A statistical model of gear mesh vibration signals is proposed in this paper. It is seen that the sample mean is first removed from the gear mesh vibration signal, and the remaining signal components are approximated with a set of sinusoidal functions in the signal model. The signal model parameters can be estimated by the least-square method and the optimal model order is determined based on t...

Misfire in an IC Engine continues to be a problem leading to reduced fuel efficiency, increased power loss and emissions containing heavy concentration of hydrocarbons. Misfiring creates a unique vibration pattern attributed to a particular cylinder. Useful features can be extracted from these patterns and can be analyzed to detect misfire. Statistical features from these vibration signals were...

With the development of industrial robots and other mechanical equipment to a higher degree automation, systems have become increasingly complex. This represents huge challenge for condition monitoring. The separation vibration source signals plays an important role in monitoring fault diagnosis. key method signal is prior knowledge, such as statistical features signal, number sources, so forth...

Abstract Vibration signals provided by rotating machinery are informative about their operating states. By nature, the vibration signal behavior is non-stationary. To this end, extraction of discriminating and fault-sensitive parameters a major challenge in field monitoring machines. Conventional fault diagnosis methods based on processing use statistical feature time domain, frequency domain t...

The purpose of this paper is to review the work that has been done in the past years by various researchers in vibration based health and usage monitoring and to identify the principal features and signal-processing algorithm used to this purpose. The damage detection concepts and the signal analysis techniques will be reviewed and categorized. Latest advances in signal processing methodologies...

Reliable measurements of ball mill load parameters and reorganization of the operating statuses are the key factors for saving energy and optimization control. Empirical mode decomposition (EMD) and partial least squares (PLS) are used to analyze shell vibration signal and monitor mill load parameters of ball mill. The shell vibration signal is decomposed into several intrinsic mode functions (...

The purpose of this paper is to review the work that has been done in the past years by various researchers in vibration based health and usage monitoring and to identify the principal features and signal-processing algorithm used to this purpose. The damage detection concepts and the signal analysis techniques will be reviewed and categorized. Latest advances in signal processing methodologies...

The wavelet based denoising has proven its ability to denoise the bearing vibration signals by improving the signal-to-noise ratio (SNR) and reducing the root-mean-square error (RMSE). In this paper seven wavelet based denoising schemes have been evaluated based on the performance of the Artificial Neural Network (ANN) and the Support Vector Machine (SVM), for the bearing condition classificati...

A damage detection problem is cast in the context of a statistical pattern recognition paradigm. In particular, this paper focuses on applying statistical process control methods referred to as "control charts" to vibration-based damage detection. First, an auto-regressive (AR) model is fitted to the measured time histories from an undamaged structure. Residual errors, which quantify the differ...