Composite Structures with Built-in Diagnostics

Composite Structures with Built-in Diagnostics Mark Lin and Fu-Kuo Chang, Dept. of Aeronautics and Astronautics, Stanford University, Stanford, CA 94305, USA

Composite materials are susceptible to damage w h i c h can be i n d u c e d by service loads a n d accidental impact. Furthermore, internal damage in c o m p o s i t e s is difficult to detect and can have a d e t r i m e n t a l effect o n the residual strength of structures. Early d e t e c t i o n of such damage is critical for m a i n t a i n i n g the integrity of structures in use. Unfortunately, c u r r e n t c o m p o s i t e structure i n s p e c t i o n techn i q u e s are time c o n s u m i n g , labor intensive, a n d expensive, w h i c h sign i f i c a n t l y i n c r e a s e s the o v e r h e a d cost associated w i t h the use of these structures. C u r r e n t available techn i q u e s i n c l u d e coin tapping, X-ray, and u l t r a s o u n d - all of w h i c h require the structure to be t a k e n out of service a n d o f t e n d i s a s s e m b l e d . This a p p r o a c h is u n e c o n o m i c a l a n d sometimes impossible to i m p l e m e n t (e.g., space structures). Recent advances in sensing technologies, material/structural damage characterization, and c o m p u t a t i o n and c o m m u n i c a t i o n have resulted in a significant interest in developing n e w structural diagnostic technologies. Intended for monitoring the integrity of both n e w and existing structures, a structural diagnostic system would be able to detect damage in real time with m i n i m u m h u m a n involvement. To use distributed sensors to m o n i t o r the "health" condition of in-service structures, the sensor signals would have to be interpreted accurately through realtime data processing to reflect the insitu condition of the structures. The entire system could be integrated to perform automated real time inspection and damage detection. The potential direct benefits from such systems are enormous:

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Real-time monitoring and reporting saving in m a i n t e n a n c e cost -

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Minimum h u m a n involvement reduce labor, downtime, and h u m a n error

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Automation - improve safety and reliability

The development of such technology is critically needed for the better use of composite structures. With the

the sensor measurements in terms of the physical conditions of the structures (Figure 1). Depending o n the inputs, structural diagnostic techniques can be divided into two types: passive sensing systems (i.e., with sensors only and without k n o w n inputs) and active sensing systems (i.e., with actuators as well as sensors and with k n o w n inputs).

Passive Sensing Diagnostics

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reduced d o w n t i m e and improved reliability, composite structures can be used more productively at less cost. The increase in reliability of the structures w o u l d also translate into an increase in productivity from the safe operation of the structures. The indirect benefit from the development of this technology for composite materials as a whole can be very significant in many sectors of industry.

Built-In Structural Health Monitoring Typically, such a built-in diagnostic system, in addition to the host structures, would consist of at least two major components: a built-in network of sensors for collecting sensor measurements and software for interpreting

For a passive sensing system, only sensors are installed in the structures. Sensor measurements are constantly taken in real time and compared with a set of (healthy) reference data while the structures are in service. The passive system estimates the condition of the structures based o n the data comparison. Hence, the technique of data comparison for interpretation of structural conditions is crucial for a reliable system. The system w o u l d require either a data bank with a history of pre-stored data or a structural simulator that can generate the n e e d e d reference data. Because the i n p u t energy to the structures is typically r a n d o m and u n k n o w n , the sensor measurements reflect the corresponding structural response to the u n k n o w n inputs, This type of diagnostics has b e e n applied primarily to determine the u n k n o w n inputs (external loads, temperature, pressure, etc.) that cause the change in sensor measurements.

Active Sensing Diagnostics For an active s e n s i n g s y s t e m , k n o w n e x t e r n a l m e c h a n i c a l or

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non-mechanical excitations are i n p u t to the s t r u c t u r e s t h r o u g h built-in devices such as transducers or actuators. Since the inputs are k n o w n , the difference in the local sensor measu r e m e n t s based o n the same i n p u t is strongly related to a physical change in the structural c o n d i t i o n such as the i n t r o d u c t i o n of damage. By using an appropriate algorithm to interpret the difference in sensor measurements, structural damages c a n be clearly identified. In general, the d e v e l o p m e n t of a structural health m o n i t o r i n g system covers four major areas: integrated s e n s o r n e t w o r k , signal g e n e r a t i o n and processing, interpretation, and system integration (Figure 1). Many types of sensors such as fiber optics, dielectric, piezoelectric, strain gauges, and MEMS are either available in the market or b e i n g developed, all of w h i c h can be used for health monitoring p u r p o s e s [ 1].

The SMART Layer Approach Although there are m a n y types of s e n s o r s available, i m p l e m e n t i n g a large n e t w o r k of sensors o n a n e w or existing structure poses a major challenge for d e v e l o p i n g a practical monitoring system. The sensor n e t w o r k m u s t be easily and reliably integrated w i t h the host structures, require minimal labor and p r o d u c e m i n i m a l or n o effect o n the integrity of the structures.

Stanford Multi-Actuator Receiver Transduction Layer ( SMART Layer) [] FLEXIBLE PRINTED CIRCUIT TECHNIQUE

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m u s t be able to w i t h s t a n d typical composite cure temperatures (350°F). 2) The layer m u s t p r o v i d e a d e q u a t e electric i n s u l a t i o n for the e m b e d d e d wires a n d devices. 3 ) T h e layer m u s t have m i n i m a l effect o n the integrity of the host s t r u c t u r e if it is e m b e d d e d inside a c o m p o s i t e material. N u m e r o u s p o t e n t i a l materials in the market w e r e s c r e e n e d a n d K a p t o n ® film was selected to make the layer.The t h i c k n e s s of the film is a b o u t 0.002 inch.

the distance b e t w e e n the piezoelectric disks can be designed to suit the specific application. The major p r o c e s s i n g steps of m a n u facturing the SMART layer involve printing and etching a conductor p a t t e r n o n t o a dielectric substrate, l a m i n a t i n g a dielectric cover layer for electrical i n s u l a t i o n , a n d m o u n t ing the array of p i e z o c e r a m i c s o n the circuit. For l a m i n a t e d c o m p o s ites, the SMART layer c a n b e conside r e d as a n e x t r a p l y laid d o w n

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Recently, a method to i m p l e m e n t a network of distributed piezoelectric sensors/actuators has b e e n developed at Stanford University [2].This method is based o n the flexible circuit printing technique which is c o m m o n l y used in the electronics industry. The fabricated thin, flexible sheet supporting a network of actuators/sensors is referred to as a SMART (Stanford MultiActuator-Receiver Transduction) Layer (Figure 2). T h e SMART layer is m a d e of a dielectric film w i t h a d i s t r i b u t e d netw o r k of p i e z o e l e c t r i c disks serving as b o t h sensors a n d actuators. The m a i n design criteria are: 1 ) T h e layer

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Piezoelectric ceramic (PZT) was selected to form the sensor network, and the size of the piezo-disks can be chosen at the discretion of the users. For the current design, a 0.25" diameter 0.01" thick disk was used.The pattern of the piezoceramic network and

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b e t w e e n c o m p o s i t e plies or p a t c h e d o n the surfaces of the laminates during lay-up.After c o - c u r i n g i n an autoclave, the resulting c o m p o s i t e lamin a t e s w o u l d have an i n t e g r a t e d netw o r k of active p i e z o e l e c t r i c transd u c e r s that c a n be u s e d to s e n d a n d

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the piezo-disks are used as sensors to m e a s u r e the strain values of the structure. To use as an active diagnostic system, o n e piezo-disk is used as an a c t u a t o r to i n p u t a diagnostic signal w h i l e a n o t h e r piezo-disk is used to retrieve the diagnostic signal. The role of each piezo-disk c a n b e reversed to w o r k e i t h e r as an a c t u a t o r or a sensor, f o r m i n g multiple c o m b i n a t i o n s of a c t u a t o r - s e n s o r pairs. In b o t h cases, the i n f o r m a t i o n retrieved from the s t r u c t u r e c a n be u s e d to i n f e r t h e h e a l t h of t h e structure.

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receive diagnostic signals w i t h i n the c o m p o s i t e structures. Tests have s h o w n that the piezoelectric actuators and sensors in the layer provided c o n s i s t e n t and uniform responses over a p e r i o d of time and for a wide range of frequencies. Figure 3 shows the variation of the r e s p o n s e of an actuator-sensor pair over a 3-day p e r i o d . T h e signals o b t a i n e d s h o w e d good c o n s i s t e n c y a n d repeatability. Figure 4 shows the variation of the r e s p o n s e b e t w e e n different actuator-sensor pairs w i t h i n the n e t w o r k . Ten a c t u a t o r - s e n s o r pairs having the same distance and the same o r i e n t a t i o n were tested. The variation b e t w e e n different actuator-sensor pairs in the n e t w o r k was minimal. Mechanical tests s h o w e d that the e m b e d d e d K a p t o n layer had little or n o effect o n the properties of the host composite. Figure 5 shows the c o m p a r i s o n of the strength of composite shear-lap joints with and without the layer at the shear interface. Each lap-joint s p e c i m e n was co-cured in an autoclave. The results of the tests indicated that the p r e s e n c e of the layer did n o t affect the interfacial b o n d strength of the composites. In most cases, s p e c i m e n s w i t h a Kapton layer at the shear interface s h o w e d higher shear strength. This is attributed to delayed failure due to the ductility of the layer.

the composite rather than in the layer or at the interface; hence, the results showed no difference in the failure loads b e t w e e n the two cases. Therefore the presence of the layer did n o t reduce the out-of-plane tensile strength of the composite.

Applications O n c e the SMART layer is i n t e g r a t e d w i t h the structure, it can retrieve i n f o r m a t i o n that relates to the envir o n m e n t a l or physical c h a n g e s in the s t r u c t u r a l c o n d i t i o n . T h e SMART layer c a n f u n c t i o n as a passive or an active diagnostic system, d e p e n d i n g o n the usage of the piezo-disks, To use as a passive diagnostic system,

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Figure 6 shows the comparison of flatwise tensile strength b e t w e e n composites with and without the layer embedded. All specimens failed within

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The i n f o r m a t i o n r e t r i e v e d b y the SMART layer can be used to assess the health c o n d i t i o n of the s t r u c t u r e in m a n y ways. In each diagnostic t e c h n i q u e , the retrieved i n f o r m a t i o n has to go t h r o u g h a series of signal p r o c e s s i n g , filtering, analysis, a n d interpretation before meaningful information about the structure's c o n d i t i o n c a n b e e x t r a c t e d . This series of i n f o r m a t i o n p r o c e s s i n g is h a n d l e d by software w r i t t e n to perf o r m a specific a p p l i c a t i o n . T h e r o b u s t n e s s of any diagnostic techn i q u e relies strongly o n the accuracy a n d reliability of the a p p l i c a t i o n software.

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b e i n g d e v e l o p e d for t h e SMART layer at Stanford. The a p p l i c a t i o n s include: 1) Identification of the locat i o n a n d force of an u n k n o w n external i m p a c t 2) E s t i m a t i o n of t h e e x t e n t of the i m p a c t d a m a g e 3) M o n i t o r i n g the cure c o n d i t i o n of composites.

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Impact Identification W h e n an impact occurs o n a composite plate with an e m b e d d e d SMART layer, the response of the structure is captured by the SMART layer. The piezo sensors on the SMART layer are used to measure the instantaneous strain of the plate caused b y the impact loading.The right side of Figure 7 shows the strain values of the plate recorded by five piezo sensors over the duration of the impact. The corresponding locations of the piezo sensors are indicated on the left side of Figure 7. Based o n the sensor measurement, software has b e e n developed to identify the location and the force-time history of the impact o n a composite panel (30" x 36") e m b e d d e d with a SMART layer containing 13 distributed piezo sensors. The application software has b e e n s h o w n to be very robust in identifying u n k n o w n external impacts [3, 4].

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Damage Defection With the SMART layer, pre-selected diagnostic signals can be generated to i n s p e c t damage inside structures. Piezo-disks can be used as actuators to send out propagating signals that can be measured b y n e a r b y piezo sensors in the structure. Before the i n t r o d u c t i o n of damage, the signal can be stored as healthy reference data (Figure 8 case A). After damage, the propagating signals may be affected due to the existence of the damage (Figure 8 case B). The difference in the signals before and after the

i n t r o d u c t i o n of damage is related to and c o n t a i n s i n f o r m a t i o n a b o u t the damage. By interpreting the change in the propagating signals, software is being developed at Stanford to infer the location and the extent of the damage in composite plates containing an e m b e d d e d SMART layer [5].

Cure Monitoring During autoclave curing of composites, the composite material undergoes

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dramatic change in material properties. Since material p r o p e r t i e s strongly affect h o w the diagnostic signal propagates inside the structure, the progress

Figure 9 (left) s h o w s t h e m o n i t o r i n g s e t u p w h i c h consists o f a c o m p o s i t e p a r t e m b e d d e d w i t h a SMART layer c u r i n g inside an autoclave. A p i e z o disk is u s e d to s e n d o u t a d i a g n o s t i c signal w h i l e a n o t h e r p i e z o - d i s k is u s e d to r e t r i e v e it. E x p e r i m e n t a l d a t a has s h o w n that t h e c h a n g e in t h e p h a s e o f t h e d i a g n o s t i c signals is v e r y sensitive to t h e c u r i n g p r o g r e s s (Figure 9 right); h e n c e , b y m e a s u r i n g the phase change of the received d i a g n o s t i c signals at different t i m e s o v e r t h e c u r e cycle, t h e c o m p l e t e cure cycle can be monitored. S o f t w a r e h a s b e e n d e v e l o p e d to automatically monitor the progress of the composite cure based on p h a s e shift [6].

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of the cure can b e m o n i t o r e d b y comparing the received diagnostic signal at different times.

Structural h e a l t h m o n i t o r i n g is an e m e r g i n g technology, w h i c h offers many advantages over c o n v e n t i o n a l NDE t e c h n i q u e s . T h e SMART layer approach p r o v i d e s an effective m e t h o d to d e v e l o p built-in monitoring systems for c o m p o s i t e s t r u c t u r e s . Several p o t e n t i a l a p p l i c a t i o n s have b e e n d e v e l o p e d for c o m p o s i t e structures e m b e d d e d w i t h a SMART layer. Software d e v e l o p m e n t is o f m a j o r i m p o r t a n c e for further applications o n real structures.

1. E K. Chang, "Manufacturing and Design of Built-In Diagnostics for Composite Structures," Progress Report to the U.S. Army Research O~ce for the Contract No. DAAH04-95-1-0611P00001, 1997. 2. M. Lin and E K. Chang, "Development of SMART Layersfor Built-in Diagnostic for Composite Structures," The 13th Annual ASC Technical Conference o n Composite Materials, Septemb~ 1998. 3. M. Tracy, "Impact Load Identification for Composite Plates Using Distributed PiezoelectricSensors," Ph.D. Dissertation, Department of Aeronautics and Astronautics, Stanford University, 1996. 4. M. Tracy and E K. Chang, =IdentifyingImpact Load in Composite Plates Basedon Distributed Piezo-sensors,"The Proceedingsof SPIE Smart Structures and Materials Conference, San Diego, CA, 1996. 5. Y. S. Roh, =Built-In Diagnostics for Identifying an Anomaly in Plates using Wave Scattering," Ph.D. Dissertation, Department of Aeronautics and Astronautics, Stanford University, 1998. 6. M. Lin, "Manufacturing of Composite Structures with a Built-in Network of Piezoc~eramics,"Ph.D. Dissertation, Department of Mechanical Engineering, Stanford LMivessity,1998.

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Materials Todoy Volume 2 Issue 2 June 1999