Wire Saw Pre-Cut Diagnosis Using Three Constant-Speed Modes
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Solution Overview
Problem
Existing wire saw devices struggle to fully monitor and perform precise abnormality diagnosis due to complex configurations requiring multi-axis synchronous control and changes in reel diameters during operation, making it difficult to maintain consistent operating states before cutting.
Innovation Solution
The implementation of a three-diagnosis mode system where the wire saw operates at constant rotational speeds for processing rollers, feed reel, and take-up reel, acquiring and comparing data groups to calculate deviation information and determine operational abnormalities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If the wire saw operates at constant linear speed during cutting, then the cutting process is stable, but the effective diameters of feed reel and take-up reel change continuously making precise abnormality diagnosis difficult
Solution Approach 1:
The system performs abnormality diagnosis before cutting by operating in three distinct diagnosis modes where each component (processing rollers, feed reel, take-up reel) is tested individually at constant rotational speeds. This preliminary testing establishes baseline data when the system is known to be normal, enabling accurate abnormality detection before the cutting process begins.
Solution Approach 2:
The diagnosis process is divided into three separate diagnosis modes: first mode tests processing rollers at constant rotational speed, second mode tests feed reel at constant rotational speed, and third mode tests take-up reel at constant rotational speed. This segmentation isolates each component's behavior, making it easier to identify specific abnormalities without the complexity of simultaneous multi-component variations during cutting.
2Productivity
If the wire saw uses multi-axis synchronous control for processing rollers, feed reel, and take-up reel, then the cutting operation is efficient, but the operating state varies making full monitoring difficult
Solution Approach 1:
The monitoring system is segmented into three independent diagnosis modes, each focusing on one component at a time. The first diagnosis mode monitors processing rollers, the second monitors feed reel, and the third monitors take-up reel. This segmentation allows complete monitoring of each component's operating state under controlled conditions, preventing information loss that would occur with simultaneous multi-component operation.
Solution Approach 2:
The system acquires operating state data in each diagnosis mode and compares it against reference data obtained when the wire saw is known to be normal. This feedback mechanism identifies deviations from normal operation, ensuring complete monitoring information is captured and analyzed for each component before cutting begins.
3Ease of repair
If maintenance grinds grooves in processing rollers to repair them, then the processing rollers can be reused, but the effective diameters change to smaller diameters affecting operation
Solution Approach 1:
The system performs diagnosis before cutting to detect any changes in processing roller effective diameters caused by maintenance grinding. By establishing baseline measurements when rollers are new and comparing them after maintenance, the system identifies diameter changes before they affect cutting operation, allowing for compensatory adjustments or further maintenance planning.
Data Source
AI summary
A wire saw abnormality diagnosis device and a wire saw abnormality diagnosis method are provided. The abnormality diagnosis device includes: a diagnosis mode executer that executes a first diagnosis mode, a second diagnosis mode, and a third diagnosis mode before the cutting; a data group acquirer that acquires a first data group, a second data group, and a third data group for pluralities of data items indicating operating states of the wire saw; a deviation information calculator that calculates deviation information relating to deviations derived by comparing a first reference data group, a second reference data group, and a third reference data group with the first data group, the second data group, and the third data group for the pluralities of data items; and a determiner that determines presence or absence of an abnormality in the wire saw based on the calculated deviation information.