# Evaluation of a Novel Condition Indicator with Comparative Application to Hypoid Gear Failures
###### Abstract  
This paper presents a condition monitoring methodology that uses a novel condition indicator (CI) algorithm, allowing for a confident assessment of system health and an advanced warning of failures. The CI is evaluated in the application of a specialized gear rig utilized for the high-cycle fatigue testing of hypoid gears. The CI is shown in this case study to ensure higher confidence in the prediction of failures than other algorithms, with variations in the results. In the comparison, consideration is given to the signal-to-noise ratio, the ability to differentiate between damages and/or damaged components and the sensitivity of the CI to the failure.  
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applications [9]; however, a comparison is lacking to assist in selecting a suitable CI for a given application.  
This paper will introduce a new CI that is applicable to a wide range of gear monitoring applications but developed with isolated automotive component-level testing. Using recorded test data from several lifetime fatigue tests, the new CI can be compared to many other available CI options to evaluate the key performance attributes needed from CM. Consideration is given to the signal-to-noise ratio, the ability to differentiate between damages and/or damaged components and the sensitivity of the CI to the failure. Through this comparison, it can be shown that some CI algorithms are not suitable for application without a detailed calibration and filtering of the signals, whereas others can produce clear and repeatable trends that reduce the risk of false flags and support the diagnosis and prognosis of the system's health.  
The goal of this paper, based on [10], is not to assess precisely how the crack propagation and breakage in this specific application of CM is influenced by the CI applied. As an in-depth assessment, which would constitute frequent stops, crack detection and examinations, was not possible during the testing, the results from using the CI and the documentation of the damage are summarized to allow for the evaluation of the capabilities and weaknesses of the CI options evaluated. This paper presents an in situ test of the algorithm in an industrial application, where the damage of the components cannot be foreseen and the method is assessed to determine if it can be used to effectively and reliably stop testing.  
Gear crack detection is commonly described in the literature based on two approaches. One is the detection of acoustic emissions (AE) in the high-frequency domain, caused by deformation or cracking [11], which is described in [12; 13]. The second and more common approach is the evaluation of vibrations, usually caused by transmission error (TE). TE is the difference between the actual instantaneous angular position of the output shaft and the position it would take if the gear were to have the perfect geometrical shape and it were a rigid bogy. A definition of TE can be found in [14], together with an explanation of the resulting system vibrations. A well known approach is to use the structure-borne noise caused by the TE for condition monitoring purposes, which is presented in [15; 16; 17; 18; 19], amongst others.  
The proposed method and CI is considered to be novel as it combines the evaluation of the complete spectrum. Not only vibration signals but any arbitrary signal (in this study, torque and rotation), by comparing it to a former, undamaged state, thus eliminating the effects of the transmission path. The information of the undamaged state is retrieved--after a running in of the test specimens-- in the so-called learning phase, during which the results are time-synchronously averaged to increase the signal-to-noise ratio and statistical confidence. As the calculation of the CI is not very resource intensive, it can be implemented in industrial systems.