Failure analysis and prediction for metal jobs using fuzzy computation
01 Jul 2017-
TL;DR: This paper provides the information regarding the metal jobs failure which was detected earlier by using fuzzy logic and these parameters used in labVIEW for designing fuzzy logic inferential system.
Abstract: Metal jobs (connecting rods) are the one of the essential components of engine's design and also used in industry purpose. The Metal jobs must be able to withstand heavy loads and transmit a great deal of power, the failure of metal jobs leads to damaging engine and other equipment's. This paper provides the information regarding the metal jobs failure which was detected earlier by using fuzzy logic. The failure of metal jobs were predicted by applying different amount of tension on metal jobs which are made of different type of metals like aluminium, copper, steel etc. These different types of metal jobs have a different tensile strength and elongation property, if the applied tension is greater than tensile strength of the material then the metal jobs will break's. So here the tensile strength of the metal jobs were predicted earlier and this values were stored in database. Prediction of failure analysis is done with the help of Hall sensor (AH49E TO-92S) which will get the elongation parameter changes and these parameters used in labVIEW for designing fuzzy logic inferential system. This fuzzy logic will helpful for diagnosing and analysis. In this analysis the tension input values are given to labVIEW to know the break point of the metal jobs without testing. It will give the indication when the metal job is abort to break.
TL;DR: In this article , an accelerometer was used on the rider's head to detect head tilt and prevent motorcyclists from drowning during a motorcycle ride, which is called accelerometer accelerometer detector.
Abstract: The purpose of the project is to develop a device that can detect and prevent motorcyclists from drowning during a motorcycle ride. The idea of building the project is because the rate of accidents for motorcyclists every year is very high. Additionally, safety issue issues for motorcyclists are less than advanced technology on wheeled vehicles. This device is designed by using the sensor input on the rider's head to detect head tilt; it was called an accelerometer. One of the drowsiness and sleepy symptoms is head drooping or lose muscle tone. The project is divided into two parts, namely the detector circuit and the operating control circuit. The detector circuit is to detect the inclination of the head by using an accelerometer detector. It will transmit data to the control circuit which will release the vibration and sound output as it prevents drowsiness and warns users. Next, the project uses Arduino Nano microcontrollers to control the detector circuit and the control circuit. Between the two circuits, it is connected to the wireless transmission medium which is Bluetooth. The development process used is based on a waterfall model which contains five phases namely analysis, design, implementation, testing and maintenance. Three types of analysis have been done which are engineering analysis, expert analysis and user analysis. First, the circuit analysis is performed on the output of the voltage in the vibration motor and the buzzer using the oscilloscope. Second, expert analysis is done based on the design and functionality of the product. As the result, it is shown that the average level for the result stated in good level. Third, the analysis of users who give feedback from the five users that used the product. Overall, this project has achieved its objectives, and it works fine.
TL;DR: This paper investigates the fault detection and isolation (FDI) problem for a class of nonlinear systems with sensor outage faults and proposes a multiple-model scheme based on the affine fuzzy model that describes the system in the presence of a specified fault.
Abstract: This paper investigates the fault detection and isolation (FDI) problem for a class of nonlinear systems with sensor outage faults. The considered nonlinear systems are described as affine fuzzy models, and the system outputs are chosen as the premise variables of fuzzy models. Different from the existing results, the influence of sensor faults on premise variables is considered. As a result, the well-known parallel distributed compensation scheme cannot be used for FDI filters design. By using the structural information encoded in the fuzzy rules, the affine fuzzy system is represented by multiple operating-regime-based models in fault-free case and faulty cases. In the multiple-model scheme, a bank of piecewise FDI filters are constructed, each of them is based on the affine fuzzy model that describes the system in the presence of a specified fault. The fault-dependent residual signals generated from the filters are used for detecting and isolating the specified fault. The FDI filter design conditions are obtained in the formulation of linear matrix inequalities. Finally, a numerical example is given to illustrate the effectiveness and merits of the proposed method.
"Failure analysis and prediction for..." refers background in this paper
...The fact is forgings produce blow hole-free and better rods gives them an advantage over metal rods()....
01 Jan 2015
TL;DR: In this paper, a 3D model of crankshaft as per the existing dimensions are created and the model is imported in FEA software to calculate the driving force of the reciprocating members, vector and acceleration analysis are calculated by using analytical method.
Abstract: The aim of this work is to analyze various failure modes occurred in crankshaft of Briquette machine subjected to cyclic loads and also to improve the overall design of the crankshaft. Finite Element Analysis provides variety range of solution in engineering industries. One among them is the analysis of Briquette machine - crank shaft. The real world problem going to solve state-of-art technology called FEA. Briquette machine used to compress the agricultural waste into high calorific solid fuel. When small particles of solid materials are pressed together to form coherent shapes of larger size, the process are termed briquette. Power from motor is used to rotate the flywheel. Crank shaft, connecting rod & Piston assembly converts the rotary motion into linear motion. Crank shaft is one of the major component plays important role of the operation of the machine. FEA used for validation, design improvement, fatigue life cycle calculation, and optimization of crank shaft. ANSYS finite element code used to solve the problem. This work investigates the fatigue analysis for various failure modes occurring in the briquette machine. 3D model of crankshaft as per the existing dimensions are created and the model is imported in FEA software. The driving force of the reciprocating members, vector and acceleration analysis are calculated by using analytical method. The parameters such as material properties, boundary conditions, mechanical properties, and load on reciprocating members are given as an input and results obtained from Ansys workbench software are analyzed at various failure modes. Finally, weak areas of failure are identified and corrected.
••06 Jan 2011
TL;DR: In this article, the fatigue and friction of big end bearing on an engine connecting rod by combining the multi-body dynamics and hydrodynamic lubrication model was studied. And the simulation results showed a good agreement when contrast the simulation result to the bearing wear in the experiment.
Abstract: This paper has studied the fatigue and friction of big end bearing on an engine connecting rod by combining the multi-body dynamics and hydrodynamic lubrication model. First, the basic equations and the application on AVL-Excite software platform of multi-body dynamics have been described in detail. Then, introduce the hydrodynamic lubrication model, which is the extended Reynolds equation derived from the Navier-Stokes equation and the equation of continuity. After that, carry out the static calculation of connecting rod assembly. At the same time, multi-body dynamics analysis has been performed and stress history can be obtained by finite element data recovery. Next, execute the fatigue analysis combining the Static stress and dynamic stress, safety factor distribution of connecting rod will be obtained as result. At last, detailed friction analysis of the big-end bearing has been performed. And got a good agreement when contrast the simulation results to the Bearing wear in the experiment.
••09 Jul 2015
TL;DR: The design, calibration and measurement uncertainty analysis of a tension measurement test system designed for measuring tension force on a towed array which is towed behind surface ships via a cable are presented.
Abstract: In this article; design, calibration and measurement uncertainty analysis of a tension measurement test system are presented. This system is designed for measuring tension force on a towed array which is towed behind surface ships via a cable. A special test setup that simulates the static and dynamic conditions for the measurement system is prepared for the calibration process. Calibration of the measurement system is carried out using different loads which are changed from 150 kg to 2500 kg by 150 kg increments. Then regression analysis is conducted by applying curve fitting procedure and lack of fit test for static and dynamic conditions separately. Data acquired by the measurement system in the calibration tests are analyzed by calculating measurement uncertainties in the test system. Standard uncertainties due to calibration data errors, instrument errors and curve fitting process are determined for static and dynamic conditions. In addition, combined and expanded uncertainties are calculated and compared to each other.