Papers by Keyword: Signal Processing

Abstract: Bearings are one of the most important components in rotating machineries. Their failures will lead to great production loss and increase the maintenance cost. So, condition monitoring work of bearings can save and avoid the potential loss caused by bearing fault. Lucy-Richardson deconvolution (LRD) algorithm, as an image processing technique, started to be used in bearing fault diagnosis. However, only data of bearings working in electric motor are used to validate the method. In engineering cases, most bearings are working in gearbox. Therefore, the bearing fault signals are very weak compared to the gear vibration signal. It is usually difficult to detect the bearing fault in this case. LRD algorithm is used to enhance the bearing fault diagnosis and some characteristics in this case are discussed. Experiment data analysis demonstrates that LRD can enhance the periodic impulse signal effectively. Otherwise, if the desired fault signal is weak compared to non-desired signal, then, the desired fault signal will be continued weaken by LRD which is not benefit to bearing’s incipient fault detection.

Abstract: The study of signals propagation inside porous media is an important field especially in the biomedical research related to compact bones. The purpose of this paper is to determine a mathematical formulation of the global coefficients of transmission and reflection of nondestructive ultrasonic waves in any bi-phase porous medium. Local coefficients of transmission and reflection on the interface of the porous medium will be determined based on a study of boundary conditions. The behavior of different waves inside the porous medium will be developed so that we can derive a new formulation of global coefficients that takes interior phenomena into consideration. Results are found independently of the geometrical and physical characteristics of the medium. Note that this study is based on normal incident ultrasonic wave propagation.

Abstract: This paper presents design and application of foot modules in exoskeleton. Detecting the walking phase and intent is most important data for controlling the wearable exoskeleton. The zero moment point (ZMP) trajectory in the robot foot support area is significant criterion for a stability of the walk. The ZMP is calculated by measured force / torque data and Force / Torque sensor (F/T sensor) can measure that. But, the thick foot module is inconvenient to walking. For such a reason, most foot modules are developed using the film type sensors such as force sensing resistor (FSR), ground contact sensor such as tape switch and so on. In this paper, the foot modules equipped optimal design of 3-axis F/T sensor and ground contact sensor are presented and experimental application of detecting the walking phase using both sensors is introduced.

Abstract: Practical approach of strain gauges using is introduced. The use of strain gauges and signal processing of measured data at static experimental load testing of a concrete beam are carried out. The ability of the strain gauge sensor to pick up the specific deformation / strain signals during loading is investigated. The Fast Fourier Transformation (FFT) is applied to obtain the signal in frequency domain and reverse FFT to transform the processed signal back to time domain. The measurements are confirmed with some inductive transducers and total station. This approach is tested on 2.7 m long concrete beam in laboratory. A practical use of strain gauges with bridge constructions under complex inspection is described.

Abstract: In tunnel lining quality testing and advanced geological forecasting, the main concern is the local signals, such as the position and form of defects or the unusual mutations; while all kinds of filtering methods based on Fourier transformation reflect the overall characteristics of the signals, but can not describe the time-frequency local properties of the signals; however, the characteristics of the multi-resolution based on the wavelet transformation have the ability to show the local characteristics of the signals in terms of the time domain and frequency domain; based on the analysis of multi-wavelet theory, the paper infers the decomposition and reconstruction of CL4 multi-wavelet, discusses the necessity of multi-wavelet preprocessing and conducts the equalization treatment of CL4 multi-wavelet, realizes CL4 balanced multi-wavelet threshold filtering algorithm based on the application of MATLAB language programming, and compares with the traditional filtering effect based on Fourier transformation; the results show that the both conventional filter and CL4 balanced multi-wavelet filter can clearly distinguish the unusual targets; but the target characteristics through multi-wavelet transformation are enhanced; the lineups are clearer, the noises are removed more thoroughly, the signals are reserved more completely and the images become “clearer”. The multi-wavelet transformation provides good assistance for improvement in GPR image resolution and the definition of the target detection image, and achieves better filtering effect.

Abstract: The Smart Grid, acting as a powerful technique for addressing the existing challenges in the power network, has matured in recent years. Its importance has been well recognised. As the most important property of the Smart Grid, the information interactivity over the power network is a frequent topic for academia and industry. Therefore this paper introduces the main achievements of recent years associated with the communication technology and signal processing methodology based on the Smart Grid. Their pros and cons will also be summarised and analysed in detail. To be brief, the novel properties and developments of the Smart Grid, the communication techniques, and the involvement of cRIO integrating FPGA, TDMS, SQL Server, DataSocket Server and LabVIEW Electrical Power Suite will be elaborated upon.

Abstract: This paper introduces a kind of measuring system based on two-dimensional position sensitive detector PSD and single-chip signal processing, and have discussed the key technology. Two-dimensional position sensitive detector (2 D-PSD) is a kind of testing device of light spot position information and the output signal is a kind of current signal related to the location information. PSD output signal processing circuits are usually made by the I/V conversion circuit ,the addition, the subtraction and division arithmetic circuit. System can quickly, accurately and easily realize the position measurement, with a simple implementation, low power consumption, fast response, etc, It can be applied to many remote laser center positioning measurement and general industrial control occasions.

Abstract: Opening the almond currently rely on the manual to complete and is unable to meet the requirements of mass production. For the design of almonds opening machine of automatic control device, we determine the morphological changes, vibration characteristics, extrusion force changes and other parameters of the almond of opening moments, so as to provide calculation basis for choosing suitable step motor and determining parameters of circuit’s electrical components. Electromagnetic buzzer as a vibration sensor to detect the vibration signal, the photoelectric sensor to detect the almond’s position signal, the proximity switch sensor to detect the working position and amplified signals to process circuits, under the control of MCU, the step motor driving a load let the almond opening process achieve the automatic.

Abstract: Intelligent classification is realized according to different components of featured information included in near infrared spectrum data of plants. The core of this theory is to research applications of ant colony algorithm in spectral analysis of plant leaves through theories and experiments. In aspect of theoretical exploration, the built-in function of clustering algorithm is used to compress and process data. In aspect of experimental research, the near infrared diffuse emission spectrum curves of the leaves of Cinnamomum camphora and Acer saccharum Marsh in two groups, which have 75 leaves respectively. Then, the obtained data are processed using ant colony algorithm and the same leaves can be classified as a class by ant colony clustering algorithm. Finally, the two groups of data are classified into two classes. Our results show the distinguishability can be 100%. Keywords:Near infrared spectroscopy; ant colony algorithm; clustering algorithm; signal processing

Abstract: Local damage detection in bearings/gearboxes is one of the most intensively explored problems in condition monitoring literature. Also for mechanical systems used in mining industry this issue might be critical due to short time local overloading of surfaces in contact in gear-pair or bearings that often happens during operation. In general, the problem of local damage detection is well defined in literature, however, specific factors related to the mining industry, require adaptation of existing methods or even developing new approaches. In the paper, some of the most promising techniques with mining machinery context are briefly re-called. The key problems identified for mining machines are: operation under time-varying load/speed conditions, presence of time varying signal to noise ratio and non-Gaussian noise (impulses that appear incidentally, randomly, not with expected cycle or cyclically, however with different cycle related to another damage). All these situations motivated us to find novel solution. The paper might be considered as brief review of recent achievements in the field rather that comprehensive, holistic description of the problem.