Recent Patents on Mechanical Engineering - Volume 16, Issue 1, 2023

Background: Bionics applied to micropumps is the most advanced technology currently accessible. The widespread use of microfluidic transport technology in fields like drug delivery and chemical analysis has made it a current research hotspot. As a core component in the microfluidic transport process, the micropump is a key part of the breakthrough. Objective: The study aims to summarize the engineering applications of various bionic micropumps in order to serve as a resource for future research in related fields. Methods: Study the application of bionic technologies that mimic fish tail fin oscillation, female mosquito blood sucking, honeybee nectar ingestion, and plant stomatal transpiration in various micropumps by sorting out typical research results. Results: This study examines the current state of bionic micropumps research and problems, as well as anticipates the future direction of functional bionic technology in micropumps. Conclusion: In this paper, we review the functional bionic technology used in micropumps and study some of the physiological processes of specific creatures from a biological perspective. We also show how effectively using bionic design can enhance the overall functionality of micropumps. However, man's knowledge of the natural world is still very limited. Functional bionics technology will shine in the area of engineering application as a result of the investigation of materials, processing technology, and biological principles.

Abrasive water jet (AWJ) machining process is one of the most sought-after machining technologies for the processing of advanced hard-to-cut materials. It involves parameters, such as abrasive size, shape, density, pressure, standoff distance (SOD), abrasive concentration, feed rate, etc., which govern the quality of machining. It is very crucial to understand the influence of these parameters on the quality attributes. Due to the complex nature of the process that involves complex process parameters, the accurate prediction of response by experimental methods is difficult. In this scenario, numerical methods are helpful in understanding the mechanisms of material removal. Thus, a comprehensive summary of these research trends is needed. In this article, a bibliometric analysis is carried out on scientific publications pertaining to AWJ machining (AWJM) using numerical simulation tools. Citation and bibliographic coupling analyses have been carried out to identify the current research trends, the important journals, authors, institutions, and countries engaged in research on AWJM using numerical simulation. The analysis revealed Shandong University to have the maximum number of affiliated researchers working in this area. The International Journal of Machine Tools and Manufacture was the leading journal based on CiteScore, SJR rank and SNIP ranks, and the largest volume of articles was published by this journal. The critical topics of research and international collaborative opportunities were identified through the analysis of keywords, Sankey and network diagrams. The present article would be valuable for academia and industry, aiding them in updating their knowledge on the latest developments in AWJM.

Background: Machine vision has been used in the industrial automation system for a long time. It also plays a significant role in the field of human behavior recognition. Behavior recognition based on machine vision, such as object tracking, motion detection and crime recognition, greatly broadens the application field of artificial intelligence and has a good application prospect. Objective: We summarize the latest applications of various machine learning algorithms in human behavior recognition, and analyze the accuracy of various algorithms combined with data sets, so as to provide reference for researchers in related fields. Methods: By sorting out the typical research results, briefly expound on the application of machine learning in the field of behavior recognition in recent years. This review focuses on the Two Stream Network structure, TSN structure, LSTM network and C3D network. Results: This paper analyzes the principles, advantages and disadvantages of various human behavior recognition methods, and briefly discusses the future development direction. Conclusion: The wide application prospect of behavior recognition and detection makes it a hot research direction in the field of computer vision, and greatly improves the accuracy of complex human motion recognition combined with deep learning. However, it still faces many difficulties, such as insufficient discrimination of violence attributes, difficult collection, verification of special action data and insufficient hardware computing resources, etc.

Background: Nutation face gear transmission is a patent about a new type of transmission based on meshing between two face gears. It replaces spur gear with internal face gear to form a “faceface” meshing gear pair and actualizes its deceleration function by combining the nutation principle, which has the advantages of both face gear and nutation drive. Objective: The purpose of this paper is to study the designing and manufacturing of a nutation face gear reducer to derive the force calculation formulas of the face gear, input shaft and bearings, calculate the contact stress of tooth surface and bending stress of tooth root, determine the basic parameters of the prototype, and analyze the processing points for the core parts of the prototype. Methods: Using the dynamic meshing force analysis method by combining it with modern digital design and manufacturing methods, the designing and manufacturing of a nutation face gear reducer are studied. Results: In the theoretical calculation, the maximum contact stress of the fixed side tooth surface is about 433MPa, and the average contact stress is about 345MPa; the maximum contact stress of the tooth surface on the rotating side is about 579MPa, with an average of about 502MPa; the comparison of which with the finite element analysis results verifies the theoretical calculation results. Conclusion: The dynamic meshing force analysis method of nutation face gear transmission is deduced and given. Based on this, gear tooth surface transient contact stress and tooth root bending stress are calculated.

Background: The wear of wheelsets on curves has always been a problem for rail vehicles; it is of great significance to research and develop radial components with excellent curve negotiating performance. Objective: This paper aims to study and design a wheelset with excellent curve negotiating performance to reduce wear on the flange. In addition, the dynamic simulation performance of the wheelset is studied. Methods: The wheel is divided into the flange part and the tread part; bearings are mounted between the two, allowing them to rotate at differential speeds, while the tread part maintains a rigid connection with the axle. Modeling and dynamics simulation of the wheelset is carried out by SOLIDWORKS and SIMPACK. Results: Based on the Archard wear model, it is found that the flange wear amount of the designed wheelset is significantly reduced compared with the traditional wheelset. Conclusion: The results show that the structural design of the wheelset is reasonable, has good curve negotiating performance, and can greatly reduce the wear of the flange; however, there is still room for further optimization of the structural design.

Background: Accurate power load forecasting is significant in ensuring power load planning, reliability and economical operation. The traditional power load is easily affected by climate, environment, data type and other factors, resulting in the problem of poor forecasting accuracy. Therefore, it is necessary to study power load forecasting. Objective: Through machine learning, dimension reduction method and intelligent optimization algorithm, the accuracy of load forecasting is improved. Methods: In order to fully extract load information and improve the accuracy of short-term load forecasting for campus electricity, an improved combination of orthogonal dimensionality reduction and Bilstm is proposed to optimize the hyperparameters in BiLSTM using an improved gray wolf algorithm. Firstly, using the advantages of principal component analysis (PCA) and Locality Preserving Projection (LPP) to maintain the global and local structure of the data, respectively, the Orthogonal PCA-LPP (OPCA-LPP) dimensionality reduction method is proposed to reduce the dimensionality of the original multidimensional data. Finally, the dimensionality-reduced data is used as the input of BiLSTM and optimized by the improved Gray Wolf algorithm, which can enhance the model's prediction capability and thus achieve accurate prediction of short-term electric load. Results: The Mae and RMSE of this paper are 1.6585 and 1.7602, respectively. The results show that the method proposed in this paper is reasonable. Conclusion: This method is applied to power load forecasting. The comparative experimental results show that this method reduces the dimension of data input, simplifies the complexity of network input data, and improves load forecasting accuracy. Compared with other methods, it can improve load forecasting accuracy and provide a basis for formulating reasonable power grid operation modes and balanced power grid dispatching.

Background: Accurate tracking of train speed is the key link to ensure the stability, accuracy and safety of automatic train operation. To solve the influence of multi-information of freight train speed control system on tracking accuracy, the information fusion preview control freight train speed tracking control system is constructed. With the increase in the speed and capacity of freight trains, the safety, energy efficiency and intelligent operation of train operation have become increasingly important. Automatic freight trains operation can replace manual operation with automated control systems, which can guarantee the safety of train operation, and improve operational efficiency and reduce operational energy consumption. Objective: Solve the problem of tracking accuracy and stability deterioration caused by multiinformation of freight train. Methods: Global navigation satellite system, inertial navigation system and speed measuring motor are selected to construct a speed fusion measurement model by using loosely coupled integrated navigation and improved entropy weight method. The information quantity of performance index and control quantity in preview control is calculated, and the controlled quantity of information fusion optimal preview control is obtained. Results: The average tracking error of the multi-source information fusion preview controller is 0.038m/s, which is 49% lower than that of the control experiment. Conclusion: Multi-source information fusion preview controller can effectively reduce the tracking error of freight train speed tracking system and improve the accuracy of automatic freight trains operation.