Creping Blade Vibration Indexing for Chatter Prediction
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Solution Overview
Problem
The creping process in tissue manufacturing is hindered by excessive vibration of the creping doctor blade, leading to chatter conditions that result in product defects, machine downtime, and costly repairs to the Yankee dryer, complicating data analysis and maintenance due to dynamic operational variations.
Innovation Solution
A method involving data tracking and analysis using sensors to measure and assign scores to vibration data, generating an index score that predicts blade replacement time and evaluates Yankee dryer performance, thereby preventing damage and optimizing creping process efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If vibration sensors continuously monitor creping blade vibration during operation, then chatter conditions and Yankee dryer damage can be detected early, but data complexity increases making analysis more difficult
Solution Approach 1:
The patent extracts only the most relevant vibration characteristics from the complex sensor data stream. By focusing on specific frequency ranges, vibration amplitudes, and temporal patterns that indicate chatter conditions, the system filters out irrelevant information while retaining critical diagnostic data about blade condition and Yankee dryer health
Solution Approach 2:
The patent replaces complex manual data analysis with automated signal processing algorithms and machine learning models. These computational systems automatically interpret vibration patterns, identify chatter conditions, and predict maintenance needs, substituting human analytical complexity with algorithmic processing that handles large datasets efficiently
2Reliability
If creping doctor blade is monitored and replaced proactively to prevent chatter, then product quality and machine runnability improve, but blade replacement frequency may increase causing production loss
Solution Approach 1:
The patent implements preliminary monitoring and prediction of blade degradation before actual chatter conditions occur. By tracking vibration trends and predicting remaining blade life, the system schedules replacements during planned maintenance windows rather than reacting to failures, ensuring product quality while minimizing unplanned production interruptions
Solution Approach 2:
The patent dynamically adjusts maintenance schedules based on actual blade condition and operational parameters. Rather than fixed replacement intervals, the system adapts maintenance timing to real-time vibration data, blade usage patterns, and production requirements, optimizing the balance between quality assurance and production continuity
3Reliability
If operational parameters are adjusted to reduce vibration without interrupting production, then chatter conditions can be mitigated, but process complexity and difficulty of detecting optimal settings increase
Solution Approach 1:
The patent implements closed-loop feedback control where vibration sensor data continuously monitors blade condition and operational parameters. The system automatically adjusts parameters such as blade pressure, speed, or positioning based on real-time vibration measurements, creating a self-regulating system that reduces chatter while adapting to changing production conditions without manual intervention
Solution Approach 2:
The patent systematically varies operational parameters within defined ranges to identify optimal settings that minimize vibration. By testing and analyzing the relationship between parameters (pressure, speed, temperature) and vibration responses, the system establishes parameter profiles for different blade conditions and production rates, simplifying the complex parameter space into actionable guidelines
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach simplifies data complexity, reduces maintenance downtime, and enhances product quality by accurately predicting blade replacement and preventing Yankee dryer damage, thus improving overall creping process efficiency and asset management.
Implementation Method 1
measuring vibration of a creping blade using one or more vibration sensors
Data Source
AI summary
The disclosure is directed to techniques for tracking data associated with a creping process. The techniques include measuring process data, wherein the process data includes vibration data, and wherein measuring process data includes measuring vibration data of a creping blade using one or more vibration sensors. The techniques further include assigning a score for the process data, including assigning a vibration score for the vibration data. The techniques also include generating an index score based on the score for the process data and the vibration score for the vibration data.