The paper presents a novel implementation of a time-to-digital converter (TDC) in field-programmable gate array (FPGA) devices. The design employs FPGA digital signal processing (DSP) blocks and gives more than two-fold improvement in mean resolution in comparison with the common conversion method (carry chain-based time coding line). Two TDCs are presented and tested depending on DSP configuration. The converters were implemented in a Kintex-7 FPGA device manufactured by Xilinx in 28 nm CMOS process. The tests performed show possibilities to obtain mean resolution of 4.2 ps but measurement precision is limited to at most 15 ps mainly due to high conversion nonlinearities. The presented solution saves FPGA programmable logic blocks and has an advantage of a wider operation range when compared with a carry chain-based time coding line.
This paper presents an overview of algorithms for one-phase active power estimation using digital signal processing in the time domain and in the frequency domain, and compares the properties of these algorithms for a sinusoidal test signal. The comparison involves not only algorithms that have already been published, but also a new algorithm. Additional information concerning some known algorithms is also included. We present the results of computer simulations in MATLAB and measurement results gained by means of computer plug-in boards, both multiplexed and using simultaneous signal sampling. The use of new cosine windows with a recently published iterative algorithm is also included, and the influence of additive noise in the test signal is evaluated.
A new ultrasound digital transcranial Doppler system (digiTDS) is introduced. The digiTDS enables diagnosis of intracranial vessels which are rather difficult to penetrate for standard systems. The device can display a color map of flow velocities (in time-depth domain) and a spectrogram of a Doppler signal obtained at particular depth. The system offers a multigate processing which allows to display a number of spectrograms simultaneously and to reconstruct a flow velocity profile. The digital signal processing in digiTDS is partitioned between hardware and software parts. The hardware part (based on FPGA) executes a signal demodulation and reduces data stream. The software part (PC) performs the Doppler processing and display tasks. The hardware-software partitioning allowed to build a flexible Doppler platform at a relatively low cost. The digiTDS design fulfills all necessary medical standards being a new useful tool in the transcranial field as well as in heart velocimetry research.