Frontiers of Mechanical Engineering

The gearbox of a wind turbine (WT) has dominant failure rates and highest downtime loss among all WT subsystems. Thus, gearbox health assessment for maintenance cost reduction is of paramount importance. The concurrence of multiple faults in gearbox components is a common phenomenon due to fault induction mechanism. This problem should be considered before planning to replace the components of the WT gearbox. Therefore, the key fault patterns should be reliably identified from noisy observation data for the development of an effective maintenance strategy. However, most of the existing studies focusing on multiple fault diagnosis always suffer from inappropriate division of fault information in order to satisfy various rigorous decomposition principles or statistical assumptions, such as the smooth envelope principle of ensemble empirical mode decomposition and the mutual independence assumption of independent component analysis. Thus, this paper presents a joint subspace learning-based multiple fault detection (JSL-MFD) technique to construct different subspaces adaptively for different fault patterns. Its main advantage is its capability to learn multiple fault subspaces directly from the observation signal itself. It can also sparsely concentrate the feature information into a few dominant subspace coefficients. Furthermore, it can eliminate noise by simply performing coefficient shrinkage operations. Consequently, multiple fault patterns are reliably identified by utilizing the maximum fault information criterion. The superiority of JSL-MFD in multiple fault separation and detection is comprehensively investigated and verified by the analysis of a data set of a 750 kW WT gearbox. Results show that JSL-MFD is superior to a state-of-the-art technique in detecting hidden fault patterns and enhancing detection accuracy.

Ultrasonic vibration-assisted grinding (UVAG) is an advanced hybrid process for the precision machining of difficult-to-cut materials. The resonator is a critical part of the UVAG system. Its performance considerably influences the vibration amplitude and resonant frequency. In this work, a novel perforated ultrasonic vibration platform resonator was developed for UVAG. The holes were evenly arranged at the top and side surfaces of the vibration platform to improve the vibration characteristics. A modified apparent elasticity method (AEM) was proposed to reveal the influence of holes on the vibration mode. The performance of the vibration platform was evaluated by the vibration tests and UVAG experiments of particulate-reinforced titanium matrix composites. Results indicate that the reasonable distribution of holes helps improve the resonant frequency and vibration mode. The modified AEM, the finite element method, and the vibration tests show a high degree of consistency for developing the perforated ultrasonic vibration platform with a maximum frequency error of 3%. The employment of ultrasonic vibration reduces the grinding force by 36% at most, thereby decreasing the machined surface defects, such as voids, cracks, and burnout.

In this paper, a typical 3-degree of freedom (3-DOF) translational parallel kinematic machine (PKM) is studied and analyzed whose tool platform has only translations along X-, Y- and Z-axes. It consists of three limbs, each of which have arm and forearm with prismatic-revolute-revolute-revolute (PRRR) joints. Inverse kinematics analysis is carried out to find the slider coordinates and joint angles for a given position of tool platform. Stiffness modeling is done based on the compliance matrices of arm and forearm of each limb. Using the stiffness modeling the variations of minimum and maximum translational stiffness in the workspace are analyzed. For various architectural parameters of the 3-DOF PKM the tendency of variations on the minimum and maximum stiffness over the entire workspace is studied; and also the deflections of the tool platform along X, Y, and Z directions with respect to various forces are presented.

Reconfigurable manufacturing systems (RMSs), which possess the advantages of both dedicated serial lines and flexible manufacturing systems, were introduced in the mid-1990s to address the challenges initiated by globalization. The principal goal of an RMS is to enhance the responsiveness of manufacturing systems to unforeseen changes in product demand. RMSs are costeffective because they boost productivity, and increase the lifetime of the manufacturing system. Because of the many streams in which a product may be produced on an RMS, maintaining product precision in an RMS is a challenge. But the experience with RMS in the last 20 years indicates that product quality can be definitely maintained by inserting in-line inspection stations. In this paper, we formulate the design and operational principles for RMSs, and provide a state-of-the-art review of the design and operations methodologies of RMSs according to these principles. Finally, we propose future research directions, and deliberate on how recent intelligent manufacturing technologies may advance the design and operations of RMSs.

Tissue engineering (TE) is an integrated discipline that involves engineering and natural science in the development of biological materials to replace, repair, and improve the function of diseased or missing tissues. Traditional medical and surgical treatments have been reported to have side effects on patients caused by organ necrosis and tissue loss. However, engineered tissues and organs provide a new way to cure specific diseases. Scaffold fabrication is an important step in the TE process. This paper summarizes and reviews the widely used scaffold fabrication methods, including conventional methods, electrospinning, three-dimensional printing, and a combination of molding techniques. Furthermore, the differences among the properties of tissues, such as pore size and distribution, porosity, structure, and mechanical properties, are elucidated and critically reviewed. Some studies that combine two or more methods are also reviewed. Finally, this paper provides some guidance and suggestions for the future of scaffold fabrication.

A three-stage molding process involving microcellular injection molding with core retraction and an “out-of-mold” expansion was developed to manufacture thermoplastic polyurethane into lightweight foams of varying local densities, microstructures, and mechanical properties in the same microcellular injection molded part. Two stages of cavity expansion through sequential core retractions and a third expansion in a separate mold at an elevated temperature were carried out. The densities varied from 0.25 to 0.42 g/cm3 (77% to 62% weight reduction). The mechanical properties varied as well. Cyclic compressive strengths and hysteresis loss ratios, together with the microstructures, were characterized and reported.

This study proposes a hybrid controller by combining a proportional-integral-derivative (PID) control and a model reference adaptive control (MRAC), which named as PID + MRAC controller. The convergence performances of the PID control, MRAC, and hybrid PID + MRAC are also compared. Through the simulation in Matlab, the results show that the convergence speed and performance of the MRAC and the PID + MRAC controller are better than those of the PID controller. In addition, the convergence performance of the hybrid control is better than that of the MRAC control.

A huge amount of information and identification accuracy in large civil engineering structural damage identification has not been addressed yet. To efficiently solve this problem, a new damage identification method based on rough set and integrated neural network is first proposed. In brief, rough set was used to reduce attributes so as to decrease spatial dimensions of data and extract effective features. And then the reduced attributes will be put into the sub-neural network. The sub-neural network can give the preliminary diagnosis from different aspects of damage. The decision fusion network will give the final damage identification results. The identification examples show that this method can simplify the redundant information to reduce the neural network model, making full use of the range of information to effectively improve the accuracy of structural damage identification.

The demand for redundant hydraulic manipulators that can implement complex heavy-duty tasks in unstructured areas is increasing; however, current manipulator layouts that remarkably differ from human arms make intuitive kinematic operation challenging to achieve. This study proposes a seven-degree-of-freedom (7-DOF) redundant anthropomorphic hydraulically actuated manipulator with a novel roll-pitch-yaw spherical wrist. A hybrid series-parallel mechanism is presented to achieve the spherical wrist design, which consists of two parallel linear hydraulic cylinders to drive the yaw/pitch 2-DOF wrist plate connected serially to the roll structure. Designed as a 1RPRRR-1SPU mechanism (“R”, “P”, “S”, and “U” denote revolute, prismatic, spherical, and universal joints, respectively; the underlined letter indicates the active joint), the 2-DOF parallel structure is partially decoupled to obtain simple forward/inverse kinematic solutions in which a closed-loop subchain “RPRR” is included. The 7-DOF manipulator is then designed, and its third joint axis goes through the spherical center to obtain closed-form inverse kinematic computation. The analytical inverse kinematic solution is drawn by constructing self-motion manifolds. Finally, a physical prototype is developed, and the kinematic analysis is validated via numerical simulation and test results.