Power Measurement Methodology for FPGA Devices

The efficiency of power optimization tools depends on information on design power provided by the power estimation models. Power models targeting different power groups can enable fast identification of the most power consuming parts of design and their properties. The accuracy of these estimation models is highly dependent on the accuracy of the method used for their characterization. The highest precision is achieved by using physical onboard measurements. In this paper, we present a measurement methodology that is primarily aimed at calibrating and validating high-level dynamic power estimation models. The measurements have been carefully designed to enable the separation of the interconnect power from the logic power and the power of the clock circuitry, so that each of these power groups can be used for the corresponding model validation. The standard measurement uncertainty is lower than 2% of the measured value even with a very small number of repeated measurements. Additionally, the accuracy of a commercial low-level power estimation tool has been also assessed for comparison purposes. The results indicate that the tool is not suitable for power estimation of data path-oriented designs.

Proposal of a dynamic performance index to analyze driving pattern effect on car emissions

The contributions of driver behaviour as well as surrounding infrastructure are decisive on pollutant emissions from vehicles in real traffic situations. This article deals with the preliminary study of the interaction between the dynamic variables recorded in a vehicle (driving pattern) and pollutant emissions produced over a given urban route. It has been established a “dynamic performance index”-DPI, which is calculated from some driving pattern parameters, which in turn depends on traffic congestion level and route characteristics, in order to determine whether the driving has been aggressive, normal or calm. Two passenger cars instrumented with a portable activity measurement system -to record dynamic variables- and on-board emission measurement equipment have been used. This study has shown that smooth driving patterns can reduce up to 80% NOX emissions and up to 20% of fuel in the same route

In situ surveillance of capacitive pressure transmitter dynamic poles

In this work, a methodology is proposed to find the dynamic poles of a capacitive pressure transmitter in order to enhance and extend the online surveillance of this type of sensor based on the response time measurement by applying noise analysis techniques and the dynamic data system procedure. Several measurements taken from a pressurized water reactor have been analyzed. The methodology proposes an autoregressive fit whose order is determined by the sensor dynamic poles. Nevertheless, the signals that have been analyzed could not be filtered properly in order to remove the plant noise; thus, this was considered as an additional pair of complex conjugate poles. With this methodology we have come up with the numerical value of the sensor second real pole in spite of its low influence on the sensor dynamic response. This opens up a more accurate online sensor surveillance since the previous methods were achieved by considering one real pole only.

Some advances in extensive bridge monitoring using low cost dynamic characterization

Dynamic measurements will become a standard for bridge monitoring in the near future. This fact will produce an important cost reduction for maintenance. US Administration has a long term intensive research program in order to diminish the estimated current maintenance cost of US$7 billion per year over 20 years. An optimal intervention maintenance program demands a historical dynamical record, as well as an updated mathematical model of the structure to be monitored. In case that a model of the structure is not actually available it is possible to produce it, however this possibility does not exist for missing measurement records from the past. Current acquisition systems to monitor structures can be made more efficient by introducing the following improvements, under development in the Spanish research Project “Low cost bridge health monitoring by ambient vibration tests using wireless sensors”: (a) a complete wireless system to acquire sensor data, (b) a wireless system that permits the localization and the hardware identification of the whole sensor system. The applied localization system has been object of a recent patent, and (c) automatization of the modal identification process, aimed to diminish human intervention. This system is assembled with cheap components and allows the simultaneous use of a large number of sensors at a low placement cost. The engineer’s intervention is limited to the selection of sensor positions, probably based on a preliminary FE analysis. In case of multiple setups, also the position of a number of fixed reference sensors has to be decided. The wireless localization system will obtain the exact coordinates of all these sensors positions. When the selection of optimal positions is difficult, for example because of the lack of a proper FE model, this can be compensated by using a higher number of measuring (also reference) points. The described low cost acquisition system allows the responsible bridge administration to obtain historical dynamic identification records at reasonable costs that will be used in future maintenance programs. Therefore, due to the importance of the baseline monitoring record of a new bridge, a monitoring test just after its construction should be highly recommended, if not compulsory.

Discrete element analysis for the assessment of the accuracy of load cell-based dynamic weighing systems in grape harvesters under different ground conditions

Dynamic weighing systems based on load cells are commonly used to estimate crop yields in the field. There is lack of data, however, regarding the accuracy of such weighing systems mounted on harvesting machinery, especially on that used to collect high value crops such as fruits and vegetables. Certainly, dynamic weighing systems mounted on the bins of grape harvesters are affected by the displacement of the load inside the bin when moving over terrain of changing topography. In this work, the load that would be registered in a grape harvester bin by a dynamic weighing system based on the use of a load cell was inferred by using the discrete element method (DEM). DEM is a numerical technique capable of accurately describing the behaviour of granular materials under dynamic situations and it has been proven to provide successful predictions in many different scenarios. In this work, different DEM models of a grape harvester bin were developed contemplating different influencing factors. Results obtained from these models were used to infer the output given by the load cell of a real bin. The mass detected by the load cell when the bin was inclined depended strongly on the distribution of the load within the bin, but was underestimated in all scenarios. The distribution of the load was found to be dependent on the inclination of the bin caused by the topography of the terrain, but also by the history of inclination (inclination rate, presence of static periods, etc.) since the effect of the inertia of the particles (i.e., representing the grapes) was not negligible. Some recommendations are given to try to improve the accuracy of crop load measurement in the field.