VERIFICATION OF FORCE TRANSDUCER FOR DIRECT AND INDIRECT MEASUREMENTS

Paper deals with verification of high load force sensor using the small weight weights. Test band was built for this purpose. Verification of test band were executed using the etalon reference sensor. Small forces were executed via using the direct method through the applying of weights. High forces were executed using the indirect method through the lever amplification of load derived from small weights. Uncertainties of measurement were evaluated.

Machine Learning for Light Sensor Calibration

Sunlight incident on the Earth’s atmosphere is essential for life, and it is the driving force of a host of photo-chemical and environmental processes, such as the radiative heating of the atmosphere. We report the description and application of a physical methodology relative to how an ensemble of very low-cost sensors (with a total cost of <$20, less than 0.5% of the cost of the reference sensor) can be used to provide wavelength resolved irradiance spectra with a resolution of 1 nm between 360–780 nm by calibrating against a reference sensor using machine learning. These low-cost sensor ensembles are calibrated using machine learning and can effectively reproduce the observations made by an NIST calibrated reference instrument (Konica Minolta CL-500A with a cost of around USD 6000). The correlation coefficient between the reference sensor and the calibrated low-cost sensor ensemble has been optimized to have R2> 0.99. Both the circuits used and the code have been made publicly available. By accurately calibrating the low-cost sensors, we are able to distribute a large number of low-cost sensors in a neighborhood scale area. It provides unprecedented spatial and temporal insights into the micro-scale variability of the wavelength resolved irradiance, which is relevant for air quality, environmental and agronomy applications.

The Concept of Accuracy Analysis of the Vertical Displacements Gained from the Hydrostatic Levelling Systems’ Measurements

Nowadays, hydrostatic levelling is a widely used method for the vertical displacements’ determinations of objects such as bridges, viaducts, wharfs, tunnels, high buildings, historical buildings, special engineering objects (e.g., synchrotron), sports and entertainment halls. The measurements’ sensors implemented in the hydrostatic levelling systems (HLSs) consist of the reference sensor (RS) and sensors located on the controlled points (CPs). The reference sensor is the one that is placed at the point that (in theoretical assumptions) is not a subject to vertical displacements and the displacements of controlled points are determined according to its height. The hydrostatic levelling rule comes from the Bernoulli’s law. While using the Bernoulli’s principle in hydrostatic levelling, the following components have to be taken into account: atmospheric pressure, force of gravity, density of liquid used in sensors places at CPs. The parameters mentioned above are determined with some mean errors that influence on the accuracy assessment of vertical displacements. In the subject’s literature, there are some works describing the individual accuracy analyses of the components mentioned above. In this paper, the author proposes the concept of comprehensive determination of mean error of vertical displacement (of each CPs), calculated from the mean errors’ values of components dedicated for specific HLS. The formulas of covariances’ matrix were derived and they enable to make the accuracy assessment of the calculations’ results. The author also presented the subject of modelling of vertical displacements’ gained values. The dependences, enabling to conduct the statistic tests of received model’s parameters, were implemented. The conducted tests make it possible to verify the correctness of used theoretical models of the examined object treated as the rigid body. The practical analyses were conducted for two simulated variants of sensors’ connections in HLS. Variant no. I is the sensors’ serial connection. Variant no. II relies on the connection of each CPs with the reference sensor. The calculations’ results show that more detailed value estimations of the vertical displacements can be obtained using variant no. II.

Satellite architecture and preliminary in-orbit experiment of Taiji-1

Taiji-1 is China’s first in-orbit technology validating satellite related to spaceborne gravitational wave (GW) detection. The satellite was launched at 600km sun synchronized orbit on 31 August 2019. It has accomplished its mission goals while all subsystems have validated their key technologies in orbit. The subsystems include optical metrology system (OMS), drag-free attitude control system (DFACS), thermal control subsystem, high-quality microgravity satellite platform and so on. This paper presents system architecture of Taiji-1 analyzing in-orbit experimental results of thermal stability, reaction wheel vibration contributing to the noise of gravitational reference sensor (GRS) measurement noise, and the center-of-mass (CoM) of GRS calibration.

First result of orbit verification of Taiji-1 hall micro thruster

The Hall Micro Thrusters (HMTs) use cold gas or accelerated plasma dual mode to provide ultra-precise spacecraft altitude control. They were operated in space for the first time as part of the demonstration payloads on Chinese Academy of Science’s (CASs) Taiji-1 spacecraft since September 2019. Hall Micro Thruster Assemblies (HMTAs) were the actuators in drag-free control, and will compensate the nonconservative force for gravity wave observatories. The HMTAs meet the requirements of operating at 5–100 [Formula: see text]N of thrust with 0.7 [Formula: see text]N resolution and [Formula: see text]0.6 [Formula: see text]N/Hz[Formula: see text] (0.01–1 Hz) noise to deliver the nanometer-level precision control as fast as 30 ms measured by Gravitational Reference Sensor (GRS). A transfer function model in z-domain was fit and used to filter HMTs cathode voltage to predict GRSs thrust noise response. Simulations of a single or dual-frequency disturbance and the corresponding compensation demonstrated that HMTAs could deliver the required thrust profile expected. The capability to meet the requirements of thruster noise in drag-free control is critical for future missions because the acceleration noise on test mass directly relates to the gravity wave signa l. Preliminary in-orbit verification of Taiji-1 has showed HMTAs’ great potential in future, and the data in the experiments are presented in this paper.

Testing, modeling and estimation of Taiji-1’s in-orbit magnetic parameters

Taiji-1’s in-orbit magnetic property is significant for the improvement of the satellite’s attitude-control performance and the acceleration noise model of gravitational reference sensor. Test data of satellite drifts have been used to construct the model including interaction among the magnetic field; remnant magnetic moment and induced magnetic moment so as to estimate the satellite’s magnetic property. Using the global optimization method, the remnant magnetic moment of Taiji-1 is estimated to be (-1.42 -0.19 -0.06) Am2.

In-orbit performance of the laser interferometer of Taiji-1 experimental satellite

Taiji-1, which is the first experimental satellite for space gravitational wave detection in China, relies on key technologies which include the laser interferometer, the gravitational reference sensor (GRS), the micro-thruster and the satellite platform. Similarly to the Laser Interferometer Space Antenna (LISA) pathfinder, except for the science interferometer, the optical bench (OB) of Taiji-1 contains reference and test mass (TM) interferometers. Limited by the lower mechanical strength of the carrier rocket and by the orbit environment, the OB of Taiji-1 is made of invar steel and fused silica, and it is aimed to achieve a sensitivity of the order of 100[Formula: see text]pm/[Formula: see text]. The experimental results from in-orbit tests of Taiji-1 demonstrate that the interferometer can reach a sensitivity of 30[Formula: see text]pm/[Formula: see text] in the frequency range of 0.01–10[Formula: see text]Hz, which satisfies the requirements of Taiji-1 mission.

Técnica de Calibração de Sensores Meteorológicos de Temperatura e Umidade Relativa do ar Utilizando um Sensor de Referência

Em pesquisas ambientais é comum a utilização de mais de um sensor meteorológico para medições, principalmente, para medições espacializadas. Porém pode ocorrer erro na coleta espacializada, quando os sensores são diferentes. Nesse contexto, por meio da regressão linear se pode calibrar as medições dos sensores utilizados em função de um sensor de referência. Assim, este trabalho tem como objetivo apresentar uma técnica de calibração de sensores meteorológicos, focado nas variáveis temperatura do ar e umidade relativa do ar, utilizando um sensor de referência, e fazendo a aplicação posterior em campo. Os sensores foram calibrados em ambiente controlado, em que se podia controlar a temperatura do ar e a umidade relativa do ar, de forma a submeter os sensores a uma amplitude maior de variações, variando de 25 ºC a 45 ºC de temperatura do ar e de 20% a 60% de umidade relativa do ar. Os resultados das regressões lineares foram considerados satisfatórios, uma vez que todos os coeficientes angulares e lineares foram considerados significativos e o menor coeficiente de determinação (R²) foi de 0,91. Após a calibração foram feitas medidas meteorológicas no Parque das Águas, Cuiabá-MT, de modo a aplicar as regressões em dados reais. As regressões corrigiram diferenças máximas de 0,9 ºC de temperatura do ar e 8,6% de umidade relativa do ar. Conclui-se que a metodologia é válida para a calibração de sensores diferentes em relação a um sensor de referência, podendo ser uma estratégia interessante para os pesquisadores, que não possuem diversos sensores calibrados. Palavras-chave: Temperatura do Ar. Umidade Relativa do Ar. Estação Meteorológica. Termohigrômetro. Abstract In environmental research it is common to use more than one meteorological sensor for measurements, mainly for spatialized measurements. However, there may be an error in the spatial collection when the sensors are different. In this context, through linear regression, it is possible to calibrate the measurements of the sensors used in function of a reference sensor. Thus, this work aims to present a calibration technique of meteorological sensors, focused on the variables air temperature and the air relative humidity, using a reference sensor, and making the subsequent application in the field. The sensors were calibrated in a controlled environment, in which air temperature and relative humidity could be controlled, in order to subject the sensors to a greater range of variations, ranging from 25 ºC to 45 ºC and 20% at 60% relative humidity. The linear regressions results were considered satisfactory, since all the angular and linear coefficients were considered significant and the lowest determination coefficient (R²) was 0.91. After calibration, meteorological measurements were made in Parque das Águas, Cuiabá-MT, in order to apply the regressions to real data. The regressions corrected maximum differences of 0.9ºC of air temperature and 8.6% of relative air humidity. It is concluded that the methodology is valid for the calibration of different sensors in relation to a reference sensor, which can be an interesting strategy for researchers who do not have several calibrated sensors. Keywords: Air Temperature. Relative Humidity. Weather Station. Thermohygrometer.