Mechanical Science and Engineering

To discuss the mechanism of muscle strain injury from biomechanical viewpoints, the change of mechanical properties of injured skeletal muscle was evaluated experimentally. We induced strain injury to rabbit tibialis anterior muscle by applying a single tension loading/unloading process under the conditions of various stretch amplitude, stretch rate, and muscle activation in situ. The results showed that isometric contractile force decreased with increasing stretch amplitude during the injury-induction process. Multiple regression analyses were conducted for the results and they showed that the stretch amplitude played a dominant role in the decrease of the contractility. The failure stress decreased significantly with the increasing stretch amplitude and dissipation energy during the injury-induction process. Moreover, the failure stresses of the muscle injured under unstimulated conditions obviously decreased in comparison with those of the muscles in intact and injured under stimulated conditions. On the basis of these results and previous experimental studies, we concluded that muscle activity played a significant roll to prevent the decrease of the failure stress and that the damage mechanism of strain injury depended on the muscle activity during injury-induction process.

In recent decades, different types of plasma sources have been used for various types of plasma processing, such as, etching and thin film deposition. The critical parameter for effective plasma processing is high plasma density. One type of high density plasma source is Microwave sheath-Voltage combination Plasma (MVP). In the present investigation, a better design of MVP source is reported, in which over-dense plasma is generated for low input microwave powers. The results indicate that the length of plasma column increases significantly with increase in input microwave power.

Microwave sheath-Voltage combination Plasma (MVP) is a high density plasma source and can be used as a suitable plasma processing device (e.g., ionized physical vapor  deposition). In the present report, the spatio-temporal behavior of an argon MVP sustained along a direct-current biased Ti rod is investigated. Two plasma modes are observed, one is an "oxidized state" (OS) at the early time of the microwave plasma and the other is "ionized sputter state" (ISS) at the later times. Transition of the plasma from OS to ISS, results a prominent change in the visible color of the plasma, resulting from a significant increase in the plasma density, as measured by a Langmuir probe. In the OS, plasma is dominated by Ar ions and the density is in amplitude order of 1011 cm-3. In the ISS, metal ions from the Ti rod contribute significantly to the ion composition and higher density plasma (1012 cm-3) is produced. Nearly uniform high density plasma along the length of the Ti rod is produced at very low input microwave powers (around 30 W). Optical emission spectroscopy measurements confirm the presence of sputtered Ti ions and Ti neutrals in the ISS.

Rolling element bearings fault diagnostic has vital role in rotating machinery condition based maintenance. When localized defect occurs, the periodic impulse feature which relates to defect location on the bearing appears in machinery vibration signal. However, this signal is generally masked by noised. Hence, an effective signal processing method is needed. The combination of high frequency resonance technique (HFRT) or envelope analysis and Morlet wavelet filter is one of commonly used method. It demodulates low frequency signal related to bearing failure from high frequency carrier related to machine system natural frequency. Unfortunately, it requires proper passband to get effective detection result. Parameters such as kurtosis and Shannon entropy of filtered signal envelope have been proposed as indicator for optimal Morlet wavelet filter selection. However, both parameters do not consider harmonics in envelope spectrum, which are directly related to periodic impulse in the s...

Failures of rolling element bearing can cause serious downtime. Early stage bearing defects require a special detection method. When localized defect occurs, the periodic impulse which relates to bearing defect location appears in machinery vibration signal. High frequency resonance technique (HFRT) or envelope analysis is used in conjunction with complex Morlet wavelet because it resembles to mechanical impulse. This detection method demodulates defect-related low frequency part from systemnatural-frequency-related high frequency part. However a proper indicator for optimal center frequency and bandwidth is needed to obtain promising detection result. This study proposes an indicator that picks optimal Morlet wavelet that gives the highest ratio of the sum of harmonics family that has maximum value to the arithmetic mean of envelope spectrum in a specified range. In simulation study, it is shown that the proposed parameter can detect bearing defect not less than 97% from signal of ...

A visual assistance system has become attractive as a technique to improve the efficiency and stability of remote control. While an operator controls a working robot, another autonomous monitoring robot evaluates a suitable viewpoint to observe the work site, and dynamically moves to the optimal viewpoint for monitoring. Choosing the observation region (ROI: region of interest) is equivalent to deciding the action of the following autonomous monitoring system. Therefore, we focus on ROI detection in our visual support system. We propose an ROI selection method to identify the most suitable observation point and interobject relations. The monitoring robot detects a gestalt of the scene in order to identify the relations between objects. Such an adaptive ROI in real time improves the efficiency of the remote control. The experimental results indicate the effectiveness of the proposed system in terms of execution time and number of errors.

Minimally invasive surgery has undergone significant advancements in recent years, transforming various surgical procedures by minimizing patient trauma, postoperative pain, and recovery time. However, the use of robotic systems in minimally invasive surgery introduces significant challenges related to the control of the robot’s motion and the accuracy of its movements. In particular, the inverse kinematics (IK) problem is critical for robot-assisted minimally invasive surgery (RMIS), where satisfying the remote center of motion (RCM) constraint is essential to prevent tissue damage at the incision point. Several IK strategies have been proposed for RMIS, including classical inverse Jacobian IK and optimization-based approaches. However, these methods have limitations and perform differently depending on the kinematic configuration. To address these challenges, we propose a novel concurrent IK framework that combines the strengths of both approaches and explicitly incorporates RCM c...

The growing need for high levels of autonomy in Autonomous Robotic Surgery Systems (ARSS) calls for innovative approaches to reduce surgeons' cognitive load, optimize hospital workflows, and ensure efficient task-level reasoning and adaptation during execution. This paper presents a novel hybrid framework that synergistically combines Task-Motion Planning and Dynamic Behavior Trees for ARSS in Minimally Invasive Surgery. Our approach is designed to address the challenges of coordinating multiple surgical tools within a small workspace, thereby making complex surgical tasks like multi-throw suturing feasible and efficient. Through an extensive evaluation in simulation across diverse initial conditions and noise scenarios, the proposed method demonstrates improved success rates, reduced execution times, and fewer regrasps compared to standalone approaches. Furthermore, it showcases robustness under increased noise conditions. By applying our framework to a complex multi-throw suturing task, we illustrate its capability to seamlessly handle comprehensive suturing tasks, including needle picking, insertion, extraction, and the handover of the needle between Patient Side Manipulators. The results suggest that our hybrid approach not only enhances ARSS autonomy but also adapts effectively to unexpected environmental changes, laying the groundwork for its potential applicability in real-world surgical robotics.