The fractional open-circuit voltage (FOCV) method is commonly adopted to track maximal power point of photovoltaic systems due to easy implementation and cost-effectiveness. However, the FOCV method is confronted with unstable output power and limited tracking accuracy. This paper proposes a novel on-site traversal FOCV method with uninterrupted output power and increased tracking accuracy through simulation and experimental verifications. Each solar cell is connected with a bypass diode and switching circuitry, so that specific solar cell can be traced and measured consecutively for determining its maximal power point (MPP). MATLAB/Simulink simulation results show that, in the time-varying irradiance case, the proposed method achieves a low ripple factor of 0.13% in 11–13 h and 0.88% in 9–15 h, under the typical 24 h irradiance curve. In the spatial-varying irradiance case, the accuracy of the proposed method reaches 99.85%. Compared with other FOCV methods, like pilot cell and semi pilot cell methods, the proposed method is of higher accuracy with a limited ripple effect. Experimental results show that this method can effectively trace different output performance of specific solar cell while generating stable output voltage with a low ripple factor of 1.55%, proving its compatibility with distributed sensing and applicability in smart photovoltaic systems.

Bi-stable vibration energy harvesters are advantageous for a wide bandwidth in low frequency ranges, but are confronted with the issue of limited output power. Bi-stability traditionally contains two low- and high-energy orbits; however, this paper reports resonance provocation of the improved energy orbit, which is much higher than the traditional two energy orbits and can be utilized for power enhancement. Theoretically, the enhanced energy orbit is provoked due to an increase in the system’s kinetic energy, achieved by modifying the bi-stable potential energy function from quartic function to quadratic function to utilize the linear resonant restoring force. Experimental results demonstrate that the provocation of the improved energy orbit is frequency selective, and the root mean square voltage is increased by 63.6% in the upward sweep and 188.5% in the downward sweep. For optimal load, the improved energy orbit increases the maximal root mean square voltage by 2.10 times and the maximal average output power by 4.37 times. Meanwhile, the device’s bi-stable bandwidth remains almost unchanged. These results prove that the resonance provocation of the improved energy orbit can refine the power while not sacrificing bandwidth, which is a promising solution to the overall performance improvement for vibration energy harvesters.

With the increasing size and complexity of the Internet, various abnormal behaviors occur frequently. It is very important to detect the abnormal behavior of traffic in the network, which is very important for ensuring the normal operation of the network. The article proposes a kind of network traffic anomaly detection algorithm for flow characteristics in the road of unsaturated chain. The algorithm comprehensively utilizes the exponentially weighted moving average (EWMA) prediction model to detect the mutation anomaly and the equilibrium model (EQM) to detect the correlation flow anomaly,modeling the link traffic and detecting traffic anomalies in the link. Analysis of the link traffic data and synthetic data through the real backbone network shows that the detection method can detect multiple types of anomalies at a low false alarm rate, and has very Good detection effect.