Dynamic Multi-Parameter Sampling for Gateway Load and Data Loss

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Solution Overview

Problem

In industrial automation, the large number of terminal devices with varying high sampling rates leads to resource overload, slow response times, data loss, and system crashes due to limited processing capacity in intelligent gateways, affecting data analysis and fault diagnosis.

Innovation Solution

Implementing a multi-parameter dynamic sampling method that dynamically adjusts sampling rates, prioritizes parameters, and performs down-sampling or up-sampling based on load conditions to prevent data loss and improve sampling reliability, while ensuring the highest priority parameters are not adjusted.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If high sampling rates are used for all parameters, then data acquisition completeness is improved, but system load increases and causes data loss

Engineering Contradiction:

Improvedata acquisition completenessVSAvoidsystem load

Core Design Contradiction:

ReliabilityVSQuantity of substance

Solution Approach 1:

The patent dynamically changes the sampling rate parameter for different parameters based on their importance and current system conditions. High-priority parameters maintain high sampling rates while low-priority parameters use lower sampling rates, optimizing the balance between data completeness and system load.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

Different sampling rates are assigned to different parameters based on their local requirements. Critical parameters receive high sampling rates for complete data acquisition, while non-critical parameters use lower sampling rates to reduce overall system load.

Inventive Principle:

Principle #3Local quality

2Reliability

If high sampling rates are used for all parameters, then data loss is reduced, but terminal device resources are overloaded

Engineering Contradiction:

Improvesampling reliabilityVSAvoidterminal device resources

Core Design Contradiction:

ReliabilityVSUse of energy by moving object

Solution Approach 1:

The sampling rate parameter is dynamically adjusted for each parameter based on its priority level. This allows the system to maintain high sampling reliability for critical parameters while reducing resource consumption for non-critical parameters.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

Instead of applying high sampling rates to all parameters (excessive action), the system applies high sampling rates only to necessary critical parameters (partial action), thereby reducing overall resource usage while maintaining adequate sampling reliability.

Inventive Principle:

Principle #16Partial or excessive action

3Measurement precision

If intelligent gateway processes all parameters at high sampling rates, then data analysis accuracy is improved, but gateway processing capacity is exceeded

Engineering Contradiction:

Improvedata analysis accuracyVSAvoidgateway processing capacity

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The gateway processes different parameters with different sampling rates according to their local importance. Critical parameters are processed with high sampling rates for accurate analysis, while non-critical parameters use lower sampling rates to prevent gateway overload.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The system dynamically changes the sampling rate parameter for parameters being processed by the gateway, adjusting the balance between data analysis accuracy and gateway processing capacity based on current system conditions.

Inventive Principle:

Principle #35Parameter changes

4Adaptability or versatility

If multiple sampling rates are configured for each parameter, then sampling flexibility is improved, but system complexity increases

Engineering Contradiction:

Improvesampling flexibilityVSAvoidsampling rate configuration

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system implements dynamic sampling rate selection where multiple sampling rates are configured for each parameter, but the actual sampling rate is dynamically chosen based on priority levels and system conditions. This provides sampling flexibility while managing complexity through automated selection.

Inventive Principle:

Principle #15Dynamics

Data Source

PatentUS11921499B2Multi-parameter dynamic sampling method and multi-parameter dynamic sampling device

Publication Date: 2024.03.05 SIEMENS AG

AI summary

The present disclosure describes multi-parameter dynamic sampling methods and systems. An example method includes: configuring two sampling rates for each parameter in a set of sampling parameters; selecting one of the sampling rates for each parameters to sample it; calculating a load for each parameter at the selected sampling rate, sorting the parameters according to the loads, and determining high-loaded parameters according to a sorting result; and determining whether each parameter has data loss, and if at least one of the sampling parameters has data loss, performing down-sampling on the high-loaded sampling parameters within a range of the configured at least two sampling rates.