Applied Mechanics and Materials Vols. 789-790

Abstract: The aim of this research is to develop 1-D mathematical equation that relates Normalized mean Square Error (NMSE) to depth of hydrocarbon (HC) for data processed using cubic spline interpolation in sea bed logging (SBL) application. Simulations were conducted using CST software that replicated real SBL environment to generate synthetic data. Frequency of 0.25Hz was used and sediment thicknesses were varied from 1000m to 3000m and incremented at every 250m. Data collected were interpolated using cubic spline and NMSE were calculated between original and interpolated data. Mathematical equation that relates NMSE (y) and depth of hydrocarbon (x) was constructed in terms of linear, exponential, logarithm and polynomial degree 2, 3, 4 and R² were calculated for each equation. Mathematical equation using exponential function was adopted because it has reasonably high R² and can be inversed easily. Average percentage error was calculated between calculated and measured data to achieve 5 % or lower values. If achievable, this model was accepted as forward mathematical model for SBL. Otherwise, the coefficients were adjusted and the processes repeated until minimum average error was achieved.

Abstract: For the technical problems of coal and rock character recognition in fully mechanized caving faces. A method on characterization and recognition of coal and rock traits were discussed based on the time domain indexes of acoustic pressure data according to the differences of physics and mechanical parameters of coal and rock, and the differences of acoustic pressure data when coal and rock falling impact the rear beam of the sublevel caving hydraulic support. Firstly, the top coal caving experiments were carried out with mining portable vibration recorder developed by China University of Mining and Technology (Beijing) in fully mechanized caving faces in the underground mines, and the acoustic pressure data in quantity were acquired; Then, signal preprocessing were carried on to remove trend items for the selected acoustic pressure data; Finally, the acoustic pressure dates were analyzed in time domain and the time domain features were acquired. Comparison found, peak to peak, variance and kurtosis index are sensitive to the working conditions and the variance with a higher recognition rate. Accordingly proposed an analytical method that based on time-domain features of acoustic pressure date which used variance as recognition indicator, providing technical support for improving the caving automation and intelligent in the fully mechanized caving face.

Abstract: In recent years, autonomous robots have been increasingly deployed in unstructured and unknown environments. In order to survive in theses environments, robots are equipped with sensors. One of the main sensors is tactile sensor which provides the robots with tactile information like texture, stiffness, temperature, vibration and normal and shear forces. In this paper, we propose a flexible capacitive tactile sensor which is designed for measuring both normal and shear forces. The tactile sensing unit consists of five layers, a bottom layer of Polyethylene Terephthalate (PET) with a pillar, two copper electrodes embedded into a Polydimethylsiloxane (PDMS) film, a spacer, a Polyimide (PI) film and finally a top PI bump. The bump and the pillar structure play a significant role in producing a torque for shear force measurement. Finite element modeling (FEM) is conducted to analyze the deformation of the sensing unit and simulated using COMSOL Multiphysics. The change of capacitance verse normal and shear forces are obtained, a comparison between the proposed sensor and other pervious sensor is conducted. The sensitivity of a cell is 0.22%/N within the full scale range of 10 N for normal force and 4%/N within the full scale range of 10 N for shear force.

Abstract: Recent approaches to preventive maintenance have shifted from periodic maintenance based on static parameters to a continuous and a periodic maintenance that deploys high-tech tools to track remotely the “health” of equipments. In this paper, we propose an approach to maintain a high level of reliability and to achieve the maximum efficient use of the working parts within vehicles and machines. This paper marks the use of various techniques in the remote maintenance and diagnostics by means of classical and new methods for monitoring equipments remotely. And hence identifying their failure at earlier stages and preventing their breakdown. The technique relies on an onboard device that monitors and analyses the vibrations of the targeted parts using local knowledge stored within the middleware data base and global knowledge obtained remotely from the server.

Abstract: In this paper, we propose a new method, namely equivalent condition score (CS) method, to calculate the failure rate of power transmission equipment with condition maintenance. Through the conversion of the CS evaluated after maintenance, we can investigate the effect of maintenance on the failure rate, and then calculate the failure rate of the equipment. The effectiveness of the proposed method is verified by field maintenance data. As shown in this paper, the equivalent CS method has a simplified calculation process and specific physical meaning.

Abstract: The concept of vibration based condition monitoring technology has been developing at a rapid stage in the recent years suiting to the maintenance of sophisticated and complicated machines. Nowadays, wavelet analysis based signal processing technique is applied as effective tool for condition monitoring. The experimental studies were conducted on the gear testing apparatus to obtain the vibration signal from a healthy gear and an induced faulty gear. In this paper, two different techniques using Laplace wavelet as base function are used to characterize the fault in the gear signals, specifically wavelet enveloped power spectrum and wavelet kurtosis. The wavelet parameters are optimized using genetic algorithm to select most fault related features. A comparative study detailing features of fault characterization is also given in order to understand the effectiveness of both the wavelet based signal processing methods and their fault diagnosis capability.

Abstract: Today companies are implementing total productive maintenance in order to become world class industries to have a competitive edge over worldwide. In this regard Kobetsu Kaizen (Focused Improvement) pillar having a very significance effect to solve the specific problem. The main aim of this paper is to implement the complete Kobetsu Kaizen methodology of TPM, to solve the issue related with the sudden drop of availability rate of hobbing machine in a gear manufacturing cell. The result of the paper shows the advantage of Kobetsu Kaizen pillar implementation in the sense that breakdown frequency of the machine has been reduced considerably.

Abstract: An intelligent diagnostic method based on 3-D plot continuous wavelet transform (3-D plot CWT) and fuzzy inference system is presented to investigate the detectability and classification of rotor broken bars faults in induction machine (IM) and to overcome the limitation of classical Fourier Transform (FT). This approach is successfully used with Motor Current Signature Analysis (MCSA) and suitable developed model of IM in healthy and faulty mode using Matlab environment. As first step we performed new results using 3-D plot CWT to extract the discriminating features. The features extracted from the wavelet transformed signal are the second most predominant frequency, the time range at which it occurs and the corresponding wavelet coefficients .Then as second and last step a fuzzy Inference system is designed and implemented using Matlab software with these three features extracted from the wavelet transformed signal as inputs and generates an output that classifies the fault and no fault conditions. It is observed that the results are satisfactory.

Abstract: The control valve is one of the fundamental components in the process control industry. It controls the flow rate of elements whether in the form of liquid or gas. The current method of control valve monitoring is done according to schedule. This requires the whole system to be shut down, and leak tests are done while the control valves are fully closed. This research attempts to find faults even while the control valve is open. Severe damage of the control valve would interrupt process which in turn could lead to plant breakdown. If this occurs, production would be interrupted. This problem motivates this research towards early detection of control valve fault. Acoustic emission (AE) method is one of the popular techniques for fault detection. This project applies the AE technique to monitor control valves’ leakage in several stages of damage; minor damage, critical damage, damaged and severe damage.

Abstract: The manufactures of the ultra-thin and smaller semiconductor chip are required over the portable electric devices. The investigation of Fan-out wafer level package (FOWLP) is used widely, among the performance improvement and miniaturization technologies. In this paper, we obtained lots of crack near the passivation (PSV) and redistributed layer (RDL) region of FOWLP during the reliability evaluation of thermal cycling test (TCT). The generated stress and deformational behavior was observed through 2D finite-element analysis. The concentrated stress and deformational behavior are observed around the Solder ball edge and RDL & PSV edges. The crack was observed experimentally as well. The verification of the mechanism for crack generation and the validity of the finite-element analysis were verified by the structural analysis.