Sensor System For Monitoring Research Articles

On improved fail-safe sensor distributions for a structural health monitoring system

Abstract Sensor placement optimization (SPO) is usually applied during the structural health monitoring sensor system design process to collect effective data. However, the failure of a sensor may significantly affect the expected performance of the entire system. Therefore, it is necessary to study the optimal sensor placement considering the possibility of sensor failure. In this article, the research focusses on an SPO giving a fail-safe sensor distribution, whose sub-distributions still have good performance. The performance of the fail-safe sensor distribution with multiple sensors placed in the same position will also be studied. The adopted data sets include the mode shapes and corresponding labels of structural states from a series of tests on a glider wing. A genetic algorithm is used to search for sensor deployments, and the partial results are validated by an exhaustive search. Two types of optimization objectives are investigated, one for modal identification and the other for damage identification. The results show that the proposed fail-safe sensor optimization method is beneficial for balancing the system performance before and after sensor failure.

Study on pressure relief effect of upper protective coal seam mining based on distributed optical fiber sensing monitoring

On site real-time monitoring of protective layer mining is an important method to deeply study its pressure relief mechanism. It is proposed that the distributed optical fiber sensing technology (BOTDA) based on Brillouin optical time domain analysis is used to conduct mining industry tests on the deformation law and pressure relief effect of the underlying coal and rock mass during the mining of the upper protective layer. Taking the 21,104 comprehensive mechanized working face of Hulusu Coal Mine as an example, the strain transmission relationship between the coal and rock mass and the force-bearing optical fiber sensor is analyzed, and the design scheme, implantation scheme and installation process of the optical fiber sensor monitoring system are introduced. Implemented the accuracy analysis of the optical fiber sensing monitoring system and the spatial positioning of the sensors. According to the mining progress of the working face, the optical fiber sensing monitoring system regularly collects data, and by analyzing the strain distribution characteristics of the sensing optical cable and its dynamic change process, the deformation law of the underlying coal and rock mass in the mining of the upper protective layer is obtained. The monitoring results show that the underlying coal and rock mass undergoes a dynamic process of compressive strain increase, tensile strain increase and tensile strain recovery during the mining of the upper protective layer, and the scale of increase and decrease of strain of coal and rock mass at different depths are different; The intensity of coal rock deformation and pressure relief effect are characterized by the fluctuation amplitude of optical fiber strain increment. The pressure relief process can be divided into three stages: the pressure relief start stage is 40.8 m, the pressure relief active stage is 68.3 m, and the pressure relief decline stage; Finally, the strike pressure relief angle of the upper protective layer mining is 58.7°, the inclined pressure relief angle is 63.6°, the pressure relief lag distance is 14.2 m, and the maximum vertical distance of pressure relief is 28.4 m. The research shows that the application of BOTDA distributed optical fiber sensing technology in monitoring the pressure relief effect of protective layer mining can provide a reliable basis for coal mine safety mining.

Batteryless, Miniaturized Implantable Glucose Sensor Using a Fluorescent Hydrogel.

We propose a biomedical sensor system for continuous monitoring of glucose concentration. Despite recent advances in implantable biomedical devices, mm sized devices have yet to be developed due to the power limitation of the device in a tissue. We here present a mm sized wireless system with backscattered frequency-modulation communication that enables a low-power operation to read the glucose level from a fluorescent hydrogel sensor. The configuration of the reader structure is optimized for an efficient wireless power transfer and data communication, miniaturizing the entire implantable device to 3 × 6 mm size. The operation distance between the reader and the implantable device reaches 2 mm with a transmission power of 33 dBm. We demonstrate that the frequency of backscattered signals changes according to the light intensity of the fluorescent glucose sensor. We envision that the present wireless interface can be applied to other fluorescence-based biosensors to make them highly comfortable, biocompatible, and stable within a body.

Sistem Monitoring Jaringan Sensor Node Berbasis Protokol MQTT

In this study, the implementation of a sensor node monitoring system based on the MQTT protocolis presented. The sensor node is made using the NodeMCU ESP8266 which is connected to thesensor to measure temperature, humidity, gas levels, and the presence of fire. Nodered is used tobuild a monitoring system. In this study, four connected sensor nodes were used. The MQTTprotocol is implemented on both sides of the sensor node and monitoring system. The sensor nodewill act as a publisher and the monitoring system will act as a subscriber. The sensor dataobtained will be sent to the monitoring system using the MQTT protocol. The test results showedthat the MQTT protocol was successfully implemented. Data from all sensor nodes can bedisplayed on the monitoring system

A contextual sensor system for non-intrusive machine status and energy monitoring

Event-driven contexts in manufacturing occur pervasively as a result of interactions among involved entities such as machines, workers, materials, and environment. One of the primary tasks in smart manufacturing is to derive a context-aware system conveniently incorporating worker knowledge for generating timely actionable intelligence for workers on factory floor and supervisors to respond. In this paper, we propose to design a human-and-machine interaction recognition framework by using a causality concept to collect contextual data for classifications of normal and abnormal machine operations. The causes and effects are between workers and machines for this initial research. To apply the causality to recognize worker interactions, initially a reliable way to identify the states of machines is necessary. The proposed contextual sensor system, consisting of a power meter for measuring machine operation conditions, a visual camera for capturing worker and machine interactions via a finite state machine model, and an algorithm for determining power signatures of individual components via energy disaggregation is implemented on semiconductor fabrication machines (manual or PLC controlled) each with multiple components. The experiment results demonstrate its context extraction capability such as components states and their corresponding energy usage in real time as well as its ability to identify anomalous operation conditions.

Flexible wireless pH sensor system for fish monitoring

It is necessary and important to develop a simple, accurate, stable, and low-cost quality detection sensor for ensuring the quality of the fish. This paper aims to develop a flexible wireless pH sensor system to detect the freshness of fish. The pH sensor system consists of an indium tin oxide (ITO) electrode, an Ag/AgCl reference electrode, a computing adder, and a wireless communication module. The operational amplifier addition circuit raises the overall potential signal collected by the pH electrode and sends it to the wireless reader from the sensor tag. The sensitivity of the pH electrode is −50.974 mV/pH, and other properties of the electrode, such as reproducibility and response times, are excellent. This paper uses a flexible wireless pH sensor system to continuously monitor fish meat stored at 28 °C for 36 h. The experimental results show that the pH of the fish tissue solution changes with the quality of the fish, and the flexible wireless pH sensor system can achieve accuracy, convenience, and long-term wireless food quality inspection.

A study on network analysis by navigation of robots using graphical measures to solve the complexity

In this paper, we present a graph theoretical analysis of a procedure for maintaining communication for tasks such as monitoring, identification, completion and productivity, where connectivity between the components involved in the task is required for conditional alertness. We present graphical measures and fuzzy theoretical tools to analyse the communication between the components in a network undergoing different tasks and accumulate a suitable information regarding the activities of the components by observing through sensor monitoring system. Also, we consider the efficiency of the robots in the monitoring system to control the position and orientation relative to other components to sustain communication links.

Efficient Mining of Frequent Item Sets on Large Uncertain Databases

In applications like location-based services, sensor monitoring systems and data integration diligence the data manipulated is highly ambiguous. mining manifold itemsets from generous ambiguous database illustrated under possible world semantics is a crucial dispute. Mining manifold Itemsets is technically brave because the ambiguous database can accommodate a fractional number of possible worlds. The mining process can be formed as a Poisson binomial distribution, by noticing that an Approximated algorithm is established to ascertain manifold Itemsets from generous ambiguous database exceedingly. Preserving the mining result of scaling a database is a substantial dispute when a new dataset is inserted in an existing database. In this paper, an incremental mining algorithm is adduced to retain the mining consequence. The cost and time are reduced by renovating the mining result rather than revising the whole algorithm on the new database from the scrap. We criticize the support for incremental mining and ascertainment of manifold Itemsets. Two common ambiguity models in the mining process are Tuple and Attribute ambiguity. Our approach reinforced both the tuple and attribute uncertainty. Our accession is authorized by interpreting both real and synthetic datasets.

Anvil state identification based on acceleration signals in ultrasonic metal welding of lithium batteries

Ultrasonic metal welding is a high-frequency vibration process that creates joints for components and has attracted extensive research attentions in recent years. Although this technology has been applied in many areas such as electronics, automotive, and aerospace, its wide adoption is still hindered by unsatisfactory welding quality. In such cases, performing process monitoring to enhance the welding quality is of great significance. In current literature, the exploration in monitoring and inspection of the ultrasonic welding process is still limited due to the ineffective offline monitoring and the lack of investigation of the anvil state impacts on welding results. To address this problem, an acceleration sensor monitoring system is proposed in this study aiming for enhancing the welding quality. In the established system, the acceleration signals are collected and decomposed by variational modal decomposition (VMD) to capture the characteristics of the intrinsic mode functions (IMFs) energy distributions. In addition, the particle swarm optimization (PSO) algorithm is adopted for penalty term selection while the system frequency and sampling rate are used for mode number determination. The proposed method is experimentally validated and suggests high effectiveness and robustness for anvil state identification in ultrasonic metal welding.

Zirconia Coatings as Efficient Soil Moisture Sensors for Water Irrigation

In agriculture sector, a soil moisture sensor plays a vital role in controlling the irrigation through the adequate and timely moisture of soil essential for the crop production. Owing to the chemically inert nature of zirconia, it is found to be a good material for soil moisture sensing. Therefore, the present study reports the synthesis of sol-gel based zirconia coatings and their application as efficient soil moisture sensor for water irrigation. For this purpose, zirconia was coated on 316L stainless steel substrate using zirconium propoxide precursor through sol-gel process and spin coating technique. The obtained zirconia coatings were used to fabricate and study the zirconia soil moisture sensors. Zirconia sensors were fabricated using zirconia coatings synthesized from various concentrations of zirconium precursor. The chemical structure and crystalline nature of zirconia coatings were analyzed using FTIR spectroscopy and X- ray diffractometer. Moreover, the contact angle and roughness of these coatings have been measured. It is observed that the contact angles and roughness of the synthesized zirconia coatings increased with increase in the precursor concentrations. All zirconia coatings manifested the tetragonal crystal structure. The resistance of the zirconia soil moisture sensors was measured for different moisture content in soil (%). The zirconia sensors are tested in an active black soil moisture condition and their resistances changed for the soil moisture range of 20 to 50%. Further, zirconia soil moisture sensor monitoring system was developed using NImyDAQ and LabVIEW which is useful for the water irrigation.

Performance of Aether Low-Cost Sensor Device for Air Pollution Measurements in Urban Environments. Accuracy Evaluation Applying the Air Quality Index (AQI)

Significant portions of European cities’ population are still exposed to levels of air pollution deemed harmful by the World Health Organization. Given the high impact of air pollution both on human health and the economy, numerous low-cost electrochemical sensor monitoring systems are being installed. The market is forced to develop new air quality monitoring systems to meet the needs of providing forecasting services based on advanced technologies and protocols that utilize certain characteristics such as high accuracy, real-time monitoring, daily and yearly statistics, data access from both experts and simple users with the use of low-cost equipment. In this study, conducted in Athens, Greece, a comparison is attempted between the findings from a low-cost electrochemical sensor device and those of a static, fixed site measurement monitoring station; this comparison is based on the data quality and Air Quality Index (AQI) concerning data accuracy and quality on adverse health effects due to air pollution. With regard to the prediction of different AQI intervals, TPR ranges from 35.2% up to 100.0%, FPR from 0.0% up to 36.1% and FNR from 0.0% up to 38.1%. The outcome of this study reveals flexible and affordable alternatives adopted during the evaluation and calibration of low-cost gas sensors for monitoring.

Uniform stress distribution road piezoelectric generator with free-fixed-end type central strike mechanism

A self-powered energy harvester for real roads to predict and detect black ice formation and pinpoint dangerous road sections was developed. An open-type piezoelectric device was developed for a high-efficiency module to achieve uniform stress distribution for enhanced energy harvesting performance by free-fixed-end type central strike mechanism. The output performance of the open-type device was 80% higher than that of the closed-type device. A uniform stress distribution road piezoelectric generator (URPG) with 120 open-type devices was installed on real roads. The URPG showed output power performance of up to 2.38 mW/cm3 when a vehicle passed once under the condition of being buried 2.5 cm below the road surface. The URPG can operate a wireless temperature sensor monitoring system for 83 s and charge a cellphone battery for 53 s. The developed self-powered energy harvesters can be used to reduce accidents caused by black ice on real roads.

Monitoring System for Railway Automation Devices Based on the Industrial Internet of Things

The features of monitoring systems for railway infrastructure and rolling stock are considered. The main approaches to organisation of monitoring of railway infrastructure and rolling stock objects are described, their advantages and disadvantages are noted. The main objective of this work is to present to the reader a conceptual vision of a system for monitoring devices and systems for ensuring train traffic safety, using technologies for transmitting diagnostic information over a radio channel. The methods of the theory of technical diagnostics and monitoring were used. Attention is focused on the use of wireless data transmission technologies and the use of autonomous industrial automation sensors for monitoring systems for railway automation devices.The architecture of the monitoring system is presented. The description of the system itself and the monitoring technology is given, the main advantages of the presented approach are noted, which, first, are linked to reduction of the volume of design work and of energy consumption of the system as a whole. The disadvantages are associated with the need to replace autonomous power supply sources, ensure security of the data transmission network, to proceed with periodic verification and calibration of measuring instruments. The basic diagrams of connecting sensors for measuring physical quantities to the circuit units of railway automation are presented. A list of parameters necessary for high-quality and effective monitoring of railway automation devices is given. The need is noted for both the control of mechanical and geometric parameters of devices and the accounting of data from interconnected objects of railway infrastructure and rolling stock. The proposed approach can find its application in the field of railway automation and, first of all, at those facilities that are located in premises with limited area (e.g. at subway facilities).

Improving Workplace Services using a Facility Management Platform Sensors Monitoring

The aim of this paper is to develop an advanced sensor monitoring system and to correlate it with a Facility Management (FM) enterprise platform in order to support the facilities managers to make decisions regarding the use of space or the cancellation of reservations. For this purpose, a system of sensors consisting of two infrared sensors working in pairs and a sensor that measures the light intensity was developed, and ARCHIBUS was chosen as the FM platform.

A Sustainable Early Warning System Using Rolling Forecasts Based on ANN and Golden Ratio Optimization Methods to Accurately Predict Real-Time Water Levels and Flash Flood.

Remote monitoring sensor systems play a significant role in the evaluation and minimization of natural disasters and risk. This article presents a sustainable and real-time early warning system of sensors employed in flash flood prediction by using a rolling forecast model based on Artificial Neural Network (ANN) and Golden Ratio Optimization (GROM) methods. This Early Flood Warning System (EFWS) aims to support decision makers by providing reliable and accurate information and warning about any possible flood events within an efficient lead-time to reduce any damages due to flash floods. In this work, to improve the performance of the EFWS, an ANN forecast model based on a new optimization method, GROM, is developed and compared to the traditional ANN model. Furthermore, due to the lack of literature regarding the optimal ANN structural model for forecasting the flash flood, this paper is one of the first extensive investigations into the impact of using different exogenous variables and parameters on the ANN structure. The effect of using a rolling forecast model compared to fixed model on the accuracy of the forecasts is investigated as well. The results indicate that the rolling ANN forecast model based on GROM successfully improved the model accuracy by 40% compared to the traditional ANN model and by 93.5% compared to the fixed forecast model.

Quantitative Monitoring of Bolt Looseness Using Multichannel Piezoelectric Active Sensing and CBAM-Based Convolutional Neural Network

The bolted connection is widely utilized in engineering to practically and rigidly couple structural components. The integrity of the connection is paramount to the safety of the structure and has prompted the development of many monitoring methods, including the piezoelectricity-based active sensing method. However, the active sensing method cannot quantify bolt looseness due to the unclear relationship between bolt looseness and the single monitoring index typically used in the active sensing method. Thus, the authors propose the unique combination of a one-dimensional convolutional neural network (1DCNN) and multichannel active sensing for quantitative monitoring of bolted connections. In an experiment, piezoelectric ceramic transducer (PZT) patches are bonded on steel plates connected by a bolt. Each patch is wired to a multichannel active sensing monitoring system. After obtaining multichannel stress wave signals at different looseness levels, a looseness vector is calculated to generate training and validation datasets. A baseline 1DCNN model and a novel model improved using the convolutional block attention module (CBAM) are used to monitor the bolt looseness. Finally, the authors verify that the multichannel active sensing method combined with the 1DCNN model can accurately perform quantitative monitoring of bolt looseness, and the monitoring accuracy of the baseline 1DCNN model is above 91.07% in three different specimens. Compared with the baseline 1DCNN model, the monitoring accuracy of the CBAMCNN model improved by approximately 5%. Overall, the method proposed in this article offers a new and highly accurate approach for quantitative monitoring of bolted connections.

A Prototype Unit of a Distributed Sensor System for Ecological Monitoring

Introduction. In this article, the basic principles of ecological monitoring were considered, and the possibilities of constructing sensor systems were analysed. It was proposed to use the NB-IoT low-energy telecommunication standard as a basic wireless protocol for ecological system development, which ensures effective communication of network devices. A prototype of the system was constructed, and algorithms for receiving and transmitting signals were simulated.Aim. To construct a prototype of a transceiver based on the NB-IoT standard and perform its simulation. To utilize digital twin in MatLab to create the proposed system.Materials and methods. The prototype was constructed using the Xilinx Zedboard evaluation board and transceiver on AD9361 chip, and the simulation was performed using the MatLab 2010 software package.Results. The results of the simulation in the channel with the additive white Gaussian noise (AWGN) were obtained, and the level of the detected synchronization signals of the NB-IoT standard was determined. The receiver and transmitter of the NB-IoT standard were implemented on the Xilinx Zedboard evaluation board. The timing simulation results show that the designed system can be tested in a real environment. The power consumption and resource utilization of the constructed wireless sensor network prototype unit were determined. Conclusion. The results obtained via the simulation process show that the designed prototype of the communication system works correctly, and the produced signal meets all the requirements of the NB-IoT standard. The results can be used for creating a domestic manufactured, specialized integrated chip for data units of ecological monitoring systems.

A Simple Sensor System for Onsite Monitoring of O2 in Vacuum-Packed Meats during the Shelf Life.

Vacuum packaging (VP) is used to reduce exposure of retail meat samples to ambient oxygen (O2) and preserve their quality. A simple sensor system produced from commercial components is described, which allows for non-destructive monitoring of the O2 concentration in VP raw meat samples. Disposable O2 sensor inserts were produced by spotting small aliquots of the cocktail of the Pt–benzoporphyrin dye and polystyrene in ethyl acetate onto pieces of a PVDF membrane and allowing them to air-dry. These sensor dots were placed on top of the beef cuts and vacuum-packed. A handheld reader, FirestinGO2, was used to read nondestructively the sensor phase shift signals (dphi°) and relate them to the O2 levels in packs (kPa or %). The system was validated under industrial settings at a meat processing plant to monitor O2 in VP meat over nine weeks of shelf life storage. The dphi° readings from individual batch-calibrated sensors were converted into the O2 concentration by applying the following calibration equation: O2 (%) = 0.034 * dphi°2 − 3.413 * dphi° + 85.02. In the VP meat samples, the O2 levels were seen to range between 0.12% and 0.27%, with the sensor dphi signals ranging from 44.03° to 56.02°. The DIY sensor system demonstrated ease of use on-site, fast measurement time, high sample throughput, low cost and flexibility.

Railway overhead contact wire monitoring system by means of FBG sensors

Safety of infrastructures represents one of the most significant concerns for governments and service providers to preserve people's well-being. One of the main ways to keep in safe facilities (buildings, bridges, railways, etc.) involves the use of monitoring sensor systems in charge of measuring critical operating conditions. Those measurements together with periodical maintenance, contribute to minimize potential risks that the infrastructure faces. The paper aims at designing, developing, and testing a monitoring system for mechanical stresses acting on the overhead contact wire (OCW) to ensure the operational safety of the railway network. In this regard, the paper proposes two Fiber Bragg Grating (FBG) sensors-based solutions, relying on the ability of these sensors to allow real-time and continuous data acquisition. The first one consists in a polyimide-coated sensor bonded on an OCW clamp, the second one is a copper-coated sensor hanging between the two separated halves of an OCW clamp. Significant results have been obtained mechanically testing both solutions, trying to simulate the operative conditions.

AUTOMATED SENSORY MONITORING SYSTEM PROTOTYPE FOR CONTINUOUS MONITORING OF MATERIAL AND STRUCTURE STATE

The goal of this article is to solve problems of automated monitoring systems of industrial and aviation constructions. Based on the latest research results, the most cost-effective solutions are covered, and a practical solution is offered. This article is part of the scientific project “Development of an integrated sensor system for material and structure monitoring”. The article describes the problem and suggests a practical solution for an integrated sensor system for material and structure monitoring prototype.