A New Method Based on Time-Varying Filtering Intrinsic Time-Scale Decomposition and General Refined Composite Multiscale Sample Entropy for Rolling-Bearing Feature Extraction.

The early fault diagnosis of rolling bearings has always been a difficult problem due to the interference of strong noise. This paper proposes a new method of early fault diagnosis for rolling bearings with entropy participation. First, a new signal decomposition method is proposed in this paper: intrinsic time-scale decomposition based on time-varying filtering.

Rolling Bearing Fault Diagnosis Based on Refined Composite Multi-Scale Approximate Entropy and Optimized Probabilistic Neural Network.

A rolling bearing early fault diagnosis method is proposed in this paper, which is derived from a refined composite multi-scale approximate entropy (RCMAE) and improved coyote optimization algorithm based probabilistic neural network (ICOA-PNN) algorithm. Rolling bearing early fault diagnosis is a time-sensitive task, which is significant to ensure the reliability and safety of mechanical fault system. At the same time, the early fault features are masked by strong background noise, which also brings difficulties to fault diagnosis.

An enhanced extrapolation method based on particle swarm optimization-support vector regression to determine the friction coefficient between aircraft tire and runway surface.

This paper proposes a hybrid pretreating method in the support vector regression (SVR) machines to enhance the extrapolated performance of the traditional method based on particle swarm optimization (PSO)-SVR. This method is introduced into a novel domain wherein the friction coefficient (COF) is extrapolated between the aircraft tire and the runway surface. It includes two parts: the normalized data and the extrapolated method for COF.

Fault Feature Extraction and Diagnosis of Rolling Bearings Based on Enhanced Complementary Empirical Mode Decomposition with Adaptive Noise and Statistical Time-Domain Features.

In this paper, a novel method is proposed to enhance the accuracy of fault diagnosis for rolling bearings. First, an enhanced complementary empirical mode decomposition with adaptive noise (ECEEMDAN) method is proposed by determining two critical parameters, namely the amplitude of added white noise (AAWN) and the ensemble trails (ET). By introducing the concept of decomposition level, the optimal AAWN can be determined by judging the mutation of mutual information (MI) between adjacent intrinsic mode functions (IMFs).

Dissipation of two field-incurred pesticides and three degradation products in rice (Oryza sativa L.) from harvest to dining table.

Background: High levels of harmful pesticide residues in rice can cause undesirable side effects and are a source of great concern to consumers. Reduction of pesticide residues to provide rice security has thus became an urgent problem.

Results: In this study, the effects of commercial and home processing on removal of chlorpyrifos and carbosulfan residues from rice, and the formation of metabolites during processing, were studied.

Experimental rig to estimate the coefficient of friction between tire and surface in airplane touchdown simulations.

To estimate the coefficient of friction between tire and runway surface during airplane touchdowns, we designed an experimental rig to simulate such events and to record the impact and friction forces being executed. Because of noise in the measured signals, we developed a filtering method that is based on the ensemble empirical mode decomposition and the bandwidth of probability density function of each intrinsic mode function to extract friction and impact force signals. We can quantify the coefficient of friction by calculating the maximum values of the filtered force signals.

[Experiment study on the metamorphic amylum production wastewater treatment by anaerobic baffled reactor].

The present study reports the start-up of treating metamorphic amylum production wastewater by anaerobic baffled reactor (ABR) and the bio-chemical features of granular sludge. The optimal conditions in treatment of the metamorphic amylum production wastewater were proposed, and the running performance in treating salt-containing wastewater was studied. Our results show that the common anaerobic activated sludge can be acclimated by increasing the organic loading and salt-concentration at the same time, and the granular sludge tolerant to low salt can be achieved by the acclimation.