Time Delay Of Signal Research Articles

Location Method of Buried Polyethylene Gas Pipeline Based on Acoustic Signal Ellipse Method

This study proposes a buried PE gas pipeline positioning method based on the elliptical method of an acoustic signal analysis. The cross-correlation time delay positioning technology is combined with the elliptical equation, forming an effective mechanism for pipeline depth positioning. First, a dual-tree complex wavelet transform is employed to denoise the collected signals, enhancing the quality and accuracy of the data. Subsequently, the cross-correlation function is utilized to extract the delay times between the signals. The obtained delay times are then substituted into the elliptical equation to calculate the depth of the buried PE pipeline. Based on this theoretical framework, a simulation model is established in COMSOL, and positioning simulation analyses are conducted under three different conditions: pipeline depth, relative sensor positions, and distances between sensors and excitation points. The simulation results indicate that a clear correlation exists between the signal delay time and the pipeline position, with simulation errors controlled within 5%, thus validating the theoretical feasibility of the method. To further assess the effectiveness of this approach, an experimental testing system is constructed. The experimental study was carried out under four different conditions: pipeline burial depth, relative sensor positions, distances between sensors and excitation points, and excitation frequencies. The experimental results demonstrate that these factors significantly affect the pipeline depth positioning. The comparison results show that the method has a high accuracy in depth positioning, with experimental errors controlled within 10%. This study proves that accurate positioning of pipeline depth could be achieved by substituting signal delay times into the elliptical equation, thereby validating the method’s feasibility in practical applications. The proposed method effectively addressed the shortcomings of existing pipeline depth positioning technologies, providing important theoretical support and a practical reference for future pipeline positioning research.

Ultralight dark matter explanation of NANOGrav observations

The angular correlation of pulsar residuals observed by NANOGrav and other pulsar timing array collaborations show evidence in support of the Hellings-Downs correlation expected from stochastic gravitational wave background (SGWB). In this paper, we offer a nongravitational wave explanation of the observed pulsar timing correlations as caused by an ultralight Lμ−Lτ gauge boson dark matter (ULDM). ULDM can affect the pulsar correlations in two ways. The gravitational potential of vector ULDM gives rise to a Shapiro time delay of the pulsar signals and a nontrivial angular correlation (as compared to the scalar ULDM case). In addition, if the pulsars have a nonzero charge of the dark matter gauge group, then the electric field of the local dark matter causes an oscillation of the pulsar and a corresponding Doppler shift of the pulsar signal. We point out that pulsars carry a significant charge of muons, and thus the Lμ−Lτ vector dark matter contributes to both the Doppler oscillations and the time delay of the pulsar signals. The synergy between these two effects provides a better fit to the shape of the angular correlation function, as observed by the NANOGrav collaboration, compared to the standard SGWB explanation or the SGWB combined with time delay explanations. Our analysis shows that, in addition to the SGWB signal, there may potentially be excess timing residuals attributable to the Lμ−Lτ ULDM. Published by the American Physical Society 2024

Time delay of reflected and transmitted laser pulse at laser action on a dense plasma slab

The time delay phenomenon of reflected and transmitted laser pulse under the action of s-polarized laser radiation on a supercritical plasma slab is considered. The dependence of the time delay and peak intensity of reflected and transmitted signals on the slab thickness, plasma density, and angle of laser radiation incidence is investigated. It is shown that with increasing thickness of the plasma slab, the saturation of the transmitted signal delay time (Hartman effect) does not occur due to the exponential decrease in its intensity. The tunneling speed of the laser pulse energy through the slab of supercritical plasma is calculated, and it is shown that at large angles of laser radiation incidence, it can exceed the speed of light in vacuum.

Long wavelength fluoride optical glass fibers performance signature in high speed local area data networks

Abstract This paper has clarified long wavelength fluoride optical glass fibers performance signature in high speed local area data networks. The signal attenuation and the total fiber pulse broadening are studied versus network length for various fluoride optical glass fibers and AS2 Se3 glass fiber at various spectral wavelengths. The total signal delay time is demonstrated with fiber numerical aperture with 15 km network length for various fluoride optical glass fibers and AS2 Se3 glass fiber at 2.5 μm optimum spectral wavelength. Total fiber signal bandwidth, total Shannon channel bit rate, and NRZ/RZ channel data rate transmission are clarified with 15 km network length for various fluoride optical glass fibers and AS2 Se3 glass fiber at 2.5 μm optimum spectral wavelength.

Modeling impacts of different data transmission delays on traffic jam, fuel consumption and emissions on curved road

Under the intelligent transportation system, the use of autonomous vehicles can ease traffic jam, and reduce fuel consumption and emissions. The effects of different data transmission delays on traffic jam, fuel consumption and emissions on curved road are studied by constructing an extended multi-vehicle curve following model considering different data transmission delays to describe the curve following behavior of multiple autonomous vehicles. Subsequently, the stability of the novel model is derived by using linear stability theory. And then, numerical simulation is executed. Finally, some influence factors including curvature radius, backward looking effect, position signal time delay, and velocity signal time delay are discussed. Numerical simulation results show that reducing curvature radius and increasing backward looking effect can reduce fuel consumption and emissions, decrease density fluctuations, thereby gradually eliminating traffic jam. In addition, as difference between position signal time delay and velocity signal time delay decreases, the improvement degree in fuel consumption and emissions is limited. Meanwhile, it also makes density fluctuation decreases gradually, enhances traffic stream stability, and alleviates traffic jam, which is keeping with theoretical analysis. The finding has theoretical implications for designing autonomous vehicle control algorithms to reduce the negative effects of data transmission delays in traffic flow.

An improved wiener filter-based method for identifying stall inception of transonic compressor

The development of the modern aviation industry poses high demands on the design of aircraft engines recently. However, the stability of compressor flow is one of the key factors affecting further improvements in engine performance. The design of next-generation aircraft engines imposes higher requirements on compressor loading, which leads to the emergence of many new stall inceptions. As a result, the onset and evolution of flow instability become more complex. For accurately capturing stall inceptions of transonic compressors, the strong pressure disturbances caused by shock waves at the blade tip and the complex flow within blade passages result in significant challenges. To address this issue, this study draws inspiration from the design methods of Wiener filters in the field of speech recognition. Based on the characteristic signal mutations during rotating stall in compressors, a Wiener filter approach that uses time-delayed signals as noise estimates during filter training is developed. The method can be used for both offline and online analysis. It was applied to analyze the stall signals of a single rotor from a 1.5-stage transonic axial compressor under distorted inlet conditions at transonic rotational speeds and the entire stage under uniform inlet conditions at subsonic rotational speeds. The results indicate that, under inlet distortion, the compressor generates disturbance signals in the distorted sector before stall, and the earliest spike-inception disturbance occurs at the circumferential position of the rotor leaving the distorted sector. Under uniform inlet conditions, random disturbances could be detected throughout the circumference before stall onset, developing into spike waves at a circumferential location that subsequently triggered stall. Compared to conventional low-pass filters, discrete wavelet transforms, and empirical mode decomposition, the Wiener filter yielded more prominent spike wave structures in the filtered signals. Under distorted inlet conditions, the Wiener-filtered signals showed a 1 % decrease in autocorrelation coefficient and a 3.7 % increase in root mean square (RMS) upon the appearance of spike waves, more pronounced than the 0.5 % decrease in autocorrelation coefficient and 1.8 % increase in RMS achieved by conventional methods. Under uniform inlet conditions, the Wiener filter also detected a 9.7 % increase in RMS upon the appearance of spike waves, more pronounced than the 6.3 % increase observed with conventional methods.

A tunable spatial coherence imaging with ultrasonic array for defects in composites

ABSTRACT Ultrasonic phased array detection technology is a promising non-destructive testing (NDT) method that has been widely used for defect detection. Due to the high attenuation characteristics of ultrasonic wave propagation in carbon fibre reinforced polymer (CFRP) and the directivity of the array elements, the possibility of false or missed detection for defects that are far from the array elements or located very close together will increase. In addition, the total focusing method (TFM) employs only the defect information contained in the full matrix capture (FMC) dataset while ignoring the spatial information of the array signals, leading to image mixed with artefact and noise. An improved method called p-weighted-TFM (p-WTFM) is proposed. First, this method scales the magnitude of time-delayed channel signal by p-th root while maintaining the phase unchanged. Second, channel summation with energy compensation and directional correction will be realised. Finally, the signal dimensionality is restored by p-th power. Experimental results show that the p-WTFM can use any rational p-value to flexibly adjust image quality. Specially, this method can accurately distinguish adjacent defects spaced 1 mm apart with p value of 2.5, and it can also detect two defects located 10 mm deep with p value of 3.0.

Properties of a Broadband Gaussian Pulse Propagating Through a Λ-type Atomic Medium at Room Temperature

Abstract In our study, we conduct a comprehensive theoretical analysis on the propagation behavior of a Gaussian pulse through a four-level Λ-type Rubidium atomic medium under room temperature conditions. Our investigation uncovers the presence of two distinct wavepackets within the medium’s transmission signal. The primary wavepacket, linked to electromagnetically induced transparency transmission, serves as the central signal in the study. Characterized by its optical beat signal utilized for fast microwave strength detection, this wavepacket demonstrates notable features such as pronounced normal dispersion and decreased group velocity. Additionally, the emergence of the Sommerfeld-Brillouin precursor as the second wavepacket further enriches our understanding of pulse dynamics in the medium. Our simulation findings reveal the potential for the optical precursor to play a dominant role in the transmission signal with the adopted methodology. Furthermore, we identify that experimental parameters like atomic density, vapor cell length, and control field intensity play crucial roles in modulating the time delay of the primary signal and the amplitude of the optical precursor.

Gaussian and Lévy noises excited delayed tumor growth model: first-passage behavior and stochastic resonance

In this paper, we analyze the dynamical behavior of a delayed tumor growth model under the joint effect of Gaussian white noise and Lévy noise by studying the mean first passage time (MFPT) and stochastic resonance (SR). Firstly, the tumor growth model under the joint effect of Gaussian white noise, Lévy noise and time delay is introduced. Then, the Lévy noise sequence is simulated by Janicki-Weron algorithm, and the MFPT and signal-to-noise ratio(SNR) of the system are simulated by using fourth-order stochastic Runge–Kutta algorithm. The effects of noise parameters, time delay and periodic signal parameters on MFPT, SR are discussed in detail, respectively. In addition, we find the phenomenon of noise enhanced stability. The results of the study can help to select the optimal regulatory parameters in the tumor growth model and promote the treatment of tumors.

Crystallization and microwave dielectric properties of CaO-B2O3-SiO2 glass-ceramic/Al2O3 for LTCC applications

High-frequency electronic devices with low dielectric loss and electronic components with high integration densities require high-performance electronic packaging materials. In this study, materials primarily composed of CaO-B2O3-SiO2 (CBS) with an elevated boron content were fabricated through solid-phase sintering using Al2O3 as the ceramic phase. The phase compositions, densification process, microstructures, thermal conductivity, thermal expansion, and dielectric properties of the LTCC were investigated. Remarkably, the CBS-1 LTCC composite sintered at 850 °C for 4 h, exhibited a dense and nonporous microstructure. It demonstrated exceptional thermoelectric properties, including a thermal shrinkage of 5.61 %, coefficients of thermal expansion of 4.86 ppm/°C, thermal conductivity of 2.36 W/m·K, dielectric constant (εr) of 4.88, and tan δ of 1.05× 10−3 at 15 GHz. These characteristics are conducive to minimizing the signal propagation time delay and filtering noisy signals. Consequently, the CBS-1 LTCC composite emerged as a promising substrate for LTCC applications.

Wind and Wave-Induced Vibration Reduction Control for Floating Offshore Wind Turbine Using Delayed Signals

Active vibration control is a critical issue of the wind turbine in the field of marine energy. First, based on a three-degree-of-freedom wind turbine, a state space model subject to wind and wave loads is obtained. Then, a delayed state feedback control scheme is illustrated to reduce the vibration of platform pitch angle and tower top foreaft displacement, where the control channel includes time-delay state signals. The designed controller’s existence conditions are investigated. The simulation results show that the delayed feedback H∞ controller can significantly suppress wind- and wave-induced vibration of the wind turbine. Furthermore, it presents potential advantages over the delay-free feedback H∞ controller and the classic linear quadratic regulator in two aspects: vibration control performance and control cost.

Independent Time-Delay Signal Cancellation for Fast Harmonic-Sequence Filters Targeting Arbitrary Sequences and Frequencies

Independent Time-Delay Signal Cancellation for Fast Harmonic-Sequence Filters Targeting Arbitrary Sequences and Frequencies

Encryption Technology of Optical Communication Network Based on Artificial Intelligence Technology

At present, research on enhancing information transmission security by addressing the two key issues of time delay signal elimination and key space expansion in chaotic secure communication systems has become a hot topic. In order to improve the encryption effect of optical communication network, this paper analyzes the encryption technology of optical communication network with AIT (artificial intelligence technology), designs the encryption scheme of optical communication network with the help of AIT, and takes the digital random sequence as the key. Moreover, this paper uses the digital signal processor to control the arbitrary wave generator to generate multi-ary step square wave, modulate the optical feedback and realize the highly random change of external cavity delay, thus eliminating the long external cavity delay information. This article proposes a chaotic secure communication system using digital sequences as keys and external cavity optical feedback, a device for forming a chaotic source through arbitrary wave phase modulation and single loop feedback, and a chaotic secure communication system with single feedback key phase modulation and injection synchronization. At the same time, this paper proposes a system scheme using single-loop optical feedback phase modulation, the CS(chaotic signal) with complex dynamic behavior is output, and the time-delay signal is effectively eliminated. This paper analyzes the strength and phase information of CS by autocorrelation and mutual information technology, and verifies the effect of optical communication network encryption technology. Through the analysis of experimental results, it can be seen that the optical communication network encryption technology based on AIT proposed in this paper can effectively improve the encryption effect of optical communication network. The algorithm model camera proposed in this article can be used in subsequent practice to improve communication encryption performance

Optimizing Accumulator Performance in Hydraulic Systems through Support Vector Regression and Rotational Factors

The piston-type accumulator is an energy storage device in hydraulic–pneumatic systems, playing a significant role in industries such as petrochemicals, heavy machinery, and steel metallurgy. The displacement parameters of the piston-type accumulator are vitally important for fault diagnosis and early warning in hydraulic systems. Traditional displacement measurement methods cannot meet the requirements of the internal testing environment of the accumulator. Therefore, this paper proposes an accumulator piston displacement signal compensation method based on rotational factors and support vector regression. Firstly, empirical mode decomposition is utilized to denoise the signal. Then, rotational factors are used to generate a delay compensation module to compensate for the signal attenuation and time delay caused by metallic reflection and scattering within the cylinder of the radar signal. The support vector regression model is improved based on a hash table to enhance its computational efficiency and achieve radar displacement signal compensation. Finally, a simulation experiment is designed to verify the effectiveness of the proposed method.

Resonating with the World: Thinking Critically about Brain Criticality in Consciousness and Cognition

Aim: Biofields combine many physiological levels, both spatially and temporally. These biofields reflect naturally resonant forms of synaptic energy reflected in growing and spreading waves of brain activity. This study aims to theoretically understand better how resonant continuum waves may be reflective of consciousness, cognition, memory, and thought. Background: The metabolic processes that maintain animal cellular and physiological functions are enhanced by physiological coherence. Internal biological-system coordination and sensitivity to particular stimuli and signal frequencies are two aspects of coherent physiology. There exists significant support for the notion that exogenous biologically and non-biologically generated energy entrains human physiological systems. All living things have resonant frequencies that are either comparable or coherent; therefore, eventually, all species will have a shared resonance. An organism’s biofield activity and resonance are what support its life and allow it to react to stimuli. Methods: As the naturally resonant forms of synaptic energy grow and spread waves of brain activity, the temporal and spatial frequency of the waves are effectively regulated by a time delay (T) in inter-layer signals in a layered structure that mimics the structure of the mammalian cortex. From ubiquitous noise, two different types of waves can arise as a function of T. One is coherent, and as T rises, so does its resonant spatial frequency. Results: Continued growth eventually causes both the wavelength and the temporal frequency to abruptly increase. Two waves expand simultaneously and randomly interfere in an area of T values as a result. Conclusion: We suggest that because of this extraordinary dualism, which has its roots in the phase relationships of amplified waves, coherent waves are essential for memory retrieval, whereas random waves represent original cognition.

Research and Development of Noise-Resistant Algorithms for Calculating the Group Delay Time of a Model Digital Signal with a Random Noise Component

Research and Development of Noise-Resistant Algorithms for Calculating the Group Delay Time of a Model Digital Signal with a Random Noise Component

Digital Close-Loop Active Gate Driver for Static and Dynamic Current Sharing of Paralleled SiC MOSFETs

SiC power devices have been extensively for the high-power density application scenarios. To increase the current rating, SiC devices are usually connected in parallel. However, the mismatching current brought by unbalanced electrical parameters can increase the current stress of a device and pose reliability concern of the converter system. Aiming at addressing the current imbalance for paralleled SiC devices, this paper reports the application of an improved active gate driver (AGD) on the paralleled SiC MOSFETs to address the current imbalance problems. The three-level driver voltage can minimize the overshoot voltage and current. The adjustable turn-on voltage and gate signal delay time can realize the current sharing of both static and dynamic process. Current sensors and a digital controller are utilized for close-loop control. The functionality of the proposed AGD is validated in continuous operating experiment.

Робастное обнаружение и оценивание широкополосных сигналов

An asymptotically robust invariant (ARI) algorithm for signal detection and time delay estimation is proposed. It is based on the q-point model of noise distributions. The algorithm is based on calculating the correlation statistics of the nonlinear transformation of the observed sample with the vector of reference signal samples. Time delay estimate is determined by special processing of the obtained statistics, taking into account the presence of mirror interference in the observed process. The algorithm is implemented in the frequency domain, which allows the use of the fast Fourier transform to reduce computational costs. The simulation results show that in the case of heavy-tailed noise distributions, ARI algorithm provides an energy gain compared to the classical correlation algorithm, and it has similar performance in the case of Gaussian noise.

Design and Simulation of MEMS Surface Acoustic Wave Biosensor Based on PVDF Thin Film

Abstract: Surface acoustic wave sensors, as a class of MEMS, are widely used recently. The sensor can transform an input electrical signal into a mechanical wave which can be easily influenced by physical phenomena. Then, the changed mechanical wave is transduced back into an electrical signal. The presence of the desired phenomenon can be detected through the difference between the input and output electrical signal (amplitude, phase, frequency, or time delay). The basic surface acoustic wave device consists of a piezoelectric substrate, an input interdigitated transducer (IDT) on one side of the surface of the substrate, and a second output interdigitated transducer on the other side of the substrate.

Research of microprocessor device and software for remote control of a robotic system

The modern stage of the development of intelligent robotic systems is characterized by the expansion of fields of application, which is due to autonomous work and decision-making in conditions of uncertainty. The object of research is the system of remote control of robotic systems. During the remote control of robotic systems, problems arise that are associated with the use of wireless communication in real time. The article analyzes software and hardware implementations of various remote control systems suitable for use as part of autonomous robotic systems and analyzes promising microcontroller platforms for implementing a remote control device for a robotic system. A brief review of existing protocols for transmitting control signals using radio communication equipment and microprocessor platforms for the development of embedded systems is performed, among which a solution is selected for research. Several approaches to the control of a robotic system are highlighted – control using a wired connection and corresponding protocols, control via wireless communication or via the Internet, control via general-purpose network protocols. The target platform is chosen and justified, and the S.BUS protocol is analyzed with the provision of an algorithm for obtaining the values of the control channels from the S.BUS package. The structure and algorithm of functioning of the microprocessor remote control system based on the ESP32 microcontroller and the FreeRTOS OS are given. A study of the operation process of the proposed remote control system is carried out, for which it is placed on the chassis of a ground autonomous robotic system with four-wheel drive, and the delay time of the control signal from the receiver to the engine control modules is determined. According to the conducted analysis, the expediency of using specialized radio communication equipment with the S.BUS protocol for controlling executive devices as part of a robotic system, for precise movement control in real time, is shown.