Corrosion is a major problem for airframe operators. For the aircraft industry in general, the direct costs of corrosion are estimated at $2.2 billion. As part of their strategy to control corrosion, airframe operators constantly seek to improve their ability to anticipate, manage and identify corrosion activity. Motivated by the need for an on-line real-time corrosion-monitoring tool for industry and aircraft a prototype system and analysis approach is presented. The tool employs ultrasonic Lamb waves along with a dispersion compensated synthetic aperture focusing technique (SAFT) to detect emerging pitting damage. In order to develop an automated detection approach the noise sources of the SAFT processed defect maps were examined and modeled. The random noise was found to be neither stationary nor normally distributed. Locally varying Weibull distribution parameters are used to characterize the image noise. An algorithm is developed to quantify the uncertainty in the corrosion detection and to allow assignment of a constant false alarm probability to any region of the monitored area.
Honeywell International has developed and flight-tested a Corrosion and Corrosivity Monitoring System (C2MS). The C2MS detects galvanic corrosion in the main gearbox feet fasteners of helicopters. In addition, it monitors the environmental conditions inside the main floorboard compartment to determine the need for structural maintenance. The C2MS sensor on a main gearbox feet fastener sends a small electrical signal through the fastener and housing to measure the conductivity of the assembly. The measured conductivity value is used to determine if galvanic corrosion is present in the fastener assembly. The floorboard compartment sensors use a surrogate metal coupon to measure the corrosivity of the environment. The information from this sensor is used to recommend an extension to the calendar-based maintenance schedule. Fleet-wide information can be gathered by the system. The C2MS uses two Data Collection Units (DCUs) to store the corrosion data: one for the main gearbox feet fasteners and one for the main floorboard compartment. The DCU design addresses the issues of long battery life for the C2MS (greater than 2 years) and compactness. The data from the DCUs is collected by a personal digital assistant and downloaded to a personal computer where the corrosion algorithms reside. The personal computer display provides the location(s) of galvanic corrosion in the main gearbox feet fasteners as well as the recommended date for floorboard compartment maintenance. This paper discusses the methodology used to develop the C2MS software and hardware, presents the principles of the galvanic corrosion detection algorithm, and gives the laboratory and flight test results that document system performance in detecting galvanic corrosion (detection and false alarm rate). The paper also discusses the benefits of environmental sensors for providing a maintenance scheduling date.
Commercially available digital signal processors (DSPs) can be used to host state-of-the-art air acoustic adaptive beamforming algorithms in low power, low cost, real-time sensor systems. These systems are suitable for use as both unattended ground sensor and in vehicle mounted microphone array applications. This paper describes a compact state-of- the-art, real-time adaptive beamforming approach and sensor hardware for vehicle mounted array operation. Recent field test results are presented for detection, tracking, and classification results with the vehicle engine idling as well as with the vehicle 'on the move.' Tracking accuracy results are also presented. The system tested used an eight- microphone array on the SARGE with two additional microphones located near the engine and the exhaust for additional adaptive noise cancellation.
Commercially available Digital Signal Processors can be used to host state-of-the-art air acoustic adaptive beamforming algorithms in low power, low cost, real-time sensor systems. These systems are suitable for use as both unattended ground sensors and in platform-mounted applications. This paper describes a compact state-of-the-art, real-time adaptive beamforming approach and sensor hardware. Recent day/night field test results for detection range, multiple target tracking, and classification are presented for various vehicles. The data focuses on long range target detection as well as tracking and classification performance in multiple target environments composed of closely spaced or clustered targets. Target location (x-y position) performance using real-time netted sensors (sensor fusion) is also presented.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.