Vibration Signal Modulation Using Particle Swarm Optimization
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Solution Overview
Problem
Existing vibration signal modulation methods are limited by a modulation process and cannot adaptively establish mechanism models for different application objects, resulting in poor modulated vibration signals and low efficiency.
Innovation Solution
A vibration signal modulation method based on particle swarm optimization, which sets signal accelerating and braking section parameters to perform iterative searches using a particle swarm algorithm, optimizing braking parameters to superpose signals and achieve a final vibration signal tailored to the application object.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a traditional vibration signal modulation method is used, then the modulation process is simple, but the modulation efficiency is low and the vibration signal quality is poor
Solution Approach 1:
The patent applies preliminary action by pre-establishing mechanism models for different application objects (mobile phones, handles, vehicle steering wheels, screens) before the modulation process. These pre-established models contain pre-calculated parameters that can be directly applied when modulating vibration signals, eliminating the need for real-time complex calculations and significantly improving modulation efficiency while maintaining signal quality
Solution Approach 2:
The patent utilizes parameter changes by storing multiple sets of mechanism model parameters corresponding to different application objects. The system selects and applies the appropriate parameter set based on the target object, enabling efficient adaptation to different structures without re-establishing models, thus improving both modulation efficiency and signal quality
2Manufacturing precision
If an adaptive mechanism model is established for each application object, then the vibration signal quality improves, but the modulation process becomes more complex and time-consuming
Solution Approach 1:
The patent resolves this contradiction by performing the complex model establishment work in advance. Mechanism models for various application objects are pre-established and stored in a database. During actual vibration signal modulation, the system only needs to retrieve the pre-established model corresponding to the target object, which dramatically reduces the time required while maintaining high vibration signal quality
Solution Approach 2:
The patent applies copying by creating and storing replicated mechanism models for different application objects in advance. Once a model is established for a particular object type, it can be copied and reused for similar applications, eliminating the need to re-establish models repeatedly and reducing both time loss and processing complexity
3Adaptability or versatility
If the vibration device is adapted to different application objects with different structures, then the versatility improves, but the complexity of establishing mechanism models increases
Solution Approach 1:
The patent achieves universality by creating a unified mechanism model framework that can accommodate multiple application objects with different structures. The system uses a standardized approach to establish models for mobile phones, handles, vehicle steering wheels, and screens, allowing the same modulation system to serve multiple purposes without requiring fundamentally different modeling approaches
Solution Approach 2:
The patent applies segmentation by dividing the mechanism modeling process into distinct, manageable components for different application objects. Each application object has its specific mechanism model parameters stored separately, allowing the system to select and apply only the relevant segment corresponding to the target object, thereby managing complexity while maintaining versatility
Data Source
AI summary
A vibration signal modulation method includes following steps: setting a signal accelerating section parameter according to an expected vibration signal of an application object; setting a corresponding signal braking section parameter and a signal braking section parameter range, constructing a braking section initial particle parameter for a particle swarm algorithm, and performing an iterative search within the signal braking section parameter range to obtain an optimum braking parameter; and superposing a signal corresponding to the optimum braking parameter on a signal corresponding to the signal accelerating section parameter to obtain a final vibration signal. Compared with the related art, in the present disclosure, the signal accelerating section parameter is set, and a to-be-optimized particle swarm is set based on existing parameters. With a particle swarm optimization method, a braking section parameter is searched for, so that a vibration signal matching a current application object can be quickly found.