Table 6 Comparison of quantifiable indicators.

From: Innovative framework for fault detection and system resilience in hydropower operations using digital twins and deep learning

Indicator

Proposed framework

Baseline (traditional method)

Improvement

Fault detection accuracy (%)

97.8

85.3

+ 14.7

False positive rate (%)

2.1

8.5

-75.3

Fault detection response time (ms)

35

120

-70.8

System downtime (hrs/year)

15

48

-68.8

Computational efficiency (seconds/iteration)

0.23

1.12

-79.5

Digital twin model accuracy (%)

98.5

90.2

+ 9.2

Maintenance cost reduction (%)

25

–

–

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