Bearings are not only the most important element but also a common source of failures in rotary machinery. Bearing fault prognosis technology has been receiving more and more attention recently, in particular because it plays an increasingly important role in avoiding the occurrence of accidents. Therein, fault feature extraction (FFE) of bearing accelerometer sensor signals is essential to highlight representative features of bearing conditions for machinery fault diagnosis and prognosis. This paper proposes a spectral regression (SR)-based approach for fault feature extraction from original features including time, frequency and time-frequency domain features of bearing accelerometer sensor signals. SR is a novel regression framework for efficient regularized subspace learning and feature extraction technology, and it uses the least squares method to obtain the best projection direction, rather than computing the density matrix of features, so it also has the advantage in dimensionality reduction. The effectiveness of the SR-based method is validated experimentally by applying the acquired vibration signals data to bearings. The experimental results indicate that SR can reduce the computation cost and preserve more structure information about different bearing faults and severities, and it is demonstrated that the proposed feature extraction scheme has an advantage over other similar approaches.

Decarboxylative cross-coupling reactions of cinnamic acids with sulfonylhydrazides were explored using oxygen as the sole terminal oxidant, realizing a conceptually novel technology for vinyl sulfone synthesis under the synergistic interactions of visible light irradiation, organic dye-type photocatalyst eosin Y, KI, and Cs2CO3 at room temperature.

Visible-light-enabled photocatalytic carbotrifluoro-methylations of allylic alcohols and sodium triflinate were explored through 1,2-migration of an aryl group, affording an efficient method for synthesis of b-trifluoromethyl-a-substituted carbonyl compounds under mild reaction conditions. This catalyst system is well tolerant of various synthetically useful functional groups.