Mechanical Diagnostics System Engineering in IMD HUMS

Abstract

The Goodrich Integrated Mechanical Diagnostics Health and Usage System (IMD-HUMS) 1 , 2 mechanical diagnostics functionality is the integration of disparate subsystems. When the aircraft is in the appropriate capture window, the primary processing unit (PPU) commands the vibration processing unit (VPU) to capture vibration data and a tachometer reference. This time domain data is processed by standard and proprietary algorithms to generate component condition indicators (CI). These CI are statistics, which when used with a priori configuration data, are mapped into component health indicators (HI). The VPU passes the component HI data to both the PPU and the data transfer unit for ground station display. The PPU, taking the HI data for a component, can determine if the component has a degraded health state. If the component is degraded, the PPU can generate an exceedance message to be reviewed during maintenance debrief. After the flight, all CI and HI data are stored in a data base and is available for display against an aircraft, composite component (e.g. line replaceable unit) and the component itself. The acquisition process is complicated by noise from internal sources (non synchronous gears, shafts and bearing not under analysis) and external sources (changes in airspeed, torque, weight, etc). The HI becomes, in essence, a statistical indicator of the components health. As such, the best estimator of component health is calculated using a Kalman filter. This reduces variance in the data prior to display of the component HI to the aircraft operator. This filtered HI is called the DHI (Display Health Indicator). The DHI uses a priori information and sampling theory to build the best available representation of health of the component. 1 1 0-7803-9546-8This paper addresses the system engineering required to integrate the vibration processing, decision algorithms, thresholding and filtering to give the operator the best representation of component health. The integration of the system allows IMD-HUMS to have a high degree of certainty in the information given to the operator. This information could potentially improve maintenance practices, lowing aircraft operating cost while improving aircraft safety. The system engineering insures that the recommendation for component maintenance has a low probability of false alarm while maintaining a high probability of component fault detection.

Investigation of Current Methods to Identify Helicopter Gear Health

“…Their system is also capable of integrating several CI's into one health indicator (HI) that can be used to identify when a component requires additional analysis or a component is faulted. [23][24][25] Fusing CI's sensitive to a specific failure can minimize the amount of information used by end user to make a decision on system health.…”

Fault Detection on Large Slow Bearings

“…Highlighted in (Bechhoefer, Duke & Mayhew, 2007) are a number of advantages of the HI over CIs, such as: controlling false alarm rate, improved detection, and simplification of user display. This approach allows the use of well established statistical methods.…”

Use of Paris Law for Prediction of Component Remaining Life

“…A number of algorithms have been proposed and tested for anomaly detection [4], [5], [6], and [7]. For this paper, the HI is based on a statistical approach of multi-dimensional hypothesis testing using the Nakagami probability distribution [8].…”