Abnormal Behavior Monitoring Method of Larimichthys crocea in Recirculating Aquaculture System Based on Computer Vision.

It is crucial to monitor the status of aquaculture objects in recirculating aquaculture systems (RASs). Due to their high density and a high degree of intensification, aquaculture objects in such systems need to be monitored for a long time period to prevent losses caused by various factors. Object detection algorithms are gradually being used in the aquaculture industry, but it is difficult to achieve good results for scenes with high density and complex environments. This paper proposes a monitoring method for Larimichthys crocea in a RAS, which includes the detection and tracking of abnormal behavior. The improved YOLOX-S is used to detect Larimichthys crocea with abnormal behavior in real time. Aiming to solve the problems of stacking, deformation, occlusion, and too-small objects in a fishpond, the object detection algorithm used is improved by modifying the CSP module, adding coordinate attention, and modifying the part of the structure of the neck. After improvement, the AP50 reaches 98.4% and AP50:95 is also 16.2% higher than the original algorithm. In terms of tracking, due to the similarity in the fish's appearance, Bytetrack is used to track the detected objects, avoiding the ID switching caused by re-identification using appearance features. In the actual RAS environment, both MOTA and IDF1 can reach more than 95% under the premise of fully meeting real-time tracking, and the ID of the tracked Larimichthys crocea with abnormal behavior can be maintained stably. Our work can identify and track the abnormal behavior of fish efficiently, and this will provide data support for subsequent automatic treatment, thus avoiding loss expansion and improving the production efficiency of RASs.

Research on a multi-dimensional image information fusion algorithm based on NSCT transform.

Traditional inspection cameras determine targets and detect defects by capturing images of their light intensity, but in complex environments, the accuracy of inspection may decrease. Information based on polarization of light can characterize various features of a material, such as the roughness, texture, and refractive index, thus improving classification and recognition of targets. This paper uses a method based on noise template threshold matching to denoise and preprocess polarized images. It also reports on design of an image fusion algorithm, based on NSCT transform, to fuse light intensity images and polarized images. The results show that the fused image improves both subjective and objective evaluation indicators, relative to the source image, and can better preserve edge information and help to improve the accuracy of target recognition. This study provides a reference for the comprehensive application of multi-dimensional optical information in power inspection.

Parallel Elastic Self-Alignment Mechanism Enhances Energy Efficiency and Reduces Misalignment in a Powered Knee Exoskeleton.

OBJECTIVE: This paper aims to enhance exoskeleton compliance during locomotion assistance by reducing misalignment and to improve energy efficiency by overcoming the limitations posed by the bulky structure of powered rigid exoskeletons. METHODS: A novel compliant knee exoskeleton, featuring a parallel elastic self-alignment mechanism, has been developed and structurally optimized. The exoskeleton uses adaptive oscillators to determine the wearer's gait phase and provides real-time assistance to the knee joint. RESULTS: Bench tests demonstrate that the parallel elastic mechanism significantly reduces the driving torque of the knee exoskeleton. Performance evaluations reveal that, compared to a commercial orthosis, the root-mean-square of knee angle error, joint misalignment, and unexpected interaction forces are reduced by 16.5 ± 11.3%, 23.3 ± 4.9%, and 17.7 ± 1.3%, respectively. Gait intervention experiments show reductions in average and maximum muscle activity of the knee joint by 7.6 ± 4.9% and 23.2 ± 5.7%, respectively. Additionally, the exoskeleton decreases negative work performed by the knee joint and the total lower limb by 22.7% and 8.6%, respectively. CONCLUSION: The parallel elastic self-alignment mechanism effectively mitigates joint misalignment, while the parallel springs offer partial gravity compensation, thereby enhancing both the energy efficiency and locomotion assistance of the exoskeleton. SIGNIFICANCE: The parallel elastic self-alignment mechanism effectively addresses both misalignment and energy efficiency challenges in powered exoskeletons, providing valuable insights for future design improvements.

A new triboelectric nanogenerator based on a multi-material stacking structure achieves efficient power conversion from discrete mechanical movement.

Due to its invaluable potential in discrete mechanical energy collection, TENG (triboelectric nanogenerator) is considered to satisfy the power requirements of intelligent electronic devices and drive the development of the Internet of Things (IoT). Nowadays, the promotion of TENGs has been hindered due to the limitation of their output performance and service life. Herein, a brand new triboelectric nanogenerator based on a multi-material stacking structure is proposed. By stacking various triboelectric materials in a specific order, a special charge balance state could be achieved inside the system such that the conductive layer generates more induced charges, and the output performance is significantly enhanced. Besides, due to the usage of the electropositive elastomer PU (polyurethane sponge), the design also effectively alleviates abrasion on the contact surface and adjusts its own output according to different compression environments. The experimental results show that the stacked PTFE/FKM/PU TENG (PFP-TENG) presents a more than 50% increase in transferred charge and almost 5 times the current output compared with the general contact-separation type TENG. When connected to the application circuit, the maximum output power reached 10.2 W m-2 and 145.2 W m-3, and more than 1400 LEDs could be easily lit. Finally, the PFP-TENG was also used to collect mechanical energy from simple motion and realize considerable power generation. This study not only provides new ideas for the design of TENGs by reasoning the theoretical model but also presents improved output performance, thus exemplifying the strong potential of this design in developing a power-generation device that can collect discrete mechanical energy.

A Stacked FKM/PU Triboelectric Nanogenerator for Discrete Mechanical Energy Harvesting.

To combine the advantages of elastic and nonelastic triboelectric materials, this work proposes a new type of triboelectric nanogenerator (TENG) based on stacking -the stacked FKM/PU TENG. By stacking the elastomer polyurethane (PU) and the nonelastomer fluororubber (FKM), the FKM/PU TENG combines the inherent triboelectric characteristics of both materials and the unique elasticity of PU to achieve an output performance that is much higher than that of the FKM-TENG or the PU-TENG. The maximum instantaneous open-circuit voltage and short-circuit current of the FKM/PU TENG reach 661 V and 71.2 µA, respectively. Under the limiting conditions of 3 Hz and maximum compression, this device can attain a maximum power density of 49.63 W/m3 and light more than 500 LEDs. Therefore, stacking materials with different properties gives the FKM/PU TENG high output performance and great application potential, which can contribute to future development of discrete mechanical energy harvesting.