The Boeing Company

Other

Mcdonnell Douglas Corporation

Lawrence Eric Pado

Jeong-Beom Ihn

James Patrick Dunne

Craig L Brown

Michael L Vandernoot

John Huntley Belk

Peter F Lichtenwalner

Methods and apparatus for structural health monitoring are described. In one example, a method for use in designing a structural health monitoring (SHM) system for use in monitoring a host structure is described. The method includes one or more of a process for designing SHM systems for any given piece of structural hardware, a process for evaluating a given SHM system, a method to quantify the performance of a given SHM system in comparison to current inspection processes, a finite element modeling approach to determining excitation frequencies to detect damage and for selecting the best time window to use for sensed excitation signals, a Bayesian Network based data fusion technique that fuses in environmental information (load cycles induced on the structure) with a damage index (DI) to produce crack detection and estimation of crack length, and a damage location and sensor selection technique.

Methods and systems for structural health monitoring

A system for detecting damage in an aircraft structure includes an aircraft structure and a structural health monitoring (SHM) system for monitoring the health of the aircraft structure independent of temperature. The SHM system includes an actuator bonded to the aircraft structure and configured to generate a reference vibration signal having a reference amplitude that propagates through the aircraft structure at a first time, and generate a comparison vibration signal having a comparison amplitude that propagates through the aircraft structure at a second time after the first time. The comparison amplitude represents damage incurred by the aircraft structure between the first time and the second time. The SHM system includes a sensor bonded to the aircraft structure that receives the reference vibration signal and the comparison vibration signal, and a processor configured to compute a gain damage index as a function of the reference amplitude divided by the comparison amplitude.

System for temperature insensitive damage detection

Described herein is an apparatus for detecting damage in a structure that includes a plurality of first piezoelectric sensing elements arranged in a generally circular shape. The apparatus also includes an annular-shaped second piezoelectric sensing element positioned adjacent the plurality of first piezoelectric sensing elements. One of the plurality of first piezoelectric sensing elements or the annular-shaped second piezoelectric sensing element generates a wave through the structure and other of the plurality of first piezoelectric sensing elements or the annular-shaped second piezoelectric sensing element senses the wave after passing through the structure.

Piezoelectric sensor configuration for detecting damage in a structure

A method for compensating for environment induced variations in structural health monitoring data is described. The method includes imparting a vibration onto a structure first location, the structure at a first temperature, receiving a comparison signal resulting from the vibration at a second location, accessing data representing a reference signal previously received at the second location, based on vibration at the first location, the reference signal received when the structure was at a second temperature, dividing the signals across multiple time windows, performing a cross correlation between the signals in each window to maximally correlate the signals within each window, performing a weighted regression on time to estimate time shift, the weights based on reference signal energy in each window, to determine a relationship between time and time shift, and using the relationship between time and time shift of the comparison signal to reduce the effects of environment on the comparison signal.

Systems and methods for providing temperature compensation in structural health monitoring

The invention relates to systems and methods which may be used to determine when an uncured composite part is ready to be cured. In one embodiment, a system under the invention may comprise an infrared camera adapted to take infrared images of an uncured composite part, a heating device adapted to heat an uncured composite part, an image capture device adapted to capture infrared images taken by the infrared camera, and a computer adapted to analyze infrared images taken by the infrared camera in order to evaluate temperatures of an uncured composite part. The infrared images may be used to determine that the composite part is substantially covered, and/or completely covered, with resin and ready to be cured.

Infusion monitoring system and method

A method for monitoring and diagnosing the health of a structure. The method includes providing a plurality of damage monitoring units each having at least one actuator, at least one sensor and a data collection device. The sensors are arranged and disposed to measure vibration produced by the actuator and provide a signal corresponding to the measured vibration to the data collection device. The actuator is activated and the vibration is measured with the sensor. The signal is compared to a reference signal and a damage index value is determined in response to the comparison between the signal and reference signal. The damage index value is transmitted for each vibratory path to a central processing device and the damage index values are analyzed for the plurality of damage monitoring units to determine the location of damage to the structure.

High density structural health monitoring system and method

A method, apparatus, and computer usable program code for identifying change indices for a structure. In one advantageous embodiment a method receives a response signal in response to a transmission of an interrogation signal into the structure. The response signal is decomposed into a first plurality of modes. The first plurality of modes is compared to a second plurality of modes for a comparison signal to form a comparison. A change index is assigned to the response signal using the comparison.

Decomposition mode matching change index

A method for determining the health of a structural element. The method includes providing a plurality of transducer elements arranged and disposed to permit measurement of vibration generated by at least one of the transducer elements at one or more of the other transducers elements. Vibration is induced with at least one transducer element. Vibration is measured at least one other transducer element, where the measured vibration corresponding to a vibratory path. At least one damage index value is calculated for each vibratory path in response to the measured vibration. At least one damage image is generated in response to the damage index value. The damage image assigns damage index values to each vibratory path. A damage location is determined from the damage image.

Method and system for the determination of damage location

A method for creating at least one input parameter for an algorithmic system to evaluate damage in a structure may include: (a) Determining a plurality of damage index factors using first signal information relating to a first signal transmitted through the structure before the damage is imposed, and second signal information relating to a second signal transmitted through the structure after the damage is imposed. (b) determining a plurality of condensed damage index factors using the plurality of damage index factors. (c) Correlating selected of the condensed damage index factors with selected measured dimensions relating to the damage to determine a correlation index for selected combinations of the condensed damage index factors and the dimensions. (d) Selecting the at least one input parameter from among the selected condensed damage index factors having a correlation index meeting at least one predetermined criterion.

Method and apparatus for creating at least one parameter for algorithmically evaluating damage in a structure

A method, a computer-readable medium, and a system for tuning a cost function to control an operational plant are provided. A plurality of cost function parameters is selected. Predicted future states generated by the neural network model are selectively incorporated into the cost function, and an input weight is applied to a control input signal. A series of known signals are iteratively applied as control input inputs, and the cost output is calculated. A phase is taken of the control and plant outputs in response to each of the known signals and combined, thereby allowing effective combinations of the cost function parameters, the input weight, and the predicted future states to be identified.

Neural network predictive control cost function designer

A method for monitoring damage to a structure having an actuator and a sensor. The method includes exciting the actuator across a predetermined frequency range to excite the structure, measuring a vibrational characteristic of the structure across the predetermined frequency range in response to the excitation of the actuator using the sensor, calculating a transfer function for the actuator and the sensor using the measured vibrational characteristic, determining a change in the vibrational characteristic across the predetermined frequency range using the transfer function, and analyzing the determined change in the vibrational characteristic across the predetermined frequency range to facilitate determining whether the structure is damaged.

Method and system for monitoring structural damage

A method and system for controlling a dynamic nonlinear plant. An input signal controls the plant and an output signal represents a state of the plant in response to the received input signal. A memory stores input and output signals corresponding to m consecutive past states of the plant. A computer neural network predicts a set of future output states representative of the output signal corresponding to the next n consecutive future states of the plant in response to a set of trial control inputs. The trial control inputs represent the input signal corresponding to the next n consecutive future states of the plant. The neural network predicts the future output states based on the past input and output signals and the future trial control inputs. A processor generates the trial control inputs and determines a performance index, indicative of plant performance over time in response to the trial control inputs, as a function of the future output states. The processor generates the input signal for controlling the plant and modifies it as a function of the trial control inputs so that the performance index reaches a desired value.

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St. Charles, MO, United States of America

Lawrence Eric Pado