NOISE IDENTIFICATION FOR HYDRAULIC AXIAL PISTON PUMP BASED ON ARTIFICIAL NEURAL NETWORKS

The noise identification model of the neural networks is established for the 63SCY14 IB hydraulic axial piston pump. Taking four kinds of different port plates as instances, the noise identification is successfully carried out for hydraulic axial piston pump based on experiments with the MATLAB and the toolbox of neural networks, The operating pressure, the flow rate of hydraulic axial piston pump, the temperature of hydraulic oil, and bulk modulus of hydraulic oil are the main parameters having influences on the noise of hydraulic axial piston pump. These four parameters are used as inputs of neural networks, and experimental data of the noise are used as outputs of neural networks, Error of noise identification is less than 1% after the neural networks have been trained. The results show that the noise identification of hydraulic axial piston pump is feasible and reliable by using artificial neural networks. The method of noise identification with neural networks is also creative one of noise theoretical research for hydraulic axial piston pump.

Metaheuristic Based Noise Identification and Image Denoising Using Adaptive Block Selection Based Filtering

Image denoising has become one of the major forms of image enhancement methods that form the basis of image processing. Due to the inconsistencies in the machinery producing these signals, medical images tend to require these techniques. In real time, images do not contain a single noise, and instead they contain multiple types of noise distributions in several indistinct regions. This paper presents an image denoising method that uses Metaheuristics to perform noise identification. Adaptive block selection is used to identify and correct the noise contained in these blocks. Though the system uses a block selection scheme, modifications are performed on pixel- to-pixel basis and not on the entire blocks;hence the image accuracy is preserved. PSO is used to identify the noise distribution, and appropriate noise correction techniques are applied to denoise the images. Experiments were conducted using salt and pepper noise, Gaussian noise and a combination of both the noise in the same image. It was observed that the proposed method performed effectively on noise levels up-to 0.5 and was able to produce results with PSNR values ranging from 20 to 30 in most of the cases. Excellent reduction rates were observed on salt and pepper noise and moderate reduction rates were observed on Gaussian noise. Experimental results show that our proposed system has a wide range of applicability in any domain specific image denoising scenario, such as medical imaging, mammogram etc.

Adaptive Noise Identification in Vision-assisted Motion Estimation for Unmanned Aerial Vehicles

Vision localization methods have been widely used in the motion estimation of unmanned aerial vehicles(UAVs).The noise of the vision location result is usually modeled as a white Gaussian noise so that this location result could be utilized as the observation vector in the Kalman filter to estimate the motion of the vehicle.Since the noise of the vision location result is affected by external environment,the variance of the noise is uncertain.However,in previous researches,the variance is usually set as a fixed empirical value,which will lower the accuracy of the motion estimation.The main contribution of this paper is that we proposed a novel adaptive noise variance identification(ANVI) method,which utilizes the special kinematic properties of the UAV for frequency analysis and then adaptively identifies the variance of the noise.The adaptively identified variance is used in the Kalman filter for more accurate motion estimation.The performance of the proposed method is assessed by simulations and field experiments on a quadrotor system.The results illustrate the effectiveness of the method.

Study of engine noise based on independent component analysis

Independent component analysis was applied to analyze the acoustic signals from diesel engine. First the basic prin-ciple of independent component analysis (ICA) was reviewed. Diesel engine acoustic signal was decomposed into several inde-pendent components (ICs); Fourier transform and continuous wavelet transform (CWT) were applied to analyze the independent components. Different noise sources of the diesel engine were separated, based on the characteristics of different component in time-frequency domain.

Analysis of external noise spectrum of high-speed railway

A schematic to make the spectra of the exterior noise of high speed railway was put forward. The exterior noise spectrum was defined based on the characteristics of the high-speed train exterior noise. Its characteristics considered here include identifying the exterior main sources and their locations, their frequency components including the Doppler effect due to the noise sources moving at high speed, the sound field intensity around the train in high-speed operation, the sound radiation path out of the train, and the pressure level and frequency components of the noise at the measuring points specified by the International Organization for Standardization(ISO). The characteristics of the high-speed train exterior noise of the high speed railways in operation were introduced. The advanced measuring systems and their principles for clearly indentifying the exterior noise sources were discussed in detail. Based on the concerned noise results measured at sites, a prediction model was developed to calculate the sound level and the characteristics of the exterior noise at any point where it is difficult to measure and to help to make the exterior noise spectrums. This model was also verified with the test results. The verification shows that there is a good agreement between the theoretical and experimental results.

Investigation on Major Noise Sources of Vehicle Diesel Engine Based on Sound Intensity Measurement

In order to reduce the noise and vibration of the diesel engine,it is crucial to exactly identify the engine noise source character.Based on "two-microphone" method,the sound intensity measurement of a vehicle four-stroke diesel engine was carried out in a hemi-anechoic chamber.Then the sound intensity contour maps were obtained from the measurement results and the main noise components of different frequencies on all the measurement surfaces were picked out to construct contour maps.By analysizing the relationship between the characteristics of contour maps and the space distribution of the engine compartment,the major sources of the exterior radiation noise of the diesel engine were identified.The results provided a creditable basis for improving the noise performance of the engine in the next phase.

Characteristics of interior noise of a Chinese high-speed train under a variety of conditions

This paper presents an investigation into the characteristics of interior noise of a Chinese high-speed train under several typical conditions. Interior noises within Vehicle TC01, which can be used as a head car or an end car, and Vehicle TP03, the third car counting from TC01, are measured for the train running at speeds from 260 km/h to 385 km/h, along two types of track including a slab track and a ballast track and either on the ground surface or in a tunnel. Data analyses are performed for sound pressure overall levels, frequency, area contributions, and possible generation mechanisms, showing how they are affected by train speed, running direction, track type, and tunnel. The results show that, whether TC01 is used as head car or end car, the interior noise characteristics in the VIP cabin are mostly related to aerodynamic noise. Differences in interior noise between tracks become smaller as the train speed increases. The effect of a tunnel on the interior noise is more important for the middle coach than that for the head coach. This study can provide a basis for noise control of high-speed trains.