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Aerodynamic performance of wind turbine governs the overall energy efficiency, which has been an ever-lasting research focus in the field of wind power technology. Due to the coupling effect among the highly complex environmental and structural uncertainties, the practical aerodynamic performance may not be reliably predicted. To aggravate, this performance declines with time in service. It is of great significance to efficiently and reliably assess the impact of uncertain factors and reduce these influences on wind turbine aerodynamic performance. This paper establishes an uncertainty analysis and robustness optimization model of wind turbine aerodynamic performance considering wind speed and pitch angle error uncertainties. An approach combined the no-instrusive probabilistic collocation method is used, and the blade element momentum theory is applied to quantify influences of variable uncertainties on NREL 5 MW wind turbine aerodynamic performance. The optimization target is to reduce the sensitivity of wind turbine aerodynamic performance to uncertainties, as well as maintain capture power. The results show that the wind turbine aerodynamic and mechanical performance will be greatly affected with uncertain factors. By optimizing and adjusting wind turbine rotor speed and blade pitch angle, the wind turbine rotor power and thrust load variation can be reduced to 9.14% and 9.36%, respectively, which indeed reduces the uncertainty effects. [ABSTRACT FROM AUTHOR]

This work develops an automatic lawnmower (Auto-Lawnmower) using computer vision technology for obstacle avoidance. Several critical issues have been overcome in this development work, including the development of a simplified convolutional neural network (CNN) for decision making, and sufficiently large datasets needed to train the Auto-Lawnmower. The following key strategies are adapted to ensure necessary functionality and efficacy with minimum cost, considering possible mass production of Auto-Lawnmowers. First, we use at-time avoidance strategy: meaning the Auto-Lawnmower makes turns when it encounters an obstacle. This is possible because of the fact that a lawn mower usually can move at a very low speed (walking speed of a man). Second, we decided to use minimum necessary sensors, so as to make the system of our Auto-Lawnmower as simple as possible and hence can be very practical. A single monocular video camera is, therefore, used as the single sensor for both: (1) to generate real-time movie images of a large number of situations that the Auto-Lawnmower may encounter, which is labelled and builds up the training datasets; (2) to capture the real-time image when the trained Auto-Lawnmower is in action, to decide on either to avoid the obstacle or move forward while cutting the grass. A Law dataset with labels, called LawNet, has been established for training of CNNs. It collects a total of 168,542 labelled images taken from the perspective of our Auto-Lawnmower for lawns at the university campus. A concise CNN is created for high efficiency and trained with our LawNet to drive the Auto-Lawnmower. A prototype of Auto-Lawnmower is finally designed, built and tested for lawn mowing in real situations. It is found that it works well as designed, with minimum sensors (a single camera), and hence it has a good potential for mass production. [ABSTRACT FROM AUTHOR]

To tackle the jittering of a robot arm-tip, a novel method of the jittering mitigation is proposed. The key idea is to transmit the jittering to vibration of a mass block nested inside the jittering-mitigator. This method only requires the frequency of the jittering at the arm-tip. To verify the practicability of the method, a practical robot was applied through simulations and physical experiments. The jittering mitigator device can be directly attached to or detached from the arm-tip. The jittering at the arm-tip was first measured through experiments using accelerometers connected to the vibration and noise testing system. Then, the dominant frequency was identified through fast Fourier transform analysis. The theoretical parameters of the jittering mitigator were calculated accordingly. A model was established to simulate the jitter reduction effect of the mitigator. The results revealed a 68% reduction in the average amplitude of the jittering vibration at the arm-tip, which is corroborated by the experiment results. The proposed method could be applicable to all types of robots theoretically because it only requires computing the frequency of jitter. [ABSTRACT FROM AUTHOR]

Appropriate regularization parameter specification is the linchpin for solving ill-posed inverse problems when regularization method is applied. This paper presents a novel technique to determine cut off singular values in the truncated singular value decomposition (TSVD) methods. Simple formulae are presented to calculate the index number of the singular value, beyond which all the smaller singular values and the corresponding vectors are truncated. The determination method of optimal truncation threshold is firstly theoretically inferred. Two-dimensional inverse problems processing Radon transform are then exemplified. Formulae to solve the problem with insufficient image resolution and projection angle number are derived by the currently proposed method. The results show that accuracy of the current method is similar to that of TSVD but with much superior efficiency. On the other hand, insufficiency in input data affects the output accuracy of the inverse solution, a least square method can be engaged to establish formulae calculating the truncation threshold. For an insufficient set of input data, the percentage difference between inversely reconstructed signal and TSVD reconstructed signal is about 3%. The current formulae offer reliable and more efficient approach to calculate the truncation threshold when TSVD is applied to solve inverse problems with known system characteristics. [ABSTRACT FROM AUTHOR]

Long glass fiber‐reinforced polypropylene (LGF/PP) foaming composite has been increasingly used in automotive components regarding its good mechanical and acoustic properties. However, the balance of its mechanical property and acoustic property is far from being understood. The objective of this study is to investigate the influences of molding thickness or foaming degree on both mechanical and acoustic properties of LGF/PP foaming composite by experimental tests. First, LGF/PP foaming composite felts with consistent surface density were fabricated, then specimens with a series of molding thicknesses were prepared by compression molding. Tensile and acoustic tests were conducted and a scanning electron microscopy was also used for analyzing microscopic characteristics. The results indicate that tensile strength and tensile modulus of the present LGF/PP composite decrease in exponential formats, whereas sound absorption coefficients of them increase in logarithmic formats, when molding thickness vary from 1.5 to 8 mm. The above curves intersect around 3 mm. Thus, both mechanical and acoustic properties should be balanced regarding structural size when designing a multi‐purpose vehicle component using the present composite. POLYM. COMPOS., 40:1315–1321, 2019. © 2018 Society of Plastics Engineers [ABSTRACT FROM AUTHOR]