Coal sample viscosity distinguishing method used for coal sample collection and preparation integration

Abstract

The invention discloses a coal sample viscosity distinguishing method used for coal sample collection and preparation integration. The method comprises the following steps: S1. monitoring the coal sample viscosity in real time: during normal operation of collection and preparation integrated coal sample detection equipment, monitoring the current value of a driving motor in a rotary wiping device in the integrated coal sample detection equipment in real time when coal samples pass through a rotary wiping position; S2. in the continuous monitoring process in the step S1, taking the current value of the driving motor at a certain period of time or at a given time, comparing the current value with the current value of the driving motor at a later certain period of time or at a later given time along with the continuity of time, and analyzing the variation trend of alternating current according to the comparison value to judge the coal sample viscosity. The method has the advantages of simple principle, extreme simplicity and convenience in operation, high precision, and the like.

Description

Technical field [0001] The invention mainly relates to the field of integrated coal sample extraction and preparation equipment, and particularly refers to a coal sample viscosity determination method suitable for the integration of coal sample extraction and preparation. Background technique [0002] Due to different coal sources, coal varieties, grades, and batches, some coal may encounter coal sticking, coal blocking, and equipment jams when entering the sampling and sample preparation links. For this reason, it is necessary to pass some early resolutions to make the sampling, sample preparation, and the process between sampling and sample preparation proceed smoothly. Under the premise of ensuring the degree of automation, the reliability and accuracy of sample preparation can be improved. The traditional methods are not designed based on fully automatic production operations, so they have the following shortcomings: [0003] In the entire sampling and sample preparation proce...

AI Technical Summary

Problems solved by technology

However, due to the strong subjectivity of artificial recognition, there are often phenomena such as missed judgments and misjudgments.

Therefore, before the coal enters the sampling system, a special person is required to be on duty and make judgments. The coal that cannot be processed by the automatic sampling equipment must be manually separated by workers, which results in its high labor intensity, long cycle time, and poor accuracy.

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