1 May 1994 Manipulations of dynamic response data for use in inductive learning methods to identify damage
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Abstract
Various dynamic response data manipulations are presented as part of the ongoing process of developing a complete, model-independent, inductive learning, damage identification method. Dynamic response data, that consist of spatial and temporal information, are verified to be dependent on changes in physical properties of a structure (i.e., mass, stiffness, damping, damage). Simulated experiments were performed on a 500 mm X 600 mm X 3 mm steel plate with simply supported boundary conditions. As a method to test the procedure, a point mass was added to the model in various locations of the structure. Using an array of sensors and a piezo-electric actuator, impulse-response functions and frequency-response functions were determined for the entire domain of sensor-actuator pairs. These impulse- response functions and frequency response functions of different sensor-actuator pairs were input into an inductive algorithm. Inductive learning methods require definitions of a dependent variable, independent variables, and specific examples. Using piecewise manipulations of the aforementioned functions and repeated data acquisition (to take into random transduction errors), these definitions were specified. An automated damage identification method incorporating the use of inductive learning is presented and shown to be successful..
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Peter M. Tappert, Harry H. Robertshaw, "Manipulations of dynamic response data for use in inductive learning methods to identify damage", Proc. SPIE 2192, Smart Structures and Materials 1994: Mathematics and Control in Smart Structures, (1 May 1994); doi: 10.1117/12.174215; https://doi.org/10.1117/12.174215
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KEYWORDS
Sensors

Actuators

Data modeling

Process modeling

Transducers

Data acquisition

Data centers

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