CyberTRIZPEDIA

Fault Detection Sensitivity vs False Alarms

Implement multi-evidence, context-sensitive fault detection to meet safety integrity requirements while eliminating nuisance alarms that erode operator trust and response quality.

CyberTRIZ analysis · Space contradiction RMA016 · one of 8,235 worked contradictions published by CyberTRIZ.AI

Regulations

Business Context

Sensitive fault-detection systems can identify abnormal spacecraft behavior early, allowing corrective action before failures propagate. However, increasingly sensitive thresholds can interpret normal variation, sensor noise, or temporary environmental effects as faults. Frequent false alarms can trigger unnecessary recovery actions and increase operator workload.

Space TRIZ Resolution

Fault detection should combine multiple sources of evidence rather than depend exclusively on fixed thresholds. Trends, correlated measurements, operating context, persistence criteria, and model-based expectations can distinguish genuine degradation from temporary variation. Detection sensitivity can also change according to mission phase and system condition.

Applicable TRIZ Principles

Principle 3 – Local Quality applies different detection criteria according to equipment and operating conditions.

Principle 15 – Dynamics adjusts fault thresholds according to mission state.

Principle 23 – Feedback combines current and historical system behavior to refine fault identification.

Expected Outcome

Earlier detection of genuine faults

Fewer false alarms

Reduced unnecessary recovery actions

Improved operator attention management

Decision Indicators

Early indicators include:

Operators routinely disregard automated warnings.

Safe modes are triggered by temporary parameter excursions.

Fixed thresholds generate different results under changing mission conditions.

Alarm frequency increases without corresponding equipment failures.

Individual measurements trigger responses without corroborating evidence.

TRIZ principles applied

P3 Local qualityP15 DynamicsP23 Feedback