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"IEEE Sensors Alert" is a pilot project of the IEEE Sensors Council. Started as one of its new initiatives, this weekly digest publishes teasers and condensed versions of our journal papers in layperson's language.
Articles Posted in the Month (July 2026)
An EMAT Based on a Novel Extrusion Static Magnetizer for Thickness Measurement of Steel Plates
Author: Xu Jiang, Hu Yulin, Zheng Zheng
Published in: IEEE Sensors Journal (Volume: 26, Issue: 1, January 2026)
Summary Contributed by: Jiang Xu (Author)
Existing symmetrical repulsive magnetizers face challenges due to a divergent upper magnetic field and low utilization efficiency. This paper introduces a novel extrusion static magnetizer that enhances magnetic field efficiency via a central magnet-silicon steel composite structure. This innovation significantly improves the signal amplitude and signal-to-noise ratio (SNR) of electromagnetic acoustic transducer (EMAT) thickness measurements, providing a more stable and reliable solution for detecting the thickness of steel plates.
Compound Fault Diagnosis of Rolling Bearings Based on the PSD-Guided Cyclostationarity Feature Mode Decomposition
Author: Wang Feng, Huang Yufeng, Sheng Zilin, Shi Yifei
Published in: IEEE Sensors Journal (Volume: 26, Issue: 1, January 2026)
Summary Contributed by: Feng Wang (Author)
Identifying compound faults in rolling bearings can be challenging due to overlapping noise and irrelevant interference. This study introduces a novel diagnostic method called Power Spectral Density (PSD)-Guided Cyclostationarity Feature Mode Decomposition (PCFMD). This approach uses power spectral density to guide adaptive filtering design, offering a more accurate and efficient method for identifying overlapping faults, supporting predictive maintenance, monitoring critical machinery, and helping minimize unexpected failures in industrial systems.
A Lightweight Perception Enhancement Network for Real-Time and Accurate Internal Surface Defect Detection of Cold-Drawn Steel Pipes
Author: Song Kechen, Yan Yunhui, Chen Hongshu, Tan You, Zhang Yu
Published in: IEEE Sensors Journal (Volume: 26, Issue: 1, January 2026)
Summary Contributed by: You Tan (Author)
Detecting internal surface defects in cold-drawn steel pipes can be challenging due to limited access and complex lighting conditions. This study introduces a Pipe Internal Surface Detection (PISD) robot equipped with vision sensors and a lightweight perception enhancement network (LPENet) for accurate detection in industrial settings. This approach enables faster, more reliable quality inspection while keeping computational costs low, making it practical for industrial inspections and deployment in demanding manufacturing environments.
Hierarchical Labeling and Layered-Training-Based CNN: An Application in Bearing Fault Diagnosis
Author: Liu Jiangchao, Ruan Diwang, Cui Yi, Li Zhaorong, Qian Yiliang, Yan Jianping
Published in: IEEE Sensors Journal (Volume: 26, Issue: 1, January 2026)
Summary Contributed by: Jiangchao Liu (Author)
Industrial systems largely depend on rolling bearings for smooth operation. However, diagnosing fault reliably can be challenging due to the limited interpretability of deep learning models. This paper proposes a hierarchical labeling and progressive freezing mechanism, combined with a layered training strategy, to address this challenge. This method improves diagnostic interpretability, accuracy, and reliability, making it suitable for diagnosing complex fault types in industrial applications.
Author: Javier Gonzalez, Moreno Juan R., Peale Robert
Published in: IEEE Sensors Journal (Volume: 26, Issue: 1, January 2026)
Summary Contributed by: F. J. González (Author)
Terahertz (THz) waves are a bridge between microwaves and infrared light. This study presents a new terahertz detector fabricated from a miniature bowtie antenna connected to a silicon-platinum thermoelectric junction. This detector operates at room temperature without requiring an external power supply and achieves state-of-the-art sensitivity across the 3.8–8 THz band. The innovation paves the way for affordable, compact THz sensing applications in security screening, biomedical imaging, and wireless communications.
Published in: IEEE Sensors Journal (Volume: 26, Issue: 1, January 2026)
Summary Contributed by: Rachel F. Bellisle (Author)
Wearable strain sensors embedded into clothing can effectively track human movement. This paper proposes a novel knot-based strain sensor integrated into the ankle of an astronaut's full-body spacesuit aboard the International Space Station. By employing machine learning techniques alongside the ankle sensor system, the researchers successfully classified non-local body movements while minimizing hysteresis. This innovation shows potential for various applications, including space missions, sports tracking, and home-based rehabilitation.
Author: Kupnik Mario, Bretthauer Christian, Dorsam Jan Helge, Haugwitz Christoph, Herbst Felix, Kim Yoojeong, Lee Hyunjoo J., Merbeler Fabian, Rutsch Matthias, Soennecken Soren, Suppelt Sven, Wiemer Elena, Wismath Sonja Katharina
Published in: IEEE Sensors Journal (Volume: 26, Issue: 2, January 2026)
Summary Contributed by: Mario Kupnik (Author)
Force-sensing technology plays a vital role in measuring mechanical force using sensors and transducers. This work introduces capacitive micromachined ultrasonic transducers (CMUTs) as a groundbreaking approach to force sensing, showcasing their advantages over conventional strain gauges. The sensing principle relies on detecting resonance frequency shifts caused by force-induced structural deformation, enabling precise frequency readout. Despite slightly lower uncertainty metrics, CMUTs offer superior scalability and integration potential for highly miniaturized applications
Distributed Stress Sensing in Polarization-Maintaining Fiber Under Circumferential Stress
Author: Zhang Hongxia, Jia Dagong, Li Tianyue, Li Zhihong, Liu Tiegen, Liu Yan, Song Rencheng, Zhang Bozhi
Published in: IEEE Sensors Journal (Volume: 26, Issue: 1, January 2026)
Summary Contributed by: Zhang Hongxia (Author)
Real-world engineering applications require continuous monitoring of structural stress. This study presents a distributed sensing method using Polarization-maintaining fiber (PMF) for circumferential stress monitoring via white-light interferometry, detecting subtle pressure changes around the fiber. Validated by 0–26 MPa pressure tank tests and 55 m downhole experiments, it demonstrated a linear response and 2.5 dB/MPa sensitivity, making it a robust solution for circumferential pressure sensing in extreme environments.
3D printing is revolutionizing the production of a wide range of sensors, allowing customization at a lower cost than conventional manufacturing techniques. This paper presents an artificial hair-like sensor (AHS) inspired by the flat hair-like mechanoreceptor of the adult Buthus occitanus scorpion. The sensor has been 3D-printed for airflow velocity measurements. Potential applications include meteorology, robotics and autonomous drones, biomedical engineering, flow cameras for multi-point measurements, and more.
Published in: IEEE Sensors Journal (Volume: 26, Issue: 1, January 2026)
Summary Contributed by: Mavrogiannis (Author)
Gait analysis is crucial in diagnosing and managing mobility disorders. This study utilizes low-cost smart insoles with embroidered textile capacitive sensors and an inertial measurement unit (IMU) to recognize the four basic phases of the human gait cycle. It uses a long short-term memory (LSTM)-based neural network trained on collected data, achieving 90% accuracy and 87.1% F1 macro score across exercises with variable gait speeds, offering an affordable gait analysis solution.
Radar detection of smaller targets requires lowering the radar cross-section and velocity thresholds. With it, an abundance of target signatures gets generated, making it necessary to classify only relevant targets. Micro-motions of targets are significant characteristics. Micro-Doppler signatures have emerged as an effective method of classifying such targets. The study presents a systematic review of various micro-Doppler-based radar target signature analysis and classification techniques.
The recent COVID outbreaks highlighted the need for breathing rate monitoring and increased the demand for hospitalized patients. Monitoring breathing rate is vital for diagnosing diseases and observing patients with pulmonary conditions. The pros and cons of different techniques are studied and categorized under contact and remote modes of respiratory monitoring systems. Various Radar-based methods found to be more suitable for respiration monitoring are discussed.
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