To effectively extract the information of compound faults of inter-shaft bearing of an aero-engine based on casing vibration signals, the paper has introduced the concept of weighted Katz fractal dimension and proposed the method combining information fusion, wavelet transform (WT), singular value decomposition (SVD), and Katz fractal dimension, the cross-correlation function (CCF-WT-SVD-Katz algorithm). The method includes homologous information fusion achieved by the CCF of horizontal and vertical vibration signals of the rotor from the same section; signal separation and denoising of blended signals through WT and SVD; reinforcement of fault characteristics of signals according to weighted Katz fractal dimension; and extraction of characteristic frequencies of compound faults of inter-shaft bearing by frequency spectrum of weighted and reconstructed signals. The result indicates that the proposed CCF-WT-SVD-Katz algorithm is capable of effectively extracting compound fault characteristics of inter-shaft bearing and precisely identifying a fault type based on whole casing vibration signals and will be of very good application value in engineering.

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To effectively identify the rotor–stator rubbing fault, the paper has brought forward a method combining principal component analysis (PCA), intrinsic time-scale decomposition (ITD), and information entropy (IE). Firstly, in considering that the characteristic information of faults extracted from the information collected by single sensor is not complete or comprehensive, the approach blends the vibration signals collected from 4 different positions at the same moment based on PCA algorithm; secondly, regarding that ITD algorithm can effectively avoid the problems of poor adaptivity and end effect, blended signals are broken down based on ITD algorithm; thirdly, calculate the IE of self-correlation function of each PRC based on the fact that the smaller IE is, the less confusion system has and the easier it is to extract fault characteristics, and treat the self-correlation function of PRC related with the minimum IE as optimal component to represent fault characteristics; fourthly, characteristic extraction of rotor–stator rubbing fault and identification are done on the basis of the frequency spectrum of optimal component. To prove the availability of method, vibration signals are subjected to validation and analysis, which are collected from different rotation speeds, casing thicknesses, rubbing positions, and types. The result indicates that the proposed PCA–ITD–IE can equally and effectively extract the characteristics of rotor–stator rubbing faults of aero-engine involved in various conditions.

Herein, we developed an efficient and convenient method to address the problem of thickener decomposition in the low- permeability oilfield production process. It is crucial to design breakers that reduce viscosity by delaying thickener decomposition in appropriate environments. By using lignin in biomass as a substrate for β-mannanase immobilization (MIL), we fabricated a gel breaker, surface gelatin-coated β-mannanase-immobilized lignin (Ge@MIL). Through experiments and performance tests, we confirmed that the prepared Ge@MIL can release enzymes at a specific temperature, meanwhile having temperature-sensitive phase change properties and biodegradability. The results also show the tight tuning over the surface coating of Ge@MIL by a water-in-oil emulsion. Therefore, the prepared Ge@MIL has a promising application in the field of oil extraction as a green and efficient temperature-sensitive sustained-release capsule.