Patent ID: 12203898

DETAILED DESCRIPTION

The technical solutions in the examples of the disclosure are clearly and completely described below with reference to the drawings in the examples of the disclosure. It is apparent that the described examples are only a part of the examples of the disclosure, and are not all of the examples. Based on the examples of the disclosure, all other examples obtained by a person of ordinary skill in the art without involving any inventive effort all fall within the scope of the disclosure.

In view of the shortcomings of the existing methods, the disclosure is directed to an urgent need for online characterization of baseline-free stress, and discloses a method for online stress monitoring without baseline data based on single-mode multi-frequency signal fusion. On the basis of an acousto-elastic effect of a Lamb wave, data fusion at multiple excitation frequencies is realized by fully utilizing the dispersion characteristics of the Lamb wave, and finally stress measurement without baseline data is realized. According to geometric dimensions of a structure to be measured, a suitable excitation frequency range is selected, and a low-order mode Lamb wave is excited inside the measured structure. Because contour structures of S0- and A0-mode Lamb waves are different, the excitation of a single S0-mode Lamb wave is realized by symmetrically exciting upper and lower surfaces of the measured structure. Due to the dispersion characteristics of Lamb waves, acousto-elastic coefficients of S0-mode Lamb waves with different frequencies are different. Therefore, acoustic time changes of two excitation frequencies caused by stress are completely different at the same propagation distance. However, relationships between stress and group velocity at two excitation frequencies are linear. Therefore, it can be determined that there is still a linear relationship between a propagation acoustic time ratio of S0-mode Lamb waves with different frequencies and stress at a fixed propagation distance. Through the relationship, an absolute stress state of the measured object may be characterized, and data in a zero-stress state is not required as baseline data. In the method of the disclosure, it is very simple to excite and receive the Lamb wave, and it is only necessary to bond a common disk piezoelectric wafer sensor to a measured structure. Therefore, the method of the disclosure combines the acousto-elastic effects of Lamb waves with different modes, and can realize online stress monitoring without baseline data.

With reference toFIGS.1-6, the disclosure provides a method for online stress monitoring without baseline data based on single-mode multi-frequency signal fusion. Firstly, a dispersion curve of a Lamb wave needs to be established according to a structure of a measured object, a cut-off frequency of a first-order Lamb wave mode is determined to ensure that an excitation frequency of a Lamb signal is below a first-order cut-off frequency, and a pure S0-mode Lamb wave is obtained inside the measured object by means of symmetric excitation. Then, a linear relationship between the S0-mode Lamb wave at different excitation frequencies and stress is obtained through theoretical analysis, and a linear relationship between a propagation acoustic time ratio of the S0-mode Lamb wave at two excitation frequencies and stress at a fixed propagation distance is further determined. A chirp signal is loaded inside a signal generator according to a selected excitation frequency range, a transmitting probe is driven after subjecting to a power amplifier, first-stage weak signal amplification is performed on a signal of a receiving probe, the signal is received by a high-speed acquisition board card and transmitted to an upper computer through a PXIE bus, and the signal is stored for data processing. Received signals under narrow-band excitation signals with different frequencies are obtained by calculating a transfer function of an entire measurement system, Hilbert transformation is performed on the received signals, a signal envelope is extracted, propagation acoustic time of the S0-mode Lamb wave is then determined by using a peak extraction algorithm, a propagation acoustic time ratio of two excitation frequency signals is solved, an average stress between the transmitting and receiving probes may be then determined by substituting into a pre-calibrated acousto-elastic equation, and a stress state of the measured object is finally characterized.

The dispersion curve of the Lamb wave is established according to geometric dimensions and material parameters of the measured object, and a free plate Lamb wave dispersion equation is a Rayleigh-Lamb wave dispersion equation, satisfying:

tan⁡(q⁢h)tan⁡(p⁢h)=-4⁢k2⁢p⁢q(q2-k2)2(1)tan⁡(q⁢h)tan⁡(p⁢h)=-(q2-k2)24⁢k2⁢p⁢q(2)where p and q are respectively expressed as:

p=ω2cL2-k2(3)q=ω2cT2-k2(4)where cLand cTrespectively represent velocities of a longitudinal wave and a transverse wave, h represents half of plate thickness, ω is an angular frequency of an ultrasonic wave, and k is a wave number.

Assuming that the object to be measured is an aluminum plate 6061 with a thickness of 1 mm, a dispersion curve of a structure to be measured may be obtained by solving equations (1) and (2). According to the dispersion curve, it can be determined that the cut-off frequency of the first-order Lamb wave mode is 1.6 MHz, and therefore a selected excitation signal is within a frequency range of 500 kHz-1000 kHz.

A dispersion curve of the measured object under pre-stress conditions is solved through a semi-analytical finite element method to obtain wave numbers at different frequencies, the dispersion curve of the Lamb wave is finally completely drawn, and a relationship between the group velocity and frequency of the Lamb wave and the wave numbers satisfies:

cg=d⁢ωd⁢k(5)

A uniaxial pre-stress of 100 MPa is applied to the measured object along a propagation direction of the Lamb wave to obtain a group velocity change of the S0-mode Lamb wave at different frequencies. The influence of the same stress on the group velocity of the Lamb wave at different frequencies is different, which indicates that the influence of stress on the Lamb wave also has the dispersion characteristics, and therefore fused data at multiple excitation frequencies may be used for stress measurement.

The pre-stress of the measured object is set to linearly increase to 100 MPa at a step of 20 MPa from 0 MPa, a relationship between the stress and group velocity change of the S0-mode Lamb wave at 500 kHz and 1000 kHz is respectively obtained so as to establish a linear relationship between the uniaxial pre-stress and the group velocity of the S0-mode Lamb wave along the propagation direction during 500 kHz and 1000 kHz excitations according to the group velocity of the S0-mode Lamb wave without stress at two frequencies:
cg(500 kHz)=4.463×10−7σ+5432  (6)
cg(1000 kHz)=3.581×10−7σ+4659  (7)where σ represents stress.

According to formulas (6) and (7), a relationship between the propagation acoustic time ratio of the S0-mode Lamb wave and stress under 500 kHz and 1000 kHz excitations at a fixed propagation distance may be obtained as:

L/cg⁡(5⁢0⁢0⁢k⁢H⁢z)L/cg⁡(1⁢0⁢0⁢0⁢k⁢H⁢z)=cg⁡(1⁢0⁢0⁢0⁢k⁢H⁢z)cg⁡(5⁢0⁢0⁢k⁢H⁢z)=3.581×1⁢0-7⁢σ+4⁢6⁢5⁢94.463×1⁢0-7⁢σ+5⁢4⁢3⁢2≈-1.3411×1⁢0-1⁢1⁢σ+0.8⁢577(8)

The propagation acoustic time ratio of an S0 mode under 500 kHz and 1000 kHz excitations at a fixed propagation distance can be determined from formula (8) to have an approximate linear relationship with stress, so that average stress measurement on a propagation path of the Lamb wave is possible without baseline data by using data fusion at two excitation frequencies.

After calibration of acousto-elastic coefficients of a single-mode multi-frequency Lamb wave is completed, a stress state of a measured structure is actually measured, and an arbitrary waveform generator is used to generate a low-voltage chirp signal. After the signal is amplified by a power amplifier, a Lamb wave is generated for two excitation piezoelectric wafers, and an S0-mode Lamb wave propagates inside the measured object and is received by a piezoelectric wafer sensor. A received signal is an mV-order weak signal, which is easily interfered by random electronic noise, so that it is necessary to perform non-distortion amplification on an original signal and then perform bandwidth filtering on the amplified signal. The original signal obtained by the piezoelectric wafer sensor is input into a high-bandwidth input amplification apparatus, the signal is amplified to an input range of a digital-to-analog conversion chip through coarse gain adjustment and fine gain adjustment, a lower cut-off frequency and an upper cut-off frequency of a filter are then set according to the bandwidth of an excitation signal, the amplified and filtered signal is input into a high-speed data acquisition system, and is encoded through an FPGA chip, and a sampling signal is transmitted to the upper computer through the PXIE bus and stored for subsequent data processing.

A general transfer function of the measurement system is obtained according to the excitation signal and the received signal as:

H⁡(ω)=Rc(w)Sc(w)(9)where Rc(w) represents a Fourier transformation result of the received signal, and Sc(w) represents a Fourier transformation result of the excitation signal.

Considering a 5-period sinusoidal excitation signal modulated by a Hanning window as excitation signal, the received signal of the sensor at this moment may be obtained according to the general transfer function of the measurement system as:
Rd(w)=H(ω)Sd(w)  (10)where Rd(w) represents a Fourier transformation result of the received signal of the sensor, and Sd(w) represents a Fourier transformation result of the excitation signal of the sensor.

A time-domain received waveform Rd(t) corresponding to a modulated excitation signal is obtained by performing inverse Fourier transformation on Rd(w), time-domain waveforms under 500 kHz and 1000 kHz excitations are respectively calculated, Hilbert transformation is then performed on the obtained signal, and the transformation process is defined as:

fˆ(t)=H[f⁡(t)]=1π⁢∫-∞∞f⁡(t)t-τ⁢d⁢τ(11)where f(t) represents an original signal, {circumflex over (f)}(t) represents a signal obtained after Hilbert transformation, and τ represents an integration variable.

After the Hilbert transformation, an amplitude envelope of the received signal is extracted, arrival time of the S0-mode directly arriving at a wave packet is determined by using the peak extraction algorithm, propagation time of the Lamb wave at a fixed distance is determined according to the width of the excitation signal, a propagation time ratio at two excitation frequencies is calculated, and the magnitude and direction of the uniaxial stress inside the measured object at this moment are determined by substituting into the calibrated acousto-elastic equation.

The disclosure also provides a system for online stress monitoring without baseline data based on single-mode multi-frequency signal fusion.

A dispersion curve establishment module, configured to firstly establish a dispersion curve of a Lamb wave according to a structure of a measured object, determine a cut-off frequency of a first-order Lamb wave mode to ensure that an excitation frequency of a Lamb signal is below a first-order cut-off frequency, and obtain a pure S0-mode Lamb wave inside the measured object by means of symmetric excitation.

An acousto-elastic equation establishment module, configured to obtain a linear relationship between the S0-mode Lamb wave at different excitation frequencies and stress through theoretical analysis, and further determine a linear relationship between a propagation acoustic time ratio of the S0-mode Lamb wave at two excitation frequencies and stress at a fixed propagation distance.

A measurement system integration module, configured to load a chirp signal inside a signal generator according to a selected excitation frequency range, drive a transmitting probe after subjecting to a power amplifier, perform first-stage weak signal amplification on a signal of a receiving probe, receive the signal by a high-speed acquisition board card, transmit the signal to an upper computer through a PXIE bus, and store the signal for data processing.

A stress calculation module, configured to obtain received signals under narrow-band excitation signals with different frequencies by calculating a transfer function of an entire measurement system, perform Hilbert transformation on the received signals, extract a signal envelope, then determine propagation acoustic time of the S0-mode Lamb wave by using a peak extraction algorithm, solve a propagation acoustic time ratio of two excitation frequency signals, then determine an average stress between the transmitting and receiving probes by substituting into a pre-calibrated acousto-elastic equation, and finally characterize a stress state of the measured object.

The disclosure also provides an electronic device, including a memory and a processor. The memory stores a computer program. The processor, when executing the computer program, implements the steps of the method for online stress monitoring without baseline data based on single-mode multi-frequency signal fusion.

The disclosure also provides a computer-readable storage medium storing computer instruction which, when executed by a processor, implements the steps of the method for online stress monitoring without baseline data based on single-mode multi-frequency signal fusion.

Under normal temperature conditions, a measured object is an aluminum plate 6061 with a thickness of 1 mm, which is an isotropic material. An arbitrary waveform generator is used to generate a chirp signal with a frequency range from 500 kHz to 1000 kHz. A low-frequency signal generated by a signal generator is amplified in one stage by an Aigtek power amplifier. A high-voltage signal is used to excite a piezoelectric wafer exciter while generating a trigger signal. A high-speed data acquisition board card is used to acquire an ultrasonic signal obtained by a piezoelectric wafer sensor. Before acquiring the received signal, the signal is subjected to weak amplification and band-pass filtering, the signal is amplified to an input voltage range of the data acquisition card, the received signal is continuously acquired for 20 times, and the acquired signal is subjected to smooth filtering to filter out a part of electronic noise, so as to improve a signal-to-noise ratio of the received signal. Then, a transfer function of a system is calculated, and received time domain waveforms under excitation signals with different frequencies are calculated according to a frequency domain transformation result of an expected signal. Propagation time of S0-mode Lamb waves with different frequencies is determined by using Hilbert transformation and a peak extraction algorithm, a propagation time ratio is substituted into a pre-calibrated acousto-elastic equation, and the obtained result is a uniaxial stress value of the measured object.

The disclosure provides a method for online monitoring of baseline-free stress based on single-mode multi-frequency Lamb wave signal fusion. The interaction of multi-frequency Lamb waves is innovatively considered, and an approximate linear relationship between a propagation time ratio of two mode waves and stress at a fixed propagation distance is obtained according to a linear relationship between group velocity of S0 modes with different frequencies and stress, so as to realize online monitoring of an absolute stress state of a measured structure without any reference baseline data.

The method, system, device, and medium for online stress monitoring without baseline data based on single-mode multi-frequency signal fusion provided by the disclosure is described in detail as above. The principles and examples of the disclosure are described by specific examples herein. The description of the above examples is only used to help understand the method and core idea of the disclosure. Meanwhile, for a person of ordinary skill in the art, according to the idea of the disclosure, there will be changes in the specific implementation mode and application scope of the disclosure. Based on the above, the content of the description shall not be construed as limiting the disclosure.