The calibration industry is renowned for its diverse and sophisticated equipment and complex processes, which necessitate innovative solutions to keep pace with rapidly advancing technology. This paper introduces an enhancement to an existing microservice-based cloud architecture, aimed at effectively managing the inherent complexity within this field. The enhanced architecture seamlessly integrates various equipment types and communication technologies, aligning diverse stakeholder expectations into a unified system that ensures efficient and accurate calibration processes. It highlights the integration of microservices to facilitate various methods of uncertainty calculation and the generation of digital calibration certificates (DCCs). A case study on RF power measurement illustrates the practical application and benefits of the enhanced architecture. Although initially focused on RF power measurement, the flexible architecture allows for future expansions to accommodate new standards and measurement techniques. The enhanced system offers a comprehensive approach to managing data flow from calibration equipment to the final generation of DCCs, utilizing cloud-based services for efficient data processing. As a future direction, this extension sets the groundwork for broader applicability across multiple measurement types, ensuring readiness for upcoming advancements in metrology.

AUTORFPOWER software has been developed for automatic RF power measurement at microwave frequencies. In this study, the capabilities of AUTORFPOWER are explained and compared with commercial alternatives. The advantages of the developed software to metrological works and its contributions to future metrological R&D are discussed.

The aim of this paper is to compare the power measurement capabilities in millimetre- and sub-millimetre-wave frequency bands of several national metrology institutes and one research institute. The first comparison, in WR-6.5 waveguide (110 GHz to 170 GHz), involved NPL, TUBITAK UME and PTB. The second comparison, in WR-1.5 waveguide (500 GHz to 750 GHz), involved NPL, METAS, TUBITAK UME, LNE, WAT, GUM and VDI. Two types of travelling standards were used for these comparisons: a thermoelectric power sensor in the WR-6.5 band and a calorimetric power sensor in the WR-6.5 and WR-1.5 bands. The thermoelectric power sensor was characterised by the participants against their own standards and a generalised effective efficiency was calculated. The calorimetric power sensor operating in the WR-6.5 band was measured to observe its behaviour during the comparison and was also measured in the WR-1.5 band after being fitted with a suitable waveguide taper and used in conjunction with a frequency multiplier. The participants measured the output of the calorimetric power sensor and their own power sensor standard. A normalised power ratio method was used as a comparison parameter for the WR-1.5 band measurements. In addition, a pyroelectric power standard was used by METAS to measure absolute power, and a frequency of 650 GHz was used as a link between the absolute power and the power ratios. Finally, all but two of the measurement points compared between the participants achieved agreement in terms of $\left|E_n\right|$ scores less than 1. For the first time, an interlaboratory comparison of power measurements at sub-millimetre frequencies has been performed and, overall, good agreement was achieved between the different laboratories.

Most calibration laboratories prefer the Direct Comparison Transfer Method (DCTM) for a reliable and accurate calibration of power sensors in the radio frequency (RF) scope. Most studies suggest using this calibration method, with its automatic power level control (APLC) of RF signal generators. The APLC is preferred to keep the output power level of the signal generator the same, while the power sensor is calibrated and the reference power sensor is connected to the measurement system. The known APLC mechanisms are also explained for the DCTM, and a comparison of the calibration factor values carried out with and without the automatic power level control process in the DCTM is also given in this study. RF power sensor calibrations with coaxial and waveguide connector types are examined with DCTM in this study as well. This study shows that the DCTM, unless with APLC, should be applied for the waveguide power sensor’s calibration at millimeter wave frequencies.

RF power measurement is essential in RF and microwave metrology. For reliable and accurate power measurement, automatic measurement is preferred. A software application in C#, named AutoRFPower, was developed for automatic RF power measurement and uncertainty calculations at this study. According to the GUM document, this application is enhanced for uncertainty calculations by utilizing the Law of Propagation method and the Monte Carlo Simulation method. Trial measurements were performed at different RF power levels and frequencies between 50 MHz and 18 GHz using the AutoRFPower software. Law of Propagation and Monte Carlo Simulation uncertainty calculations were carried out by AutoRFPower based on the trial measurements and by the Oracle Crystal Ball simulation application. All measurements and their uncertainty calculations were compared with each other, and this study validated the uncertainty calculation of AutoRFPower. In addition, it was observed that in the Monte Carlo Simulation, uncertainty calculation results were non-symmetrical normal distribution, contrary to the assumption of symmetrical normal distribution according to the Low of Propagation method. Moreover, it has been observed that the statistical distribution of uncertainty changes depending on the dominant component of the parameters in the model function used for the uncertainty calculation with the Monte Carlo Simulation method.

Radio Frequency (RF) power sensor calibration is one of the essential measurements in RF and microwave metrology. For a reliable and accurate power sensor calibration, there are various methods, such as the substitution method, the direct comparison transfer method (DCTM), and the vector network analyzer (VNA)-based calibration method (VBCM). The VBCM is a method that is derived from the DCTM. It is a preferred method since the VNA has a better measurement capability and has fewer connection requirements for measurement devices. In this study, the milestones and potential application errors of the VBCM are given by considering the connection mistakes, measurement faults, calculation errors, and control software coding problems. At the end of the power sensor calibration measurements with the VBCM, the model function components and the uncertainty calculation examples according to the GUM Bayesian method are also presented in this study. In addition, the advantages and disadvantages of the VBCM compared to the former methods are discussed in this study.