Structural health monitoring using active members and neural networks

A method for monitoring structural integrity of a mechanical structure, said method comprising:

• generating an input signal;
• generating vibrations in said structure in response to an input signal;
• sensing said vibrations;
• generating an output signal in response to said vibrations;
• thereafter, receiving said sensor output in a trainable adaptive interpreter;
• and
• generating an output which characterizes the structural integrity of said mechanical structure, said characterized structural integrity being indicative of damage to said mechanical structure.

A system for detecting the existence of structural damage in a mechanical structure, said system comprising:

• a mechanical structure having at least one structural member with a cross-sectional area;
• an actuator attached to said structural member for generating vibrations in said structure in response to an input signal;
• means for generating said input signal to said actuator;
• a sensor attached to said mechanical structure member for sensing said vibrations and generating an output signal in response thereto;
• a neural network coupled to said sensor for receiving said sensor output and generating an output which characterizes the structural integrity of said mechanical structure said characterized structural integrity being indicative of damage to said mechanical structure, and said output being related to the cross-sectional area of said structural member of said mechanical structure.

A system for monitoring structural integrity, said system comprising:

• a mechanical structure;
• an actuator attached to said mechanical structure for generating vibrations in said structure in response to an input signal;
• means for generating said input signal;
• a sensor attached to said mechanical structure member for sensing said vibrations and generating an output signal in response thereto;
• a neural network coupled to said sensor for receiving said sensor output and generating an output which characterizes the structural integrity of said mechanical structure;
• a preprocessor means coupled to said sensor for analyzing the sensor output signals, wherein said preprocessor means includes means for determining the poles and zeros of a transfer function of said mechanical structure and said poles and zeros are used as input to said adaptive interpreter;
• and
• means for training said neural network, wherein said poles and zeros from an undamaged mechanical structure are used as training input by said means for training said neural network,
• said mechanical structure having at least one structural member and said means for training said neural network trains said neural network to produce an output that is proportional to the cross-sectional area of said structural member.

A system for monitoring structural integrity, said system comprising:

• a mechanical structure;
• an actuator attached to said mechanical structure for generating vibrations in said structure in response to an input signal;
• means for generating said input signal;
• a sensor attached to said mechanical structure member for sensing said vibrations and generating an output signal in response thereto;
• a neural network coupled to said sensor for receiving said sensor output and generating an output which characterizes the structural integrity of said mechanical structure, said neural network being a back propagation neural network;
• and
• a preprocessor means coupled to said sensor for analyzing the sensor output signals, wherein said preprocessor means includes means for determining the poles and zeros of a transfer function of said mechanical structure and said poles and zeros are used as input to said adaptive interpreter.

A method for monitoring structural integrity of a mechanical structure which has a cross-sectional area, said method comprising:

• generating an input signal;
• generating vibrations in said structure in response to an input signal;
• sensing said vibrations;
• generating an output signal in response to said vibrations;
• training an adaptive interpreter to produce an output that is proportional to the cross-sectional area of a member of said mechanical structure;
• receiving said sensor output in said trainable adaptive interpreter;
• and
• generating an output which characterizes the structural integrity of said mechanical structure.