Sensor monitoring strategy

In its overall strategy, COMMON SENSE work packages (11) can be grouped into 3 key phases: (1) RD basis for cost-effective sensor development, (2) Sensor development, sensor web platform and integration, and (3) Field testing. In the Phase 1, within WP1 and WP2, partners have provided a general understanding and integrated basis for a cost effective sensors development. In Phase 2, within the WP3 and WPs 4 to 8, the new sensors have been created and planned to be integrated into instruments for the different identified platforms and how data produced will be processed, organised and saved. During the phase 3, within WP9, partners are deploying precompetitive prototypes at chosen platforms (e.g. research vessels, oil platforms, buoys and submerged moorings, ocean racing yachts, drifting buoys). Starting from August 2015 (month 22; Task 9.2), these platforms are permitting the partnership to test the adaptability and performance of the in-situ sensors and verify if the transmission of data is properly made and correct observed deviations. Sensor monitoring strategy (Deliverable 2.4 for Task 2.5) is the last task within Phase 1. As the other tasks in Phase 1 it has to provide a basis for designing field testing activities to be useful. That is how to validate the performance of sensors, integration, data acquisition, transmission, under real conditions in different platforms. Since there is a wide sensor variety, each one with its own characteristics, and several platforms, to prepare a general methodological review and give the corresponding directions as it was initially planned, would be a huge and useless effort. Given the initially fixed calendar a first version of the present deliverable was presented when most of the sensors were still not developed. The document addressed how projected sensors should be tested, their limitations and conditions for their monitoring and final certification. Now, when D2.2 (Procedures of sensors deployment methodology on physical supports/platforms) has been rewritten (May 2016), all sensors are fully developed and most of them have started their tests at sea, the present new updated version of the deliverable becomes more precise, with much better knowledge on the real sensors and their performance. In addition, a complete new chapter on data transmission –initially proposed but not developed in the previous version– is included. The information from the six sensor developers in COMMON SENSE on which the initial plan on where and how to test each sensor that was presented in D9.1 (April 2015) has been updated (May 2016). The update includes the final properties of sensors after the respective full laboratory tests and even some of the results from field tests that had been carried out starting August 2015. This task assesses field testing procedures and deployment specificities. Two tables are presented based on the information of the report for D9.1 delivered in April 2015. One table was created for sensor developers and one for those who will test the sensors at sea. In this report some information from the testers’ table is shown and updated according to the new version of D2.2 (May 2016) for platforms. Objectives and rationale The objective of Task 2.5 within the WP2 is the definition of sensor monitoring strategy based on the premises for water monitoring, sensor performances and data storage and transmission. For any new sensor, available instruments currently used in the oceanographic studies will be identified to perform comparisons. Suitable transmission technology will be selected according to the test conditions: open sea, coastal areas, remote locations, etc. Sensitivity and stress tests will be designed in order to establish confidence limits under different environmental situations, so that the results obtained in the testing exercises (WP9) will enable to certify the performance of the new instruments

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

Reconfigurable Sensor Monitoring System

A reconfigurable sensor monitoring system includes software tunable filters, each of which is programmable to condition one type of analog signal. A processor coupled to the software tunable filters receives each type of analog signal so-conditioned

Fiber Optic Sensor : Monitoring Precast Beams

A new bridge over the Rio Puerco river, west of Albuquerque will be the first of its kind in the nation with built-in fiber-optic sensors to monitor stress in the bridge\u27s girders. Known as smart bridge technology, the self-monitoring system offers many advantages over methods that rely largely on visual inspections

multi sensor signal processing for catastrophic tool failure detection in turning

Abstract This paper presents a methodology aimed at the identification of a catastrophic tool failure (CTF) in turning processes based on multiple sensor monitoring. Experimental turning tests were carried out under various cutting conditions (cutting speed, feed, depth of cut) using a multi-sensor monitoring system consisting of a triaxial force sensor to acquire the three components of the cutting force and an acoustic emission sensor. Signals analysis, interpretation and processing was performed on the multi-sensor signals acquired during the turning process and relevant statistical features were extracted and used to develop a methodology for the automatic CTF detection during turning

Space shuttle onboard navigation console expert/trainer system

A software system for use in enhancing operational performance as well as training ground controllers in monitoring onboard Space Shuttle navigation sensors is described. The Onboard Navigation (ONAV) development reflects a trend toward following a structured and methodical approach to development. The ONAV system must deal with integrated conventional and expert system software, complex interfaces, and implementation limitations due to the target operational environment. An overview of the onboard navigation sensor monitoring function is presented, along with a description of guidelines driving the development effort, requirements that the system must meet, current progress, and future efforts

SENSOR MONITORING LEVEL AIR UNTUK SISTEM PENDETEKSI BANJIR BERBASIS MIKROKONTROLLER AT89S52

Tujuan pembuatan proyek akhir ini adalah untuk membuat sebuah sistem pendeteksi banjir. Sistem ini dibuat dengan menggunakan Sensor Ultrasonik untuk mengukur level air. Sistem ini berbasis Mikrokontroler AT89S52 sebagai pemproses data. Prinsip kerja dari Sensor Monitoring Level Air Untuk Sistem Pendeteksi Banjir Berbasis Mikrokontroler AT89S52 adalah sensor digunakan untuk membaca elevasi air, kemudian mikrokontroler akan membaca input berupa PWM yang dikeluarkan oleh sensor ping parallax, mikrokontroler memproses input tersebut dengan cara menghitung lebar pulsa PWM dengan menggunakan bahasa Bascom, dan hasil dari pengukuranya ditampilkan melalui LCD. Metode yang digunakan dalam membangun Sensor Monitoring Level Air Untuk Sistem Pendeteksi Banjir Berbasis Mikrokontroler AT89S52 ini menggunakan metode rancang bangun yang terdiri dari beberapa tahap yaitu, (1) Identifikasi kebutuhan, (2) Analisis Kebutuhan, (3) Perancangan perangkat keras dan perangkat lunak, (4) Pembuatan dan (5) pengujian. Sehingga didapatkan sebuah sistem monitoring yang berupa sistem minimum Mikrokontroler AT89S52. Dari hasil perancangan dan pembuatan alat, Sensor Monitoring Level Air Untuk Sistem Pendeteksi Banjir Berbasis Mikrokontroler AT89S52 ini dapat dimanfaatkan dengan baik. Sensor Ping Parallax yang digunakan ternyata dapat berkerja dengan optimal, hal ini dapat kita ketahui setelah kita melakukan simulasi pengukuran sebanyak 18 kali dengan pengulangan setiap pengukuran sebanyak 3 kali, sistem ini mempunyai rata-rata error terhadap jarak sebenarnya sebesar 3,14 %

Wireless sensor monitoring of Paddington Station Box Corner

This paper presents the real performance of three diaphragm wall panels on the southeast corner of Paddington Station Box during excavation, monitored using a wireless sensor network. In total, 15 LPDT displacement sensors, 12 tilt sensors, 13 relay nodes and a gateway were deployed at three different stages. Each wireless sensor node is programmed with Contiki OS using the in-built IPv6-based network layer (6LoWPAN/RPL) for link-local addressing and routing, and ContikiMAC at the medium access control (MAC) layer for radio duty cycling. Extensive testing and calibration was carried out in the laboratory to ensure that the system functioned as expected. Wireless tilt and displacement sensors were installed to measure the inclination, angular distortion and relative displacement of these corner panels at three different depths. The monitoring data reveal that the corner produced a stiffening effect on the station box, which might result in a breakdown of plane strain conditions. The network performance characteristics (e.g. message reception ratio and network topology status) and challenges are also highlighted and discussed

Contemporary analysis and architecture for a generic cloud-based sensor data management platform.

An increasing volume of data is being generated by sensors and smart devices deployed in different areas, often far from computing facilities such as data centres. These data can be difficult to gather and process using local computing infrastructure. This is due to cost and limited resources. Cloud computing provides scalable resources that are capable of addressing such problems. However, platform-independent methods of gathering and transmitting sensor data to Clouds are not widely available. This paper presents a state-of-the-art analysis of Cloud-based sensor monitoring and data gathering platforms. It discusses their strengths and weaknesses and reviews the current trends in this area. Informed by the analysis, the paper further proposes a generic conceptual architecture for achieving a platform-neutral Cloud-based sensor monitoring and data gathering platform. We also discuss the objectives, design decisions and the implementation considerations for the conceptual architecture.IC