# Investigations into the Recognisability of Gear Damage
## 1 Introduction  
Condition monitoring is becoming increasingly important in many areas, such as gearbox or drive monitoring. In most cases, condition monitoring aims at the intelligent evaluation of sensor data for the derivation of a machine's condition and the estimation of its remaining useful lifetime. This is based on sensor values that are recorded on machine-relevant components. Since sensors only detect changes above a certain size, this paper first investigates the size of damage to tooth flanks at which changes occur in the recorded vibration signals. In addition to monitoring vibrations, there are many other influencing factors, such as lubricants or machine currents, which are investigated in the area of condition monitoring. A comprehensive overview of other methods is given in [1]. The focus of this approach is on the analysis of vibration signals. For this purpose, gearboxes with synthetically damaged tooth flanks are examined more closely in the time and frequency domain. Furthermore, the aim of this paper is to calculate digital filter limits to improve the recognisability of damage in the vibration signal. Previous approaches and investigations into gear tooth flanks are mainly aimed at the detection of damage. In [2], synthetic damage to gears is examined. For this purpose, entire teeth are removed from the gear and subsequently, the vibration data are recorded and evaluated. A comparable investigation is carried out in [3]. Here, entire teeth were removed and a damage analysis was carried out. The investigation is based on the study of the current of the drive. In [4; 5], real tooth fractures are investigated, which are also quite massive. In [6], different degrees of damage to gears are investigated. Here, the examinedt teeth of the gears are removed by 25%, 50% and 100% from the top. In [7], two methods for modelling vibrations are presented and compared with experimental investigations. The tooth damage studied is quite small, but not precisely quantified. In [8], we presented an analysis of the tooth damage of gears under real load conditions, in which time-domain data are investigated via a correlation-based approach. The studies shown have in common that the damage is very massive or not precisely quantified. Furthermore, it is unclear from which damage level onwards that the damage becomes recognisable in the vibration signal. Investigations such as [9; 10] into the wear and remaining useful lifetime of gearboxes usually do not deal with this aspect either, as these investigations examine the long-term changes of previously determined characteristics. In contrast to the previous studies, this paper presents a novel method for calculating the digital filter limits of gear damage. Furthermore, this paper demonstrates, for the examined gearbox type, the measurable damage level to tooth flanks from which a change in the vibration signal occurs. This paper first presents an investigation of the different degrees of damage on two different gears. A metric of gear measurement is used to quantify the different damage levels. In the analysis of the measurements, the data sets are first segmented so that a statistically representative number of damaged tooth meshes can be considered for each damage level. Subsequently, a correlation-based investigation in the time domain and a comparison of the frequency spectra of damaged tooth meshes are described in order to make a statement on the recognisability of quantified damage levels in the vibration signal. In order to derive appropriate filter limits, smoothed spectra are first calculated via linear prediction coefficients [11] and then filter limits are determined via difference spectra. Here, a number of filter coefficients are estimated via the Akaike information criterion. This contribution is structured as follows. Section two describes the experimental setup. First, the test rig for operating the gearbox is presented.