Recurrent neural network for pitch control of variable-speed wind turbine.

Wind is one of the most widely used renewable energy sources due to its cost-effectiveness, power requirements, operation, and performance. There are many challenges in wind turbines, such as wind fluctuation, pitch control, and generator speed control. When the wind speed exceeds its rated value, the pitch angle controller limits the generator output power to its rated value. In this research work, several soft computing techniques have been implemented for pitch control of variable-speed wind turbine. The data is collected for the National Renewable Energy Laboratory offshore 5 MW baseline wind turbine. Wind speed, tip speed ratio, and power coefficient are taken as inputs, and pitch angle as output. Machine learning and artificial intelligence-based techniques such as recurrent neural networks (RNNs), adaptive neuro-fuzzy inference system (ANFIS), multilayer perceptron feed-forward neural network (MLPFFNN), and fuzzy logic controller (FLC) are implemented on MATLAB, and their results are evaluated in terms of mean square error (MSE) and root mean square error (RMSE). The controllers have been implemented in MATLAB/Simulink to schedule the wind turbine blade pitch angle and keep the output power stable at the rated value. The experimental results show that RNN provided the best results for 15 neurons in hidden layers and 1000 epochs with MSE of 3.28e-11 and RMSE of 5.54e-06, followed by MLPFFNN with MSE of 2.17e-10 and RMSE of 1.56e-05, ANFIS with MSE of 8.5e-05 and RMSE of 9.22e-03, and FLC with MSE of 6.25e-04 and RMSE of 0.025. The proposed scheme is more reliable and robust and can be easily implemented on a physical setup by using interfacing cards such as dSPACE, NI cards, and data acquisition cards.

Needs, Requirements and a Concept of a Tool Condition Monitoring System for the Aerospace Industry.

In this paper, we describe the needs and specific requirements of the aerospace industry in the field of metal machining; specifically, the concept of an edge-computing-based production supervision system for the aerospace industry using a tool and cutting process condition monitoring system. The new concept was developed based on experience gained during the implementation of research projects in Poland's Aviation Valley at aerospace plants such as Pratt & Whitney and Lockheed Martin. Commercial tool condition monitoring (TCM) and production monitoring systems do not effectively meet the requirements and specificity of the aerospace industry. The main objective of the system is real-time diagnostics and sharing of data, knowledge, and system configurations among technologists, line bosses, machine tool operators, and quality control. The concept presented in this paper is a special tool condition monitoring system comprising a three-stage (natural wear, accelerated wear, and catastrophic tool failure) set of diagnostic algorithms designed for short-run machining and aimed at protecting the workpiece from damage by a damaged or worn tool.

Feasibility of Cobalt-Free Nanostructured WC Cutting Inserts for Machining of a TiC/Fe Composite.

The paper presents results of investigations on the binderless nanostructured tungsten carbide (WC) cutting tools fabrication and performance. The scientific novelty includes the description of some regularities of the powder consolidation under electric current and the subsequent possibility to utilize them for practical use in the fabrication of cutting tools. The sintering process of WC nanopowder was performed with the electroconsolidation method, which is a modification of spark plasma sintering (SPS). Its advantages include low temperatures and short sintering time which allows retaining nanosize grains of ca. 70 nm, close to the original particle size of the starting powder. In respect to the application of the cutting tools, pure WC nanostructure resulted in a smaller cutting edge radius providing a higher quality of TiC/Fe machined surface. In the range of cutting speeds, vc = 15-40 m/min the durability of the inserts was 75% of that achieved by cubic boron nitride ones, and more than two times better than that of WC-Co cutting tools. In additional tests of machining 13CrMo4 material at an elevated cutting speed of vc = 100 m/min, binderless nWC inserts worked almost three times longer than WC-Co composites.