Motor Load Ratio Feedback Control for Mechanical Equipment

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Solution Overview

Problem

Mechanical equipment control systems face challenges in dynamically adjusting operation parameters while maintaining motor load ratios within allowable limits, leading to inefficiencies in production tasks such as production speed and equipment longevity.

Innovation Solution

A mechanical equipment control system incorporating a load ratio detection circuit and integration control circuit that monitors and adjusts motor load ratios using operation parameters, allowing for real-time adjustments through automatic and manual control modes, including deep learning-based adjustments to optimize production tasks.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If the mechanical equipment operates at high speed to improve productivity, then production speed increases, but the motor load ratio may exceed allowable limits causing equipment failure

Engineering Contradiction:
Improveproduction speedVSAvoidmotor load ratio
Core Design Contradiction:
ProductivityVSReliability

Solution Approach 1:

The control apparatus continuously monitors the load ratio of the motor and uses this feedback to dynamically adjust operation parameters. The load ratio detection circuit provides real-time information about motor stress levels, enabling the integration control circuit to modify operational settings to maintain reliable operation while maximizing productivity.

Inventive Principle:
Principle #23Feedback

Solution Approach 2:

The system dynamically adjusts operation parameters based on real-time load ratio conditions rather than using fixed settings. This allows the mechanical equipment to adapt its speed and other parameters dynamically, optimizing productivity when load conditions permit while preventing excessive load situations that would compromise reliability.

Inventive Principle:
Principle #15Dynamics

2Productivity

If the mechanical equipment operates continuously to improve productivity, then production output increases, but equipment longevity decreases due to excessive motor load

Engineering Contradiction:
Improveproduction outputVSAvoidequipment longevity
Core Design Contradiction:
ProductivityVSDuration of action of stationary object

Solution Approach 1:

Continuous monitoring of motor load ratio provides feedback that enables the control system to detect approaching excessive load conditions before they cause damage. This allows for preventive adjustment of operation parameters, enabling continuous operation at high productivity levels while preventing the excessive stress that would reduce equipment longevity.

Inventive Principle:
Principle #23Feedback

Solution Approach 2:

The system prepares for potential excessive load conditions by continuously monitoring load ratios and making preventive adjustments before damage occurs. The control apparatus cushions against equipment failure by detecting early signs of excessive stress and adjusting parameters to maintain safe operating levels throughout extended production cycles.

Inventive Principle:
Principle #11Beforehand cushioning (Prior cushioning)

3Reliability

If the control system frequently adjusts operation parameters to maintain load ratios, then motor reliability improves, but system complexity increases

Engineering Contradiction:
Improvemotor reliabilityVSAvoidcontrol system complexity
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The control system performs self-adjustment based on automatic load ratio detection without requiring complex external intervention. The integration control circuit autonomously modifies operation parameters in response to load ratio changes, reducing the need for complex manual control mechanisms while maintaining high motor reliability through continuous self-regulation.

Inventive Principle:
Principle #25Self-service

4Productivity

If deep learning-based adjustments are implemented to optimize production tasks, then productivity and efficiency improve, but device complexity and computational requirements increase

Engineering Contradiction:
Improveproduction efficiencyVSAvoidcontrol algorithm complexity
Core Design Contradiction:
ProductivityVSDevice complexity

Solution Approach 1:

The deep learning model performs preliminary learning during idle periods or between production cycles, preparing optimized control strategies in advance. This allows the system to implement sophisticated productivity optimization through pre-computed adjustments without adding real-time computational complexity to the production process itself.

Inventive Principle:
Principle #10Preliminary action

Data Source

PatentUS11397414B2Mechanical equipment control system, control apparatus for mechanical equipment, and method for controlling mechanical equipment
Publication Date: 2022.07.26 YASKAWA DENKI KK
  • US11397414B2 patent drawing
  • US11397414B2 patent drawing
  • US11397414B2 patent drawing

AI summary

A mechanical equipment control system includes a mechanical apparatus, a load ratio detection circuit, and an integration control circuit. The mechanical apparatus includes a motor which is configured to drive the mechanical apparatus. The load ratio detection circuit is configured to detect a load ratio of the motor. The integration control circuit is configured to control the mechanical apparatus based on an operation parameter while keeping the load ratio in an allowable load state.