Multipoint Sensor System Research Articles

Multi-Point Optical Fiber Fabry-Perot Curvature Sensor Based on Microwave Photonics

This article reports a multi-point curvature sensor system based on multiplexed optical fiber Fabry-Perot interferometric (FPI) sensor devices and a microwave photonics interrogation technique. The FPI sensor is fabricated with the assistance of a capillary tube, where a short section of the capillary is sandwiched between two single-mode fibers, forming the air-gap Fabry-Perot cavity. Bending of the FPI device leads to changes in the fringe contrast of its reflection spectrum. Based on the microwave photonics filtering technique, variations of the fringe contrast are encoded into the changes in the peak magnitude of the passband in the frequency response of the FPI device. By multiplexing such FPI devices with different cavity lengths, multi-point measurements of curvature can be realized by tracking changes in corresponding passbands in the frequency response of the system. The FPI curvature sensor is easy-to-manufacture and cost-effective, and the microwave photonics-based system provides an alternative and robust solution to interrogating the multiplexed FPI sensors for multi-point curvature sensing that could be desired in structural health monitoring, human-machine interface sensing, and other related fields.

Robust thermal error estimation for machine tools based on in-process multi-point temperature measurement of a single axis actuated by a ball screw feed drive system

In machine tools, thermal errors account for 70 % of the total machining errors. The latest improvements in sensor technology have enabled the robust estimation of thermal displacement using the multi-point temperature data of an entire structure. The complex geometry and constant motion of a feed drive system make the direct measurement of temperature difficult because of the sensor power supply and data transmission. In this study, a wireless multi-point temperature sensor system was developed, and the temperature of a ball screw was measured. The ball screw was developed with a built-in temperature sensor array and was installed in an actual machining center. Thermal error measurement tests were conducted, wherein the temperatures of 277 points on the structure and 25 points on the Z-axis ball screw were measured during machine operation. Using finite element analysis (FEA) with multi-point temperature mapping of the drive system, the difference between the relative displacement of the tool center point (TCP) along the Z-axis, measured by an eddy current sensor, and the value estimated by the FEA was calculated to be less than 10 μm. However, the Z-axis ball screw temperature distribution contributed little to the accuracy of thermal displacement estimation along other axes. Therefore, a superposition of the thermal displacements of the structure and drive system provided TCP relative displacement, suggesting the effect of temperature-dependent geometric errors on the volumetric error model of machine tools.

Monitoring the propagation of mechanical discontinuity using data-driven causal discovery and supervised learning

Mechanical wave transmission through a material is influenced by the mechanical discontinuity in the material. The propagation of embedded discontinuities can be monitored by analyzing the wave-transmission measurements recorded by a multipoint sensor system placed on the surface of the material. The proposed workflow monitors the propagation of mechanical discontinuity through three stages, namely initial, intermediate, and final stages, by using supervised learning followed by data-driven causal discovery. To the end, the workflow processes the multipoint waveform measurements resulting from a single impulse source, while considering the effects of wave attenuation, dispersion and multiple wave-propagation modes due to the discontinuity and material boundaries. Among various feature reduction techniques ranging from decomposition methods to manifold approximation methods, the features derived based on statistical parameterizations of the measured waveforms lead to reliable monitoring that is robust to changes in precision, resolution, and signal-to-noise ratio of the multipoint sensor measurements. The numbers of zero-crossing, negative-turning, and positive turning in the waveforms are the strongest causal signatures of the propagation of mechanical discontinuity. Higher order moments of the waveforms, such as variance, skewness and kurtosis, are also strong causal signatures of the propagation. The newly discovered causal signatures confirm that the statistical correlations and conventional feature rankings are not always statistically significant indicators of causality.

Low-Cost Interrogation of Long-Distance and Multipoint FBG Sensor Using Incoherent-FMCW Optical Ranging System

More than a decade, multipoint sensor systems involving fiber Bragg gratings (FBGs) have been widely used in various implementations, especially the structural health monitoring system (SHMS). In this paper, a three-points FBG sensor was successfully analyzed by combination of incoherent frequency modulated continuous wave (I-FMCW) optical ranging system and a vertical-cavity surface-emitting laser (VCSEL) as a wavelength-tunable laser source. This system is not only capable of reading out the FBG sensors, but also identifying the location of the installed FBGs. The I-FMCW can be conducted by intensity modulation of a low-cost commercial VCSEL. Furthermore, the wavelength of the VCSEL can also be tuned by the injection current change to match the Bragg wavelength of FBGs. The detected signal from the FBGs and the reference signal from the signal generator are electrically mixed to obtain the beat frequency. A thermo-electric controller (TEC) controls temperature of one of the FBGs in the range of 25° C ~ 45° C, and contrary the others are kept at room temperature. As well as measuring temperature, one of the FBGs is strained in the range of $369~\mu \varepsilon \sim ~2137~\mu \varepsilon $ . The measurement result shows that the system can clearly distinguish all FBGs installed in totally 6.6 km-long optical fiber. In addition, the Bragg wavelength shift of the FBGs according to temperature as well as strain changes was successfully measured. The system can be scaled up more than three FBGs and extended scale area, and is a candidate as a low-cost and simple FBG interrogator for a long-range SHMS.

Fiber-Optic Multipoint Sensor System with Low Drift for the Long-Term Monitoring of High-Temperature Distributions in Chemical Reactors.

A low-drift fiber-optic sensor system, consisting of 24 regenerated fiber Bragg gratings (RFBG), equally distributed over a length of 2.3 m, is presented here. The sensor system can monitor spatially extended temperature profiles with a time resolution of 1 Hz at temperatures of up to 500 °C. The system is intended to be used in chemical reactors for both the control of the production ramp-up, where a fast time response is needed, as well as for production surveillance, where low sensor drifts over several years are required. The fiber-optic sensor system was installed in a pilot test reactor and was exposed to a constant temperature profile, with temperatures in the range of 150–500 °C for more than two years. During this period, the temperature profile was measured every three to five months and the fiber-optic temperature data were compared with data from a three-point thermocouple array and a calibrated single-point thermocouple. A very good agreement between all temperature measurements was found. The drift rates of the 24 RFBG sensor elements were determined by comparing the Bragg wavelengths at a precisely defined reference temperature near room temperature before and after the two-year deployment. They were found to be in the range of 0.0 K/a to 2.3 K/a, with an average value of 1.0 K/a. These low drift rates were achieved by a dedicated temperature treatment of the RFBGs during fabrication. Here, the demonstrated robustness, accuracy, and low drift characteristics show the potential of fiber-optic sensors for future industrial applications.

Multi-Point Wireless Temperature Sensing System for Monitoring Pharmaceutical Lyophilization.

This work presents the design and evaluation of a fully wireless, multi-point temperature sensor system as a Process Analytical Technology (PAT) for lyophilization. Each sensor contains seven sensing elements which measure the product temperature at various positions of the contents of a glass vial. The sensor performance was studied by freeze drying experiments with sensor placement in both center and edge of full shelf of 6R glass vials with 4 ml fill volume. Product temperature profile and primary drying time measured at the bottom center position in the glass vial by the wireless sensor as well as the primary drying time are in close comparison with the thermocouple data. The drying times during primary drying were determined at the top, higher middle, lower middle and bottom positions which are 3.26 mm apart vertically in the vial by the wireless sensor based on the temperature profile measured at different positions. For a center vial, the drying time from the start of primary drying to each layer was measured at 3.9, 9.3, 14.2, and 21 h respectively, allowing to track the sublimation interface during primary drying phase. In addition, sublimation rate at each layer was calculated based on the drying time and theoretical weight loss of ice in the product. The sublimation rate at the beginning of the primary drying was similar to the sublimation rate by gravimetric method. Furthermore, the vial heat transfer coefficient (Kv) was also calculated based on the sublimation rate. Thus, allowing the use of the multi-point wireless sensor to rapidly monitor the sublimation rate and Kv for every batch as continuous process verification. Similar tests were also conducted with 3% w/v mannitol solutions and the results were consistent demonstrating potential for real-time monitoring, process verification and cycle optimization for pharmaceutical lyophilization.

Capacity and capability enhancements of FBG sensor system by utilizing intensity and WDM detection technique

In this paper, we demonstrate a multipoint fiber Bragg grating (FBG)-based sensor system by using intensity and wavelength-division-multiplexing (I-WDM) technique to enhance the sensing capacity and capability. In the proposed multipoint sensor system, a three output port optical splitter with different output ratios of 50%, 35% and 15% is proposed to connect each intensity coding FBG sensor for strain and temperature sensing simultaneously. Different output ratios of connected ports can produce different intensity-coding for I-WDM application. Nine FBGs with different Bragg wavelengths are employed for demonstration. The proposed FBG sensor system not only can sense the strain and temperature simultaneously, but also can increase the capacity and capability.

A Robust Distributed Multipoint Fiber Optic Gas Sensor System Based on AGC Amplifier Structure.

A harsh environment-oriented distributed multipoint fiber optic gas sensor system realized by automatic gain control (AGC) technology is proposed. To improve the photoelectric signal reliability, the electronic variable gain can be modified in real time by an AGC closed-loop feedback structure to compensate for optical transmission loss which is caused by the fiber bend loss or other reasons. The deviation of the system based on AGC structure is below 4.02% when photoelectric signal decays due to fiber bending loss for bending radius of 5 mm, which is 20 times lower than the ordinary differential system. In addition, the AGC circuit with the same electric parameters can keep the baseline intensity of signals in different channels of the distributed multipoint sensor system at the same level. This avoids repetitive calibrations and streamlines the installation process.

Spectral characteristics of chromatic confocal imaging systems.

We present signal-generation models for chromatic confocal imaging systems with illumination and detection pinholes of finite size: a collinear model that considers neither aberrations nor diffraction effects, a geometrical model that accounts for aberrations, and a wave optical model covering both aberrations and diffraction effects. These models are aimed at describing the spectral response of multipoint sensor systems with field-dependent aberrations and vignetting effects. They are suitable for single- and double-pass systems with either diffusely or specularly reflecting surfaces under test. We show experimental results to verify our models.

Hexagonal Mesh Architecture for Large-Area Multipoint Fiber Sensor System

This letter presents a reliable hexagonal mesh architecture for a large-area multipoint fiber sensor system. While covering a large area, the proposed mesh architecture demarcates a large number of fiber sensing regions. Within each sensing region, a ring subnet is constructed to serve many fiber Bragg grating (FBG). In particular, the proposed sensor system incorporates the fiber laser scheme cooperation with the signal-averaging module to enhance its signal-to-noise ratio (SNR) performance. The self-restored capability of the proposed system is achieved by optical switches, allowing it to protect numerous FBG sensors against fiber break(s). A higher SNR with respect to any FBG sensor setting in our experiment is available due to the signal-averaging module.

Multiplexing of PVA-coated multimode-fiber taper humidity sensors

A simple multiplexing method for relative humidity (RH) sensors based on multimode-fiber tapers (MFTs) is proposed and demonstrated. By cascading a polyvinyl alcohol (PVA) coated MFT with every channel of an Arrayed-Waveguide Grating (AWG), multipoint RH measurement is achieved. Experimental results show that the proposed multipoint RH sensor system works well. The output power for every sensor head is almost linearly increased with the RH, and the average sensitivity of the proposed sensor is about 0.23nW/%RH within the measurement range of 35%RH–90%RH with the taper waist diameter of ∼22μm.

Fiber Bragg Grating Sensor System With Two-Level Ring Architecture

This investigation proposes a fiber Bragg grating (FBG) sensor system with a two-level ring architecture. The survivability and capacity of a FBG for a multipoint sensor system are enhanced by adding remote nodes and optical switches in the two-level ring architecture. Additionally, to enhance the signal-to-noise ratio (SNR) of the sensor system, a fiber ring laser approach is utilized to construct the proposed two-level ring architecture. The fiber ring laser adopted herein yields the high SNR of the sensor system. The proposed system can increase the reliability of FBG sensor systems for multipoint smart structures.

A simple self-restored fiber Bragg grating (FBG)-based passive sensing ring network

In this investigation, we propose and experimentally investigate a simple self-restored fiber Bragg grating (FBG)-based sensor ring system. This proposed multi-ring passive sensing architecture does not require active components in the network. In this experiment, the network survivability and capacity for the multi-point sensor systems are also enhanced. Besides, the tunable laser source (TLS) is adopted in a central office (CO) for FBG sensing. The survivability of an eight-point FBG sensor is examined and analyzed. It is cost effective since the sensing system is entirely centralized in the CO. Experimental results show that the proposed system can enhance the reliability of the FBG sensing network for large-scale and multi-point architecture.

Enhancement of FBG Multiplexing Capability Using a Spectral Tag Method

Multiplexing of fiber Bragg grating (FBG) sensors is one of the most effective technologies to reduce both installation and operation costs for quasi-distributive strain and temperature measurements such as smart structure applications. We propose a novel method of enhancing the multiplexing capability of a multipoint FBG sensor system without increasing system complexity by providing a unique spectral response as an identification tag to each FBG. The number of sensors in the proposed spectral tag method can increase as N(N-1)/2 as the number of spectral codes N increases at the expense of the free spectral range.

Self-Protection Multi-Ring-Architecture Fiber Sensing System

In this investigation, we propose and experimentally investigate a simply self-restored ring-based fiber Bragg grating (FBG) based sensor system. This proposed multi-ring passive sensing architecture is without any active components in the entire network. In this experiment, the network survivability and capacity for the multi-point sensor systems are also enhanced. Besides, the tunable laser source (TLS) is adopted in central office (CO) for FBG sensing. The survivability of a eight-point FBG sensor is examined and analyzed. Due to the passive sensor network, the cost-effective and intelligent sensing system is entirely centralized by CO. As a result, the experimental results show that the proposed system can assist the reliable FBG sensing network for a large-scale and multi-point architecture.

Star-Bus-Ring Architecture for Fiber Bragg Grating Sensors

A star-bus-ring architecture for fiber Bragg grating (FBG) sensors is proposed and demonstrated. The FBG survivability and capacity of a multipoint sensor system are enhanced by adding remote nodes and 2×2 optical switches to the star-bus-ring architecture. Moreover, to enhance the signal-to-noise ratio (SNR) of the sensor system, we adopt a FBG laser scheme in constructing our proposed star-bus-ring architecture. The fiber laser adopted in this system resulted in an SNR of more than 50 dB for the sensor system. Finally, the network survivability is experimentally verified.

Interrogation of multipoint optical fibre sensor signals based on artificial neural network pattern recognition techniques

An optical fibre multipoint sensor system incorporating multiple (3) U-bend sensors is presented which is capable of detecting contaminants in water. The sensors are based on 62.5 μm core diameter polymer clad silicone (PCS) fibre which has had its cladding removed in the sensing regions. The addressing of the fibre is achieved using an optical time domain reflectometer (OTDR) and is, thus, capable of spatially resolving power loss (along the fibre’s length). The signal analysis is performed using artificial neural networks (ANN) pattern recognition, which allows classification of the samples under test, thus, allowing the true measurand to be recognised. The system described is capable of both measurement at multiple points on a single fibre loop, and of recognising cross-sensitivity from interfering parameters such as lime scale coating in hard water and the presence of other species, e.g. alcohol in the water. Experimental results and the suitability of the ANN for their interpretation and classification are reported.

A novel fiber-laser-based sensor network with self-healing function

We present a novel fiber-laser-based sensor network with self-healing function and demonstrate its effectiveness. The network survivability and capacity for a multipoint sensor system are enhanced by adding switches in a self-healing ring architecture. The fiber laser adopted in this system is a linear-cavity fiber Bragg grating (FBG) laser leading to the signal-to-noise ratio over 52 dB for the sensor network. The network survivability of a ten-point FBG sensor is experimentally examined. The experimental results show that the proposed system can facilitate reliable sensing networks for a large-scale and multipoint smart structure.

A Universal Thermal Module™ for Clusterable RTP and MOCVD Applications

AbstractA Universal Thermal Module™ (UTM™) has been developed for vacuum-integrated cluster RTP and MOCVD as well as stand-alone atmospheric RTP applications. The UTM™ architecture provides highly modular RTP and MOCVD tool configurations for various single-wafer thermal processes. The UTM™ design comprises a temperature-controlled UHV-grade process chamber as well as an ultraclean gearless wafer rotation assembly for improved temperature uniformity and enhanced built-in reliability. The UTM™ RTP employs bottom/backside wafer heating using a multi-zone axisymmetric illuminator and a reflective multi-zone gas showerhead located above the wafer. Precision RTP control is achieved using a multi-zone controller in conjunction with a multipoint sensor system with real-time multi-zone compensations for wafer emissivity and illuminator light interference effects. The RTP temperature measurement and control techniques fully compensate for any axisymmetric or non-axisymmetric wafer emissivity patterns, eliminating the need for pre-RTP wafer backside conditioning. The UTM™ showerhead provides capabilities for ultraclean multi-zone gas injection and in-situ RF plasma for MOCVD and RTCVD processes. The UTM™ MOCVD module meets the most stringent specifications and tool parameters for various metallization and high-K dielectric deposition applications. This module has been used for deposition of low-resistivity copper films with excellent void-free sub-half-micron gap fill for high-performance multilevel interconnects. The UTM™ RTP and MOCVD modules have been implemented based on design optimizations in a virtual reactor environment.