CN101025430A - Cage type asynchronous motor rotor strip-broken failure detecting method - Google Patents

Abstract

A cage-type asynchronous motor rotor broken bar fault detection method and device, which belong to the detection technology field, are used to solve the problem of online detection of rotor broken bar initial faults. Its technical solution is: it obtains its fundamental wave, that is, the reference signal u _S by continuously refining the Fourier transform of the collected stator current instantaneous signal i _s , and then calculates the stator current instantaneous signal u _S and its frequency f ₁ The signal i _s is adaptively filtered, and then the filtered output signal e _T is continuously refined by Fourier transform to determine the ratio of the current (1±2s) f ₁ side frequency component to the amplitude of the fundamental component and take it as a fault feature , and finally determine the fault index according to the detection threshold, and judge whether there is a broken rotor bar fault according to the fault index. The invention can detect the incipient broken rotor bar fault of the asynchronous motor on-line with high sensitivity and high reliability.

Description

Cage type asynchronous motor rotor strip-broken failure detecting method

Technical field

The present invention relates to a kind of method and device that can online detection cage type asynchronous motor rotor strip-broken fault, belong to the detection technique field.

Background technology

Cage type asynchronous motor is in operational process, rotor bar is subjected to the effect of alterante stresses such as radial electromagnetic force, rotating electromagnetic power, centrifugal force, thermal flexure amount of deflection power, the rotor manufacturing defect all may cause broken bar fault in addition, and this kind fault probability of happening is about 15%.

Rotor broken bar is typical gradual fault, common 1,2 bar failure of initial stage, then development decline even shutdown so that motor is exerted oneself gradually.Therefore, must implement the online detection of rotor bar breaking fault, particularly the online detection of the property sent out rotor bar breaking fault just.

After the cage type asynchronous motor generation rotor bar breaking fault, (1 ± 2s) f will appear in its stator current ₁(s is a revolutional slip to the extra current component of frequency, f ₁Be line frequency), this current component is called the side frequency component, can be used as the rotor bar breaking fault feature.And stator current signal is easy to gather, and therefore the stator current signal frequency spectrum analysis method based on Fourier transform is widely used in the rotor bar breaking fault detection.

Initial rotor strip-broken failure detecting method is that the stable state stator current signal is directly carried out spectrum analysis, according to whether there being (1-2s) f in the spectrogram ₁Frequency component judges that rotor has or not disconnected bar.When slightly breaking bar owing to rotor, (1-2s) f ₁The amplitude of component is with respect to f ₁Component is very little, and asynchronous motor when operation revolutional slip s is very little, (1-2s) f ₁With f ₁These two frequency numerical value are approaching, if directly do the Fourier spectrum analysis, and (1-2s) f then ₁Component may be by f ₁The leakage of component is flooded.This is the weak point of the method.

In order to remedy the deficiency of the method, development has formed adaptive filter method and starting current Time-Varied Spectrum Analysis method, and the core of adaptive filter method is: at first adopt adaptive filter method to offset stator current f ₁Frequency component is carried out spectrum analysis afterwards again, and this can give prominence to rotor bar breaking fault characteristic component---(1-2s) f in spectrogram ₁Frequency component, thus the rotor bar breaking fault detection sensitivity significantly improved.

Fig. 2 is the theory diagram of adaptive filter method.Among Fig. 2, i _SRepresent actual stator current signal, it comprises signal S to be extracted _TWith noise n _T, and u _SIt is reference signal.Here, S _TBe (1-2s) f in the stator current ₁Frequency component, n _TBe the f in the stator current ₁Frequency component, and e _TThen represent i _sMake auto adapted filtering and handle resulting signal afterwards.If the response of sef-adapting filter is y _T, obviously, e _T=i _S-y _TAccording to e _TSize, adjust the parameter of wave filter, appropriate change y by adaptive algorithm _T, can make y _TUnder the meaning of least mean-square error, offset n _T, and e _TTo under the meaning of least mean-square error, approach signal S to be extracted _T

When adopting adaptive filter method, noise u _SAdopt test circuit shown in Figure 3 to obtain.Obviously, resistance R ₁On voltage signal be i among Fig. 2 _s, and resistance R ₂On voltage signal when net capacity is enough big, only contain f ₁Frequency component can be used as noise u _SAmong Fig. 3, resistance R ₁Effect be that secondary side current signal with current transformer CT is converted into a voltage signal that amplitude is suitable, resistance R ₂Be connected to the secondary side of voltage transformer pt.

The weak point of adaptive filter method is following two aspects.At first, this method needs test circuit shown in Figure 3 to obtain noise signal u _S, hardware circuit is slightly complicated.Secondly and since motor itself intrinsic asymmetric, air gap eccentric centre, rotor misalignment and other factor, even asynchronous motor is in normal operating condition, also may comprise (1 ± 2s) f in its stator current ₁And other frequency component, and for different asynchronous motors, (Fig. 4, Fig. 5 are respectively Y100L-2 type, the Y100L1-4 type rotor normal motor stator a phase current auto adapted filtering frequency spectrum under full load conditions to the situation complexity; Fig. 5, Fig. 6 represent the stator a phase current auto adapted filtering frequency spectrum of Y100L-2 type motor under fully loaded and sliver of rotor and two bar failure situations respectively).This easily obscures mutually with the rotor bar breaking fault feature, causes erroneous judgement, influences the fault detect reliability.Adaptive filter method can not be taken into account above-mentioned factor, and it is not enough that reliability is still disliked.

Starting current Time-Varied Spectrum Analysis method is gathered the stator current signal of cage type asynchronous motor in start-up course, and it is done the segmentation spectrum analysis, obtains time varying spectrum, judges that in view of the above rotor has or not disconnected bar.This method possesses distinct advantages: at first, s is bigger in start-up course, thus in spectrogram (1-2s) f ₁Frequency component can be away from f ₁Frequency component, this can reduce the requirement to the spectrum analysis frequency resolution; Secondly, (1-2s) f in start-up course ₁Frequency component and f ₁The ratio of the amplitude of the ratio of frequency component amplitude during much larger than steady-state operation, thereby make (1-2s) f ₁Frequency component is easy to detect.

The weak point of starting current Time-Varied Spectrum Analysis method is: must wait for that electric motor starting can use.Similar with adaptive filter method, this method can not take into account motor itself intrinsic asymmetric, air gap eccentric centre, rotor misalignment and other factor, reliability still remains to be improved.

Summary of the invention

The object of the present invention is to provide a kind of can high sensitivity, the asynchronous motor rotor strip-broken failure detecting method and the device of the online detection cage type asynchronous motor rotor strip-broken fault in high reliability ground.

The alleged problem of the present invention realizes with following technical proposals:

A kind of cage type asynchronous motor rotor strip-broken failure detecting method the steps include: that it passes through stator current momentary signal i to gathering _sDo continuous refinement Fourier transform, obtaining its first-harmonic is reference signal u _S, again according to reference signal u _SAnd frequency f ₁To stator current momentary signal i _SDo auto adapted filtering, then to the filtering output signal e _TDo continuous refinement Fourier transform, determine current (1 ± 2s) f ₁Side frequency component and the ratio of fundametal compoment amplitude and it as fault signature, determine fault index according to detection threshold at last, judge whether to exist rotor bar breaking fault according to fault index.

Above-mentioned cage type asynchronous motor rotor strip-broken failure detecting method, fault index calculates as follows:

A. measure a phase stator current momentary signal i _s:

For high-voltage motor, adopt 1 current clamp to measure a phase stator current momentary signal at current transformer CT secondary side; For low voltage motor, adopt 1 current clamp directly to measure a phase stator current momentary signal at the connecting terminal of motor place;

B. to stator current momentary signal i _sDo continuous refinement Fourier transform, determine the frequency f of its fundametal compoment ₁, amplitude I _mWith initial phase angle φ, form reference signal u _S:

For sample frequency is f _s, sampling number is the time series i (t of N _k),

u _S(k)＝I _msin(2πf ₁kT _S+φ+π)

Wherein, k=0,1,2, Λ, N-1, I _m, f ₁, φ determines by continuous refinement Fourier transform.

C. according to the fundametal compoment frequency f ₁, reference signal u _STo stator current momentary signal i _sDo auto adapted filtering, offset its fundametal compoment, obtain the filtering output signal e _T

D. to the filtering output signal e _TDo continuous refinement Fourier transform, inquiry (1 ± 2s) f in its continuous refinement spectrogram ₁The side frequency component information is determined current (1 ± 2s) f ₁Side frequency component and f ₁The ratio ratio of component amplitude _{(1-2s) f1}+ ratio _{(1+2s) f1},

Wherein, ratio _{(1-2s) f1}Be (1-2s) f ₁Side frequency component and f ₁The ratio of component amplitude, ratio _{(1+2s) f1}Be (1+2s) f ₁Side frequency component and f ₁The ratio of component amplitude;

E. determine fault index:

Under the situation of not setting up normal motor sample reference paper as yet, according to conventional experience detection threshold is set and (is approximately

Z _rBe the rotor slot number), ratio _{(1-2s) f1}+ ratio _{(1+2s) f1}Be fault index with the ratio of detection threshold;

F. whether exist according to the fault index failure judgement:

Fault index numerical value＜1, the expression motor is in health status, and its numerical value is littler, and health status is clearer and more definite; Fault index numerical value＞1, the expression motor is in malfunction, and its numerical value is bigger, and malfunction is more serious.

Above-mentioned cage type asynchronous motor rotor strip-broken failure detecting method is for can be in the filtering output signal e _TContinuous refinement spectrogram in accurately the inquiry (1 ± 2s) f ₁The side frequency component information, should calculate revolutional slip s earlier:

$s=1-\frac{P}{Z_r}(\frac{{\mathrm{<figure-callout\; id="1"\; label="f\; rsh\; f"\; filenames="A20071006163400131.png,A20071006163400141.png"\; state="\{\{state\}\}">f</figure-callout>}}_{\mathrm{rsh}}}{f_{}}\&PlusMinus;v),v=\mathrm{1,3,5},\mathrm{\&Lambda;}$

Wherein, f _RshFor rotor tooth slot harmonic component frequency, P are the motor number of pole-pairs, Z _rBe the rotor slot number.

Then according to the fundametal compoment frequency f ₁, revolutional slip s, in the filtering output signal e _TContinuous refinement spectrogram in the inquiry (1 ± 2s) f ₁The side frequency component information is determined current (1 ± 2s) f ₁Side frequency component and f ₁The ratio ratio of component amplitude _{(1-2s) f1}+ ratio _{(1+2s) f1}

Above-mentioned cage type asynchronous motor rotor strip-broken failure detecting method, for eliminate real electrical machinery itself the influence of intrinsic asymmetric, air gap eccentric centre, rotor misalignment and other factor, should be under the rotor normal condition, according to revolutional slip s and fault signature ratio _{(1-2s) f1}+ ratio _{(1+2s) f1}Concrete numerical value set up sample database, and the detection threshold of adjusting in view of the above:

If the current numerical value of revolutional slip between sample data revolutional slip upper and lower limit, then adopts the linear interpolation mode that detection threshold is set; Otherwise, determine immediate with it sample data revolutional slip, as detection threshold, and make safety factor be not less than 1 the fault signature numerical value of correspondence.

The present invention is by gathering asynchronous motor stator winding current signal, and data acquisition card is sent to computing machine with this signal, by computing machine current signal is handled, and judges whether to exist rotor bar breaking fault, and operating process is simple and convenient.Utilize stator current (1 ± 2s) f ₁Frequency component is as fault signature, continuous refinement Fourier transform, auto adapted filtering, the estimation of rotor tooth slot harmonic revolutional slip, detection threshold automatic-adjusting technique are organically combined, when improving sensitivity, eliminated motor itself intrinsic asymmetric, air gap eccentric centre, rotor misalignment and other factor to extracting the influence of fault signature, effectively prevented erroneous judgement.But high sensitivity, the online detection asynchronous motor in high reliability ground be the property sent out rotor bar breaking fault just.

Description of drawings

The invention will be further described below in conjunction with accompanying drawing.

Fig. 1 is an electric theory diagram of the present invention;

Fig. 2 is the theory diagram of adaptive filter method;

Fig. 3 is the schematic diagram of adaptive filter method signal acquisition circuit;

Fig. 4 is the stator a phase current auto adapted filtering frequency spectrum of Y100L-2 type rotor normal motor under full load conditions;

Fig. 5 is the stator a phase current auto adapted filtering frequency spectrum of Y100L1-4 type rotor normal motor under full load conditions;

The stator a phase current auto adapted filtering frequency spectrum that Fig. 6 is a Y100L-2 type motor under fully loaded and 1 bar failure situation;

The stator a phase current auto adapted filtering frequency spectrum that Fig. 7 is a Y100L-2 type motor under fully loaded and 2 bar failure situations;

Fig. 8 is the normal sample notebook data of experiment motor;

Stator a phase current when Fig. 9 is experiment motor semi-load and a bar failure;

Stator a phase current frequency spectrum when Figure 10 is experiment motor semi-load and a bar failure.

Each label is among the figure: PT, voltage transformer (VT), CT, current transformer, M, motor, R1, R2, resistance.

The meaning of used each symbol: s, revolutional slip in the literary composition; f ₁, line frequency (fundamental frequency); i _s, stator current signal; S _T, auto adapted filtering signal to be extracted; n _T, noise signal; u _S, (auto adapted filtering) reference signal; e _T, the filtering output signal; y _T, filter response; I _m, the reference signal amplitude; φ, reference signal initial phase angle; f _s, sample frequency; N, sampling number; I (t _k), the current sample instantaneous value; t _k, sampling instant; Ratio _{(1-2s) f1}, (1-2s) f ₁Side frequency component and f ₁The ratio of component amplitude; Ratio _{(1+2s) f1}, (1+2s) f ₁Side frequency component and f ₁The ratio of component amplitude; f _Rsh, rotor tooth slot harmonic component frequency, P, motor number of pole-pairs; Z _r, the rotor slot number; T _s, sampling time interval; A (n), b (n), a (0) represent fourier coefficient; Δ f, frequency discrimination unit.

Embodiment

The present invention adopts circuit shown in Figure 1 to detect, this circuit is made up of current transformer CT, data acquisition card and computing machine, described current transformer is connected on the phase line of asynchronous motor stator winding, its signal output part connects the simulating signal input channel 5 (input terminal 5 and 17) of data acquisition card, and the output port of described data acquisition card connects the USB mouth of computing machine.Data acquisition card adopts auspicious rich magnificent RBH8321 type data acquisition card, and the model of computing machine is DELL M1210, data acquisition card is integrated circuit such as low-pass filter, signals collecting maintenance, mould/number conversion.The stator current momentary signal is delivered to data acquisition card, and data acquisition card is connected in portable computer by USB interface.Portable computing machine control signal capture card is with appropriate frequency sampling stator current momentary signal, and is stored in hard disk, by computing machine current signal handled again, judges whether to exist rotor bar breaking fault.This matched with devices software is based on Windows XP operating system and adopt the establishment of Visual C++ application development platform.

Use continuous refinement Fourier transform and auto-adaptive filtering technique and can guarantee to extract in high sensitivity motor stator electric current (1 ± 2s) f ₁Frequency component; Use rotor tooth slot harmonic revolutional slip estimation technique and can judge correctly whether this component is really caused by rotor bar breaking fault; Application then can suitably be provided with detection threshold based on the detection threshold of sample learning from the strategy of adjusting, and avoids fault omission and erroneous judgement.

Use continuous refinement fourier transform method, can obtain the accurate and analytical expression of a certain main frequency component in the signal to be analyzed, i.e. frequency, amplitude and initial phase angle.

For sample frequency is f _s, sampling number is the time series i (t of N _k), discrete Fourier progression is:

$\left\{\begin{array}{c}a\left(n\right)=\frac{2}{N}\underset{k=0}{\overset{N-1}{\mathrm{\&Sigma;}}}i\left(t_k\right)\cos (2\mathrm{\&pi;kn}/N)\\ b\left(n\right)=\frac{2}{N}\underset{k=0}{\overset{N-1}{\mathrm{\&Sigma;}}}i\left(t_k\right)\sin (2\mathrm{\&pi;kn}/N)\\ a\left(0\right)=\frac{1}{N}\underset{k=0}{\overset{N-1}{\mathrm{\&Sigma;}}}i\left(t_k\right)\\ n=\mathrm{0,1,2},\mathrm{\&Lambda;},N-1\end{array}\right.---\left(1\right)$

Wherein, t _k=kT _s, T _s=1/f _s, k=0,1,2, Λ, N-1, a (n), b (n), a (0) represent fourier coefficient.

Fast Fourier Transform (FFT) is the special circumstances of above-mentioned discrete transform, i.e. N=2 ^m(m is a positive integer), at this moment, Fourier transform can adopt the recursion fast algorithm.This conversion, frequency discrimination unit are Δ f=f _s/ N, N is inversely proportional to sampling number.Obviously,, must increase sampling number exponentially if wish to improve the frequency discrimination ability, sampling number one timing, the frequency discrimination ability can't further improve.

Time series i (t _k) comprise signal 0 to f _sInformation in/2 these frequency domains if spectrum curve is regarded as continuously, thinks that promptly the n in the formula (1) is a continuous real number that belongs to interval [0, N/2], and formula (1) can be rewritten an accepted way of doing sth (2).At this moment, the frequency discrimination ability no longer is subjected to the restriction of sampling number, and the value of frequency f is continuous.

$\left\{\begin{array}{c}a\left(f\right)=\frac{2}{N}\underset{k=0}{\overset{N-1}{\mathrm{\&Sigma;}}}i\left(t_k\right)\cos (2\mathrm{\&pi;kf}/f_s)\\ b\left(f\right)=\frac{2}{N}\underset{k=0}{\overset{N-1}{\mathrm{\&Sigma;}}}i\left(t_k\right)\sin (2\mathrm{\&pi;kf}/f_s)---\left(2\right)\\ 0<f\&le;f_s/2\end{array}\right.$

When using continuous refinement Fourier transform, refinement scope, refinement density can be carried out step by step, to improve computing velocity.

The sensitivity and the reliability of the fault detect of refinement Fourier pair raising cage type asynchronous motor rotor strip-broken are significant continuously.At first, can accurately determine motor stator current first harmonics frequency f by continuous refinement Fourier transform ₁Secondly, can determine motor stator current first harmonics component accurate and analytical expression, i.e. frequency f ₁, amplitude I _mWith initial phase angle φ, form reference signal u in view of the above _S, handle stator current signal is done auto adapted filtering.

Reference signal u _SDetermine according to formula (3).

$\left\{\begin{array}{c}{u}_S\left(k\right)=I_m\sin (2\mathrm{\&pi;}{f}_{1}k{T}_S+\mathrm{\&phi;}+\mathrm{\&pi;})\\ k=\mathrm{0,1,2},\mathrm{\&Lambda;},N-1\end{array}\right.---\left(3\right)$

Fig. 2 is an adaptive filtration theory, and its basic ideas are: adopt adaptive filter method to offset motor stator electric current f ₁Component, outstanding (1-2s) f in spectrogram ₁Component---rotor bar breaking fault feature, thus the sensitivity that rotor bar breaking fault detects significantly improved.Reference signal u _SUsing continuous refinement Fourier transform determines.

In motor operation course, because rotor mmf teeth groove harmonic wave and first-harmonic air-gap flux reciprocation will comprise rotor tooth slot harmonic component in the stator current.According to its frequency f _Rsh, motor number of pole-pairs P and rotor slot count ZT and can determine motor slip ratio by formula (4).

$s=1-\frac{P}{Z_r}(\frac{f_{\mathrm{rsh}}}{{\mathrm{<figure-callout\; id="1"\; label="f"\; filenames="A20071006163400131.png,A20071006163400141.png"\; state="\{\{state\}\}">f</figure-callout>}}_1}\&PlusMinus;v),v=\mathrm{1,3,5},\mathrm{\&Lambda;}---\left(4\right)$

In engineering reality, often select (1 ± 2s) f ₁Frequency component and f ₁The ratio ratio of component amplitude _{(1-2s) f1}, ratio _{(1+2s) f1}As fault signature, by judging whether its numerical value surpasses a certain threshold value and realize that rotor bar breaking fault detects.

For take into account real electrical machinery itself intrinsic asymmetric, air gap eccentric centre, rotor misalignment and other factor, should adopt detection threshold based on sample learning from the strategy of adjusting to improve sensitivity and reliability.

Suppose that initial rotor is normal, according to revolutional slip s and fault signature ratio _{(1-2s) f1}+ ratio _{(1+2s) f1}Concrete numerical value set up sample database, this is because fault signature ratio _{(1-2s) fi}+ ratio _{(1+2s) f1}Basically only depend on revolutional slip s.

Fig. 8 represents the normal sample notebook data of Y100L-2 type experiment motor.Set up sample database, should pay attention to its simple and direct property, and, contain the revolutional slip normal fluctuation as far as possible in conjunction with the motor actual operating.

As soon as the normal motor sample database is set up, can carry out from adjusting detection threshold according to the current numerical value of revolutional slip, specific as follows: if the current numerical value of revolutional slip between sample data revolutional slip upper and lower limit, then adopts the linear interpolation mode that detection threshold is set; Otherwise, determine immediate with it sample data revolutional slip, as detection threshold, and make safety factor be not less than 1 the fault signature numerical value of correspondence.

From Fig. 6, Fig. 7 as can be seen, rotor bar breaking fault after taking place in real electrical machinery, and its stator current frequency spectrum often comprises a plurality of spectrums peak, and (1 ± 2s) f ₁Side frequency component spectrum peak-to-peak value may not be maximum.This be attributable to real electrical machinery itself intrinsic asymmetric, air gap eccentric centre, rotor misalignment and other factor.These the spectrum peaks very easily with rotor bar breaking fault feature---(1 ± 2s) f ₁Frequency component is obscured mutually, causes erroneous judgement, influences the reliability that rotor bar breaking fault detects.Therefore, when carrying out the rotor bar breaking fault detection, should predict f ₁With the concrete numerical value of s, thereby in the stator current frequency spectrum, on purpose inquire about (1 ± 2s) f ₁The side frequency component, and it is done quantitative test, to guarantee the broken bar fault detecting reliability.

According to Fig. 4,5 as can be known, owing to technology, manufacturing and reason is installed, intrinsic asymmetric, air gap eccentric centre, rotor misalignment, the other factors in addition to a certain degree of any real electrical machinery certainty itself, even motor is in normal operating condition, also may comprise (1 ± 2s) f in its stator current ₁And other frequency component.And for different asynchronous motors, the situation complexity.

How suitably this be provided with detection threshold to take into account this problem of sensitivity and reliability simultaneously with regard to having proposed.If it is too high that detection threshold is provided with, then be unfavorable for improving sensitivity.For example, rotor broken bar detection method in the past is mostly with (1-2s) f ₁Component and f ₁Likening to of component amplitude is fault signature, and detection threshold generally is set at 1～2%, and be obviously relatively conservative for Y100L-2 type experiment motor, will cause the fault omission.Because during bar failure of this rotor, its stator current (1-2s) f ₁Component and f ₁The ratio of component amplitude only is 0.67%.On the other hand, low if detection threshold was provided with, so that be lower than motor stator current (1-2s) f when normal operation ₁Component and f ₁The ratio of component amplitude must cause the fault erroneous judgement, and reliability is not just known where to begin yet.

The analysis showed that more than the rotor bar breaking fault that carries out high sensitivity, high reliability detects, must at first clear and definite normal motor (1 ± 2s) f ₁Side frequency component and f ₁The ratio of component amplitude is provided with suitable detection threshold in view of the above, to avoid fault omission and erroneous judgement.

The asynchronous motor just property sent out rotor strip-broken failure detecting method can be realized above-mentioned purpose by using based on the detection threshold of sample learning from the strategy of adjusting.

Fig. 6, Fig. 7 show, behind the cage type asynchronous motor generation rotor bar breaking fault, and stator current (1-2s) f ₁, (1+2s) f ₁Frequency component is that coupling occurs, and for disconnected bar detection sensitivity and reliability consideration, should inquire about (1 ± 2s) f simultaneously ₁Frequency component information.

Stator a phase current frequency spectrum when the stator a phase current when Fig. 9 represents Y100L-2 type experiment motor semi-load and a bar failure, Figure 10 are represented Y100L-2 type experiment motor semi-load and a bar failure, concrete data are shown in table 2.

Experimental result under table 2 motor semi-load and the bar failure situation

f 1(Hz)	50.01
		s(％)	1.78
(1-2s)f 1(Hz)	48.27
		(1+2s)f 1(Hz)	51.83
f 1Component amplitude (A)	3.7113
		(1-2s)f 1Component amplitude (A)	0.0227
(1+2s)f 1Component amplitude (A)	0.0235
		Fault signature amount ratio (1-2s)f1+ratio (1+2s)f1(％)	1.24
Do not set up the detection threshold (%) under the normal motor sample reference paper situation as yet	1.0
		Set up the detection threshold (%) under the normal motor sample reference paper situation	0.40

Claims (4)

1. A method for detecting broken rotor bars of cage-type asynchronous motors, which is characterized in that it obtains its fundamental wave reference signal u _S by performing continuous refinement Fourier transform on the collected stator current instantaneous signal i _s , and then according to The reference signal u _S and its frequency f ₁ do adaptive filtering on the stator current instantaneous signal i _s , and then perform continuous refinement Fourier transform on the filtered output signal e _T to determine the current (1±2s) f ₁ side frequency component and The ratio of the fundamental wave component amplitude is used as the fault feature, and finally the fault index is determined according to the detection threshold, and the rotor broken bar fault is judged according to the fault index. 2. According to claim 1, the method for detecting broken rotor bars of cage-type asynchronous motors is characterized in that the fault index is calculated according to the following steps: a. Measure the instantaneous signal i _s of one-phase stator current: b. Continuously refine the Fourier transform of the instantaneous signal i _s of the stator current to determine the frequency f ₁ , amplitude I _m and initial phase angle φ of the fundamental component to form a reference signal u _S : For the time series i(t _k ) whose sampling frequency is f _s and the number of sampling points is N, u _S (K)＝I _m sin(2πf ₁ kT _S +φ+π) Wherein, k=0, 1, 2, Λ, N-1, _Im , f ₁ , φ are determined by continuous refinement Fourier transform. c. According to the frequency f ₁ of the fundamental wave component and the reference signal u _S , perform adaptive filtering on the instantaneous signal _is of the stator current to offset its fundamental wave component, and obtain the filtered output signal e _T ; d. Perform continuous refinement Fourier transform on the filtered output signal e _T , query (1±2s) f ₁ side frequency component information in its continuous refinement spectrogram, and determine the current (1±2s) f ₁ side frequency component Ratio _(1-2s)f1 +ratio _(1+2s)f1 with the amplitude of the f ₁ component, Among them, ratio _{(1-2s) f1} is the ratio of (1-2s) f ₁ side frequency component to f ₁ component amplitude, ratio _{(1+2s) f1} is (1+2s) f ₁ side frequency component and f ₁ ratio of component magnitudes; e. Determine the failure index: In the case that no normal motor sample reference files have been established, the detection threshold is set according to conventional experience, which is approximately

Among them, Zr is the number of rotor slots, and the ratio of ratio _(1-2s)f1 +ratio _(1+2s)f1 to the detection threshold is the failure index; f. Judging the fault according to the fault index: If the fault index value<1, it means that the motor is in a healthy state, and the smaller the value, the clearer the health state; if the fault index value>1, it means that the motor is in a fault state, and the larger the value, the more serious the fault state. 3. According to claim 1 or 2, the method for detecting broken rotor bars of cage-type asynchronous motors is characterized by determining the slip s: $\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>\frac{\mathrm{<span\; class="notranslate">\; P</span>}}{{\mathrm{<span\; class="notranslate">\; Z</span>}}_{\mathrm{<span\; class="notranslate">\; r</span>}}}<span\; class="notranslate">\; (</span>\frac{{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; rsh</span>}}}{{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}}<span\; class="notranslate">\; \&PlusMinus;</span>\mathrm{<span\; class="notranslate">\; v</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; v</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1,3,5</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; \&Lambda;</span>}$ Among them, f _rsh is the harmonic frequency of the rotor cogging, P is the number of pole pairs of the motor, Z _r is the number of rotor slots, Then, according to the fundamental component frequency f ₁ and the slip rate s, query the (1±2s) f ₁ edge frequency component information in the continuous refinement spectrogram of the filtered output signal e _T to determine the current (1±2s) f ₁ edge Ratio _(1-2s)f1 +ratio _(1+2s)f1 of frequency component and f ₁ component amplitude. 4. According to claim 3, the method for detecting the broken bars of the cage-type asynchronous motor rotor is characterized in that, under the normal condition of the motor rotor, according to the slip s and the fault characteristic ratio _(1-2s)f1 +ratio _{(1+ 2s) Establish a sample database based on the specific value of f1} , and set the detection threshold accordingly: If the current value of the slip is between the upper and lower limits of the sample data slip, use linear interpolation to set the detection threshold; otherwise, determine the closest sample data slip, and use the corresponding fault characteristic value as Check the threshold and make the reliability factor not less than 1.

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