Non-linear Torsional Vibration Characteristics of an Internal Combustion Engine Crankshaft Assembly

Crankshaft assembly failure is one of the main factors that affects the reliability and service life of engines.The linear lumped mass method,which has been universally applied to the dynamic modeling of engine crankshaft assembly,reveals obvious simulation errors.The nonlinear dynamic characteristics of a crankshaft assembly are instructionally significant to the improvement of modeling correctness.In this paper,a general expression for the non-constant inertia of a crankshaft assembly is derived based on the instantaneous kinetic energy equivalence method.The nonlinear dynamic equations of a multi-cylinder crankshaft assembly are established using the Lagrange rule considering nonlinear factors such as the non-constant inertia of reciprocating components and the structural damping of shaft segments.The natural frequency and mode shapes of a crankshaft assembly are investigated employing the eigenvector method.The forced vibration response of a diesel engine crankshaft assembly taking into account the non-constant inertia is studied using the numerical integral method.The simulation results are compared with a lumped mass model and a detailed model using the system matrix method.Results of non-linear torsional vibration analysis indicate that the additional excitation torque created by non-constant inertia activates the 2nd order rolling vibration,and the additional damping torque resulting from the non-constant inertia is the main nonlinear factor.The increased torsional angular displacement evoked by the high order excitation torque relates to the non-constant inertia.This research project is aimed at improving nonlinear dynamics theory,and the confirmed nonlinear parameters can be used for the structure design of a crankshaft assembly.

Analysis of Potential Failure Modes in an Assembly Line by Fuzzy Expert Systems

The failure modes and effects analysis （FMEA） is widely applied in manufacturing industries in various phases of the product life cycle to evaluate the system, its design and processes for failures that can occur. The FMEA team often demonstrates different opinions and these different types of opinions are very difficult to incorporate into the FMEA by the traditional risk priority number model. In this paper, for each of the Occurrence, Severity and Detectivity parameters a fuzzy set is defined and the opinion of each FMEA team members is considered. These opinions are considered simultaneously with weights that are given to each individual based on their skills and experience levels. In addition, the opinion of the costumer is considered for each of the FMEA parameters. Then, the Risk Priority Numbers （RPN） is calculated using a Multi Input Single Output （MISO） fuzzy expert system. The proposed model is applied for prioritizing the failures of Peugeot 206 Engine assembly line in IKCo （Iran Khodro Company）.