Complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) effectively separates the fault vibration signals of rolling bearings and improves the diagnosis of rolling bearing faults. However, CEEMDAN has high memory requirements and low computational efficiency. In each iteration of CEEMDAN, fault vibration signals are added with noises, both the vibration signals added with noises and the added noises are decomposed with classical empirical mode decomposition (EMD). This paper proposes a rolling bearing fault diagnosis method that combines piecewise aggregate approximation (PAA) with CEEMDAN. PAA enables CEEMDAN to decompose long signals and to achieve enhanced diagnosis. In particular, the method first yields the vibration envelope using bandpass filtering and demodulation, then compresses the envelope using PAA, and finally decomposes the compressed signal with CEEMDAN. Test data verification results show that the proposed method is more effective and more efficient than CEEMDAN.
Three new species isolated from sugarcane rhizosphere in China, namely Conlariumbaiseensesp. nov., C.nanningensesp. nov., and C.saccharisp. nov., are described and illustrated. Molecular evidence (phylogenetic analysis of combined LSU, SSU, ITS and RPB2 sequence data) and phenotypical characters support their independent status from related and similar species. The new species, as dark spetate endophytes, inhabit sugarcane rhizosphere and can form a symbiosis with sugarcane.
We isolated a new species, proposed here as Serendipita sacchari, from a sugarcane rhizosphere in Guangxi Province, China. This species is characterized by its unstable nucleus numbers (1–15) in its chlamydospores versus their regular distribution in hyphal cells. ITS rDNA
and combined LSU+ TEF1-α sequence analyses also support the uniqueness of this new plant symbiont.
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