Neural network detection of grinding burn from acoustic emission

An artificial neural network (ANN) approach is proposed for the detection of workpiece `burn', the undesirable change in metallurgical properties of the material produced by overly aggressive or otherwise inappropriate grinding. The grinding acoustic emission (AE) signals for 52100 bearing steel were collected and digested to extract feature vectors that appear to be suitable for ANN processing. Two feature vectors are represented: one concerning band power, kurtosis and skew; and the other autoregressive (AR) coefficients. The result (burn or no-burn) of the signals was identified on the basis of hardness and profile tests after grinding. The trained neural network works remarkably well for burn detection. Other signal-processing approaches are also discussed, and among them the constant false-alarm rate (CFAR) power law and the mean-value deviance (MVD) prove useful.

Control of thermal damage in grinding by digital signal processing of raw acoustic emission

Grinding process is usually the last finishing process of a precision component in the manufacturing industries. This process is utilized for manufacturing parts of different materials, so it demands results such as low roughness, dimensional and shape error control, optimum tool-life, with minimum cost and time. Damages on the parts are very expensive since the previous processes and the grinding itself are useless when the part is damaged in this stage. This work aims to investigate the efficiency of digital signal processing tools of acoustic emission signals in order to detect thermal damages in grinding process. To accomplish such a goal, an experimental work was carried out for 15 runs in a surface grinding machine operating with an aluminum oxide grinding wheel and ABNT 1045 e VC131 steels. The acoustic emission signals were acquired from a fixed sensor placed on the workpiece holder. A high sampling rate acquisition system at 2.5 MHz was used to collect the raw acoustic emission instead of root mean square value usually employed. In each test AE data was analyzed off-line, with results compared to inspection of each workpiece for burn and other metallurgical anomaly. A number of statistical signal processing tools have been evaluated.

In-process grinding monitoring through acoustic emission

This work aims to investigate the efficiency of digital signal processing tools of acoustic emission signals in order to detect thermal damages in grinding processes. To accomplish such a goal, an experimental work was carried out for 15 runs in a surface grinding machine operating with an aluminum oxide grinding wheel and ABNT 1045 Steel as work material. The acoustic emission signals were acquired from a fixed sensor placed on the workpiece holder. A high sampling rate data acquisition system working at 2.5 MHz was used to collect the raw acoustic emission instead of the root mean square value usually employed. Many statistical analyses have shown to be effective to detect burn, such as the root mean square (RMS), correlation of the AE, constant false alarm rate (CFAR), ratio of power (ROP) and mean-value deviance (MVD). However, the CFAR, ROP, Kurtosis and correlation of the AE have been presented more sensitive than the RMS. Copyright © 2006 by ABCM.

Study of utilization of petrol engine equipped with exhaust gas recirculation (EGR) and catalytic converter to reduce consumption and NOx emission

Study of consumption rate and gaseous pollutant emission from engine tests simulating real work conditions, using spark point manually controlled and exhaust gas recirculation (EGR) in diverse proportion levels. The objective of this work is to re-examine the potential of the EGR conception, a well-known method of combustion control, employed together electronic fuel injection and three-way catalytic converter closed-loop control at a spark ignition engine, verifying the performance characteristics and technical availability of this conception to improve pollution control, fuel economy at low torque drive condition and to improve the engine exhaust components useful life. The pollutant emissions and consumption levels under operational conditions simulations were analysed and compared with the expected by concerning theory and real tests performed by EGR equipped engines by factory. Copyright © 2006 Society of Automotive Engineers, Inc.

A novel straightforward compromising method for dynamic economic and emission dispatch considering valve-point effect

This paper proposes a straightforward compromising method to determine the output power of all committed units during the scheduling time horizon. Unlike the conventional methods that work based on a constant pollution control cost (CPCC), this method works based on the system topology such as demand, minimum cost and minimum output emission of the system. In order to have a meaningful compromise between costs and emission in economic and emission dispatch (EED) problem, a flexible pollution control cost (FPCC) is proposed. Also a dynamic economic emission dispatch (DEED) approach is considered where the ramping constraints couple the scheduling hours; the inclusion of valve-point effect makes the DEED modeling more practical. The validity and effectiveness of the unproblematic FPCC approach is verified through an IEEE 30-bus test system with 6 unit for the 6-hour scheduling horizon. © 2013 IEEE.

White Light and Multicolor Emission Tuning in Triply Doped Yb3+/Tm3+/Er3+ Novel Fluoro-phosphate Transparent Glass-ceramics

New Yb3+, Er3+ and Tm3+ doped fluoro-phosphate glasses belonging to the system NaPO3–YF3–BaF2–CaF2 and containing up to 10 wt% of rare-earth ion fluorides were prepared and characterized by differential scanning calorimetry, absorption spectroscopy and up-conversion emission spectroscopy under excitation with a 975 nm laser diode. Transparent and homogeneous glass-ceramics have been reproducibly obtained with a view to manage the red, green and blue emission bands and generate white light. X-ray diffraction as well as electron microscopy techniques have confirmed the formation of fluorite-type cubic nanocrystals at the beginning of the crystallization process while complex nanocrystalline phases are formed after a longer heat-treatment. The prepared glass-ceramics exhibit high optical transparency even after 170 h of thermal treatment. An improvement of up-conversion emission intensity – from 10 to 160 times larger – was measured in the glass-ceramics when compared to the parent glass, suggesting an important incorporation of the rare-earth ions into the crystalline phase(s). The involved mechanisms and lifetime were described in detail as a function of heat-treatment time. Finally, a large range of designable color rendering (from orange to turquoise through white) can be observed in these materials by controlling the laser excitation power and the crystallization rate.

Seasonal fluctuation of soil carbon dioxide emission in differently managed pastures

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)