Low-Process–Voltage–Temperature-Sensitivity Multi-Stage Timing Monitor for System-on-Chip Applications

High performance and complex system-on-chip (SoC) design require a throughput and stable timing monitor to reduce the impacts of uncertain timing and implement the dynamic voltage and frequency scaling (DVFS) scheme for overall power reduction. This paper presents a multi-stage timing monitor, combining three timing-monitoring stages to achieve a high timing-monitoring resolution and a wide timing-monitoring range simultaneously. Additionally, because the proposed timing monitor has high immunity to the process–voltage–temperature (PVT) variation, it provides a more stable time-monitoring results. The time-monitoring resolution and range of the proposed timing monitor are 47 ps and 2.2 µs, respectively, and the maximum measurement error is 0.06%. Therefore, the proposed multi-stage timing monitor provides not only the timing information of the specified signals to maintain the functionality and performance of the SoC, but also makes the operation of the DVFS scheme more efficient and accurate in SoC design.

The Improvement of PQI Density Testing Method of Considering Texture Depth of Asphalt Pavement

In recent years, nondestructive testing is applied more and more widely on the road detection, PQI as a kind of advanced testing equipment in asphalt pavement detection, it has been paid great attention by the road testing personnel. Based on the analysis of the densities which measured by PQI of different types of asphalt pavement, it sums up that the surface texture depth of asphalt pavement significantly affects the measuring accuracy of the density of PQI. In this paper, it suggests to use sand to fill the surface texture depth of asphalt pavement combining with PQI for pavement density measurement. Field testing shows that, compared with the bulk density of core sampling method, the density measured by PQI has obviously been affected by the surface texture depth of asphalt pavement. As the surface texture depth of the asphalt pavement is deeper, the error between the two methods is larger. Considering the influence of texture depth, the author improved the PQI detection method. The improved method shows that, compared with the bulk density of the core sampling, the coefficient of variation of the original testing method is 10.2%, and the new method is 3.8%. In the original testing method , it use the average value of the core sample densities as the compensation value of PQI measurement in the degree of compaction testing, and the maximum measurement error reached up to 2.2%. While, the improved testing method use the average value of the core sample densities as the compensation value of PQI measurement, the maximum measurement error reduces to 0.7%, the accuracy of the testing result is significantly improved.

Research on Dust Concentration Measurement Technique and Experiment Based on Charge Induction

In order to solve the problem of monitoring dust concentration, the paper applies the charge induction method in the design of the monitoring sensor. Specifically, the dust concentration can be characterized by the induction voltage of the sensor which is located in the high-voltage alternating electric field. In particular, the paper introduces the structure of the sensor and analyses the basic principles and feasibility of the measuring equipment. Furthermore, couples of simulation test is conducted based on the test platform. According to the test results, the monitoring sensor performs well when the dust concentration is between 0.81g/m3 and 1.99g/m3, in which the maximum measurement error is only 1.8%. Undoubtedly, the method used for the dust concentration monitoring has a wide prospect in industrial application.