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This work introduces the instrument design of the medium-energy proton detector (MEPD, detection range: 30 keV–5 MeV) mounted on the Chinese Fengyun-4B (FY-4B) satellite. Compared to a similar detector on the Fengyun-3E (FY-3E) satellite, this instrument has undergone significant changes due to the different orbital radiation environment and solar lighting conditions. Based on the calculation of the radiation model AP8, the geometrical factor is reduced to 0.002 cm²sr, while that of the MEPD on the FY-3E satellite is 0.005 cm²sr. Another difference is that the sensors in some directions are exposed to direct sunlight for 80 min every day on this orbit, depending on the attitude angle of the satellite, which is much worse than that on the FY-3E satellite. According to the calculation results of transmittance of photons through different materials, a 100 nm thickness nickel film is added in front of the sensors to eliminate light pollution completely. The test using a solar simulator shows that the measure is effective and the detector has no error count when the solar irradiance coefficient is 1.0. In addition, the Geant4 software is applied to simulate the particle transportation process under complete machine condition to check the contamination of electrons in the sensors in all directions after magnetic deflection. The data obtained in orbit show that the instrument works properly, and the data are in good agreement with the AP8 model. The observations of the MEPD on board the FY-4B satellite can provide important support for the safety of spacecraft and theoretical research related to space weather. Full article

Mobile service robots are expanding their use to outdoor areas affected by various weather conditions, but the outdoor environment directly affects the functional safety of robots implemented by vision-based safety-related sensors (SRSs). Therefore, this paper aims to set the fog as the environmental condition of the robot and to understand the relationship between the quantified value of the environmental conditions and the functional safety performance of the robot. To this end, the safety functions of the robot built using SRS and the requirements for the outdoor environment affecting them are described first. The method of controlling visibility for evaluating the safety function of SRS is described through the measurement and control of visibility, a quantitative means of expressing the concentration of fog, and wavelength analysis of various SRS light sources. Finally, object recognition experiments using vision-based SRS for robots are conducted at low visibility. Through this, it is verified that the proposed method is a specific and effective method for verifying the functional safety of the robot using the vision-based SRS, for low visibility environmental requirements. Full article