Trapezoidal shaping is frequently used in nuclear digital pulse processing to realize high-resolution and highthroughput spectroscopy. However, this algorithm is susceptible to parameter drifts of front-end detector and circuit. To examine how parameter drifts influence the performance of trapezoidal shaping, we keep the shaping parameters unchanged while varying the input signals. From shaping results, we find that the trapezoidal shapes are distorted when uni- and bi-exponential signal parameters deviating from predetermined values. While for ramp reset signal, the effects of parameter drifts can be eliminated by subtracting the baseline. Exploiting the gradient of the trapezoid top, a parameter correction method is introduced. Simulation results validate the feasibility of the algorithm and it is helpful to enhance the system robustness.

In smart grid, the topological relationship between the transformers and the consumers in a low-voltage distribution network is crucial for powerline loss analysis, fault locating, and power dispatching, etc. The state-of-the-art method for topological relationship identification relies on the precision detection of weak characteristic current with a frequency of ~833 Hz. In this work, we design a magnetoelectric sensor based on the cantilever beam that made of Metglas/Ni/PZT composite and NdFeB permanent magnets, whose second-order resonant frequency is comparable to the frequency of characteristic current. Due to the resonant-enhanced sensitivity of the magnetoelectric sensor, weak characteristic current at μA level is detectable with a high sensitivity of about 111 mV/A in a non-intrusive manner. The proposed magnetoelectric current sensor doesn't require power supply and is able to detect weak currents as low as 0.43 μA. Theoretical calculations, finite element simulations, laboratory and field experiments have verified the effectiveness of the sensor, showing great potential for practical applications in non-invasive characteristic current detection.

The Sallen-Key filter is frequently used to realize radiation detector pulse shaping. To improve the performance of the digital pulse-shaping algorithm, we establish the full parameter Kirchhoff's Current Law equations of the analog Sallen-Key circuit. Synthesizing these equations, a second-order nonhomogeneous difference equation is obtained. By analyzing the symmetry degree of the response function of the difference equation, an optimal pulse-shaping algorithm is derived. Given any shaping time, the parameters needed by this algorithm can be calculated easily. As well, this algorithm has no limitation on gain parameter and no undershoot. Simulation and field-programmable gate array test results validate the feasibility of the new algorithm.

Magnetic field sensors based on acoustic resonators and the ΔE effect in ferromagnetic thin films enable compact size, high sensitivity, wide bandwidth, chip-scale field detection. The sensing performance of the device strongly depends on the soft magnetic and magnetostrictive properties of ferromagnetic films. Here, we systematically investigate the relationship between the magnetic field response of ΔE effect-based delay line surface acoustic wave (SAW) devices and the boron (B) doping concentration in Fe-Ga-B magnetostrictive thin films. Structural characterizations reveal a transition from a polycrystalline to a fully amorphous phase at a B content of 9.69 at. %, accompanied by a sharp reduction in both coercivity and in-plane anisotropy field. This transition leads to a step-like improvement in sensor performance. By optimizing the B composition, we identify a doping range that significantly enhances the performance of SAW devices, with a maximum phase shift of 60.81° at a B content of 12.33 at. % and a peak phase sensitivity of 5.95°/Oe at a B content of 18.84 at. %, providing a magnetic material design guideline for advancing magnetoelectric acoustic devices.