Inclinometer Research Articles

A novel slight-tilt measure method based on dynamic Vernier effect using dual Fabry-Perot interferometers on vertical cantilever beam

In this work, a new method for measuring slight tilt based on the dynamic Vernier effect is proposed and verified. A pair of the Fabry-Perot interferometers (FPIs) are fixed on the surfaces of a cantilever beam horizontally, and a mass block at the tail end of the beam supplies longitudinal strain on the surfaces, resulting in opposite variations in the cavity lengths (CLs) of FPIs. According to the principle of dynamic Vernier effect at the superposition of reflected light, the shift of the Vernier envelope would be proportional to the tilt angle of the entire structure. The experimental results revealed a strain sensitivity of as high as 6.733 nm/με with a magnification factor of 41. Furthermore, the theoretical simulated results show that the maximum sensitivity would achieve from 204.408 nm/° to 613.25 nm/° within the tilt range from 0° to 15°. In addition, the merits of the proposed tilt sensor such as simple in structure, low cost, and temperature insensitivity in normal environments, all of which promise great application prospects in monitoring suddenly major structural deformation such as mountains and buildings • An inclinometer consists of two FPIs on a cantilever beam based on enhanced Vernier effect is realized. • This paper proposed a new tilt measurement method that considers a horizontal cantilever beam as the inclinometer. • A strain test verifies that sensitivity of 6.733 nm/με and tilt sensitivity of 204.48 nm/° in the range of 15°.

Design and Investigation of a High-Sensitivity Tilt Sensor Based on FBG

In this paper, a high-sensitivity fiber Bragg grating (FBG) tilt sensor using a cantilever-based structure is introduced. Two FBGs are fixed on a specially designed elastomer. One end of the elastomer is connected to the mass block, and the other end is connected to the shell. The principle of the tilt sensor is introduced in detail, and the mathematical model is established. The performance of the sensor is studied. The results show that there is a good linear relationship between the central wavelength difference of the two FBGs and the tilt angle in the range of −5° to 5°. The repeatability of the sensor is good, and the tilt sensitivity can reach 231.7pm/°. The influence of the silicone oil on the damping capacity of the sensor is studied. The results show that the damping capacity of the sensor has been improved by sealing the silicone oil inside the shell of the sensor. The field test is carried out on a pier of an elevated bridge, and the result is good, which verifies the practicability of the sensor.

Multi-Sensor Fusion-based Settlement Monitoring Method for Power Transmission Towers

Transmission lines are the main arteries of power systems, which inevitably pass-through geological areas such as coal mining areas, desert areas, soft soil areas, etc. Transmission towers are at risk of tilting and settling. Traditional tower monitoring methods such as GPS/Beidou method and static level have high price, inconvenient installation and risk of external breakage. In this paper, we propose a multi-sensor fusion method for tower settlement monitoring, using ultrasonic distance sensor and tilt sensor fusion to achieve the monitoring of tower settlement, and design a monitoring system and carry out a simulation of settlement experiments, the experimental results show that the average measurement error of the system is 5%, the system has the advantages of good economy, easy installation and good measurement accuracy.

An Electrochemical Tilt Sensor with Double-Band Electrodes Fabricated by Wire Winding.

This paper presents the principle, design, fabrication, and characterization of Molecular Electronic Transducer (MET) dual-axis tilt sensors. The proposed sensor has a 3D-printed cylindrical channel inserted with four double-band electrodes and partially filled with a liquid electrolyte. The double-band electrodes were fabricated by wire winding with a ~0.1 mm anode-cathode distance under controlled tension. It allows the electrode to become any 3D coil rather than a 2D structure by microfabrication and exhibits good repeatability (). The tilting changes the electrolyte level and electrode-electrolyte contact area, resulting in Faradaic current changes. The x-axis and the y-axis sensitivity reach 0.121 V/° and 0.154 V/°, respectively.

Free-Surface Velocity Measurement Using Direct Sensor Orientation-Based STIV.

Particle image velocimetry (PIV) is a quantitative flow visualization technique, which greatly improves the ability to characterize various complex flows in laboratory and field environments. However, the deployment of reference objects or ground control points (GCPs) for velocity calibration is still a challenge for in situ free-surface velocity measurements. By combining space-time image velocimetry (STIV) with direct sensor orientation (DSO) photogrammetry, a laser distance meter (LDM)-supported photogrammetric device is designed, to realize the GCPs-free surface velocity measurement under an oblique shooting angle. The velocity calibration with DSO is based on the collinear equation, while the lens distortion, oblique shooting angle, water level variation, and water surface slope are introduced to build an imaging measurement model with explicit physical meaning for parameters. To accurately obtain the in situ position and orientations of the camera utilizing the LDM and its embedded tilt sensor, the camera’s intrinsic parameters and relative position within the LDM are previously calibrated with a planar chessboard. A flume experiment is designed to evaluate the uncertainty of optical flow estimation and velocity calibration. Results show that the proposed DSO-STIV has good transferability and operability for in situ measurements. It is superior to propeller current meters and surface velocity radars in characterizing shallow free-surface flows; this is attributed to its non-intrusive, whole-field, and high-resolution features. In addition, the combined uncertainty of free-surface velocity measurement is analyzed, which provides an alternative solution for error assessment when comparing measurement failures.

Gesture Vocalizer Using Flex Sensor and Software Visualization

Abstract: Hardware version of the project: Gesture Vocalizer is a multi-microcontroller-based framework intended to work with the correspondence among the imbecilic, hard of hearing and visually impaired networks and their correspondence with the ordinary individuals. This system can be flexibly changed to function as a "smart device.". In this project we showcased a gesture vocalizer based on a microcontroller and sensors. Gesture vocalizer design is basically a hand glove and a microcontroller system. A hand glove can detect practically all hand gestures, and a microcontroller-based system can translate a few of those gestures into identifiable speech. The hand glove has two types of sensors: flex sensors that act as bend sensors and accelerometers that act as tilt sensors. This device is advantageous to deaf people because it allows their hands to speak once they have worn the gesture vocalizer glove. In this project we use flex sensors and Arduino Mega microcontroller which are the backbone of the project. The flex sensor otherwise called the twist sensor is a sort of sensor that measures the measure of bowing or avoidance or flexing as the name proposes. As the sensors are bowed the sensors give us an obstruction esteem, the sensor gives so the more the sensors are twisted, more opposition esteem. When estimated with a multimeter, the flex sensor at a level and consistent position gives an opposition esteem close to 25k ohm while when the sensors are completely bowed, they give an obstruction worth of 72k ohm. The flex sensors are typically of a slim construction and are entirely agreeable to utilize, and can be twisted without utilizing a lot of power.

TILT CORRECTION OF ONBOARD DRONE IRRADIANCE MEASUREMENTS – EVALUATION OF HYPERSPECTRAL METHODS

Abstract. An accurate onboard irradiance measurement on drones is a requirement direct reflectance transformation of aerial images and remote sensing data without use of on-ground reference targets. One of the major error sources in onboard irradiance measurement is the effect of sensor tilt to the observed irradiances. In this paper/presentation, we will present an intercomparison of two methods: the FGI AIRS method and the Köppl method. Both methods require an irradiance sensor with good cosine response and IMU system providing accurate tilt angle for each irradiance measurement. Additionally to this, the AIRS method requires special hardware with multiple tilted irradiance sensors, which effectively allow interpolation of a virtual horizontal sensor. The Köppl method requires the irradiance sensor to be a spectral sensor, which allows the direct and diffuse fractions of irradiance spectrum to be deducted from shape of the measured spectrum using the spectral unmixing between direct and diffuse spectrum shapes. We present a field experiment where the AIRS sensor was flown in a typical mapping pattern flight and evaluate the tilt correction methods during it. During a fully sunny period of the flight, the standard deviations of the irradiances was ±6.4% for the uncorrected tilted irradiances, ±1.8% for the AIRS method, and ±2.0% for the Köppl method. The data shows that an accurate irradiance measurement onboard a drone is feasible using a well-calibrated irradiance sensor system and both methods are capable to produce quite similar results.

Risk evaluation and warning threshold of unstable slope using tilting sensor array

Slope monitoring and early warning systems are a promising approach toward mitigating landslide-induced disasters. Many large-scale sediment disasters result in the destruction of infrastructure and loss of human life. The mitigation of vulnerability to slope and landslide hazards will benefit significantly from early warning alerts. The authors have been developing monitoring technology that uses a micro-electro-mechanical systems tilt sensor array that detects the precursory movement of vulnerable slopes and informs the issuance of emergency caution and warning alerts. In this regard, the determination of alarm thresholds is very important. Although previous studies have investigated the recording of threshold values by an extensometer which installation of an extensometer at appropriate sites is also difficult. The authors prefer tilt sensors and have proposed a novel threshold for the tilt angle, which was validated in this study. This threshold has an interesting similarity to previously reported viscous models. Additionally, multi-point monitoring has recently emerged and allows for many sensors to be deployed at vulnerable slopes without disregarding the slope’s precursory local behavior. With this new technology, the detailed spatial and temporal variation of the behavior of vulnerable slopes can be determined as the displacement proceeds toward failure.

Anti-Poaching of Trees in Forest-Based on IoT

Day today life their area unit several incidents concerning importation of trees like shoe, Sagwan etc. These trees area unit terribly pricey and hand-to-mouth. they're employed in the medical sciences, cosmetics. to limit their importation and to avoid wasting forests round the globe some preventive measures must be deployed. we've got developed a system which might be wont to prohibit importation. the planning system uses 3 sensors tilt sensor (to find the inclination of tree once it’s being cut), temperature sensor (to find forest fires), sound sensor (for effective detection of embezzled work i.e., even the sounds generated whereas axing the tree also are sensed). Data generated from these sensors is unendingly monitored with the help of Blynk App. With relevancy the sensors, their output devices area unit activated through relay switch. For tilt sensing element and sound sensing element a buzzer is activated and for temperature sensing element a pump is activated. Generated information is hold on in Blynk Server over the Wi-Fi module. Forest officers’ area unit notified once any event happens in order that acceptable action is often taken.

Ultra-Compact Full-Angle-Range Direction-Distinguishable Tilt Sensor Based on Fiber in-Line Polymer Microcavity

We propose an ultra-compact full-angle-range direction-distinguishable tilt sensor based on a polymer column working as a Fabry–Perot (FP) microcavity fixed between two sections of single-mode fibers (SMFs). The directional tilt angle from −90 deg to +90 deg can be demodulated by monitoring the wavelength shift of interference fringe, based on the deformation of the polymer column under the effect of the gravity force. The sensitivity of the sensor can be adjusted by changing the shape and size of the polymer column that is fabricated by the single beam illumination with high efficiency and low cost. The sensor can satisfy the engineering requirements owing to its small size, flexible structure, cost-effective performance, large measurement range, and direction-distinguishable ability.

Research Facilities for Europe’s Next Generation Gravitational-Wave Detector Einstein Telescope

The Einstein Telescope is Europe’s next generation gravitational-wave detector. To develop all necessary technology, four research facilities have emerged across Europe: The Amaldi Research Center (ARC) in Rome (Italy), ETpathfinder in Maastricht (The Netherlands), SarGrav in the Sos Enattos mines on Sardinia (Italy) and E-TEST in Liége (Belgium) and its surroundings. The ARC pursues the investigation of a large cryostat, equipped with dedicated low-vibration cooling lines, to test full-scale cryogenic payloads. The installation will be gradual and interlaced with the payload development. ETpathfinder aims to provide a low-noise facility that allows the testing of full interferometer configurations and the interplay of their subsystems in an ET-like environment. ETpathfinder will focus amongst others on cryogenic technologies, silicon mirrors, lasers and optics at 1550 and 2090 nm and advanced quantum noise reduction schemes. The SarGrav laboratory has a surface lab and an underground operation. On the surface, the Archimedes experiment investigates the interaction of vacuum fluctuations with gravity and is developing (tilt) sensor technology for the Einstein Telescope. In an underground laboratory, seismic characterisation campaigns are undertaken for the Sardinian site characterisation. Lastly, the Einstein Telecope Euregio meuse-rhine Site & Technology (E-TEST) is a single cryogenic suspension of an ET-sized silicon mirror. Additionally, E-TEST investigates the Belgian–Dutch–German border region that is the other candidate site for Einstein Telescope using boreholes and seismic arrays and hydrogeological characterisation. In this article, we describe the Einstein Telescope, the low-frequency part of its science case and the four research facilities.

2-D Tilt Sensor Based on Coaxial Cable Fabry–Perot Resonators With Submicroradian Resolution

For the past 50 years, open-ended coaxial lines were commonly employed for the determination of electromagnetic properties of various materials. In this article, the application of an open-ended hollow coaxial cable resonator (OE-HCCR) as a 1-D inclinometer for tilt measurements with 110 nanoradian (nrad) resolution is proposed and demonstrated. The coaxial cable resonant structure is formed between a metal post welded within the coaxial cable at the RF input end and the open end of the coaxial cable. A metal mass block, suspended in proximity to the open end in parallel is used to construct a pendulum structure, serving as the element responsive to a tilt. When the device is tilted, the distance between the mass block and the open end varies due to the displacement of the suspended pendulum. The change in the gap distance modifies the phase reflection coefficient associated with the open end, causing the resonance frequency of the coaxial cable resonator to change. By tracking the resonance frequency, the coaxial line resonator is effectively used as an inclinometer. The experimental results demonstrated that the novel device has a measurement resolution of 110 nrad over a range of 0–3 milliradians (mrad). Additionally, based on the same principle, a 2-D inclinometer based on two perpendicularly aligned OE-HCCRs, useful for simultaneous tilt measurements in two orthogonal dimensions is demonstrated. The open-ended coaxial cable resonator-based inclinometer holds several advantages, including high resolution, robustness, cost effectiveness, ease of signal interrogation, and user-configurable sensitivity and dynamic range.

Unveiling Falling Urban Trees before and during Typhoon Higos (2020): Empirical Case Study of Potential Structural Failure Using Tilt Sensor

Urban trees in a densely populated environment may pose risks to the public’s safety in terms of the potential danger of injuries and fatalities, loss of property, impacts on traffic, etc. The biological and mechanical features of urban trees may change over time, thereby affecting the stability of the tree structure. This can be a gradual process but can also be drastic, especially after typhoons or heavy rainstorms. Trees may fall at any time with no discernible signs of failure being exhibited or detected. It is always a challenge in urban tree management to develop a preventive alert system to detect the potential failure of hazardous urban trees and hence be able to have an action plan to handle potential tree tilting or tree collapse. Few studies have considered the comparison of tree morphology to the tilt response relative to uprooting failure in urban cities. New methods involving numerical modeling and sensing technologies provide tools for an effective and deeper understanding of the interaction of root-plate movement and windstorm with the application of the tailor-made sensor. In this study, root-plate tilt variations of 889 trees with sensors installed during Typhoon Higos (2020) are investigated, especially the tilting pattern of the two trees that failed in the event. The correlation of tree response during the typhoon among all trees with tilt measurements was also evaluated. The results from two alarm levels developed in the study, i.e., Increasing Trend Alarm and Sudden Increase Alarm indicated that significant root-plate movement to wind response is species-dependent. These systems could help inform decision making to identify the problematic trees in the early stage. Through the use of smart sensors, the data collected by the alert system provides a very useful analysis of the stability of tree structure and tree health in urban tree management.

Tilt Sensor with Recalibration Feature Based on MEMS Accelerometer.

The main errors of MEMS accelerometers are misalignments of their sensitivity axes, thermal and long-term drifts, imprecise factory calibration, and aging phenomena. In order to reduce these errors, a two-axial tilt sensor comprising a triaxial MEMS accelerometer, an aligning unit, and solid cubic housing was built. By means of the aligning unit it was possible to align the orientation of the accelerometer sensitive axes with respect to the housing with an accuracy of 0.03°. Owing to the housing, the sensor could be easily and quickly recalibrated, and thus errors such as thermal and long-term drifts as well as effects of aging were eliminated. Moreover, errors due to local and temporal variations of the gravitational acceleration can be compensated for. Procedures for calibrating and aligning the accelerometer are described. Values of thermal and long-term drifts of the tested sensor, resulting in tilt errors of even 0.4°, are presented. Application of the sensor for monitoring elevated loads is discussed.

An Operational Methodology for Validating Satellite-Based Snow Albedo Measurements Using a UAV

Snow albedo is highly variable over multiple temporal and spatial scales. This variability is more pronounced in areas that experience seasonal snowpack. Satellite retrievals, physically based models and parameterizations for snow albedo all require ground-based measurements for calibration, initialization, and validation. Ground measurements are generally made using upward and downward-facing pyranometers at opportunistically located weather stations that are sparsely distributed, particularly in mountainous regions. These station-based measurements cannot capture the spatial variability of albedo across the land surface. Uncrewed Aerial Vehicles (UAVs) equipped with upward and downward-facing pyranometers provide near-surface measurements of broadband albedo that are spatially distributed across landscapes, offering improvements over in-situ sensors. At the hillslope to watershed scale albedo measurements from UAVs taken over heterogeneous terrain are a function of the spatial variability in albedo and topography within the downward-facing sensor’s field-of-view (FOV). In this research we propose methods for topographic correction of UAV snow albedo measurements and comparison to gridded satellite albedo products. These methods account for the variability of surface topography and albedo within the sensor FOV, sensor tilt, and the angular response of pyranometers. We applied the proposed methodologies to UAV snow albedo measurements collected over an alpine meadow in southwest Montana, United States (45.23°, −111.28°). Sensitivity analyses were conducted to determine the effect of altering the processing FOV (PFOV) for both topographic corrections and comparison to coincident Landsat 8-derived albedo measurements. Validation from ground-based albedo measurements showed the topographic correction to reduce albedo measurement error considerably over mildly sloping terrain. Our sensitivity analyses demonstrated that outcomes from the topographic correction and satellite comparison are highly dependent on the specified PFOV. Based on field observations and analyses of UAV albedo measurements made at different altitudes, we provide guidelines for strategizing future UAV albedo surveys. This research presents considerable advances in the standardization of UAV-based albedo measurement. We establish the foundation for future research to utilize this platform to collect near-surface validation measurements over heterogeneous terrain with high accuracy and consistency.

A Novel Tilt and Acceleration Measurement System Based on Hall-Effect Sensors Using Neural Networks

A tilt sensor is a device used to measure the tilt on many axes of a reference point. Tilt sensors measure the bending position according to gravity and are used in many applications. Slope sensors allow easy detection of direction or slope in the air. These tilt gauges have become increasingly popular and are being adapted for a growing number of high-end applications. As an example of practical application, the tilt sensor provides valuable information about an aircraft’s vertical and horizontal tilt. This information also helps the pilot understand how to deal with obstacles during flight. In this paper, Hall-effect effective inclination and acceleration sensor design, which makes a real-time measurement, have been realized. 6 Hall-effect sensors with analog output (UGN-3503) have been used in the sensor structure. These sensors are placed in a machine, and the hall sensor outputs are continuously read according to the movement speed and direction of the sphere magnet placed in the assembly. Hall sensor outputs produce 0–5 Volt analog voltage according to the position of the magnet sphere to the sensor. It is clear that the sphere magnet moves according to the inclination of the mechanism when the mechanism is moved angularly, and the speed of movement from one point to the other changes according to the movement speed. Here, the sphere magnet moves between the hall sensors in the setup according to the ambient inclination and motion acceleration. Each sensor produces analog output values in the range of 0–5 V instantaneous according to the position of the spheroid. Generally defined, according to the sphere magnet position and movement speed, the data received from the hall sensors by the microcontroller have been sent to the computer or microcomputer unit as UART. In the next stage, the actual sensor has been removed. The angle and acceleration values have been continuously produced according to the mechanism’s movement and output as UART. Thanks to the fact that the magnet is not left idle and is fixed with springs, problems such as vibration noises and wrong movements and the magnet leaning to the very edge and being out of position even at a slight inclination are prevented. In addition, the Hall-effect sensor outputs are given to an artificial neural network (ANN), and the slope and acceleration information is estimated in the ANN by training with the data obtained from the real-time slope and accelerometer sensor.

Assistive ultrasonic sensor based smart blind stick using fuzzy logic

Smart Blind Stick as the name suggests is a very effective device for visually impaired people. It works by detecting the obstacles and objects that might hinder in the way of visually impaired person by portraying them in the form of beeps or audio signals. According to a survey conducted by WHO, about 0.285 billion people worldwide are visually impaired out of which the blind people comprises 0.039 billion and 0.026 billion people that suffer from low vision(severe or moderate impairment).This number is expected to increase in future due to various reasons. So, need of the hour was to develop a device which can be used by visually impaired people to navigate easily without much dependency on others. In this paper, we analyzed the problems faced by the blind people and made a smart stick which is incorporated with various components like Ultrasonic Sensors, Tilt Sensors, LEDs, Radio Frequency Transmitter-Receiver Kit.

Experimental Verification of the Modified PSA Algorithm

Being abundant and non-polluted, solar energy is an increasingly desirable energy source. Growing research is concerned about maximum solar energy acquisition from solar panels, especially in the automatic sun-tracking of the solar panels. This paper presents a modified algorithm based on the “PSA Algorithm” proposed in the 2001. And presents a new automatic solar tracking system with a two-axis is designed based on the algorithm. The PSA modified algorithm is used to calculate the sun’s horizontal azimuth and zenith angle combined with time, longitude, latitude, and other information. We designed a prototype mainly composed of a microcontroller, a Global Positioning System (GPS) module, a digital compass, a tilt sensor, a 555 timer, and gates, optical couples, an H-bridge and two stepper motors. Then using the proposed prototype, a series of experiments are conducted in Tianjin City. Measured zenith angle values were collected and recorded based on the PSA modified algorithm and the original PSA algorithm, compared with the actual Zenith Angle of the Sun in Tianjin City. The comparison curves of Zenith Angle show that the measurement accuracy of the modified PSA algorithm is higher than that of the PSA original algorithm.

Deep-Learning-Based Human Activity Recognition Using Wearable Sensors

Accurate activity recognition has multiple useful health applications, including home-based monitoring in various chronic disease applications. This paper utilizes a deep-learning-based algorithm for recognition of various daily living activities. A nonlinear observer that estimates body segment tilt angles and sensor bias parameters, using inertial sensors provides the inputs to the deep-learning-based algorithm. The observer is designed using Lyapunov analysis and an LMI to obtain the observer gain. Switched gains are utilized for each monotonic region of the nonlinear dynamics to ensure global stability. A convolutional neural network long short-term memory network (CNN-LSTM) is trained as the state-of-the-art deep learning-based activity recognition algorithm. Experimental results are presented on the performance of the CNN-LSTM network with the raw inertial sensor data and compared with results when inputs are the angles estimated by the nonlinear observer instead of the raw data. The activity recognition algorithm that utilizes 18 raw inertial signal data shows an average accuracy of 96.47% while the algorithm that utilizes only the 3 tilt angles estimated by the nonlinear observer provides an average accuracy of 99.81%.

Novel Fiber Bragg Grating Tilt Sensor with High Sensitivity

Novel Fiber Bragg Grating Tilt Sensor with High Sensitivity