Wireless Self-Powered Vibration Sensor System for Intelligent Spindle Monitoring

In recent years,high-end equipment is widely used in industry and the accuracy requirements of the equipment have been risen year by year.During the machining process,the high-end equipment failure may have a great impact on the product quality.It is necessary to monitor the status of equipment and to predict fault diagnosis.At present,most of the condition monitoring devices for mechanical equipment have problems of large size,low precision and low energy utilization.A wireless self-powered intelligent spindle vibration acceleration sensor system based on piezoelectric energy harvesting is proposed.Based on rotor sensing technology,a sensor is made to mount on the tool holder and build the related circuit.Firstly,the energy management module collects the mechanical energy in the environment and converts the piezoelectric vibration energy into electric energy to provide 3.3 Vfor the subsequent circuit.The lithium battery supplies the system with additional power and monitors’the power of the energy storage circuit in real-time.Secondly,a three-axis acceleration sensor is used to collect,analyze and filter a series of signal processing operations of the vibration signal in the environment.The signal is sent to the upper computer by wireless transmission.The host computer outputs the corresponding X,Y,and Z channel waveforms and data under the condition of the spindle speed of 50∼2500 r/min with real-time monitoring.The KEIL5 platform is used to develop the system software.The small-size piezoelectric vibration sensor with high-speed,high-energy utilization,high accuracy,and easy installation is used for spindle monitoring.The experiment results show that the sensor system is available and practical.

A DFB Fiber Laser Sensor System with Ultra-High Resolution and Its Noise Analysis

A distributed feedback fiber laser （DFB FL） sensor system with ultra-high resolution is described. The sensor is made by writing distributed feedback structures into a high gain active fiber, and the system employs an unbalanced Michelson interferometer to translate laser wavelength shifts induced by weak measurands into phase shifts. A digital phase generated carrier demodulation scheme is introduced to achieve ultra-high resolution interrogation. A detailed noise analysis of the system is presented, and it is shown that the system resolution is limited by the frequency noise of the DFB FL.

A 4-layer method of developing integrated sensor systems with LabVIEW

System integrity is important for fast and accurate measurement and control.LabVIEW is widely used in education and industry.Many LabVIEW codes are hard to be read and shown because of their 2D topology.In order to simplify the programming,a 4-layer model of developing sensor or measurement systems with LabVIEW is proposed in this paper.The purpose of this paper is to show the readers how to design simple,clear and strong automated systems with LabVIEW.Using a Sensirion SHT75 humidity sensor and an NI USB6008 DAQ board as an example,this paper describes the steps of developing a sensor system from the physical layer to application layer in detail.In layer 2,port selection and signal regulation are demonstrated.In layer 3,timing waveform analysis and synthesis,state diagram analysis,instruction set design,micro operation and fault tolerance designs are demonstrated.In layer 4,data visualization is covered with a vivid example.Programmers found it was hard to show readers their LabVIEW codes because many LabVIEW codes occupy several screens.A layer model simplifies the programming,so one is able to show a medium size LabVIEW code easily.

Multifunctional Flexible Humidity Sensor Systems Towards Noncontact Wearable Electronics

In the past decade,the global industry and research attentions on intelligent skin-like electronics have boosted their applications in diverse fields including human healthcare,Internet of Things,human–machine interfaces,artificial intelligence and soft robotics.Among them,flexible humidity sensors play a vital role in noncontact measurements relying on the unique property of rapid response to humidity change.This work presents an overview of recent advances in flexible humidity sensors using various active functional materials for contactless monitoring.Four categories of humidity sensors are highlighted based on resistive,capacitive,impedance-type and voltage-type working mechanisms.Furthermore,typical strategies including chemical doping,structural design and Joule heating are introduced to enhance the performance of humidity sensors.Drawing on the noncontact perception capability,human/plant healthcare management,human-machine interactions as well as integrated humidity sensor-based feedback systems are presented.The burgeoning innovations in this research field will benefit human society,especially during the COVID-19 epidemic,where cross-infection should be averted and contactless sensation is highly desired.

Data Fusion in Distributed Multi-sensor System

This paper presents a data fusion method in distributed multi-sensor system including GPS and INS sensors’ data processing. First, a residual χ 2 \|test strategy with the corresponding algorithm is designed. Then a coefficient matrices calculation method of the information sharing principle is derived. Finally, the federated Kalman filter is used to combine these independent, parallel, real\|time data. A pseudolite (PL) simulation example is given.

Recent Advances in Long-distance FBG Sensor Systems at UESTC

Recent progress in long-distance in-Fiber Bragg Grating （FBG） sensor systems at University of Electronic Science ＆ Technology of China （UESTC） is reviewed in this paper. Two novel approaches with a 50km transmission distance are proposed and demonstrated. The first one is based on the combination of bidirectional Raman amplification and a dual Erbium-Doped Fiber （EDF） configuration. A good Signal-to-Noise Ratio （SNR） of ～16dB is achieved with only a pump power of ～280 mW, which is ～10 dB higher than that without amplification. The second is based on a novel tunable fiber ring laser configuration with hybrid Raman/EDFA configuration. Experimental results show that an excellent optical SNR of-～60 dB has been achieved for a 50 km transmission distance with a low Raman pump power of ～170 mW and a low EDFA pump power of～40 mW at wavelength of 980 nm. It is anticipated that these long-distance FBG sensing systems could find important applications in health monitoring of large infra-structures, such as oil or gas pipelines, ultra-long bridges and tunnels, river banks, and so on.

Multi-functional optical fiber sensor system based on a dense wavelength division multiplexer

We propose a novel and efficient multi-functional optical fiber sensor system based on a dense wavelength division multiplexer(DWDM).This system consists of an optical fiber temperature sensor, an optical fiber strain sensor, and a 48-channel DWDM.This system can monitor temperature and strain changes at the same time.The ranges of these two sensors are from-20℃ to 100℃ and from-1000 με to 2000 με, respectively.The sensitivities of the temperature sensor and strain sensor are 0.03572 nm/℃ and 0.03808 nm/N, respectively.With the aid of a broadband source and spectrometer,different kinds and ranges of parameters in the environment can be monitored by using suitable sensors.

Blood Glucose Sensor Systems for Elderly People

Electrochemical blood glucose sensors were developed with use of enzymes and an electron mediator.Electrodes were patterned on a resin plate,and a reagent layer containing an enzyme and an electron mediator was disposed on the electrodes in a dried state.A sample chamber to which the soluble reagent layer was exposed was assembled with the enzyme-loaded electrodes to hold a certain volume of blood in the sensor.The fabricated sensors enabled rapid and precise measurements of blood glucose of oneself.The sensor systems combined with the customized hand-held meter especially for the sensor were maintenance-free chiefly due to disposable sensors,and would be simple and easy enough to be operated by elderly people.

The research of optical windows used in aircraft sensor systems

The optical windows used in aircrafts protect their imaging sensors from environmental effects. Considering the imaging performance, flat surfaces are traditionally used in the design of optical windows. For aircrafts operating at high speeds, the optical windows should be relatively aerodynamic, but a flat optical window may introduce unacceptably high drag to the airframes. The linear scanning infrared sensors used in aircrafts with, respectively, a flat window, a spherical window and a toric window in front of the aircraft sensors are designed and compared. Simulation results show that the optical design using a toric surface has the integrated advantages of field of regard, aerodynamic drag, narcissus effect, and imaging performance, so the optical window with a toric surface is demonstrated to be suited for this application.

Hardware Design for Low Power Integrated Sensor System

An integrated sensor system is implemented using inter-integrated circuit mode (I2C) software, utilizing the PIC182585 MPLAB embedded control system utilizing hardware. The hardware implementation features high level of integration, reliability, high precision, and high speed communications. The system was demonstrated by temperature and CO2 sensors. An extension for Zigbee system is proposed to enhance the security of the integrated system. A bi-directional air/liquid flow sensor is also added to detect the flow magnitude and direction that can be applied to heating, ventilating, and air-conditioning (HVAC), local and national security within subway systems, and medical equipment. The hardware design of the flow sensor included one heating element and two sensing elements to detect the bi-directional flow. Platinum sensors were found to be of high sensitivity and linear characteristics within 0℃ to 100℃ range, and their high temperature coefficient (0.00385 Ω/Ω/℃). Polyimide thin film heater was used as the heating element due to its high throughput and good thermal efficiency. Two bridge circuits were also designed to sense the temperature distribution in the vicinity of the sensing elements. Three high precision instrumentation low power amplifiers with offset voltage ~2.5 μV (50 μV max) were used for the overall design. The system security is also enhanced with the detection of poison gas using Carbon Nanotube devices (CNT). An antenna system was designed, and a frequency shift was detected to designate the type of poison gas used for a general threat.

Studies on Non-potentiometric Piezoelectric Sensor System for Determination of Vitamin B_1

A piezoelectric sensor responsive to vitamin B 1 was fabricated based on the vitamin B 1 tetraphenylborate ion pair. The general performance characteristics of the sensor are presented here. The proposed sensor showed a wide working pH range, a good sensitivity and selectivity. The response range is between 1 0×10 -7 -4 9×10 -5 mol/L with a detection limit of 8×10 -8 mol/L at pH 4 0. The selectivity should be attributed to the preferential adsorption of the component ion on the membrane/solution interface. The adsorption behavior of vitamin B 1 on the crystal surface was investigated with a quartz crystal impedance(QCI) system.

Modeling and identification for soft sensor systems based on the separation of multi-dynamic and static characteristics

Data-driven soft sensor is an effective solution to provide rapid and reliable estimations for key quality variables online. The secondary variables affect the primary variable in considerably different speed, and soft sensor systems exhibit multi-dynamic characteristics. Thus, the first contribution is improving the model in the previous study with multi-time-constant. The characteristics-separation-based model will be identified in substep way,and the stochastic Newton recursive(SNR) algorithm is adopted. Considering the dual-rate characteristics of soft sensor systems, the proposed model cannot be identified directly. Thus, two auxiliary models are first proposed to offer the intersample estimations at each update period, based on which the improved algorithm(DAM-SNR) is derived. These two auxiliary models function in switching mechanism which has been illustrated in detail. This algorithm serves for the identification of the proposed model together with the SNR algorithm, and the identification procedure is then presented. Finally, the laboratorial case confirms the effectiveness of the proposed soft sensor model and the algorithms.

A Dual-Parameter Fusion Distributed Optical Fiber Sensor System for Oil and Gas Pipeline Monitoring

For oil and gas pipeline monitoring applications, this paper proposed a dual-parameter fusion distributed fiber optic sensor system that enables distributed temperature and distributed vibration measurements in a single fiber. Through the fiber-scattering spectrum time domain detection combined with coded pulse sequence and Raman scattering spectrum is obtained, which realizes high-resolution temperature measurement and wide-band vibrational wave measurement. The experimental results show that, on 10 km optical fiber measurement, temperature resolution up to 0.1?C and vibration response frequency range 20 Hz - 5 kHz. This sensing system achieves temperature and vibration dual-parameter measurements with fiber optics, greatly simplifying the system and facilitating installation and it can be widely used in oil and gas pipeline monitoring.

Implementation of Machine Learning Classification Regarding Hemiplegic Gait Using an Assortment of Machine Learning Algorithms with Quantification from Conformal Wearable and Wireless Inertial Sensor System

The quantification of gait is uniquely facilitated through the conformal wearable and wireless inertial sensor system, which consists of a profile comparable to a bandage. These attributes advance the ability to quantify hemiplegic gait in consideration of the hemiplegic affected leg and unaffected leg. The recorded inertial sensor data, which is inclusive of the gyroscope signal, can be readily transmitted by wireless means to a secure Cloud. Incorporating Python to automate the post-processing of the gyroscope signal data can enable the development of a feature set suitable for a machine learning platform, such as the Waikato Environment for Knowledge Analysis (WEKA). An assortment of machine learning algorithms, such as the multilayer perceptron neural network, J48 decision tree, random forest, K-nearest neighbors, logistic regression, and na&#239ve Bayes, were evaluated in terms of classification accuracy and time to develop the machine learning model. The K-nearest neighbors achieved optimal performance based on classification accuracy achieved for differentiating between the hemiplegic affected leg and unaffected leg for gait and the time to establish the machine learning model. The achievements of this research endeavor demonstrate the utility of amalgamating the conformal wearable and wireless inertial sensor with machine learning algorithms for distinguishing the hemiplegic affected leg and unaffected leg during gait.

Observer-based dynamic event-triggered control for distributed parameter systems over mobile sensor-plus-actuator networks

We develop a policy of observer-based dynamic event-triggered state feedback control for distributed parameter systems over a mobile sensor-plus-actuator network.It is assumed that the mobile sensing devices that provide spatially averaged state measurements can be used to improve state estimation in the network.For the purpose of decreasing the update frequency of controller and unnecessary sampled data transmission, an efficient dynamic event-triggered control policy is constructed.In an event-triggered system, when an error signal exceeds a specified time-varying threshold, it indicates the occurrence of a typical event.The global asymptotic stability of the event-triggered closed-loop system and the boundedness of the minimum inter-event time can be guaranteed.Based on the linear quadratic optimal regulator, the actuator selects the optimal displacement only when an event occurs.A simulation example is finally used to verify that the effectiveness of such a control strategy can enhance the system performance.

Hybrid pedestrian positioning system using wearable inertial sensors and ultrasonic ranging

Pedestrian positioning system(PPS)using wearable inertial sensors has wide applications towards various emerging fields such as smart healthcare,emergency rescue,soldier positioning,etc.The performance of traditional PPS is limited by the cumulative error of inertial sensors,complex motion modes of pedestrians,and the low robustness of the multi-sensor collaboration structure.This paper presents a hybrid pedestrian positioning system using the combination of wearable inertial sensors and ultrasonic ranging(H-PPS).A robust two nodes integration structure is developed to adaptively combine the motion data acquired from the single waist-mounted and foot-mounted node,and enhanced by a novel ellipsoid constraint model.In addition,a deep-learning-based walking speed estimator is proposed by considering all the motion features provided by different nodes,which effectively reduces the cumulative error originating from inertial sensors.Finally,a comprehensive data and model dual-driven model is presented to effectively combine the motion data provided by different sensor nodes and walking speed estimator,and multi-level constraints are extracted to further improve the performance of the overall system.Experimental results indicate that the proposed H-PPS significantly improves the performance of the single PPS and outperforms existing algorithms in accuracy index under complex indoor scenarios.

Design and application of thickness measurement calibration system based on laser displacement sensor

This study aims to improve the accuracy and safety of steel plate thickness calibration.A differential noncontact thickness measurement calibration system based on laser displacement sensors was designed to address the problems of low precision of traditional contact thickness gauges and radiation risks of radiation-based thickness gauges.First,the measurement method and measurement structure of the thickness calibration system were introduced.Then,the hardware circuit of the thickness system was established based on the STM32 core chip.Finally,the system software was designed to implement system control to filter algorithms and human-computer interaction.Experiments have proven the excellent performance of the differential noncontact thickness measurement calibration system based on laser displacement sensors,which not only considerably improves measurement accuracy but also effectively reduces safety risks during the measurement process.The system offers guiding significance and application value in the field of steel plate production and processing.

Actuator and sensor fault isolation in a class of nonlinear dynamical systems

Fault isolation in dynamical systems is a challenging task due to modeling uncertainty and measurement noise,interactive effects of multiple faults and fault propagation.This paper proposes a unified approach for isolation of multiple actuator or sensor faults in a class of nonlinear uncertain dynamical systems.Actuator and sensor fault isolation are accomplished in two independent modules,that monitor the system and are able to isolate the potential faulty actuator(s)or sensor(s).For the sensor fault isolation(SFI)case,a module is designed which monitors the system and utilizes an adaptive isolation threshold on the output residuals computed via a nonlinear estimation scheme that allows the isolation of single/multiple faulty sensor(s).For the actuator fault isolation(AFI)case,a second module is designed,which utilizes a learning-based scheme for adaptive approximation of faulty actuator(s)and,based on a reasoning decision logic and suitably designed AFI thresholds,the faulty actuator(s)set can be determined.The effectiveness of the proposed fault isolation approach developed in this paper is demonstrated through a simulation example.

Distributed fault diagnosis observer for multi-agent system against actuator and sensor faults

Component failures can cause multi-agent system(MAS)performance degradation and even disasters,which provokes the demand of the fault diagnosis method.A distributed sliding mode observer-based fault diagnosis method for MAS is developed in presence of actuator and sensor faults.Firstly,the actuator and sensor faults are extended to the system state,and the system is transformed into a descriptor system form.Then,a sliding mode-based distributed unknown input observer is proposed to estimate the extended state.Furthermore,adaptive laws are introduced to adjust the observer parameters.Finally,the effectiveness of the proposed method is demonstrated with numerical simulations.