Digital Measurement

3DFS > Technological Innovation > Digital Measurement

Digital Multiparametric Measurement

Digital multiparametric measurement is a highly accurate method of measuring electricity in true real time incorporating Real Time Computing within the data acquisition system. Using sophisticated mathematical modeling and synchronization algorithms, the data acquisition system oversamples the electricity, simultaneously acquiring 26 separate electrical parameters including current, voltage, phase angle, power factor, harmonics, reactive power, etc. at 24 bit resolution and MHz frequencies, thereby bridging the loss on analog to digital conversion.

 

The mathematical principle of oversampling in this data acquisition system provides a wide, deep, and clear understanding of electricity flow with the data already formatted for data processing. Each phase, neutral and ground of a multiphase system are measured identically, synchronized and fed directly into a mathematical model.

 

Data acquisition at this speed means that every 1/60th of a second (one cycle in 60Hz network), for each of 26 the parameters, on each phase, measurement occurs an average of 8192 times.

 

The high fidelity data stream has been exquisitely designed for the highest possible trust value for exact, subcycle contour awareness of the live electricity flow. This real time layer of electricity informatics provides a multidimensional view of the electricity and a far greater understanding of the changes that occur closer to the speeds that electricity travels.

 

This allows 3DFS Technology to accurately calculate the real time energy losses that exist during the generation, transmission, distribution, storage, conversion or consumption of electricity and represent it in a single metric, Power Quality Rating.

 

Digital multiparametric measurement of electricity also provides an insurmountable technological advantage for electrical signature analysis, opening up the ability to non-intrusively identify every load and event that occurs in a power network in addition to predicting the performance and failure