RESUMO
When rotating machinery fails, the consequent vibration signal contains rich fault feature information. However, the vibration signal bears the characteristics of nonlinearity and nonstationarity, and is easily disturbed by noise, thus it may be difficult to accurately extract hidden fault features. To extract effective fault features from the collected vibration signals and improve the diagnostic accuracy of weak faults, a novel method for fault diagnosis of rotating machinery is proposed. The new method is based on Fast Iterative Filtering (FIF) and Parameter Adaptive Refined Composite Multiscale Fluctuation-based Dispersion Entropy (PARCMFDE). Firstly, the collected original vibration signal is decomposed by FIF to obtain a series of intrinsic mode functions (IMFs), and the IMFs with a large correlation coefficient are selected for reconstruction. Then, a PARCMFDE is proposed for fault feature extraction, where its embedding dimension and class number are determined by Genetic Algorithm (GA). Finally, the extracted fault features are input into Fuzzy C-Means (FCM) to classify different states of rotating machinery. The experimental results show that the proposed method can accurately extract weak fault features and realize reliable fault diagnosis of rotating machinery.
RESUMO
The changes in the qualities and sweet-substance levels of Junzao jujube during variable-temperature drying (VTD) were investigated. The results showed that VTD retains the original color of jujube, reduces its hardness and chewiness, and decreases its wrinkling while shortening the drying time by 13.2% compared with that of constant temperature drying (CTD). "Electronic-tongue" taste analysis showed that the sweetness of VTD jujube is significantly higher than that for CTD. This is shown to be related to the contents of sucrose, fructose, and glucose, as well as the activities of invertase and sucrose synthase enzymes. In addition, the content trends for sweet amino acids are correlated with the temperature gradient used in VTD. Thus, the present study elucidates the factors governing the transformation of sugar substances in jujube during VTD, as well as providing a practical reference for the application of VTD in the jujube industry.
RESUMO
This study investigated the effects of convective drying(CD) and freeze drying(FD) on bioactive and volatile components in jujube. No significant difference in total phenolic, total flavonoids and antioxidant capacity among CD60, CD70, CD80 and FD samples (P > 0.05). LC-MS/MS analysis showed that this trend mainly originated from the dynamic equilibrium relationships between caffeic acid, chlorogenic acid, p-hydroxybenzoic acid, rutin, epicatechin, and quercetin. HS-SPME-GC-MS identified 31 volatile organic compounds (VOCs) comprising more than 80% aldehydes and acids. Principal component analysis distinguished the VOC characteristics of samples subjected to different drying methods. Six VOCs had an odor activity value (OAV) >1, most of which were fatty acid oxidation or Maillard reaction products. Combined with the precursor components, these reactions were speculated to be the major VOC-producing pathways in dried jujube. Considering the bioactive components and flavor retention, CD at 60 °C was an effective drying method with potential to replace FD.