On account of the characteristics of high bearing capacity and lightweight, the ribbed components are widely applied to aerospace and national defense equipment, such as the overall wall of the fuselage of the space shuttle, the overall wall of the fuel tank of the launch vehicle, the missile cabin, and the conical shell body. The manufacturing methods of large-scale ribbed components usually include milling, welding, and spinning. Therefore, various types of defects are also brought during the manufacturing process, such as cracks and scratches. During the milling forming process, pores and inclusions in the welding, fractures, and rib penetration at the rounded corners during the spinning, which will seriously reduce the bearing capacity and fatigue strength of the components thus affecting the service performance and safety of related equipment.To solve the problems of rapid detection and precise identification of multi-type defects in the R-zone of ribbed components, this paper innovatively proposed a method for the detection, classification, and identification of defects in the R-zone of ribbed components based on distributed laser ultrasonics. Combining the characteristic signals of multiple detection receiving points, this method realizes the classification, identification with quantitative detection of the defects in the R-zone of the ribbed component; and it was carried out that the modeling simulation and experimental verification of the laser ultrasonic detection of the R-zone of the ribbed components.Firstly, finite element models were established to study the propagation law of laser ultrasound in ribbed components and the interaction mechanism between laser ultrasound and defects such as surface cracks and near-surface blowholes in the R-zone; then based on the above-mentioned propagation law and the structural characteristics of the ribbed member, two detection receiving points were set at both sides of the R-zone of the ribbed component. According to the characteristic waveform propagation path, the reflected defect echo RR and RS wave received at the receiving point 1, the diffracted wave RL, RS and SCS wave received at the receiving point 2 could classify and identify the defects in the R-zone of ribbed components based on the reflection and diffraction principle, and the quantitative calculation model of defect location was established through the sound path, sound velocity and the geometric size of the rib. To sum up, the distributed receiving can realize the rapid detection, classification, recognition, positioning, and quantitative detection of defects in the R-zone of ribbed components.Then, 6061 aluminum alloy ribbed component samples were designed and manufactured with typical artificial defects (the angle between crack and fillet is 43°, the crack depth is 1.15 mm, and the angle between blowhole and fillet is 43°, the distance between the blowhole center and the center of the rounded corner is 7.80 mm, the blowhole diameter is 1.20 mm) for distributed laser ultrasonic testing experiment, and obtained the time domain waveforms of two receiving points. When testing the component with crack defect, the receiving point 1 can receive SP-wave, R-wave and RR-wave, and receiving point 2 can receive RS-wave. But it cannot receive a high amplitude R-wave because of the crack hindering the propagation of the R-wave. When detecting the component with porosity defect, receiving point 1 can obviously receive sP-wave, R-wave and RS-wave, and receiving point 2 can also receive RL-wave, SCS-wave and high amplitude R-wave, which was consistent with the simulation results, thus verifying the feasibility of distributed laser ultrasonic testing method.At the same time, the B-scan images with different defects were obtained through experiments, then the experiment was repeated to get three groups of data in total. The arrival time of characteristic waveforms of different defects was obtained from groups of data taken from the scan position x=0 mm in the three B-scan images. The positioning angle of two defects, the crack depth, the distance between the blowhole center and the center of the rounded corner, and blowhole diameter were obtained by the positioning quantitative calculation model, and the positioning quantitative calculation of the three measurement points was calculated on average. The relative error of crack positioning and crack quantification was 3.2% and 7.8%, respectively, and the relative error of blowhole positioning (including the relative angle of the blowhole and the distance from the blowhole to the center of the fillet) was 4.1% and 1.1%, and the relative error of blowhole quantification was 11.7%. Thus, the positioning and quantitative detection of defects in R-zone of ribbed components were realized. In addition, the relative error of blowhole quantification was too large for two reasons. On the one hand, it was because the speed of SCS-wave could only be approximated as the speed of S-wave when calculating the quantitative error, but in fact the two were slightly different, on the other hand, because the inner convex surface of the rounded corners made the sound waves diverge, which had a certain influence on the reception of the diffracted wave signals.In conclusion, this study can provide a new idea for rapid detection and classification of manufacturing defects of ribbed components.