Sistem monitoring kemiringan gedung berbasis resistor variabel

Sistem deteksi kemiringan gedung bertingkat dibuat mengguanakan resistor variabel yang dipasang bandul sebagai sensor. Bandul selalu menghadap ke bawah karena adanya gaya gravitasi. Gaya gravitasi berfungsi sebagai torsi untuk merubah resistansi resistor variabel. Resistor variabel disusun menjadi rangkaian pembagi tegangan supaya perubahan resistansinya berubah menjadi perubahan beda potensial yang dapat dibaca oleh arduino. untuk meningkatkan sensitivitasnya, resistor variabel dipasang pada sebuah gear kecil dan bandul gear besar. Kemudian kedua gear disinggungkan. Sensor dibuat sebanyak 2 buah untuk mendeteksi perubahan kemiringan terhadap sumbu x dan sumbu y. Hasil yang didaptkan yaitu sistem deteksi kemiringan gedung bertingkat dapat dibuat menggunakan resistor variabel. Sistem deteksi memiliki karakteristik yang baik dengan akurasi sebesar 89,34%, presisi 91,07%, eror 10,66%, dan waktu respon 4,125 detik. Sistem deteksi kemiringan dapat mendeteksi perubahan kemiringan sudut dan arahnya serta dapat memberikan peringatan dini setelah sudut yang terbaca melibihi 1,5°. Threshold yang dimiliki sistem adalah 0,17°.The tilt detection system of multi-storey buildings are made using a variable resistor mounted by the pendulum as a sensor. The pendulum always faces down because of the force of gravity. The force of gravity serves as the torque to change the resistance of the variable resistor. Variable resistors are arranged into a voltage divider circuit so that the transform in resistance turned into alteration in difference of potential, which can be read by Arduino. The increasing of sensitivity, a variable resistor is mounted on a small gear and a large gear pendulum. Then the two gears get contact. Two sensors are made to detect the alteration in the slope of the x axis and y axis. The result is the slope detection system of multi-storey buildings can be made using a variable resistor. The detection system has good characteristics with an acceleration of 89.34%, a precision of 91.07 % error of 10.66%, and a response time of 4.13 seconds. The tilt detection system can detect changes in tilt angel and direction and can provide an early warning after the angel reading exceeds 1,5°. The system threshold is 0.17

Quickest Change Detection of a Markov Process Across a Sensor Array

Recent attention in quickest change detection in the multi-sensor setting has been on the case where the densities of the observations change at the same instant at all the sensors due to the disruption. In this work, a more general scenario is considered where the change propagates across the sensors, and its propagation can be modeled as a Markov process. A centralized, Bayesian version of this problem, with a fusion center that has perfect information about the observations and a priori knowledge of the statistics of the change process, is considered. The problem of minimizing the average detection delay subject to false alarm constraints is formulated as a partially observable Markov decision process (POMDP). Insights into the structure of the optimal stopping rule are presented. In the limiting case of rare disruptions, we show that the structure of the optimal test reduces to thresholding the a posteriori probability of the hypothesis that no change has happened. We establish the asymptotic optimality (in the vanishing false alarm probability regime) of this threshold test under a certain condition on the Kullback-Leibler (K-L) divergence between the post- and the pre-change densities. In the special case of near-instantaneous change propagation across the sensors, this condition reduces to the mild condition that the K-L divergence be positive. Numerical studies show that this low complexity threshold test results in a substantial improvement in performance over naive tests such as a single-sensor test or a test that wrongly assumes that the change propagates instantaneously.Comment: 40 pages, 5 figures, Submitted to IEEE Trans. Inform. Theor

Optical fiber sensors for in-situ detection of solid-liquid phase change for n-octadecane

In the past few decades solid-liquid phase change materials (PCMs) have gained an increasingly important role in thermal energy storage applications due to their ability to absorb or release large amounts of energy during melting or solidification. The precise phase change temperature varies with different conditions, such as external pressure, small variations in the PCM composition in the case of multi-component mixtures and/or material purity. In order to achieve better energy efficiency for the energy storage process, it is necessary to be able to accurately detect the solid-liquid phase changes in the bulk of a PCM. Optical fiber sensors allow for direct detection of the phase changes in PCMs while also offering the advantages of a passive nature and small size. The focus of the research presented in this thesis is on the development of a novel approach to detecting the solid-liquid phase changes in selected PCMs using optical fiber sensors. To achieve this goal, initially the correlation between the temperature, changes in the refractive index (RI) and internal pressure acting upon the optical fiber during the phase transitions was studied for the selected PCM, n-octadecane. Based on the results of these studies, several optical fiber sensing structures have been proposed and demonstrated for the detection of phase changes as follows: An optical fiber Fresnel reflection sensor for detection of phase changes. An fiber Fresnel reflection sensor for detection of solid-liquid phase change in n-octadecane is proposed and experimentally demonstrated. The sensor probe consists of a single-mode fiber with a cleaved end immersed in the n-octadecane sample under test. The detection relies on measuring the slope of the output power ratio change which is caused by the RI change during the phase transition. The results of this work suggest that such a simple optical fiber sensor can be used for detection of liquid-solid phase changes in other materials with similar thermo-optic properties to n-octadecane. This sensor realized in-situ detection for a solid liquid phase change, which is a significant advantage compared to the traditional phase change detection methods. A fiber heterostructure based optical fiber sensor for detection of phase changes. A single-mode-no-core-single-mode fiber optical sensor for the detection of solid-liquid and liquid-solid phase changes in n-octadecane is proposed and demonstrated. The transmission-type sensor probe consists of a short section of no-core fiber sandwiched between two sections of a single-mode fiber. The detection relies on measuring the level of the output power ratio which is caused by the large step-like variations in the RI of n-octadecane’s. Importantly, compared to the Fresnel reflection sensor, the proposed fiber heterostructure is resistant to bending and strain disturbances during the measurements. The results of this work suggest that the proposed sensor is potentially capable of detecting liquid-solid phase changes in other materials whose thermo-optic properties are similar to those of n-octadecane. Moreover, this sensor not only has the advantage of achieving in-situ phase change detection, but also has the ability of working in an environment subjected to mechanical disturbance, which makes it has great potential of industry applications. Optical fiber Fabry-Perot sensor based on a singlemode-hollow core-singlemode fiber. An optical fiber Fabry-Perot sensor to monitor the solid-liquid and liquid-solid phase changes in n-octadecane is also proposed and investigated. The sensor probe is fabricated by splicing a short section of a hollow core fiber between two single-mode fibers. By analyzing the changes in the output spectrum of the probe, such as spectral shift of a selected interference dip, the phase change within a material sample in the vicinity of the fiber probe can be accurately detected. The proposed sensor can deal with PCM types whose RI values make it difficult for the other two sensor types to work, and also can be used for detection of the material’s phase state at a particular point of its volume. This work has the potential to better understanding phase change mechanism and its application in energy engineering. Compared to the other sensors developed in the research presented in this thesis, this sensor has the advantage that the application is not limited by the RI of the PCMs

Investigating rock mass failure precursors using a multi-sensor monitoring system. Preliminary results from a test-site (Acuto, Italy)

In the last few years, several approaches and methods have been proposed to improve early warning systems for managing risks due to rapid slope failures where important infrastructures are the main exposed elements. To this aim, a multi-sensor monitoring system has been installed in an abandoned quarry at Acuto (central Italy) to realise a natural-scale test site for detecting rock-falls from a cliff slope. The installed multi-sensor monitoring system consists of: i) two weather stations; ii) optical cam (Smart Camera) connected to an Artificial Intelligence (AI) system; iii) stress- strain geotechnical system; iv) seismic monitoring device and nano-seismic array for detecting microseismic events on the cliff slope. The main objective of the experiment at this test site is to investigate precursors of rock mass failures by coupling remote and local sensors. The integrated monitoring system is devoted to record strain rates of rock mass joints, capturing their variations as an effect of forcing actions, which are the temperature, the rainfalls and the wind velocity and direction. The preliminary tests demonstrate that the data analysis methods allowed the identification of external destabilizing actions responsible for strain effects on rock joints. More in particular, it was observed that the temperature variations play a significant role for detectable strains of rock mass joints. The preliminary results obtained so far encourage further experiments

INVESTIGATION OF DEFORESTATION USING MULTI-SENSOR SATELLITE TIME SERIES DATA IN NORTH KOREA

Department of Urban and Environmental Engineering(Environmental Science and Engineering)North Korea is very vulnerable to natural disasters such as floods and landslides due to institutional, technological, and other various reasons. Recently, the damage has been more severe and vulnerability is also increased because of continued deforestation. However, due to political constraints, such disasters and forest degradation have not been properly monitored. Therefore, using remote sensing based satellite imagery for forest related research of North Korea is regarded as currently the only and most effective method. Especially, machine learning has been widely used in various classification studies as a useful technique for classification and analysis using satellite images. The aim of this study was to improve the accuracy of forest cover classification in the North Korea, which cannot be accessed by using random forest model. Indeed, another goal of this study was to analyze the change pattern of denuded forest land in various ways. The study area is Musan-gun, which is known to have abundant forests in North Korea, with mountainous areas accounting for more than 90%. However, the area has experienced serious environmental problems due to the recent rapid deforestation. For example, experts say that the damage caused by floods in September 2016 has become more serious because denuded forest land has increased sharply in there and such pattern appeared even in the high altitude areas. And this led the mountain could not function properly in the flood event. This study was carried out by selecting two study periods, the base year and the test year. To understand the pattern of change in the denuded forest land, the time difference between the two periods was set at about 10 years. For the base year, Landsat 5 imageries were applied, and Landsat 8 and RapidEye imageries were applied in the test year. Then the random forest machine learning was carried out using randomly extracted sample points from the study area and various input variables derived from the used satellite imageries. Finally, the land cover classification map for each period was generated through this random forest model. In addition, the distribution of forest changing area to cropland, grassland, and bare-soil were estimated to the denuded forest land. According to the study results, this method showed high accuracy in forest classification, also the method has been effective in analyzing the change detection of denuded forest land in North Korea for about 10 years.ope

Development of miniature all-solid-state potentiometric sensing system

A procedure for the development of a pen-like, multi-electrode potentiometric sensing platform is described. The platform comprises a seven-in-one electrode incorporating all-solid-state ion-selective and reference electrodes based on the conductive polymer (poly(3,4-ethylenedioxythiophene) (PEDOT)) as an intermediate layer between the contacts and ion-selective membranes. The ion-selective electrodes are based on traditional, ionophore-based membranes, while the reference electrode is based on a polymer membrane doped with the lipophilic salt tetrabutyl ammonium tetrabutyl borate (TBA-TBB). The electrodes, controlled with a multichannel detector system, were used for simultaneous determination of the concentration of Pb2+ and pH in environmental water samples. The results obtained using pH-selective electrodes were compared with data obtained using a conventional pH meter and the average percent difference was 0.3%. Furthermore, the sensing system was successfully used for lead-speciation analysis in environmental water samples

Rapid design of tool-wear condition monitoring systems for turning processes using novelty detection

Condition monitoring systems of manufacturing processes have been recognised in recent years as one of the key technologies that provide the competitive advantage in many manufacturing environments. It is capable of providing an essential means to reduce cost, increase productivity, improve quality and prevent damage to the machine or workpiece. Turning operations are considered one of the most common manufacturing processes in industry. It is used to manufacture different round objects such as shafts, spindles and pins. Despite recent development and intensive engineering research, the development of tool wear monitoring systems in turning is still ongoing challenge. In this paper, force signals are used for monitoring tool-wear in a feature fusion model. A novel approach for the design of condition monitoring systems for turning operations using novelty detection algorithm is presented. The results found prove that the developed system can be used for rapid design of condition monitoring systems for turning operations to predict tool-wear