Current Issue : April - June Volume : 2020 Issue Number : 2 Articles : 5 Articles
In state analysis of rolling bearings using collaborative representation theory, how to construct an excellent redundant dictionary\nto collaboratively represent the acquired normal or abnormal data has been being a significant issue. Thus, a new method for fault\ndetection and classification of rolling bearings is proposed in this paper. The proposed algorithm mainly consists of three\ncomponents. First, a wavelet transform is employed to extract features, which takes advantage of the observation that vibration\nsignals under different conditions have similar frequency spectra. This similarity ensures that we can collaboratively represent any\ntest sample by using training samples. Second, under the similarity assumption, a dictionary pair learning strategy is employed to\nbuild an overcomplete dictionary pair, which is used to realize an optimal representation of the vibration signal. Meanwhile, the\nsparse constraint is also taken into account during dictionary training to enhance the robustness of the classification. Finally, the\nlearned dictionary combined with collaborative representation is used to intelligently perform pattern classification of rolling\nbearings. The effectiveness and superiority of the method are verified by applying the proposed algorithm on the simulated and\nreal vibration signals. The results show that, for different fault categories generated from different fault size and motor loads, our\nmethod can rapidly and accurately identify the fault category to which the input sample belongs....
Diamond-like carbon (DLC) is a metastable amorphous material that exhibits\nunique properties. However, there are many limitations regarding the use of\nthis material due to factors such as its tribological characteristics at high\ntemperature and limited thermal stability. In this study, the thermal stability\nand tribological properties of DLC/silicon-nitrogen (DLC/Si-N) composite\nfilms were investigated and compared to those of pure DLC films. All the\nfilms were synthesized using a combination of radio frequency (RF) magnetron\nsputtering and plasma-based ion implantation (PBII) (a so-called sputtering-\nPBII hybrid system) which is newly developed by us. A high purity silicon\nnitride (99.9%) disk was used as the target, applying an RF power in the\nrange of 500 - 700 W and a negative pulsed bias voltage of 5 kV to the substrate.\nAn Ar-CH4 mixture was used as the reactive gas. The CH4 partial\npressure was varied between 0 and 0.15 Pa, while the total gas pressure and\ntotal gas flow were fixed at 0.30 Pa and 30 sccm, respectively. The structures\nof the resulting films were characterized using Raman spectroscopy, while the\nthermal stabilities were assessed using thermogravimetric-differential thermal\nanalysis (TG-DTA) and friction coefficients were obtained via ball-on-disk\nfriction tests. The results indicate that the DLC/Si-N composite films produced\nin this work exhibit improved thermal stability relative to that of pure\nDLC owing to the presence of thermally stable atomic-scale Si-N compound\nin the carbon main flame networks. A DLC/Si-N film containing approximately\n11 at.%Si and 18.5 at.%N shows good thermal stability in air over\n800DegreeC up to 1100DegreeC, together with excellent tribological performance at 500DegreeC\nin air. Overall, the data demonstrate that DLC/Si-N composite films offer\nimproved thermal stability and superior tribological performance at high\ntemperatures....
With the development of ship enlargement, the problems of coupling vibration between hull and propulsion system and vibration\ntransmission via bearings are more and more prominent. Based on the theory of shaft vibration and the experimental system for\ndynamic characteristics of the shaft, an experiment plan about propulsion shaft vibration under dynamic excitations is designed in\nthis paper. The performance of propulsion shaft vibration under hull deformation excitations applied on intermediate and stern\nbearings is studied. Hydraulic excitations in horizontal and vertical directions on the intermediate bearing and stern bearing of the\nexperimental model of propulsion shaft are considered in this paper to simulate hull deformation on bearings of the ship.\nVibration characteristics of the shaft under different excitations are gained and coupling effects are discussed. Moreover, the\ninfluences of amplitude and direction of excitations on bearings and the shaft rotation speed on the vibration of propulsion are\nstudied. The results show that aiming at improving the safety and reliability of navigation, the hull deformation, especially the\nhorizontal hull deformation excitation on the intermediate bearing, is not neglectable and should be considered during primary\ndesign. Also, rotation speed and resonant frequency are needed to be well designed with the frequencies of hull\ndeformation excitations....
To accurately diagnose fine-grained fault of rolling bearing, this paper proposed a new fault diagnosis method combining\nmultisynchrosqueezing transform (MSST) and sparse feature coding based on dictionary learning (SFC-DL). Firstly, the highresolution\ntime-frequency images of raw vibration signals, including different kinds of fine-grained faults of rolling bearing, were\nconstructed by MSST. Then, the basis dictionary was trained through nonnegative matrix factorization with sparseness constraints\n(NMFSC), and the trained basis dictionary was employed to extract features from time-frequency matrixes by using nonnegative\nlinear equations. Finally, a linear support vector machine (LSVM) was trained with features of training samples, and the trained\nLSVM was employed to diagnosis the fault classification of test samples. Compared with state-of-the-art fault diagnosis methods,\nthe proposed method, which was tested on the bearing dataset from Case Western Reserve University (CWRU), achieved the finegrained\nclassification of 10 mixed fault states. Meanwhile, the proposed method was applied on the dataset from the Machinery\nFailure Prevention Technology (MFPT) Society and realized the classification of 3 fault states under different working conditions.\nThese results indicate that the proposed method has great robustness and could better meet the needs of practical engineering....
Corn stalk fibre reinforced nonasbestos environment-friendly friction composite materials have been fabricated, and their\nphysical, mechanical, and tribological properties are characterized. The tribological properties of the friction composites were\nevaluated following GB5763-2008 norms on a constant-speed-type friction tester. The experimental outcome reveals that the\ncontent of corn stalk fibre has a noteworthy impact on the tribological, mechanical, and physical properties of the friction\ncomposites. Specifically, the friction composite with a content of 7% exhibited excellent friction and wear properties. The worn\nsurface morphology of friction composites was further investigated using a scanning electron microscope. It was found that the\ncorn stalk fibre content greatly affected the tribological properties of the friction composites....
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