This application claims priority to German Application No. 102023205738.7, filed Jun. 20, 2023, the entirety of which is hereby incorporated by reference.
The present disclosure is directed to devices for processing a digital signal and methods for processing a digital signal.
Condition monitoring algorithms, for example to detect a fault of a bearing such as a fault of an inner raceway of the bearing, require a constant rotational speed of the bearing to work properly.
Generally, condition monitoring algorithms perform spectral analysis of the rotating bearing to detect faults from specific tones and harmonics.
Rotational speed changes of the bearing during signal measurement smears out the spectral tones reducing the ability to identify the frequencies and harmonics that may be associated with faults, for example faults of an inner raceway of the bearing or faults of the outer raceway of the bearing.
Consequently, the present disclosure intends to correct deleterious effects of rotational speed changes to perform a spectral analysis.
According to an aspect, a method for processing a digital signal comprising samples of a continuous signal sampled at a fixed sample rate, the continuous signal being representative of vibrations of a bearing comprising a stationary ring and a rotating ring capable of rotating concentrically relative to the stationary ring is proposed.
The method comprises:
The method permits the use of existing constant rotation speed algorithms in conditions of varying rotational speed so that repetitive attempts to obtain constant-speed data acquisition are not necessary.
Taking into account the rotation speed of the rotating ring permits to take into account auxiliary speed measurements.
Advantageously, determining couples of control values from the determined moments comprises decomposing each determined moment into a first value equal to the integer part of the determined moment and a second value equal to the fractional part of the determined moment, each couple of control values comprising the first value and the second value.
Preferably, the Farrow structure comprises:
Advantageously, determining the rotation speed of the mobile ring comprises determining a continuous estimate of the rotation speed.
Preferably, the moments are identified from the rotation angle and/or speed of the rotating ring.
According to an aspect, a device for processing a digital signal comprising samples of a continuous signal sampled at a fixed sample rate, the continuous signal being representative of vibrations of a bearing comprising a stationary ring and a rotating ring capable of rotating concentrically relative to the stationary ring is proposed.
The device comprises:
Advantageously, the control means are configured to decompose each determined moment into a first value equal to the integer part of the determined moment and a second value equal to the fractional part of the determined moment, each couple of control values comprising the first value and the second value.
Preferably, the Farrow structure comprises:
According to an aspect, a bearing device is proposed.
The bearing device comprises:
Preferably, the first means comprise a second sensor configured to measure the rotation speed of the rotating ring.
Other advantages and features of the present disclosure will appear on examination of the detailed description of embodiments, in no way restrictive, and the appended drawings in which:
Reference is made to
The machine 1 comprises a housing 2 and a shaft 3 supported in the housing 2 by a rolling bearing 4 (e.g. roller bearing or ball bearing).
The rolling bearing 4 is provided with a rotating ring 5 mounted on the shaft 3, and with a stationary ring 6 mounted into the bore of the housing 2. The stationary ring 6 radially surrounds the rotating ring 5. The rotating and stationary rings 5, 6 rotate concentrically relative to one another.
The rolling bearing 4 is further provided with a row of rolling elements 7 radially interposed between inner and outer raceways of the rotating and stationary rings 5, 6. In the illustrated example, the rolling elements 7 are balls. Alternatively, the rolling bearing may comprise other types of rolling elements 7, for example rollers. In the illustrated example, the rolling bearing comprise one row of rolling elements 7. Alternatively, the rolling bearing comprise may comprise several rows of rolling elements.
A first sensor 8 is mounted in the housing 2 to measure vibrations of the bearing 4 undergoing rotational speed changes.
The first sensor 8 may be mounted on a bore of the housing 2.
In variant, the first sensor 8 may be mounted elsewhere on the machine, near the stationary ring 6 or in the vicinity of housing 2, for example.
The first sensor 8 delivers a continuous signal S8 representative of the vibrations of the bearing 4 to an input of a sampler 9.
The sampler 9 delivers a digital signal S9 comprising multiple sequential samples xp of the continuous signal S8 sampled at a fixed sample rate to a first input 101 of a device 10 for processing the digital signal S9, p being an integer.
First means 11 are intended to determine the rotation speed of the rotating ring 5 and to deliver the rotation speed of the rotating ring 5 to a second input 102 of the device 10.
The first means 11 comprise for example a second sensor intended to measure the rotation speed of the rotating ring 5 or may estimate the rotation speed of the rotating ring 5 for example, from a set of pulses generated at fixed intervals of angular rotation of a shaft or wheel attached via fixation means to the rotating ring 5 or similar tachometer related methods.
The bearing 4, the first sensor 8, the sampler 9, the device 10, and the first means 11 form a bearing device.
A memory (not represented) may store the output signal S9 and delivers the output signal S9 to the device 10.
A first output 103 of the device 10 is connected to first implementing means 12 implementing at least one constant speed time domain algorithm from a first output signal S103 delivered by the device 10 on the first output 103, for example to implement an enveloping fault detection algorithm.
A second output 104 of the device 10 is connected to second implementing means 13 implementing at least one constant speed spectrally oriented algorithm from a second output signal S104 delivered by the device 10 on the second output 104, for example to implement a fast Fourier transform paired with a fault frequencies detection method.
The first and second implementing means 12, 13 are for example each made of a processing unit implementing the said algorithm.
A processing unit 14 implements the first sensor 8, the sampler 9, the device 10, and the first means 11.
The device 10 comprises a Farrow structure 15 known from the document U.S. Pat. No. 4,866,647, identifying means 16, control means 17, and spectral analysis means 18.
The Farrow structure 15 comprises an input 151 connected to the input 101 of the device 10, an output 152 connected to the first output 103 of the device 10 and to an input 181 of the spectral analysis means 18, and comprises a control input 153 connected to an output 172 of the controlling means 17.
An output 182 of the spectral analysis means 18 is connected to the second output 104 of the device 10.
The spectral analysis means 18 comprise a spectral analysis algorithm ALGO1, for example a fast Fourier transform algorithm.
An input 161 of the identifying means 16 is connected to the second input 102 of the device 10 and an output of the identifying means 16 is connected to an input 171 of the controlling means 17.
The Farrow structure 15 iteratively adjusts intersample delays (resampling) of measurement data.
The Farrow structure 15 is based on a N order finite impulse response FIR filter with coefficients h(n, Δ) that may be varied by means of a control variable Δ equal to the inter-sample position or delay of the Farrow structure, n being an integer between 0 and N.
The filter coefficients h(n, Δ) are formed from a polynomial of the control variable Δ.
The coefficient h(n, Δ) is equal to:
The coefficients Cmn may be represented as a coefficient matrix C of dimension (M+1)×(N+1).
The transfer function H(z, Δ) of the Farrow structure 15 is given by:
The term Cm(z) refers to a subfilter of the Farrow structure 15, the Farrow structure 15 comprising M+1 subfilters.
The Farrow structure 15 delivers a signal S152 on its output 152.
The Farrow structure 15 comprises M+1 subfilters denoted CM(z), . . . , C1(z), C0(z), M+1 memory banks 19, 20, 21, M multipliers 22, 23 having each a variable gain G22, G23, and M adders 24, 25.
Each multiplier 22, 23 comprises an input, an output delivering a signal received on the input multiplied by the variable gain G22, G23, and a control input receiving the variable gain value.
Each adder 24, 25, comprises a first and a second inputs, and an output delivering the sum of the first and second inputs.
Each subfilter CM(z), . . . , C1(z), C0(z) comprises an input 26, 27, 28 connected to the input 151 of the Farrow structure and an output 29, 30, 31 connected to an input of a different memory bank 19, 20, 21.
An output of the Mth memory bank 19 is connected to the input of the Mth multiplier 22.
The first input of the Mth adder is connected to an output of the Mth multiplier 22 and a second input of the Mth adder is connected to the M−1th memory bank.
For P varying between 1 and M−1, P being an integer, the input of the Pth multiplier is connected to the output of the P+1th adder, the first input of the Pth adder is connected to the output of the Pth multiplier, and the second input of the Pth adder is connected to the P−1th memory bank.
For example, as seen in
The output of the final adder 25 is connected to the output 152 of the Farrow structure 15.
Each memory bank 19, 20, 21 is connected to the control input 153 to select which memory data item of each memory bank 19, 20, 21 is forwarded to the multiplier G22, G23 and adders 24, 25.
The control input of the M variable gains G22, G23 is connected to the control input 153 of the Farrow structure 15 to control the value of the variable gains having each the same value.
As the structure of the subfilters CM(z), . . . , C1(z), C0(z) is identical, only the structure of the subfilters CM(z) is detailed.
The subfilter CM(z) comprises a chain of N delay elements D 33, N+1 second multipliers 35, 36, 37, 38 and a second summer 39.
The N+1 second multipliers 35, 36, 37, 38 multiply N+1 sequential samples xn of the signal received on the input 26 of the subfilter CM(z) by the N+1 filter coefficients CM0 to CMN and deliver the multiplied sequential samples xn to the second summer 39.
The second summer 39 sums the N+1 sequential samples xn multiplied by the N+1 second multipliers 35, 36, 37, 38 and delivers the sum to the input of the memory bank 19.
In a step 40, the order N of the Farrow structure 15 and the order M of the polynomial is defined according to the required accuracy of the device 10.
At any single moment of time, the control value Δ of each multiplier G22, G23 is the same.
In another embodiment, the control value Δ of each multiplier G22, G23 may be varying on a sample by sample basis and are denoted Δn. The values of the fractional delay Δ n are controlled by a control unit of the device 10 (not represented) and are chosen according to the needed fractional delay to be applied to each input sample xn. The control unit also selects which data sample is extracted from memories 19, 20, 21 according to the fractional delay Δn to achieve the necessary integer component of the needed delay.
To provide for the implementation of a continuous range of delays, the Farrow structure relies on a polynomial curve fitting based on a set of fixed-delay reference filters. For example, assuming a bank of 8 reference filters each implementing a fixed delay, the fixed delay Δ for each reference filter could be chosen between −0.5 to 0.5 in increments of 0.125 so that the integer j varies between 0 and 7 with Δ0=−0.5, .Δ1=−0.375, . . . Δ7=+0.375.
In a step 41, a set of functions gj(n, Δj) is computed for each j value and a given n value.
The function gj may be for example equal to:
In step 42, the coefficients Cmn of the coefficient matrix C are determined so that for a given n value and the desired delay value Δ, the filter coefficient h(n, Δ) fits the polynomial interpolation of functions gj(n, Δj) defined by Cmn for all values of Δ between −0.5 to +0.5.
It is assumed that the coefficient matrix C is defined and that the subfilters CM(z), . . . , C1(z), C0(z) are parametrized according to the coefficient matrix C.
During a step 50, the sampler 9 delivers the digital signal S9 comprising the samples xp from the continuous signal S8 delivered by the sensor 8 and the first means 11 deliver a continuous estimate of the rotation speed of the rotating ring 5.
During a step 51, the identifying means 16 identify moments when the rotating ring has rotated from a predetermined rotation angle, for example π/4.
The moments are identified by the identifying means 16 from the rotation speed Ω of the rotating ring 5, for example by integrating the rotation speed Ω.
In variant, the moments are identified by the identifying means 16 from the rotation angle θ of the rotating ring 5.
During a step 52, the control means 17 determine couples of control values (Δi, Δf) from the moments determined by the identifying means 16.
The control means 17 decompose each moment into a first value equal to the integer part Δi of the determined moment and a second value equal to the fractional part Δf of the determined moment, each couple of control values comprising the first value Δi and the second value Δf.
The delay Δ is such that:
During a step 53, the control means 17 control the Farrow structure 15 from the couples of control values (Δi, Δf) so that the Farrow structure 14 applies to the digital signal S9 comprising the samples xp a time-varying sample rate conversion from the fixed sample rate to a time varying sampling, and delivers on the output 152 of the Farrow device 15 a resulting signal comprising the digital signal sampled at the time-varying sample interval achieving speed change compensation.
The resulting signal is the first output signal S152 delivered on the output 152 of the Farrow device 15.
The time-variation of the resulting sampling depends on the values of the couples of control values (Δi, Δf) delivered by the controlling means 17.
The control means 17 selecting the memory data item of each memory bank 10, 20, 21 stored at the address equal to the first value Δi, and control the M multipliers 22, 23 so that the variable gain of the M multipliers is equal to the second value Δf.
Points P1 to P8 are determined by the Farrow device 15 so that the samples (points P1 to P8) of the signal S152 are per the predetermined rotation angle, for example π/4.
The method goes back to step 50 with the next samples xp delivered by the sampler 9.
A graph SP3 is plotted and represents the spectrum delivered on the second output 103 of the device 10 when the rotation speed of the bearing 4 has undergone a 3% speed change during data collection after application of speed change compensation. This compares closely to the steady rotation speed.
In the graph SP1, three tones T10, T20, T30 are easily identifiable at the respective frequencies F1, F2, F3.
The tone T10 is the fundamental and the tones T20, T30 are two harmonics. The sharp characteristics of the graph SP1 is the assumed appearance of a constant speed spectrum.
In the graph SP2, three tones T11, T21, T31 having reduced peaks are hardly identifiable. It is not possible to ascertain their precise location so that the constant speed time domain algorithm implemented by the first implementing means 11 and the constant speed spectral oriented algorithm implemented by the second implementing means 12 may not ascertain if the three tones T11, T21, T31 are of interest. The skewness value of the graph SP1 is smaller than the reference skewness value.
In the graph SP3, three tones T12, T22, T33 are easily identifiable at the respective frequencies F1, F2, F3. The sharp characteristics of the original constant speed spectrum has been recovered.
The device 10 re-establishes the sharp peaks of the tones T12, T22, T32 and their frequencies F1, F2, F3.
The device 10 permits to use existing constant rotation speed algorithms when the rotation speed is varying so that repetitive attempts at data acquisition due to speed changes are not necessary.
The ability to permit use of data acquired under speed changes permits to expand the range of use cases, and allows more efficient data usage in bearing condition monitoring in general. As an example, the suppression of repetitive attempts at data acquisition permit to save supply power of a device comprising the sensor 8, the sampler 9 and the device 10, for example a wireless power comprising a supply source such as a battery.
The time-variation of the resulting sampling depends on the values of the couples of control values (Δi, Δf) delivered by the controlling means 17.
The control means 17 selecting the memory data item of each memory bank 10, 19, 20, 21 stored at the address equal to the first value Δi, and control the M multipliers 22, 23 so that the variable gain of the M multipliers is equal to the second value Δf.
The first value Δi and the second value Δf allow respectively a coarse and fine-level delay providing an accurate compensation for rotational speed changes.
Taking into account the rotation speed of the rotating ring 5 permits to take into account auxiliary speed measurements.
Number | Date | Country | Kind |
---|---|---|---|
102023205738.7 | Jun 2023 | DE | national |