AI in fault detection and diagnosis – MCQs – EE

1. What is the primary purpose of AI in fault detection and diagnosis?
(A) To automatically identify and classify system faults
(B) To increase manual supervision
(C) To replace circuit breakers
(D) To design sensors

2. Which AI technique is most commonly used for fault detection in electrical systems?
(A) Artificial Neural Networks (ANN)
(B) Fourier Series
(C) Boolean Logic
(D) Linear Regression

3. Fault detection aims to:
(A) Identify abnormal conditions before system failure
(B) Increase downtime
(C) Disable protection systems
(D) Replace automation

4. The main benefit of using AI for fault diagnosis is:
(A) Faster and more accurate fault identification
(B) Increased human error
(C) Manual decision-making
(D) Slower system response

5. Which AI method is effective for detecting nonlinear faults in power systems?
(A) Neural Networks
(B) Boolean Logic
(C) Ohm’s Law
(D) Linear Models

6. AI-based fault classification can distinguish between:
(A) Different types and locations of faults
(B) System components only
(C) Manual inputs
(D) Power ratings

7. The training data for AI fault detection systems usually consists of:
(A) Historical fault and normal operating data
(B) Random measurements
(C) Only theoretical data
(D) Voltage ratings only

8. Fuzzy logic systems are suitable for fault diagnosis because they:
(A) Handle uncertainty and imprecise data effectively
(B) Depend only on exact thresholds
(C) Require binary inputs
(D) Ignore uncertainty

9. Expert systems for fault diagnosis use:
(A) Knowledge-based rules and inference mechanisms
(B) Manual testing procedures
(C) Random guessing
(D) Boolean switches

10. The input features for an AI-based fault detection system may include:
(A) Voltage, current, frequency, and temperature data
(B) Only voltage ratings
(C) Mechanical dimensions
(D) Material color

11. Which machine learning algorithm is commonly used for fault classification?
(A) Support Vector Machine (SVM)
(B) Fourier Transform
(C) Boolean Function
(D) PID Controller

12. In AI-based systems, pattern recognition helps in:
(A) Identifying fault signatures from data
(B) Designing sensors
(C) Increasing resistance
(D) Measuring power factor

13. The process of training an AI fault model involves:
(A) Adjusting model parameters to minimize detection error
(B) Manual calculation of thresholds
(C) Increasing noise
(D) Reducing data accuracy

14. Which AI technique can learn from real-time streaming data?
(A) Deep Learning models
(B) Boolean Logic
(C) Relay-based logic
(D) Static Regression

15. Genetic Algorithms (GA) can be used in fault detection for:
(A) Optimizing the diagnostic model parameters
(B) Designing new relays
(C) Replacing control loops
(D) Simplifying circuits

16. AI helps in predictive fault detection by:
(A) Analyzing patterns to forecast possible failures
(B) Waiting for faults to occur
(C) Stopping the system manually
(D) Ignoring historical data

17. Anomaly detection in AI identifies:
(A) Data patterns that deviate from normal behavior
(B) Only normal conditions
(C) Predefined inputs
(D) Binary states

18. In power transformers, AI-based fault diagnosis can detect:
(A) Insulation degradation and winding faults
(B) Frequency mismatch
(C) Manual switch failures
(D) Cable color

19. Which AI model is best suited for sequential fault data analysis?
(A) Recurrent Neural Network (RNN)
(B) Linear Regression
(C) Decision Tree
(D) Boolean Model

20. In fuzzy logic-based fault detection, a rule may look like:
(A) IF temperature is high AND current is low THEN fault = minor
(B) IF load = 0 THEN voltage = ∞
(C) IF current = 0 THEN power = 0 always
(D) IF logic = 1 THEN output = 0

21. The defuzzification process in fuzzy systems converts:
(A) Fuzzy outputs into crisp fault decisions
(B) Binary inputs into fuzzy sets
(C) Voltage into current
(D) Rules into signals

22. The accuracy of an AI fault detection system depends on:
(A) Quality and diversity of training data
(B) Hardware voltage ratings
(C) Number of resistors used
(D) System color

23. AI-based condition monitoring systems primarily use:
(A) Sensor data and real-time analytics
(B) Manual readings
(C) Paper logs
(D) Relay signals only

24. Which AI method can adaptively learn to improve fault detection over time?
(A) Reinforcement Learning (RL)
(B) Static Regression
(C) Boolean Algebra
(D) Linear Model

25. The confusion matrix is used to:
(A) Evaluate fault classification performance
(B) Display voltage readings
(C) Compare circuits
(D) Plot resistance curves

26. AI-based fault isolation means:
(A) Identifying the specific location or component causing the fault
(B) Disconnecting the whole system
(C) Resetting protection relays
(D) Increasing resistance

27. Deep Neural Networks (DNNs) are useful in complex fault detection because:
(A) They can model non-linear and high-dimensional data
(B) They require no data
(C) They use simple arithmetic
(D) They ignore noise

28. AI-based fault-tolerant control systems aim to:
(A) Maintain operation even when faults occur
(B) Shut down at every minor fault
(C) Bypass automation
(D) Eliminate redundancy

29. The main advantage of AI over traditional fault detection methods is:
(A) Ability to handle large data and detect hidden faults automatically
(B) Dependence on manual thresholds
(C) Need for constant supervision
(D) Simpler logic circuits

30. The ultimate goal of AI in fault detection and diagnosis is to:
(A) Enhance reliability, minimize downtime, and prevent failures proactively
(B) Increase manual fault analysis
(C) Simplify circuit drawing
(D) Delay fault response