To achieve low-power convolutional neural networks, we develop a photoelectric hybrid neural network (PHNN), which consists of the optical interference unit (OIU) and field-programmable gate array (FPGA). The OIU composed of Mach–Zehnder interferometers (MZI) arrays, used as convolution kernels, performs multiplication and accumulation operations. The convolution kernel is split and reorganized, forming a new unitary matrix, which reduces MZI quantity. FPGA realizes nonlinear calculation, data scheduling and storage, and phase encoding and modulation. Our PHNN has an accuracy rate of 88.79%, and the energy efficiency ratio is 1.73 times that of traditional electronic products.
A planar lightwave circuit-based multi-channel arrayed waveguide grating (AWG) is used as a critical part of the fiber Bragg grating (FBG) interrogation unit and designed to be integrated into the fiber grating sensing system. We designed and fabricated a high-performance, 40 channels AWG in the device, enabling whole C-band wavelength demodulation while maintaining high-measurement resolution. The AWG was designed to have 100-GHz channel spacing; the channel crosstalk was measured to be −45 dB. An AWG-based FBG interrogation system was built to analyze the characteristics of our unit. The testing result shows that our system has the capability of demodulating wavelength from 1526.438 to 1563.863 nm with wavelength accuracy within ±10 pm; the wavelength resolution is measured to be 1 pm. Our testing result confirms that an AWG-based FBG interrogator is an excellent choice for FBG sensing systems.
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