Personnel Detection in Dark Aquatic Environments Based on Infrared Thermal Imaging Technology and an Improved YOLOv5s Model.

This study presents a novel method for the nighttime detection of waterborne individuals using an enhanced YOLOv5s algorithm tailored for infrared thermal imaging. To address the unique challenges of nighttime water rescue operations, we have constructed a specialized dataset comprising 5736 thermal images collected from diverse aquatic environments. This dataset was further expanded through synthetic image generation using CycleGAN and a newly developed color gamut transformation technique, which significantly improves the data variance and model training effectiveness. Furthermore, we integrated the Convolutional Block Attention Module (CBAM) at the end of the last encoder's feedforward network. This integration maximizes the utilization of channel and spatial information to capture more intricate details in the feature maps. To decrease the computational demands of the network while maintaining model accuracy, Ghost convolution was employed, thereby boosting the inference speed as much as possible. Additionally, we applied hyperparameter evolution to refine the training parameters. The improved algorithm achieved an average detection accuracy of 85.49% on our proprietary dataset, significantly outperforming its predecessor, with a prediction speed of 23.51 FPS. The experimental outcomes demonstrate the proposed solution's high recognition capabilities and robustness, fulfilling the demands of intelligent lifesaving missions.

Stable Q-switched and femtosecond mode-locked erbium-doped fiber laser based on a CuSe nanosheets saturable absorber.

Stable Q-switched and femtosecond mode-locked erbium-doped fiber laser (EDFL) have been achieved using CuSe nanosheets as novel saturable absorber (SA), where the CuSe nanosheets were prepared by a hydrothermal method. The nonlinear optical properties of CuSe nanosheets were measured using an Z-scan setup, revealing nonlinear absorption coefficients of -3.67 ± 0.22 cm GW-1 at 1560 nm. The prepared CuSe nanosheets were mixed with polyvinyl alcohol (PVA) to obtain a CuSe-PVA SA with a modulation depth of 3.8 ± 0.13%, and it was utilized to realize a Q-switched EDFL, obtaining the narrowest pulse duration of 1.29 µs and the maximum output power of 5.96 mW, which corresponds to a pulse energy of up to 103.7 nJ. In addition, CuSe nanosheets were deposited on a D-shaped fiber (DSF) to fabricate a CuSe-DSF SA with a modulation depth of 5.6 ± 0.17%, and it was utilized to realize a mode-locked EDFL. The mode-locked EDFL demonstrated a low threshold of only 42 mW, a pulse duration of 740 fs, and a maximum output power of 9.7 mW. Meanwhile, it exhibited a high signal-to-noise ratio of 72 dB. To the best of our knowledge, this is the first time of CuSe nanosheets as SA in EDFL. The results demonstrate that CuSe nanosheets are a highly promising nonlinear optical material with great potential for applications in ultrafast photonics.

Acoustic Emission Detection and Analysis Method for Health Status of Lithium Ion Batteries.

The health detection of lithium ion batteries plays an important role in improving the safety and reliability of lithium ion batteries. When lithium ion batteries are in operation, the generation of bubbles, the expansion of electrodes, and the formation of electrode cracks will produce stress waves, which can be collected and analyzed by acoustic emission technology. By building an acoustic emission measurement platform of lithium ion batteries and setting up a cycle experiment of lithium ion batteries, the stress wave signals of lithium ion batteries were analyzed, and two kinds of stress wave signals which could characterize the health of lithium ion batteries were obtained: a continuous acoustic emission signal and a pulse type acoustic emission signal. The experimental results showed that during the discharge process, the amplitude of the continuous acoustic emission signal decreased with the increase of the cycle times of batteries, which could be used to characterize performance degradation; there were more pulse type acoustic emission signals in the first cycle of batteries, less in the small number of cycles, and slowly increased in the large number of cycles, which was in line with the bathtub curve and could be used for aging monitoring. The research on the health of lithium ion batteries by acoustic emission technology provides a new idea and method for detecting the health lithium ion batteries.

A reliable initial rotor position estimation method for sensorless control of interior permanent magnet synchronous motors.

In this paper, a novel initial rotor position estimation method for reliable start-up of the IPMSM is presented. The proposed method combines the improved high frequency pulse signal injection with positive and negative d-axis current bias injection. Differing from the conventional initial rotor position detection scheme, the injection and the field-oriented control periods are separated in the proposed method. Therefore, the filters are not needed in the process of high-frequency response current and fundamental current extraction. The magnet polarity can be estimated by exciting the positive and negative d-axis currents. Afterwards, the peak values of d-axis current during the voltage injection period are accumulated to detect the rotor magnetic polarity. The proposed method can improve the reliability of the magnet polarity detection. Moreover, it is suitable for both the standstill rotor application and the free-running rotor application. The effectiveness of the proposed method is verified on a 1.5 kW IPMSM drive platform.

Illumination Robust Heart-rate Extraction from Single-wavelength Infrared Camera Using Spatial-channel Expansion.

Heart rate (HR) is one of the most important vital signs for indicating the health condition of a person. Contactless camera-based HR measurement is particularly beneficial for sleep monitoring, as it is comfortable and convenient. However, compared with ambient light, the skin pulsation in near infrared range is much weaker and more susceptible to distortions (e.g. body motion, light changes). In this paper, we propose a method to expand the single-wavelength channel of a near infrared camera to multiple channels for illumination noise reduction, where the channel expansion is performed in the spatial domain using skin and non-skin pixels. The essence is using illumination changes of non-skin pixels to eliminate such a distortion on skin pixels and thus improve pulse extraction. On average, measurement coverage increased from 50% to 83% for the methods of subtraction and Segment Principal Component Analysis (Seg-PCA), and Signal-to-Noise Ratio (SNR) is increased from -8.40 dB to -4.62 dB for the method of Segment Independent Component Analysis (Seg-ICA).

A Review of Microwave Thermography Nondestructive Testing and Evaluation.

Microwave thermography (MWT) has many advantages including strong penetrability, selective heating, volumetric heating, significant energy savings, uniform heating, and good thermal efficiency. MWT has received growing interest due to its potential to overcome some of the limitations of microwave nondestructive testing (NDT) and thermal NDT. Moreover, during the last few decades MWT has attracted growing interest in materials assessment. In this paper, a comprehensive review of MWT techniques for materials evaluation is conducted based on a detailed literature survey. First, the basic principles of MWT are described. Different types of MWT, including microwave pulsed thermography, microwave step thermography, microwave pulsed phase thermography, and microwave lock-in thermography are defined and introduced. Then, MWT case studies are discussed. Next, comparisons with other thermography and NDT methods are conducted. Finally, the trends in MWT research are outlined, including new theoretical studies, simulations and modelling, signal processing algorithms, internal properties characterization, automatic separation and inspection systems. This work provides a summary of MWT, which can be utilized for material failures prevention and quality control.

Improvement of Source Number Estimation Method for Single Channel Signal.

Source number estimation methods for single channel signal have been investigated and the improvements for each method are suggested in this work. Firstly, the single channel data is converted to multi-channel form by delay process. Then, algorithms used in the array signal processing, such as Gerschgorin's disk estimation (GDE) and minimum description length (MDL), are introduced to estimate the source number of the received signal. The previous results have shown that the MDL based on information theoretic criteria (ITC) obtains a superior performance than GDE at low SNR. However it has no ability to handle the signals containing colored noise. On the contrary, the GDE method can eliminate the influence of colored noise. Nevertheless, its performance at low SNR is not satisfactory. In order to solve these problems and contradictions, the work makes remarkable improvements on these two methods on account of the above consideration. A diagonal loading technique is employed to ameliorate the MDL method and a jackknife technique is referenced to optimize the data covariance matrix in order to improve the performance of the GDE method. The results of simulation have illustrated that the performance of original methods have been promoted largely.

Eddy Current Pulsed Thermography with Different Excitation Configurations for Metallic Material and Defect Characterization.

This paper reviews recent developments of eddy current pulsed thermography (ECPT) for material characterization and nondestructive evaluation (NDE). Due to the fact that line-coil-based ECPT, with the limitation of non-uniform heating and a restricted view, is not suitable for complex geometry structures evaluation, Helmholtz coils and ferrite-yoke-based excitation configurations of ECPT are proposed and compared. Simulations and experiments of new ECPT configurations considering the multi-physical-phenomenon of hysteresis losses, stray losses, and eddy current heating in conjunction with uniform induction magnetic field have been conducted and implemented for ferromagnetic and non-ferromagnetic materials. These configurations of ECPT for metallic material and defect characterization are discussed and compared with conventional line-coil configuration. The results indicate that the proposed ECPT excitation configurations can be applied for different shapes of samples such as turbine blade edges and rail tracks.

Defect characterisation based on heat diffusion using induction thermography testing.

Pulsed eddy current (PEC) thermography (a.k.a. induction thermography) has been successfully applied to detect defects (corrosion, cracks, impact, and delamination) in metal alloy and carbon fiber reinforced plastic. During these applications, the defect detection mechanism is mainly investigated based on the eddy current interaction with defect. In this paper, defect characterisation for wall thinning defect and inner defect in steel is investigated based on heat diffusion. The paper presents the PEC thermography testing, which integrates the reflection mode and transmission mode by means of configuring two cameras on both sides of sample. The defect characterisation methods under transmission mode and reflection mode are investigated and compared through 1D analytical analysis, 3D numerical studies, and experimental studies. The suitable detection mode for wall thinning and inner defects quantification is concluded.