Semi-Siamese Network for Robust Change Detection Across Different Domains with Applications to 3D Printing

Automatic defect detection for 3D printing processes, which shares many characteristics with change detection problems, is a vital step for quality control of 3D printed products. However, there are some critical challenges in the current state of practice. First, existing methods for computer vision-based process monitoring typically work well only under specific camera viewpoints and lighting situations, requiring expensive pre-processing, alignment, and camera setups. Second, many defect detection techniques are specific to pre-defined defect patterns and/or print schematics. In this work, we approach the defect detection problem using a novel Semi-Siamese deep learning model that directly compares a reference schematic of the desired print and a camera image of the achieved print. The model then solves an image segmentation problem, precisely identifying the locations of defects of different types with respect to the reference schematic. Our model is designed to enable comparison of heterogeneous images from different domains while being robust against perturbations in the imaging setup such as different camera angles and illumination. Crucially, we show that our simple architecture, which is easy to pre-train for enhanced performance on new datasets, outperforms more complex state-of-the-art approaches based on generative adversarial networks and transformers. Using our model, defect localization predictions can be made in less than half a second per layer using a standard MacBook Pro while achieving an F1-score of more than 0.9, demonstrating the efficacy of using our method for in-situ defect detection in 3D printing

Acoustic Signal Spread-spectrum System Using Piezoelectric Transducer

Spread-spectrum communication, with its inherent interference attenuation capability, has become an increasingly popular technique in many different systems. Applications range from anti-jam systems, code division multiple access systems (CDMA), and systems designed to combat multi-path. Specific to the CDMA, it has strong anti-interference ability in which other communication system can not be compared with. Due to the broadband transmission, CDMA has strong anti-fading ability which makes the ratio of the useful signals much lower than the interference signal in the transmission channel. To realize the CDMA System of Spread-spectrum communication, I incorporate a piezoelectric transducer to send spread spectrum code obtained from the M sequence ( the longest linear feedback shift register sequence). Also, for the future research of Spread-spectrum underwater communication, the underwater piezoelectric transducer is applied as the transmitting and receiving device whose frequency should be from 30KHz-300KHz， considering the attenuation and absorption of underwater sound wave. As a result, 50KHz or 200Khz is selected as the test frequency. In order to test the reliability and the accuracy of the piezoelectric transducer, the simulation of the transducer is needed. KLM model is applied in the research for model and simulation. The design of spread sequence is the key technology of spectrum communication. White noise is a random process, which has excellent correlation characteristics. However amplification, detection, modulation, synchronization and control of the white noise are still unable to be realized up to now [1]. Therefore, the pseudo random sequence which has similar statistical characteristic can be regarded as the spread spectrum sequence in the spread spectrum system. There are several pseudo random sequences such as M sequence, Walsh sequence, Gold sequence and other [2]. Since the M sequence has good auto-correlation ability and cross-correlation characteristic, as well its easy generation, it was employed in this research finally. To meet the frequency requirement of the transducer, the baseband signal needs to be translated into high frequency, which means that the modulation technology is essential. Modulation is able to move signal spectrum to any location, which is convenient to transmit the signal and make full use of spectrum resources. Also, the binary baseband digital signal without coding just shows the constant change of level. Low level and high level all can replace 1 or 0. For this kind of simplest baseband signal which has a long series of 1 or 0, the synchronization signal can not be extracted from the bit stream in the receiving end. To resolve both problems above, Manchester coding is applied [2]. Meanwhile, when the signal is translated by Manchester coding, the anti-interference ability and bandwidth are also improved. To realize the full data transmission process, the data acquisition part is essential. Compared with varieties of data acquisition cards, the DAQ card PCIE-1816h is applied in the research, due to simple interface, easy testing, various programming support and moderate price. Keywords: spread-spectrum communication, CDMA, piezoelectric transducer, KLM model, M sequence, Manchester coding, data transmission