Evaluation of Hand-Crafted Feature Extraction for Fault Diagnosis in Rotating Machinery: A Survey.

This article presents a comprehensive collection of formulas and calculations for hand-crafted feature extraction of condition monitoring signals. The documented features include 123 for the time domain and 46 for the frequency domain. Furthermore, a machine learning-based methodology is presented to evaluate the performance of features in fault classification tasks using seven data sets of different rotating machines. The evaluation methodology involves using seven ranking methods to select the best ten hand-crafted features per method for each database, to be subsequently evaluated by three types of classifiers. This process is applied exhaustively by evaluation groups, combining our databases with an external benchmark. A summary table of the performance results of the classifiers is also presented, including the percentage of classification and the number of features required to achieve that value. Through graphic resources, it has been possible to show the prevalence of certain features over others, how they are associated with the database, and the order of importance assigned by the ranking methods. In the same way, finding which features have the highest appearance percentages for each database in all experiments has been possible. The results suggest that hand-crafted feature extraction is an effective technique with low computational cost and high interpretability for fault identification and diagnosis.

Testing the environmental Kuznets curve hypothesis in terms of ecological footprint and CO2 emissions through energy diversification for Turkey.

This research work analyzes the relationship between environmental degradation, economic growth, trade openness, primary energy consumption, coal consumption, and hydroelectricity consumption in Turkey from 1971 to 2015 using the autoregressive distributed lag (ARDL) time series approach through the hypothesis of the environmental Kuznets curve (EKC). Carbon dioxide (CO2) emissions and ecological footprint are both used as indicators of environmental degradation, which employs six different models. According to the results found in this study, while trade openness increases CO2 emissions, it decreases ecological footprint in the long-run. Coal consumption raises both CO2 emissions and ecological footprint. While hydroelectric energy reduces CO2 emissions, it has no effect on the environment. The results demonstrate that the EKC hypothesis is correct for both CO2 emissions and Turkey's ecological footprint. The threshold points are investigated as $18,704, $16,361, and $13,571 in models, where CO2 emissions are the dependent variable. In models where the ecological footprint is the dependent variable, the investigated threshold points of $11,824, $11,821, and $15,476 are higher than the gross domestic product (GDP) per capita during the analysis periods. Furthermore, the findings highlight the importance of renewable energy use in reducing environmental degradation and coal use in increasing environmental degradation. These findings can shed light on the importance of transition to renewable energy sources (i.e., hydroelectricity consumption), from fossil fuels (i.e., coal consumption), related to future planning in energy diversification for Turkey.

Development of a Linear Acoustic Array for Aero-Acoustic Quantification of Camber-Bladed Vertical Axis Wind Turbine.

Vertical axis wind turbines (VAWT) are a source of renewable energy and are used for both industrial and domestic purposes. The study of noise characteristics of a VAWT is an important performance parameter for the turbine. This study focuses on the development of a linear microphone array and measuring acoustic signals on a cambered five-bladed 45 W VAWT in an anechoic chamber at different tip speed ratios. The sound pressure level spectrum of VAWT shows that tonal noises such as blade passing frequencies dominate at lower frequencies whereas broadband noise corresponds to all audible ranges of frequencies. This study shows that the major portion of noise from the source is dominated by aerodynamic noises generated due to vortex generation and trailing edge serrations. The research also predicts that dynamic stall is evident in the lower Tip speed ratio (TSR) region making smaller TSR values unsuitable for a quiet VAWT. This paper compares the results of linear aeroacoustic array with a 128-MEMS acoustic camera with higher resolution. The study depicts a 3 dB margin between two systems at lower TSR values. The research approves the usage of the 8 mic linear array for small radius rotary machinery considering the results comparison with a NORSONIC camera and its resolution. These observations serve as a basis for noise reduction and blade optimization techniques.

Investigation of Heat Transfer and Pressure Drop in Microchannel Heat Sink Using Al2O3 and ZrO2 Nanofluids.

A new micro heat exchanger was analyzed using numerical formulation of conjugate heat transfer for single-phase fluid flow across copper microchannels. The flow across bent channels harnesses asymmetric laminar flow and dean vortices phenomena for heat transfer enhancement. The single-channel analysis was performed to select the bent channel aspect ratio by varying width and height between 35-300 µm for Reynolds number and base temperature magnitude range of 100-1000 and 320-370 K, respectively. The bent channel results demonstrate dean vortices phenomenon at the bend for Reynolds number of 500 and above. Thermal performance factor analysis shows an increase of 18% in comparison to straight channels of 200 µm width and height. Alumina nanoparticles at 1% and 3% concentration enhance the Nusselt number by an average of 10.4% and 23.7%, respectively, whereas zirconia enhances Nusselt number by 16% and 33.9% for same concentrations. On the other hand, thermal performance factor analysis shows a significant increase in pressure drop at high Reynolds number with 3% particle concentration. Using zirconia for nanofluid, Nusselt number of the bent multi-channel model is improved by an average of 18% for a 3% particle concentration as compared to bent channel with deionized water.