Compensation of Temperature Effects on an Automatic System for Diameter Measurement

Marcotuli, Valerio; Marelli, Stefano; Casartelli, Renato; Scaccabarozzi, Diego; Saggin, Bortolino; Tarabini, Marco

doi:10.1109/metroind4.0iot48571.2020.9138279

Cited by 3 publications

(2 citation statements)

References 6 publications

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“…Industrial machineries' faults limit the production efficiency, decrease the goods' quality and may lead to stop the production [1]. It is therefore important to predict incipient faults by identifying physical phenomena that are related to the behavior of the machinery under inspection [2]. These phenomena are usually complex and the earlier the effect of the fault, the harder is the identification.…”

Section: Introductionmentioning

confidence: 99%

Electrical and mechanical data fusion for hydraulic valve leakage diagnosis

Conti

Madeo

Boiano

et al. 2023

Meas. Sci. Technol.

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This paper describes a method for the identification of valves’ failure identification, with the final aim of creating a predictive maintenance architecture. After revising the scientific literature, we selected the electric current, the acoustic emission and the vibration signals as the most promising monitoring techniques. The processes of feature extraction and data fusion have been optimized to detect early symptoms of a failure. Performances of five different Machine Learning algorithms have been compared. Results, obtained in a specific case study, evidenced that a data fusion process based on vibration and current data, paired with a Random Forest model allowed a Prediction Accuracy and a Jaccard index close to 99%.

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Section: Introductionmentioning

confidence: 99%

Electrical and mechanical data fusion for hydraulic valve leakage diagnosis

Conti

Madeo

Boiano

et al. 2023

Meas. Sci. Technol.

Self Cite

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“…And the variation range of the temperature of the workpiece and the environment is limited, and the error compensation under various temperature conditions can not be realized. Marcotuli [5] developes a compensation algorithm, taking fluctuation of the ambient temperature into measurement system. The errors caused by the temperature of workbench and workpiece to the measurement results are respectively analyzed.…”

Section: Introductionmentioning

confidence: 99%

Research on Temperature Compensation Method in Crankshaft Online Measurement System

2021

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The crankshaft online measurement system has realized the full inspection function with fast beats, at the same time it requires for high-precision measurement. Considering the effect of ambient temperature and temperature changes on measuring machine, the calibration part, the measured crankshaft and displacement sensor, a temperature compensation method is proposed. Firstly, relationship between calibration part and ambient temperature can be get through the zero calibration. Then use the material properties to obtain compensation values of the calibration part and the measured crankshaft part at different temperatures. Finally, the compensation parameters for displacement sensor can be obtained through the BP algorithm. The improved dragonfly algorithm (DA) is used to optimize the parameters of BP neural network algorithm. Experiments verify the effectiveness of IDA-BP for LVDT in temperature compensation. After temperature compensation, the error range of main journal radius is reduced from 0.0156 mm to 0.0028 mm, the residual error decreased from −0.0282 mm~+0.0018 mm to −0.0058 mm~−0.0008 mm. The influence of temperature changes on the measurement is reduced and measurement accuracy is improved through the temperature compensation method. The effectiveness of the method is proved.

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