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After the training phase is completed, the parameters of the dynamic neural networks are

Figure 44 After the training phase is completed, the parameters of the dynamic neural networks are

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And last, but definitely not least, I would like to thank my amazing wife Karla for her infinite (MIDEPLAN) for economically supporting me during the entire period of study and research.
And last, but definitely not least, I would like to thank my amazing wife Karla for her infinite (MIDEPLAN) for economically supporting me during the entire period of study and research.
To avoid the occurrence of these failures, an FDI system must detect and isolate the faults to
To avoid the occurrence of these failures, an FDI system must detect and isolate the faults to
in Figure 2.3, a qualitative model-based method called Fault-Tree technique is used as the engine unmanned space vehicle has been investigated by the approach that is proposed in [28]. As shown
in Figure 2.3, a qualitative model-based method called Fault-Tree technique is used as the engine unmanned space vehicle has been investigated by the approach that is proposed in [28]. As shown
A simulated ACS-model was used to generate the database for the automatic construction of as attributes with specific numerical value. Finally, the correct combination of this attributes the above fault-tree system. The attributes selected are: reaction wheel motor current, reaction analysis purposes. From the database example, preliminary information is extracted and labeled
A simulated ACS-model was used to generate the database for the automatic construction of as attributes with specific numerical value. Finally, the correct combination of this attributes the above fault-tree system. The attributes selected are: reaction wheel motor current, reaction analysis purposes. From the database example, preliminary information is extracted and labeled
The proposed FDI system in [27] includes two different structures: a dynamic neural perform the tasks of detection and isolation. As shown in Figure 2.5, neural networks are network for detection and a static neural network for isolation. The composition of a multilaye
The proposed FDI system in [27] includes two different structures: a dynamic neural perform the tasks of detection and isolation. As shown in Figure 2.5, neural networks are network for detection and a static neural network for isolation. The composition of a multilaye
Using a simulated ACS-model, healthy and faulty data set from a reaction wheel actuator
Using a simulated ACS-model, healthy and faulty data set from a reaction wheel actuator
important and research efforts in this field are needed.
important and research efforts in this field are needed.
the z-axis (right-handed rule). Figure 3.1 shows the axes of the Earth Centered Inertial (ECI) Earth, parallel to the rotation axis of the Earth, and the y-axis is perpendicular to the x-axis and center of the Earth, but rotates with it. The x-axis points to the Greenwich meridian in the
the z-axis (right-handed rule). Figure 3.1 shows the axes of the Earth Centered Inertial (ECI) Earth, parallel to the rotation axis of the Earth, and the y-axis is perpendicular to the x-axis and center of the Earth, but rotates with it. The x-axis points to the Greenwich meridian in the
satellite. This coordinate system is mainly used for attitude calculations and to describe relative positions and directions of the satellite. Figure 3.3 shows the system axes.
satellite. This coordinate system is mainly used for attitude calculations and to describe relative positions and directions of the satellite. Figure 3.3 shows the system axes.
Figure 3.4. Orbit Reference Frame (Nadir pointing frame). 3.2.2 Attitude Representation
Figure 3.4. Orbit Reference Frame (Nadir pointing frame). 3.2.2 Attitude Representation
where the superscript ‘b’ indicates the satellite body fixed CS.
where the superscript ‘b’ indicates the satellite body fixed CS.
Similar to the dynamic equations, the kinematic equations can be written as quaternion quaternion and rates, Equations (3.13) and (3.14) can represent the kinematics of the spacecraft.
Similar to the dynamic equations, the kinematic equations can be written as quaternion quaternion and rates, Equations (3.13) and (3.14) can represent the kinematics of the spacecraft.
conditions given by Equation (3.22). leaderp where sys,i 18 the producible torque in the direction of the i-th axis. Finally, in order to avoid the activation of the actuators for small values of “““’Tyom,;, it is desirable to include a deadband
conditions given by Equation (3.22). leaderp where sys,i 18 the producible torque in the direction of the i-th axis. Finally, in order to avoid the activation of the actuators for small values of “““’Tyom,;, it is desirable to include a deadband
Figure 3.6. (a) Attitude Control Subsystem for a Leader Spacecraft and (b) Attitude Control Subsystem for a Follower Spacecraft. shows the complete ACS for the leader and the followers respectively. spacecraft are equipped with a system of Pulsed Plasma Thrusters (PPTs). Figure 3.6 (a) and (b) In Chapter 2, we have indicated that a controlled system is composed of the dynamic plant
Figure 3.6. (a) Attitude Control Subsystem for a Leader Spacecraft and (b) Attitude Control Subsystem for a Follower Spacecraft. shows the complete ACS for the leader and the followers respectively. spacecraft are equipped with a system of Pulsed Plasma Thrusters (PPTs). Figure 3.6 (a) and (b) In Chapter 2, we have indicated that a controlled system is composed of the dynamic plant
(LES-8/9) [59], [60] and [94]. As shown in Figure 3.7, the main components are the capacitor, the Parallel-Plate Ablative PPT similar to the one utilized in the Lincoln Experimental Satellite 8/9
(LES-8/9) [59], [60] and [94]. As shown in Figure 3.7, the main components are the capacitor, the Parallel-Plate Ablative PPT similar to the one utilized in the Lincoln Experimental Satellite 8/9
L,+L,+Ly-. Equations (3.32) and (3.33) provide expressions for R, and L,,(t) respectively, and the
L,+L,+Ly-. Equations (3.32) and (3.33) provide expressions for R, and L,,(t) respectively, and the
where x, is the position, x2 is the capacitor charge, x; is the velocity and x, is the current, v is the
where x, is the position, x2 is the capacitor charge, x; is the velocity and x, is the current, v is the
we consider the so-called six-independent PPT configuration (refer to Figure 3.9). spacecraft where independent control actuation is achieved. Equations (3.36) and (3.37) show the
we consider the so-called six-independent PPT configuration (refer to Figure 3.9). spacecraft where independent control actuation is achieved. Equations (3.36) and (3.37) show the
where T;,;; is the magnitude that the i-th thruster generates in the direction of the j-axis. The torque matrix and the total control torque that is applied to the satellite respectively:
where T;,;; is the magnitude that the i-th thruster generates in the direction of the j-axis. The torque matrix and the total control torque that is applied to the satellite respectively:
Table 3.11. Nullspace Vectors for the Six-Independent PPT Configuration. Eth as shown in Equations (3.34) and (3.35) are specified in Table 3.TIII.
Table 3.11. Nullspace Vectors for the Six-Independent PPT Configuration. Eth as shown in Equations (3.34) and (3.35) are specified in Table 3.TIII.
chapters of this thesis to simulate attitude maneuvers under normal and abnormal PPT’s
chapters of this thesis to simulate attitude maneuvers under normal and abnormal PPT’s
well as the settling time.
well as the settling time.
Figure 4.1. (c) Discharge Current with Measurement Noise (Healthy Scenario). equation (4.1). Figures 4.1 (a)-(c) show the behavior of capacitor voltage, thrust and discharge
Figure 4.1. (c) Discharge Current with Measurement Noise (Healthy Scenario). equation (4.1). Figures 4.1 (a)-(c) show the behavior of capacitor voltage, thrust and discharge
Figure 4.2. (c) Discharge Current with Measurement Noise (Faulty Scenario 1). used. Figures 4.2 (a) — (b) show the resulting simulated responses.
Figure 4.2. (c) Discharge Current with Measurement Noise (Faulty Scenario 1). used. Figures 4.2 (a) — (b) show the resulting simulated responses.
Figure 4.3. (c) Discharge Current with Measurement Noise (Faulty Scenario 2). the width of the electrodes w = 0.0254 m is changed to w = 0.02195 m. For this faulty scenario,
Figure 4.3. (c) Discharge Current with Measurement Noise (Faulty Scenario 2). the width of the electrodes w = 0.0254 m is changed to w = 0.02195 m. For this faulty scenario,
equation (4.1). 4.2.4 PPT Operation Under Faulty Scenario 3
equation (4.1). 4.2.4 PPT Operation Under Faulty Scenario 3
faulty scenario, the resistance of the electrodes R,- = 0.00 Q is changed to R,, = 0.008 Q. Figures
faulty scenario, the resistance of the electrodes R,- = 0.00 Q is changed to R,, = 0.008 Q. Figures
equation (4.1). The simulations for the above three faulty scenarios generate faults with severity of 15%. which is 15% less than the nominal value and is just bellow the lower limit that is defined by
equation (4.1). The simulations for the above three faulty scenarios generate faults with severity of 15%. which is 15% less than the nominal value and is just bellow the lower limit that is defined by
detect if the pulse is healthy or faulty. The classification signature is called Health Status. The neural network considered in this thesis is a multilayer perceptron network whit neurons (corresponding to a single pulse of the thruster). The MAE is compared with the Threshold to having internal feedbacks. As presented in [105], [122]-[128], these special neurons allow the
detect if the pulse is healthy or faulty. The classification signature is called Health Status. The neural network considered in this thesis is a multilayer perceptron network whit neurons (corresponding to a single pulse of the thruster). The MAE is compared with the Threshold to having internal feedbacks. As presented in [105], [122]-[128], these special neurons allow the
criterion. The mse for the entire data set is calculated and when mse < t.c. the training is stopped. until a termination criterion (t.c.) is satisfied. For t.c. we used the mean square error (mse
criterion. The mse for the entire data set is calculated and when mse < t.c. the training is stopped. until a termination criterion (t.c.) is satisfied. For t.c. we used the mean square error (mse
details of the results obtained under this faulty scenario. are generated by the PPT, are correctly classified as healthy pulses. Table 4.VIII contains the
details of the results obtained under this faulty scenario. are generated by the PPT, are correctly classified as healthy pulses. Table 4.VIII contains the
pulses generated. In the case of the PPT,, our FDI scheme classifies the first 28 pulses as healthy The actual pulses that are generated by the pair of thrusters are shown in Figure 4.15. The complete set of pulses generated by the PPT; is within the healthy interval (85 — 115) pN. On the scheme. According to this figure, the behavior of the PPT; is considered healthy for all the 64
pulses generated. In the case of the PPT,, our FDI scheme classifies the first 28 pulses as healthy The actual pulses that are generated by the pair of thrusters are shown in Figure 4.15. The complete set of pulses generated by the PPT; is within the healthy interval (85 — 115) pN. On the scheme. According to this figure, the behavior of the PPT; is considered healthy for all the 64
are classified as faulty pulses. Table 4.[X shows the actual healthy and faulty pulses and the Table 4.1X. Actual and Detected Condition of the Generated Pulses (Faulty Scenario 2). other hand, only the first 8 pulses that are generated by the PPT; are healthy. The other 33 pulses
are classified as faulty pulses. Table 4.[X shows the actual healthy and faulty pulses and the Table 4.1X. Actual and Detected Condition of the Generated Pulses (Faulty Scenario 2). other hand, only the first 8 pulses that are generated by the PPT; are healthy. The other 33 pulses
13 pulses are classified as faulty pulses. The 41 pulses generated by the PPT, are classified as
13 pulses are classified as faulty pulses. The 41 pulses generated by the PPT, are classified as
Figure 4.17. Actual Thrust Generated by PPT; and PPT, Under Faulty Scenario 3.
Figure 4.17. Actual Thrust Generated by PPT; and PPT, Under Faulty Scenario 3.
These results indicate that the proposed FDI scheme is capable of correctly classify the 96.09% of the healthy pulses and the 57.63% of the faulty pulses. The accuracy level (88.89%)
These results indicate that the proposed FDI scheme is capable of correctly classify the 96.09% of the healthy pulses and the 57.63% of the faulty pulses. The accuracy level (88.89%)
design an alternative fault diagnosis and health monitoring system.
design an alternative fault diagnosis and health monitoring system.
Table 5.VI. Expected Settling Time and Tracking Error Values for s/cj and s/cp. simulations that are performed in this chapter have a final simulation time (tjna) of 3000 sec. he faulty cases described in Chapter 4 are used to simulate different faulty scenarios
Table 5.VI. Expected Settling Time and Tracking Error Values for s/cj and s/cp. simulations that are performed in this chapter have a final simulation time (tjna) of 3000 sec. he faulty cases described in Chapter 4 are used to simulate different faulty scenarios
Figure 5.1. (a) Angular Rotation (in quaternion) of s/cy w.r.t. s/c; (Healthy Scenario).
Figure 5.1. (a) Angular Rotation (in quaternion) of s/cy w.r.t. s/c; (Healthy Scenario).
Table 5.VIH. Since s/cy; and s/cz are identical spacecraft, the results of the above simulation are
Table 5.VIH. Since s/cy; and s/cz are identical spacecraft, the results of the above simulation are
Figure 5.1. (c) Sequence of the Pulses (+1/0/-1 states) of s/cy; w.r.t. s/c; (Healthy Scenario). racking errors, settling times and the number of generated pulses for s/c are shown in
Figure 5.1. (c) Sequence of the Pulses (+1/0/-1 states) of s/cy; w.r.t. s/c; (Healthy Scenario). racking errors, settling times and the number of generated pulses for s/c are shown in
Due to the loss of elasticity in the spring of the thruster PPT, the amount of force produced by Figure 5.2. (b) Angular Velocity (in degree/seconds) of s/cj; w.r.t. s/c; (Faulty Scenario 1). 5.2.2 Simulations for the Faulty Scenario 1
Due to the loss of elasticity in the spring of the thruster PPT, the amount of force produced by Figure 5.2. (b) Angular Velocity (in degree/seconds) of s/cj; w.r.t. s/c; (Faulty Scenario 1). 5.2.2 Simulations for the Faulty Scenario 1
he healthy case (Table 5. VII).
he healthy case (Table 5. VII).
Table 5.VIII shows the performance parameters for s/cj under the Faulty scenario 1 conditions. Follower s/cy is not subjected to a faulty actuator, therefore its results are the same as
Table 5.VIII shows the performance parameters for s/cj under the Faulty scenario 1 conditions. Follower s/cy is not subjected to a faulty actuator, therefore its results are the same as
Figure 5.3. (b) Angular Velocity (in degree/seconds) of s/c w.r.t. s/c; (Faulty Scenario 2). (sedimentation) may produce force pulses 15% greater than the nominal values. Figures 5.3 (a}+
Figure 5.3. (b) Angular Velocity (in degree/seconds) of s/c w.r.t. s/c; (Faulty Scenario 2). (sedimentation) may produce force pulses 15% greater than the nominal values. Figures 5.3 (a}+
the same as that of the healthy case (Table 5. VII). able 5. VIX. Since the follower s/cp is not subjected to faulty actuators therefore the results are
the same as that of the healthy case (Table 5. VII). able 5. VIX. Since the follower s/cp is not subjected to faulty actuators therefore the results are
The performance parameters for s/cy under the Faulty scenario 2 conditions are shown in
The performance parameters for s/cy under the Faulty scenario 2 conditions are shown in
reduction in the amount of thrust produced. A conductivity fault in the thruster PPT; of s/cy
reduction in the amount of thrust produced. A conductivity fault in the thruster PPT; of s/cy
shown in Table 5.VX, one can conclude that the performance of the formation flying system
shown in Table 5.VX, one can conclude that the performance of the formation flying system
condition.
condition.
filters and hyperbolic tangent sigmoid and linear activation functions for the neurons in the
filters and hyperbolic tangent sigmoid and linear activation functions for the neurons in the
references that are expressed in the quaternions. The modeling capability of our DNN approach is illustrated in Figures 5.9 — 5.10. In these
references that are expressed in the quaternions. The modeling capability of our DNN approach is illustrated in Figures 5.9 — 5.10. In these
Similar to the procedure performed in the training phase, in the validation phase we simulate
Similar to the procedure performed in the training phase, in the validation phase we simulate
The data set generated from the missions 1-6 include only the healthy data, therefore the
The data set generated from the missions 1-6 include only the healthy data, therefore the
5.4. Simulations for the FDI
5.4. Simulations for the FDI
Section 3.3.2, PPT; and PPT> generate torques in the +x and —x axes, respectively. is “considerably” higher than the amount of pulses generated by the other actuator (PPT)).
Section 3.3.2, PPT; and PPT> generate torques in the +x and —x axes, respectively. is “considerably” higher than the amount of pulses generated by the other actuator (PPT)).
The number of pulses that are generated by PPT; and PPT) are 10 and 2890, respectively Figure 5.12 shows the real effect that this fault produces on the thruster PPT, and Table
The number of pulses that are generated by PPT; and PPT) are 10 and 2890, respectively Figure 5.12 shows the real effect that this fault produces on the thruster PPT, and Table
5.XVI presents the results that are obtained by using our proposed FDI scheme. torques in +y and —y axes, respectively (see Chapter 3, Section 3.3.2).
5.XVI presents the results that are obtained by using our proposed FDI scheme. torques in +y and —y axes, respectively (see Chapter 3, Section 3.3.2).
Finally, from this simulated faulty scenario, we can see that when thruster PPT; generates Based on the results shown in Table 5.XVII, we detect the presence of a fault in the pair of less torque than expected, the amount of pulses generated by this actuator is ‘considerably’ higher
Finally, from this simulated faulty scenario, we can see that when thruster PPT; generates Based on the results shown in Table 5.XVII, we detect the presence of a fault in the pair of less torque than expected, the amount of pulses generated by this actuator is ‘considerably’ higher
thrusters PPT;/PPT,. The other two pairs of thrusters are identified as healthy.
thrusters PPT;/PPT,. The other two pairs of thrusters are identified as healthy.
represents a promising detection capability, however as far as the isolation purposes are
represents a promising detection capability, however as far as the isolation purposes are
Figure 6.2 shows the “High Level” FDI scheme that was proposed in Chapter 5 which is composed by three DNNs. As described in Chapter 5, Section 5.3, a set of three relative attitude variables and the sequence of pulses that are generated by the corresponding pair of thrusters
Figure 6.2 shows the “High Level” FDI scheme that was proposed in Chapter 5 which is composed by three DNNs. As described in Chapter 5, Section 5.3, a set of three relative attitude variables and the sequence of pulses that are generated by the corresponding pair of thrusters
threshold value, the pair of thrusters responsible for the rotational maneuvers around that axis is “High Level” FDI scheme is an efficient fault detection tool. Using the relative attitude variables,
threshold value, the pair of thrusters responsible for the rotational maneuvers around that axis is “High Level” FDI scheme is an efficient fault detection tool. Using the relative attitude variables,
.IIT are used to represent the faulty pair of thrusters that is detected by the “High Level” FD]
.IIT are used to represent the faulty pair of thrusters that is detected by the “High Level” FD]
Table 6.[I. Definition of Variables used by the “Integrated” FDI Scheme when PPT;./PPT, is the Faulty Pair of Thrusters.
Table 6.[I. Definition of Variables used by the “Integrated” FDI Scheme when PPT;./PPT, is the Faulty Pair of Thrusters.
Now, with the Logic Threshold Selection Block specified, the integrated FDI scheme is
Now, with the Logic Threshold Selection Block specified, the integrated FDI scheme is
residuals (MAE) are generated and then using the corresponding Threshold values the health
residuals (MAE) are generated and then using the corresponding Threshold values the health
Table 6.IV. Health Analysis Conditions Considered by Our Proposed “Integrated” FDI Approach. parameters of the faulty PPT as shown equations (6.1) — (6.4), namely details are shown in Table 6.IV. The injected faults are simulated by modifying the corresponding
Table 6.IV. Health Analysis Conditions Considered by Our Proposed “Integrated” FDI Approach. parameters of the faulty PPT as shown equations (6.1) — (6.4), namely details are shown in Table 6.IV. The injected faults are simulated by modifying the corresponding
As shown in Figure 6.6, the first stage of our proposed “Integrated” FDI scheme estimates utside the healthy zone. On the other hand, PPT> did not generate pulses during the entire
As shown in Figure 6.6, the first stage of our proposed “Integrated” FDI scheme estimates utside the healthy zone. On the other hand, PPT> did not generate pulses during the entire
variables to generate the corresponding residuals (SAE;). The results are shown in Table 6.V. the three components of the angular velocity and then compares the estimates with the actual
variables to generate the corresponding residuals (SAE;). The results are shown in Table 6.V. the three components of the angular velocity and then compares the estimates with the actual
Table 6.VIL. “Integrated” FDI Scheme Results for s/ey, under Fault Scenario 1. number 1. Table 6.VII shows the final health monitoring results that are obtained by using our
Table 6.VIL. “Integrated” FDI Scheme Results for s/ey, under Fault Scenario 1. number 1. Table 6.VII shows the final health monitoring results that are obtained by using our
for PPT; and PPT) for all the simulated period. According to these status signals the entire set of
for PPT; and PPT) for all the simulated period. According to these status signals the entire set of
For the sake of brevity, figures such as Figures 6.6 to 6.8 are not shown for the following
For the sake of brevity, figures such as Figures 6.6 to 6.8 are not shown for the following
The fault is declared in the pair of thrusters PPT;/ PPT;. Based on the number of pulses generated by the pair, the Logic Threshold Selection Block especifies the Threshold values for
The fault is declared in the pair of thrusters PPT;/ PPT;. Based on the number of pulses generated by the pair, the Logic Threshold Selection Block especifies the Threshold values for
first stage of our proposed “Integrated” FDI scheme estimates the three components of the
first stage of our proposed “Integrated” FDI scheme estimates the three components of the
The fault is declared in the pair of thrusters PPT;/ PPTs. Based on the number of pulse: generated by the pair, the Logic Threshold Selection Block especifies the Threshold values fc corresponding residuals (SAE,). The results are shown in Table 6.XI. 90th thrusters. Table 6.XII shows the resulting Thresholds. angular velocity and then compares the estimates with the actual variables to generate the
The fault is declared in the pair of thrusters PPT;/ PPTs. Based on the number of pulse: generated by the pair, the Logic Threshold Selection Block especifies the Threshold values fc corresponding residuals (SAE,). The results are shown in Table 6.XI. 90th thrusters. Table 6.XII shows the resulting Thresholds. angular velocity and then compares the estimates with the actual variables to generate the
Table 6.XIV. Health Analysis Results Obtained by our Proposed FDI approach for the Fault Scenario 4. corresponding residuals (SAE;). The results are shown in Table 6.XIV.
Table 6.XIV. Health Analysis Results Obtained by our Proposed FDI approach for the Fault Scenario 4. corresponding residuals (SAE;). The results are shown in Table 6.XIV.
Figure 6.16. Misclassification of Pulses Generated by PPT; (Fault Scenario 3).
Figure 6.16. Misclassification of Pulses Generated by PPT; (Fault Scenario 3).
The fault is declared in the pair of thrusters PPT;/ PPT. Based on the number of pulses that
The fault is declared in the pair of thrusters PPT;/ PPT. Based on the number of pulses that
Table 6.XVII. Health Analysis Results Obtained by our Proposed FDI Approach for the Fault Scenario 5. generate the corresponding residuals (SAE;). The results are shown in Table 6.XVII. components of the angular velocity and then compares the estimates with the actual variables t¢
Table 6.XVII. Health Analysis Results Obtained by our Proposed FDI Approach for the Fault Scenario 5. generate the corresponding residuals (SAE;). The results are shown in Table 6.XVII. components of the angular velocity and then compares the estimates with the actual variables t¢
Fault Scenario 5 Results: Figures 6.19 shows the actual reduction in the amount of the torque generated by the thruster PPT; due to the fault injected after t = 400 sec. Meanwhile, some of the pulses that are generated by PPT; are outside the healthy zone, and the pulses that are generated by PPT, are healthy. The first stage of our proposed “Integrated” FDI scheme estimates the three
Fault Scenario 5 Results: Figures 6.19 shows the actual reduction in the amount of the torque generated by the thruster PPT; due to the fault injected after t = 400 sec. Meanwhile, some of the pulses that are generated by PPT; are outside the healthy zone, and the pulses that are generated by PPT, are healthy. The first stage of our proposed “Integrated” FDI scheme estimates the three
The fault is declared in the pair of thrusters PPT3/ PPT;. Based on the number of pulses that
The fault is declared in the pair of thrusters PPT3/ PPT;. Based on the number of pulses that
The fault is declared in the pair of thrusters PPT;/ PPTs. Based on the number of pulses that
The fault is declared in the pair of thrusters PPT;/ PPTs. Based on the number of pulses that
Fault Scenario 7 Results: Figures 6.25 shows the actual augmentation in the amount of the torque that is generated by the thruster PPT; due to the fault injected after t = 300 sec
Fault Scenario 7 Results: Figures 6.25 shows the actual augmentation in the amount of the torque that is generated by the thruster PPT; due to the fault injected after t = 300 sec
Figure 6.25. Actual Sequence of Pulses Generated by PPT,/ PPT, for the Fault Scenario 7. The fault is declared in the pair of thrusters PPT;/ PPT;. Based on the number of pulses that are generated by the pair, the Logic Threshold Selection Block defines the Threshold values for
Figure 6.25. Actual Sequence of Pulses Generated by PPT,/ PPT, for the Fault Scenario 7. The fault is declared in the pair of thrusters PPT;/ PPT;. Based on the number of pulses that are generated by the pair, the Logic Threshold Selection Block defines the Threshold values for
The fault is declared in the pair of thrusters PPT;/ PPT. Based on the number of pulses that
The fault is declared in the pair of thrusters PPT;/ PPT. Based on the number of pulses that
6.4. Confusion Matrix Results for the Integrated FDI Scheme The performance of our proposed “Integrated” FDI scheme is studied using the Confusion Matrix as described in Chapter 4, Section 4.4. Table 6.X XIX contains the results for the four Confusion Matrix parameters evaluated for each of the fault scenarios. The last row of this table shows the
6.4. Confusion Matrix Results for the Integrated FDI Scheme The performance of our proposed “Integrated” FDI scheme is studied using the Confusion Matrix as described in Chapter 4, Section 4.4. Table 6.X XIX contains the results for the four Confusion Matrix parameters evaluated for each of the fault scenarios. The last row of this table shows the
Table 6.XXX. Performance Results for Our Proposed “Low Level” and “Integrated” FDI Schemes. with the results that are obtained in Chapter 4.
Table 6.XXX. Performance Results for Our Proposed “Low Level” and “Integrated” FDI Schemes. with the results that are obtained in Chapter 4.
misclassification rate as expressed as False Healthy and False Faulty parameters is quite
misclassification rate as expressed as False Healthy and False Faulty parameters is quite
actuator or two or more actuators affected by faults concurrently) and the development of fault
actuator or two or more actuators affected by faults concurrently) and the development of fault
Related topics:
EngineeringComputer ScienceFault Detection and IsolationElectrical Circuit TheoryFault IsolationMultilayer PerceptronDynamic Networksdynamic Neural Network
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