Determination of a probability distribution for pressure scanner noise and digitization uncertainty reporting

Semmelmayer, Frank; Reeder, Mark F.; Seymour, R. S.

doi:10.1088/1361-6501/ab2abe

Cited by 2 publications

(2 citation statements)

References 13 publications

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“…Currently, pressure scanners and test equipment are primarily the products of Pressure Systems Inc. [4], Scanivalve Corp. [5], and Kulite Inc. [6]. They have significantly matured in the development of pressure scanners for pressure measurement.…”

Section: Introductionmentioning

confidence: 99%

A novel whale-based algorithm for optimizing the ANN approach: application to temperature compensation in pressure scanner calibration systems

Wang

Zeng

Zhang

et al. 2023

Meas. Sci. Technol.

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To solve the problem of the measured value of pressure scanners drifting nonlinearly with temperature change when measuring pressure, resulting in low accuracy, this paper proposes and develops a new calibration system based on neural networks for pressure scanners. Specifically, we start by calibrating the pressure scanner production process, then design the sealing device applicable to the working environment of pressure scanner, and finally install the calibration system of pressure scanner for calibration experiments, so that accurate measurement results can be obtained. In addition, at the algorithmic level, this paper proposes a whale optimization algorithm based back propagation (BP) neural network method instead of the traditional least squares method to complete the temperature compensation. Both the off-line compensation results and the compensated on-line experimental results show the high measurement accuracy of this temperature compensation method. The full-scale error (FS) is 0.07%, the coefficient of determination (R2) =99.27%, with similar results for all channels of the pressure sensor in the temperature environment -40°C to 60°C and absolute pressures ranging from 0 to 1.1Mpa. The result is not only a significant reduction in full-scale error of 0.25%, R2 =91.32% based on conventional algorithm compensation, but also applies to the pressure scanner with wide temperature region, wide range and high accuracy temperature compensation, which is important for its future research of low-cost overall calibration and high accuracy algorithms.

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Section: Introductionmentioning

confidence: 99%

A novel whale-based algorithm for optimizing the ANN approach: application to temperature compensation in pressure scanner calibration systems

Wang

Zeng

Zhang

et al. 2023

Meas. Sci. Technol.

View full text Add to dashboard Cite

show abstract

“…In response to this phenomenon, Pressure System Inc. (PSI) released the PSI9000 series of pressure scanners. The main parameters of the instrument are measurement range: up to 850 psi, accuracy: ±0.05% FS, and temperature compensation range: 0 to 70 • C [5]. The DSA3200 series pressure scanner has been introduced by Scanivalve Corp, Liberty Lake, WA, USA.…”

Section: Introductionmentioning

confidence: 99%

Research on Temperature Compensation of Multi-Channel Pressure Scanner Based on an Improved Cuckoo Search Optimizing a BP Neural Network

et al. 2022

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A multi-channel pressure scanner is an essential tool for measuring and acquiring various pressure parameters in aerospace applications. It is important to note, however, that the pressure sensor of each of these channels will drift significantly with the increase in the temperature range of the pressure measurement, and the output voltage of each of these channels will show nonlinear characteristics, which will constrain the improvements in the accuracy of the measurement. In the regression fitting process, it is difficult to fit nonlinear data with the traditional least-squares method, which leaves pressure measurement accuracy unsatisfactory. A temperature compensation method based on an improved cuckoo search optimizing a BP neural network for a multi-channel pressure scanner is proposed in this paper to improve pressure measurement accuracy in a wide temperature range. Using the chaotic simplex algorithm, we first improved the cuckoo search algorithm, then optimized the connection weights and thresholds of the BP neural network, and finally constructed an experimental calibration system to investigate the temperature compensation of the multi-channel pressure scanning valves in the −40 °C to 60 °C temperature range. The compensation test results show that the algorithm has a better compensation effect and is more suitable for the temperature compensation of multi-channel pressure scanners than the traditional least-squares method and the standard RBF and BP neural networks. The maximum full-scale error of all 32 channels is 0.02% FS (full-scale error) and below, which realizes its high-accuracy multi-point pressure measurement in a wide temperature range.

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Determination of a probability distribution for pressure scanner noise and digitization uncertainty reporting

Cited by 2 publications

References 13 publications

A novel whale-based algorithm for optimizing the ANN approach: application to temperature compensation in pressure scanner calibration systems

A novel whale-based algorithm for optimizing the ANN approach: application to temperature compensation in pressure scanner calibration systems

Research on Temperature Compensation of Multi-Channel Pressure Scanner Based on an Improved Cuckoo Search Optimizing a BP Neural Network

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