Image-Based Non-Contact Conductivity Prediction for Inkjet Printed Electrodes and Follow-Up Work of Toner Usage Prediction for Laser Electro-Phorographic Printers
thesisposted on 16.08.2019 by Yang Yan
In order to distinguish essays and pre-prints from academic theses, we have a separate category. These are often much longer text based documents than a paper.
This thesis includes two parts. The main part is on the topic of conductivity prediction for Inkjet printed silver electrodes. The second part is about the follow-up work of toner usage prediction of laser electro-photographic printers.
For conductivity prediction of Inkjet printed silver electrodes part, the brief introduction is described below. Recently, electronic devices made with Inkjet printing technique and flexible thin films have attracted great attention due to their potential applications in sensor manufacturing. This imaging system has become a great tool to monitor the quality of Inkjet printed electrodes due to the fact that most thickness or resistance measuring devices can destroy the surface of a printed electrode or even whole electrode. Thus, a non-contact image-based approach to estimate sheet resistance of Inkjet printed electrodes is developed.
The approach has two stages. Firstly, strip-shaped electrodes are systematically printed with various printing parameters. The sheet resistance measurement data as
well as images of the electrodes are acquired. Then, based on the real experimental data, the fitting model is constructed and further used in predicting the sheet
resistance of the Inkjet printed silver electrodes.
For toner usage prediction part, the introduction is described below. With the widespread use of laser electro-photographic printers in both industry and households fields, estimation of toner usage has great significance to ensuring the full utilization of each cartridge. The follow-up work is focused on testing and improving feasibility, reliability, and adaptability of the Black Box Model (BBM) based two-stage strategy in estimating the toner usage. Comparing with previous methods, the training process for the firrst stage requires less time and disk storage, all while maintaining high accuracy. For the second stage, experiments are performed on various models of printers, with cyan(C), magenta(M), yellow(Y), and black(K) color cartridges.