Advanced Signal Processing Tools for the Vibratory Surveillance of Assembly Faults in Diesel Engine Cold Tests

Abstract

This paper addresses the use of several signal processing tools for monitoring and diagnosis of assembly faults in diesel engines through the cold test technology. One specific fault is considered here as an example: connecting rod with incorrectly tightened screws. First, the experimental apparatus concerning the vibration tests is introduced. Subsequently, the dynamic analysis of the engine has been carried out in order to calculate the connecting rod forces against the crankpin for predicting the position where mechanical impacts are expected. Then, a vibration signal model for this type of faults is introduced. It deals with the cyclostationary model in which the signal is subdivided into two main parts: deterministic and nondeterministic. Finally, the acceleration signals acquired from the engine block during a cold test cycle at the end of the assembly line are analyzed. For quality control purposes in order to obtain reliable thresholds for the pass/fail decision, a method based on the image correlation of symmetrized dot patterns is proposed. This method visualizes vibration signals in a diagrammatic representation in order to quickly detect the faulty engines in cold tests. Moreover, the fault identification is discussed on the basis of the cyclostationary model of the signals. The first-order cyclostationarity is exploited by the analysis of the time synchronous average (TSA). In addition, the residual signal is evaluated by subtracting the TSA from the raw synchronized signal, and thus, the second-order cyclostationarity analysis is developed by means of the Wigner–Ville distribution (WVD), Wigner–Ville spectrum (WVS), and mean instantaneous power. Moreover, continuous wavelet transform is presented and compared with the WVD and WVS.

The Detection of Defects in Rolling Bearings Based on the Analysis of Vibroacoustic Signal

“…The disadvantages of vibration analysis are: a. very weak sensitivity; b. special requirements for mounting the vibration sensor; c. the dependence of vibration parameters on a large number of factors and the complexity of the vibration signal, due to the presence of a fault, which requires an in-depth knowledge of the methods of correlation and regression analysis and their correct use; d. the accuracy of diagnosis in most cases depends on the number of smoothed parameters, for example, the number of SPM ratings [6]. Complete analysis of the technical condition of the reducer after assembly and run-in on the test bench ( Fig.2) will allow not only revealing and correcting manufacturing defects, but also will exclude possibility of delivery on-to the consumer of substandard production [7]. Also, the obtained data can form the basis for the development of an automated quality control system.…”

An Approach on Fault Detection in Diesel Engine by Using Symmetrical Polar Coordinates and Image Recognition

“…Finally, hexagonal flakes mirror symmetry graphics are produced in polar coordinates [10]. Changes in amplitude and frequency of the sampled signal can be expressed by the difference of the image.…”

On the Use of Wavelet Transform for Practical Condition Monitoring Issues

“…As explained in [32] the peak is caused by the absence of controlled bush deformation when the correct tightening torque is not applied. This clearance is abruptly traversed whenever a change in the direction of the resultant force occurs on the rod.…”