Intrinsic time-scale decomposition and graph signal processing are combined to effectively identify a rotor–stator rubbing fault. The vibration signal is decomposed into mutually independent ...rotational components, and then, the Laplacian energy index is obtained by the graph signal of the autocorrelation function of rotational components, and the signal is reconstructed by an autocorrelation function of each proper rotation (PR) component relative to smaller Laplacian energy index (less complexity). Finally, characteristics are extracted from rotor–stator rubbing faults in an aeroengine according to square demodulation spectrum of a reconstructed signal. To validate the effectiveness of the algorithm, a comparative analysis is made among traditional intrinsic time-scale decomposition algorithm, combination of intrinsic time-scale decomposition and autocorrelation function, and the proposed intrinsic time-scale decomposition–graph signal processing algorithm. Comparative result shows that the proposed intrinsic time-scale decomposition–graph signal processing algorithm is more precise and effective than the traditional intrinsic time-scale decomposition and intrinsic time-scale decomposition and autocorrelation function algorithms in extracting characteristic frequency and frequency multiplication of rotor–stator rubbing faults and can greatly reduce the number of noise components irrelevant to faults.
For effective identification of rub-impact faults between rotor and stator of equipment, the paper has contributed the method integrating dual complexity parameters and variational mode decomposition ...(VMD). Firstly, to effectively separate the fault characteristics involved in signals, VMD algorithm was applied to decompose vibration signals and the component signals were obtained; secondly, taking account of the large difference of fault feature information involved in different component signals and in order to make options of sensitive fault component signals and reduce the loss of fault features, multi-scale Lempel–Ziv complexity and complexity parameter in Hjorth parameters were brought. Starting from 2 different perspectives of complexity evaluation, choose from the sensitive component signals containing more fault characteristics with these 2 complexity parameters; thirdly, signals were reconstructed based on selected sensitive component signals, and meanwhile, singular value difference spectrum algorithm was used to denoise reconstructed signals to further lessen the influence of noises; finally, the rub-impact fault between rotor and stator was identified by square demodulation spectrum (SDS) of denoised signal. The effectiveness of the proposed method has been proved by comparative analysis with other approaches as well as validation analysis of rub-impact fault signals in multiple situations.
The combined effect of polystyrene (PS) particles and triphenyltin chloride (TPTCl) to the green algae
Chlorella pyrenoido
s
a
was studied. The 96 h IC
50
of TPTCl to the green algae
C. pyrenoidosa
...was 30.64 μg/L. The toxicity of PS particles to
C. pyrenoidosa
was size-dependent, with the 96 h IC
50
at 9.10 mg/L for 0.55 μm PS but no toxicity observed for 5.0 μm PS. The exposure to 0.55 μm PS led to damage on structure of algal cells, which could in turn cause inhibition on photosynthesis and population growth of the green algae. TPTCl concentrations in test medium were lowered by 15–19% at presence of 0.55 μm PS particles, indicating a reduced bioavailability of TPTCl. In spite of this reduced bioavailability, the presence of PS increased the toxicity of TPTCl, which might be attributed to facilitated uptake of TPTCl by the green algae after the damage of cell structure. The overall results of the present study provided important information on the effect of PS on the bioavailability and toxicity of TPTCl to phytoplankton species.
Bearing is the most vulnerable key part in rotating machine and bears important influence on the safety of equipment. Weakness and complexity are the two features of fault characteristic information ...carried by signals in the early stage of fault. For that, a fault is difficult to be recognized correctly. To identify a compound failure of bearing, the paper has brought forward a new self-adaptive option method for component signals that are sensitive to failure feature information of bearing. The sensitivity of kurtosis to bearing failure is exploited and the influence of signal complexity on the extraction of failure feature information is taken seriously, the paper has proposed the self-adaptive option method for component signals that are sensitive to failure feature by combined kurtosis with Complexity parameter included in Hjorth parameters. Furthermore, as the mid-value represents the general level of signal and is not affected by larger or smaller data, with the mid-values of kurtosis and Complexity parameter as the boundary, the paper has chosen the component signals which can more comprehensively show the failure features of bearing. Additionally, by principal component analysis (PCA), component signals selected are blended and reconstructed. Finally, by the Hilbert envelope spectrum of signals reconstructed, failure types of bearing are identified. To verify the effectiveness of presented method, the presented method is compared with conventional method on the basis of the exactly consistent data. The result indicates that the proposed method is superior to the traditional one in extracting fault information and identifying the multiple failure types of bearing.
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.
To accurately locate rotor–stator rubbing faults in aero-engine, a method combining intrinsic time scale decomposition (ITD), Hjorth parameter and cepstrum analysis has been proposed. First, the ...method works by decomposing vibration signals from casing into proper rotation components (PRCs) based on ITD; second, calculates the autocorrelation function of each rotation component and the complexity parameters of autocorrelation functions; third, chooses PRCs for signal reconstruction according to complexity from Hjorth parameters and reconstructs the signals based on chosen PRCs; at last, considering that with different positions of rubbing, transfer paths of signals collected by the sensors from the same position are different, cepstrum analysis has been made according to reconstructed signals, and the transfer paths characteristics from cepstrum are taken as feature vectors and inputted into support vector machine for identifying the positions of rotor-stator rubbing faults. The results indicate proposed ITD-Hjorth-Cepstrum method can work well in the identification rate of training and test samples as for the identification rate for an unknown sample.
Multi-frequency intravascular ultrasound (IVUS) imaging Teng Ma; Mingyue Yu; Zeyu Chen ...
IEEE transactions on ultrasonics, ferroelectrics, and frequency control,
2015-January, 2015-Jan, 2015-1-00, 20150101, Letnik:
62, Številka:
1
Journal Article
Recenzirano
Odprti dostop
Acute coronary syndrome (ACS) is frequently associated with the sudden rupture of a vulnerable atherosclerotic plaque within the coronary artery. Several unique physiological features, including a ...thin fibrous cap accompanied by a necrotic lipid core, are the targeted indicators for identifying the vulnerable plaques. Intravascular ultrasound (IVUS), a catheter-based imaging technology, has been routinely performed in clinics for more than 20 years to describe the morphology of the coronary artery and guide percutaneous coronary interventions. However, conventional IVUS cannot facilitate the risk assessment of ACS because of its intrinsic limitations, such as insufficient resolution. Renovation of the IVUS technology is essentially needed to overcome the limitations and enhance the coronary artery characterization. In this paper, a multi-frequency intravascular ultrasound (IVUS) imaging system was developed by incorporating a higher frequency IVUS transducer (80 to 150 MHz) with the conventional IVUS (30-50 MHz) system. The newly developed system maintains the advantage of deeply penetrating imaging with the conventional IVUS, while offering an improved higher resolution image with IVUS at a higher frequency. The prototyped multifrequency catheter has a clinically compatible size of 0.95 mm and a favorable capability of automated image co-registration. In vitro human coronary artery imaging has demonstrated the feasibility and superiority of the multi-frequency IVUS imaging system to deliver a more comprehensive visualization of the coronary artery. This ultrasonic-only intravascular imaging technique, based on a moderate refinement of the conventional IVUS system, is not only cost-effective from the perspective of manufacturing and clinical practice, but also holds the promise of future translation into clinical benefits.
Breakthroughs in the field of nanotechnology, especially in nanochemistry and nanofabrication technologies, have been attracting much attention, and various nanomaterials have recently been developed ...for biomedical applications. Among these nanomaterials, nanoscale titanium dioxide (nano-TiO2) has been widely valued in stomatology due to the fact of its excellent biocompatibility, antibacterial activity, and photocatalytic activity as well as its potential use for applications such as dental implant surface modification, tissue engineering and regenerative medicine, drug delivery carrier, dental material additives, and oral tumor diagnosis and treatment. However, the biosafety of nano-TiO2 is controversial and has become a key constraint in the development of nano-TiO2 applications in stomatology. Therefore, in this review, we summarize recent research regarding the applications of nano-TiO2 in stomatology, with an emphasis on its performance characteristics in different fields, and evaluations of the biological security of nano-TiO2 applications. In addition, we discuss the challenges, prospects, and future research directions regarding applications of nano-TiO2 in stomatology that are significant and worthy of further exploration.
Large-sized rotating machines usually contain weak feature information of rub-impact fault, which is hard to extract. General scale transformation stochastic resonance (GSTSR) can match input signals ...with different frequencies by using the optimal barrier height and boost the weak fault feature in signals. The performance of GSTSR is determined by systemic parameters. When a rub-impact fault occurs between rotor and stator, vibration signals are often accompanied by an impact. Therefore, the paper takes advantage of sensibility of waveform factor to rub-impact fault information and margin factor to impact properties of signal and reconstructs a new signal evaluation index based on waveform and margin factors. The signal evaluation index is treated as the fitness function of grey wolf optimization (GWO) algorithm and combined with GSTSR to perform a comprehensive evaluation to rub-impact fault feature information. The result of comparison with conventional method (with signal to noise ratio (SNR) as fitness function) indicates that in case of extracting rub-impact fault features, the proposed method identifies a rotor-stator rub-impact fault more precisely than the classical method.
PDF
