The method of building the FEA model of traction converter box in high-speed EMU and analyzing the static strength and fatigue strength of traction converter box based on IEC 61373-2010 and EN 12663 standards is presented in this paper. The load-stress correlation coefficients of weak points is obtained by FEA model, applied to transfer the load history of traction converter box to stress history of each point. The fatigue damage is calculated based on Miner's rule and the fatigue life of traction converter box is predicted. According to study, the structural strength of traction converter box meets design requirements.
Neuromorphic engineering has a wide range of applications in the fields of machine learning, pattern recognition, adaptive control, etc. Photonics, characterized by its high speed, wide bandwidth, low power consumption and massive parallelism, is an ideal way to realize ultrafast spiking neural networks (SNNs). Synaptic plasticity is believed to be critical for learning, memory and development in neural circuits. Experimental results have shown that changes of synapse are highly dependent on the relative timing of pre- and postsynaptic spikes. Synaptic plasticity in which presynaptic spikes preceding postsynaptic spikes results in strengthening, while the opposite timing results in weakening is called antisymmetric spike-timing-dependent plasticity (STDP) learning rule. And synaptic plasticity has the opposite effect under the same conditions is called antisymmetric anti-STDP learning rule. We proposed and experimentally demonstrated an optical implementation of neural learning algorithms, which can achieve both of antisymmetric STDP and anti-STDP learning rule, based on the cross-gain modulation (XGM) within a single semiconductor optical amplifier (SOA). The weight and height of the potentitation and depression window can be controlled by adjusting the injection current of the SOA, to mimic the biological antisymmetric STDP and anti-STDP learning rule more realistically. As the injection current increases, the width of depression and potentitation window decreases and height increases, due to the decreasing of recovery time and increasing of gain under a stronger injection current. Based on the demonstrated optical STDP circuit, ultrafast learning in optical SNNs can be realized.
A scheme for all-optical repetition rate multiplication of pseudorandom bit sequences (PRBS) is demonstrated with a precision delay feedback loop cascaded with a terahertz optical asymmetric demultiplexer (TOAD)-based power equalizer. Its feasibility has been verified by experiments, which show a multiplication for PRBS at cycle 2^7−1 from 2.5 to 10 Gb/s. This scheme can be employed for the rate multiplication of a much longer cycle PRBS at a much higher bit rate over 40 Gb/s if the time-delay, the loss, and the dispersion of an optical delay line are all precisely managed.
KEYWORDS: Signal processing, Wavelets, Digital filtering, Filtering (signal processing), Electronic filtering, Digital signal processing, Linear filtering, Silicon, Lithium, Electrical engineering
Anti-jamming techniques were studied in dynamic stress test on bogie structure form the hardware and software. The paper sums up the hardware techniques like compound protection technique and anti-radiation jamming technique; and mainly introduces the software techniques such as zero drift signal processing, digital signal filtering processing, and wavelet signal processing. Additionally, an algorithm 'three-peak-valley stress value compare' is proposed in the wavelet signal processing. The results in application prove these measurements help to provide valid and reliable stress-time history signals for programming the bogie stress spectrum.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.