Integrator Drift Compensation of Magnetic Flux Transducers by Feed-Forward Correction

Integrator drift is a problem strongly felt in different measurement fields, often detrimental even for short-term applications. An analytical method for modelling and feed-forward correcting drift in magnetic flux measurements was developed analytically and tested experimentally. A case study is reported on the proof of principle as a novel kind of quasi-DC field marker of the 5-ppm Nuclear Magnetic Resonance (NMR) transducer Metrolab PT2026, applied to the Extra Low ENergy Antiproton (ELENA) ring and the Proton Synchrotron Booster (PSB) at CERN. In some particle accelerators, such as in ELENA, the resulting feed-forward correction guarantees 1 μ T field stability over 120-s long magnetic cycle on a plateau of 50 mT, reducing by three orders of magnitude the field error caused by the integrator drift with respect to the state of the art

Dynamic Ferromagnetic Hysteresis Modelling Using a Preisach-Recurrent Neural Network Model

In this work, a Preisach-recurrent neural network model is proposed to predict the dynamic hysteresis in ARMCO pure iron, an important soft magnetic material in particle accelerator magnets. A recurrent neural network coupled with Preisach play operators is proposed, along with a novel validation method for the identification of the model's parameters. The proposed model is found to predict the magnetic flux density of ARMCO pure iron with a Normalised Root Mean Square Error (NRMSE) better than 0.7%, when trained with just six different hysteresis loops. The model is evaluated using ramp-rates not used in the training procedure, which shows the ability of the model to predict data which has not been measured. The results demonstrate that the Preisach model based on a recurrent neural network can accurately describe ferromagnetic dynamic hysteresis when trained with a limited amount of data, showing the model's potential in the field of materials science

Drift-Free Integration in Inductive Magnetic Field Measurements Achieved by Kalman Filtering

Sensing coils are inductive sensors commonly used to measure magnetic fields, such as those generated by electromagnets used in many kinds of industrial and scientific applications. Inductive sensors rely on integrating the output voltage at the coil’s terminals in order to obtain flux linkage, which may suffer from the magnification of low-frequency noise resulting in a drifting integrated signal. This article presents a method for the cancellation of integrator drift. The method is based on a first-order linear Kalman filter combining the data from the coil and a second sensor. Two case studies are presented. In the first one, the second sensor is a Hall probe, which senses the magnetic field directly. In a second case study, the magnet’s excitation current was used instead to provide a first-order approximation of the field. Experimental tests show that both approaches can reduce the measured field drift by three orders of magnitude. The Hall probe option guarantees, in addition, one order of magnitude better absolute accuracy than by using the excitation current

Magnetic properties of a nanocrystalline material for current derivative sensors of magnets protection systems

Nanocrystalline materials are becoming ever more broadly used in transformer-based transducers due to their low losses, high relative permeability and high saturation flux density. In this paper, the magnetic characterization of one of these materials is presented by highlighting its influence on the performance of a current derivative sensor. This sensor was recently prototyped at CERN in the framework of the consolidation activity on the quench protection of superconducting magnets for the high-luminosity upgrade of the Large Hadron Collider. The performance is analyzed in terms of linearity and dynamic response

Characterization of Magnetic Steels for the FCC-ee Magnet Prototypes

At the European Organization for the Nuclear Research (CERN), several efforts were combined for a preliminary design of a new accelerator, the Future Circular Collider (FCC), a 100-TeV double-ring hadron collider to be installed in a 100-km tunnel. As potential intermediate step, a high-luminosity lepton collider called FCC-ee is foreseen with more than 9,000 magnets. This paper provides an insight into the magnetic properties of the steels, potentially considered for the new dipole magnets, with nominal field of only 56 mT. The influence of the properties of these steels on the magnet transfer function has been assessed analytically using an equivalent reluctance network to model the first 1-m long dipole prototypes. The analytical results were validated experimentally. The proposed approach can be a useful tool for traceability and quality control during the series production

Hysteresis Modeling in Iron-Dominated Magnets Based on a Multi-Layered Narx Neural Network Approach

A full-fledged neural network modeling, based on a Multi-layered Nonlinear Autoregressive Exogenous Neural Network (NARX) architecture, is proposed for quasi-static and dynamic hysteresis loops, one of the most challenging topics for computational magnetism. This modeling approach overcomes drawbacks in attaining better than percent-level accuracy of classical and recent approaches for accelerator magnets, that combine hybridization of standard hysteretic models and neural network architectures. By means of an incremental procedure, different Deep Neural Network Architectures are selected, fine-tuned and tested in order to predict magnetic hysteresis in the context of electromagnets. Tests and results show that the proposed NARX architecture best fits the measured magnetic field behavior of a reference quadrupole at CERN. In particular, the proposed modeling framework leads to a percent error below 0.02% for the magnetic field prediction, thus outperforming state of the art approaches and paving a very promising way for future real time applications

A Static-Sample Magnetometer for Characterizing Weak Magnetic Materials

In this paper, a static-sample magnetometer is presented to measure the relative permeability of weakly magnetic materials. The method consists of scanning the magnetic field inside a dipole magnet by using an NMR teslameter to measure the perturbation of a test specimen on the externally applied field. Then, an inverse problem is used to compute the specimen's relative permeability. As a case study, the measurement of three different materials with different shapes and dimensions is carried out. The method was validated by measuring the same material by a vibrating sample magnetometry as proposed by the standard ASTM A342/A342M-14. The Monte Carlo evaluated expanded measurement uncertainty of the relative permeability is about 10 −4 for all the cases, with a level of confidence of 95 %

Rotating-Coil Measurement System for Small-Bore-Diameter Magnet Characterization

Rotating-coil measurement systems are widely used to measure the multipolar fields of particle accelerator magnets. This paper presents a rotating-coil measurement system that aims at providing a complete data set for the characterization of quadrupole magnets with small bore diameters (26 mm). The PCB magnetometer design represents a challenging goal for this type of transducer. It is characterized by an aspect ratio 30% higher than the state of the art, imposed by the reduced dimension of the external radius of the rotating shaft and the necessity of covering the entire magnet effective length (500 mm or higher). The system design required a novel design for the mechanical asset, also considering the innovation represented by the commercial carbon fiber tube, housing the PCB magnetometer. Moreover, the measurement system is based primarily on standard and commercially available components, with simplified control and post-processing software applications. The system and its components are cross-calibrated using a stretched-wire system and another rotating-coil system. The measurement precision is established in a measurement campaign performed on a quadrupole magnet characterized by an inner bore diameter of 45 mm

Performance comparison of nuclear magnetic resonance and FerriMagnetic resonance field markers for the control of low-energy synchrotrons

A field marker is a magnetic field sensor used in synchrotrons, which provides a digital trigger when the magnetic field reaches a pre-set threshold. This paper describes the results of an in-situ measurement performed on the Extra Low ENergy Antiproton (ELENA) decelerator's main bending dipoles at the European Organization for Nuclear Research (CERN). It compares the dynamic behavior of Nuclear Magnetic Resonance (NMR) markers and FerriMagnetic Resonance (FMR) markers in different magnetic fields for the operation of these sensors in low-energy synchrotrons.peer-reviewe

A Superconducting Permeameter for Characterizing Soft Magnetic Materials at High Fields

Asuperconductingpermeameterisproposedtocharacterizethemagneticpropertiesofhigh-energysuperconducting magnet yokes at their operating temperatureand saturation level. The main problem of superconductingcoils, an undesired quench, was faced by specific protectionsimulations, which has led to a self-protected system. Thesuperconducting permeameter was used to perform the magneticcharacterization of ARMCO Pure Iron, the material for the newHigh-Luminosity Large Hadron Collider (HL-LHC) supercon-ducting magnet yokes, which was performed at the cryogenictemperature of 4.2 K and a saturation level of nearly 3 T.Two case studies based on the new HL-LHC superconductingquadrupole and dipole magnets highlight the impact of themagnetic properties of the yoke on the performance of thesuperconducting magnets, showing that the common assumptionthat heavily saturated steels with similar chemical compositionbehave precisely the same way has been proven wrong