Leak Detection of Gas Pipelines Based on Characteristics of Acoustic Leakage and Interfering Signals

When acoustic method is used in leak detection for natural gas pipelines,the external interferences including operation of compressor and valve,pipeline knocking,etc.,should be distinguished with acoustic leakage signals to improve the accuracy and reduce false alarms.In this paper,the technologies of extracting characteristics of acoustic signals were summarized.The acoustic leakage signals and interfering signals were measured by experiments and the characteristics of time-domain,frequency-domain and time-frequency domain were extracted.The main characteristics of time-domain are mean value,root mean square value,kurtosis,skewness and correlation function,etc.The features in frequency domain were obtained by frequency spectrum analysis and power spectrum density,while time-frequency analysis was accomplished by short time Fourier transform.The results show that the external interferences can be removed effectively by the characteristics of time domain,frequency domain and time-frequency domain.It can be drawn that the acoustic leak detection method can be applied to natural gas pipelines and the characteristics can help reduce false alarms and missing alarms.

Extraction Characteristics of Radio Frequency ICP Ion Source

An inductively coupled radio frequency ion source has been developed and its extraction characteristics measured. Beam current density up to 0.11 mA/ cm2 was obtained with argon at a rf discharge power of about 140 W. The dependences of ion beam on the discharge parameters such as rf source power, gas pressure and gas flow rate was studied.

EXTRACTION OF CHARACTERISTIC ROOTS ON BESSEL-NEUMANN’S MIXED EQUATIONS

This paper discusses the problem of the extraction of characteristic roots on Bessel-Neumann's mixed equations. It gives the expressions and the evaluation of the minimum root. The advantage of the method has no use for the table of the multi-figure number Bessel function and it does not need computer but can calculate all the characteristic roots The precision of these roots is still high.

PREDICTION TECHNIQUES OF CHAOTIC TIME SERIES AND ITS APPLICATIONS AT LOW NOISE LEVEL

The paper not only studies the noise reduction methods of chaotic time series with noise and its reconstruction techniques, but also discusses prediction techniques of chaotic time series and its applications based on chaotic data noise reduction. In the paper, we first decompose the phase space of chaotic time series to range space and null noise space. Secondly we restructure original chaotic time series in range space. Lastly on the basis of the above, we establish order of the nonlinear model and make use of the nonlinear model to predict some research. The result indicates that the nonlinear model has very strong ability of approximation function, and Chaos predict method has certain tutorial significance to the practical problems.

Method of Fire Image Identification Based on Optimization Theory

In view of some distinctive characteristics of the early-stage flame image, a corresponding method of characteristic extraction is presented. Also introduced is the application of the improved BP algorithm based on the optimization theory to identifying fire image characteristics. First the optimization of BP neural network adopting Levenberg-Marquardt algorithm with the property of quadratic convergence is discussed, and then a new system of fire image identification is devised. Plenty of experiments and field tests have proved that this system can detect the early-stage fire flame quickly and reliably.

Numerical simulation and experimental research on an inductively coupled RF plasma cathode

In this study,numerical simulation and discharge current tests were conducted on an inductively coupled radio frequency(RF)plasma cathode.Numerical simulations and experimental measurements were performed to study the factors influencing the electron extraction characteristics,including the gas type,gas flow,input power and extracting voltage.The simulation results were approximately consistent with the experimental results.We experimentally found that the RF input power mainly determines the extracted electron current.An electron current greater than 1 A was acquired at 270 W(RF input power),2.766 sccm(xenon gas).Our results prove that an inductively coupled RF plasma cathode can be reasonable and feasible,particularly for low power electric propulsion devices.

Weak characteristic information extraction from early fault of wind turbine generator gearboxKeywords wind turbine generator gearbox, B-singular value decomposition, local mean decomposition, weak characteristic information extraction, early fault warning

Given the weak early degradation characteristic information during early fault evolution in gearbox of wind turbine generator, traditional singular value decomposition （SVD）-based denoising may result in loss of useful information. A weak characteristic information extraction based on μ-SVD and local mean decomposition （LMD） is developed to address this problem. The basic principle of the method is as follows： Determine the denoising order based on cumulative contribution rate, perform signal reconstruction, extract and subject the noisy part of signal to LMD and μ-SVD denoising, and obtain denoised signal through superposition. Experimental results show that this method can significantly weaken signal noise, effectively extract the weak characteristic information of early fault, and facilitate the early fault warning and dynamic predictive maintenance.