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•The paper presents the applied method for indirect surface finishing measurement in aerospace manufacturing industry.•This paper introduces a method to quantify and correlate the ...deburring stage with the features extracted from sensors data.•This study covers signal processing, feature extraction and analytical method for surface finish quality estimation in deburring processes.•Wavelet decomposition and Welch spectrum estimate are used as a signal processing and feature extraction method.•The features are used as the basis for classification analysis by adaptive neuro-fuzzy inference system (ANFIS).
Manufacturing of aerospace components consists of combination of different types of machining, finishing, and measuring processes. One of the finishing processes is deburring, i.e. a finishing process to remove burrs from work coupons after a boring hole process. Deburring is conducted to achieve required surface finish quality prior to further processes in assembly line. This paper introduces sensor data analysis as a tool to quantify and correlate the deburring stage with the features extracted from sensors data. This study covers signal processing, feature extraction and analytical method to determine its relevancy to the surface finish quality from deburring process. Wavelet decomposition and Welch’s spectrum estimate is used as a signal processing and feature extraction method. Consequently, the features are used as the basis for analysis by adaptive neuro-fuzzy inference system (ANFIS). The ANFIS yields the output corresponding to the predicted surface finish quality in terms of boss hole chamfer length and the stage classification of deburring process. The results show a decreasing trend in measured vibration signal, which is qualitatively well correlated to the deburring stage and the development of chamfer length during deburring process.
With excellent mechanical and optical properties, sapphire substrate becomes a very important industrial material especially for LED manufacturing. Its quality control requires two tasks, ...double-sided surface profiling and defect detection. In this paper, a 3D surface scanning system is proposed as a platform for sapphire substrate inspection. During the scanning process, the height information of both upper and lower surfaces is measured by a chromatic confocal probe. For lateral positioning feedback, an in-house developed sensor, namely, image grating, is introduced in this paper. For these inspection processes, there are three challenges: 1) the motion error in the vertical direction, 2) simultaneous measurement of both upper and lower surfaces, and 3) lateral positioning error in a large scanning area. To address these challenges, three key technologies were developed: 1) real-time motion error compensation based on a fringe interferometer, 2) a double-sided measurement for transparent specimen without the pre-knowledge of its refractive index, and 3) planar image grating pair for accurate 2D displacement feedback. The experimental results showed that the proposed measurement system was able to achieve 50 nm accuracy of the standard deviation when measuring the step height of gauge blocks. When the system measured 4-inch double-sided polished sapphire substrate, the measurement repeatability of TTV (Total Thickness Variation) was within 60 nm; and that of warpage was within 10 nm. As a side product, refractive index can also be measured using the proposed system, and experimental results showed respectable consistency.
•A motion error compensation system is proposed based on film interferometry.•By setting up a pair of image gratings, lateral positioning errors and 2D Abbe error can be minimised.•The proposed technology is able to achieve nanometer repeatability in measuring thickness variation and warpage.•This system is able to simultaneously measure transparent specimens without having to know the refractive index.•The proposed system can also be used for general surface topography measurement purposes.
Wire and Arc Additive Manufacturing (WAAM) aims to be a cost-effective and material-efficient process to produce medium and large-scale metal parts. Nevertheless, post-processing is still required ...due to the low quality of the as-deposited surface. With the objective to divulge the complex interaction between the welding and machining phenomena, which determines the final surface quality, this paper focuses on the machinability of WAAM parts through a comprehensive investigation on the key parameters of both additive and subtractive processes. The effect of the WAAM parameters on the as-deposited part characteristics (i.e., hardness, flatness deviation, wall thickness, and initial surface waviness) and machining process has been analyzed. Consequently, the first of its kind, a non-linear function that can predict the effect of welding and milling parameters on the final surface roughness, is presented. The complex interaction between the local (e.g., surface irregularities and hardness) and global (e.g., wall thickness) effects of welding heat input and the resulting impact on the machining stability is analyzed. For example, slow welding speed results in a soft and irregular surface that is not easy to machine. Still, at the same time, the slow speed increases the wall width that provides the essential damping to reduce the chatter during machining. The obtained results help understand the interactions between the WAAM and milling processes and further determine the optimal machining allowances and optimal process conditions.
Due to the complexity of the Wire-arc Additive Manufacturing (WAAM) process, it is prone to the occurrence of defects in the product. One of the most common defects is porosity, which is detrimental ...to the mechanical and fatigue properties of the product. To guarantee the product quality, it is important to detect its occurrence. In this research, a strategy was developed to detect the occurrence of porosity and to identify its root cause. To develop a porosity detection strategy, a monitoring set-up was designed in which the WAAM process is monitored by a current sensor, condenser microphone, structural Acoustic Emission sensor, spectrometer and flow meter. Seventeen experiment samples were produced and the sensor data were stored using a data acquisition system. A sensor data analysis showed that current and acoustic signals could be correlated with the occurrence of porosity. From these sensor signals, 74 features were extracted. A validation of the samples, based on milling, grinding and image processing, was developed to obtain the pore density values for the corresponding feature set. A long short-term memory neural network was trained through supervised learning to classify feature data into acceptable or non-acceptable pore densities. A test accuracy of 82.52% was achieved. Apart from the porosity detection, a strategy for porosity root cause detection was developed in order to distinguish between process related porosity and contaminant related porosity. An accuracy of 90.67% was achieved, whereby the remaining inaccuracy is interpreted as a physical phenomenon and the results from the model are interpreted actually as more accurate than the prior assumption of the training labels.
Two inherent issues manifest themselves in flying mini-unmanned aerial vehicles (mini-UAV) in the dense area at tropical climate regions, namely disturbances from gusty winds and limited space for ...deployment tasks. Flexible membrane wing (FMW) UAVs are seen to be potentials to mitigate these problems. FMWs are adaptable to gusty airflow as the wings are able to flex according to the gust load to reduce the effective angle-of-attack, thus, reducing the aerodynamic loads on the wing. On the other hand, the flexible structure is allowing the UAV to fold in a compact package, and later on, the mini-UAV can be deployed instantly from the storage tube, e.g. through a catapult mechanism. This paper discusses the development of an FMW UAV actuated by a tendon-sheath mechanism (TSM). This approach allows the wing to morph to generate a rolling moment, while still allowing the wing to fold. Dynamic characteristics of the mechanism that exhibits the strong nonlinear phenomenon of friction on TSM are modeled and compensated for. A feed-forward controller was implemented based on the identified nonlinear behavior to control the warping position of the wing. The proposed strategy is validated experimentally in a wind tunnel facility by creating a gusty environment that is imitating a realistic gusty condition based upon the results of computational fluid dynamics (CFD) simulation. The results demonstrate a stable and robust wing-warping actuation, even in gusty conditions. Accurate wing-warping can be achieved via the TSM, while also allowing the wings to fold.
•A flexible wing morphing to cater for gusty-proof mini-UAVs is developed.•Tendon-sheath mechanism is utilized for the actuation.•The dynamics of the tendon-sheath mechanism is characterized and modeled.•A model based control strategy to regulate the wing actuation is implemented.•The system is validated satisfactorily on a wind tunnel with gusty scenario.
This paper analyses the dynamics of cable-driven robots with a passive backbone and develops techniques for their dynamic identification, which are tested on the H-Man, a planar cabled differential ...transmission robot for haptic interaction. The mechanism is optimized for human–robot interaction by accounting for the cost-benefit-ratio of the system, specifically by eliminating the necessity of an external force sensor to reduce the overall cost. As a consequence, this requires an effective dynamic model for accurate force feedback applications which include friction behavior in the system. We first consider the significance of friction in both the actuator and backbone spaces. Subsequently, we study the required complexity of the stiction model for the application. Different models representing different levels of complexity are investigated, ranging from the conventional approach of Coulomb to an advanced model which includes hysteresis. The results demonstrate each model's ability to capture the dynamic behavior of the system. In general, it is concluded that there is a trade-off between model accuracy and the model cost.
•Dynamics of cable-driven robots for haptic interface is modeled.•The significance of the frictional effect on the system is confirmed.•We evaluate the required complexity of the friction model.•The optimized models are validated experimentally with satisfactory results.•Suitable models for haptic interface are identified.
The all-electric ship (AES) with DC-grid configuration has demonstrated advantages compared to the traditional AC system and has become the state-of-the-art for ships with electric propulsion in the ...low to medium power range during the past decade. However, the integration with different power sources, such as fuel cells, batteries and diesel gen-sets, increases the system complexity and requires an advanced power management system (PMS) to handle vessel operation and to achieve optimal power control. This paper presents an optimized power management strategy to reduce the total cost of ownership of such vessels, considering not only the fuel cost and emission penalty, but also the power device degradation and equipment replacement cost. In this study, Model Predictive Control (MPC) and Reinforcement Learning (RL)-based PMS control methods are approached respectively. In order to demonstrate the performance of MPC and RL techniques, a typical tugboat load profile is simulated. The testing results are also compared with a traditional rule-based power management control.
This paper presents a review of surgical simulators, developed to enhance the learning process of surgical procedures, that involves bones, ranging from musculoskeletal system (orthopedics) and the ...skull (ENT and neurosurgeries). The paper highlights the specific challenges in terms of the extended reality representation of surgical training along with its latest advances. The study gathers journal and conference proceedings from various database sources (bibliographic databases and online search engines) that fulfills a predetermined eligibility criterion. From the search, 185 journals were found but only 144 met the inclusion criteria. Surgical simulators emerge as a promising alternative to aid residents in surgical training. It encompasses surgical procedures done in the craniomaxillofacial, joints, limbs and spine section of the human body. The study was partially supported by internal grant STG/19/047 from KU Leuven.
Abstract Although the aspects that affect the performance and the deterioration of abrasive belt grinding are known, wear prediction of abrasive belts in the robotic arm grinding process is still ...challenging. Massive wear of coarse grains on the belt surface has a serious impact on the integrity of the tool and it reduces the surface quality of the finished products. Conventional wear status monitoring strategies that use special tools result in the cessation of the manufacturing production process which sometimes takes a long time and is highly dependent on human capabilities. The erratic wear behavior of abrasive belts demands machining processes in the manufacturing industry to be equipped with intelligent decision-making methods. In this study, to maintain a uniform tool movement, an abrasive belt grinding is installed at the end-effector of a robotic arm to grind the surface of a mild steel workpiece. Simultaneously, accelerometers and force sensors are integrated into the system to record its vibration and forces in real-time. The vibration signal responses from the workpiece and the tool reflect the wear level of the grinding belt to monitor the tool’s condition. Intelligent monitoring of abrasive belt grinding conditions using several machine learning algorithms that include K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Multi-Layer Perceptron (MLP), and Decision Tree (DT) are investigated. The machine learning models with the optimized hyperparameters that produce the highest average test accuracy were found using the DT, Random Forest (RF), and XGBoost. Meanwhile, the lowest latency was obtained by DT and RF. A decision-tree-based classifier could be a promising model to tackle the problem of abrasive belt grinding prediction. The application of various algorithms will be a major focus of our research team in future research activities, investigating how we apply the selected methods in real-world industrial environments.
Cable-conduit mechanism (CCM) is widely used in robotic hands, rescue robots, rehabilitation robots, and surgical robots because it offers efficient transmission of forces/torques from the external ...actuator to the end effector with lightweight and high flexibility. However, the accurate position control is challenging in such mechanism due to friction and backlash-like hysteresis between the cable and the conduit. In this paper, a new control approach is proposed to enhance the trajectory tracking performances of the CCM. Unlike current approaches for the CCM in the literature, the proposed scheme considers the position transmission of the CCM as an approximation of backlash-like hysteresis nonlinearities without requiring the exact values of model parameters and their bounds. Online approximation-based robust control laws, which have the capabilities of estimating unknown system parameters, are also established. In addition, the deigned controller can adapt to any changes of the cable-conduit configuration and it is stable. The results of the proposed control techniques have been experimentally validated on a flexible robotic system using a flexible endoscope. Experimental validations show substantial improvements on the performances of position tracking for the use of CCM regardless of the arbitrary changes of the cable-conduit configurations.
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