Linear Variable Transformer Research Articles

A novel data acquisition approach for valves in industrial refrigeration

In this paper, a novel method is introduced for the acquisition and transmission of critical parameters from valves used in industrial refrigeration. The parameter sensing provides local intelligence to the valve, which can be later used as a feedback signal for the controller. The hardware design includes ICS (Industrial Control Servo) valve with modifications to connect a Linear Variable Transformer (LVT) position sensor, pressure and temperature sensors. Also, a circuit board carrying the phase shift oscillator, Root Mean Square (RMS) to Direct Current (DC) converter, power supply and a dedicated Bluetooth Low Energy (BLE) module for transmitting the collected data is designed. The transmitted data can be received in a mobile phone android application and used for a secondary data calculation, alarm notification and alerting service technician. The sensor integration along with BLE connectivity creates a novel platform for data acquisition in Industrial Refrigeration (IR). The proposed method tested in real time to regulate the Helium gas flow rate and measured valve parameters is monitored by the dedicated mobile application.

A Statistical Approach to Broken Stick Problems

Let a stick be broken at random at n – 1 points to form n pieces. We consider three problems on forming k-gons with k out of these n pieces, 3≤ k ≤ n, and show how a statistical approach, through a linear transformation of variables, yields simple solutions that also allow fast computation.

Development of Supervised Learning Predictive Models for Highly Non-linear Biological, Biomedical, and General Datasets.

In highly non-linear datasets, attributes or features do not allow readily finding visual patterns for identifying common underlying behaviors. Therefore, it is not possible to achieve classification or regression using linear or mildly non-linear hyperspace partition functions. Hence, supervised learning models based on the application of most existing algorithms are limited, and their performance metrics are low. Linear transformations of variables, such as principal components analysis, cannot avoid the problem, and even models based on artificial neural networks and deep learning are unable to improve the metrics. Sometimes, even when features allow classification or regression in reported cases, performance metrics of supervised learning algorithms remain unsatisfyingly low. This problem is recurrent in many areas of study as, per example, the clinical, biotechnological, and protein engineering areas, where many of the attributes are correlated in an unknown and very non-linear fashion or are categorical and difficult to relate to a target response variable. In such areas, being able to create predictive models would dramatically impact the quality of their outcomes, generating an immediate added value for both the scientific and general public. In this manuscript, we present RV-Clustering, a library of unsupervised learning algorithms, and a new methodology designed to find optimum partitions within highly non-linear datasets that allow deconvoluting variables and notoriously improving performance metrics in supervised learning classification or regression models. The partitions obtained are statistically cross-validated, ensuring correct representativity and no over-fitting. We have successfully tested RV-Clustering in several highly non-linear datasets with different origins. The approach herein proposed has generated classification and regression models with high-performance metrics, which further supports its ability to generate predictive models for highly non-linear datasets. Advantageously, the method does not require significant human input, which guarantees a higher usability in the biological, biomedical, and protein engineering community with no specific knowledge in the machine learning area.

Single-chip Implementation of LVDT Signal Conditioning

The aim of this work was to prove that the signal conditioning electronics for linear variable transformers (LVDTs) can be implemented in inexpensive, general-purpose 8-bit microcontrollers, making expensive dedicated signal conditioning chips redundant. A low-cost, high-resolution signal conditioning solution for LVDTs is presented. Apart from a few external passive components, the entire solution is implemented in a low-cost, analog-digital hybrid microcontroller. The excitation sinusoid is generated by filtering out the fundamental frequency of a (self-sustained) pwm-generated square wave and the secondary coils’ signals are demodulated with classic peak detector circuits implemented in the microcontroller using a combination of its embedded analog and digital building blocks. A resolution of 1 m over a range of ±6.35 mm for a commercial LVDT is reported and an uncertainty of 6 m in the absolute value is deduced. The entire solution is implemented as surface mounted components on a small printed circuit board and the LVDT core displacement is displayed on an LCD display. Due to the simplicity and low-cost components required, this signal conditioning proposal has the potential to have a significant impact on commercial LVDT signal conditioning chips in the future since it is significantly less expensive than the present state-of-the-art signal conditioning chips offered by the main commercial suppliers and other solutions previously suggested in scientific literature.

Comment on “Fluctuation-dissipation considerations and damping models for ferromagnetic materials”

In a recent article (Phys. Rev. B 71, 224402 (2005)), Safonov and Bertram claim "inconsistent" results can occur when applying the "Callen-Welton fluctuation dissipation theorem" to magnetic systems with dissipation. This author strongly disputes these claims, and instead will show that the inconsistencies claimed by Safonov and Bertram stem solely from a failure to correctly complete a linear transformation of variables, and a concomitant invalid application of well known fluctuation dissipation relations. When used correctly, such fluctuation-dissipation relations most certainly will apply to magnetic (or other physical) systems with dissipation.

Approximate Algorithms for Minimization of Binary Decision Diagrams on the Basis of Linear Transformations of Variables

Algorithms for an approximate minimization of binary decision diagrams (BDD) on the basis of linear transformations of variables are proposed. The algorithms rely on the transformations of only adjacent variables and have a polynomial complexity relative to the size of the table that lists values of the function involved.

Design of a high power brushless linear variable transformer

High power variable transformers are required for use in advanced high voltage-high power laboratories. However, their design is always confronted with various difficulties caused by different physical and electromagnetic design constraints. This paper presents a new design for a high power brushless linear variable transformer. The proposed design has desirable features such as low short circuit impedance which may be useful for different tests particularly high current tests, over a wide range of power requirement. An analytical design procedure is followed, after which a finite element analysis is used to confirm the analytical design results.

Design of a High Power Brushless Linear Variable Transformer

High power variable transformers are required for use in advanced high voltage high power laboratories. However, their design is always confronted with various difficulties caused by different physical and electromagnetic design constraints. This paper presents a new design for a high power brushless linear variable transformer. The proposed design has desirable features such as low short circuit impedance which may be useful for different tests particularly high current tests, over a wide range of power requirement. An analytical design procedure is followed, after which a finite element analysis is used to confirm the analytical design results.

Delay Independent Stabilization of Delayed Systems and Quadratic Stabilizability of Uncertain Delay-Free Linear Systems

So far obtained condition for the delay independent stabilization is improved. A linear transformation of variables are proved to be useful to improve the conditions. On the other hand Wei has proved a necessary and sufficient condition called antisymmetric configuration for the quadrtic stabilizability of uncertain linear time-varyind systems. It is proved that as the result of this imporvement. Wei's condition, with miner restriction, is also sufficient for the delay independent stabilizability

A Comparison of Formulations for the Single-Airport Ground-Holding Problem with Banking Constraints

Both the single-airport ground-holding problem (GH) and the multi-airport ground-holding problem can be extended by the addition of banking constraints to accommodate the hubbing operations of major airlines. These constraints enforce the desire of airlines to land certain groups of flights, called banks, within fixed time windows, thus preventing the propagation of delays throughout their entire operation. GH can be formulated as a transportation problem and readily solved. But in the presence of banking constraints, GH becomes a difficult integer programming problem. In this paper, we construct five different models of the single-airport ground-holding problem with banking constraints (GHB). The models are evaluated both computationally and analytically. For two of the models, we show that the banking constraints induce facets of the convex hull of the set of integer solutions. In addition, we explore a linear transformation of variables and a branching technique.

かみしめ時の下顎の変位と非かみしめ側のこう合接触面積との関係

To investigate the factors affecting the non-chewing side contact, the relationship among simulated non-chewing side tooth contact, jaw displacement, and masticatory muscle activity was evaluated.Seven healthy male subjects volunteered for this study. They were asked to clench on a central bearing device, and vertical displacements of lower bilateral second molars were measured by linear variable transformers. Simultaneously, EMG activity was measured from masseter and anterior temporal muscles. Thesubjects were also asked to clench with film strips in place on unilateral premolars in order to simulate the occlusal phase of the chewing cycle. Occlusal registrations on the contralateral sides were recorded, and then the occlusal contact area was calculated for each side.Comparison of bilateral tooth contact area and second molar displacements showed that the contact area tended to be larger on the side where larger molar displacement was found. The side difference of the contact area was significantly correlated to that of second molar displacement (Pearson's r =0.85 p= 0.01), however, not to EMG activity.

Universal Affine Classification of Boolean Functions

In this paper we advance a practical solution of the classification problem of Boolean functions by the affine group – the largest group of linear transformations of variables. We show that the affine types (equivalence classes) can be arranged in a unique infinite sequence which contains all previous lists of types. The types are specified by their minimal representatives, spectral invariants, and stabilizer orders. A brief survey of the fundamental transformation groups is included.

Reversibility of the decomposability theorem of linear extensions of dynamical systems on a torus

It is known from [I, 2] that, in general, the exponential separation of the solutions of systems of linear differential equations with almost periodic or quasiperiodic coefficients is not sufficient in order that the initial system should be split into subsystems of smaller order by a linear transformation of variables with an almost periodic or quasiperiodic transformation matrix. In [3] one has given sufficient conditions for such a decomposability.

A combined algorithm for weighting the variables and clustering in the clustering problem

One problem in clustering (classification) analysis relates to whether or not the original variables should be transformed in some way before they are used by the clustering algorithm. More often than not, the original variables do require some transformation. The purpose of the transformation may be a desire to have more compact clusters in the space of the transformed variables, to take into account the different nature and/or units of the variables involved, to allow for the different or equal ‘importance’ of different variables, to minimize the number of variables used, etc. Among the linear transformations of variables we distinguish two groups - those which change only the scales of the variables (they are often called weighting procedures), and those which also rotate the space of variables (a good example would be the method of principal components (1)). This paper addresses the former group of transformations. One strong reason for using the weighted variables (as opposed to their linear combinations) is that when using them one can interpret the results of the classification in terms of the original (physical) variables. Unfortunately, weighting the variables can result in ‘spoiling’ the compactness of the clusters in the space of the weighted variables if the weighting procedure being used ‘does not care’ about the results of clustering (in other words if the weighting is done prior to and independently of the clustering). A method of weighting the variables which is a part of the classification procedure and thus guarantees an improvement of the cluster clarity is suggested in this paper. The weights of variables and the clusters of objects produced by the algorithm correspond to a local minimum of some classification criterion. Because of this, the resultant weights can be interpreted as a measure of ‘importance’ of the variables for the classification purpose. These weights are compared with such popular weighting procedures as equal variance (6) and Mahalanobis distance (7) methods. Two examples of the performance of the algorithm are presented.

Initial Sintering of Glass

The shrinkage isotherms of the powder compacts of spherical soda-lime glasses were measured in the temperature range of 590° to 660°C in air. An analytical equation for the initial sintering of glass powders was developed from the viewpoint of non-Newtonian flow. The shrinkage data measured with a dilatometer consisting of a linear variable transformer were best correlated with the equation. The results indicated that the length of unit flow, δ, was 3-10Å and that the viscosity coefficients were in fairly good agreement with those obtained by other authors.

An Automatically Recording Thermal‐Expansion Apparatus

An automatic thermal‐expansion apparatus is described in which the device for sensing sample dilation is a linear variable differential transformer. The equipment plots temperature vs. expansion using a two‐function recording potentiometer. The linear variable transformer was chosen because of insensitivity to thermal changes and to horizontal misalignment, flexibility of range and sensitivity, and small size. Performance data are presented for a number of tests and the advantages and disadvantages of the equipment are discussed. The electrical circuit necessary for adapting the sensing device to this particular use is also described.

Microformer Dilatometer

The construction, calibration, and use of a dilatometer that is ideally suited for use with radioactive materials is described. Expansion measurements are made electrically with a linear variable transformer.