MEMS deflection angle detection method, optical communication equipment and storage medium

Abstract

The invention relates to the technical field of optical communication, in particular to an MEMS deflection angle detection method, optical communication equipment and a storage medium. The micro-mirror deflection angle detection method is applied to a micro-electro-mechanical system, and the micro-electro-mechanical system comprises a micro-mirror array and a driving module used for driving the micro-mirror array to deflect. The method comprises the following steps: generating a high-frequency excitation signal, and coupling the high-frequency excitation signal to a driving module; when the micromirror array is driven by the driving module to deflect, a modulation signal is obtained from the driving module, and the modulation signal is generated after a high-frequency excitation signal is modulated by the driving module; and acquiring the deflection angle of the micromirror array based on at least one of the modulation phase and the modulation amplitude of the modulation signal. According to the invention, the detection cost can be effectively reduced, and the detection accuracy and reliability are improved.

Description

Technical Field

[0001] The present invention relates to the field of optical communication technology, and in particular to a MEMS deflection angle detection method, optical communication equipment and storage medium. Background Art

[0002] Currently, detecting the deflection angle of MEMS (Micro-Electro-Mechanical Systems) arrays in optical routers requires the installation of additional angle sensors (such as optical encoders and capacitive sensors). This results in a complex system structure, low integration, and high cost. Furthermore, external sensors are susceptible to external factors such as temperature, vibration, and electromagnetic noise, reducing detection accuracy and reliability. Summary of the Invention

[0003] The technical problem to be solved by the embodiments of the present invention is to provide a MEMS deflection angle detection method, optical communication equipment and storage medium to solve the problems in the prior art of MEMS measurement system, such as complex structure, low integration, high cost and susceptibility to interference.

[0004] The present invention discloses a method for detecting a micromirror deflection angle, which is applied to a micro-electromechanical system (MEMS). The MEMS comprises a micromirror array and a driving module for driving the micromirror array to deflect.

[0005] The micromirror deflection angle detection method comprises:

[0006] generating a high-frequency excitation signal, and coupling the high-frequency excitation signal to the driving module;

[0007] When the micromirror array is driven by the driving module to deflect, a modulation signal is obtained from the driving module, where the modulation signal is generated after the high-frequency excitation signal is modulated by the driving module;

[0008] A deflection angle of the micromirror array is obtained based on at least one of a modulation phase and a modulation amplitude of the modulation signal.

[0009] Optionally, the step of acquiring the deflection angle of the micromirror array based on at least one of a modulation phase, a modulation amplitude, and a modulation frequency of the modulation signal includes:

[0010] The local reference signal is adjusted according to the phase difference between the high-frequency excitation signal and the local reference signal through a digital phase-locked loop, thereby tracking and locking the modulation signal.

[0011] Optionally, after the step of tracking and locking the modulation signal, the method further comprises:

[0012] Acquiring the modulation phase through the digital phase-locked loop, measuring and acquiring the modulation amplitude, and acquiring the equivalent resistance caused by the deflection of the micromirror array based on the modulation phase and / or the modulation amplitude;

[0013] The deflection angle is obtained based on the equivalent resistance.

[0014] Optionally, the step of obtaining the equivalent resistance caused by the deflection of the micromirror array based on the modulation phase and / or the modulation amplitude includes:

[0015] Acquiring mechanical inertia characteristics and parasitic parameter characteristics of the micromirror array through an adaptive filtering algorithm based on the modulation phase and the modulation amplitude;

[0016] The mechanical inertia characteristic includes angular velocity, and the parasitic parameter characteristic includes at least one of the equivalent resistance, equivalent capacitance, and equivalent inductance.

[0017] Optionally, the adaptive filtering algorithm includes Kalman filtering and / or wavelet transform.

[0018] Optionally, after the step of acquiring the mechanical inertia characteristics and parasitic parameter characteristics of the micromirror array through an adaptive filtering algorithm based on the modulation phase and the modulation amplitude, the method further comprises:

[0019] The modulation amplitude, the modulation phase and the angular velocity are substituted into a nonlinear mapping function to obtain the deflection angle, wherein the nonlinear function is determined by calibration data fitting or neural network training.

[0020] Optionally, the micromirror deflection angle detection method further includes:

[0021] A detection signal-to-noise ratio is obtained based on the modulation amplitude, and an angle resolution is obtained based on the number of bits of the modulation signal.

[0022] Optionally, the high-frequency excitation signal is a dither signal, and its waveform is a sine wave or a square wave.

[0023] The present invention also discloses a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the processor executes the steps of the method described above.

[0024] The present invention also discloses an optical communication device, comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the above method.

[0025] Compared with the existing technology, the beneficial effect of the micromirror deflection angle detection method provided by the embodiment of the present invention is: by coupling the high-frequency excitation signal to the driving module of the MEMS micromirror, when the micromirror deflects, the driving module modulates the high-frequency excitation signal to generate a modulation signal, thereby converting the mechanical deflection angle into a measurable electrical signal change. The corresponding deflection angle can be obtained by analyzing the modulation signal. There is no need to set up a sensor, the system structure is compact, and it will not be affected by the external environment. The detection results are more accurate and reliable. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments, in which:

[0027] Figure 1 1 is a flow chart of an embodiment of a method for detecting a micromirror deflection angle provided by the present invention;

[0028] Figure 2 It is a structural diagram of an embodiment of the micro-electromechanical system provided by the present invention.

[0029] The reference numerals in the figures are:

[0030] 10. Micro-electromechanical system; 11. Micromirror array; 12. Driving module. DETAILED DESCRIPTION

[0031] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in this application can be combined with each other. Now, in conjunction with the accompanying drawings, the preferred embodiments of the present invention will be described in detail.

[0032] Please refer to Figure 1 and Figure 2 , Figure 1 FIG. 1 is a flow chart of an embodiment of a method for detecting a micromirror deflection angle provided by the present invention. Figure 2 FIG. 1 is a schematic structural diagram of an embodiment of a micro-electromechanical system provided by the present invention. Figure 2 As shown, the MEMS 10 includes a micromirror array 11 and a driving module 12 for driving the deflection of the micromirror array 11. Specifically, the driving module 12 can output a driving electrical signal, so that the micromirrors in the micromirror array 11 can be deflected by a corresponding angle under the driving electrical signal. To achieve accurate optical signal transmission, it is necessary to detect whether the micromirror deflection angle is correct.

[0033] The micromirror deflection angle detection method provided by the present invention specifically includes the following steps:

[0034] S101: Generate a high-frequency excitation signal, and couple the high-frequency excitation signal to a driving module.

[0035] In a specific implementation scenario, a high-frequency excitation signal, such as a dither signal, is generated. Its waveform can be a sine wave or a square wave. High-frequency excitation signals are high-frequency, small-amplitude excitation signals. The mechanical resonance frequency of MEMS is typically in the kHz range (e.g., 1–10 kHz). The frequency of the high-frequency excitation signal is much higher than this, at least one order of magnitude higher than the mechanical resonance frequency (e.g., 1 MHz), to avoid excitation of mechanical resonance. Furthermore, high-frequency excitation signals (e.g., above 1 MHz) are not affected by low-frequency environmental noise (e.g., temperature drift and mechanical vibration), effectively improving the signal-to-noise ratio (SNR).

[0036] In this implementation scenario, a high-frequency excitation signal can be generated by a high-speed DAC (Digital-to-Analog Converter). In other implementation scenarios, a high-frequency excitation signal can also be generated by direct digital synthesis or other technologies.

[0037] S102: When the micromirror array is deflected under the driving of the driving module, a modulation signal is obtained from the driving module. The modulation signal is generated after the high-frequency excitation signal is modulated by the driving module.

[0038] In a specific implementation scenario, when the micromirror is deflected, its mechanical structure and electrical parameters (such as capacitance, inductance, and resistance) will change, thereby affecting the propagation of the high-frequency signal and realizing the modulation of the high-frequency signal. Specifically, the high-frequency excitation signal is coupled to the driving module (such as the electrostatic comb drive electrode). When the micromirror in the MEMS is deflected, the angle change of its mechanical structure (such as the movable comb teeth) will change the mechanical inertia and parasitic parameters (RLC) of the microelectromechanical system, causing the high-frequency excitation signal to be modulated and generating a corresponding modulation signal. By analyzing the modulation signal, the mechanical inertia and parasitic parameters of the microelectromechanical system can be obtained, thereby obtaining the corresponding deflection angle and realizing the detection of the deflection angle of the micromirror.

[0039] Specifically, the deflection angle of the micromirror affects the electrode spacing, resulting in a change in capacitance. The change in capacitance will change the coupling efficiency of the signal, and thus change the amplitude of the excitation signal. Mechanical inertia will cause the mass-spring system of the movable part to produce inertial delay, introduce phase delay, and change the phase of the excitation signal. Different deflection angles result in different amplitude changes and phase delays. Therefore, the deflection angle of the micromirror can be obtained by the difference between the amplitude and phase of the excitation signal and the amplitude and phase of the modulation signal.

[0040] In one implementation scenario, after acquiring the modulated signal in real time through a high-speed analog-to-digital converter (ADC), anti-aliasing filtering is used to remove high-frequency noise and aliasing components introduced by the ADC sampling. Digital down-conversion is then used to bring the high-frequency modulated signal to baseband, reducing the complexity of subsequent processing. The dither signal can be coupled to the driver module via a capacitor or transformer to avoid affecting the main drive signal (such as the optical path control voltage).

[0041] S103: Obtain a deflection angle of the micromirror array based on at least one of a modulation phase and a modulation amplitude of the modulation signal.

[0042] In a specific implementation scenario, a mapping relationship between phase change and / or amplitude change and deflection angle can be established in advance, so that the deflection angle of the micromirror in the micromirror array can be obtained based on at least one of the modulation phase and modulation amplitude of the modulation signal.

[0043] Specifically, the change in the capacitance C(θ) in the parasitic parameters will cause the impedance amplitude |Z(θ)| to change, so the modulation amplitude of the modulation signal is:

[0044]

[0045] Establish the relationship between θ and A through experiments response The static relationship, θ=f(A response ). In this way, according to the modulation amplitude A response The deflection angle θ can be obtained. The function f(x) can be implemented by neural network training or calibration data fitting.

[0046] Phase delay φ caused by mechanical inertia response and angular velocity The deflection angle θ can be deduced after integration.

[0047] That is Then θ(t)=∫g(φ response )dt. The function g(x) can be implemented through neural network training or calibration data fitting.

[0048] Digital PLL can accurately track the phase changes of the modulated signal. Its essence is a closed-loop control system that dynamically adjusts the frequency and phase of the local reference signal to synchronize it with the input signal.

[0049] Assume that the high-frequency excitation signal generated by the high-speed DAC is:

[0050] V dither (t) = A·sin(2πf dither t)

[0051] Where A is the original amplitude of the high-frequency excitation signal, fdither is the original frequency of the high-frequency excitation signal, which is used to stimulate the dynamic response of the parasitic parameters of MEMS.

[0052] The corresponding collected modulation signal is:

[0053] I response (t) = A response ·sin(2πf dither t-φ response )

[0054] The relationship between the modulation amplitude and modulation phase and the change of equivalent resistance is:

[0055]

[0056] φ response =arg(Z(θ))

[0057] Get φ response The phase difference Δφ from the reference signal:

[0058] Δφ=φ response -φ ref

[0059] The loop filter performs a proportional-integral operation on the phase difference:

[0060] f correction =K p ·Δφ+K i ∫Δφdt

[0061] K p is the proportional gain. The larger the value, the faster the response speed. i K is the integral gain. The larger the value, the smaller the steady-state error. p Δφ is a proportional term used to quickly respond to phase mutations (such as sudden rotation of the micromirror), K i ∫Δφdt is an integral term used to eliminate steady-state errors (such as long-term frequency drift).

[0062] According to f correction Adjust the output frequency so that Δφ approaches 0. After locking, the output phase of the voltage-controlled oscillator is φ response , thus achieving the acquisition of the modulation phase through the digital phase-locked loop.

[0063] Based on the relationship between the modulation phase, modulation amplitude and equivalent resistance, the equivalent resistance Z(θ) can be obtained. The relationship between Z(θ) and the deflection angle is:

[0064]

[0065] The real part R(θ) is the energy loss (heat / damping), and the imaginary part is the reactance (competition between inductive and capacitive reactance).

[0066] Therefore, the deflection angle θ can be obtained based on the equivalent resistance Z(θ).

[0067] In one implementation scenario, the mechanical inertia characteristics and parasitic parameter characteristics of the micromirror array are obtained through an adaptive filtering algorithm based on the modulation phase and the modulation amplitude. Specifically, the predicted state is obtained based on the deflection angle and the mechanical model at the previous moment, and the observed state can be obtained based on the currently obtained modulation phase and modulation amplitude. Based on the difference between the observed state and the predicted state, the parameters or weights in the adaptive filtering algorithm are dynamically adjusted to obtain the optimal state. Based on the optimal state, the mechanical inertia characteristics and parasitic parameter characteristics are separated, the mechanical inertia characteristics include angular velocity, and the parasitic parameter characteristics include at least one of the equivalent resistance, equivalent capacitance, and equivalent inductance.

[0068] The adaptive filtering algorithm includes Kalman filtering and / or wavelet transform.

[0069] The state equation of the Kalman filter is:

[0070] x k =Fx k-1 +w k

[0071] x k is the state vector, which contains all the key variables that need to be tracked, usually including: θ: the current deflection angle of the micromirror, Angular velocity, parasitic parameters: at least one of ΔR, ΔC, and ΔT, that is, at least one of the changes in equivalent impedance, equivalent capacitance, and equivalent inductance. In one example:

[0072] F is the state transfer matrix, which describes how the state variables evolve over time and is constructed based on Newtonian mechanics and circuit models. The Newton-Euler equation describes the torque balance when the micromirror is deflected:

[0073]

[0074] J is the moment of inertia, B is the damping coefficient, K is the elastic coefficient, τ ext is the external torque. is the moment of inertia (related to angular acceleration), is the damping torque (angular velocity related), and Kθ is the elastic restoring torque (angle related).

[0075] The mechanical part of F can be discretized by the Newton-Euler equation. Assuming that the parasitic parameters vary slowly, it can be obtained:

[0076]

[0077] w k Process noise is caused by the uncertainty of modeling prediction (such as mechanical friction mutation and driving voltage fluctuation), which is usually assumed to be Gaussian white noise.

[0078] The observation equation of Kalman filter is:

[0079] Z k =Hx k +v k

[0080] Z k is the observation vector, including the response amplitude, response phase, etc. In one example: Z k =[A respobse ,φ response ] T

[0081] H is the measurement matrix, which defines how the state variables are mapped to the observation signals. For example, define A response Related to capacitance change (ΔC), φ response and angular velocity Related (inertial delay).

[0082] v k Observation noise represents the noise caused by measurement errors (such as circuit noise and ADC quantization error), which is usually assumed to be Gaussian white noise.

[0083] In one embodiment, the prior state estimate x is first calculated: k - =Fx k-1 , and calculate the prior error covariance: P k - =FP k-1 F T +Q. Then calculate the Kalman gain: K k =P k - H T (HP k - H T +R) -1 , then integrate the observed data x k =x k - +K k (Z k -Hx k - ), and finally update the error covariance: P k =(IK k H)P k* Q is the process noise covariance, and R is the observation noise covariance.

[0084] By using Kalman filtering, even if the micromirror deflects at high speed (angular velocity Even when the sensor changes rapidly, it can still predict inertial delays through the state equation, avoiding detection lags. It also synchronously estimates ΔR and ΔC, automatically distinguishing between true angle changes and temperature drift / aging effects.

[0085] For example, when the micromirror deflects from 0° to 5°, there is a temperature-induced capacitance drift. The state equation predicts that the deflection angle reaches 5.1° (because the model overestimates the stiffness K), and the A is obtained based on the observation equation. response and φ response The calculated angle is 4.8° (lower due to capacitance drift), and the Kalman filter yields 4.95° (balancing predictions with observations and correcting the ΔC estimate).

[0086] In other implementation scenarios, the modulation amplitude, the modulation phase and the angular velocity are substituted into a nonlinear mapping function to obtain the deflection angle, that is, The nonlinear function f(x) is determined by calibration data fitting or neural network training.

[0087] In one embodiment, the high-frequency excitation signal can be a dither signal, and its waveform can be a sine wave or a square wave. The dither signal is a high-frequency, small-amplitude excitation signal. Traditional static (DC) or low-frequency detection is easily interfered by environmental noise, while the high-frequency dither signal can extract effective information through filtering. MEMS deflection may be a high-speed transient process (such as optical path switching). The rapid modulation and demodulation of the dither signal can achieve real-time detection. The dither signal is injected from the output electrode of the driving module, modulated by the MEMS mechanical response, and then returned through the same electrode or adjacent electrodes to form a closed-loop detection.

[0088] In other implementation scenarios, the detection signal-to-noise ratio is obtained based on the modulation amplitude, and the quantization error limit is obtained based on the number of bits of the modulation signal. Specifically, the signal-to-noise ratio is obtained according to the following formula:

[0089]

[0090] A response is the modulation amplitude, σ noise 2 is the total noise power of the system, including thermal noise, mechanical noise and circuit noise, etc., σ quant 2The quantization noise power of the ADC sampling circuit is used to acquire the modulated signal. SNR determines the minimum detectable signal. Optimization measures can be taken according to the calculated SNR, such as increasing the A response , the amplitude of the high-frequency excitation signal can be increased or the MEMS sensitivity can be optimized (such as reducing the electrode spacing).

[0091] The angular resolution is obtained according to the following formula:

[0092]

[0093] Δθ max is the maximum measurable angle range, i.e. the maximum deflection angle of the micromirror, which is determined by the mechanical structure of the MEMS. N is the number of bits of the ADC, i.e. the number of bits of the modulation signal, which determines the number of quantization levels. For example, a 16-bit ADC can divide a 20° range into 65,536 discrete levels. res =20° / 4096≈0.0049°. θ of 16-bit ADC res ≈0.0003°.

[0094] From the above description, it can be seen that in this embodiment, by coupling the high-frequency excitation signal to the driving module of the MEMS micromirror, when the micromirror deflects, the driving module modulates the high-frequency excitation signal to generate a modulation signal, thereby converting the mechanical deflection angle into a measurable electrical signal change. The corresponding deflection angle can be obtained by analyzing the modulation signal. There is no need to set up a sensor, the system structure is compact, and it will not be affected by the external environment. The detection results are more accurate and reliable.

[0095] The present invention further provides an optical communication device comprising a processor and a memory. The processor is coupled to the memory. The memory stores a computer program, and the processor, when operating, executes the computer program to implement the above method. The detailed steps are described above and are not repeated here.

[0096] The present invention also provides a computer-readable storage medium. The computer-readable storage medium stores at least one computer program, which is configured to be executed by a processor to implement the above method. The detailed steps are described above and are not repeated here. In one embodiment, the computer-readable storage medium can be a memory chip, a hard disk, a removable hard disk, a USB flash drive, an optical disk, or other readable and writable storage medium in a terminal, or a server, etc.

[0097] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0098] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0099] It should be understood that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Those skilled in the art may modify the technical solutions described in the above embodiments, or make equivalent replacements for some of the technical features therein; and all these modifications and replacements should fall within the scope of protection of the claims attached to the present invention.

Claims

1. A method for detecting a micromirror deflection angle, characterized in that: Applied to a micro-electromechanical system, the micro-electromechanical system comprising a micro-mirror array and a driving module for driving the micro-mirror array to deflect; The micromirror deflection angle detection method comprises: generating a high-frequency excitation signal, and coupling the high-frequency excitation signal to the driving module; When the micromirror array is driven by the driving module to deflect, a modulation signal is obtained from the driving module, where the modulation signal is generated after the high-frequency excitation signal is modulated by the driving module; A deflection angle of the micromirror array is obtained based on at least one of a modulation phase and a modulation amplitude of the modulation signal.

2. The micromirror deflection angle detection method according to claim 1, wherein: The step of obtaining the deflection angle of the micromirror array based on at least one of the modulation phase, modulation amplitude and modulation frequency of the modulation signal comprises: The local reference signal is adjusted according to the phase difference between the high-frequency excitation signal and the local reference signal through a digital phase-locked loop, thereby tracking and locking the modulation signal.

3. The micromirror deflection angle detection method according to claim 2, wherein: After the step of tracking and locking the modulation signal, the method further comprises: Acquiring the modulation phase through the digital phase-locked loop, measuring and acquiring the modulation amplitude, and acquiring the equivalent resistance caused by the deflection of the micromirror array based on the modulation phase and / or the modulation amplitude; The deflection angle is obtained based on the equivalent resistance.

4. The micromirror deflection angle detection method according to claim 3, wherein: The step of obtaining the equivalent resistance caused by the deflection of the micromirror array based on the modulation phase and / or the modulation amplitude includes: Acquiring mechanical inertia characteristics and parasitic parameter characteristics of the micromirror array through an adaptive filtering algorithm based on the modulation phase and the modulation amplitude; The mechanical inertia characteristic includes angular velocity, and the parasitic parameter characteristic includes at least one of the equivalent resistance, equivalent capacitance, and equivalent inductance.

5. The micromirror deflection angle detection method according to claim 4, wherein: The adaptive filtering algorithm includes Kalman filtering and / or wavelet transform.

6. The micromirror deflection angle detection method according to claim 4, wherein: After the step of obtaining the mechanical inertia characteristics and parasitic parameter characteristics of the micromirror array through an adaptive filtering algorithm based on the modulation phase and the modulation amplitude, the method further includes: The modulation amplitude, the modulation phase and the angular velocity are substituted into a nonlinear mapping function to obtain the deflection angle, wherein the nonlinear function is determined by calibration data fitting or neural network training.

7. The micromirror deflection angle detection method according to claim 1, wherein: The micromirror deflection angle detection method further includes: A detection signal-to-noise ratio is obtained based on the modulation amplitude, and an angle resolution is obtained based on the number of bits of the modulation signal.

8. The micromirror deflection angle detection method according to claim 1, wherein: The high-frequency excitation signal is a dither signal, and its waveform is a sine wave or a square wave.

9. A computer-readable storage medium, characterized in that A computer program is stored, and when the computer program is executed by a processor, the processor is caused to perform the steps of the method according to any one of claims 1 to 8.

10. An optical communication device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the method according to any one of claims 1 to 8.

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