Non-destructive evaluation (NDE) is critical to assure the structural safety for modern engineering structures due to their long service life and harsh environmental conditions. Conventional NDE methods for carbon fiber reinforced plastic (CFRP) composites include X-ray tomography [1, 2], IR thermography [3, 4], and a variety of ultrasonic (US) techniques. 3D X-ray imaging requires extensive data acquisition and is time-consuming; moreover, the size of the instrument chamber limits the size of the sample to the coupon level and makes this approach completely unsuitable for most field applications, particularly those involving aerospace or automotive devices [5]. More advanced optical methods, such as digital image correlation (DIC)[3] and optical coherence tomography (OCT)[6], are sometimes used, but they are usually limited to surface inspection or measurements on semi-transparent composites [7]. In conventional ultrasonic NDE systems, most ultrasonic waves are generated in a small frequency band, and are only able to detect structural damages and flaws with a relatively low resolution (the minimum length of several millimeters).

In the last two decades, significant amount of efforts have been spent to develop real-time NDE technologies to continuously monitor the structural integrity and apply early warnings to operators. Certain real-time NDE technologies are often referred as structural health monitoring (SHM) and prognostics [8-12]. Advanced sensors, including piezoelectric ceramic sensors [13, 14], impedance based sensors [15, 16], piezoresistive sensors [17, 18], and fiber Brag grating (FBG) sensors [19-21], have been investigated for the application in SHM and prognostics. In addition, cutting-edge signal process and pattern recognition algorithms have been developed to process the collected sensor signals and to identify the structural damage conditions under regular service load conditions [22-24]. However, due to the limitation of sensors, batteries, and real-time data processing capabilities, current SHM and prognostics technologies have not been mature enough for large-scale industrial applications, particularly in aerospace industry. CFRP composites have been widely used in various industries, including automotive, aerospace, construction, and sports due to their excellent strength to weight ratio, superior fatigue properties, high stiffness, outstanding heat tolerance and resistance, and suitable for complex structural optimization and design [25-27]. Despite its popularity, CFRP composites can be damaged by various factors during manufacturing and service [5]. Additionally, multiple length scales of structural damage, such as microscale damage precursors and macroscale delamination, can exist simultaneously in CFRP composites. Common microscale damage precursors include fiber breakages, fiber pullout from matrix, and matrix cracks at the scale of microns. Macroscale delamination is considered to be insidious as it is always embedded inside of the composite, therefore, can't be visualized from the composite surface [5]. Traditional NDE methods, including X-ray tomography, IR thermography, and ultrasonic (US) techniques, are able to detect macroscale structural damage, such as delamination, but they struggle at detecting microscale structural damage due to their low spatial resolution imaging capabilities. In order to detect and characterize microscale damage precursors in CFRP composites, a high-resolution NDE technique needs to be developed. In this paper, a new damage detection method is being developed using photo-acoustic (PA) technology. Short time span laser is used to heat sample surface and generate …