Passive seismic interferometry is a technique that reconstructs virtual seismic records using ambient noise, such as random noise or microseisms. The ambient noise in passive seismic data contains rich information, with surface waves being useful for...
Power line interference (PLI) is a major source of noise in sEMG signals. As the bandwidth of PLI overlaps with the sEMG signals, it can easily affect the interpretation of the signal. The processing methods used in the literature are mostly notch fi...
The stage subdivision of gravity-flow deposits is crucial for identifying deep-water reservoirs. Traditional methods relying on visual core observation or macroscopic well log correlation are often subjective and lack the resolution to decipher dynam...
To tackle the challenges associated with conventional methods of diagnosing hydraulic turbine faults, which depend heavily on expert knowledge and exhibit low efficiency and precision, a model for detecting hydraulic turbine faults has been developed...
Epilepsy is a common neurological disease worldwide, characterized by recurrent seizures. There is currently no cure for epilepsy. However, seizures can be controlled by drugs and surgeries in about 70% of epileptic patients. A timely and accurate pr...
The most classical subsynchronous oscillation (SSO) mode extraction methods have some shortcomings, such as lower mode identification and poor anti-noise properties. Thus, this paper proposes a new time-frequency analysis method, namely, synchrosquee...
Background/Objectives: Cardiac auscultation is an important method for identifying cardiovascular abnormalities, but conventional methods are limited by examiner-dependent variability and sensitivity. The automatic classification of phonocardiogram (...
This study proposes a novel rolling bearing fault diagnosis technique based on a synchrosqueezing wavelet transform (SWT) and a transfer residual convolutional neural network (TRCNN) designed to address the difficulties of feature extraction caused b...
Wind turbines usually operate under nonstationary conditions, such as wide-range speed fluctuation and time-varying load. Its critical component, the planetary gearbox, is prone to malfunction or failure, which leads to downtime and repair costs. The...
Magnetic anomaly signal detection (MASD) is a passive method for the detection of visually obscured ferromagnetic objects. This paper proposes a new method for MASD based on the ambient field of power frequency magnetic (power transmission line syste...
Nowadays, fault diagnostics is widely applied under Industry 4.0 to reduce machine maintenance costs, improve productivity, and increase machine availability. However, fault diagnostics are mostly post-mortem. When the fault is identified, it is alre...
During the long-term operation of thyristor converter valves, the saturable reactor vibration (mainly caused by magnetostriction) will lead to core looseness faults. In order to accurately evaluate the fault degradation degree, this paper proposes a...
Passive surface wave imaging based on noise cross-correlation has been a research hotspot in recent years. However, because randomness of noise is difficult to achieve in reality, prominent noise sources will inevitably affect the dispersion measurem...
Radio frequency interference (RFI) significantly hampers the target detection performance of frequency-modulated continuous-wave radar. To address the problem and maintain the target echo signal, this paper proposes a priori assumption on the interfe...
In electrical engineering, partial discharge (PD) measurement has been widely used for inspecting and judging insulation conditions of high voltage (HV) apparatus. However, on-site PD measurement easily becomes contaminated by noises. Particularly, s...
Motor fault identification is often constrained by scarce labeled samples and the limited representation capability of a single time–frequency transform. Conventional CNN–Softmax models may also produce unstable decision boundaries under...
To address the limitations of one-dimensional vibration signals in convolutional neural networks and the insufficient feature extraction capability of traditional single data processing methods under complex operating conditions, this paper proposes...
Accurately diagnosing sleep disorders is essential for clinical assessments and treatments. Polysomnography (PSG) has long been used for detection of various sleep disorders. In this research, electrocardiography (ECG) and electromayography (EMG) hav...
The primary purpose of this research is to evaluate the uncertainty associated with modal parameter estimation for an inverse dynamic problem in which the structural parameters are random. The random nature of the structure’s parameters will be...
Snoring, a common sleep-disordered breathing phenomenon, impairs sleep quality for both the sufferer and any bed partner. While mild snoring primarily disrupts sleep continuity, severe cases often indicate obstructive sleep apnea (OSA), a disorder af...
Nowadays, the accurate identification of natural frequencies and damping ratios play an important role in smart civil engineering, since they can be used for seismic design, vibration control, and condition assessment, among others. To achieve it in...
Ultrasonic echo estimation has played an important role in industrial non-destructive testing and analysis. The ability to estimate parameters in the ultrasonic echo model is crucial to ensure the effectiveness of practical ultrasonic testing applica...
Respiratory rate (RR) is a key parameter used in healthcare for monitoring and predicting patient deterioration. However, continuous and automatic estimation of this parameter from wearable sensors is still a challenging task. Various methods have be...
With widespread non-linear loads and the increasing penetration of distributed generations in the power system, harmonic pollution has become a great concern. The causes of harmonic pollution not only include the integer harmonics, but also interharm...
Magnetic flux leakage (MFL) signals in steel wire rope defect detection are often corrupted by structural noise and environmental interference, leading to reduced defect recognition accuracy. This study proposes a denoising approach combining synchro...
The increasing demand on electrical power consumption all over the world makes the need for stable and reliable electrical power grids is indispensable. Meanwhile, power grid fault diagnosis based on fault recording data is an important technology to...
Deriving critical parametric information from recorded signals for system identification is critical in structural health monitoring and damage detection, while the time-varying nature of most signals often requires significant processing efforts due...
Chipless RFID tags have attractive low-cost advantages. However, traditional RFID anti-collision algorithms cannot be applied due to a lack of computing and processing capabilities. Problems with multitag detection must be solved to commercialize chi...
Respiration rate (RR) provides useful information for assessing the status of a patient. We propose RR estimation based on photoplethysmography (PPG) because the blood perfusion dynamics are known to carry information on breathing, as respiration-ind...
The vibrational behaviour of misaligned rotating machinery is described and analysed in this paper. The model, constructed based on the equations of vehicle dynamics, considered the dynamic excitation of a single Hooke’s joint. The system adopted the...
High-rate dynamic systems are defined as engineering systems experiencing dynamic events of typical amplitudes higher than 100 g
Vibration signal analysis is an efficient online transformer fault diagnosis method for improving the stability and safety of power systems. Operation in harsh interference environments and the lack of fault samples are the most challenging aspects o...
We propose a method based on Synchrosqueezing Transform (SST) for vibration event analysis and identification in Phase Sensitive Optical Time-Domain Reflectometry (Φ-OTDR) systems. SST has high time-frequency resolution and phase information, whi...
Accurate vibration classification using inertial measurement unit (IMU) data is critical for various applications such as condition monitoring and fault diagnosis. This study proposes a novel convolutional neural network (CNN) based approach, the IMU...
Electrocardiogram (ECG) arrhythmia classification remains critical for automated cardiac diagnosis, yet feature extraction methods are frequently adopted without systematic comparative evaluation. This study presents a controlled comparative analysis...
To robustly and adaptively reconstruct displacement, we propose the amplitude modulation integral reconstruction method (AM-IRM) for displacement sensing in a self-mixing interferometry (SMI) system. By algebraically multiplying the SMI signal with a...
A new method for measurement of the material damping coefficient based on the laser self-mixing interference (SMI) technique is proposed. The dominant frequency that varies over time is extracted by using the synchro-squeezed wavelet transform to obt...
Background: Parkinson’s disease is a progressive neurodegenerative disorder. Early PD detection plays a key role in effective therapy. Electroencephalography is a neuroimaging technique used to analyze brain abnormalities, such as those seen in...
Low probability of intercept (LPI) radar signal recognition under low signal-to-noise ratio (SNR) is a challenging task within electronic reconnaissance systems, particularly when faced with scarce labeled data and limited resources. In this paper, w...
The current study aims to study the drill string–casing system operating in an inviscid fluid under imbalanced and rubbing damage types. The Navier–Stokes equations were linearized to establish the hydrodynamic forces surrounding the dril...
In this paper, a new time-frequency analysis method—Synchrosqueezing Generalized S-transform (SSGST)—is proposed to meet the needs of high-resolution seismic signal processing and interpretation. The basic wavelet of the generalized S-transform (GST)...
In modern power systems, interharmonics have emerged as noninteger frequency components that appear in current or voltage signals. Double-stage AC-DC-AC converters have been identified as a primary source of interharmonics. Previous studies have high...
Long-period resonant excitation can amplify local damage and promote global instability in tall core–outrigger structures. This study presents an event-guided reanalysis of the shaking-table collapse response of a 28-level, 1/40-scale model rep...
Focal and non-focal Electroencephalogram (EEG) signals have proved to be effective techniques for identifying areas in the brain that are affected by epileptic seizures, known as the epileptogenic zones. The detection of the location of focal EEG sig...
High-frequency measurements of tides, waves, and turbulence were made using the bottom-mounted tripod equipped with the Nortek 6-MHz acoustic Doppler velocimetry during 20–23 February 2016 (winter) and 12–26 June 2017 (summer) in Heini Ba...
Dynamic muscle fatigue during repetitive movements can lead to changes in communication between the central nervous system and peripheral muscles. This study investigated these changes by examining electromyogram (EMG) characteristics from agonist an...
In engineering applications, the accuracy of on-load tap changer (OLTC) mechanical fault identification methods based on vibration signals is constrained by the quantity and quality of the samples. Therefore, a novel small-sample-size OLTC mechanical...
Due to the lack of fault data in the daily work of rotating machinery components, existing data-driven fault diagnosis procedures cannot accurately diagnose fault classes and are difficult to apply to most components. At the same time, the complex an...
Reliable motor-current-based bearing diagnosis requires evaluation on unseen physical bearings and operating conditions. This study uses the Paderborn University benchmark, acquired from a 425 W permanent-magnet synchronous motor (PMSM) test rig, to...
Speech emotion recognition (SER) tasks are conducted to extract emotional features from speech signals. The characteristic parameters are analyzed, and the speech emotional states are judged. At present, SER is an important aspect of artificial psych...
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