DTP2RFM Calculates rainflow matrix from discrete turning points. CALL: RFM = dtp2rfm(dtp,n) [RFM,RFM1,res] = dtp2rfm(dtp,n,def) [RFM,RFM1,res] = dtp2rfm(dtp,def,RFM0,res0) Output: RFM = Rainflow matrix (residual included). [n,n] RFM1 = Rainflow matrix (without resudual). [n,n] res = Residual. [nres,1]/[nres,2] Input: dtp = Turning points (taking values 1,...,n). [T,1]/[T,2] n = Number of levels. def = Treatment of residual. 'up': Count min-to-Max cycles, (default) gives correct number of upcrossings. 'down': Count Max-to-min cycles, gives correct number of downcrossings. 'CS': Cloormann/Seeger method, gives all closed hysterisis loops. This method is identical to the French AFNOR recommendation, and the ASTM standard (variant called simplified version). RFM0 = Rainflow matrix (without resudual). [n,n] res0 = Residual (taking values 1,...,n). [nres0,1]/[nres0,2] Calculates the rainflow matrix (RFM) for the sequence of discrete turning points, by using the so-called 4-point algorithm. It is possible to split the signal into smaller parts, and calculate RFM part by part. It can be especially useful for long signals. We count the first part and for the second part we continue counting from previously counted 'RFM0' with residual 'res0': [RFM1,RFM0,res0] = dtp2rfm(dtp(1:1000,:),32); % Firts 1000 points [RFM2] = dtp2rfm(dtp(1001:end,:),[],RFM0,res0); % Point 1001 to end This shall give the same result as (i.e. ARFM=ARFM2) [RFM] = dtp2rfm(dtp,32); % Calculate all at once sum(sum(RFM~=RFM2)) % Shall return 0 Example: x = load('sea.dat'); % Load data [dtp,u,tp] = dat2dtp([-2 2 32],x,0.2); % Discrete TP & rainflow filter 0.2 RFM = dtp2rfm(dtp,32); % Calculate rainflow matrix cmatplot(u,u,RFM,3), colorbar % Plot rainflow matrix See also dtp2arfm, dcc2cmat, tp2rfc, dat2tp

- dtp2arfm
- error
- triu

Calculates asymmetric RFM from discrete turning points. | |

Display message and abort function. | |

Extract upper triangular part. |

- Chapter4
- dat2rfm
- itmkurs_lab2
- itmkurs_lab4
- rfc2load_fat
- smctpsim
- test_cycles
- test_markov

% CHAPTER4 contains the commands used in Chapter 4 of the tutorial | |

Calculates the rainflow matrix from a time signal. | |

Script to computer exercises 2 | |

Script to computer exercises 4 | |

Recontructs a load process given the frequency matrix (and residual). | |

Simulates a switching Markov chain of turning points, | |

Quick test of the routines in module 'cycles' | |

Quick test of the routines in module 'markov' |

001 function [RFM,RFM1,res] = dtp2rfm(x,varargin) 002 %DTP2RFM Calculates rainflow matrix from discrete turning points. 003 % 004 % CALL: RFM = dtp2rfm(dtp,n) 005 % [RFM,RFM1,res] = dtp2rfm(dtp,n,def) 006 % [RFM,RFM1,res] = dtp2rfm(dtp,def,RFM0,res0) 007 % 008 % Output: 009 % RFM = Rainflow matrix (residual included). [n,n] 010 % RFM1 = Rainflow matrix (without resudual). [n,n] 011 % res = Residual. [nres,1]/[nres,2] 012 % 013 % Input: 014 % dtp = Turning points (taking values 1,...,n). [T,1]/[T,2] 015 % n = Number of levels. 016 % def = Treatment of residual. 017 % 'up': Count min-to-Max cycles, (default) 018 % gives correct number of upcrossings. 019 % 'down': Count Max-to-min cycles, 020 % gives correct number of downcrossings. 021 % 'CS': Cloormann/Seeger method, 022 % gives all closed hysterisis loops. 023 % This method is identical to the French AFNOR recommendation, 024 % and the ASTM standard (variant called simplified version). 025 % RFM0 = Rainflow matrix (without resudual). [n,n] 026 % res0 = Residual (taking values 1,...,n). [nres0,1]/[nres0,2] 027 % 028 % Calculates the rainflow matrix (RFM) for the sequence of discrete turning 029 % points, by using the so-called 4-point algorithm. 030 % 031 % It is possible to split the signal into smaller parts, and calculate 032 % RFM part by part. It can be especially useful for long signals. 033 % We count the first part and for the second part we continue counting 034 % from previously counted 'RFM0' with residual 'res0': 035 % [RFM1,RFM0,res0] = dtp2rfm(dtp(1:1000,:),32); % Firts 1000 points 036 % [RFM2] = dtp2rfm(dtp(1001:end,:),[],RFM0,res0); % Point 1001 to end 037 % This shall give the same result as (i.e. ARFM=ARFM2) 038 % [RFM] = dtp2rfm(dtp,32); % Calculate all at once 039 % sum(sum(RFM~=RFM2)) % Shall return 0 040 % 041 % Example: 042 % x = load('sea.dat'); % Load data 043 % [dtp,u,tp] = dat2dtp([-2 2 32],x,0.2); % Discrete TP & rainflow filter 0.2 044 % RFM = dtp2rfm(dtp,32); % Calculate rainflow matrix 045 % cmatplot(u,u,RFM,3), colorbar % Plot rainflow matrix 046 % 047 % See also dtp2arfm, dcc2cmat, tp2rfc, dat2tp 048 049 % Tested on Matlab 5.3 050 % 051 % History: 052 % Revised by PJ 26-Jul-2000 053 % New input 'def'. 054 % Now supports AFNOR and ASTM standards for rainflow counting. 055 % Revised by PJ (Pär Johannesson) 12-Jan-2000 056 % updated for WAFO 057 % Created by PJ (Pär Johannesson) 1999 058 059 % Check input arguments 060 ni = nargin; 061 no = nargout; 062 error(nargchk(2,4,ni)); 063 064 % Calculate asymetric RFM 065 if no < 2 066 RFM = dtp2arfm(x,varargin{:}); 067 else 068 [RFM,RFM1,res] = dtp2arfm(x,varargin{:}); 069 end 070 071 % Convert to symetric rainflow 072 RFM = RFM+RFM'; 073 RFM = triu(RFM); 074 if no >= 2 075 RFM1 = RFM1+RFM1'; 076 RFM1 = triu(RFM1); 077 end 078 079

Mathematical Statistics

Centre for Mathematical Sciences

Lund University with Lund Institute of Technology

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