Purpose. To inspect the ability of the new testing algorithms of coal-water slurries moisture calculation to retain stability when working with experimental results that have natural random variation. Methodology. Symmetric variation has been artificially introduced into the values of binary material-water slurry dielectric permittivity, applied in appropriate testing algorithm of moisture calculation. Inspection of the testing algorithm ability to retain the calculated water content values stability have been done for the conditions, when each value of dielectric permittivity that enters the testing algorithm takes maximum or minimum inside the symmetric variation range. Results of such an inspection allowed detecting some negative features of the existing testing algorithms and producing a new testing algorithm with sufficient stability for the calculated moisture values of material-water slurries. Findings. When inspecting two testing algorithms for the calculated water content values conditionality, it was detected, in spite of our expectations, that variation of dielectric permittivity values in a rather small range of 0.1 % gives a significant dispersion of calculated moister values. This situation signified low conditionality for both testing algorithms. It caused the authors to generate the modified testing algorithm, able to provide a sufficient stability for the calculated binary coal-water system moisture values according to the results of its comparison with modern analogues with a help of Pyrson's test. Originality. Testing algorithms inspection for the calculated moisture values conditionality allowed generating more relevant testing algorithm of moisture calculating in binary systems and, as a result, increasing the accuracy of coal-water slurries moisture measurement. Practical value. Application of the two additive, two multiplicative and two additional test influences on the substance under consideration in a new testing algorithm allowed increasing moisture measurement accuracy for capacitance moisture meters by several times. It is provided at the expense of small testing algorithm sensitivity to the substance's variation of physicochemical structure and due to the conditionality increase for the calculated values of moisture.

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The water content in fuel–water emulsions can vary from 10% to 30%, and is under control during the process of emulsification. The main task of this study was to obtain near-linear static function for a water-cut meter with capacitive sensors, and to provide it with effective type-uncertainty compensation during the process of water–fuel emulsion moisture control. To fulfill the capacitive measurements, two capacitive sensors in the measuring channel and two capacitive sensors in the reference channel were used. The method of least squares and general linear regression instruments were used to obtain robust and near-linear transfer function of the capacitive water-cut meter. The prototype product of the water-cut meter was developed with the purpose of fulfilling multiple moisture measurements and checking the workability of the new transfer function. Values of moisture content for the new transfer function and the closest analog were compared with the help of dispersion analysis. The new transfer function provided minimal dispersions of repeatability and adequacy, and minimal F-test values, proving its better capability for type-uncertainty compensation and better adequacy for the nominal linear transfer function of the water-cut meter.