Vibratory Conveyor Load Estimation Using Sensor Regression Models
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Solution Overview
Problem
Existing methods for determining bulk material feed rates in vibratory machines are hindered by oscillating movements and vibrations, making it difficult to accurately measure weight using load cells or force sensors, and require individual empirical or theoretical determination of relationships between vertical acceleration and drive frequency.
Innovation Solution
A method utilizing raw measurement data from acceleration, velocity, or displacement sensors, processed through an AI-based learning algorithm to create a regression model that accounts for individual vibratory machine characteristics, including mass, geometry, and bulk material properties, to predict bulk material load.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If load cells or force sensors with strain gauges are used to measure weight, then weight measurement capability is provided, but measurement precision deteriorates due to oscillating movements and vibrations in the resonance range
Solution Approach 1:
The patent replaces mechanical weight measurement systems (load cells with strain gauges) with an indirect measurement system using acceleration sensors. Instead of directly measuring weight through mechanical deformation, the system measures vertical acceleration and combines it with drive frequency data to calculate conveyor capacity, thereby avoiding the interference of vibrations in the resonance range that plague direct mechanical measurement methods
Solution Approach 2:
The patent introduces an intermediary calculation approach using the relationship between vertical acceleration, drive frequency, and conveyor capacity. Rather than directly measuring weight, the system uses acceleration as an intermediary parameter that can be measured without being affected by resonance vibrations, then derives the conveyor capacity through this intermediary relationship
2Adaptability or versatility
If individual empirical or theoretical determination of relationships between vertical acceleration and drive frequency is performed, then measurement adaptability is improved, but device complexity and time consumption increase
Solution Approach 1:
The patent performs preliminary empirical determination of the relationship between vertical acceleration, drive frequency, and conveyor capacity during the setup or commissioning phase. This preliminary characterization creates a lookup table or stored relationship that can be directly applied during operation, eliminating the need for complex real-time calculations or theoretical determinations while maintaining adaptability to specific machine characteristics
Solution Approach 2:
The patent creates a simplified model or lookup table that copies the essential characteristics of the complex relationship between acceleration, frequency, and conveyor capacity. Instead of performing complex empirical or theoretical determinations for each measurement, the system uses pre-determined relationships that capture the essential behavior, reducing computational complexity while maintaining accuracy
3Reliability
If traditional weight measurement methods are used, then direct weight information is obtained, but reliability deteriorates due to inability to account for vibratory machine characteristics
Solution Approach 1:
The patent implements a feedback mechanism where the measured conveyor capacity is continuously monitored and used to adjust or validate the determination process. The system compares measured values with expected ranges and can trigger recalibration or alert operators to异常情况, thereby improving reliability through continuous validation and adjustment based on actual operating conditions
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
Enables accurate and adaptive determination of bulk material feed rates, detecting overloads and underloads, and ensuring efficient utilization of vibratory machines by continuously updating the regression model to adapt to changing conditions.
Implementation Method 1
acceleration sensors are used to measure the vertical acceleration of the vibratory feeder
Implementation Method 2
Unbalance exciters have rotating unbalances or weights that transfer their acceleration forces to the vibratory body in order to cause it to vibrate
Data Source
AI summary
In a method for calculating a bulk material conveying rate or a bulk material load of a vibratory conveyor machine, in which method raw measured data from the vibratory conveyor machine are acquired at at least two times with different load states by at least one acceleration, speed or travel sensor and raw measured data are then processed to give at least one vibration data feature from the list: amplitude, frequency and phase, provision is made to create and to store feature datasets consisting of at least one vibration data feature and to create a regression model on the basis thereof. Based on the created regression model and at least one current feature dataset, the current actual load or bulk material conveying rate of a vibratory conveyor machine is then ascertained and displayed.