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Bandwidth, Sampling, and Error Propagation
Published in Clarence W. de Silva, Sensor Systems, 2016
Instrument error may be represented by a random variable that has a mean value μe and a standard deviation σe. If the standard deviation is zero, the variable is considered deterministic for most practical purposes. In that case, the error is said to be deterministic or repeatable. Otherwise, the error is said to be random. The precision of an instrument is determined by the standard deviation of the error in the instrument response. Readings of an instrument may have a large mean value of error (e.g., large offset), but if the standard deviation is small, the instrument has high precision. Hence, a quantitative definition for precision would be () Precision = (Measurement range)σe
Basic Instrumentation
Published in Vinayak Bairagi, Mousami V. Munot, Research Methodology, 2019
Pradeep B. Mane, Shobha S. Nikam
Instrument error can occur due to a variety of factors: drift, environment, electrical supply, addition of components to the output loop, process changes, and so on. Since calibration is performed by comparing or applying a known signal to the instrument under test, errors are detected by performing calibration.
Effect of the Primary Air Ratio on Combustion of the Fuel Preheated in a Self-preheating Burner
Published in Combustion Science and Technology, 2022
Ziqu Ouyang, Hongliang Ding, Wen Liu, Xiaoyang Cao, Shujun Zhu
The compositions of coal gas collected at the outlet of the self-preheating burner were analyzed by Agilent 3000A Micro GC (the sensitivity was less than 10–20 ppm) equipped with a thermal conductivity detector. According to the manufacturer’s specifications, the instrument error was within ± 2%. Figure 4 shows the main compositions of the coal gas (excluding N2) at the outlet of the self-preheating burner with different λp. It was seen that the content of H2 and CH4 in the coal gas increased with the increase of λp; but the CO content was the highest when λp was 0.35. The combustible components in the coal gas were not much different when λp was 0.35 and 0.43, and the combustible components content was low when λp was 0.27. No O2 was detected at the outlet of the self-preheating burner, indicating a reducing atmosphere in the self-preheating burner. The NO and NO2 levels detected were extremely low, approximately zero, indicating that the fuel bound nitrogen was unlikely to be converted into NO or NO2 under this atmosphere.
Fuel efficiency enhancement of modified diesel engine operated in dual fuel mode using renewable and sustainable fuels
Published in International Journal of Sustainable Engineering, 2019
Sushurth Halewadimath, V. S. Yaliwal, N. R. Banapurmath
Any measured quantity during experimentation leads without certainty. There are always some errors in measurement. This may limit the exact outcome of the research work. The errors may be of random error or systematic error, which are caused by the variation in readings, when several trials of measurement were taken, and instrument error. Therefore, in this present work, five readings were taken and averaged out value is considered for analysis. Observed uncertainties of different quantities were 1.85%, 2.64%, 4.1%, 6.85%, 5.12%, 14.28% and 3.50% for BTE, fuel substitution, Exhaust gas temperature (EGT), volumetric efficiency, smoke opacity, CO and NOx, respectively.
Effect of SnO2 and Ag nano-additives on the performance, combustion and emission characteristics of diesel engine fueled with mango seed biodiesel
Published in Petroleum Science and Technology, 2022
N. Senniangiri, J. Bensam Raj, Y. Brucely, A. Bovas Herbert bejaxhin
Uncertainty analysis determines the errors occurred during the experimental works due to instrument error, human error, calculation error and environmental errors (Soudagar et al. 2021; Hussain et al. 2020). In this research, the errors were determined by plotting the error bars. The average value of the three readings was taken for the calculation. The uncertainty analysis is shown in Table 5.