Rotary Oven Partition Clogging Detection via Composite Flow Variable
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Solution Overview
Problem
Rotary fire furnaces face challenges in detecting partial clogging of partitions, which can lead to inadequate combustion air flow, potentially causing explosions and affecting the baking quality of carbonaceous blocks due to the reliance on flow measurements that can be masked by air infiltrations.
Innovation Solution
A method that analyzes real-time measurements in the preheating zone by defining a variable representing flue gas flow as a combination of flow rate, temperature, and static depression, using weighting coefficients to detect deviations outside a confidence interval, thereby identifying partial blockages without additional instrumentation and minimizing false alarms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If flow measurements are used to detect partition clogging, then detection capability is provided, but false alarms occur due to air infiltrations masking the measurements
Solution Approach 1:
The patent combines three measurement parameters (flow rate Q, temperature T, and static depression P) into a single composite variable R that represents flue gas flow. This merging of multiple measurement dimensions allows the system to detect partition clogging more reliably by considering the interrelationship between these parameters rather than relying on flow rate alone, thereby reducing false alarms caused by air infiltrations.
Solution Approach 2:
The system continuously monitors the composite variable R and compares it against a confidence interval derived from statistical analysis of normal operation data. When R falls outside this interval, the system generates an alarm signal. This feedback mechanism enables real-time detection and response to partition clogging conditions while filtering out normal variations through statistical thresholds.
2Measurement precision
If additional instrumentation is added to improve detection accuracy, then measurement precision improves, but device complexity increases
Solution Approach 1:
The patent makes existing measurements multi-functional by using the same flow rate, temperature, and static depression sensors for both process control and clogging detection purposes. The composite variable R and its confidence interval analysis enable clogging detection without requiring dedicated additional sensors, thereby improving detection precision while avoiding increased device complexity.
3Reliability
If statistical analysis with confidence intervals is used, then false alarms are minimized, but calculation complexity increases
Solution Approach 1:
The system performs preliminary statistical analysis during normal operation to establish confidence intervals for the composite variable R. These pre-established thresholds are then used for real-time clogging detection without requiring complex calculations during alarm-critical moments. This preliminary action minimizes false alarms while keeping real-time processing simple.
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 method effectively detects partial clogging of partitions, reducing the risk of explosions and ensuring consistent baking quality by adjusting furnace operations based on accurate detection, with a reliability demonstrated through minimal false alarms and consistent performance over time.
Implementation Method 1
a flow meter 12, slightly upstream, in the pipe 11a corresponding
Implementation Method 2
a temperature sensor (thermocouple) 13 for measuring the temperature of the combustion fumes on intake
Implementation Method 3
Pressure sensors to measure the pressure prevailing in each of the hollow partitions 6
Implementation Method 4
defining a variable Rx representative of the flue gas flow for a hollow partition of rank x among the hollow partitions of a chamber of the furnace, with a confidence interval of a population of variables R of at least several partitions of rank 1 to n of the chamber excluding Rx from a mean m and a standard deviation σ
Data Source
Figure 1
Figure 2~3
Figure 4~5
AI summary
The invention relates to a method that comprises defining a variable Rx representative of the smoke flow in an x-rank partition (6) in the chamber (2) of an oven (1), defining a confidence interval of the population of R variables of at least several partitions (6) ranking from 1 to n in the chamber (2), with the exclusion of Rx, from an average m and a typical deviation s of the R variables, checking at consecutive moments if Rx is outside the F confidence interval by a lower value and, if such is the case, providing an alarm signal indicative of an at least partial clogging of at least one partition (6) in the partition line to which the x-rank partition (6) belongs and/or controlling at least one modification of the operational adjustment of the oven (1). The invention can be used for detecting clogged hollow partitions in a so-called rotating-heat chamber oven.