelastic effect, which relates the speed of elastic waves in a solid, typically longitudinal and shear waves, to the stress state. A major shortcoming of methods based on the acoustoelastic effect is their poor sensitivity. Another shortcoming of acoustoelastic methods is associated with the rapid attenuation of bulk waves in the propagation medium, requiring the use of dense sensor networks. The purpose of this article is twofold: to demonstrate the application of Rayleigh (guided) waves rather than bulk waves towards stress monitoring based on acoustoelasticity, and to propose a new method for stress monitoring based on the rate of accumulation of the second harmonic of large-amplitude Rayleigh waves. An experimental study is conducted using the cross-correlation signal processing technique to increase the accuracy of determining Rayleigh wave speeds when compared with traditional methods. This demonstrates the feasibility of Rayleigh wave–based acoustoelastic structural health monitoring systems, which could easily be integrated with existing sensor networks. Second harmonic generation is then investigated to demonstrate the sensitivity of higher order harmonics to stress-induced nonlinearities. The outcomes of this study demonstrate that the sensitivity of the new second harmonic generation method is several orders of magnitude greater than the acoustoelastic method, making the proposed method more suitable for development for online stress monitoring of in-service structures.

PSIN: A scalable, Parallel algorithm for Seismic INterferometry of large-N ambient-noise data

Seismic interferometry is a technique for extracting deterministic signals (i.e., ambient-noise Green's functions) from recordings of ambient-noise wavefields through cross-correlation and other related signal processing techniques. The extracted ambient-noise Green's functions can be used in ambient-noise tomography for constructing seismic structure models of the Earth's interior. The amount of calculations involved in the seismic interferometry procedure can be significant, especially for ambient-noise datasets collected by large seismic sensor arrays (i.e., “large-N” data). We present an efficient parallel algorithm, named pSIN (Parallel Seismic INterferometry), for solving seismic interferometry problems on conventional distributed-memory computer clusters. The design of the algorithm is based on a two-dimensional partition of the ambient-noise data recorded by a seismic sensor array. We pay special attention to the balance of the computational load, inter-process communication overhead and memory usage across all MPI processes and we minimize the total number of I/O operations. We have tested the algorithm using a real ambient-noise dataset and obtained a significant amount of savings in processing time. Scaling tests have shown excellent strong scalability from 80 cores to over 2000 cores.

High-resolution optical refractometer based on a long-period grating Michelson interferometer using a cross-correlation signal-processing method

We report a high-resolution optical refractometer based on the long-period grating Michelson interferometer. The interferometer phase shift depends on the refractive index that surrounds the fiber probe. A cross-correlation signal-processing method is used to demodulate the interferometer phase shift. Experimental results show that a resolution of 3×10 −6 refractive index unit (RIU) can be obtained using this cross-correlation signal processing method. In addition, a measurement sensitivity up to 3×10 3 deg/RIU is showed as the surrounding refractive index changing from 1.33 to 1.42. Such high-resolution and low-cost optical refractometers would find more applications in chemical or biochemical sensing fields.

Non-invasive monitoring of Achille's tendon stiffness variations in-vivo using mechanical vibrations

A non-invasive monitoring technique of laser Doppler vibrometer (LDV) is used to find the stiffness of Achilles tendon. It is difficult for an ultrasound to collect the elastographic images of high stiffness areas such as Achilles tendon. Magnetic resonance images (MRI) technique is expensive and requires extensive training of the clinicians for elastographic image processing. This non-invasive technique needs short setup time and a simple physical structure for the data collection. A shaker is used as an excitation source, which generates waves on the tendon surface. This dynamic elastography technique measure wave velocities by an LDV. Achilles tendon is excited from 10 Hz to 1000 Hz using shaker and sensed by the LDV at four positions, which are one cm apart. Cross correlation signal processing is used for finding the time delays of the waves approaching each sensor location. It is found that as the contraction level increases, tendon stiffness increases. A comparison of average and varied stiffness values is shown in Achilles tendon. This technique may assist clinicians in characterizing muscle tone changes due to sport injuries in tendon.

Network analysis of time-lapse microscopy recordings.

Multicellular organisms rely on intercellular communication to regulate important cellular processes critical to life. To further our understanding of those processes there is a need to scrutinize dynamical signaling events and their functions in both cells and organisms. Here, we report a method and provide MATLAB code that analyzes time-lapse microscopy recordings to identify and characterize network structures within large cell populations, such as interconnected neurons. The approach is demonstrated using intracellular calcium (Ca2+) recordings in neural progenitors and cardiac myocytes, but could be applied to a wide variety of biosensors employed in diverse cell types and organisms. In this method, network structures are analyzed by applying cross-correlation signal processing and graph theory to single-cell recordings. The goal of the analysis is to determine if the single cell activity constitutes a network of interconnected cells and to decipher the properties of this network. The method can be applied in many fields of biology in which biosensors are used to monitor signaling events in living cells. Analyzing intercellular communication in cell ensembles can reveal essential network structures that provide important biological insights.

Extrinsic Fabry–Perot interferometric optical fiber hydrogen detection system

We present a new hydrogen sensor system based on the use of an optical fiber extrinsic Fabry-Perot interferometer coated with palladium silver (Pd-Ag) film. The sensing mechanism of such a sensor is based on the mechanical stress that is induced in the Pd-Ag film when it absorbs hydrogen. To obtain the absolute length of the air gap, a modified cross-correlation signal processing method is introduced. Results are presented for a comparison between two Pd-Ag films of different thicknesses. A temperature compensation method based on an optical switch is presented. The sensor is suitable for monitoring concentrations of hydrogen below the lower explosive limit.

Single and multiple sensor identification of avalanche-generated infrasound

The ability to identify snow avalanches as they occur is essential for aggressive avalanche management in transportation corridors and is a fundamental ingredient of avalanche forecasting. Past studies have shown that moving avalanches emit a detectable sub-audible sound signature in the low frequency infrasonic spectrum. Experimental infrasound avalanche monitoring activities conducted in the United States Rocky Mountain West clarify avalanche event identification capabilities of single sensor and multiple sensor systems. Avalanche identification performance of single sensor monitoring systems vary according to ambient noise and signal levels. While single sensor auto correlation signal processing algorithms identify avalanche activity, uncertainties (i.e. false negative identifications and false positive identifications) increase as wind noise increases, and as signal levels decrease due to increasing distance or smaller sources. Monitoring with multiple sensor systems substantially improves avalanche event identification robustness under windy and noisy conditions, while also allowing location estimates of avalanche events to be made. Avalanche event identification and localization capabilities of cross correlation and semblance multiple sensor signal processing algorithms are demonstrated via a sensor array monitoring system. Also demonstrated are avalanche identification and localization capabilities of distributed networks of infrasound monitoring systems. Garnered knowledge is being ported into near real-time prototype systems that will be operated in the Jackson Hole, Wyoming region. Prototype operation will provide performance evaluations in practical highway and recreational area settings. Reliable implementation of infrasound monitoring technology to automatically identify avalanche events requires further innovative solutions to problematic ambient wind noise and interfering signals.

A Wavelet-Based Method for Measuring Particulate Velocity by an Active Electrostatic Sensor

In this paper, a wavelet-based method for measuring the particulate velocities in a duct via an active electrostatic sensor is presented. The main motivation behind this paper is to avoid the known problems which exist with cross-correlation signal processing techniques; i.e., they are sensitive to the distortion of the output waveforms and the variance of the output pulse width from the detecting electrode of the sensor. Instead of cross-correlation techniques, the signal rising edges from the wavelet transforms of the signals of the electric charger and the detecting electrode of the sensor are used to determine the particulate velocity in the duct. As a consequence, the proposed method is robust to the distortion of the output waveforms and the variance of the output pulsewidth, so that it is specifically suitable for measuring the particulate velocity with the spread of velocities within a conveyor. Experimental results confirm the effectiveness of the proposed method and show that the new method can achieve a better measured result than that of the cross-correlation techniques.

"Real time" noise measurements with sensitivity exceeding the standard thermal noise limit

A possibility of "real-time" noise measurements with spectral resolution better than a standard thermal noise limit has been experimentally demonstrated at microwave frequencies. The enhancement in the sensitivity of spectral measurements was achieved due to more efficient use of the signal power via the power recycling technique. By utilizing such a technique, the noise floor of a 9 GHz "real time" measurement system was reduced by 3 dB below the standard thermal noise limit. This makes possible the characterization of intrinsic fluctuations in individual low-noise microwave components, such as ferrite circulators, without the need for cascading them or using the cross-correlation signal processing.

Evaluation of Ultrasound Technique for Solid-Propellant Burning-Rate Response Measurements

The development of an ultrasound technique for precisely measuring the instantaneous regression rate of a solid-rocket propellant under transient conditions is reviewed. The technique is used to measure the burning-rate response of several solid propellants to an oscillatory chamber pressure with a frequency of up to 300 Hz. This measurement is known as the propellant's pressure-coupled response function and is used as an input into rocket stability prediction models. The ultrasound waveforms are analyzed using cross-correlation and other digital signal processing techniques to determine burning rate. Digital methods are less prone to bias and offer greater flexibility than other techniques previously used. The resulting data are corrected for compression effects. The effects of a changing thermal profile on the measurement are discussed. Other phenomena that may corrupt the measurement, such as surface roughness, are also covered. Results of the experiments are compared to data from two other measurement techniques: a T-burner and a magnetic flowmeter.

Interpreting anomalously low voltage noise in two-channel measurement systems.

In this work we 1) analyze and give a theoretical explanation for the anomalously low cross-spectral density of voltage fluctuations that is observed when two thermal noise sources with matched intensities are coupled to the inputs of two-channel phase modulation (PM) or amplitude modulation (AM) noise measurement systems (NMS), 2) empirically evaluate spectral resolutions of different types of measurement systems, and 3) discuss noise measurement techniques involving cross-correlation signal processing. Our work shows that the statistical uncertainty, which sets the ultimate spectral resolution in the thermal noise limited regime, is approximately the same for both systems. However, in practical terms, the non-stationary nature of the noise, the temporal separation of calibration and measurement, and the difficulty of reproducing the calibrations for two measurements make it extremely difficult to resolve noise that is more than 10 dB below the noise floor in a single channel NMS. In a two-channel NMS, however, the calibrations of the two channels are carried out simultaneously, and one can take full advantage of a large number of averages and make reproducible noise measurements with resolution 10 dB below the noise floor of a single channel NMS.

Measurement of particulate velocity under stack-flow conditions

Electrostatic sensing technology in combination with cross-correlation signal processing techniques offers a promising and cost effective solution to the on-line continuous velocity measurement of particles in a stack. This paper presents the principle, design and evaluation of a novel instrumentation system, called `StackFlow 2000', which has recently been developed for the velocity measurement of particles in a stack. Experiments with aloxite, building plaster and icing sugar as test materials were conducted on a 300 mm bore stack-flow test facility over a velocity range of 2.5 to 22 m s-1 for particle-mass concentrations of between 0.1 and 10 mg m-3. The performance of the system was quantified in terms of repeatability, linearity, response time and the lower limit of mass concentration. The accuracy of the system was studied by comparing the measured particle velocity to the air velocity in the duct. Effects of sensor contamination on the measurement and the suitability of the system for a wider range of stack sizes are also included. Results obtained from the test facility have demonstrated that the system is capable of providing highly repeatable velocity readings with nonlinearity no greater than ±1%, and a response time of less than 1 s.