Drive Train
Impact Technologies has developed a comprehensive, automated health management software package for performing advanced diagnostic and prognostic reasoning of critical drive train components. The software utilizes robust and specifically tuned vibration monitoring algorithms that are combined with physics of failure prognostic models to provide real-time fault monitoring and incipient warning of system failures.
Built-in sensor analysis features and validation algorithms provide automated integrity checks on all acquired signals to minimize false alarms and maximize real fault detections. Our suite of drive train component PHM modules includes specific algorithms for bearing PHM (ImpactEnergy™), gear PHM (GearMod™), shaft/shaft coupling PHM (GearMod-Shaft™), and vibration sensor validation (FirstCheck™), as well as algorithms for system-level PHM (VibeCheck™ and SignalPro™).
Software tools for false alarm mitigation (FAST PHM™), embedded hardware, and smart sensing technologies for oil quality (fluid quality sensor) assessment have also been developed. Impact has delivered these algorithms for many key military platforms including:
ImpactEnergy™ - Bearing Fault Detection Module
The ImpactEnergy™ algorithm is a customizable, Commercial Off-The-Shelf (COTS) sensor compatible, feature extraction technique developed by Impact Technologies that incorporates both high frequency resonance and mid-frequency selected band-pass demodulation. ImpactEnergy takes advantage of a variation of the demodulation process associated with the High Frequency Resonance (HFR) techniques to discover mechanical fault frequencies that serve as early warning indicators for impending failure.
GearMod™ - Gear Fault Detection Module
As previously mentioned, gear failure is another prevalent failure mechanism that occurs in gas turbine engines. Unfortunately, the envelope-based signal processing methods that are used for detecting bearing faults are not the best choice for detecting incipient faults in gears. One of the key differences between the bearing and gear fault detection algorithms is the fact that gear fault detection is best performed when utilizing time synchronous
averaging (TSA).
Impact’s parameterized process accepts various inputs regarding data collection, mechanical system configuration and processing options to compute a time synchronous average in order to extract a residual signal from the TSA. The process diagram describes a “no-tach” algorithm that utilizes an expected range of shaft speed and searches for the actual speed. Note that the first step of the process subdivides the time sample into segments. Blocked processing permits the algorithm to account for shaft non-stationarity, since torsional modulation of speed often occurs. Shaft non-stationarity, if unaccounted for, can often lead to smearing or bleeding of energy across the frequency bins, which reduces the effectiveness of the notch filtering later used to arrive at the residual signal. A linear interpolation is utilized in the frequency domain to further reduce the loss of relevant signal due to frequency smearing and bleed.
GPSys™ for Rotary Wing
Impact offers its customers the GPSys™ software package for stress and fracture analysis of spiral bevel gears. Spiral bevel gears are used in helicopter main drives and their fracture resistance is key to helicopter reliability. GPSys™ takes operational data and converts into stresses and crack growth rate to allow various operational scenarios to be evaluated. GPSys™ works with the Gleason T-900 program, the ANSYS finite element program and Franc3D fracture mechanics program to predict margin against catastrophic tooth fracture. Conventional gear formulas that are used for ground vehicle applications have very rigid gears that may not be suitable for rotorcraft applications. Impact knows this important difference and has developed a system to model finite elements and pinions for rotary wings.
FirstCheck™ Application
Rigorous and automated analysis of the integrity of engine vibration data is critical to providing accurate health assessments for the sensor validation module. Based on Impact’s direct experience with various test cell data sets, vibration monitoring algorithms can be impeded by faulty accelerometer data, as seen in Figure 5. This figure shows the result of Impact’s sensor validation analysis of a sensor failure that occurred on an engine OEM’s test stand. As seen through FirstCheck™ , several vibration features react simultaneously, indicating that a potential fault is present in the system. Upon further investigation of the raw sensor data (top plot), however, one can see that this reaction was caused by faulty (intermittent) data and, therefore, should not be trusted. As such, the probability of false alarm is much greater if sensor validation is not performed. Early detection of sensor problems helps recover data that would otherwise be lost without sensor maintenance.
On-line Fluid/Oil Monitoring
Impact Technologies has developed a fully integratedin-line/online fluid quality sensing technology for use in monitoring a wide variety of lubrication and hydraulic systems. The fluid quality sensor autonomously monitors
overall oil fluid health using multiple sensing technologies that combine to provide strong diagnostic abilities. The patented backbone sensing technology uses broadband AC impedance measurements to determine changes inthe fluid’s electrochemical properties.
This technology has been applied to a number of applications, with different contaminants and degradation modes:
A number of real-time off-board communication methods (including serial, analog, digital, Modbus and CAN) have been implemented for different customers.
Related Technical Publications & Presentations:
Application Solutions
> Aerospace
> Ground Vehicles
> Marine Systems
> Power & Industrial
> Electronic Systems
> Maintenance Management
> Design & Systems Eng.
> Commercial Systems
Integration
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Propulsion |
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Avionics |
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Flight Controls |
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Structures |
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Drive Train |
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Accessories |
Related Technology
> SignalPro™
> Drive Train PHM
> Fluid Quality Sensor
