Research on a Partial Aperture Factor Measurement Method for the Agri Onboard Calibration Assembly

A partial aperture onboard calibration method can solve the onboard calibration problems of some large aperture remote sensors, which is of great significance for the development trend of increasingly large apertures in optical remote sensors. In this paper, the solar diffuser reflectance degradation monitor (SDRDM) in the onboard calibration assembly (CA) of the FengYun-4 (FY-4) advanced geostationary radiance imager (AGRI) is used as the reference radiometer for measuring the partial aperture factor (PAF) for the AGRI onboard calibration. First, the linear response count variation relationship between the two is established under the same radiance source input. Then, according to the known bidirectional reflection distribution function (BRDF) of the solar diffuser (SD) in the CA, the relative reflectance ratio coefficient between the AGRI observation direction and the SDRDM observation direction is calculated. On this basis, the response count value of the AGRI and the SDRDM is used to realize the high-precision measurement of the PAF of the AGRI B1 ~ B3 bands by simulating the AGRI onboard calibration measurement under the illumination of a solar simulator in the laboratory. According to the determination process of the relevant parameters of the PAF, the measurement uncertainty of the PAF is analyzed; this uncertainty is better than 2.04% and provides an important reference for the evaluation of the onboard absolute radiometric calibration uncertainty after launch.

Calibration of the Marshall Grazing Incidence X-Ray Spectrometer Experiment. II. Flight Instrument Calibration

The Marshall Grazing Incidence X-ray Spectrometer (MaGIXS) is a sounding rocket experiment that observes the soft X-ray spectrum of the Sun from 6.0–24 Å (0.5–2.0 keV), successfully launched on 2021 July 30. End-to-end alignment of the flight instrument and calibration experiments are carried out using the X-ray and Cryogenic Facility at NASA Marshall Space Flight Center. In this paper, we present the calibration experiments of MaGIXS, which include wavelength calibration, measurement of line spread function, and determination of effective area. Finally, we use the measured instrument response function to predict the expected count rates for MaGIXS flight observation looking at a typical solar active region.

Cutting Temperature Measurement in Turning of Thermoplastic Composites Using a Tool-Work Thermocouple

Turning of carbon fibre reinforced thermoplastic pipes is used for production of fluid ducts for the aerospace and oil industries. Although thermoplastics are chemically stable, the matrix could be affected by the heat introduced by the machining process. This paper presents how to measure cutting temperature using C/PEEK and C/PA12 material as examples. A suitable method based on a thermocouple circuit and electric conductivity of the carbon fibres is presented, including system calibration. Measurement uncertainties were established for this new method of calibration and measurement for both tested materials. The cutting temperature measurements were analysed by ANOVA and significant factors and its dependence on temperature were identified for further machining process optimization and determination of the predictive model equation. This mathematical cutting temperature model was estimated based on the measurements, and empirical coefficients were identified for selected statistically significant parameters for both composite materials. Because the measured temperatures were above the melting point, the machined surface, chips and structural changes of polymeric matrices were measured in order to prove heat affection.

Estimating cover fraction from TLS return intensity in coniferous and broadleaved tree shoots

Terrestrial laser scanning (TLS) provides a unique opportunity to study forest canopy structure and its spatial patterns such as foliage quantity and dispersal. Using TLS point clouds for estimating leaf area density with voxel-based methods is biased by the physical dimensions of laser beams, which violates the common assumption of beams being infinitely thin. Real laser beams have a footprint size larger than several millimeters. This leads to difficulties in estimating leaf area density from light detection and ranging (LiDAR) in vegetation, where the target objects can be of similar or even smaller size than the beam footprint. To compensate for this bias, we propose a method to estimate the per-pulse cover fraction, defined as the fraction of laser beams’ footprint area that is covered by vegetation targets, using the LiDAR return intensity and an experimental calibration measurement. We applied this method to a Leica P40 single-return instrument, and report our experimental results. We found that conifer foliage had a lower average per-pulse cover fraction than broadleaved foliage, indicating an increased number of partial hits in conifer foliage. We further discuss limitations of our method that stem from unknown target properties that influence the LiDAR return intensity and highlight potential ways to overcome the limitations and manage the remaining uncertainty. Our method’s output, the per-beam cover fraction, may be useful in a weight function for methods that estimate leaf area density from LiDAR point clouds.

Metrology for heterogeneous sensor networks and Industry 4.0

Networks of sensors for different measured variables increasingly form the backbone for a variety of applications in, for example, industry, mechanical engineering and environmental monitoring. The merging of data (sensor fusion) plays a central role in the application and is generally a well investigated research area. However, the consideration of metrological basic principles such as calibration, measurement uncertainties and thus traceability to the SI system of units for comparable and reproducible measurement results has been investigated comparatively little. This article discusses fundamental questions, presents approaches to solutions from the currently running EMPIR project “Metrology for the Factory of the Future” (Met4FoF) and gives an outlook on future fields of research. The article focuses on the field of application of the so-called “Industry 4.0” as the “factory of the future”.

Toward high precision XCO2 retrievals from TanSat observations

<p>TanSat is the 1<sup>st</sup> Chinese carbon dioxide measurement satellite, launched in 2016. Preliminary TanSat XCO<sub>2</sub> retrievals have been introduced in previous studies based on the 1.6 m weak CO<sub>2</sub> band. In this study, the University of Leicester Full Physics (UoL-FP) algorithm is implemented for TanSat nadir mode XCO<sub>2</sub> retrievals. We develop a spectrum correction method to reduce the retrieval errors by an online fitting of an 8<sup>th</sup> order Fourier series. The model and a priori is developed by analyzing the solar calibration measurement. This correction provides a significant improvement to the O<sub>2</sub> A band retrieval. Accordingly, we extend the previous TanSat single CO<sub>2</sub> weak band retrieval to a combined O<sub>2</sub> A and CO<sub>2</sub> weak band retrieval. A Genetic Algorithm (GA) has been applied to determine the threshold values of post-screening filters. In total, 18.3% of the retrieved data is identified as high quality compared. The same quality control parameters have been used in the bias correction due to the stronger correlation with the XCO<sub>2</sub> retrieval error. A footprint independent multiple linear regression is applied to determine the sounding XCO<sub>2</sub> retrieval error and bias correction. Twenty sites of the Total Column Carbon Observing Network (TCCON) have been selected to validate our new approach of the TanSat XCO<sub>2</sub> retrieval. We show that our new approach produces a significant improvement of the XCO<sub>2</sub> retrieval accuracy and precision when compared with TCCON with an average bias and RMSE of -0.08 and 1.47 ppm respectively. The methods used in this study, such as continuum correction, can help to improve the XCO<sub>2</sub> retrieval from TanSat and subsequently the Level-2 data production, and hence will be applied in the TanSat operational XCO<sub>2</sub> processing.</p>

Digital Pressure Meter Equipped with Temperature and Humidity

Calibration is a technical activity which consists of the determination, the determination of one or more properties or characteristics of a product, process or service in accordance with a special procedure has been set. The purpose of which is to ensure the calibration measurement results in accordance with national and international standards. The tools used for the calibration of pressure Digital Pressure Meter. This tool is used to measure the pressure and suction pump spygnomanometer or other devices that use parameters for measuring pressure. This module manufacturing system using Arduino system as a controller and as processing analog data into digital data of the sensor MPX5100GP and MPXV4115V using analog signal conditioning circuit and displayed on the LCD Touchscreen with 2 modes of measurement that is positive pressure and vacuum pressure with pressures ranging from 0-300 mmHg for positive pressure and 0 –(-400) mmHg to vacuum pressure. There are also DHT22 sensor, As a detector for temperature and humidity for use in the work method in the calibration process. Based on a stress test generated and using comparators Digital Pressure Meter 2 plus brand fluke, this tool has an error value of 0 to 0.58% and has a value increment or correction value of 0 - 3. It can be concluded that the DPM DUA MODE this deserves to be used.

Assessment of Open-path Spectrometer Accuracy at Low Path-integrated Methane Concentrations

The accurate measurement of greenhouse gas emissions is a challenge for atmospheric science. Long-range open-path sensors are flexible enough to be applied to a variety of complex emission sources, and single devices are often used to measure both high and low path-integrated concentrations. As this technology develops, it is important to examine potential sources of inaccuracy. A GasFinder3 open-path laser was tested with a range of path-integrated concentrations from 11.7 to 182 ppm∙m CH4 using certified standard gases. The measured path-integrated concentrations had a positive bias which was higher than 10% at low path-integrated concentrations (<50 ppm∙m) with a declining trend expected to be under 2% at 200 ppm∙m. A linear equation was used to correct the measured path-integrated concentrations to fit the expected values. After correction, the average bias was reduced to −0.36% and there was no relationship with path-integrated concentration. A relative bias less than ±3% was achieved above ca. 150 ppm∙m with or without calibration. Measurement campaigns may reduce error by increasing path lengths to maximize path-integrated concentration. When low path-integrated concentrations are expected, calibration over the expected range is beneficial.

Microscopic Traffic Simulation Calibration Level for Reliable Estimation of Vehicle Emissions

Vehicle emissions are largely determined by the details of driving behaviours. Accordingly, emissions are often estimated by integrating micro-scale emission models into traffic simulations. Under this approach, it is essential to replicate the actual traffic situation being considered in an emission evaluation using a proper calibration procedure. Most previous research with respect to traffic flow has primarily focused on adjusting the complex combinations of parameters evaluated in these models, but it is not guaranteed that the use of widely used calibration measures can lead more accurate emissions estimates. Accordingly, we propose a systematic guideline for calibration to ensure reliable micro-scale emissions estimates. A calibration procedure is thus established in this paper based on various measure of effect (MOE) compositions (i.e., calibration levels) consisting of aggregated traffic data to identify the level that most reliably estimates micro-scale emissions. Five calibration levels of progressively more detailed measurements are first defined, valid calibration levels are identified, and the reliable calibration level is finally selected based on the available traffic data. The effect of vehicle type (i.e., light vs. heavy vehicles) composition on the estimated emissions is also evaluated for a well-calibrated simulation. We expect that a highly reliable estimation of emissions is possible using this more detailed traffic simulation calibration measurement.