## 1 Introduction  
Corrosion is one of the primary factors for durability and security of structures. Compared with uniform corrosion, pitting corrosion is prone to impose more adverse impacts on the mechanical properties of structures [1]. Since the generation and development of pitting corrosion are stochastic, the prediction of its influence is inaccurately implemented using the mathematical models [1; 2; 3]. However, towards the pitting corrosion diagnosis, beyond that realizing the approximate prediction, one has to assess the current corrosion state, which drives a requirement to non-destructive evaluation techniques, and even has to complete more specific predetermination according to the updated destructive data to reduce the uncertainty [4]. Guided waves based techniques are proven as accurate and efficient in local damage detection and structural health assessment of aerospace and civil infrastructures. When the dispersion equation was solved by numerical methods, the researchers had been practically applying ultrasonic guided waves in rods for length measurement and defects recognition conveniently [5]. Combining with intelligent algorithms, [PERSON] et al. detected a flaw of different positions and depths on the surface of a steel bar. \(L(0,2)\) mode was selected considering its particular sensitivity to superficial defects [6]. Reference-free algorithms were proposed to estimate the cross-section loss based on the differential time-of-flight of propagating guided waves in rod-like waveguides [7; 8]. [PERSON] and [PERSON] extensively studied the attenuation properties of guided waves determined by the material properties, propagation distance, frequency et al. in an imbedded bar, and then applied it to the anchor structures detection [9; 10; 11; 12]. Surface and core seeking guided waves were excited and respectively used to monitor reinforced-concrete beams suffering from damages with different corrosion mechanisms, such as delamination and pitting corrosion on steels [13; 14]. For guided waves in either cylinders or plates, numerous vibrating modes propagate simultaneously at one single excitation frequency, and with its growth the number of modes also increase, that is multimode nature of guided waves. Multipath nature denotes that guided waves propagate along numerous possible paths between the transducers. As a result of the two native characteristics along with dispersion, the response signals are sometimes difficult to interpret definitely and then give rise to troubles for defect detection. In order to overcome the stringent constraints, lots of research was carried out to enhance resolution of signals, such as optimizing excitation mode, signal processing and loading compensation [15; 16]. However, the characteristics of guided waves mentioned above have their strengths in damage detection. A refined method, considering the multimode nature and multipath nature with rich defect information, is able to improve the flexibility in selecting appropriate modes based on NAPFD distribution, and hence increase the quality of damage identification. TRM is a testing technique that signals captured by transducers are inverted in time domain and then reemitted by the same transducers. The identical modes traveling in the same forward and backward propagation paths will arrive simultaneously at the trigger point of excitation, so the discrepancy due to multimode and multipath in time domain can be eliminated. Furthermore, the effect of the within-mode dispersion can be completely compensated. Numerous works relating to TRM have been done in damage detection with guided waves mainly including waveform reconstruction and signal focus [17; 18; 19]. [PERSON] and [PERSON] et al. established the theoretical basis of the Lamb wave focus and reconstruction in plate using the simplified Mindlin plate theory [20]; [PERSON] et al. improved the time reversal theory of Lamb wave with multimode and applied it to damage identification in composite plate [21; 22].