Performance analysis of a novel flat lay-type synthetic jet pump with Y-shaped jet chamber.

Recently, synthetic jet pumps have been expected to be used in electronic heat dissipation devices due to the vortex suction phenomenon for transporting fluids. Aiming to improve the delivery ability of the jet pump to output fluid continuously, a novel flat lay-type synthetic jet pump (FLTSJP) with a Y-shaped jet chamber is proposed in this paper. Based on the synthetic jet effect, the pump chamber continuously outputs fluid in one cycle. The output performance of FLTSJP is theoretically analyzed to be affected by the outlet cone angle. The one-cycle flow mechanism of the fluid in the Y-shaped jet chamber is simulated. FLTSJP is manufactured, and a test system is built. Experiments show that the Y-shaped jet chamber effectively improves the output performance. The optimum flow rate and outlet pressure were both reached at 160 V and 40 Hz, which were 20.63 ml/min and 333.43 Pa, respectively. This FLTSJP effectively improves the output performance of synthetic jet pumps and provides a new research concept of water-cooled devices for electronic heat dissipation.

Silicon-Based Zipper Photonic Crystal Cavity Optomechanical System for Accelerometers.

The cavity optomechanical accelerometer based on photonic crystal microcavities combines mechanical resonators with high-quality factor photonic crystal cavities. The mechanical vibrator is sensitive to weak force/displacement in mechanical resonance modes, which can achieve extremely low noise levels and theoretically reach the standard qillatum noise limit. It is an important development direction for high-precision accelerometers. This article analyzes the principle and structural characteristics of a zipper type photonic crystal cavity optomechanical accelerometer, and designs a silicon-based zipper type photonic crystal cavity and mechanical vibrator structure applied to the accelerometer. The influence of the structural parameters of the zipper cavity on the optical Q factor was analyzed in detail. The resonant frequency of the optical cavity was controlled around 195 THz by adjusting the structural parameters, and the mechanical resonance characteristics of the mechanical vibrator and the optical cavity were analyzed. The effective mass of the optical cavity was 30 pg, and, with the addition of the mechanical vibrator, the effective mass was 3.1 ng. The optical mechanical coupling rate reached the GHz/nm level, providing guidance for the manufacturing and characterization of silicon-based zipper cavity accelerometers.

Performance study of a valveless piezoelectric pump with built-in semi-arc bluffbody antique tower channel.

According to the bluffbody bypass effect, the irregular bluffbody can be used to improve the valveless piezoelectric pump. This paper designs a semi-arc bluffbody based on the bluffbody bypassing principle to alleviate the phenomenon of fluid backflow. The fluid passes through the shape of the antique tower to further enhance pumping efficiency. A positive fluid flow mechanism in the pump cavity is theoretically derived. The simulation of the velocity and pressure distribution in the tower-shaped channel of the pump cavity leads to the conclusion that the forward flow has better performance than the reverse flow, and the correctness of the theory is also verified. Experiments further proved that the volume of fluid in the forward direction was reduced by 10.8% when compared to the reverse direction. The study of the height of different semi-arc bluffbody and the angle of the tower trough shows that as the height and angle increase, the flow rate grows first and then reduces. The maximum flow rate is 243.83 ml/min when the bluffbody height is 4 mm and the channel angle is 20° (220 V, 85 Hz).

An Improved ResNet-1d with Channel Attention for Tool Wear Monitor in Smart Manufacturing.

Tool wear is a key factor in the machining process, which affects the tool life and quality of the machined work piece. Therefore, it is crucial to monitor and diagnose the tool condition. An improved CaAt-ResNet-1d model for multi-sensor tool wear diagnosis was proposed. The ResNet18 structure based on a one-dimensional convolutional neural network is adopted to make the basic model architecture. The one-dimensional convolutional neural network is more suitable for feature extraction of time series data. Add the channel attention mechanism of CaAt1 to the residual network block and the channel attention mechanism of CaAt5 automatically learns the features of different channels. The proposed method is validated on the PHM2010 dataset. Validation results show that CaAt-ResNet-1d can reach 89.27% accuracy, improving by about 7% compared to Gated-Transformer and 3% compared to Resnet18. The experimental results demonstrate the capacity and effectiveness of the proposed method for tool wear monitor.

MSFT-YOLO: Improved YOLOv5 Based on Transformer for Detecting Defects of Steel Surface.

With the development of artificial intelligence technology and the popularity of intelligent production projects, intelligent inspection systems have gradually become a hot topic in the industrial field. As a fundamental problem in the field of computer vision, how to achieve object detection in the industry while taking into account the accuracy and real-time detection is an important challenge in the development of intelligent detection systems. The detection of defects on steel surfaces is an important application of object detection in the industry. Correct and fast detection of surface defects can greatly improve productivity and product quality. To this end, this paper introduces the MSFT-YOLO model, which is improved based on the one-stage detector. The MSFT-YOLO model is proposed for the industrial scenario in which the image background interference is great, the defect category is easily confused, the defect scale changes a great deal, and the detection results of small defects are poor. By adding the TRANS module, which is designed based on Transformer, to the backbone and detection headers, the features can be combined with global information. The fusion of features at different scales by combining multi-scale feature fusion structures enhances the dynamic adjustment of the detector to objects at different scales. To further improve the performance of MSFT-YOLO, we also introduce plenty of effective strategies, such as data augmentation and multi-step training methods. The test results on the NEU-DET dataset show that MSPF-YOLO can achieve real-time detection, and the average detection accuracy of MSFT-YOLO is 75.2, improving about 7% compared to the baseline model (YOLOv5) and 18% compared to Faster R-CNN, which is advantageous and inspiring.

An Improved Feature Selection Method Based on Random Forest Algorithm for Wind Turbine Condition Monitoring.

Feature selection and dimensionality reduction are important for the performance of wind turbine condition monitoring models using supervisory control and data acquisition (SCADA) data. In this paper, an improved random forest algorithm, namely Feature Simplification Random Forest (FS_RF), is proposed, which is capable of identifying features closely correlated with wind turbine working conditions. The Euclidian distances are employed to distinguish the weight of the same feature among different samples, and its importance is measured by means of the random forest algorithm. The selected features are finally verified by a two-layer gated recurrent unit (GRU) neural network facilitating condition monitoring. The experimental results demonstrate the capacity and effectiveness of the proposed method for wind turbine condition monitoring.

Design and Modification of a High-Resolution Optical Interferometer Accelerometer.

The Micro-Opto-Electro-Mechanical Systems (MOEMS) accelerometer is a new type of accelerometer that combines the merits of optical measurement and Micro-Electro-Mechanical Systems (MEMS) to enable high precision, small volume, and anti-electromagnetism disturbance measurement of acceleration, which makes it a promising candidate for inertial navigation and seismic monitoring. This paper proposes a modified micro-grating-based accelerometer and introduces a new design method to characterize the grating interferometer. A MEMS sensor chip with high sensitivity was designed and fabricated, and the processing circuit was modified. The micro-grating interference measurement system was modeled, and the response sensitivity was analyzed. The accelerometer was then built and benchmarked with a commercial seismometer in detail. Compared to the previous prototype in the experiment, the results indicate that the noise floor has an ultra-low self-noise of 15 ng/Hz1/2.

A rapid performance evaluation approach for lower mobility hybrid robot based on gravity-center position.

This article develops a rapid performance evaluation approach for lower mobility hybrid robot, which provides guidance for manipulator evaluation, design, and optimization. First, a general position vector model of gravity center for the lower mobility hybrid robot in the whole workspace is constructed based on a general inverse kinematic model. A performance evaluation index based on gravity-center position is then proposed, where the coordinates pointing to the supporting direction are selected as the evaluation index of the robot performance. Furthermore, the credibility of the evaluation approach is verified from a 5-DOF hybrid robot (TriMule) by comparing with the condition number and the first natural frequency. Analysis results demonstrate that the evaluation index can not only reflect the performance spatial distribution in the whole workspace but also is sensitive to the performance difference caused by mass distribution. The proposed performance evaluation approach provides a new index for the rapid design and optimization of the cantilever robot.

Nanostructure Nickel-Based Selenides as Cathode Materials for Hybrid Battery-Supercapacitors.

Supercapacitors (SCs) have attracted many attentions and already became part of some high-power derived devices such as Tesla's electric cars because of their higher power density. Among all types of electrical energy storage devices, battery-supercapacitors are the most promising for superior performance characteristics, including short charging time, high power density, safety, easy fabrication procedures, and long operational life. An SC usually consists of two foremost components, namely electrode materials, and electrolyte. The selection of appropriate electrode materials with rational nanostructured designs have resulted in improved electrochemical properties for high performance and has reduced the cost of SCs. In this review, we mainly spotlight the nickel-based selenides nanostructured which applied as high-performance cathode materials for SCs. Different nickel-based selenides materials are highlighted in various categories, such as nickel-cobalt-based bimetallic chalcogenides and nickel-M based selenides. Also, we mentioned material modification for this material type. Finally, the designing strategy and future improvements on nickel-based selenides materials for the application of SCs are also discussed.

The diagnosis of gallbladder agenesis: two cases report.

Congenital absence of the gallbladder is an extremely rare embryological aberration that is frequently mistaken for cholecystolithiasis; the aim of this study is to investigate the diagnostic methods for agenesis of the gallbladder. Two surgically confirmed gallbladder agenesis cases in our hospital and 75 cases of gallbladder agenesis reported in the literature in China were reviewed. It is extremely difficult to make a correct diagnosis of gallbladder agenesis before operation. When suspected, it may be confirmed by ERCP and MRCP. Interoperate, if no gallbladder can be found during laparoscopy, open surgery should be immediately performed Clinician's understanding of this disease is of great help in avoiding unnecessary surgical exploration and minimizing the risk of complication. Patients with gallbladder agenesis can be classified into two new types, I: Symptomatic, II: Asymptomatic. Type I can be divided into two subtypes: I a with fatal malformations and I b without fatal malformations.