CN109934100A - A kind of amplitude-frequency time-varying process signal dividing method based on sliding window - Google Patents
A kind of amplitude-frequency time-varying process signal dividing method based on sliding window Download PDFInfo
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Abstract
The invention discloses a kind of amplitude-frequency time-varying process signal dividing method based on sliding window: (1) sliding window is arranged to amplitude-frequency time-varying process signal that needs analyze；(2) segmentation threshold point under process curve is set dynamically according to mean value, to obtain lower cut-off rule in the mean value for seeking each process signal point in sliding window；(3) each lower cut-point of process curve is determined according to lower cut-off rule, and carries out the segmentation of process curve according to lower cut-point；(4) using the process signal in segmentation curve, segmentation curve similarity is sought, Effective judgement is split.The present invention is directed to amplitude-frequency time-varying process curve, carries out process cycle segmentation to it, and adapt to the change of technological parameter, has stronger adaptivity, stability and robustness.
Description
Technical field
The present invention relates to process signal segmentation technology, in particular to a kind of amplitude-frequency time-varying technique based on sliding window
Signal dividing method.
Background technique
In fault diagnosis and device status monitoring field, the extraction to process curve characteristic value is all relied on, and feature
A kind of mode that value is extracted is exactly to be split to process curve, then carry out feature extraction for segmentation curve.Therefore, technique is bent
Line partitioning algorithm is the basis of equipment fault diagnosis and monitoring running state.
Currently, there are many research of equipment operation process curve segmentation algorithm, conventional method is: first, in accordance with the pole of signal
The functional section being worth in the practical significance definition signal period of point, monotonicity or signal divides, then using between signal cut-point
Time relationship, signal cut-point extremum characteristic signal is divided with the methods of time-domain analysis, cepstral analysis, wavelet transformation
Point extracts, to realize the purpose of signal segmentation.
However, technological parameter is real-time change, and leading to equipment operation process curve is one in actual production processing
Skill of exchanging work parameter curve, the amplitude and frequency of process curve can change, existing signal segmentation side with the change of technological parameter
The process signal that method can not adapt to the period, extreme value changes, often will appear mistake.
Summary of the invention
In view of the defects and deficiencies of the prior art, the present invention intends to provide when a kind of amplitude-frequency based on sliding window
Become process signal dividing method.
To achieve the above object, the technical solution adopted by the present invention is that:
1) sliding window is set, and determines the window of the sliding window according to the process cycle of amplitude-frequency time-varying process curve
Mouth size and sliding step；
2) amplitude-frequency time-varying process curve is traversed using the sliding window of step 1) setting and seek sliding mean value, slide mean value
For the average value for corresponding to each signaling point in sliding window, the lower segmentation threshold of amplitude-frequency time-varying process curve is set according to sliding mean value
Point can carry out the lower cut-off rule of successive segmentation using the setting of lower segmentation threshold point to amplitude-frequency time-varying process curve；
3) amplitude-frequency time-varying technique is determined according to positioned at lower cut-off rule amplitude-frequency time-varying process curve signal minimum point below
The lower cut-point of curve, the technique that the lower cut-point according to amplitude-frequency time-varying process curve carries out signal to amplitude-frequency time-varying process curve
Period divisions.
Preferably, in the step 1), the size of sliding window is 1.5~3 times of the process cycle, sliding window
Sliding step is 1~5.
Preferably, in the step 2), lower segmentation threshold point is sliding window center in the position of sampling time dimension, under
Segmentation threshold point is equal to sliding mean value and Δ in the position of signal value dimensiontDifference, ΔtFor amplitude-frequency time-varying process curve peak peak
Value and factor betatProduct.
Preferably, the βtValue range be 0.1~0.3.
Preferably, in the step 2), all lower segmentation threshold points is connected and obtain lower cut-off rule.
Preferably, in the step 3), the determination of lower cut-point is specifically includes the following steps: to amplitude-frequency time-varying process curve
In be located at lower cut-off rule curve section below and extract, pass through to traverse and determine that corresponding signal is minimum on every section of curve section
Value point.
Preferably, the determination of the lower cut-point is further comprising the steps of: by the sampling interval of adjacent signals minimum point
Distance is compared with the minimum threshold of distance of setting, if the distance of adjacent signals minimum point is greater than the threshold value, stick signal
Minimum point is made conversely, then giving up the wherein signal minimum point of sampling time rearward by all signal minimum points retained
For lower cut-point, wherein minimum threshold of distance is 2~10.
Preferably, the process signal dividing method is further comprising the steps of: to the process cycle being partitioned into step 3)
Signal seeks the similarity of corresponding segmentation curve, filters out effective process cycle signal according to the similarity.
Preferably, the similarity of the segmentation curve is sought using dynamic time warping algorithm (DTW), and each section is divided
Process cycle signal out acquires similarity value using the algorithm and referring to specified standard technology periodic signal, if similarity value
Greater than the threshold value (i.e. shape is similar) of setting, then retain the segment process periodic signal being partitioned into；Otherwise, give up this being partitioned into
Segment process periodic signal.
Preferably, the standard technology periodic signal is specified from all process cycle signals being partitioned into.
The invention has the advantages that:
The present invention is directed to amplitude-frequency time-varying process curve, according to the sliding mean value of sliding window, dynamically seeks lower segmentation threshold
Value determines lower cut-off rule and lower cut-point, and then carries out period divisions to process curve, adapts to the change of technological parameter, has
There are stronger adaptivity, stability and robustness.The work that the present invention changes for all kinds of periods, extreme value with technological parameter
The segmentation of skill signal has versatility, is adapted to various types of signal situation of change in technical process, realizes easy, quick, effective
Process cycle signal segmentation.
Further, the present invention is split the evaluation of effect according to curve similarity after segmentation, can preferably adapt to
The variation of process curve amplitude and frequency improves the adaptivity, stability and robustness of segmentation result.
Detailed description of the invention
Fig. 1 is the amplitude-frequency time-varying process signal dividing method flow chart based on sliding window in the present invention.
Fig. 2 is certain intelligently equipment normal operation process curve.
Fig. 3 is certain intelligently equipment process curve segmentation result.
Specific embodiment
The present invention is further illustrated with reference to the accompanying drawings and examples.The embodiment is only used for explaining this hair
It is bright, rather than limiting the scope of the invention.
As shown in Figure 1, the process of the amplitude-frequency time-varying process signal dividing method based on sliding window is as follows:
(1) sliding window is arranged to the amplitude-frequency time-varying process signal that needs are analyzed, determines that window size and sliding walk
It is long；
Process curve as shown in Figure 2 is defined, with vector X=[x1,x2,…,xi,…,xn]TIt represents and acquires in technical process
Data acquisition system, i.e. process curve form (signaling point is sequentially connected by the sampling time as process curve) by n original signal point；Really
Determining sliding window size N is 2.2 times that certain intelligently equips (for example, fast forging press) process cycle, sliding step 1.
(2) signaling point in cycling among windows, the sliding mean value for seeking sliding window (it is bent for technique in sliding window to slide mean value
The average value of line each point), segmentation threshold point δ under process curve is set accordinglyb(i), connecting all lower segmentation threshold points is lower minute
Secant；Lower segmentation threshold point is specifically using will slide the mean value a small amount of Δs that subtract onetAnd be calculated, this is process curve in a small amount
Peak-to-peak value (Max (X)-Min (X)) multiply a coefficient (βt) result, it may be assumed that
Δt=βt(Max(X)-Min(X))
Wherein, X (i) is centre one point of the sliding window in process curve current position, βtIt is taken as 0.2.
From fig. 2 it can be seen that obtained lower cut-off rule has run through each section in process curve, it can be lower point according to this
Secant finds the starting point and ending point of each process cycle.
(3) key of process curve segmentation is accurately to find technique cut-point (being known as lower cut-point in the present invention)；
All original signal points are traversed, is lower than lower cut-off rule, then retains and be added to minimum value and judge sequence, otherwise give up
It abandons；The lower cut-point of process curve is the minimum point SL in any section of lower cut-off rule or lesspb:
Wherein,Respectively indicate the forward and backward endpoint in section.
(4) set minimum threshold of distance, judge the distance between adjacent minimum point (i.e. between two o'clock abscissa away from
From)；Distance is greater than minimum threshold of distance, then is added to segmentation point sequence, and it is more biggish otherwise to give up abscissa, in this example most
Small distance threshold value takes 4.
(5) process curve period divisions are carried out based on cut-point；Referring to fig. 2, divide under specified first and light, often
A lower cut-point of p (for example, p=2) carries out once to the segmentation of process curve.
(6) using the process cycle signal being partitioned into, segmentation curve similarity is sought, Effective judgement is split；
Specific deterministic process are as follows: first process cycle signal is standard technology periodic signal in specified Fig. 3, bent to segmentation
Line carries out DTW similitude solution paragraph by paragraph, and according to the threshold value of setting, the high segmentation curve of similitude is retained；
xxj=[xx1,…,xxj,…,xxm(j)] represent the signal of effective process cycle that j-th of process curve is partitioned into
Data acquisition system (signaling point is k), j=1 ..., m.As can be seen thatSs
Starting point is sampled for process curve, Se is that process curve samples end point, mSs(j)For process curve starting point call number, mSe(j)
Process curve end point call number；And have:
As shown in Fig. 2, certain, which intelligently equips normal operation curve, is presented certain periodicity, but amplitude and frequency are not solid
Fixed, but change with the change of technological parameter.Dividing method of the invention is applied to the curve, obtained result is such as
Shown in Fig. 3, determine through similarity, there is no the section that needs are given up, segmentation result is ideal.
In short, the amplitude-frequency time-varying process signal dividing method of the present invention based on sliding window, passes through setting one
Sliding window determines lower segmentation threshold point, lower cut-off rule is connected as, according to lower cut-point to process curve according to sliding mean value
Process cycle segmentation is carried out, and the evaluation of effect can also be split according to curve similarity, obtains preferable segmentation effect.
Claims (10)
1. a kind of amplitude-frequency time-varying process signal dividing method based on sliding window, it is characterised in that: the process signal segmentation side
Method the following steps are included:
1) sliding window is set, and determines that the window of the sliding window is big according to the process cycle of amplitude-frequency time-varying process curve
Small and sliding step；
2) amplitude-frequency time-varying process curve being traversed using the sliding window of step 1) setting and seeking sliding mean value, sliding mean value is to slide
The lower segmentation threshold point of amplitude-frequency time-varying process curve is arranged according to sliding mean value for the average value that each signaling point is corresponded in dynamic window,
The lower cut-off rule of successive segmentation can be carried out to amplitude-frequency time-varying process curve using the setting of lower segmentation threshold point；
3) amplitude-frequency time-varying process curve is determined according to positioned at lower cut-off rule amplitude-frequency time-varying process curve signal minimum point below
Lower cut-point, according to amplitude-frequency time-varying process curve lower cut-point to amplitude-frequency time-varying process curve carry out signal process cycle
Segmentation.
2. a kind of amplitude-frequency time-varying process signal dividing method based on sliding window as described in claim 1, it is characterised in that: institute
It states in step 1), the size of sliding window is 1.5~3 times of the process cycle, and the sliding step of sliding window is 1~5.
3. a kind of amplitude-frequency time-varying process signal dividing method based on sliding window as described in claim 1, it is characterised in that: institute
It states in step 2), lower segmentation threshold point is sliding window center in the position of sampling time dimension, in the position of signal value dimension
Equal to sliding mean value and ΔtDifference, ΔtFor amplitude-frequency time-varying process curve peak-to-peak value and factor betatProduct.
4. a kind of amplitude-frequency time-varying process signal dividing method based on sliding window as claimed in claim 3, it is characterised in that: institute
State βtValue range be 0.1~0.3.
5. a kind of amplitude-frequency time-varying process signal dividing method based on sliding window, feature exist as claimed in claim 1 or 3
In: in the step 2), all lower segmentation threshold points are connected and obtain lower cut-off rule.
6. a kind of amplitude-frequency time-varying process signal dividing method based on sliding window as described in claim 1, it is characterised in that: institute
State in step 3), the determination of lower cut-point specifically includes the following steps: to be located in amplitude-frequency time-varying process curve lower cut-off rule with
Under curve section extract, pass through traverse determine every section of curve section on corresponding signal minimum point.
7. a kind of amplitude-frequency time-varying process signal dividing method based on sliding window as claimed in claim 6, it is characterised in that: institute
The determination for stating lower cut-point is further comprising the steps of: by the most narrow spacing of the sampling interval distance of adjacent signals minimum point and setting
From threshold value comparison, if the sampling interval distance of adjacent signals minimum point is greater than the threshold value, stick signal minimum point, instead
It, then give up the wherein signal minimum point of sampling time rearward, by all signal minimum points for retaining as lower cut-point,
Wherein minimum threshold of distance is 2~10.
8. a kind of amplitude-frequency time-varying process signal dividing method based on sliding window as described in claim 1, it is characterised in that: institute
It is further comprising the steps of to state process signal dividing method: to the process cycle signal being partitioned into step 3), seeking corresponding segmentation
The similarity of curve filters out effective process cycle signal according to the similarity.
9. a kind of amplitude-frequency time-varying process signal dividing method based on sliding window as claimed in claim 8, it is characterised in that: institute
The similarity for stating segmentation curve is sought using dynamic time warping algorithm, and each section of process cycle signal being partitioned into is utilized should
Algorithm simultaneously acquires similarity value referring to specified standard technology periodic signal, if similarity value is greater than the threshold value of setting, retains
The segment process periodic signal being partitioned into；Otherwise, give up the segment process periodic signal being partitioned into.
10. a kind of amplitude-frequency time-varying process signal dividing method based on sliding window as claimed in claim 9, it is characterised in that:
The standard technology periodic signal is specified from all process cycle signals being partitioned into.
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