Laser precision angle rotation system constructed based on multi-layer PCB

Abstract

The invention relates to the technical field of laser precision positioning equipment, and discloses a laser precision angle rotation system based on multi-layer PCB construction. Comprising a multi-layer PCB, a driving circuit, a sensing circuit and a control circuit are integrated, and an electromagnetic coil array is arranged on the multi-layer PCB; the rotor is matched with the electromagnetic coil array, and a laser reflecting mirror and a grating are fixedly connected to the rotor; the angle feedback system comprises a fixedly arranged photoelectric sensor array and is used for reading a signal generated when the grating rotates, the signal is sequentially amplified, filtered and shaped to form a digital square wave signal, and the digital square wave signal is subjected to quadruplicated frequency processing and position counting to obtain original angle data; after the original angle data is subjected to Kalman filtering processing, a high-precision angle value is output; and the control module comprises an upper computer, a main controller and a driving chip. The system is suitable for laser scanning, optical image stabilization, precision measurement and other scenes needing high-precision angle control.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of laser precision positioning equipment, and particularly relates to a laser precision angle rotation system constructed based on a multilayer PCB. BACKGROUND

[0002] In the fields of laser precision machining, optical measurement and precision instruments, a high-precision angle rotation system is a core component for realizing laser beam pointing control. A traditional angle rotation system usually adopts a separated design, and a driving circuit, a sensing circuit and a control circuit are independently laid out. A mechanical transmission structure (such as a gear or a worm gear) is used to connect a driving unit and a rotor, which leads to a large system size, angle errors caused by mechanical clearances, low integration and insufficient reliability. In addition, the angle feedback of the traditional system is usually achieved by simple counting, without effectively filtering out noise and jitter. Thermal deformation compensation relies on empirical formulas, and the compensation precision is limited, which is difficult to meet the requirements of precision angle control in microns or even nanometers.

[0003] In the prior art, an electromagnetic driving structure usually adopts a layout in which independent coils are separated from a PCB. The installation precision of the coils depends on mechanical positioning, which increases assembly complexity. Angle signal processing is only through simple filtering, without combining intelligent algorithms such as Kalman filtering to improve precision. Thermal management compensation lacks real-time prediction mechanisms and cannot dynamically adapt to changes in working conditions. Therefore, there is an urgent need for a system to solve at least one of the above problems. SUMMARY

[0004] The present application provides a laser precision angle rotation system constructed based on a multilayer PCB, which aims to solve the problems in the prior art that an electromagnetic driving structure usually adopts a layout in which independent coils are separated from a PCB. The installation precision of the coils depends on mechanical positioning, which increases assembly complexity. Angle signal processing is only through simple filtering, without combining intelligent algorithms such as Kalman filtering to improve precision. Thermal management compensation lacks real-time prediction mechanisms and cannot dynamically adapt to changes in working conditions.

[0005] In a first aspect, the embodiments of the present application provide a laser precision angle rotation system constructed based on a multilayer PCB, which comprises: A multilayer PCB, which integrates a driving circuit, a sensing circuit and a control circuit, and is provided with an electromagnetic coil array; A rotor, which is arranged in cooperation with the electromagnetic coil array, and is fixedly connected with a laser reflector and a grating; An angle feedback system, which comprises a fixedly arranged photoelectric sensor array, the photoelectric sensor array is used to read signals generated when the grating rotates, the signals are sequentially subjected to amplification, filtering and shaping to form a digital square wave signal, the digital square wave signal is subjected to four times frequency processing and position counting to obtain original angle data, and the original angle data is subjected to Kalman filtering processing to output a high-precision angle value. A control module, including a host computer, a main controller and a driving chip, the host computer is used for inputting instructions, the instructions include two modes of continuous trajectory and point-to-point and generating angle instruction sequence, the angle instruction sequence is transmitted to the main controller through the protocol, the main controller generates three-phase PWM signal and inputs to the driving chip according to the angle instruction sequence and the high-precision angle value, and the driving chip outputs three-phase current to drive the electromagnetic coil array.

[0006] In some embodiments, the electromagnetic coil array is integrated in the conductive layer of the multi-layer PCB board in a layered manner, each layer of electromagnetic coil is arranged in a ring shape at a preset angle interval, the electromagnetic coils of adjacent layers are staggered in the circumferential position, and the electromagnetic coil array is directly electrically connected with the driving circuit of the multi-layer PCB board, the electrical connection of each layer of coil is realized through the conductive via of the multi-layer PCB board, and an embedded electromagnetic driving structure without mechanical transmission components is formed.

[0007] In some embodiments, the analog signal output by the photoelectric sensor array is first input to a preamplifier for gain-adjustable amplification processing, the amplified signal is filtered through a band-pass filter with fixed center frequency and limited bandwidth to filter out high-frequency and low-frequency noise, and the filtered signal is compared with a preset threshold voltage through a voltage comparator to convert the analog signal into a digital square wave signal with fixed high and low levels.

[0008] In some embodiments, the rotor is a center-symmetric disc structure, the central axis of the rotor coincides with the central axis of the electromagnetic coil array, the laser reflector is fixedly installed on the upper surface of the rotor and rotates synchronously with the rotor, the grating is fixedly installed concentrically on the edge region of the rotor, and the scale line direction of the grating is consistent with the radial direction of the rotor, so that the grating can be read by the photoelectric sensor array when the grating rotates with the rotor.

[0009] In some embodiments, the digital square wave signal is divided into A-phase and B-phase signals with a phase difference of 90 degrees, the A-phase and B-phase signals are input to a programmable logic device for four times frequency processing, that is, a counting pulse is triggered at the rising edge and the falling edge of each signal period, the pulse signal after four times frequency processing is counted by a 32-bit counter, and the original rotation angle data of the rotor is calculated according to the preset grating line number and the pulse counting result.

[0010] In some embodiments, the original angle data is output as high-precision angle values after Kalman filtering, including: establishing a state space model containing angle state and angular velocity state, inputting the original angle data into the Kalman filter as measurement values, and iteratively estimating the angle state through a prediction step and an update step; wherein the prediction step predicts the current state based on the state of the previous moment and the system dynamics model, and the update step corrects the predicted state combined with the current measurement value, and finally outputs the high-precision angle values filtered from random noise and jitter.

[0011] In some embodiments, the main controller inputs the difference between the angle instruction sequence and the high-precision angle value into a position PID controller to calculate a speed instruction; the speed instruction is superimposed with an acceleration feedforward compensation amount and input into a field-oriented control module, the current in the three-phase stationary coordinate system is converted into direct-axis and quadrature-axis current instructions in the rotating coordinate system through coordinate transformation, and the direct-axis and quadrature-axis currents are controlled in a closed loop based on a PI controller; the control output voltage vector generates three PWM signals through a space vector pulse width modulation algorithm, and the duty cycle of the PWM signal is determined according to the amplitude and phase of the voltage vector and input into the drive chip.

[0012] In some embodiments, it further includes a thermal management compensation system, including temperature sensors distributed at key positions of the multi-layer PCB board, the temperature sensors collect temperature data in real time and input into a thermal deformation model, the thermal deformation model predicts the thermal expansion trend of the structure combined with historical data and outputs a thermal deformation angle prediction value, and the thermal deformation angle prediction value is superimposed on the angle instruction sequence as a feedforward compensation value to realize real-time compensation.

[0013] In some embodiments, the main controller inputs the temperature data and the current coil current value into a pre-trained long short-term memory neural network model, and the model outputs a predicted thermal deformation angle value; the main controller superimposes the thermal deformation angle value as a feedforward compensation value into the angle instruction sequence to realize real-time compensation of the angle deviation caused by rotor thermal expansion, and the system uses the newly added data to incrementally update the parameters of the long short-term memory neural network model during the idle period.

[0014] In some embodiments, it further includes a safety monitoring module for real-time monitoring of three-phase coil current, temperature at each key position, and the difference between the instruction angle and the feedback angle, and when the monitoring value exceeds the set threshold, triggering a protection mechanism to shut down the drive and report fault information.

[0015] The application relates to the technical field of laser precision positioning equipment, in particular to a high-precision electromagnetic driving angle rotation system based on multi-layer PCB integrated design, which is suitable for scenes requiring high-precision angle control such as laser scanning, optical image stabilization and precision measurement.

[0016] The driving circuit, sensing circuit, control circuit and electromagnetic coil array are integrated by the multi-layer PCB, the mechanical connecting components of the traditional separated design are eliminated, the system volume is significantly reduced, the structural compactness and reliability are improved, and the angle error caused by the mechanical transmission gap is avoided. The angle feedback system improves the angle measurement accuracy to sub-arcsecond level through four times frequency processing and Kalman filter algorithm, and effectively filters out the grating signal noise and rotor jitter. The control module adopts field oriented control (FOC) and space vector pulse width modulation (SVPWM), combined with speed feedforward compensation, to realize dynamic response speed improvement and torque ripple suppression.

[0017] The safety monitoring module monitors the current, temperature and angle deviation in real time, quickly closes the drive when the threshold value is triggered, avoids the risk of overcurrent, overheating and out-of-control, and improves the system fault protection response speed. Based on the mature PCB manufacturing process, the electromagnetic coil array and the circuit are integrated, the independent component assembly steps are reduced, the processing cost is reduced, and the batch production is suitable.

[0018] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present application. BRIEF DESCRIPTION OF DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0020] Figure 1 It is a structure schematic diagram of a laser precision angle rotation system based on a multi-layer PCB constructed based on a self-focusing optical fiber coupling scheme provided by an embodiment of the present application.

[0021] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present application. DETAILED DESCRIPTION

[0022] The technical solutions in the embodiments of the present application will be described clearly and completely in the following combined with the drawings in the embodiments of the present application. Obviously, the described embodiments are some embodiments of the present application, not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0023] The flowcharts shown in the drawings are merely illustrative and are not necessarily required to include all the contents and operations / steps, nor are they necessarily executed in the order described. For example, some operations / steps can also be broken down, combined, or partially merged, so the actual execution order can be changed according to actual conditions.

[0024] It should be understood that, in order to facilitate clear description of the technical solutions of the embodiments of the present application, in the embodiments of the present application, the terms "first", "second", and the like are used to distinguish the same or similar items with basically the same functions and effects. Those skilled in the art can understand that the terms "first", "second", and the like do not limit the number and execution order, and the terms "first", "second", and the like do not necessarily mean different.

[0025] It should be understood that the terms used in this application specification are only for the purpose of describing specific embodiments and do not intend to limit the application. As used in the specification and the appended claims of the present application, unless otherwise clear from the context, the singular forms "a", "an" and "the" are intended to include the plural forms.

[0026] It should also be understood that the term "and / or" used in the specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes these combinations.

[0027] Some embodiments of the present application will be described in detail below with reference to the accompanying drawings. The following embodiments and features in the embodiments can be combined with each other without conflict.

[0028] In the field of laser precision machining, optical measurement and precision instruments, a high-precision angle rotation system is a core component for realizing laser beam pointing control. Traditional angle rotation systems usually adopt a separate design, with the driving circuit, sensing circuit and control circuit independently laid out, relying on mechanical transmission structures (such as gears, worm gears) to connect the driving unit and the rotor, resulting in a large system size, angle errors caused by mechanical clearances, low integration and insufficient reliability. In addition, the angle feedback of the traditional system is mostly in the form of simple counting, without effectively filtering out noise and jitter, and the thermal deformation compensation relies on empirical formulas, with limited compensation accuracy, making it difficult to meet the requirements of micron-level or even nanometer-level precision angle control.

[0029] In the prior art, the electromagnetic driving structure mostly adopts a layout with independent coils and PCBs separated, the coil installation precision relies on mechanical positioning, increasing the assembly complexity; the angle signal processing is only through simple filtering, without combining intelligent algorithms such as Kalman filtering to improve accuracy; the thermal management compensation lacks real-time prediction mechanism and cannot dynamically adapt to changes in working conditions. Therefore, there is an urgent need for a system to solve at least one of the above problems.

[0030] To solve the above problems, please refer to Figure 1 The embodiment of the application provides a laser precision angle rotation system based on a multi-layer PCB, which comprises a multi-layer PCB, integrated driving circuit, sensing circuit and control circuit, an electromagnetic coil array is arranged on the multi-layer PCB; a rotor is arranged in cooperation with the electromagnetic coil array, and a laser reflector and a grating are fixedly connected to the rotor; an angle feedback system comprises a fixedly arranged photoelectric sensor array, the photoelectric sensor array is used for reading signals generated when the grating rotates, the signals are sequentially subjected to amplification, filtering and shaping processes to form a digital square wave signal, the digital square wave signal is subjected to four times frequency processing and position counting to obtain original angle data, and a high-precision angle value is output after the original angle data is subjected to Kalman filtering processing; a control module comprises an upper computer, a main controller and a driving chip, the upper computer is used for inputting instructions, the instructions comprise two modes of continuous trajectory and point-to-point and generate an angle instruction sequence, the angle instruction sequence is transmitted to the main controller through a protocol, the main controller generates a three-phase PWM signal and inputs the three-phase PWM signal into the driving chip according to the angle instruction sequence and the high-precision angle value, and the driving chip outputs a three-phase current to drive the electromagnetic coil array.

[0031] Specifically, the system is designed by multi-layer PCB integration, which deeply integrates electromagnetic drive, angle sensing and control algorithm to form a full-electronic precision angle control scheme without mechanical transmission. By embedding the electromagnetic coil array in the multi-layer PCB conductive layer, the driving / sensing / control circuit is integrated on the same board to eliminate the mechanical connection gap of the traditional separate drive; the angle signal is obtained by the grating-photoelectric sensor combination, and the measurement accuracy is improved through multi-stage signal processing and Kalman filtering; the magnetic field oriented control (FOC) is combined with speed feedforward compensation to realize the dynamic response optimization of electromagnetic drive, and the temperature drift is compensated through the thermal deformation prediction model.

[0032] Multi-layer PCB: 6-10 layers of FR-4 or high thermal conductivity substrate, 2-4 layers as conductive layers, integrating the following functional modules: driving circuit layer: containing power MOSFET, freewheeling diode and other driving devices, directly connected with electromagnetic coil array through copper foil circuit; sensing circuit layer: integrating preamplifier, bandpass filter, voltage comparator and other signal conditioning circuits to process analog signals output by photoelectric sensor; control circuit layer: arranging main controller (such as DSP or ARM chip), programmable logic device (FPGA), communication interface (such as SPI / I2C / UART) to realize control algorithm and data interaction.

[0033] Through etching annularly arranged planar spiral coils on each conductive layer, the number of single coils is 6-12 groups, which are evenly distributed at intervals of 30°-60°; adjacent layer coils are staggered by 15°-30° in the circumferential position, and are connected in series or parallel through conductive vias to form a three-dimensional magnetic field distribution; the coil wire width is 0.2-0.5mm, and the wire spacing is 0.3-0.6mm, which improves the conductivity through PCB plating process and reduces copper loss. After the electromagnetic coil array is powered on, an alternating magnetic field is generated, which interacts with the permanent magnet (or induced eddy current) on the rotor to drive the rotor to rotate around the central axis. Since the coil is directly integrated on the PCB, no additional mechanical fixation is needed, eliminating the problem of magnetic field non-uniformity caused by traditional coil assembly deviation.

[0034] A central symmetric disc structure is adopted, the material is aluminum alloy or titanium alloy, and the surface is plated with nickel-chromium alloy to improve hardness; the central shaft is coaxially installed with the central hole of the PCB board, and cooperates with a high-precision bearing (radial runout ≤1μm) to ensure rotation accuracy; the laser mirror is fixed on the upper surface of the rotor by vacuum adsorption or epoxy resin adhesion, and the mirror surface flatness is ≤λ / 10 (λ=632.8nm); the grating adopts a glass transmission type incremental grating, with a line number of 1000-2000 lines per circle, and the scale lines are distributed along the radial direction of the rotor to form a reading system with the photoelectric sensor array (fixed on the edge of the PCB board). The distance between the rotor and the PCB board is controlled at 0.5-1mm, and the axial movement is prevented by limiting structure to ensure that the electromagnetic air gap uniformity error is less than 5%.

[0035] The photoelectric sensor array includes 4 groups of transmitting and receiving type photoelectric sensors, which output two-way orthogonal (phase difference 90°) analog signals (A phase, B phase) with an amplitude of 0-5V; the signal conditioning process includes: amplification: gain adjustable amplification (gain range 10-100 times) is performed by an instrument amplifier (such as AD620) to compensate for grating signal attenuation; filtering: a fourth-order Butterworth band-pass filter (center frequency 10kHz, bandwidth 5kHz) is used to filter out low-frequency noise (<1kHz) and high-frequency electromagnetic interference (>20kHz) introduced by mechanical vibration; shaping: a hysteresis comparator (such as LM311) is used to convert the filtered sine wave into a square wave signal at TTL level, and the hysteresis voltage is 50-100mV to prevent noise jitter.

[0036] Four times frequency and counting are realized by receiving A and B phase square wave signals through FPGA, detecting each edge (rising edge / falling edge), achieving four times frequency (resolution is improved by 4 times), and accumulating pulse number through a 32-bit counter. Angle calculation formula: original angle = (pulse count × 360°) / (grating line number × 4).

[0037] A two-dimensional state space model is established, the state quantity is angle θ and angular velocity ω, and the observation value is the original angle data after four times frequency. Through the prediction equation (θk = θk-1 + ωk-1*Δt, ωk= ωk-1) and the update equation, the measurement noise is corrected in real time, and the output noise standard deviation is less than 0.1″.

[0038] The host computer inputs the target angle (point-to-point mode) or trajectory curve (continuous mode) through the human-machine interface, generates an instruction sequence containing time-angle parameters, and transmits the instruction sequence to the main controller through the CAN / LAN bus. The main controller calculates the deviation between the instruction angle and the feedback angle, outputs the speed instruction through the PID controller, the proportional coefficient Kp = 200-500, the integral time Ti = 0.01-0.05s, and the differential time Td = 0.001-0.005s; speed feedforward compensation: according to the instruction angular velocity, the required electromagnetic torque is pre-calculated and superimposed to the PID output, reducing the dynamic response lag (response time <1ms); The magnetic field oriented control (FOC) converts the measured three-phase current into the direct-axis current i_d (excitation current) and the quadrature-axis current i_q (torque current) through Clark transformation (three-phase static → two-phase static) and Park transformation (two-phase static → two-phase rotating); PI controller is used to control i_d and i_q (i_d*=0 to realize unit power factor control), and voltage instructions u_d and u_q in rotating coordinate system are output; space vector pulse width modulation (SVPWM): u_d and u_q are converted into PWM signals of three-phase bridge arms, the carrier frequency is 20kHz, the switching loss is reduced through seven-segment modulation strategy, and the output voltage harmonic distortion is less than 5%. The driving chip receives the PWM signal, controls the three-phase bridge circuit to output 0-48V, 0-5A current to drive the electromagnetic coil, and the current sampling resistance (precision 1%) feedback to the main controller realizes overcurrent protection.

[0039] For example, the corresponding parameters are shown in the following table: In some embodiments, the electromagnetic coil array is integrated in the conductive layer of the multi-layer PCB board in a layered manner, each layer of electromagnetic coil is arranged in a ring shape at a preset angle interval, the electromagnetic coils of adjacent layers are distributed in a staggered manner in the circumferential position, and the electromagnetic coil array is directly electrically connected with the driving circuit of the multi-layer PCB board. The electrical connection of each layer of coil is realized through the conductive via of the multi-layer PCB board, forming an embedded electromagnetic driving structure without mechanical transmission components.

[0040] The core of the embodiment is to realize the layered embedded integration of the electromagnetic coil array through the conductive layers of the multi-layer PCB, and eliminate the mechanical connecting parts of the traditional driving structure. Specifically, the electromagnetic coils are layered and arranged in the conductive layers of the multi-layer PCB according to functions, each layer of coils is independently etched and interconnected through conductive vias; the single-layer coils are arranged in a ring shape at a preset angle interval (such as 30°, 45°), the adjacent layer coils are staggered by 15°-30° in the circumferential position, forming a three-dimensional magnetic field superposition effect; the coils are directly connected with the driving circuit through the copper foil of the PCB, without external cables or mechanical fixing structure, realizing the integrated integration of the driving unit and the circuit.

[0041] The PCB layered structure adopts an 8-layer PCB board, in which the 2nd, 4th and 6th layers are used as coil layers, each layer has a thickness of 50 μm copper foil; each coil layer is etched with 8 groups of planar spiral coils, which are distributed in a ring shape at an interval of 45° with the center of the PCB as the center, each coil has an outer diameter of 5 mm, an inner diameter of 3 mm, a line width of 0.3 mm and a line spacing of 0.4 mm.

[0042] The staggered design of adjacent layers is that the starting position of the 2nd layer coil is 0°, the starting position of the 4th layer coil is 22.5° (i.e. staggered by 1 / 8 period), and the starting position of the 6th layer is 45°, forming the staggered superposition of each layer coil in the circumferential direction; the adjacent layers are connected through conductive vias with a diameter of 0.3 mm, and the adjacent layer coils are connected in series (such as the output end of the 2nd layer coil 1→via→the input end of the 4th layer coil 1), and the total inductance value is adjustable through the interlayer connection mode (series connection increases inductance, and parallel connection reduces impedance). The electrical connection and the driving circuit integration are directly connected to the power MOSFET of the driving circuit layer through the copper foil of the coil layer, the drain is connected to the coil input end, and the source is connected to the current diode (such as a fast recovery diode); the driving circuit is powered by the power supply layer (3rd and 5th layers) in the PCB, the voltage range is 12-48V, and the current carrying capacity is 5A / mm 2 Copper foil (satisfying the peak current requirement of the coil).

[0043] In some embodiments, the analog signal output by the photoelectric sensor array is first input to a preamplifier for gain-adjustable amplification processing, the amplified signal is filtered through a band-pass filter with fixed center frequency and limited bandwidth to filter out high-frequency and low-frequency noise, and the filtered signal is compared with a preset threshold voltage through a voltage comparator, so as to convert the analog signal into a digital square wave signal with fixed high and low levels.

[0044] The embodiment specifies the three-stage preprocessing procedure of analog signals in the angle feedback system, including adjustable gain amplification, band-pass filtering, threshold comparison, to ensure the reliability of the digital square wave signal. Specifically, the weak analog signal output by the photoelectric sensor is amplified with adjustable gain to compensate for signal attenuation; a filter with fixed center frequency and bandwidth is used to filter out mechanical vibration (low frequency) and electromagnetic interference (high frequency) noise; the filtered sine wave is converted into a square wave signal with standard TTL level by a voltage comparator to eliminate noise jitter.

[0045] The preamplifier circuit includes: device selection: instrument amplifier AD620, gain set by external resistor Rg (gain formula G=1+49.4kΩ / Rg, adjustable range 10-200 times); input signal: orthogonal analog signal (A phase, B phase) output by the photoelectric sensor, peak-to-peak value 0.5-2V, DC bias 2.5V; circuit design: differential input to suppress common-mode noise, input end in parallel with 100nF decoupling capacitor to suppress high-frequency interference.

[0046] The band-pass filter circuit includes: filter type: fourth-order Butterworth band-pass filter, center frequency f0=10kHz, passband width BW=8kHz (cutoff frequency 2kHz-18kHz); component parameters: designed with operational amplifier OPA227, resistor R=10kΩ, capacitor C=1.59nF (calculated according to f0=1 / (2πRC)); filtering effect: attenuate mechanical vibration noise (<1kHz, such as bearing vibration) and PWM switching noise (>20kHz, suppression amplitude >40dB).

[0047] The voltage comparator circuit includes: device selection: hysteresis comparator, reference voltage Vref=2.5V (consistent with the sensor bias voltage); hysteresis voltage setting: ±50mV (achieved by feedback resistor voltage division), to prevent output signal oscillation caused by noise; output signal: converted into a square wave signal with 3.3V TTL level, rise / fall time <100ns, duty cycle 50%±5%. The preprocessing circuit is integrated in the PCB sensing layer, close to the photoelectric sensor (distance <5mm), to reduce noise introduced by long wires; The analog ground and digital ground share a single ground point through a 0Ω resistor to suppress ground loop interference.

[0048] In some embodiments, the rotor is a centrally symmetric disc structure, the central axis of the rotor coincides with the central axis of the electromagnetic coil array, the laser mirror is fixedly installed on the upper surface of the rotor and rotates synchronously with the rotor, the grating is fixedly installed concentrically on the edge region of the rotor, and the scale line direction of the grating is consistent with the radial direction of the rotor, so that the grating can be read by the photoelectric sensor array when the grating rotates with the rotor.

[0049] The embodiment defines the mechanical structure of the rotor and the installation method of the optical element, to ensure that the laser mirror and the grating rotate synchronously with high precision. The core design includes: central symmetric disc structure: the geometric center of the rotor coincides with the center axis of the electromagnetic coil, reducing the rotation error caused by eccentricity; mirror and grating coaxial installation: the mirror is fixed on the center area of the upper surface of the rotor, and the grating is concentrically arranged on the edge, with the scale lines distributed radially, facilitating the reading of the photoelectric sensor.

[0050] The rotor body design includes: material: aviation aluminum alloy (such as 6061-T6), density 2.7 g / cm 3 , thermal expansion coefficient 23.6×10 -6 / ℃, surface anodizing treatment; structure: diameter 60 mm, thickness 5 mm, center shaft hole diameter 8 mm (cooperating with high-precision bearing), edge area thickness 3 mm (lightening weight, moment of inertia ≤5×10 -6 kg*m 2 ); processing precision: perpendicularity of center shaft hole and rotor end face ≤5 μm, circumferential runout ≤2 μm.

[0051] Laser mirror installation: mirror specifications: diameter 20 mm, thickness 2 mm, surface coated with high reflection film (reflectivity > 99.5% @ 632.8 nm), flatness ≤ λ / 20; the fixing method is to use low-expansion coefficient epoxy resin (such as EPO-TEK 353ND) to bond to the center of the upper surface of the rotor, with a bonding layer thickness ≤50 μm, and after curing, angle calibration is performed (perpendicularity of mirror normal line and rotor axis ≤10″).

[0052] Grating installation and scale design includes: grating type: transmissive glass incremental grating, line number 2000 lines / turn, outer diameter 50 mm, inner diameter 40 mm; installation position: the grating is fixed to the edge of the rotor (25 mm away from the center axis) by three evenly distributed elastic pressure tablets, and the scale lines extend radially along the rotor (with an included angle ≤1° with the radial direction); reading cooperation: the photoelectric sensor array (4 groups of reflection type) is fixed to the edge of the PCB, maintaining a 0.5 mm spacing with the grating, to ensure that the light transmittance is > 80%. Mechanical cooperation: bearing selection: deep groove ball bearing EZO R8804 is used, with radial runout ≤1 μm and axial runout ≤2 μm; air gap control: the spacing between the rotor and the PCB coil layer is 1 mm, which is axially positioned by a limiting ring (thickness 1 mm), and the air gap uniformity error is <3%.

[0053] In some embodiments, the digital square wave signal is divided into A-phase and B-phase signals with a phase difference of 90 degrees, which are input to a programmable logic device for four times frequency processing, that is, a counting pulse is triggered at the rising and falling edges of each signal period, and the pulse signal after four times frequency processing is counted by a 32-bit counter. The original rotation angle data of the rotor is calculated according to the preset grating line number and pulse counting result.

[0054] The embodiment improves the angle measurement resolution by quadrupling the orthogonal A / B phase signals, specifically including: the phase difference of 90° of the orthogonal signals: A-phase and B-phase signals output by the photoelectric sensor are used to determine the rotation direction and realize edge triggering; the quadrupling principle: triggering the counting at the rising and falling edges of each signal period, so that the resolution is improved to 4 times the original grating line number; 32-bit counter: accumulates the pulse number and converts it to an angle value, meeting the high-precision angle calculation requirement.

[0055] The orthogonal signal characteristics include: the phase difference of 90° of A-phase and B-phase signals, the A-phase leading the B-phase by 90° when the rotor rotates forward, and the B-phase leading the A-phase by 90° when the rotor reverses; the signal frequency: f=ω×N / (2π), where ω is the rotor angular velocity (rad / s), N is the grating line number (such as 2000 lines / turn), and the maximum frequency ≤50kHz (corresponding to the rotation speed of 3000rpm).

[0056] Quadrupling implementation: hardware carrier: programmable logic device (FPGA, such as Xilinx Spartan-6), internally integrated edge detection module; edge detection: detecting the rising edge (↑) and falling edge (↓) of A-phase and B-phase respectively, generating 4 count trigger signals (A↑, A↓, B↑, B↓); direction determination: comparing the current A / B phase state with the previous state (such as A(n)=1, B(n)=0, A(n-1)=0, B(n-1)=0, determining as forward rotation), controlling the counter to add or subtract.

[0057] Counting and angle calculation includes: counter: 32-bit unsigned register, maximum count value 4,294,967,296, corresponding to the angle measurement range > 360°×4,294,967,296 / (2000×4)=193,712,424° (satisfying full circle measurement); Angle calculation formula: θ=(pulse count×360°) / (grating line number×4)= (pulse count×360°) / (2000×4)=pulse count×0.045°. The resolution is 0.045° / pulse=162″ / pulse, which is 4 times the original grating resolution (360° / 2000=108″ / line) after quadrupling to 40.5″ / pulse (actually further improved to sub-arcsecond level through Kalman filtering). By setting 2-level register synchronization at the FPGA input port, sub-stable state noise is filtered out; every 1ms, overflow detection is performed on the counter (when the count value > the upper limit, it is reset to zero and the overflow flag is marked), ensuring the continuity of angle calculation.

[0058] In some embodiments, the original angle data is output as a high-precision angle value after Kalman filtering, including: establishing a state space model containing angle state and angular velocity state, inputting the original angle data as a measurement value into a Kalman filter, and iteratively estimating the angle state through a prediction step and an update step; wherein the prediction step is based on the state at the previous time and the system dynamics model to predict the current state, and the update step is combined with the current measurement value to correct the predicted state, and finally output a high-precision angle value after filtering out random noise and jitter.

[0059] The embodiment establishes a two-dimensional state space model to perform Kalman filtering on the original angle data, filter out random noise and high-frequency jitter, and output a high-precision angle value. The core steps include: state space modeling: defining angle θ and angular velocity ω as state quantities, and constructing a prediction equation containing system dynamics; Kalman filtering iteration: through a "prediction-update" loop, the state at the previous time is used to predict the current state, and the measured value is used to correct the prediction error, and noise suppression is achieved.

[0060] State vector: xk=[θk, ωk] T , wherein θ is the angle (rad), and ω is the angular velocity (rad / s). Prediction equation (based on uniform motion model): xk|k-1=Fxk-1|k-1+Buk; state transition matrix F= ; control input matrix B= , (considering the influence of acceleration u, u=0 in this embodiment, simplified as a uniform model). Observation equation: zk=Hxk+vk, H=[1, 0], the observation value z is the original angle data after four times frequency, and vk is the measurement noise (Gaussian distribution, standard deviation σz=10").

[0061] The Kalman filter parameter setting includes: process noise covariance matrix Q= , angle noise σθ=5", and angular velocity noise σω=2" / ms. Measurement noise covariance matrix: R=σz 2 =(10") 2 . Initial state estimation: x0=[0, 0] T , covariance matrix P0=diag([(30") 2 ,(5" / ms) 2 ]). The iteration steps include calculating the state prediction value, calculating the prediction covariance, calculating the Kalman gain, correcting the state estimation, and updating the covariance.

[0062] In some embodiments, the main controller inputs the difference between the angle instruction sequence and the high-precision angle value into a position PID controller to calculate a speed instruction; the speed instruction is superimposed with an acceleration feedforward compensation amount to input into a magnetic field orientation control module, three-phase static coordinate system current is converted into direct-axis and quadrature-axis current instructions in a rotating coordinate system through coordinate transformation, and PI controllers are used to close-loop control the direct-axis and quadrature-axis currents; the control output voltage vector is used to generate three PWM signals through a space vector pulse width modulation algorithm, and the duty cycles of the PWM signals are determined according to the amplitude and phase of the voltage vector and input into the driving chip.

[0063] The embodiment constructs a "position loop-PID-speed feedforward-FOC-SVPWM" closed-loop control chain to achieve high-precision angle tracking. The position error calculation inputs the deviation between the target angle and the filtered angle into a PID controller to generate a speed instruction; the speed feedforward compensation pre-calculates the torque required for dynamic response to reduce control lag; the magnetic field orientation control separates the excitation current and torque current through coordinate transformation to independently control to improve response speed; and the SVPWM modulation is used to generate efficient PWM signals to drive the electromagnetic coil.

[0064] Position PID controller: input and output: error e(t)=θ∗(t)-θ(t), output speed instruction vcmd(t); wherein: ; Parameter range: Kp=300-500, Ki=10-20, Kd=0.5-1.0 (adaptively adjusted according to rotor inertia); anti-saturation design: set output amplitude limit ±1000° / s to prevent integral saturation.

[0065] The speed feedforward compensation includes: torque pre-calculation: Tff=Jω'cmd+Bωcmd, wherein J is the rotor rotational inertia (5×10 -6 kg*m 2 ), B is the viscous damping coefficient (0.001 N*m*s / rad); current instruction mapping: iqff=Tff / Kt (Kt is the torque constant, 0.1 N*m / A), superimposed with the iq∗ output by the PID.

[0066] The magnetic field orientation control (FOC) includes: coordinate transformation: Clark transformation (three-phase to two-phase static), Park transformation (two-phase static to two-phase rotating), current loop PI control, carrier parameter, voltage vector synthesis and driving output.

[0067] In some embodiments, further comprising: a thermal management compensation system, including temperature sensors distributed at key positions of the multi-layer PCB board, the temperature sensors collecting temperature data in real time and inputting to a thermal deformation model, the thermal deformation model combining historical data to predict thermal expansion trend of the structure and outputting a thermal deformation angle prediction value, the thermal deformation angle prediction value being superimposed on the angle command sequence as a feedforward compensation value to achieve real-time compensation.

[0068] The present embodiment collects temperature rise data of key positions of the PCB in real time through temperature sensors, inputs a thermal deformation model to predict angle deviation caused by structural expansion, and eliminates temperature drift through feedforward compensation. The temperature collection network covers heat sources (coils, driving chips) and sensitive areas (encoders) through multi-point deployment of NTC sensors; the thermal deformation prediction is based on historical data or physical models to output a thermal deformation angle prediction value; and the real-time compensation dynamically corrects the temperature influence by superimposing the predicted deviation on the command sequence.

[0069] The temperature sensor deployment includes: position distribution: coil layer center (1), coil layer edge (2) - monitor electromagnetic heating; driving chip surface (1), encoder circuit board (1) - monitor circuit heating; sensor type: NTC thermistor (B value 3950K, accuracy ±0.3℃, model MF52E), cooperate with 10kΩ voltage dividing resistor to collect voltage signal, and convert through 12-bit ADC (resolution 0.1℃).

[0070] The thermal deformation model includes: thermal expansion formula: Δθ=αΔTL / r×180° / π, where α is the thermal expansion coefficient of the rotor material (23.6×10⁻ 6 / ℃), ΔT is the temperature rise (℃), L is the distance from the rotor edge to the center axis (25mm), r is the grating radius (25mm), which is simplified as Δθ=αΔT×360° / 2π (angle deviation is related to circumferential expansion amount); dynamic correction is achieved by collecting temperature data every 5ms, calculating the average temperature rise ΔT, and updating the compensation amount in real time (response delay <10ms).

[0071] The compensation control logic includes: instruction superposition: target angle θcomp∗ =θcmd∗+Δθpred, where Δθpred is the predicted deviation (when the rotor outer diameter expands due to positive temperature rise, the angle feedback lags, and the compensation direction is opposite to the expansion direction); when the temperature change rate of any measuring point is >0.5℃ / min, dynamic compensation is enabled; and the compensation amount is set to 0 when in stable temperature zone (ΔT<1℃).

[0072] In some embodiments, the main controller inputs the temperature data and current coil current value to a pre-trained long short-term memory neural network model, the model outputs a predicted thermal deformation angle value; the main controller superimposes the thermal deformation angle value as a feedforward compensation value into the angle instruction sequence, realizing real-time compensation of the angle deviation caused by rotor thermal expansion, and the system uses new data to incrementally update the parameters of the long short-term memory neural network model during the idle period.

[0073] The embodiment adopts a long short-term memory neural network (LSTM) to construct a thermal deformation model, inputs temperature data and coil current (reflecting heating power), and outputs a thermal deformation angle prediction value, realizing nonlinear and dynamic thermal drift compensation. Data-driven modeling trains the model by using historical temperature rise-angle deviation data, adapting to complex thermal coupling effects; an incremental update mechanism optimizes model parameters with new data during system idle time, maintaining prediction accuracy; feedforward compensation superimposes real-time prediction values to the instruction sequence, compensating for fast temperature rise scenarios (such as high-power operation).

[0074] The LSTM model architecture includes: input layer: 8 nodes - 4 temperature sensor data (current time t-2, t-1, t), 3-phase coil current effective value (current time t); hidden layer: 64 LSTM units, time step 3 (input the latest 3 time data to capture temperature change trend); output layer: 1 node - predicted thermal deformation angle Δθ_pred (unit: μrad) in the future 1 ms; activation function: linear activation for input layer / output layer, tanh activation for hidden layer.

[0075] The training data preparation includes: sample collection: temperature rise test in a temperature chamber, control coil current 0-5A (corresponding to power consumption 0-24W), collect temperature (50Hz), angle deviation (1kHz), generate 5000 groups of samples (4000 for training set, 1000 for validation set); data preprocessing: temperature normalization (0-1), angle deviation standardization (mean 0, standard deviation 1), use sliding window (window size 3) to generate time series samples.

[0076] Model training and updating includes: optimizer: Adam (learning rate 0.001), loss function MSE, train until the validation set MSE < (0.5 μrad) 2 ; incremental update: when the system is idle (such as when there is no angle instruction), add the latest 100 groups of data to the training set, and retrain the last 10 hidden layer units (cold start update, time consumption < 100 ms).

[0077] Real-time prediction and compensation includes: prediction frequency: 1kHz (synchronous with control period), input current and temperature data at current and previous 2 time points, output Δθpred; compensation logic: θcmd* = θref* - Δθpred (thermal expansion causes the actual angle of the rotor to lag behind the feedback value, and the compensation direction is opposite).

[0078] In some embodiments, further comprising: a safety monitoring module for real-time monitoring of three-phase coil current, temperature at each key position, and the difference between command angle and feedback angle, and when the monitored values exceed the set threshold, triggering the protection mechanism to shut down the drive and report fault information.

[0079] The present embodiment prevents system damage by monitoring key parameters such as current, temperature, and angle deviation in real time, triggering hardware-level protection and fault reporting when abnormalities occur. Multi-parameter monitoring: covering electrical, thermal, and kinematic risk indicators; hierarchical protection mechanism: combining hardware fast response (μs level) with software logic judgment; fault diagnosis: recording fault codes for easy maintenance later.

[0080] The monitoring parameters and threshold values are shown in the following table: Overcurrent protection compares the current sampling signal with a 5A threshold voltage through a comparator (LM339) and outputs a low level to the drive chip enable end (EN) to directly shut off the MOSFET drive signal; Over-temperature protection triggers a relay to disconnect the power input (backup battery maintains fault records) through the temperature sensor signal output by the hysteresis comparator. After clearing the fault, a "reset" command needs to be sent by the upper computer, and the system restarts according to the "sensor self-test -> hardware initialization -> zero-point calibration" process to prevent false actions.

[0081] In some embodiments, for the difference in thermal characteristics under different working modes (such as high-precision positioning mode and fast scanning mode), a transfer learning technique is used to fine-tune a pre-trained LSTM model with a small amount of target working condition data, achieving fast adaptation of cross-mode thermal deformation prediction. Solving the prediction delay problem of traditional models when switching working conditions, and improving the real-time performance of dynamic compensation.

[0082] The migration learning architecture design comprises: a source domain model: a general LSTM model is trained by using historical full working condition data (containing 10 typical operation modes), and common features of the thermal-deformation relationship (such as temperature conduction delay and coil heating coupling law) are extracted; target domain fine tuning: when the system is switched to a new working condition (such as entering the 'high-speed rotation mode' for the first time), 10 minutes of real-time data (about 60,000 samples) are collected, the first two layers of LSTM parameters are frozen, and only the last layer of full connection is trained, so that the model quickly adapts to the thermal dynamic characteristics under the specific working condition. Working condition feature vector: input current control mode (1-10 categories), coil current waveform (frequency domain features), and temperature gradient (sensor temperature difference), and the current working condition category is identified through a lightweight CNN (3 layers of convolution); model storage and calling: 8 lightweight sub-models (each about 200KB) are built in the main control chip, corresponding to different priority working conditions, and the corresponding sub-model is loaded or the fine tuning process is triggered according to the identification result. After each working condition switching, the new working condition data is added to the source domain data set, and the global model is updated (incremental training) every 24 hours during the system sleep period to avoid 'catastrophic forgetting'; the prediction delay is reduced from 15ms of the traditional LSTM to 5ms after migration learning (when the working condition is known), and the first adaptation time of the unknown working condition is less than 3 minutes.

[0083] The application relates to the technical field of laser precision positioning equipment, in particular to a high-precision electromagnetic driving angle rotation system based on multi-layer PCB integrated design, which is suitable for scenes requiring high-precision angle control such as laser scanning, optical image stabilization and precision measurement.

[0084] The driving circuit, the sensing circuit, the control circuit and the electromagnetic coil array are integrated by the multi-layer PCB, mechanical connecting components in traditional separated design are eliminated, the system volume is significantly reduced, the structure compactness and reliability are improved, and angle errors caused by mechanical transmission gaps are avoided. The angle feedback system improves the angle measurement accuracy to sub-arcsecond level through four times frequency processing and Kalman filtering algorithm, and effectively filters out grating signal noise and rotor jitter. The control module adopts magnetic field oriented control (FOC) and space vector pulse width modulation (SVPWM), and combines speed feedforward compensation to realize dynamic response speed improvement and torque ripple suppression.

[0085] The safety monitoring module monitors the current, temperature and angle deviation in real time, quickly closes the drive when the threshold value is triggered, avoids overcurrent, overheating and out-of-control risks, and improves the system fault protection response speed. Based on the mature PCB manufacturing process, the electromagnetic coil array and the circuit are integrated, the independent component assembly steps are reduced, the processing cost is reduced, and batch production is suitable.

[0086] In some embodiments, for a cluster system composed of multiple devices, a federated learning (Federated Learning) technology is adopted to train a safety monitoring model locally on each device, and only upload model parameters to the central server for aggregation, realizing “data not moving model moving”, protecting user data privacy while improving fault prediction generalization ability. Solving the problem of insufficient fault data of a single device, especially suitable for early warning of rare faults (such as coil insulation aging).

[0087] The device end (edge node) includes: a local safety monitoring module collects current waveform, temperature sequence, angle deviation and other data (100 groups per second), and labels abnormal data (such as waveform 10 seconds before overcurrent); based on 1D-CNN, a local fault prediction model is trained (detecting 6 types of faults such as overtemperature and inter-turn short circuit), and model gradient (non-original data) is sent to the server every 10 minutes; the central server aggregates multiple device gradients to update the global model (FedAvg algorithm), and updates the model (parameter size < 50KB) every 50 times of aggregation; a global fault feature library is maintained, and rare fault samples (such as bearing wear fault occurring in only 3 devices) are labeled, and the data source is protected by differential privacy technology (ε = 0.5).

[0088] The specific model includes: CNN structure: 2 layers of convolution (3x3 kernel, step 1) + global average pooling + fully connected layer (output 6 types of fault probability); training strategy: the device only starts training during the idle period (such as night), CPU occupancy < 20%, and battery-powered devices can prolong the endurance through low-power mode; anomaly detection: when the local model predicts the fault probability > 0.95, the local protection mechanism is triggered immediately, and a warning is sent to the server (including anonymous device ID).

[0089] In some embodiments, for extreme working conditions (such as sudden power failure and sensor total failure) that are difficult to reproduce in actual systems, a generative adversarial network (GAN) is used to generate virtual extreme scenario data to enhance the robustness of the safety monitoring module. By training the discriminator to distinguish between real data and generated data, the generator is forced to learn extreme fault features, improving the fault tolerance of the system under unknown faults.

[0090] The GAN model construction includes: a generator (G): input a random noise vector (100 dimensions), generate sensor data under extreme conditions (such as current surge 10A, temperature mutation +50℃, angle feedback jump ±10°) through a deconvolution network, the output dimension is consistent with the real sensor data (6 dimensions); a discriminator (D): a 3-layer fully connected network, judges whether the input data is a real sample or a generated sample, the loss function uses WGAN-GP (Wasserstein distance + gradient penalty) to avoid mode collapse; the training data: the initial real data contains 2000 normal samples + 500 known fault samples, the generator aims to deceive the discriminator, and the discriminator aims to correctly classify.

[0091] The safety monitoring model enhancement is achieved by adding the generated extreme data (accounting for 30% of the training set) to the training set of the safety monitoring module, and retraining the fault detection classifier (such as SVM or lightweight CNN); The real-time fault tolerance strategy includes: when detecting that the sensor data exceeds the historical normal range ±3σ, triggering the "extreme condition mode"; switching to the backup control strategy (such as open-loop compensation relying only on current and temperature) trained based on GAN generated data, maintaining system safety shutdown rather than directly powering off.

[0092] The generator and the discriminator are only trained offline on the PC, and after the training is completed, the key fault features (such as high-frequency harmonic components of the current waveform) are extracted, and converted into rules (such as "current rise rate > 5A / ms and temperature > 90℃ to determine coil short circuit") recognizable by the embedded system; the response time under extreme conditions is <20μs, which is realized by hardware comparators and logic circuits to avoid software delay.

[0093] It should be understood that the terms used herein in this application are merely for the purpose of describing particular embodiments and are not intended to limit the present application. It should be understood that when an element or layer is referred to as "on", "adjacent to", "connected to", or "coupled to" another element or layer, it can be directly on, adjacent to, connected or coupled to the other element or layer, or there can be intervening elements or layers. Conversely, when an element is referred to as "directly on", "directly adjacent to", "directly connected to", or "directly coupled to" another element or layer, there are no intervening elements or layers. It should be understood that although the terms first, second, third, etc. are used to describe various elements, components, regions, layers and / or parts, these elements, components, regions, layers and / or parts should not be limited by these terms. These terms are only used to distinguish one element, component, region, layer or part from another element, component, region, layer or part. Therefore, the first element, component, region, layer or part discussed below can be represented as the second element, component, region, layer or part without departing from the teachings of the present application.

[0094] Spatially relative terms, such as "beneath", "below", "lower", "under", "above", "upper" and the like, can be used herein for ease of description to describe one element or feature's relationship to another element(s) or feature(s) as illustrated in the figures. It will be understood that the spatially relative terms are intended to encompass different orientations of the device in use and / or operation in addition to the orientations depicted in the figures. For example, if a device in the figures is inverted, then a dependent- element described as "below" or "beneath" another element or feature would then be oriented "above" and "over" the other element or feature. Thus, the exemplary term "below" can encompass both an orientation of above and below. The device can be otherwise oriented (rotated 90 degrees or at other orientations) and the spatially relative descriptors used herein interpreted accordingly.

[0095] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the present application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and / or "comprising", when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0096] It will be further understood that the terms "comprises" and / or "comprising", when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0097] The above description is only specific embodiments of the present application, but the protection scope of the present application is not limited thereto, and any person skilled in the art can easily think of various equivalent modifications or replacements within the technical range disclosed by the present application, and these modifications or replacements should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A laser precision angle rotation system constructed based on a multi-layer PCB, characterized in that, The application relates to a high-precision rotary actuator. The application comprises: a multi-layer PCB board integrating driving circuit, sensing circuit and control circuit, wherein an electromagnetic coil array is arranged on the multi-layer PCB board; a rotor cooperating with the electromagnetic coil array, wherein a laser reflector and a grating are fixedly connected to the rotor; an angle feedback system comprising a fixedly arranged photoelectric sensor array, wherein the photoelectric sensor array is used for reading signals generated by the grating rotation, the signals are sequentially subjected to amplification, filtering and shaping treatment to form a digital square wave signal, the digital square wave signal is subjected to four times frequency processing and position counting to obtain original angle data, and the original angle data is subjected to Kalman filtering treatment to output a high-precision angle value; 2. The laser precision angle rotation system constructed based on multi-layer PCB according to claim 1, characterized in that, a control module comprising an upper computer, a main controller and a driving chip, wherein the upper computer is used for inputting instructions, the instructions comprise two modes of continuous trajectory and point-to-point and generate angle instruction sequences, the angle instruction sequences are transmitted to the main controller through a protocol, the main controller generates three-phase PWM signals through position control loop calculation, speed feedforward compensation, magnetic field orientation control and space vector pulse width modulation treatment according to the angle instruction sequences and the high-precision angle value, and the three-phase PWM signals are input into the driving chip, and the driving chip outputs three-phase current to drive the electromagnetic coil array.

3. The laser precision angle rotation system constructed based on multi-layer PCB according to claim 1, characterized in that, The electromagnetic coil array is integrated in a conductive layer of the multi-layer PCB board in a layered mode, each layer of electromagnetic coil is arranged in a ring shape at a preset angle interval, the electromagnetic coils of adjacent layers are distributed in a staggered mode in a circumferential position, and the electromagnetic coil array is directly electrically connected with a driving circuit of the multi-layer PCB board, the electrical connection of each layer of coil is realized through a conductive via of the multi-layer PCB board, and an embedded electromagnetic driving structure without mechanical transmission components is formed.

4. The laser precision angle rotation system constructed based on multi-layer PCB according to claim 1, characterized in that, The analog signal output by the photoelectric sensor array is first input into a preamplifier for gain-adjustable amplification treatment, the amplified signal is filtered through a band-pass filter with fixed center frequency and limited bandwidth to remove high-frequency and low-frequency noise, and the filtered signal is compared with a preset threshold voltage through a voltage comparator to convert the analog signal into a digital square wave signal with fixed high and low levels.

5. The laser precision angle rotation system constructed based on multi-layer PCB according to claim 1, characterized in that, The rotor is a center-symmetrical disc structure, the central axis of the rotor coincides with the central axis of the electromagnetic coil array, the laser reflector is fixedly installed on the upper surface of the rotor and rotates synchronously with the rotor, the grating is concentrically fixed on the edge region of the rotor, and the scale line direction of the grating is consistent with the radial direction of the rotor, so that the grating can be read by the photoelectric sensor array when the grating rotates with the rotor.

6. The laser precision angle rotation system constructed based on multi-layer PCB according to claim 1, characterized in that, The digital square wave signal is divided into A-phase and B-phase signals with a phase difference of 90 degrees, the A-phase and B-phase signals are input into a programmable logic device for four times frequency processing, that is, a counting pulse is triggered at the rising edge and the falling edge of each signal period, the pulse signal after four times frequency processing is accumulated and counted by a 32-bit counter, and the original rotation angle data of the rotor is calculated according to preset grating line numbers and pulse counting results. The original angle data is subjected to Kalman filtering treatment to output a high-precision angle value, which comprises: A state space model containing angle state and angular velocity state is established, the original angle data is input into the Kalman filter as measurement value, and the angle state is iteratively estimated through the prediction step and the update step; wherein, the prediction step predicts the current state based on the state of the previous time and the system dynamics model, and the update step corrects the predicted state combined with the current measurement value, and finally outputs the high-precision angle value after filtering out random noise and jitter.

7. The laser precision angle rotation system constructed based on multi-layer PCB according to claim 1, characterized in that, The main controller inputs the difference value between the angle instruction sequence and the high-precision angle value into the position PID controller, and calculates the speed instruction; the speed instruction is superimposed with the acceleration feedforward compensation amount and input into the field-oriented control module, the current in the three-phase static coordinate system is converted into the direct-axis and quadrature-axis current instructions in the rotating coordinate system through coordinate transformation, and the PI controller is used for closed-loop control of the direct-axis and quadrature-axis currents; The control output voltage vector generates three PWM signals through the space vector pulse width modulation algorithm, and the duty cycle of the PWM signal is determined according to the amplitude and phase of the voltage vector and input into the drive chip.

8. The laser precision angle rotation system constructed based on multi-layer PCB according to claim 1, characterized in that, Further comprising: A thermal management compensation system including temperature sensors distributed at key positions of the multi-layer PCB, the temperature sensors collect temperature data in real time and input into a thermal deformation model, the thermal deformation model predicts the thermal expansion trend of the structure combined with historical data and outputs a thermal deformation angle prediction value, and the thermal deformation angle prediction value is superimposed on the angle instruction sequence as feedforward compensation to realize real-time compensation.

9. The laser precision angle rotation system constructed based on multi-layer PCB according to claim 8, characterized in that, The main controller inputs the temperature data and the current coil current value into a pre-trained long short-term memory neural network model, and the model outputs a predicted thermal deformation angle value; the main controller superimposes the thermal deformation angle value as feedforward compensation value into the angle instruction sequence to realize real-time compensation of the angle deviation caused by rotor thermal expansion, and the system uses the newly added data to incrementally update the parameters of the long short-term memory neural network model during the idle period.

10. The laser precision angle rotation system constructed based on multi-layer PCB according to claim 1, characterized in that, Further comprising: A safety monitoring module for real-time monitoring of three-phase coil current, temperature at each key position, and difference between instruction angle and feedback angle, and triggering a protection mechanism to shut down the drive and report fault information when the monitored value exceeds the set threshold.

Images