Morphology genetic 3D hierarchical SnO2microstructures constructed by Sub 5 nm nanocrystals for highly sensitive ethanol-sensor.

SnO2is widely used for ethanol-sensing applications due to its excellent physicochemical properties, low toxicity and high sensitivity. However it is a challenge to construct 3D-hierarchical structures with sub 5 nm primary grain particle, which is the optimized size for ethanol sensor. Herein, genetic tri-level hierarchical SnO2microstructures are synthesised by the genetic conversion of 3D hierarchical SnS2flowers assembled by ultrathin nanosheets. The SnS2nanosheets are morphology genetic converted to porous nanosheets with sub 5 nm SnO2nanoparticles during the calcination process. When used for the detection of ethanol, the sensor exhibits a high sensitivity of 0.5 ppm (Ra/Rg = 6.8) and excellent gas-sensing response (Ra/Rg= 183 to 100 ppm) with short response/recovery time (12 s/11 s). The excellent gas sensing performance is much better than that of the previous reported SnO2-based sensors. The highly sensitivity is attributed to the large surface area derived from the recrystallization and volume changes, which offers more active sites during the morphology genetic conversion from SnS2to SnO2. Furthermore, the flower-like 3D structure enhances the stability of the materials and is beneficial for the mass diffusion dynamics of ethanol.

A hybrid intelligent multi-fault detection method for rotating machinery based on RSGWPT, KPCA and Twin SVM.

This paper proposes a hybrid intelligent method for multi-fault detection of rotating machinery, in which three methods, i.e. including the redundant second generation wavelet package transform (RSGWPT), the kernel principal component analysis (KPCA) and the twin support vector machine (TWSVM), are combined. Firstly, RSGWPT is used to extract feature vectors from representative statistical characteristics in the decomposition frequency band, and then the KPCA in the feature space is performed to reduce the dimension of features and to extract the dominant features for the following classification. Finally, a novel support vector machine, called twin support vector machine is used to construct a multi-class classifier. Inputting superior features to this classifier, the condition of the monitored machine component can be determined. Experimental results demonstrate that the proposed hybrid method is effective for multi-fault detection of rotating machinery. The TWSVM is also indicated that has better classification performance and faster convergence speed than the normal SVM.

Novel Downhole Electromagnetic Flowmeter for Oil-Water Two-Phase Flow in High-Water-Cut Oil-Producing Wells.

First, the measuring principle, the weight function, and the magnetic field of the novel downhole inserted electromagnetic flowmeter (EMF) are described. Second, the basic design of the EMF is described. Third, the dynamic experiments of two EMFs in oil-water two-phase flow are carried out. The experimental errors are analyzed in detail. The experimental results show that the maximum absolute value of the full-scale errors is better than 5%, the total flowrate is 5-60 m³/d, and the water-cut is higher than 60%. The maximum absolute value of the full-scale errors is better than 7%, the total flowrate is 2-60 m³/d, and the water-cut is higher than 70%. Finally, onsite experiments in high-water-cut oil-producing wells are conducted, and the possible reasons for the errors in the onsite experiments are analyzed. It is found that the EMF can provide an effective technology for measuring downhole oil-water two-phase flow.

Manchester code telemetry system for well logging using quasi-parallel inductive-capacitive resonance.

In this paper, a quasi-parallel inductive-capacitive (LC) resonance method is proposed to improve the recovery of MIL-STD-1553 Manchester code with several frequency components from attenuated, distorted, and drifted signal for data telemetry in well logging, and corresponding telemetry system is developed. Required resonant frequency and quality factor are derived, and the quasi-parallel LC resonant circuit is established at the receiving end of the logging cable to suppress the low-pass filtering effect caused by the distributed capacitance of the cable and provide balanced pass for all the three frequency components of the Manchester code. The performance of the method for various encoding frequencies and cable lengths at different bit energy to noise density ratios (Eb/No) have been evaluated in the simulation. A 5 km single-core cable used in on-site well logging and various encoding frequencies were employed to verify the proposed telemetry system in the experiment. Results obtained demonstrate that the telemetry system is feasible and effective to improve the code recovery in terms of anti-attenuation, anti-distortion, and anti-drift performances, decrease the bit error rate, and increase the reachable transmission rate and distance greatly.