CN112415267B - LCR series-parallel network identification device - Google Patents

Abstract

The invention provides a device for LCR series-parallel network identification, including: a main control MCU, an excitation source generator, a subtractor, an adder, an anti-aliasing filter, and an analog-to-digital converter; wherein, the main control MCU is STM32H743 produced by ST Company; the excitation source generator is a DDS direct digital frequency synthesizer, the model is AD9959, and the excitation source is a 1K-100KHz sinusoidal signal; the function of the subtractor is to convert the band generated by the excitation source The DC-biased sinusoidal signal is level-shifted to make it a pure AC signal; the function of the adder is to raise the level-shifted two-way signals after complex impedance to above 0 level respectively, so that the amplitude of The value is within the input range of the analog-to-digital converter; the antialiasing filter acts to prevent aliasing of high frequency noise.

Description

A device for LCR series-parallel network identification

technical field

The invention relates to complex impedance measurement in the measurement field, and NN classifier technology in the field of machine learning, in particular to a device for LCR series-parallel network identification.

Background technique

Complex impedance measurement is an important item in the field of measurement. The measurement of LCR can be used as the pre-stage of an electronic system, as a transition from real-world signals to electronic systems. LCR network measurement is widely used, and it can be used as the pre-stage of water level measurement, light intensity measurement and other systems. Nowadays, there are many instruments and meters based on the independent parameter measurement of L, C, and R, but there are very few instruments and devices that can accurately identify LCR series and parallel. The invention can not only accurately identify and measure the value of the independent LCR parameter, but also identify the topology structure of any two or three LCR series-parallel networks according to the known independent LCR parameter value. The invention has simple structure and powerful function, and realizes the identification of LCR series-parallel network.

SUMMARY OF THE INVENTION

The present invention provides a device for LCR series-parallel network identification in view of the deficiencies of the prior art.

The invention includes a main control MCU, the main control MCU is STM32H743 produced by ST company, an excitation source generator, a subtractor, two adders, two anti-aliasing filters, and an analog-to-digital converter.

The excitation source generator is a DDS direct digital frequency synthesizer, the model is AD9959, and the excitation source is a 1K-100KHz sinusoidal signal; the function of the subtractor is to convert the sinusoidal signal with DC bias generated by the excitation source. Level-shift it to make it a pure AC signal. The function of the adder is to raise the level-shifted two-channel signals to levels above 0 respectively after passing through the complex impedance, so that the amplitude is within the input range of the analog-to-digital converter; the anti-aliasing filter The role of the filter is to prevent aliasing of high frequency noise.

After the pure AC excitation signal passes through the complex impedance to be measured, a phase shift will occur according to its inductance or capacitance. According to the phase difference between the current and the voltage on the complex impedance to be measured, the real part and the imaginary part of the complex impedance to be measured can be calculated. Part value, you can analyze that the complex impedance to be measured belongs to L, C or R. and its exact value can be calculated.

After the values of L, C, and R are pre-stored, any two or three series-parallel networks of L, C, and R are connected to the system as the complex impedance to be measured. Calculate the equivalent real and imaginary parts of the 14 possible network structures of the series-parallel network, and compare the calculated 14 values with the real and imaginary parts of the network under test. The idea is to find the network structure with the smallest mean square error between the real part and the imaginary part of the measured network among the 14 possible networks, and this structure is the structure of the LCR series-parallel network to be tested.

Description of drawings

FIG. 1 is a system block diagram of the present invention.

FIG. 2 is a circuit diagram of a subtractor of the present invention.

FIG. 3 is a circuit diagram of the adder of the present invention.

FIG. 4 is a circuit diagram of an anti-aliasing filter of the present invention.

FIG. 5 is a topology diagram of the 14 LCR network structures that can be identified by the present invention.

FIG. 6 is a code flow chart of the present invention.

FIG. 7 is a block diagram of the phase difference measured by the correlation method of the present invention.

Detailed ways

The invention will be further described in detail with reference to the following specific embodiments and accompanying drawings. Except for the content specifically mentioned below, the process, conditions, experimental methods, etc. for implementing the present invention are all common knowledge and common knowledge in the field, and the present invention is not particularly limited.

The invention includes a main control MCU, the main control MCU is STM32H743 produced by ST company, an excitation source generator, a subtractor, two adders, two anti-aliasing filters, and an analog-to-digital converter.

The excitation source generator is a DDS direct digital frequency synthesizer, the model is AD9959, and the excitation source is a 1K-100KHz sinusoidal signal; the function of the subtractor is to convert the sinusoidal signal with DC bias generated by the excitation source. Level-shift it to make it a pure AC signal. The function of the adder is to raise the level-shifted two-channel signals to levels above 0 respectively after passing through the complex impedance, so that the amplitude is within the input range of the analog-to-digital converter; the anti-aliasing filter The role of the filter is to prevent high frequency noise from aliasing.

After the pure AC excitation signal passes through the complex impedance to be measured, a phase shift will occur according to its inductance or capacitance. According to the phase difference between the current and the voltage on the complex impedance to be measured, the real part and the imaginary part of the complex impedance to be measured can be calculated. Part value, you can analyze that the complex impedance to be measured belongs to L, C or R. And can calculate its exact value.

After the values of L, C, and R are pre-stored, any two or three series-parallel networks of L, C, and R are connected to the system as the complex impedance to be measured. Calculate the equivalent real and imaginary parts of the 14 possible network structures of the series-parallel network, and compare the calculated 14 values with the real and imaginary parts of the network under test. The idea is to find the network structure with the smallest mean square error between the real part and the imaginary part of the measured network among the 14 possible networks, and this structure is the structure of the LCR series-parallel network to be tested.

Referring to Figure 1, the frequency of the excitation source is f, the complex impedance to be measured Z is expressed as a complex number of r+jb, the complex impedance to be measured Z and the standard resistance R form a voltage divider network, which can be obtained from simple circuit analysis knowledge

Available after transfer

Written in plural form

Solutions have to

and

According to the above derivation, the values of U1 and U2 are measured by ADC, and the phase difference between U1 and U2 is measured, and the values of the real part and the imaginary part of the complex impedance Z to be measured can be obtained.

The methods of measuring the phase difference are: correlation method, using DFT to find the phase

The block diagram of the correlation method to measure the phase difference is shown in Figure 7.

The two signals are shifted, multiplied and added correspondingly. When the number of shifted points is n*Ts=τ=(τ1-τ2), the peak value is obtained. The phase difference between the two signals can be obtained according to the number of shifts and the sampling rate.

The principle of DFT phase measurement is as follows:

Let the signal after windowing discrete sampling be expressed by the following formula:

s _1w (n)=A ₁ cos(2πf ₀ n/f _s +θ ₁ )w(n)

s _2w (n)=A ₂ cos(2πf ₀ n/f _s +θ ₂ )w(n) (1)

Do DFT on S1 to get the discrete spectrum:

Considering the frequency deviation δ existing in the spectrum leakage, the phase of S1 is φ1=θ1+δπ, and similarly φ2=θ2+δπ, so the phase difference between the signals S1 and S2 is θ1-θ2.

Referring to Figure 2, using the INA132 unity-gain instrument amplifier can ensure that the DC component of the excitation source can be accurately subtracted.

Referring to Figure 3, adding two followers to the front stage of the adder can isolate the front and rear two-stage circuits and ensure that the front and rear two-stage circuits work normally.

Referring to FIG. 4 , an active filter is used as an anti-aliasing filter to ensure a stable gain of the filter.

Referring to FIG. 5, there are 14 kinds of series-parallel topologies of any two or three LCRs in total.

Let R=a+jb, C=c+jd, L=e+jf, then the calculation results of the real and imaginary parts of the 14 topological equivalents are shown in Table 1.

Table 1 Values of real and imaginary parts of 14 series-parallel topologies

According to Table 1, the real and imaginary parts of the 14 network structures can be calculated.

Referring to FIG. 6 , the process of the present invention is as follows: firstly, the values of the independent L, C, and R parameters are calculated according to the amplitude and phase of the measured two-way signals, and the values of the independent parameters of R, L, and C are recorded. When identifying the network, first locate the excitation source at DC. If the measured network is an equivalent short circuit at this time, it can be determined that the network is R//L, C//L, (R+C)//L , one of the four categories of R//L//C, and then use the values of the real and imaginary parts listed in Table 1 to determine the exact network; if the measured network measured at this time is an equivalent open circuit, it can be determined that the network It is one of the four categories of R+C, C+L, R//L+C, R+L+C, and then use the values of the real and imaginary parts listed in Table 1 to determine the exact network; the other 6 cases show Equivalent resistance, use the values of the real and imaginary parts listed in Table 1 to determine the exact network.

The excitation source is located at DC first, and the 14 types of networks can be divided into three situations: equivalent open circuit, equivalent short circuit, and equivalent resistance. Then, the real part and imaginary part of up to 6 types of networks only need to be calculated, and the measured network The real and imaginary values of the real and imaginary parts calculate the mean square error, which greatly reduces the complexity of the code.

In the actual use process of the present invention, the corresponding network can be accurately identified within 1S, and the function is powerful.

The protection content of the present invention is not limited to the above embodiments. Variations and advantages that can occur to those skilled in the art without departing from the spirit and scope of the inventive concept are included in the present invention, and the appended claims are the scope of protection.

Claims (1)

1. a device for LCR series-parallel network identification, is characterized in that, comprises: main control MCU, excitation source generator, subtractor, adder, anti-aliasing filter, analog-to-digital converter; Wherein, The main control MCU is STM32H743 produced by ST Company; The excitation source generator is a DDS direct digital frequency synthesizer, the model is AD9959, and the excitation source is a sine signal of 1K-100KHz; The function of the subtractor is to level-shift the sinusoidal signal with DC bias generated by the excitation source to make it a pure AC signal; The function of the adder is to raise the level-shifted two-channel signals to levels above 0 respectively after passing through the complex impedance, so that the amplitude is within the input range of the analog-to-digital converter; The function of the anti-aliasing filter is to prevent high-frequency noise from aliasing; After the pure AC signal passes through the complex impedance to be measured, a phase shift will occur according to its inductance or capacitance. According to the phase difference between the current and the voltage on the complex impedance to be measured, the real part and the imaginary part of the complex impedance to be measured can be calculated. value, it can be analyzed that the complex impedance to be measured belongs to L, C or R, and its exact value can be calculated; After the values of L, C, and R are pre-stored, any two or three series-parallel networks of L, C, and R are connected to the system as the complex impedance to be measured. Calculate the equivalent real and imaginary parts of the 14 possible network structures of the series-parallel network, and compare the calculated 14 values with the real and imaginary parts of the network under test. The idea is to find the network structure with the smallest mean square error between the real part and the imaginary part of the measured network among the 14 possible networks, and this structure is the structure of the LCR series-parallel network to be tested.

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