Inductive Sensor Research Articles

A novel demodulator design for signal processing of inductive oil debris sensors

Abstract Metal debris from bearing wear occurred in the lubrication system of aircraft engines represents valuable information, which can be utilized to assess the current engine condition and further enable the life-cycle prediction. The demodulation of debris signals consists of two parts: mixing and filtering. In traditional methods, the mixing process is complex to adjust and prone to failure, while the filtering employs the fixed low-pass filtering, which significantly affects the demodulation performance when the debris flow rate changes. To address these issues, this paper proposes a novel demodulation model to enhance the demodulation performance and increase the signal-to-noise ratio of chip signals. Firstly, the circuit innovatively adopts a self-frequency mixing method to avoid the complex phase adjustment required by traditional reference-frequency mixing methods for the improved stability of the circuit. Following that, a digital potentiometer is employed to implement the flow rate filtering, enabling precise control over the filter type and range, thus mitigating signal distortion caused by changes in flow rate and increasing the signal-to-noise ratio. Throughout extensive experiments and data analysis, the self-frequency mixing method improves the signal-to-noise ratio by 0.72 dB and reduces the signal standard deviation by 59.12% as compared to the reference-frequency mixing method. Considering the debris flow rate in the range of 0.2 to 0.5 m/s, the flow rate filtering method improves the signal-to-noise ratio by 19.71 dB and reduces the amplitude standard deviation by 66.18%, as compared to results by the traditional fixed low-pass filtering method. Results demonstrate that the aforementioned circuit design effectively enhances the signal amplitude and stability of inductive oil debris sensors in the wear assessment of mechanical systems and provides useful insights into the development of advanced sensors used in the field of structural health monitoring.

Online Quality Control of Powder Bed Fusion with High-Resolution Eddy Current Testing Inductive Sensor Arrays.

This paper presents the development of a novel eddy current array (ECA) system for real-time, layer-by-layer quality control in powder bed fusion (PBF) additive manufacturing. The system is integrated into the recoater of a PBF machine to provide spatially resolved electrical conductivity imaging of the manufactured part. The system features an array of 40 inductive sensors spaced at 1 mm pitch and is capable of performing a full array readout every 0.192 mm at 100 mm/s recoater speed. Array scalability was achieved through the careful selection of the electromagnetic configuration, miniaturized and seamlessly integrated sensor elements, and the use of advanced mixed signal processing techniques. Experimental validation was performed on stainless steel 316L parts, successfully detecting metallic structures and confirming system performance in both laboratory and real-time PBF environments. The prototype achieved a signal-to-noise ratio (SNR) of 26.5 dB, discriminating metal from air and thus demonstrating its potential for improving PBF part design, process optimization, and defect detection.

Modeling of an inductive displacement sensor based on 1DCNN-LSTM-AT

Abstract The input-output relationship of inductive displacement sensors is typically nonlinear, which demands numerous computational resources for precise calculation. Therefore, the traditional analytical methods for the inductive displacement sensors cannot meet the real-time high-precision measurement requirements. In response to the aforementioned issues, this paper proposes an optimized Long Short-Term Memory (LSTM) neural networks based on one-dimensional convolutional neural networks (1DCNN) to modeling the input-output relationship of the inductive displacement sensor. First, the measurement principle of the inductive displacement sensors was analyzed, and the analytical model of the sensor output was derived. And the influences of the key parameters of sensors on the relationship between the induced voltage and the displacement were studied. Then, the 1DCNN-LSTM-AT network for modelling the input-output relationship of the inductive displacement sensor was studied. The spatial features of historical induced electromotive force (EMF) data generated by the induction coil were initially extracted using the 1DCNN network. And these spatial features were then utilized as input to the LSTM neural network to capture the temporal features of the historical induced EMF data. Subsequently, the spatiotemporal features of the induced EMF data were fed into the regression prediction layer to compute the displacement measurement results corresponding to the current input. Moreover, the attention mechanism was used for the 1DCNN-LSTM model to enhance the prediction accuracy and stability of the model. Finally, the experimental results demonstrate that the proposed 1DCNN-LSTM-AT model achieves an average absolute percentage error (MAPE) of 3.1%, significantly outperforming traditional models such as LSTM (29.3%), CNN (4.7%), and ANN (4.3%). This paper provides a new method for modelling the nonlinear relationships of the inductive displacement sensor, and presents a fresh perspective for research in the data processing of nonlinear sensors.

Inductive Frequency-Coded Sensor for Non-Destructive Structural Strain Monitoring of Composite Materials

Structural composite materials have gained significant appeal because of their ability to be customized for specific mechanical qualities for various applications, including avionics, wind turbines, transportation, and medical equipment. Therefore, there is a growing demand for effective and non-invasive structural health monitoring (SHM) devices to supervise the integrity of materials. This work introduces a novel sensor design, consisting of three spiral resonators optimized to operate at distinct frequencies and excited by a feeding strip line, capable of performing non-destructive structural strain monitoring via frequency coding. The initial discussion focuses on the analytical modeling of the sensor, which is based on a circuital approach. A numerical test case is developed to operate across the frequency range of 100 to 400 MHz, selected to achieve a balance between penetration depth and the sensitivity of the system. The encouraging findings from electromagnetic full-wave simulations have been confirmed by experimental measurements conducted on printed circuit board (PCB) prototypes embedded in a fiberglass-based composite sample. The sensor shows exceptional sensitivity and cost-effectiveness, and may be easily integrated into composite layers due to its minimal cabling requirements and extremely small profile. The particular frequency-coded configuration enables the suggested sensor to accurately detect and distinguish various structural deformations based on their severity and location.

ANÁLISE DE UM PROTÓTIPO DE UMA ESTEIRA TRANSPORTADORA COM AUTOMAÇÃO INDUSTRIAL PARA SEPARAÇÃO DE PEÇAS METÁLICAS E NÃO METÁLICAS UTILIZANDO ARDUINO UNO

Introduction: The use of Arduino Uno and the LS PLC allows for an innovative approach to process automation, offering a practical and effective solution for industrial applications. This automated system is designed to increase productivity and accuracy in material separation, minimizing manual intervention and associated errors. Objective: to analyze a prototype of a conveyor belt with industrial automation for separating metal and non-metal parts using Arduino. Methodology: This study is a qualitative case study of the development of a prototype conveyor belt with industrial automation using the arduino system. Results: The data showed that the NPN inductive and ultrasonic sensors had high detection accuracy rates, with 95% and 97% success, respectively. Communication between the Arduino and the PLC was efficient, allowing the system to respond quickly to sensor readings and trigger the actuators synchronously. The implementation of safety devices, such as pushbuttons and circuit breakers, ensured system protection, while the visual monitoring provided by the 16×2 LCD display facilitated real-time monitoring of operations. Conclusion: The automation of the conveyor belt proved to be a viable and effective solution for sorting materials in an industrial context. The integration of the components and the efficient communication between them were fundamental to the success of the project. This project serves as a solid foundation for future innovations in industrial automation, contributing to the modernization and efficiency of production processes.

ANÁLISE DE UM PROTÓTIPO DE UMA ESTEIRA TRANSPORTADORA COM AUTOMAÇÃO INDUSTRIAL PARA SEPARAÇÃO DE PEÇAS METÁLICAS E NÃO METÁLICAS UTILIZANDO ARDUINO UNO

Introduction: The use of Arduino Uno and the LS PLC allows for an innovative approach to process automation, offering a practical and effective solution for industrial applications. This automated system is designed to increase productivity and accuracy in material separation, minimizing manual intervention and associated errors. Objective: to analyze a prototype of a conveyor belt with industrial automation for separating metal and non-metal parts using Arduino. Methodology: This study is a qualitative case study of the development of a prototype conveyor belt with industrial automation using the arduino system. Results: The data showed that the NPN inductive and ultrasonic sensors had high detection accuracy rates, with 95% and 97% success, respectively. Communication between the Arduino and the PLC was efficient, allowing the system to respond quickly to sensor readings and trigger the actuators synchronously. The implementation of safety devices, such as pushbuttons and circuit breakers, ensured system protection, while the visual monitoring provided by the 16×2 LCD display facilitated real-time monitoring of operations. Conclusion: The automation of the conveyor belt proved to be a viable and effective solution for sorting materials in an industrial context. The integration of the components and the efficient communication between them were fundamental to the success of the project. This project serves as a solid foundation for future innovations in industrial automation, contributing to the modernization and efficiency of production processes.

Instrumentation in Tractor for Evaluating Performance of a Tractor Drawn Rotavator

Performance measurement of agricultural machinery is essential for enhancing their efficiency for which they are operated. The performance related data helps the operator to select optimum operating parameters which reduce fuel consumption and increase field productivity. This study was aimed to develop various sensing units and install them on the tractor for evaluating performance of a tractor drawn rotavator. A microcontroller based embedded system was developed for continuous recording of wheel slip, actual forward speed, throttle opening, engine speed, velocity ratio, draft and power take-off (PTO) torque related data while carrying out tillage operation with rotavator. The wheel slip (from 1.5% to 35%) and actual forward speed of the tractor (up to 6 km h-1) was measured using inductive proximity sensors. For measuring throttle opening (0 to 100%), engine speed (750 to 2500 rpm), draft (65 to 350 kg) and PTO torque (up to 420 N-m) values, a potentiometer, magnetic pickup sensor, S-type loadcell and PTO torque transducer, respectively, were used. For computing velocity ratio, peripheral speed of rotavator was measured using PTO speed data received from PTO torque transducer, and actual forward speed of tractor was measured using inductive proximity sensor. The developed sensing units were calibrated under both dynamic and static conditions, and were also verified in laboratory and field conditions. Results showed that output signals received from the sensing units varied linearly with applied load. The mean absolute percentage error (MAPE) between measured and actual values was found to be below 5%. From the measured parameters, specific energy requirement and total power required for carrying out tillage operation could be computed. The power requirement was found to increase with increase in both gear and throttle settings. The specific energy requirement was minimum when rotavator was operated in L2 gear of the tractor. The minimum specific energy of 21 Wh m-3 was found at L2 gear and 75% throttle opening.

In-Motion, Non-Contact Detection of Ties and Ballasts on Railroad Tracks

This study aims to develop a robust and efficient system to identify ties and ballasts in motion using a variety of non-contact sensors mounted on a robotic rail cart. The sensors include distance LiDAR sensors and inductive proximity sensors for ferrous materials to collect data while traversing railroad tracks. Many existing tie/ballast health monitoring devices cannot be mounted on Hyrail vehicles for in-motion inspection due to their inability to filter out unwanted targets (i.e., ties or ballasts). The system studied here addresses that limitation by exploring several approaches based on distance LiDAR sensors. The first approach is based on calculating the running standard deviation of the measured distance from LiDAR sensors to tie or ballast surfaces. The second approach uses machine learning (ML) methods that combine two primary algorithms (Logistic Regression and Decision Tree) and three preprocessing methods (six models in total). The results indicate that the optimal configuration for non-contact, in-motion differentiation of ties and ballasts is integrating two distance LiDAR sensors with a Decision Tree model. This configuration provides rapid, accurate, and robust tie/ballast differentiation. The study also facilitates further sensor and inspection research and development in railroad track maintenance.

Balancing of Resonant Differential Coils for Broadband Inductive Sensor Systems.

Differential coils are frequently implemented in inductive sensing systems. They can be considered as a single coil that is made up of two or more subcoils, wound in series opposition. They can be used on the transmit or receive side of measurement systems, and, if designed correctly, ensure no coupling between coils under background conditions. By cancelling background coupling, the receive electronics only needs to be able to measure the change in coupling produced by a target. This allows for a more efficient use of the dynamic range, and for larger receive-side amplifier gain, thereby improving SNR. When subcoils are not electrically similar, it can be hard to engineer the coil to be perfectly balanced across a wide bandwidth. This paper presents an analytical model of a resonant differential coil pair that is tested and applied on a planar metal detector for the detection of buried objects. The model demonstrates the capability to balance an arbitrary differential coil pair, which has a broad applicability across a range of inductive sensor applications such as metal detection and non-destructive testing. The method is applied to the practical system. The results show that the correction resulting from this method ensures a stable balance across a significantly enhanced bandwidth. In the case studied here, the bandwidth of the experimental system is increased from 20 kHz to 90 kHz.

Research on the application and prospects of variable reluctance inductive sensors

Variable reluctance inductive sensors are extensively utilized in the industrial field due to its unique working mechanism and good performance characteristics. Based on the working principle of Variable Reluctance Inductive Sensors, this paper reviews its development history, application in industrial automation and medical industry. Through the analysis of variable reluctance inductive sensors, variable reluctance inductive sensors have the advantages of high sensitivity, low cost and reliability which can support its wide application in precision measurement, position detection and motion control, but it is susceptible to the interference of the external magnetic field and the influence of the temperature which limits its development space and scope. However, the advancement of new materials, intelligent technologies and multi-mode integration has broadened the potential of future development of sensors and created more challenges for the development of variable reluctance inductive sensors. The update of new research conditions also provides a valuable reference of research and application in related fields

LC contact lens sensor for ultrasensitive intraocular pressure monitoring

Twenty-four hours continuous intraocular pressure (IOP) monitoring is beneficial for glaucoma care. Contact lens sensors using LC technology can achieve non-invasive continuous IOP measuring around the clock and are relatively simple in principle and structure, thus dominating the mainstream. Among them, stretchable inductive LC contact lens sensors constructed with liquid metal have advantages in signal quality as well as wearing comfort, but currently its sensitivity is slightly insufficient. Here, we propose an LC sensor that constructed with liquid metal to form the stretchable inductance and capacitance further. The capacitive plate and inductive coil can response to IOP changes simultaneously, thus able to enhance the sensitivity in principle. We modeled the sensing mechanism and conducted design, fabrication, as well as various tests. The device exhibits good characteristics, including reliability, good signal quality, etc. Especially, it has a threefold increase in sensitivity, exceeding the current state-of-the-art contact lens sensors.

An Experimental Study of Odometer as a Navigation aid for Land Vehicle Application

Strap-down inertial navigation system (SINS) shall provide position, velocity, and orientation information with reference to a pre-defined reference frame. The SINS shall have excellent accuracy over a short duration and is highly self-contained. However, the errors in navigation solutions build up exponentially with time and make the system output very unstable. In order to mitigate these errors, there is a need for a damping mechanism through external aiding sensors. In this article, one such approach is proposed to improve navigation accuracy for land vehicles in the GNSS (Global Navigation Satellite Systems) denied environment. The design and implementation of an odometer are carried out with the use of inductive proximity sensors and a mounting assembly to attach the odometer to one of the non-steering wheels of a vehicle. The odometer gives the pulse-high and pulse-low output with reference to the rotation of the wheel to which it is attached. Vehicle ground velocity is derived through sensed output pulses processed through quadrature decoder circuitry. Odometer measurements along with non-holonomic constraints (NHC) are used for minimizing velocity and position errors in SINS using an extended Kalman Filter (EKF) technique. Field trials are carried out to validate the proposed scheme of hybrid navigation with odometer design and experimental results are presented with a positioning accuracy of 0.05 % of distance travelled (DT).

Distortion-Free Magnetic Tracking of Metal Instruments in Image-Guided Interventions.

Electromagnetic tracking (EMT) can benefit image-guided interventions in cases where line of sight is unavailable. However, EMT can suffer from electromagnetic distortion in the presence of metal instruments. Metal instruments are widely used in laparoscopic surgery, ENT surgery, arthroscopy and many other clinical applications. In this work, we investigate the feasibility of tracking such metal instruments by placing the inductive sensor within the instrument shaft. We propose a magnetostatic model of the field within the instrument, and verify the results experimentally for frequencies from 6 kHz to 60 kHz. The impact of the instrument's dimensions, conductivity and transmitting field frequency is quantified for ranges representative of typical metal instruments used in image-guided interventions. We then performed tracking using the open-source Anser EMT system and quantify the error caused by the presence of the rod as a function of the frequency of the eight emitting coils for the system. The work clearly demonstrates why smaller tool diameters (less than 8 mm) are less susceptible to distortion, as well as identifying optimal frequencies (1 kHz to 2 kHz) for transmitter design to minimise for distortion in larger instruments.

Development of a Two-Parameter Inductive Sensor for use in Digital Program Control Systems for Machine Tools

Development of a Two-Parameter Inductive Sensor for use in Digital Program Control Systems for Machine Tools

Inductive Sensor Based on Micromachined Coil for Conductive Target Detection

Inductive Sensor Based on Micromachined Coil for Conductive Target Detection

Radial and axial integrated inductive displacement sensor used for magnetic bearing system

This paper presents a small size and high-integration inductive displacement sensor used for magnetic bearings. This sensor is a circular ring structure fixed on radial direction of a magnetic bearing and can measure radial and axial displacement at the same time. Sensitivity results show that displacement detection along each direction will not be affected by others. Then, the proposed sensor is applied in closed-loop control of a magnetic bearing when the rotor is levitated and rotates at 40k, 50k, and 60k r/min. According to experiment results, radial and axial displacement vibrate noise can be controlled within ±10 μm and about ±10 μm, respectively, evaluating the feasibility of inductive displacement sensor in closed-loop control. Contribution of this paper is to explore application boundary and provide a guide of applicable speed for inductive displacement sensor, which will help to promote application of magnetic bearing in more fields. And based on the experiment results present in this paper, inductance sensor can be used for magnetic bearing control when the rotation speed is below 60k r/min.

Design and Analysis of Receiver Coils with Multiple In-Series Windings for Inductive Eddy Current Angle Position Sensors Based on Coupling of Coils on Printed Circuit Boards.

We present a method for improving the amplitude and angular error of inductive position sensors, by advancing the design of receiver coil systems with multiple windings on two layers of a printed circuit board. Multiple phase-shifted windings are connected in series, resulting in an increased amplitude of the induced voltage while decreasing the angular error of the sensor. The amplitude increase for a specific number of windings can be predicted in closed form. Windings are placed electrically in series by means of a differential connection structure, without adversely affecting the signal quality while requiring a minimal amount of space in the layout. Further, we introduce a receiver coil centerline function which specifically enables dense, space-constrained designs. It allows for maximization of the number of possible coil windings while minimizing the impact on angular error. This compromise can be fine-tuned freely with a shape parameter. The application to a typical rotary encoder design for motor control applications with five periods is presented as an example and analyzed in detail by 3D finite-element simulation of 18 different variants, varying both the number of windings and the type of centerline functions. The best peak-to-peak angular error achieved in the examples is smaller than 0.1° electrically (0.02° mechanically, periodicity 5) under nominal tolerance conditions, in addition to an amplitude increase of more than 170% compared to a conventional design which exhibits more than twice the angular error. Amplitude gains of more than 270% are achieved at the expense of increased angular error.

Inductive Paper-Based Flexible Contact Force Sensor Utilizing Natural Micro-Nanostructures of Paper: Simplicity, Economy, and Eco-Friendliness.

Inductive contact force sensors, known for their high precision and anti-interference capabilities, hold significant potential applications in fields such as wearable and medical monitoring devices. Most of the current research on inductive contact force sensors employed novel nanomaterials as sensitive elements to enhance their sensitivity and other performance characteristics. However, sensors developed through such methods typically involve complex preparation processes, high costs, and difficulty in biodegradation, which limit their further development. This article introduces a new flexible inductive contact force sensor using paper as a sensitive element. Paper inherently possesses micro- and nanostructures on its surface and interior, enabling it to sensitively convert changes in contact force into changes in displacement, making it suitable for use as the sensor's sensitive element. Additionally, the advantages of paper also include its great flexibility, low cost, wide availability, and biodegradability. Performance testing on this flexible sensor showed good repeatability, hysteresis, sensitivity, and consistency. When used in experiments for monitoring human motion and respiration, this sensor also exhibited great detection performance. The proposed inductive paper-based flexible contact force sensor, with its simple structure, easy manufacturing process, cost-effectiveness, eco-friendliness, and good sensing performance, provides new insights into research for contact force sensors.

Elbow Gesture Recognition with an Array of Inductive Sensors and Machine Learning.

This work presents a novel approach for elbow gesture recognition using an array of inductive sensors and a machine learning algorithm (MLA). This paper describes the design of the inductive sensor array integrated into a flexible and wearable sleeve. The sensor array consists of coils sewn onto the sleeve, which form an LC tank circuit along with the externally connected inductors and capacitors. Changes in the elbow position modulate the inductance of these coils, allowing the sensor array to capture a range of elbow movements. The signal processing and random forest MLA to recognize 10 different elbow gestures are described. Rigorous evaluation on 8 subjects and data augmentation, which leveraged the dataset to 1270 trials per gesture, enabled the system to achieve remarkable accuracy of 98.3% and 98.5% using 5-fold cross-validation and leave-one-subject-out cross-validation, respectively. The test performance was then assessed using data collected from five new subjects. The high classification accuracy of 94% demonstrates the generalizability of the designed system. The proposed solution addresses the limitations of existing elbow gesture recognition designs and offers a practical and effective approach for intuitive human-machine interaction.

A Wear Debris Signal Processing Method Based on Inductive Monitoring for Aero-Engine

In view of the high false alarm rate in the oil debris monitoring results of the triple-coil inductive sensor in the transmission lubrication system of the aero-engine, a new debris signal processing method based on inductive monitoring is proposed. A time domain analysis is carried out first, and the signal energy is the most effective index to distinguish the debris signature from the noise signature. On this basis, signal energy values within a fixed-length sliding window is processed through the histogram. Finally, a threshold is set for the detection of the debris signature, which is based on the distribution of data within the histogram. This method is applied to the experimental data from a test run of an aero-engine, and the results show that all the debris is detected even if part of it appears during a change in the working condition of the aero-engine. Therefore, this method shows satisfactory results in debris detection accuracy and especially the inhibition of false alarms. It is also applicable for real-time monitoring due to the similarity between the movement of the sliding window and real-time data acquisition. In addition, it is applicable for various sensing principles, including but not limited to the inductive sensor signal, since the detection performance is only related to the signal itself.