Recent Patents on Engineering - Volume 16, Issue 6, 2022

Background: The trachea is an important part of the respiratory system. Long-term airway diseases and the effects of human physiological conditions can cause trachea stenosis. This will seriously affect patients’ physical health. Tracheal stents can provide durable support by means of dilating the narrowed area; they can effectively relieve the patient's breathing difficulties, which is of value that is more practical. Objective: To meet the vital requirements for better adaptation to the human airway environment and prevent complications associated with stent placement, the construction and materials of tracheal stents have been improved constantly. Methods: This paper investigates various representative patents related to the tracheal stent. The structure type, placement method and applications situation of these tracheal stents are discussed. Results: The characteristics of different types of tracheal stents are analyzed. This paper analyzes the main problems in its development. The solutions to the issues and the current and future research on tracheal stents are discussed. Conclusion: The tracheal stents are classified into metal stent, silicone stent, biodegradable stent and hybrid material stent. Further improvements are needed in the aspects of structural design, safety, applicability, biocompatibility, algorithm of drive model of tracheal stent. More related patents about tracheal stents need to be developed.

Background: Pulverized coal detection is an indispensable detection measure in the coal industry. The current detection devices can be divided into two types: invasive and non-invasive. The coal dust detection methods and devices based on acoustics, optics, and electricity have been extensively studied. In order to achieve a high-efficiency online detection scheme, improving the accuracy and stability of the detection means is the primary goal of the research. Objective: The general problems and characteristics of coal dust detection device design are summarized, as well as recent technological developments and the need for online testing to predict future research trends. Methods: The current typical detection devices are classified according to the detection principle and whether they invade the target, analyzing its advantages and disadvantages according to the device performance and application scenarios. Results: It has a beneficial effect on the design of the pulverized coal concentration detection device. Conclusion: The paper summarizes and analyzes several representative coal concentration detection device patents in recent years. Then it points out advantages and main problems. On this basis, the main development direction of the coal dust concentration detection device in the future is discussed.

Background: 3D printing technology is widely applied in transportation, industrial equipment, medical, aerospace, and civil industry due to its less use of material, no requirement of manufacturing model, and machinability of complex parts. The mechanical structure of a 3D printer mainly includes a 3D printer head structure and working platform. It plays a major role in the machining efficiency and processing accuracy of the 3D printer. Thus, increasing attention has been paid to the current trends in the mechanical structure of 3D printers. Objective: To meet the increasing requirements of 3D printing processing efficiency and precision, the mechanical structure of 3D printers, such as 3D print head structure and working platform, needs to be carefully studied, and a feasible mechanical structure of 3D printers should be proposed. Methods: This paper studies various representative patents related to the mechanical structure of 3D printers, analyzes the mechanical structure of 3D printers, and examines the perfect mechanical structure of 3D printers. Results: By summarizing several patents on the mechanical structure of 3D printers, the main current existing problems, such as platform jitter and machining error, are summarized and analyzed, and a new mechanical structure of 3D printers is proposed. Moreover, the development tendency of the mechanical structure of 3D printers in the future is discussed. Conclusion: The optimization of the mechanical structure of the 3D printer is conducive to increasing the machining efficiency and processing accuracy in the 3D printing process. More relevant patents on the working platform and 3D printer heads will be granted in the future.

Background: Sliding bearing is a kind of bearing that works under sliding friction, which has the characteristics of stable operation, safety and reliability, and is noiseless. With the technological progress of the machinery industry, modern machinery and equipment is developing in the direction of high speed and heavy load, its power is getting higher and higher, and the working environment is getting worse, so plain bearings are more and more widely used. Objective: In order to improve the lubricating performance of sliding bearings, the influencing factors of the lubricating performance of sliding bearings are summarized and commented on. Methods: The research progress and achievements at home and abroad are summarized from three aspects: influencing factors of lubrication performance of radial sliding bearings, thrust sliding bearings, and influencing factors of lubricating oil on lubrication performance of sliding bearings, which provides reference for the future development of sliding bearings. Results: The study discusses the experimental method, simulation process, and experimental results of the factors affecting the lubrication performance of sliding bearing. Conclusion: The texture, deformation, surface morphology of oil cavity, eccentric load, and flow state of sliding bearings all affect the lubricating performance of sliding bearings, and lubricating oil also affects the lubricating performance of sliding bearings.

Background: As the demand for petroleum products grows, pipes to carry these products are also required extensively. Consequently, petroleum pipe blockage has become a frequent and severe problem in China. In order to ensure trouble-free operation, it is necessary to clean and inspect the petroleum pipe regularly. However, currently available petroleum pipe inspection gauges can block the petroleum pipe easily, and their cleaning efficiency is not as high as desired. Therefore, mechanisms to prevent pipe blockage and ensure high-efficiency cleaning are being given much importance in studies on petroleum pipe inspection gauges. Objective: The aim of the study is to review recent patents related to petroleum pipe inspection gauges in China and forecast possible designs that can mitigate present-day problems associated with petroleum pipe inspection gauges. Methods: This paper has studied and compared various representative patents relevant to the petroleum pipe inspection gauge. Results: A large number of patents filed in China related to petroleum pipe inspection gauges have been studied and the anti-blocking mechanism as well as the cleaning efficiency of the petroleum pipe inspection gauges described in those patents have been analyzed and compared. Forecasts were made regarding the possible development trajectories in the design of petroleum pipe inspection gauges. Conclusion: The problems of easy blockage and poor cleaning efficiency are yet unsolved for petroleum pipe inspection gauges. It is expected that future work will focus on the development of pigging, new materials, power sources, and intelligent control to resolve these issues.

Background: The equations of Monge-Ampère type which arise in geometric optics are used to design illumination lenses and mirrors. The optical design problem can be formulated as an inverse problem: determine an optical system consisting of a reflector and/or refractor that converts a given light distribution of the source into a desired target light distribution. For two decades, the development of fast and reliable numerical design algorithms for the calculation of freeform surfaces for irradiance control in the geometrical optics limit is of great interest in current research. Objective: The objective of this paper is to summarize the types, algorithms, and applications of Monge-Ampère equations. It helps scholars better grasp the research status of Monge-Ampère equations and further explore the theory of Monge-Ampère equations. Methods: This paper reviews the theory and applications of Monge-Ampère equations from four aspects. We first discuss the concept and development of Monge-Ampère equations. Then we derive two different cases of Monge-Ampère equations. We also list the numerical methods of the Monge-Ampère equation in actual scenes. Finally, the paper gives a brief summary and an expectation. Results: The paper gives a brief introduction to the relevant papers and patents of the numerical solution of Monge-Ampère equations. There is quite a lot of literature on the theoretical proofs and numerical calculations of Monge-Ampère equations. Conclusion: Monge-Ampère equation has been widely applied in the geometric optics field since the predetermined energy distribution and the boundary condition creation can be well satisfied. Although the freeform surfaces designed by the Monge-Ampère equations is developing rapidly, there is still plenty of room for development in the design of the algorithms.

Background: The failure model is an important basis for research on material failure and fracture, and plays an important role in the finite element simulation of metal cutting. Johnson- Cook damage model is widely used to predict the onset of damage to many materials. Its damage evolution is controlled by five parameters. Objective: This study aimed to decrease the cost of damage parameters’ identification and find out the damage parameters which have a great influence on the simulation results. This work can provide assistance in the optimization and selection of constitutive model parameters. Methods: Suitable Johnson-Cook damage model parameters, which can be used in the metal cutting simulation of AISI 1045 steel, are selected by comparing the simulation results and the experimental results. The cutting process of AISI 1045 steel is simulated by changing the Johnson- Cook damage parameters in the ABAQUS/Explicit. Results: The relevance of cutting force, feed force, cutting temperature, and deformation coefficient with five Johnson-Cook damage parameters are determined. Conclusion: The finite element simulation results show that the Johnson-Cook damage model parameters D2 and D3 have the biggest impact on the cutting simulation of AISI 1045 steel. Meanwhile, different Johnson-Cook damage parameters would cause diverse changes in the simulation results.

Background: To reduce environmental pollution and improve resource utilization, lightweight equipment has become an important development trend of manufacturing. Therefore, thin-walled parts are being widely used in automobiles, aerospace, etc. due to their lightweight and high specific strength. However, they usually deform during machining due to poor stiffness. Objective: To reduce the machining deformation, the finite element method has been used to analyze the deformation law of thin-walled parts. Methods: A 3D milling model of Al7050-T7451 thin-walled parts was established. Then, the influence of hole structure, rib, and auxiliary support on the deformation was investigated under the condition of optimized parameters. Moreover, some related patents on the research of machining deformation of thin-walled parts were also consulted. Results: The results showed that the established 3D model could accurately predict the machining deformation of thin-walled parts. The machining deformation on the edges is more severe due to holes that weaken the stiffness of thin-walled parts. Besides, ribbed slab and auxiliary support can shorten machining deformation by 71.9% and 65.2%, respectively.

Background: The supporting quadric method (SQM) is a versatile method for designing freeform optics for desired irradiance redistribution, but the time of solution optimization increases rapidly with the refinement of the mapping grid. Objective: As the complexity of light distribution is getting higher and higher, time consumed will also increase exponentially. This paper proposes an idea of applying the deep neural network method to optical design. Methods: In this article, we established a special corresponding relationship and prepared a dataset, which underwent deep network learning and training. Finally, a hybrid design method of deep learning and optical design was realized and verified. Results: Compared with the traditional method, this method is more efficient. Here, we used a deep neural network(DNN) to accelerate the freeform optical design. After the DNN was trained by a sample set consisting of a uniform pattern and eight different Chinese characters represented by an array with 11 × 11, it can generate a character's reflector within few milliseconds. Conclusion: As proof of this new method, a character pattern reflector was manufactured and tested, and the experimental irradiance distribution was found close to the expectation, which means that the neural network has the excellent capability to memorize all of the learned characters. SQM combined with DNN has the potential to establish a particular “optical font library” and even offers a promising path for rapid freeform optical design to realize the function of “optical typography”.

Background: In some applications, retaining the residual noise at a specified frequency can provide a better vehicle interior sound quality for occupant’s driving experience. The hybrid vibro-acoustic adaptive noise equalizer (HVA-ANE) algorithm introduces a sound retention factor on the basis of the hybrid vibro-acoustic filter-u, and filter-x least mean square (HVA-FUXLMS) algorithm to achieve control of the sound quality, but it is not possible to retain varying degrees of different frequency bands. The hybrid vibro-acoustic empirical-mode-decomposition frequencydomain block adaptive noise equalizer (HVA-EBANE) algorithm introduces Empirical-Mode- Decomposition (EMD) and frequency domain block methods to achieve different degrees of retention of noise in different frequency bands but cannot deal with the irrelevant frequency components in the error signal. Objective: This paper proposes an improved active control algorithm for vehicle interior sound quality, the so-called hybrid vibro-acoustic EMD frequency-domain block FELMS (HVA-EBFELMS) algorithm. Methods: Based on the filtered error, the least mean square algorithm and the residual filter of the specific frequency band are designed according to the psychoacoustic parameters of each component. The filter filters the irrelevant frequency components in the residual signal, and only retains the frequency components that have a great influence on the sound quality so as to achieve the regulation of the desired sound quality. Results: In order to verify the effectiveness of our algorithm, we used the noise and vibration in the vehicle at idle speed as the object and compared the noise control effect with HVA-ANE and HVAEBANE algorithms considering the sound quality. The simulation experiment shows that our algorithm reduces the loudness of the ear-side noise by more than 40% while taking into account the noise and vibration control. Conclusion: The loudness control effect of hybrid vibro-acoustic EMD frequency-domain block FELMS (HVA-EBFELMS) algorithm is better than HVA-ANE and HVA-EBANE algorithms; it has a better effect of improving loudness as well.

Background: Induction motor plays a major role in various industries, and its importance is increasing. Due to the environmental temperature or sealed working environment, heat generation is generally severe. The heat exchange with the outside environment does not take place smoothly, and the motor temperature increases. The performance of the induction motor is also significantly influenced by the temperature. Therefore, it is necessary to study the influence of temperature on the performance of induction motor. Objective: This study aimed to analyse the influence of temperature on induction motor. At different temperatures, variation in performance parameters has been observed. Methods: Taking an 11 kW 1500r/min induction motor as an example, a two-dimensional transient electromagnetic field model was established, and the correctness of the model was verified by experiments. The motor starting performance, various losses and efficiencies under different temperatures wereestimated. Results: As the stator and rotor resistance increased, the starting current decreased by 11.99% when the internal temperature rose from 25°C to 150°C. When the internal temperature rose from 25°C to 150°C, the stator copper loss increased by 32.83%, and the rotor copper loss increased by 28.79%. However, the core loss of the motor increased by 3W, and the motor efficiency decreased by 2.12%. Conclusion: When the temperature is different, the starting torque of the motor is almost unchanged, and the starting current decreases with an increase in temperature. The stator copper loss and rotor copper loss of the motor increase with the increase in temperature, while the core loss is almost unchanged. In addition, the efficiency of the motor gradually decreases with the increase in temperature.

Background: With the development of robotics, more and more robots are being used in industrial production. However, as the production environment surrounding the robots becomes increasingly complex, there is a need for more intelligent industrial robots. For improving the intelligence of industrial robots, the most important thing is to ensure that they can carry out safe industrial production activities in a complex production environment. Therefore, studying the autonomous dynamic obstacle avoidance path planning of industrial robots in complex environments is of great significance for improving the intelligence of industrial robots and the application of human-machine collaboration. Objective: The main purpose of this paper is to improve the traditional artificial potential field method. It aims to improve the disadvantages of the traditional artificial potential field method, such as falling into the local minimum and failing to reach the target. Secondly, the background difference method, which is based on binocular vision and Kalman filtering algorithm, is used, and the environmental map containing the static and dynamic obstacles is obtained. After obtaining the information on the position of static and dynamic obstacles, the robot arm can make good use of the improved artificial potential field method to plan its own trajectory, thus realizing the dynamic obstacle avoidance of the robot arm in a complex environment. Methods: This paper proposes an improved artificial potential field method. First of all, in order to solve the problem of not being able to achieve the goal, the method of modifying the repulsion field function, as proposed by Wang Huili and others, has been cited. In the traditional repulsion function, the relative distance between the robot and the target is introduced. Due to this, the target point is always the minimum point of the potential field. It is necessary to ensure that the robot can reach the target position smoothly. For the local minimum problem, by adding a gravitational increase factor β, the gravitational force received is greater than the repulsive force, thereby breaking the balance of the resultant force. Finally, for the traditional artificial potential field method that does not consider the path planning problem in the presence of dynamic obstacles, the velocity vector of the dynamic obstacle is brought into the potential field function to improve the traditional artificial potential field method. Results: The robot easily falls into the local optimum during path planning, and the improved artificial potential field method overcomes this shortcoming. Therefore, the manipulator can perform autonomous dynamic obstacle avoidance path planning in an environment with dynamic obstacles, finally reaching the target point safely. Conclusion: The industrial production field faces an increasing demand for intelligent industrial robots. This paper improves on the traditional artificial potential field method based on binocular vision so that the mechanical arm can avoid dynamic obstacles autonomously in the presence of dynamic obstacles, thereby improving the degree of intelligence of the robotic arm, enabling the technology to meet the needs of future industrial development and contribute to the development of future industrial robot technology.