Ales Belsak

Methods for detecting fatigue cracks in gears

A crack in the tooth root is the least desirable damage caused to gear units and it often causes failure of gear unit operation. For fault analyses presented in this article, gear units with real damages or faults produced on the basis of numerical simulations of real operating conditions are used; tests were carried out in a laboratory test plant. Damages in gear units can be identified by monitoring vibrations. The influences of a crack in a single-stage gear unit on produced vibrations are presented. Significant changes in tooth stiffness are caused by a fatigue crack in the tooth root whereas, in relation to other faults, changes of other dynamic parameters are more expressed. Non-stationary signals are analysed, using the family of Time Frequency Analysis tools, which include Wavelets and Joint Time Frequency Analyses.

Adaptive wavelet transform method to identify cracks in gears

Many damages and faults can cause problems in gear unit operation. A crack in the tooth root is probably the least desirable among them. It often leads to failure of gear unit operation. By monitoring vibrations, it is possible to determine the presence of a crack. Signals are, however, very noisy. This makes it difficult to define properties of individual components. Wavelet analysis is an effective tool for analysing signals and for defining properties. In this paper, a denoising method based on wavelet analysis, which takes prior information about impulse probability density into consideration, is used to identify transient information from vibration signals of a gear unit with a fatigue crack in the tooth root.

Measurements of sound pressure in a very near field

Numerical calculations of sound pressure field from a known vibration velocity field are often used for the prediction of the acoustic behavior of the complex noise sources. In some cases an inverse procedure is possible. A calculation of velocity field on the vibrating surface can be performed based on measured sound pressure field. It is demonstrated, that inverse calculation is possible if the sound pressure field is measured in the near field, and that there is practically no need for the inverse calculation if measurements are performed in the very near field.

Analysis of Vibrations and Noise to Determine the Condition of Gear Units

The main goal of maintenance is to maintain the characteristics of a technical system at the most favourable or still acceptable level. Maintenance costs can be reduced, operation can become more reliable and the frequency and complexity of damages can be reduced. To evaluate the condition of a technical system, it is necessary to collect precise data, and the to analyse, compare and process this data properly. Gear units are the most frequent machine parts or couplings. They consist of a housing, toothed wheels, bearings and a lubricating system and are of various types and sizes. Durable damages in gear units are often a resulta of the following factors: geometrical deviations or unbalanced component parts, material fatigue, which is a result of engagement of a gear pair, or damages caused to roller bearings. To monitor the condition of mechanical systems, methods for measuring vibrations and noise are usually used; data about a gear unit can be acquired in this way. Afterwards certain tools are used to analyse the data. Features that denote the presence of damages and faults are identified in this way.

Acoustic Damage Analysis of a Gear System

In diagnostics, noise can be a very reliable way of defining the condition of mechanical systems. There are different methods to visualise the noise source. Primarily, they deal with a specific noise source in a specific acoustic environment. This paper presents a visualization method of complex noise sources, using an acoustic camera. This method makes it possible to visualise all types of different complex noise sources; a special acoustic algorithm is applied for this purpose. Also, it is possible to observe various transient acoustical phenomena.

Investigating Faulty Gear-Unit Vibration

A crack in the tooth root is probably the least desirable problem in gear unit operation; it often leads to failure. Signals produced by a gear with a crack in the tooth root, produced through real operating conditions, and signals caused by a faultless gear are used for the analysis. By monitoring vibrations it is possible to detect the presence of a crack. A fatigue crack in the tooth root brings about significant changes in tooth stiffness. Other faults are usually linked with modifications of other dynamic parameters. Time Frequency Analysis tools, e.g. Wavelets Analyses, are used to analyse a non-stationary signal. The wavelet transform is chosen for the analysis. The wavelet function similar to the dynamic reaction of the crack in the tooth root is selected. By means of the methods and the analysis presented in this paper, the reliability of determining modifications in signal vibrations is improved.

Investigating Sound Sources of Faulty Gear Units

In diagnostics, the condition of mechanical systems can be determined very reliably on the basis of noise. Noise source visualization is based on a number of different methods. These methods are primarily intended for a specific noise source in a specific acoustic environment. In this paper, a visualization method of complex noise sources, based on the use of acoustic camera, is dealt with. All types of different complex noise sources can be visualized, using a special acoustic algorithm. Also, various transient acoustical phenomena can be observed.

Investigating Vibration Sources of Faulty Gear Units

A crack in the tooth root is the least desirable damage of gear units, which often leads to failure of gear unit operation. A possible damage can be identified by monitoring vibrations. The influences that a crack in the tooth root of a single-stage gear unit has upon vibrations are dealt with. Changes in tooth stiffness are much more expressed in relation to a fatigue crack in the tooth root, whereas in relation to other faults, changes of other dynamic parameters are more expressed. Signal analysis has been performed in relation to a non-stationary signal, by means of the Time Frequency Analysis tool, such as Wavelets. Typical scalogram patterns resulting from reactions to faults or damages indicate the presence of faults or damages with a very high degree of reliability.

Identification of Noise Emission in a Gear Unit

Today it is very important to ensure a stable production without unscheduled outages. To achieve this objective it is required to use advanced production technologies, to ensure adequate maintenance of mechanical systems and to monitor the condition of a device or machine. Reliable and accurate operation of machines and devices with as few outages as possible is desired. The significance of a life cycle design of machines and devices is growing. Possible damages in gear units can be defined by means of monitoring acoustic emission. A crack in the tooth root is usually indicated by significant changes in tooth stiffness. A difference in dynamic responses of an undamaged gear and of a damaged gear can be noted. The possibility of the use of an acoustic method in the field of condition diagostics is dealt with. The noises produced by a gear unit have been analysed, the noise sources within a gear unit have been determined and the corresponding time‐frequency analysis of these sources have been performed, usi...

Crack Identification in Gear Tooth Root Using Adaptive Analysis

Problems concerning gear unit operation can result from various typical damages and faults. A crack in the tooth root, which often leads to failure in gear unit operation, is the most undesirable damage caused to gear units. This article deals with fault analyses of gear units with real damages. A laboratory test plant has been prepared; it has been possible to identify certain damages by monitoring vibrations. In concern to a fatigue crack in the tooth root significant changes in tooth stiffness are more expressed. When other faults are present, however, other dynamic parameters prevail. Signal analysis has been performed also in concern to a non-stationary signal, using the adaptive transformation for signal analysis.