A new implementation of PID‐type fuzzy controller for a battery grid‐supporting inverter in an autonomous distributed variable‐speed wind turbine

This paper presents a new implementation of a proportional‐integral‐derivative (PID)‐type fuzzy controller (PIDfc) for a battery grid‐supporting inverter to regulate the frequency and voltage of an autonomous distributed variable‐speed wind turbine (VSWT). The VSWT which drives a permanent magnet synchronous generator (PMSG) is assumed for demonstration. The PIDfc is built from a set of control rules that adopts the droop control method and uses only locally measurable frequency and voltage signals. The output control signals are determined from the knowledge base and the fuzzy inference. To ensure safe battery operating limits, we also propose a protection scheme called intelligent battery protection (IBP). Several simulation experiments are performed by using MATLAB/SimPowerSystems. Next, to verify the scheme's effectiveness, the simulation results are compared with the results of a conventional controller through some performance indices. The results demonstrate the effectiveness of the PIDfc scheme to control a grid‐supporting inverter of battery in the reduction of frequency and voltage fluctuations. © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Fatigue Failure of Flanged Thermowell

A fractured flanged thermowell was received for analysis. The fracture was located at the root of “U” insertion/immersion length which was welded to the flange. The failure of flanged thermowell was attributed to the vortex-induced fatigue. The failure was initiated by the weld failure to withstand the fluctuating load resulted from vortex after years of service. This weld failure then created stress raisers, as evidenced by the ratchet marks and river marks near the outer surface.     

Modelling and simulation of a distributed power generation system with energy storage to meet dynamic household electricity demand

Electrical consumption in a household is not stable but changeable in one day throughout a whole year. The consumption depends on weather, seasons and users. This characteristic of demand makes it difficult to design and build a distributed power generation system to meet the demand for a household. For this reason, a stand-alone distributed power generation system (DPGS) needs to be carefully designed not only to meet the dynamic household electricity demand, but also to be economical. Hence, for a DPGS, it is essential to utilise electrical energy storage (EES) unit to store the excessive energy while power generation is running at off-peak time; and then the EES may supply the stored energy during the peak demand period. This study investigates a distributed power generation system with an electric energy storage unit to meet the dynamic electricity demand in a household. The system composes of one diesel-engine-generator (DG) running with biofuel; a fuel cell; integrated with an energy storage unit including a supercapacitor and a group of batteries. Models have been set up in Dymola software and two different system configurations are proposed and simulated. The characteristics of the integrated DPGS–EES system are presented and discussed. The results show that both configurations are working properly to meet the demand.     

A multirobot system for autonomous deployment and recovery of a blade crawler for operations and maintenance of offshore wind turbine blades

Offshore wind farms will play a vital role in the global ambition of net zero energy generation. Future offshore wind farms will be larger and further from the coast, meaning that traditional human-based operations and maintenance approaches will become infeasible due to safety, cost, and skills shortages. The use of remotely operated or autonomous robotic assistants to undertake these activities provides an attractive alternative solution. This paper presents an autonomous multirobot system which is able to transport, deploy and retrieve a wind turbine blade inspection robot using an unmanned aerial vehicle (UAV). The proposed solution is a fully autonomous system including a robot deployment interface for deployment, a mechatronic link-hook module (LHM) for retrieval, both installed on the underside of a UAV, a mechatronic on-load attaching module installed on the robotic payload and an intelligent global mission planner. The LHM is integrated with a 2-DOF hinge that can operate either passively or actively to reduce the swing motion of a slung load by approximately 30%. The mechatronic modules can be coupled and decoupled by special maneuvers of the UAV, and the intelligent global mission planner coordinates the operations of the UAV and the mechatronic modules for synchronous and seamless actions. For navigation in the vicinity of wind turbine blades, a visual-based localization merged with the location knowledge from Global Navigation Satellite System has been developed. A proof-of-concept system was field tested on a full-size decommissioned wind-turbine blade. The results show that the experimental system is able to deploy and retrieve a robotic payload onto and from a wind turbine blade safely and robustly without the need for human intervention. The vicinity localization and navigation system have shown an accuracy of 0.65 and 0.44 m in the horizontal and vertical directions, respectively. Furthermore, this study shows the feasibility of systems toward autonomous inspection and maintenance of offshore windfarms.     

Effect of Cooling Rate and Neodymium Addition on Beta Intermetallic Phase of Al–Fe–Si Ternary System

Aluminium silicon alloys are widely used in automotive industry and other structural application. However, the presence of high content of iron element in Al–Si alloys lead to precipitation of beta intermetallic phase that has a detrimental effect on mechanical properties. Reducing the adverse effects of β-Al₉Fe₂Si₂ precipitates can be achieved by altering their morphology by adding element modifier and increasing solidification cooling rate. In this present work, simultaneous thermal analysis was used to study the effect of cooling rate (5, 10 and 30 °C min^?1) on beta phase formation in Al–7Si–1Fe alloy added with neodymium at 0.3, 0.6 and 1 wt%. The beta phase precipitates were then characterized using optical microscopy and scanning electron microscopy equipped with EDS. Image analysis results showed the reduction in size of beta intermetallic phase as a result of the rare earth addition. Further analysis also showed the refinement of eutectic silicon.     

Differential Thermal Analysis Assessment of Beta Phase Precipitation in Al-6.5Si-1Fe Alloy

Iron-bearing intermetallic phases formed during solidification of Al?CSi casting alloys are known for having detrimental effect on their mechanical properties. This is particularly the case of the ??-Al₅FeSi phase which precipitates as thin and extended plates. Many researchers already studied the factors that could influence the formation of this phase and in most cases it has been concluded that low-level additives (e.g. manganese) may lead to the replacement of the beta phase with other intermetallics that are less harmful because of being more compact.In this preliminary work, differential thermal analysis (DTA) was used to study the effect of cooling rate (0.2?C40?°C/min) on beta phase formation in Al-6.5Si-1Fe alloy. The effect of cooling rate on the characteristic temperature for phase changes was described and compared to literature information. The beta phase was then characterized using scanning electron microscopy and X-ray tomography. Metallographic analysis showed the phase morphology was heavily affected by the cooling rate, and parameters to quantify this have been selected and measured. Moreover, observation also revealed that some alpha phase precipitates at low cooling rate.     

Overfitting in semantics-based automated program repair

The primary goal of Automated Program Repair (APR) is to automatically fix buggy software, to reduce the manual bug-fix burden that presently rests on human developers. Existing APR techniques can be generally divided into two families: semantics- vs. heuristics-based. Semantics-based APR uses symbolic execution and test suites to extract semantic constraints, and uses program synthesis to synthesize repairs that satisfy the extracted constraints. Heuristic-based APR generates large populations of repair candidates via source manipulation, and searches for the best among them. Both families largely rely on a primary assumption that a program is correctly patched if the generated patch leads the program to pass all provided test cases. Patch correctness is thus an especially pressing concern. A repair technique may generate overfitting patches, which lead a program to pass all existing test cases, but fails to generalize beyond them. In this work, we revisit the overfitting problem with a focus on semantics-based APR techniques, complementing previous studies of the overfitting problem in heuristics-based APR. We perform our study using IntroClass and Codeflaws benchmarks, two datasets well-suited for assessing repair quality, to systematically characterize and understand the nature of overfitting in semantics-based APR. We find that similar to heuristics-based APR, overfitting also occurs in semantics-based APR in various different ways.