This paper presents a generic passive non-contact based approach using ultrasonic acoustic emissions (UAE) to facilitate
the neural network classification of bearing health, and more specifically the bearing operating condition. The acoustic
emission signals used in this study are in the ultrasonic range (20-120 kHz). A direct benefit of microphones capable of
measurements in this frequency range is their inherent directionality. Using selected bands from the UAE power
spectrum signature, it is possible to pose the health monitoring problem as a multi-class classification problem, and make
use of a single neural network to classify the ultrasonic acoustic emission signatures. Artificial training data, based on
statistical properties of a significantly smaller experimental data set is used to train the neural network. This specific approach is generic enough to suggest that it is applicable to a variety of systems and components where periodic acoustic emissions exist.
Orthogonal Eigenstructure Control (OEC) is a novel control method that can be used for active vibration
cancellation. OEC is an output feedback control method applicable to multiple-input, multiple-output linear
systems. In this paper, application of OEC for active vibration cancellation in a plate is presented. A steel
plate clamped at four edges is used as a test plate and piezoelectric actuators are used as control actuators.
Accelerometers are used for measuring the acceleration and displacement at ten locations on the plate. A
tonal disturbance with a frequency of 150 Hz is applied to the plate by an electromagnetic actuator. After
identification of the state-space model of the plate, orthogonal eigenstructure control is used to find the
control gains that decouple the modes of vibrations and reduce transferring of vibrational energy between
them. The results show significant vibration suppression throughout the plate.
KEYWORDS: Control systems, Data modeling, Amplifiers, Systems modeling, Device simulation, Instrument modeling, Control systems design, Algorithm development, Performance modeling, Mathematical modeling
The increased prevalence of semi-active control systems is largely due to the emergence of cost effective commercially
available controllable damper technology such as Magneto-Rheological (MR) devices. Unfortunately, MR dampers are
highly nonlinear, which presents an often over-looked complexity to the control system designer. The well-known
Skyhook Damping control algorithm has enjoyed great success for both fully active and semi-active control problems.
The Skyhook design strategy is to create a control force that emulates what a passive linear damper would create when
connected to an inertial reference frame. Skyhook control is device independent since it generates a desired control
force command output that must be produced by the control system. For simplicity, MR dampers are often assumed to
have a linear relationship between the current input and the force output at a given relative velocity. Often this
assumption is made implicitly and without knowledge of the underlying nonlinearity. In this paper, we show that the
overall performance of a semi-active Skyhook control system can be improved by explicitly inverting the nonlinear
relationship between input current and output force. The proposed modification will work with any semi-active control
algorithm, such as Skyhook, to insure that the controller performance is at least as good as the performance without the
proposed modification. This technique is demonstrated through simulation on a quarter-vehicle system.
KEYWORDS: Control systems, Actuators, Control systems design, Sensors, Beam guidance systems, Feedback control, Matrices, Aerospace engineering, Error analysis, Vehicle control
Orthogonal eigenstructure control is used for designing a control law that decouples the dynamic modes of a flying
vehicle. Orthogonal eigenstructure control is a feedback control method for linear time invariant multi-input multi-output
systems. This method has been recently developed by authors. The advantage of this control method over eigenstructure
assignment methods is that there is no need for defining the closed-loop poles or shaping the closed-loop eigenvectors.
This method eliminates the error due to the difference between achievable and desirable eigenvectors, by finding vectors
orthogonal to the open-loop eigenvectors within the achievable eigenvectors set and replacing the open-loop
eigenvectors with them. This method is also applicable to the systems with non-collocated actuators and sensors.
Application of this method for designing a flight control law for the lateral directional dynamics of an F-18 HARV is
presented, and compared to the results of an eigenstructure assignment method. In this case study, the actuators and
sensors are not collocated. It is shown that the application of the orthogonal eigenstructure control results in a more
significant dynamic modes decoupling in comparison to the application of the eigenstructure assignment technique.
Conference Committee Involvement (10)
Active and Passive Smart Structures and Integrated Systems X
21 March 2016 | Las Vegas, Nevada, United States
Active and Passive Smart Structures and Integrated Systems IX
9 March 2015 | San Diego, California, United States
Active and Passive Smart Structures and Integrated Systems VIII
10 March 2014 | San Diego, California, United States
Active and Passive Smart Structures and Integrated Systems VII
10 March 2013 | San Diego, California, United States
Active and Passive Smart Structures and Integrated Systems VI
12 March 2012 | San Diego, California, United States
Active and Passive Smart Structures and Integrated Systems V
7 March 2011 | San Diego, California, United States
Active and Passive Smart Structures and Integrated Systems IV
8 March 2010 | San Diego, California, United States
Active and Passive Smart Structures and Integrated Systems III
9 March 2009 | San Diego, California, United States
Active and Passive Smart Structures and Integrated Systems II
10 March 2008 | San Diego, California, United States
Active and Passive Smart Structures and Integrated Systems
19 March 2007 | San Diego, California, United States
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