Modeling of High-Frequency Electromagnetic Effects on an Ironless Inductive Position Sensor

Danisi, Alessandro; Masi, A.; Losito, R.; Perriard, Yves

doi:10.1109/jsen.2013.2271546

Cited by 13 publications

(10 citation statements)

References 28 publications

(41 reference statements)

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“…The NLP, NLS, NLC and ac will influence the output voltage produced, the sensitivity of the sensor and the Non-Linearity Error (NLE) [12]. The NLE is computed as = 100 max( ′ − * ) (8) where p* is the core reference position, p' is the position calculated through linear interpolation of the curve and CPR is the core position range. In [13], it was found out that the optimum choice for the coils length would be of ≥ 2 , where Pmax is the maximum range required.…”

Section: International Journal Of Computer Electrical Engineeringmentioning

confidence: 99%

See 1 more Smart Citation

A Novel Holistic Design Optimisation Algorithm for the Ironless Inductive Position Sensor

Grima¹,

Castro²,

Masi³

et al. 2018

IJCEE

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The Ironless Inductive Position Sensor (I2PS) is a state-of-the-art high precision linear position sensor, which is designed to be radiation hard and immune to magnetic fields. This sensor is built for the Large Hadron Collider collimation system at the European Organization for Nuclear Research. It is continuously monitored to assess the precision, accuracy and drifts during the machine's operation. The ironless inductive position sensor was previously designed and optimised manually on a programmed electromagnetic model and simulated using a finite element model simulator. This sensor has the potential to be used extensively in industry, especially in areas with high radiation and high electro-magnetic interference. To industrialise it, an automated design procedure is required that offers the possibility to a user with minimal knowledge to design and optimise the sensor. This paper identifies the optimisation parameters and constants required in the manual design. It hence presents an automated design procedure which uses a multi-objective optimisation algorithm to automatically produce ironless inductive position sensors tailor-made to the user's specifications.Designing an I2PS requires a multi-objective [14], [15] optimisation algorithm. Furthermore, the user is required to input the constants depending on the dependencies and is required to select the weighting and the number of recombinations. It can also be understood that the objectives targeted at this point can be increased to the extent that new objects, such as costs, can also be included.

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Section: International Journal Of Computer Electrical Engineeringmentioning

confidence: 99%

“…The sensor is characterised in terms of high frequency [8] and thermal phenomena [9]. A procedure is also presented that explains how the sensor is optimised without the use of an automatic optimisation procedure [7].…”

Section: Introductionmentioning

confidence: 99%

A Novel Holistic Design Optimisation Algorithm for the Ironless Inductive Position Sensor

Grima¹,

Castro²,

Masi³

et al. 2018

IJCEE

Self Cite

View full text Add to dashboard Cite

show abstract

“…IPSs, which are improving continuously, are applied in various dynamic controls, such as landing gear [30,31], cabin doors [32], panels [33], and thrust reversers [34]. This type of sensor applies a full-closed structure [35,36,37] which can lower pollution effects [38]. This sensor plays an indispensable role in the detection of motion and positioning of airborne electro-mechanical components [29,37,39].…”

Section: Introductionmentioning

confidence: 99%

Differential Structure of Inductive Proximity Sensor

Guo

Lai

Shao

et al. 2019

Sensors

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The inductive proximity sensor (IPS) is applicable to displacement measurements in the aviation field due to its non-mechanical contact, safety, and durability. IPS can increase reliability of position detection and decrease maintenance cost of the system effectively in aircraft applications. Nevertheless, the specialty in the aviation field proposes many restrictions and requirements on the application of IPS, including the temperature drift effect of the resistance component of the IPS sensing coil. Moreover, reliability requirements of aircrafts restrict the use of computational-intensive algorithms and avoid the use of process control components. Furthermore, the environment of airborne electronic equipment restricts measurements driven by large current and proposes strict requirements on emission tests of radio frequency (RF) energy. For these reasons, a differential structured IPS measurement method is proposed in this paper. This measurement method inherits the numerical separation of the resistance and inductance components of the IPS sensing coil to improve the temperature adaptation of the IPS. The computational complexity is decreased by combining the dimension-reduced look-up table method to prevent the use of process control components. The proposed differential structured IPS is equipped with a differential structure of distant and nearby sensing coils to increase the detection accuracy. The small electric current pulse excitation decreases the RF energy emission. Verification results demonstrate that the differential structured IPS realizes the numerical decoupling calculation of the vector impedance of the sensing coil by using 61 look-up table units. The measuring sensitivity increased from 135.5 least significant bits (LSB)/0.10 mm of a single-sensing-coil structured IPS to 1201.4 LSB/0.10 mm, and the linear approximation distance error decreased from 99.376 μm to −3.240 μm. The proposed differential structured IPS method has evident comparative advantages compared with similar measuring techniques.

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“…Inductive proximity sensors (IPSs) meet the requirements of no mechanical contact, resistance to fouling and abrasion, water tightness [ 1 ], long service life, and low mechanical system maintenance cost [ 1 , 2 ]. High mean time between failure (MTBF) value [ 3 ], strong magnetic immunity [ 4 , 5 , 6 ], and built-in self-test (BIST) function are convenient for application [ 7 , 8 , 9 ]. IPS is applicable in the high-reliability industrial field of position detection, especially in aviation and aerospace [ 7 , 10 , 11 ].…”

Section: Introductionmentioning

confidence: 99%

Dimension-Reduced Analog—Digital Mixed Measurement Method of Inductive Proximity Sensor

Guo

Shao

Tao

et al. 2017

Sensors

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Inductive proximity sensors (IPSs) present a unique no-contact advantage. They are widely preferred for displacement measurement in various industrial fields (e.g., aviation and aerospace), and they are improved continuously. When the inductance and resistance components of the IPS sensing core are separated, the influence of temperature drift on measurement can be eliminated. The complexity of online computation of component separation can be reduced using a two-dimensional look-up table method. However, this method exhibits disadvantages, such as large capacity of the look-up table, dependency on precision measurement of sensing core parameter, and nonlinear distribution of measurement resolution. This study aims to overcome these disadvantages by examining the nonlinear relationship between the response of the sensing core and the ambient temperature, and proposes a dimension-reduced measurement method. The proposed method extracts the characteristics of the response curves at two temperatures and calculates the characteristics of the response curves at any temperature using a linear approximation. The look-up table capacity is less than 0.37% of the two-dimensional look-up table capacity (condensed) under the same condition; dimension reduction enables the construction of a complete look-up table directly by calibration procedures and avoids precise measurement on sensing core parameters; the calibration procedures establish uniform mapping of the distribution of measurement resolution. The experiment shows that, when the measurement ranges are 0–6, 0–5, and 0–4 mm, the maximum measurement errors are 0.140, 0.065, and 0.040 mm, respectively, under temperature ranging from 20 ∘C to 110 ∘C. This study extends the measurement range from 0–5 mm to 0–7 mm and improves the measurement accuracy over 0.1 mm (50% at 5 mm) compared with the two-dimensional look-up table method. Therefore, the proposed method not only inherits the advantages of the original method but also achieves the above-mentioned expected capacity improvements effectively.

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Modeling of High-Frequency Electromagnetic Effects on an Ironless Inductive Position Sensor

Cited by 13 publications

References 28 publications

A Novel Holistic Design Optimisation Algorithm for the Ironless Inductive Position Sensor

A Novel Holistic Design Optimisation Algorithm for the Ironless Inductive Position Sensor

Differential Structure of Inductive Proximity Sensor

Dimension-Reduced Analog—Digital Mixed Measurement Method of Inductive Proximity Sensor

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