Fault Detection & Diagnosis in Control Valve Shahriar iar - PowerPoint PPT Presentation

BSc Project Fault Detection & Diagnosis in Control Valve Shahriar iar Shahra ram Super ervi visor: sor: Dr. No Noba bakhti hti

2 of 29 Content  What is fault?  Why we detect fault in a control loop?  What is “ Stiction ” ?  Comparing “ stiction ” with other faults  Ways we can resolve “ stiction ”  First method : Shape based (MV-OP diagram analysis)  Second method : Cross Correlation Function  Third method : Curve Fitting  Comparing methods  New method : EMD  Challenges Shahriar Shahram Sharif University of Technology Fault Detection & Diagnosis in Control Valve

3 of 29 What is fault? Controller Actuator Plant SP Output Sensor Controller : poor tuning is not fault Actuator Fault : valve friction Plant Fault : leakage , human error Sensor Fault : calibration Shahriar Shahram Sharif University of Technology Fault Detection & Diagnosis in Control valve

4 of 29 Why we detect a fault? A. Increasing product quality B. Reducing the rate of rejection C. Fault signals propagation in physical components D. Minimizing risk of instability Shahriar Shahram Sharif University of Technology Fault Detection & Diagnosis in Control Valve

5 of 29 Valve Stiction What is “ Stiction ” referred to? • According to Horch (2000) ‘‘ The control valve is stuck in a certain position due to high static friction. The (integrating) controller then increases the set point to the valve until the static friction can be overcome. Then the valve breaks off and moves to a new position (slip phase) where it sticks again. The new position is usually on the other side of the desired set point such that the process starts in the opposite direction again ’’ . Reference3 Shahriar Shahram Sharif University of Technology Fault Detection & Diagnosis in Control Valve

6 of 29 Stiction in a control valve  Valve stiction is very important. The first reason is that valve stiction causes 30% of loops work poorly(2 nd rank). Another reason is when a valve has Reference 1 stiction , the risk of instability will rise. Schematic of a control valve Reference 3 Shahriar Shahram Sharif University of Technology Fault Detection & Diagnosis in Control Valve

7 of 29 Comparing “ stiction ” with Other Faults Reference1 Shahriar Shahram Sharif University of Technology Fault Detection & Diagnosis in Control Valve

8 of 29 MV-OP analysis: Method A,B  This method utilizes the fact that MV does not change even though OP changes if stiction occurs in control valves.  We can quantify the degree of stiction by checking the length where MV stays constant. Stiction index (SI A ) No stiction Uncertainty Stiction SI A ≤ 0.25 --------- SI A > 0.25 Reference 1 Reference 1 Shahriar Shahram Sharif University of Technology Fault Detection & Diagnosis in Control Valve

9 of 29 MV-OP analysis: Method C  Method C is based on the qualitative shape analysis of the characteristics in Fig.1  Time segments of signals can be qualitatively approximated by means of three qualitative symbols: increasing (I), decreasing (D) and steady (S). No stiction Unceratinty Stiction SI C ≤ 0.25 ------------- SI C > 0.25 Stiction index (SI c ) Reference 1 Fig.1 Reference 1 Shahriar Shahram Sharif University of Technology Fault Detection & Diagnosis in Control Valve

10 of 29 MV-OP analysis: Method A Advantages • They are intuitive • Easy to understand • Easy to implement • Computationally efficient • They work even when no periodical oscillation occurs Disadvantages • We should have position of the valve in every moment (only in smart valves) • Method C is more confident than the other methods but this method also needs choosing an efficient sample time; Because lowering the sample time increases the noise & increasing the sample time is harmful. [Reference 1] Shahriar Shahram Sharif University of Technology Fault Detection & Diagnosis in Control Valve

11 of 29 CCF : Cross Correlation Function  If the cross-correlation function (CCF) between controller output and process output is an odd function (i.e. asymmetric with respect to (w.r.t.) the vertical axis), the likely cause of the oscillation is stiction. If the CCF is even (i.e. symmetric w.r.t. the vertical axis), then stiction is not likely to having caused the oscillation. a)Stiction case b) Non-stiction case Reference 1 Shahriar Shahram Sharif University of Technology Fault Detection & Diagnosis in Control Valve

12 of 29 CCF : Cross Correlation Function a)Stiction case b) Non-stiction case Reference 1  Note that the proposed method will work under the following assumptions, which will be discussed later: • The process itself is not integrating (such as level control). • Note that it is important that a procedure for automatic distinction between odd and even functions needs to have a deadzone. Shahriar Shahram Sharif University of Technology Fault Detection & Diagnosis in Control Valve

13 of 29 CCF : Cross Correlation Function 𝜐 𝑠 = 𝑨𝑓𝑠𝑝 − 𝑑𝑠𝑝𝑡𝑡𝑗𝑜𝑕 𝑔𝑝𝑠 𝑞𝑝𝑡𝑗𝑢𝑗𝑤𝑓 𝑚𝑏𝑕𝑡 −𝜐 𝑚 = 𝑨𝑓𝑠𝑝 − 𝑑𝑠𝑝𝑡𝑡𝑗𝑜𝑕 𝑔𝑝𝑠 𝑜𝑓𝑕𝑏𝑢𝑗𝑤𝑓 𝑚𝑏𝑕𝑡 𝑠 0 = 𝐷𝐷𝐺 𝑏𝑢 𝑚𝑏𝑕 0 𝑠 𝑝𝑞𝑢 = 𝑡𝑗𝑕𝑜(𝑠 0 ). Max( 𝑠 𝑣𝑧 ( 𝜐 )) ( 𝜐 ∈ [−𝜐 1 , 𝜐 𝑠 ] ) ∆ρ = ∣ 𝜐 𝑚 −𝜐 𝑠 ∣ ∣ 𝜐 𝑚+ 𝜐 𝑠 ∣ ∆𝜐 = ∣ 𝜐 𝑠 −𝜐 𝑝𝑞𝑢 ∣ Stiction index (SI) Reference 1 ∣ 𝜐 𝑠+ 𝜐 𝑝𝑞𝑢 ∣ Non stiction Uncertainty Stiction 0 ≤ ∆ρ ≤ 0.072 0.072 ≤ ∆ρ ≤ 1/3 1/3 ≤ ∆ρ ≤ 1 0 ≤ Δτ≤ 1/3 1/3 ≤ Δτ ≤ 2/3 2/3 ≤ Δτ ≤ 1 Reference 1 Shahriar Shahram Sharif University of Technology Fault Detection & Diagnosis in Control Valve

14 of 29 CCF : Cross Correlation Function Advantages • Easy implementing • Using routine data • No need to filtering the noise Disadvantages • Not practical on integrator systems • Function phase shift depends on the controller design • Cross correlation function doesn ’ t work for dominant proportional controllers [Reference 2] Shahriar Shahram Sharif University of Technology Fault Detection & Diagnosis in Control Valve

15 of 29 Curve Fitting  To identify stiction-induced oscillations from others, we fit two different functions, triangular wave and sinusoidal wave, to the output signal of the first integrating component located after the valve.  OP for self-regulating processes or PV for integrating processes.  A better fit to a triangular wave indicates valve stiction, while a better fit to a sinusoidal wave indicates non-stiction. Stiction index (SI) Not stiction Uncertainty Stiction SI ≤ 0.4 0.4<SI<0.6 SI ≥ 0.6 Reference 1 Shahriar Shahram Sharif University of Technology Fault Detection & Diagnosis in Control Valve

16 of 29 Curve Fitting OP/PV signal fitting a)Sinusoidal fitting b)triangular fitting Reference 1 Shahriar Shahram Sharif University of Technology Fault Detection & Diagnosis in Control Valve

17 of 29 Curve Fitting Advantages • One advantage is that it is applicable to both self regulating and integrating processes. • Another advantage is its industrial practicability due to the following reasons: 1. The methodology is straightforward and easy to implement. 2. The detection is fully automatic and does not require user interaction. 3. Because of the piecewise fit, it is flexible in handling asymmetric or damped oscillations. Disadvantages • Need to know the zero crossings but because of the noise it will be hard. • Does not guarantee detection of valve stiction in all cases. • Sufficient data resolution is required for reliable diagnosis. [Reference 1] Shahriar Shahram Sharif University of Technology Fault Detection & Diagnosis in Control Valve

18 of 29 Comparing  These methods are the most famous methods because they are : • Easy to understand • Easy to implement • Needs routine data • Rate of success in analysis  Curve fitting is the most efficient method among these methods.  Note that no method works perfectly for all systems. Shahriar Shahram Sharif University of Technology Fault Detection & Diagnosis in Control Valve

19 of 29 New Method : EMD  EMD or Empirical Mode Decomposition proposed by Norden E. Huang in 1998 for analyzing data from nonstationary and nonlinear processes . Reference 4  EMD decomposes any time-series signals into the sum of a finite number of Intrinsic Mode Functions (IMFs)  EMD vs. Wavelet Analysis & Fourier Transform  Conditions where the sifting process stops: 1. The residual is a monotonic function 2. The residual has less than two extrema 3. The residual is a constant Reference 4 Shahriar Shahram Sharif University of Technology Fault Detection & Diagnosis in Control Valve