Recent Patents on Engineering - Volume 17, Issue 6, 2023

Background: With the continuous development of the modern machinery industry, the technical level of rotating machinery is increasing. As a key component of the bearing system and power transmission system in rotating machinery, the hydrostatic bearing has higher performance requirements in all aspects. When the system is working normally, due to the shearing effect of the lubricating oil driven by the spindle rotation, a large amount of heat will be generated. The system will generate thermal effects on the bearing through heat accumulation and heat conduction. The thermal effect will directly reduce the viscosity of the hydraulic oil, affecting the bearing capacity. Seriously, it will cause thermal deformation of the parts, which will affect the normal operation of the bearing, and even cause an accident. Objective: Analysis and discussion on the thermal effect of hydrostatic bearing in recent years. Methods: More than 70 recently published patents, as well as journal and conference papers on hydrostatic bearings, were reviewed. The results of temperature fields, pressure fields, deformation, lubrication, bearing capacity and friction were studied. Results: This review summarizes the research results from three aspects: the influencing factor of temperature rise, the influence of temperature rise on bearing structure and performance, and the effective control of temperature rise. Conclusion: The relevant research methods are analyzed. The problem of thermal effect of hydrostatic bearing is summarized and prospected, and the future development can be expected.

Perception-based navigation systems have become more popular in robotic applications such as autonomous moving vehicles in hospitals, logistics, packing and forwarding, mines, military, defense, consumer robots, building surveillance, rescuing and carrying a child or physically challenged people, and so on, due to the need, advanced development, and large influence. To improve positioning, localization, and path planning on obstacle-free trajectories, several navigation designs have been developed. In this study, we attempt to analyze various navigation methods and technologies applied by mobile robots in various applications. On paths without obstacles, a number of navigation designs have been created to enhance positioning, localization, and path planning. An overview of many navigation technologies is given in this article. The paper focuses on Measurand- based navigation of mobile robot applications in a diverse environment by taking into account previous research works. Additionally, there is a comparison of technologies, methodologies, applications, algorithms for error reduction, and different kinds of perception systems, in addition to metrics like accuracy and usability. This limited study focuses on the integration of an antenna with an IMUbased navigation system that is suited for all environments, as well as some future trends to detect to aid in the profound-implication of navigation system enhancement in robotic applications.

Background: The dynamic viscosity-temperature characteristics of lubricants are the main factors used to determine the oil film thickness and carrying capacity. There are few studies on the factors affecting the dynamic viscosity-temperature characteristics of lubricating oils and the dynamic viscosity-temperature model. Objective: This research aims to analyse the influences of lubricating oil type and initial kinematic viscosity on dynamic viscosity-temperature characteristics and present a new dynamic viscositytemperature model. Methods: The characteristic curves of dynamic viscosity versus temperature of polyol ester oil, paraffinic mineral oil, and five types of PAO (poly α-olefin) oils with different initial viscosities were obtained by using a kinematic viscosity test device and a density test device. The influences of lubricating oil type and lubricating oil viscosity on dynamic viscosity-temperature characteristics were analysed. A new dynamic viscosity-temperature model was presented based on our patent technology and repeated verification. Results: Viscosity-temperature curves of three different types of lubricating oils and viscositytemperature curves of PAO oils with different initial kinematic viscosities were obtained. A new dynamic viscosity-temperature model η = A x e^(-T/n) + η0 was proposed. Conclusion: The dynamic viscosity-temperature characteristics of lubricating oils are not only determined by the type of oils but also determined by the initial kinematic viscosity. The variation of dynamic viscosity of lubricating oils with temperature in the scope of -40~110°C can be described by the following viscosity-temperature model: η = A x exp ^(-T/n) + η0 which can be used in a wider temperature range than the existing models.

Background: Depression is a mental disorder that often negatively impacts the actions and feelings of the affected person. No laboratory tests are available to detect and properly diagnose depression. Presently, the detection of depression is done based on standardized questionnaires like the Diagnostic and Statistical Manual of Mental Disorders-fifth edition (DSM-V) and Hamilton Depression Rating Scale (HAM-D), which are subjective. Objective: The purpose of the study is to propose a framework for more accurate detection of depression from EEG signals using only three channels, which makes the system portable as well as efficient. Methods: In this study, we propose a classification model using EEG signal with the help of an Adaptive Neuro Fuzzy Inference System optimized by a nature-inspired algorithm. The proposed model is efficient, accurate, and portable as the features are extracted from only three channels, namely, Fp1, Fp2, and Fz. The three Data Channel (3EDANFIS) Adaptive Neuro Fuzzy Inference System (ANFIS) for detection of depression as well as three variants of Hybrid ANFIS - Adaptive Neuro Fuzzy Inference System-Genetic Algorithm (ANFIS-GA), Adaptive Neuro Fuzzy Inference System- Particle Swam Optimization (ANFIS-PSO) and Adaptive Neuro Fuzzy Inference System-Firefly Algorithm (ANFIS-FA) has been analyzed in this study. The features extracted are delta, theta, alpha, and beta and their corresponding sub-bands delta1, delta2, theta1, theta2, alpha1, alpha2, beta1, and beta2. Genetic Algorithm (GA), Particle Swam Optimization (PSO), and Firefly Algorithm (FA) are all nature-inspired metaheuristic algorithms that are used to optimize ANFIS by adapting the premise and consequent parameters. Results: The analysis showed that the GA and FA performed equally well in optimizing ANFIS with the highest accuracy of 83.33% using delta1 power as well as delta power. The overall accuracy of the ANFIS-GA was found to be higher than that of the ANFIS-PSO, ANFIS-FA, and ANFIS. It was also found that the sub-band classification accuracy was higher than that of the band itself for delta, theta, and alpha bands. In the case of ANFIS, ANFIS-GA, ANFIS-PSO, and ANFIS- FA, delta1 was found to be having higher accuracy than delta power, theta1 was found to be having higher accuracy than theta power, and both alpha1 and alpha2 showed higher accuracy than alpha power. Conclusion: The use of only three EEG channels for data recording makes our technique to be more feasible, portable, convenient, and faster and hence can act as an adjunct tool for psychiatrists in the future.

Background: With the development of technology, the data amount has increased significantly. In data processing, the multi table query is the most frequent operation. Because the join keys cannot correspond one by one, there will be much redundant data transmission, resulting in a waste of network bandwidth. Objective: In order to solve the problems of network overhead and low efficiency, this paper proposes a heuristic multi table join optimization method. By sharing information, the unconnected tuples are eliminated so as to reduce the amount of data transmitting. This shortens response time and improves execution performance. Methods: Firstly, the join key information of one table is compressed by the algorithm to make the filtered information for sharing. Then, the concurrent execution is controlled according to the pancake parallel strategy. Finally, the selection strategy of multi table join order is proposed. Results/Discussion: The experiments show that the proposed algorithm can filter a large amount of useless data and improve query efficiency. At the same time, the proposed algorithm reduces a lot of network overhead, improves the algorithm performance, and better solves the problem of low efficiency of multi table join. Conclusion: This paper introduces the heuristic strategy to optimize the algorithm, so that it can perform the join tasks in parallel, which further improves the performance of multi table join. The algorithm creatively combines heuristic data filtering, which greatly improves the quality of data processing. The algorithm is worth popularizing and applying.

Background: Corn harvesting is an important part of the entire corn production process. Corn harvester power, turning radius and dehulling device will directly affect harvest efficiency and the quality of harvested corn. Obtaining better performance peeling device with strong power and minimum turning radius is the research direction in this field. Objective: This paper summarizes the patents of the walking system of corn harvesters at home and abroad in recent years, and introduces the characteristics and development of knapsack harvesters, trailed harvesters and self-propelled harvesters, such as power, turning radius and artificial intelligence. summarize its development trend, and provide reference for the development of various aspects of crop harvester. Methods: This paper reviewed the research status of the corn harvester walking system in recent years, and discussed the structure types and applications of various harvester walking systems. Results: By summarizing the patents of the walking system of the corn harvester, this paper obtains the current patent application status, analyzes the main problems in its development, and discusses the problems existing in the walking system of the harvester and the future research direction. Conclusion: The running device of the existing harvester needs to be further improved in terms of reliability, power system, turning radius, etc. The patent of the walking device of the harvester is yet to be developed. With the application of GPS, sensing and detection, information processing, automatic control and other technologies in the field of harvesting, the mechanized corn harvesting is gradually developing towards intelligence and automation.

Background: Based on the high-speed operation of the spindle, the influence of the rotation accuracy of the spindle on the system will increase with the increase of the rotation speed. Therefore, how to predict rotation accuracy becomes very important for mechanical equipment based on the spindle. Objective: To summarize the classification and characteristics of the spindle rotation accuracy detection device to predict future development. Methods: The current status of various representative patents related to spindle rotation accuracy testing equipment is analyzed. According to the characteristics of testing equipment, the development level of existing testing equipment in error separation and high-speed detection of the spindle is analyzed, and the latest patented technology is expounded and compared. Results: The structure of the spindle rotation accuracy detection device is analyzed and compared, and the typical characteristics are summarized. The problems existing in the detection of spindle rotation accuracy are analyzed, and their development trend is prospected. Conclusion: It is obtained that the contact-type rotary accuracy testing equipment is generally suitable for static measurement, the single-probe and multi-probe testing equipment can be basically satisfied with the measurement, and the optical testing equipment can be widely used in the measurement under the high-speed rotation of the spindle. There is room for further development in the dynamic load detection of the spindle.

Background: While the CNC (Computerised Numerical Control) machine spindle is driving the tool to cut the workpiece, impurities such as cutting fluid splash, metal chips, or metal dust tend to enter the internal system of the spindle. Optimization of the spindle sealing design can significantly improve the durability of the motorized spindle. A high-speed motorized spindle is the primary heat source of CNC machine tools. Under current conditions, a cooling and lubrication system is the main measure to control the heat of a high-speed motorized spindle. Objectives: This paper introduces the current research progress in bearing lubrication and new spindle sealing structures. Methods: The research on bearing lubrication is sorted by comparing the relevant literature on bearing lubrication; some sealing structures are introduced by giving examples of patents on motorized spindle seals. Results: This paper reviews the bearing lubrication research and spindle sealing structure and provides an outlook on the future development of bearing lubrication technology and spindle sealing structure. Conclusion: The High-speed motorized spindle is the primary heat source of CNC machine tools. Bearing lubrication can effectively control the motorized spindle heat; a motorized spindle sealing structure can prevent impurities from causing damage to the internal parts of the spindle and improve the service life of the motorized spindle.

Background: With the increasing number of patients with cardiovascular and respiratory diseases, medical stents are needed to reshape the blood vessels and trachea to restore their function. Due to its high degree of standardization, the existing medical stent manufacturing technology is mature and suitable for most groups. However, conventional medical stents are not suitable for every patient due to the patients’ individual differences and other reasons. Hence, patients need custom medical stents. Therefore, 3D printing technology with high customization function as an emerging stent manufacturing method has attracted much attention in recent years. Objective: By solving the problem of poor matching rates between traditional medical stents and human body channels, 3D printing technology will continue to develop in the medical stent manufacturing field. Methods: This study traces the representative patents related to the vascular stent and tracheal stent manufacturing based on 3D printing technology. Results: Through the analysis of numerous patents about 3D printed vascular stents and tracheal stents, the reasons for the mismatched medical stent specifications and low efficiency are summarized. The challenges in the development of 3D printing medical stents are discussed. Conclusion: Research on the 3D printing of medical stents is conducive to improving patients’ suitability and medical stent implantation and reducing the time cost. More patents will be invented in the future.

Background: Vision-based dynamic target detection is an important research topic in computer vision, which is the basis for intelligent behavior analysis and event detection. Further research on dynamic target detection methods can help improve target detection and tracking mechanisms while also driving the development of other related fields. Hence, conducting a review on vision-based dynamic target detection is very significant. Objective: There are many methods for dynamic target detection. This paper introduces their classification, characteristics, advantages, disadvantages and development trends. Methods: This paper reviews recent patents and representative articles on dynamic target detection in simple visual and complex contexts. The crucial methods of these references are introduced from the aspects of algorithm, innovation, and principle. Results: This paper analyzes and compares the existing dynamic target detection methods, summarizes their characteristics, main applications, and advantages and disadvantages in the current development stage, and discusses the future development and potential problems of dynamic target tracking methods. Conclusion: Vision-based dynamic target detection can accurately extract moving targets from the scene. Due to its inherent complexity, each detection method has its advantages and disadvantages in specific scenes. Currently, the research mainly focuses on the real-time robustness and accuracy of the algorithm, which needs to be further improved in the aspects of algorithm innovation, multialgorithm fusion, multi-target recognition, and algorithm adaptability. Therefore, relevant research patents and documents should be put forward, initiating the future development trend.

Background: Virtualization adequately maintains increasing requirements for storage, networking, servers, and computing in exhaustive cloud data centers (CDC)s. Virtualization assists in gaining different objectives like dedicated server sustenance, fault tolerance, comprehensive service availability, and load balancing, by virtual machine (VM) migration. The VM migration process continuously requires CPU cycles, communication bandwidth, memory, and processing power. Therefore, it detrimentally prevails over the performance of dynamic applications and cannot be completely neglected in the synchronous large-scale CDC, explicitly when service level agreement (SLA) and analytical trade goals are to be defined. Introduction: Live VM migration is intermittently adopted as it grants the operational service even when the migration is executed. Currently, power competence has been identified as the primary design requirement for the current CDC model. It grows from a single server to numerous data centres and clouds, which consume an extensive amount of electricity. Consequently, appropriate energy management techniques are especially important for CDCs. Methods: This review paper delineates the need for energy efficiency in the CDC, the systematic mapping of VM migration methods, and research pertinent to it. After that, an analysis of VM migration techniques, the category of VM migration, duplication, and context-based VM migration is presented along with its relative analysis. Results: The various VM migration techniques were compared on the basis of various performance measures. The techniques based on duplication and context-based VM migration methods provide an average reduction in migration time of up to 38.47%, data transfer rate of up to 51.4%, migration downtime of up to 36.33%, network traffic rate of up to 44% and reduced application efficiency overhead up to 14.27%. Conclusion: The study aids in analyzing threats and research challenges related to VM migration techniques which ultimately help in exploring future research directions that would help aspiring cloud professionals.

Background: The trachea is an essential part of the respiratory system. Lesions such as inflammatory granulomas cause Bronchial stenosis, which may be life-threatening. Tracheal stent placement is vital for treating airway stenosis, relieving dyspnea, and improving symptoms. Objective: This paper reviews the patents of tracheal stent placement and removal and auxiliary devices for diagnosis in recent years (from 2007 to the present) and introduces the characteristics and development of tracheal stent implantation, treatment, and assistive removal devices. In order to meet the need for more rapid operation and cause less harm to the human trachea, the structure of the tracheal stent surgical device needs to be improved continuously. Methods: This paper summarizes the research status of tracheal stent placement and removal and auxiliary devices for diagnosis and treatment in recent years and discusses the structural types and applications of tracheal stent auxiliary devices. Results: This paper summarizes the patent application of tracheal stent placement and removal and auxiliary devices for diagnosis and treatment at the present stage. This paper analyzes the main problems in its development and discusses the solutions to the problems and the future research direction. Conclusion: Tracheal stent surgical devices need further improvement in mechanical design, control strategy, etc. Tracheal stent surgical devices should be developed into universal, semiautomatic, and multi-functional machines. The relevant patents of the auxiliary device of the tracheal stent need to be developed.

As the demand for jujubes grows, so does the acreage of jujubes. However, the main method of jujube picking is traditional manual picking, which is the most time-consuming and labor- intensive in the production chain. Through the analysis and discussion of the patents on the jujube harvester, some valuable conclusions are drawn to predict the research and development of the jujube harvester in the future. An overview of various representative patents of the current jujube harvester is provided in this paper. A large number of patents of jujube harvesting devices have been summarized, the characteristics of these patents have been analyzed and compared, and the further development trend of jujube harvesting machines has been developed. The research on the multifunction, intelligence and versatility of the jujube harvester is helpful to solve the problems of low efficiency, low quality, and poor versatility of the jujube harvester.

With the increasing severity of ecological and environmental problems, determining how to develop a low-carbon economy has become the focus of scholarly research. As a necessary component of a low-carbon economy, the low-carbon consumption mode plays an important role in the sustainable development of all countries. In this paper, the existing research on the traditional and low-carbon consumption modes is sorted out, the differences between the two consumption modes are compared and analyzed, and relevant suggestions for the low-carbon transformation of the consumption mode are put forward. To put forward the path from the traditional consumption mode of residents to the low-carbon consumption mode. In order to minimize the harm to the ecological environment, the low-carbon transformation of the consumption mode should be actively carried out. The low-carbon transformation of the consumption mode of residents can be realized from three perspectives, namely cultivating the low-carbon consumption awareness of residents, establishing and perfecting the supervision system, and guiding the low-carbon production of enterprises.

The Internet of things (IoT) is widely used for communication between portable and intelligent heterogeneous devices, like laptops, smartphones, computers, etc. IoT networks are popular in the modern era because they allow data to be exchanged anywhere when connected to the internet. IoT networks have several challenges, including those related to routing, connectivity, privacy, security, and other issues. The major challenge is routing in terms of choosing the best route for sharing data in IoT networks; IoT routing algorithms use more time and energy. In this paper, we review relevent literature and patents and also various routing approaches are categorized into groups, like multicast, clustering, emergency application, traffic, location, tree, and residual energy based approach, and they are compared based on several parameters, like energy consumption, network lifetime, path length, packet delivery ratio, and network latency. In terms of performance metrics, like energy consumption, network lifetime, reliability, efficiency, and packet delivery ratio, the comparison shows that Routing Protocol for Low Power and Lossy Networks (RPL), Efficient Treebased Self-organizing Protocol (ETSP), Collection Tree Protocol (CTP), and Fast Multi-constrained Multicast Routing Algorithms (FAMOUS) are the best protocols. The best approach is a tree-based one since it solves the larger problem in the hierarchy with the least amount of time complexity.