Multispectral confocal collaborative optimization power equipment monitoring lens

Abstract

The invention provides a multispectral confocal collaborative optimization power equipment monitoring lens, belongs to the field of power equipment monitoring lenses, and is used for solving the problems of low confocal precision, poor multi-target adaptation, weak environmental adaptability, easy wear and control lag in the related technology. Modules such as a four-piece type confocal lens group, a confocal control unit, a porous phase change protection layer and a micro-nano light splitting-confocal adaptive array are integrated, an organic whole is formed through technical means such as material optimization, graded self-repairing, active prediction compensation and multi-parameter cooperative adaptation, and all the parts are complementary in function and are in cooperative linkage; the system realizes multispectral accurate confocal and multi-target parallel monitoring, adapts to an extreme environment, ensures long-acting stable operation, and meets the efficient monitoring requirement of power equipment.

Description

Technical Field

[0001] This application relates to the field of power equipment monitoring lenses, and more particularly to a multispectral confocal synergistic optimization power equipment monitoring lens, belonging to the G02B optical instrument category. Background Technology

[0002] As the scale of new energy power plants continues to expand, the monitoring of the operational status of power equipment places higher demands on the confocal accuracy, environmental adaptability, and long-term stability of lenses. Currently, power equipment monitoring mostly uses traditional optical lenses. Although some lenses have basic confocal functions, they lack a coordinated design for multispectral imaging and confocal accuracy.

[0003] In existing technologies, monitoring lenses generally suffer from core defects: the confocal structure design is simple, and the focus is prone to shift when switching between multiple spectra; lens components are easily corroded and worn by extreme environments such as salt spray and icing, and there is a lack of effective self-repair and protection coordination mechanisms; they are difficult to adapt to multi-target parallel monitoring scenarios, and the confocal misalignment problem of targets at different distances is prominent; the control logic is mostly passive deviation correction, and it does not fully integrate multiple environmental parameters for active prediction and compensation.

[0004] These shortcomings result in low monitoring accuracy, short service life, and limited application scenarios for existing lenses, making it impossible to meet the all-weather, high-precision, and long-term monitoring needs of large-scale new energy power plants, thus hindering the improvement of power equipment operation and maintenance efficiency. Summary of the Invention

[0005] This application provides a multispectral confocal collaborative optimization power equipment monitoring lens, which can solve the technical problems of insufficient confocal accuracy, easy wear, poor multi-target adaptation and weak environmental adaptability of existing lenses through integrated collaborative design.

[0006] This application provides a multispectral confocal synergistic optimization power equipment monitoring lens. It includes a four-element confocal lens group, a confocal control unit, and a porous phase change protective layer arranged sequentially along the optical axis. The four-element confocal lens group, from object side to image side, consists of a first lens with negative optical power, a second lens with positive optical power, an aperture stop, a third lens with positive optical power, and a fourth lens with negative optical power. The image-side surface of the second lens is coated with a confocal interference film. The first and fourth lenses integrate self-healing microcapsules. The four-element confocal lens group is equipped with distributed confocal monitoring probes, which are respectively arranged on the image side of the second lens, the object side of the third lens, and the image side of the fourth lens. The confocal control unit is linked with the distributed confocal monitoring probes and the four-element confocal lens group, configured to achieve confocal reference initialization and environmental deviation compensation. The porous phase change protective layer covers the front end of the lens barrel and does not conflict with the optical path of the four-element confocal lens group.

[0007] By adopting the above technical solutions, the four-piece confocal lens group and the confocal interference film constitute the basic confocal architecture. The self-healing microcapsule and the distributed monitoring probe realize the basic wear monitoring and repair. The confocal control unit links the core components to complete the benchmark initialization and deviation compensation. The porous phase change protective layer provides environmental protection. The integrated design ensures the confocal accuracy and basic stability from a structural perspective, solving the problems of the single and lack of coordination in the traditional lens confocal structure.

[0008] Furthermore, the first and fourth lenses are made of PMN-PT ceramic material, the self-healing microcapsules are silicon-based self-healing microcapsules, the silicon-based self-healing microcapsules are uniformly doped in the non-optically effective areas of the first and fourth lenses, the confocal interference film is a PDMS-TiO2 composite matrix, formed by alternating deposition of HfO2, SiO2 and TiO2, and the porous phase change protective layer is a porous PEG-graphene composite structure.

[0009] By adopting the above technical solutions, the material selection is precisely matched with the functions of the lens, film, and porous phase change protective layer. The silicon-based self-healing microcapsule and PMN-PT ceramic have good refractive index matching. The composite interference film has high transmittance. The PEG-graphene porous phase change protective layer takes into account both phase change anti-icing and structural stability, thus strengthening the material basis for confocal accuracy and environmental adaptability.

[0010] Furthermore, it also includes a micro / nano beam splitting-confocal adaptive array, which is deployed between the aperture and the third lens, and matches the confocal optical path of the four-element confocal lens group with the confocal optical path deviation within a preset range. The micro / nano beam splitting-confocal adaptive array is a multi-unit array structure, and each array unit includes a microlens, a micro filter and a MEMS confocal fine-tuner. The MEMS confocal fine-tuner is configured to perform independent displacement adjustment.

[0011] By adopting the above technical solution, the micro-nano beam splitting-confocal adaptive array expands the multi-target monitoring function. Each array unit can independently adapt to the target distance, and the MEMS confocal fine-tuner ensures the confocal accuracy of multiple targets, solving the problem of confocal inaccuracy in traditional lens multi-target monitoring.

[0012] Furthermore, the switching control of the micro-filter is related to the confocal deviation fed back by the distributed confocal monitoring probe, and the displacement of the MEMS confocal fine-tuner is dynamically adjusted based on the target distance and the confocal deviation. Moreover, the switching of the micro-filter, the displacement of the MEMS confocal fine-tuner, and the optical power adjustment of the four-element confocal lens group are performed synchronously.

[0013] By adopting the above technical solutions, the synergistic linkage of spectral switching, confocal fine-tuning and optical power adjustment can be achieved, reducing focus shift during multi-target monitoring and improving response speed and confocal consistency.

[0014] Furthermore, the confocal control unit is equipped with a three-dimensional confocal parameter library and a full-dimensional environmental confocal influence coefficient calculation model. The three-dimensional confocal parameter library is configured to store confocal calibration parameters corresponding to different focal lengths and imaging bands. The full-dimensional environmental confocal influence coefficient calculation model integrates parameters related to salt spray, rainfall, icing, air pressure, humidity and vibration, and fuses them with data from the distributed confocal monitoring probe in real time.

[0015] By adopting the above technical solutions, the three-dimensional confocal parameter library provides data support for accurate initialization, and the full-dimensional environment model realizes multi-parameter fusion compensation, solving the problems of single traditional control parameters and insufficient environmental adaptability.

[0016] Furthermore, the confocal control unit is also equipped with a confocal sharpness-spectral dual-target matching algorithm and a filter-MEMS confocal fine-tuner synchronous driving logic. The confocal sharpness-spectral dual-target matching algorithm dynamically corrects the target band based on the confocal deviation fed back by the distributed confocal monitoring probe and the image recognition sharpness.

[0017] By adopting the above technical solution, the algorithm achieves dual optimization of spectral matching and confocal accuracy, avoiding the contradiction of spectral adaptation but confocal inaccuracy, and improving the synergistic effect of target recognition and confocal monitoring.

[0018] Furthermore, the confocal control unit is also equipped with a fusion prediction model, a multi-field confocal deviation calculation model, and a second lens predictive compensation displacement algorithm. The fusion prediction model predicts confocal deviation based on historical data from the distributed confocal monitoring probe. The multi-field confocal deviation calculation model covers temperature change, environment, vibration, surface shape, and nonlinear related deviations. The second lens predictive compensation displacement algorithm introduces a focal length-related correction term.

[0019] By adopting the above technical solution, passive deviation correction is upgraded to active prediction compensation, which fully covers multiple interference factors, improves the confocal compensation accuracy under different focal lengths, and reduces the impact of hysteresis.

[0020] Furthermore, the self-healing microcapsule's triggering repair mechanism is a graded self-healing mechanism, including ultra-low power pre-repair and precise power emergency repair. The graded self-healing mechanism determines the repair level based on the confocal deviation and lens wear status fed back by the distributed confocal monitoring probe. During the repair process, the voltages of the first and fourth lenses, as well as the displacement of the MEMS confocal fine-tuner and the displacement of the second lens are adjusted simultaneously.

[0021] By adopting the above technical solution, the graded self-repair mechanism adapts to different degrees of wear, and the repair and confocal compensation are carried out simultaneously, avoiding the impact of the repair process on the monitoring accuracy and extending the lens service life.

[0022] Furthermore, the confocal control unit is configured with a confocal priority hard constraint threshold, a module parallel execution timing, and a three-level compensation circuit breaker mechanism. The three-level compensation circuit breaker mechanism is executed in stages in the order of MEMS fine-tuning, second lens displacement, and confocal interference film voltage adjustment.

[0023] By adopting the above technical solutions, a collaborative rule prioritizing confocal accuracy is established, module parallel execution improves efficiency, and a three-level compensation circuit breaker mechanism ensures confocal stability under extreme conditions, thus preventing system failure.

[0024] Furthermore, it also includes a multi-parameter fusion sensor array, which includes a vibration frequency domain sensor, a barometric pressure sensor, and a humidity sensor. The confocal control unit is also equipped with a porous phase change protective layer-confocal optical path compensation logic, which dynamically corrects the optical power of the four-piece confocal lens group and the adaptation parameters of the porous phase change protective layer based on the data from the multi-parameter fusion sensor array.

[0025] By adopting the above technical solutions, the multi-parameter sensor array expands the environmental perception dimension, and the collaborative compensation logic of the porous phase change protective layer and confocal optical path enhances the adaptability to extreme environments, achieving linkage optimization of protection and confocal accuracy.

[0026] In summary, this application has at least the following beneficial effects:

[0027] It provides an integrated co-focus collaborative monitoring solution to achieve high-precision, long-term, and multi-scenario adaptable monitoring of power equipment;

[0028] Precise matching of materials and structure enhances confocal stability and environmental resistance to erosion.

[0029] The combination of predictive compensation and tiered self-healing extends service life and ensures continuous monitoring.

[0030] It should be understood that the description in the Summary Section is not intended to limit the key or essential features of the embodiments of this application, nor is it intended to restrict the scope of this application. Other features of this application will become readily apparent from the following description. Attached Figure Description

[0031] The above and other features, advantages, and aspects of the embodiments of this application will become more apparent from the accompanying drawings and the following detailed description. In the drawings, the same or similar reference numerals denote the same or similar elements, wherein:

[0032] Figure 1 A schematic diagram of a multispectral confocal collaborative optimization power equipment monitoring lens is shown in an embodiment of this application.

[0033] Figure 2A schematic diagram of the four-element confocal lens group structure in an embodiment of this application is shown.

[0034] Figure 3 A schematic diagram of the confocal control unit functional module in an embodiment of this application is shown.

[0035] Figure 4 A schematic diagram of the micro / nano beam splitter-confocal adaptive array in an embodiment of this application is shown.

[0036] Figure 5 A schematic diagram illustrating the principle of distributed monitoring and sensing linkage in an embodiment of this application is shown. Detailed Implementation

[0037] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0038] Furthermore, the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0039] This application provides a multispectral confocal collaborative optimization power equipment monitoring lens, which realizes multispectral precise confocal and multi-target parallel monitoring, adapts to extreme environments, has self-healing and long-lasting characteristics and active prediction and compensation functions, and greatly improves monitoring reliability and operation and maintenance efficiency.

[0040] This application discloses a multispectral confocal collaborative optimization power equipment monitoring lens.

[0041] Reference Figures 1-5 The lens includes a four-element confocal lens group, a confocal control unit, a porous phase change protective layer, a micro-nano beam splitting-confocal adaptive array, and a multi-parameter fusion sensor array.

[0042] The four-element confocal lens group consists of, along the optical axis from object to image, a first lens with negative optical power, a second lens with positive optical power, an aperture, a third lens with positive optical power, and a fourth lens with negative optical power. All four lenses employ a circular optical lens structure, have the same effective aperture, and a coaxiality ≤ φ0.003mm. The center thickness is designed to match the confocal optical path. The first and fourth lenses are biconcave, while the second and third lenses are biconvex, used to achieve basic multispectral confocal imaging. Each lens is fixed to the inner wall of the lens barrel via a carbon fiber flexible hinge bracket. One end of the bracket is fastened to the lens barrel using a titanium alloy threaded connector (thread precision M2×0.25, tightening torque 5N・cm), while the other end is fitted to the non-optical area of ​​the lens edge using an elastic clamp. The bracket stiffness is ≥20N / μm, effectively suppressing lens displacement caused by vibration and ensuring confocal stability.

[0043] The image-side surface of the second lens is coated with a confocal interference film. This film is a PDMS-TiO2 composite matrix, formed by the alternating deposition of HfO2, SiO2, and TiO2 in a periodic pattern of "HfO2 (20nm) - SiO2 (30nm) - TiO2 (15nm)", with a total thickness of 1.4μm and a transmittance ≥99.9%. The design meets the multi-band confocal conditions of 400nm-1700nm, and the optical path difference for different bands satisfies the formula:

[0044]

[0045] in To ensure multispectral focus deviation, the center wavelength of the imaging band is used. .

[0046] The first and fourth lenses integrate self-healing microcapsules, which are silicon-based and have a particle size range of [missing information]. Doping amount Uniformly dispersed in the non-optically effective area (edge ​​width) during the lens forming process Its refractive index after curing Refractive index matching error with PMN-PT ceramic material This avoids introducing additional optical path difference. When a crack width appears on the lens surface... Or wear and tear can cause a decrease in transmittance. At this time, the microcapsules rupture to release the repair agent, which solidifies at ambient temperature to form a dense repair layer. During the repair process, lens distortion occurs. The first and fourth lenses are made of PMN-PT electrostrictive ceramic material. This material's radius of curvature can be adjusted by applying voltage, thereby changing the optical power. The relationship between the optical power adjustment range and the output voltage of the confocal control unit satisfies the following:

[0047]

[0048] in The initial optical power, This is the voltage-optical power coefficient. The output voltage is provided to the confocal control unit to ensure the balance of the confocal optical path during zooming.

[0049] The self-healing microcapsules are silicon-based composite materials with polydimethylsiloxane (PDMS) as the capsule wall and a mixture of hydroxyl-terminated polysiloxane (HO-PDMS) and titanate coupling agent (KH-550) as the core material for repair. The capsule wall thickness is 0.5-1 μm, and the mass ratio of HO-PDMS to KH-550 in the core material is 95:5. When the microcapsules rupture due to cracks or wear on the lens surface, the repair agent undergoes a polycondensation crosslinking reaction under exposure to ambient moisture, generating a polysiloxane elastomer with a network structure. The cured elastomer has a refractive index n=2.59, and the refractive index matching error with the PMN-PT ceramic matrix is ​​≤0.002, thus repairing the damage while avoiding the introduction of additional optical path difference.

[0050] The four-element confocal lens assembly is equipped with a distributed confocal monitoring probe, which is a Shack-Hartmann miniature wavefront sensor. This probe is fixed to the image side of the second lens, the object side of the third lens, and the image side of the fourth lens via miniature adjustment mounts. The adjustment mounts support… Three-dimensional fine-tuning, after installation, the probe's detection direction is parallel to the optical axis. The sampling frequency is 50Hz, used to collect wavefront errors at various locations in real time. The directly measured wavefront error is defined by the system as total focal deviation (TFO). This is the core input for all subsequent control and compensation logic. To accurately trace the source of the deviation and achieve predictive compensation, the confocal control unit calls the "multiphysics analytical model of confocal deviation," which decomposes the deviation into temperature-varying deviations. Environmental deviation Vibration deviation Surface shape deviation Nonlinear deviation Five categories, each calculated using its corresponding sub-model, are combined to form the total deviation:

[0051]

[0052] in ( , (The change in temperature) With vibration frequency Related ( hour This system covers temperature variation, environment, vibration, surface shape, and nonlinear related deviations, enabling a comprehensive analysis of the sources of deviations. The collected data is transmitted to the confocal control unit in real time, providing a basis for confocal compensation.

[0053] Surface deviation ΔWs refers to the deviation between the actual surface of each lens in a four-element confocal lens group and the ideal design surface. It is calculated using the Zernike polynomial decomposition method, and the specific formula is as follows: ,in, The coefficients of the i-th Zernike polynomial are obtained by fitting the lens surface shape after measuring it with an interferometer. In this application, the first 8 Zernike polynomials are used, and the fitting error is ≤0.0001mm. For standard Zernike polynomials ( For normalized radial coordinates, (in angular coordinates) The value range is 0~0.0005mm.

[0054] Nonlinear deviation This refers to the optical path deviation caused by the nonlinearity of the electrostrictive properties of PMN-PT ceramic material, and its relationship with the driving voltage U of the first and fourth lenses is as follows: ,in, (The calibration was obtained through voltage-photon power characteristics experiments of PMN-PT ceramics, with an experimental voltage range of 0~10V and a calibration error of ≤5%). The value range is 0~0.0002mm.

[0055] The confocal control unit uses an FPGA+ARM heterogeneous architecture as its core hardware platform. The FPGA chip, model XC7K325T, is responsible for real-time data acquisition and drive signal generation, while the ARM chip, model Cortex-A9, handles complex algorithm calculations and parameter management. The two interact via an AXI4 bus with a transmission rate ≥1Gbps. This unit establishes communication with the distributed confocal monitoring probe via an RS485 interface (communication baud rate 115200bps, data delay ≤1ms). It is linked with the electrostriction drive circuit of the four-piece confocal lens group through a D / A conversion module (16-bit accuracy, output voltage range 0-10V) to achieve confocal reference initialization and environmental deviation compensation. During the initialization phase, the system calls data from the 3D confocal parameter library and adjusts the voltages of the first and fourth lenses and the displacement of the second lens to ensure that the multi-band focal overlap meets the reference requirement of ≤λ / 5. The initialization time is ≤200ms.

[0056] The confocal control unit is equipped with a three-dimensional confocal parameter library, a full-dimensional environmental confocal influence coefficient calculation model, a confocal sharpness-spectral dual-target matching algorithm, a filter-MEMS confocal fine-tuner synchronous driving logic, a fusion prediction model, a multi-field confocal deviation calculation model, a second lens predictive compensation displacement algorithm, a confocal priority hard constraint threshold, a module parallel execution timing, a three-level compensation fuse mechanism, and a porous phase change protective layer-confocal optical path compensation logic.

[0057] The synchronous drive logic of the filter-MEMS confocal tuner is implemented by the FPGA module of the confocal control unit, employing a precise timing control mechanism based on a hardware timer. This logic comprises three synchronization phases: timing alignment, instruction issuance, and execution verification. In the timing alignment phase, the FPGA's internal counter generates a reference timestamp t0 upon receiving confocal deviation data. In the instruction issuance phase, filter switching instructions, MEMS displacement instructions, and lens group optical power adjustment instructions are issued in parallel with delays of t1=0.1ms, t2=0.15ms, and t3=0.2ms respectively, using t0 as the reference, to compensate for the response time differences of each execution device. In the execution verification phase, the synchronization execution result is verified by reading back the completion flag bits of each device's status register. If any device fails to complete within a timeout threshold of 5ms, a synchronization exception interrupt is triggered, and the drive sequence is reinitialized. This synchronization logic ensures precise time coordination of the three key actions: spectral switching, focus adjustment, and optical system reconstruction, avoiding momentary defocusing due to timing misalignment. The delay parameters t1=0.1ms, t2=0.15ms, and t3=0.2ms are determined based on the measured response characteristics of each actuator: the mechanical response time of the micro-filter switching mechanism is 0.3ms, and the instruction preprocessing needs to be issued 0.2ms in advance; the electrical response time of the MEMS confocal fine-tuner is 0.25ms, and it needs to be triggered 0.1ms in advance; the piezoelectric ceramic response time of the lens group optical power adjustment is 0.35ms, and it needs to be started 0.15ms in advance. Each delay parameter is calculated through time alignment to ensure that all three reach the specified state simultaneously at the target time.

[0058] The 3D confocal parameter library is built on an SQLite database, with storage dimensions of (focal length f, band λ, confocal reference value). driving voltage Compensation displacement The focal length range is 50-200mm, and the wavelength range is 400-1700nm. A set of calibration parameters is set every 5mm focal length and 20nm wavelength. The parameters are obtained through offline calibration experiments with a calibration error of ≤0.0002mm. It supports fast query by dual keywords of "focal length + wavelength" with a query response time of ≤50μs. It is configured to store confocal calibration parameters corresponding to different focal lengths and imaging wavelengths.

[0059] The comprehensive environmental co-focusing influence coefficient calculation model is constructed using multiple linear regression. First, influence coefficients are assigned to six environmental parameters: salt spray (S), precipitation (R), icing (I), air pressure (P), humidity (H), and vibration (V). - ,coefficient - The values ​​were determined through orthogonal experiments, specifically: in a controlled environment simulation chamber, a single environmental parameter was changed sequentially while keeping other parameters at standard values. , The baseline confocal deviation caused by this parameter under various conditions is recorded using a distributed confocal monitoring probe. Finally, through normalization (making Σω=1), we obtain... (salt spray) (Rainfall) (freeze), (Air pressure) (humidity), (Vibration). The overall environmental impact deviation is then calculated using the following formula:

[0060]

[0061] in For standard environmental parameters, the model is fused with real-time data acquired by the distributed confocal monitoring probe, with the fusion weights based on "real-time data percentage". Model prediction accounts for "Dynamic allocation and real-time fusion of data from distributed confocal monitoring probes enable precise quantification of environmental deviations."

[0062] The confocal sharpness-spectral dual-target matching algorithm uses the image Tenengrad gradient function as the sharpness evaluation index T, combined with confocal deviation. Construct a bi-objective optimization function:

[0063]

[0064] in Weighting coefficients The algorithm searches for the optimal band based on the confocal deviation feedback from the distributed confocal monitoring probe and the image recognition clarity, using the golden section method. Dynamically correct the target band, and the corresponding confocal deviation of the corrected band. .

[0065] The synchronous drive logic for the filter-MEMS confocal tuner uses an FPGA to generate synchronous pulse signals (pulse width). (Period 1ms) to ensure that the filter switching voltage is synchronized with the rising edge of the MEMS drive signal, and the filter switching response time. MEMS confocal fine-tuner displacement response time The time difference between the two and the lens group's optical power adjustment To ensure synchronization.

[0066] The fusion prediction model is an LSTM+CNN hybrid network structure implemented based on the PyTorch framework. Its input layer has a dimension of 10 (corresponding to historical confocal deviation data at 10 time points within the past 200ms), and its output layer has a dimension of 1 (corresponding to the predicted confocal deviation value ΔW_pred for the next 50ms). The LSTM layer consists of 3 layers with 64 hidden units, used to extract long-term dependencies in the time series. The CNN layer includes two one-dimensional convolutional layers (with kernel sizes of 3 and 5, and 32 channels each) and one max-pooling layer (with a kernel size of 2), used to extract local spatial features from the data. The model uses mean squared error (MSE) as the loss function and is trained to convergence on over 100,000 sets of historical confocal data using the Adam optimizer, achieving a final prediction error ≤0.0001 mm.

[0067] The second lens predictive compensation displacement algorithm introduces a focal length quadratic term correction to compensate for displacement. Deviation from prediction Current focal length The relationship is:

[0068]

[0069] Among them, the proportionality coefficient The coefficient of the quadratic term of focal length was obtained through linear regression analysis of historical compensation data (covering a focal length range of 50-200mm). Its value is determined by fitting the nonlinear confocal deviation curve caused by material dispersion at different focal lengths. After introducing a focal length-related correction term, the compensation accuracy is improved by 40% compared to the linear algorithm.

[0070] The confocal priority hard constraint threshold is set to ≤0.0008mm. When the real-time confocal deviation exceeds this threshold, the system triggers the highest priority interrupt, suspends non-core tasks (such as data storage), and prioritizes the execution of compensation logic. The parallel execution timing of the modules is managed by a state machine. The three core modules—confocal monitoring, deviation calculation, and compensation drive—execute in parallel according to the cycle of "acquisition (10ms) → calculation (5ms) → drive (5ms)". The execution cycle of non-core modules (such as self-healing status monitoring) is 100ms, ensuring that resources are preferentially allocated to confocal control.

[0071] The parallel execution timing of the modules is implemented using a five-state finite state machine (FSM), and the state definitions and transition conditions are as follows:

[0072] S0_IDLE (Idle State): The initial state of the system, waiting for an external trigger signal.

[0073] S1_ACQ (Data Acquisition Status): Activates the distributed confocal monitoring probe and multi-parameter fusion sensor array, with an acquisition cycle of 10ms. Transition condition: Acquisition completion flag is set.

[0074] S2_CALC (Bias Calculation Status): Parallel execution of full-dimensional environmental confocal influence coefficient calculation, multi-field confocal bias calculation, and fusion prediction model inference, with a calculation cycle of 5ms. Transition condition: All calculation tasks are completed.

[0075] S3_COMP (Compensation Drive State): Based on the three-level compensation circuit breaker mechanism, compensation actions are executed according to priority, with a drive cycle of 5ms. Transition condition: Compensation completed or timeout.

[0076] S4_MONITOR (Monitoring Status): Performs non-core tasks such as self-healing status monitoring and system health assessment, with a cycle of 100ms. Transition condition: Monitoring completes or high-priority task is interrupted.

[0077] The state machine is managed by the ARM core of the confocal control unit through a priority preemptive scheduler. When the confocal deviation exceeds the hard constraint threshold, the highest priority interrupt is immediately triggered, forcibly jumping to the S3_COMP state. The context switching time between each state is ≤50μs to ensure real-time requirements. The determination of the state switching time ≤50μs is based on the clock cycle analysis of the FPGA hardware logic: the system main clock frequency is 100MHz, each state machine state encoding occupies 4 clock cycles, state decoding and condition judgment occupy 6 clock cycles, and context saving and restoration occupy 40 clock cycles, totaling 50 clock cycles corresponding to a 50μs switching time. This value was verified and confirmed in actual FPGA deployment using a logic analyzer.

[0078] The three-level compensation and circuit breaker mechanism executes in stages, following the sequence of MEMS fine-tuning, second lens displacement, and confocal interference film voltage adjustment. The first-level compensation (MEMS fine-tuning) is triggered when ΔW ≤ 0.0005 mm, with a fine-tuning range of ±10 μm and an accuracy of ±0.001 μm. When ΔW > 0.0005 mm, the second-level compensation (second lens displacement) is triggered, driven by a piezoelectric ceramic actuator, with a displacement range of ±50 μm. If ΔW > 0.001 mm, the third-level compensation (confocal interference film voltage adjustment) is triggered, with an adjustment voltage of 0-5V. The relationship between the change in optical path length and the voltage is ΔL = 0.0002U. Subsequent operations stop when any first-level compensation brings the deviation back within the threshold. If the deviation still exceeds the limit after third-level compensation, a system alarm is triggered.

[0079] The porous phase change protective layer-confocal optical path compensation logic establishes the relationship between the volume expansion rate η of the porous phase change protective layer and the optical path change. relational model = ( , The coefficient is the expansion coefficient of the protective layer versus the optical path conversion factor. This coefficient is determined based on the optical properties and geometry of the porous phase change protective layer material. Substituting the thickness of the porous phase change protective layer d=1.5mm and the effective refractive index... and air refractive index The theoretical value was calculated. After being calibrated and corrected to 0.001 mm / % by environmental temperature change experiments to cover the nonlinear expansion effect of the material), the optical path compensation amount Δd is calculated by combining real-time data from the multi-parameter fusion sensor array. Then, the optical power is corrected by adjusting the voltages of the first and fourth lenses to bring the total optical path deviation back to the allowable range. The phase change protective layer-confocal optical path compensation logic establishes a hardware association with the voltage drive circuit of the four-piece confocal lens group through the dedicated analog output module (AO-16B, 16-bit precision, output range ±10V) of the confocal control unit. The specific implementation process is as follows: After the logic operation unit calculates the optical path compensation amount Δd based on the real-time data of the multi-parameter fusion sensor array, it converts it into the drive voltage through the following mapping relationship:

[0080]

[0081] in This is the optical path-voltage mapping coefficient, which was determined through photoelectric characteristic calibration experiments of the lens group. Driving voltage. The output from the AO-16B module is sent to the piezoelectric ceramic drivers of the first and fourth lenses. The drivers have an input impedance of 1MΩ and a response bandwidth of DC-1kHz, ensuring fast and accurate transmission of the compensation signal. Simultaneously, the logic unit sends an enable signal to the temperature control circuit of the porous phase change protective layer via a digital I / O interface (optically isolated, response time ≤10μs). When the ambient temperature is below 0℃, the active heat preservation function of the phase change material is activated.

[0082] A porous phase change protective layer covers the front end of the lens barrel, which has an annular stepped surface (step width 5mm, depth 2mm). The porous phase change protective layer adopts a circular sheet structure with an outer diameter consistent with the inner diameter of the front end of the lens barrel (φ50mm) and an inner diameter matching the effective aperture of the first lens (φ30mm). It is bonded and fixed to the stepped surface with an epoxy-based high-temperature resistant adhesive (bonding strength ≥5MPa, temperature range -40℃~80℃). After bonding, the coaxiality of the porous phase change protective layer with the optical axis of the four-element confocal lens group is ≤φ0.005mm, and the surface flatness is ≤0.001mm, ensuring no optical path conflict with the four-element confocal lens group. The porous phase change protective layer is designed to be 1.5 mm thick, with the thickness tolerance of the optically effective area (within an inner diameter of φ30 mm) controlled within ±0.002 mm to avoid introducing additional optical path deviations and provide protection in extreme environments. The porous phase change protective layer is a porous PEG-graphene composite structure, with PEG (polyethylene glycol, molecular weight 4000) as the phase change matrix and graphene as the thermally conductive reinforcing phase. The mass ratio of the two is PEG:graphene = 97:3. It is prepared by freeze-drying to form a three-dimensional interconnected porous network structure with a pore size distribution of 50-100 μm and a porosity of 65%~70%. This ensures both the energy storage space for the phase change material and maintains structural strength (compressive strength ≥2 MPa).

[0083] PEG, as the core component of the phase change process, has a phase change temperature range set at 0-5℃, which precisely covers the temperature range prone to icing in power equipment monitoring scenarios. With a latent heat of phase change ≥180J / g, when the ambient temperature is below 0℃, PEG undergoes a solid-liquid phase change, releasing latent heat and preventing icing on the surface of the porous phase change protective layer. When the temperature rises above 5℃, it absorbs heat and returns to a solid state, completing the phase change cycle. The introduction of graphene increases the thermal conductivity of the porous phase change protective layer to 1.2W / (m・K) (6 times higher than pure PEG), ensuring rapid heat conduction during the phase change and preventing structural deformation caused by uneven local temperature distribution. The volume expansion rate of the porous phase change protective layer follows a linear relationship with temperature change, as shown in the following formula:

[0084]

[0085] in for Reference volume expansion rate at time ( ), Coefficient of thermal expansion ( ), For real-time ambient temperature, Reference temperature This formula can be used to accurately calculate the volume change of porous phase change protective layers at different temperatures, including their maximum volume expansion rate. This is to avoid deformation of the lens barrel due to expansion stress.

[0086] This porous phase change protective layer also exhibits excellent environmental resistance, passing salt spray tests ( After continuous spraying of the solution for 96 hours, no surface corrosion was observed, and the transmittance remained unchanged. Rainfall test (rainfall amount) Water absorption rate after 24 hours Furthermore, its phase change performance remains undiminished. It is linked with the porous phase change protective layer of the confocal control unit—the confocal optical path compensation logic—and the temperature sensor in the multi-parameter fusion sensor array collects the surface temperature of the porous phase change protective layer in real time. Substitute into the above formula for volume expansion rate to calculate Then, the optical path deviation introduced by the porous phase transition protective layer is derived using the optical path change model:

[0087]

[0088] in The thickness of the porous phase change protective layer is 1.5 mm. The effective refractive index of the porous phase change protective layer is 1.45. The confocal control unit is based on... Dynamically adjust the driving voltages of the first and fourth lenses to bring the total optical path deviation back to normal. Within the permissible range, it achieves synergistic protection of protective functions and confocal accuracy.

[0089] The micro / nano beam-confocal adaptive array is deployed between the aperture stop and the third lens. It is fixed to the inner wall of the lens barrel via a ceramic-based PCB board (40mm×40mm×2mm, high temperature resistance ≥120℃) and positioning pins. The clearance between the positioning pins and the pre-drilled holes on the PCB board is ≤0.002mm. After installation, the coaxiality between the array center and the optical axis of the four-element confocal lens group is ≤φ0.003mm. Its installation position along the optical axis is calibrated using a dial indicator to ensure that it matches the confocal optical path of the four-element confocal lens group and that the confocal optical path deviation is within a preset range (≤0.0003mm). The optical path matching relationship satisfies the formula:

[0090]

[0091] in The optical path from the array to the image plane, The optical path lengths of the first and second lenses are respectively. The optical path length from the aperture stop to the second lens is used to achieve parallel confocal imaging of multiple targets; the micro / nano beam-confocal adaptive array is... Multi-unit array structure, unit spacing 3mm, effective field of view coverage of the array Matching the effective aperture of the first lens, each array unit is arranged in a square (3mm on each side) and includes a microlens, a micro filter, and a MEMS confocal fine tuner. The three are integrated sequentially along the optical axis into the unit base. The base is made of silicon-based material and integrally formed by MEMS technology to ensure a compact structure and precise positioning.

[0092] The microlens has a plano-convex lens structure and is made of quartz glass (refractive index 100%). transmittance With a focal length of 5mm and an effective aperture of 2.5mm, it is cured by UV-curing adhesive (bonding strength). Refractive index matching error It is bonded and fixed to the stepped surface of the unit base, with its convex surface facing the object, and is used to focus the incident light onto the surface of the microfilter. The microfilter is an electro-controlled liquid crystal filter (size...). Integrated within the middle layer of the base, it connects to the drive circuit via conductive pins on both sides, enabling... Multi-band switching within the range, half bandwidth of each band Switch response time The filter surface is coated with an anti-reflection film, and the transmittance is... The MEMS confocal fine-tuner is an electrostatically driven comb structure, consisting of a fixed electrode, a movable electrode, and an elastic beam. The movable electrode is connected to a micro-platform that carries the filter, and the elastic beam has a high stiffness. It can achieve the direction along the optical axis. Displacement adjustment, adjustment precision Drive voltage range displacement resolution The MEMS confocal fine-tuner is configured for independent displacement adjustment, and its displacement feedback is achieved through an integrated miniature capacitive sensor. .

[0093] The switching control of the microfilter is related to the confocal deviation feedback from the distributed confocal monitoring probe, and a confocal deviation threshold is set. th When the distributed confocal monitoring probe collects data... At this time, the confocal control unit outputs a switching signal and calculates the filter drive voltage corresponding to the optimal band using the following formula:

[0094]

[0095] in The reference band driving voltage, The deviation-voltage conversion factor ensures that the wavelength band corresponding to the filter after switching matches the confocal requirements. The displacement of the MEMS confocal fine-tuner is dynamically adjusted based on the target distance and the confocal deviation. Obtained through image ranging algorithm ( ), reference distance The displacement calculation model is as follows: (The reference focusing distance for the array is given.)

[0096]

[0097] in The distance-displacement coefficient. The deviation-displacement coefficient is used to achieve dual compensation for target distance and confocal deviation through this model.

[0098] Furthermore, the switching of the micro-filters, the displacement of the MEMS confocal fine-tuner, and the adjustment of the optical power of the four-element confocal lens group are executed synchronously. The synchronous control is achieved by the FPGA module of the confocal control unit generating a synchronous pulse signal (pulse frequency 100Hz, pulse width...). The filter switching signal, MEMS drive signal, and lens group optical power adjustment signal are all triggered based on this synchronization pulse, and the triggering time difference among the three is... To ensure consistent and coordinated confocal movements of all units during multi-target imaging, and to avoid focus shifts caused by timing misalignments, the synchronous execution timing must satisfy the formula:

[0099]

[0100] in The timing of the synchronization pulse trigger. To fix the delay and ensure the continuity and accuracy of the entire confocal adjustment process.

[0101] The self-healing microcapsule's triggering and repair mechanism is a tiered self-healing mechanism, including ultra-low power pre-repair and precise power emergency repair. The repair trigger signal is generated by the confocal control unit based on multi-source data. The lens wear status is determined by combining wavefront error data collected by a distributed confocal monitoring probe with data from a miniature transmittance sensor integrated into the inner wall of the lens barrel (measurement range 90%-100%, accuracy ±0.1%). The transmittance sensor collects the transmitted light intensity from the surfaces of the first and fourth lenses via fiber optic coupling and calculates the transmittance T. The wear degree quantification formula is:

[0102]

[0103] in The initial transmittance of the lens ( ), Crack width identified by the distributed confocal monitoring probe (unit: ), The crack influence coefficient is the graded self-healing mechanism based on the confocal deviation fed back by the distributed confocal monitoring probe. Lens wear condition Determine the repair level and set two threshold levels: when and When, trigger ultra-low power pre-repair; when or At that time, precise power emergency repair is triggered.

[0104] Ultra-low power pre-repair employs resistance heating-assisted curing; miniature heating resistors (power) are integrated into the non-optical areas at the edges of the first and fourth lenses. heating temperature The confocal control unit outputs a PWM drive signal (duty cycle). The heating resistor is controlled to allow the repair agent released from the silicon-based self-healing microcapsules to slowly cure under gentle conditions. The curing time... Lens temperature fluctuations during repair To avoid high temperatures affecting confocal performance, the heating resistor power is increased to [a specific value] during precise power emergency repairs. Heating temperature controlled at Simultaneously, by outputting an excitation voltage through the confocal control unit, the flow and cross-linking of the repair agent are accelerated, shortening the curing time to [missing information]. Shore hardness after the repair agent has cured The bonding strength with PMN-PT ceramic substrate This ensures the stability of the lens structure after repair.

[0105] During the repair process, the voltages of the first and fourth lenses, as well as the displacement of the MEMS confocal fine-tuner and the second lens, are adjusted simultaneously. The adjustment amount is based on real-time dynamic calculation of the confocal deviation, and the voltage adjustment formula is as follows:

[0106]

[0107] in This is the voltage-deviation adjustment coefficient. The distributed confocal monitoring probe provides real-time feedback on the confocal deviation; the MEMS confocal fine-tuning device's displacement adjustment, combined with target distance compensation and deviation correction compensation, is calculated using the following formula:

[0108]

[0109] in This is the displacement compensation amount caused by changes in the target distance. The displacement-deviation adjustment coefficient; the displacement of the second lens is controlled by a piezoelectric ceramic actuator (displacement range). precision To achieve this, the formula is adjusted as follows:

[0110]

[0111] in The displacement-deviation adjustment coefficient is used to coordinate all adjustment actions through the synchronous drive logic of the confocal control unit, ensuring that the confocal deviation is always controlled within a certain range during the repair process. Within the specified range, after the repair is completed, the system will automatically call the three-dimensional confocal parameter library for calibration and restore the accuracy to the reference confocal value.

[0112] The multi-parameter fusion sensor array includes a vibration frequency domain sensor, a barometric pressure sensor, and a humidity sensor. All three are surface-mount packaged (10mm × 8mm × 3mm) and secured to a sensor mounting base on the inner wall of the microscope tube using M3 threaded fasteners. The mounting base is integrally formed with the microscope tube, achieving a positioning accuracy of ≤ ±0.1mm. The mounting base integrating the humidity and barometric pressure sensors features a semi-open dustproof structure: three 0.5mm diameter vent holes are formed on the side wall of the mounting base (each vent is lined with a PTFE dustproof and breathable membrane with a permeability ≥80%, effectively isolating salt spray and dust), allowing the sensors to access external airflow. The entire mounting base is sealed to the inner wall of the microscope tube using a rubber sealing ring (IP65 sealing rating), preventing extreme environments from directly penetrating the microscope tube. The humidity sensor employs a temperature compensation algorithm to eliminate the influence of temperature changes in the porous phase change protective layer. The compensation formula is as follows: ,in, (Calibrated through high and low temperature experiments). The real-time temperature of the porous phase change protective layer is collected by an integrated miniature temperature sensor; meanwhile, the humidity sensor's measurement frequency is set to 1Hz (lower than the confocal control cycle), and the measurement stability is further improved by averaging multiple samples.

[0113] The vibration frequency domain sensor is deployed in the middle section of the lens barrel near the third lens. It is a piezoelectric accelerometer (measurement range 0-5g, frequency response 10-1000Hz, sensitivity 100mV / g, measurement error ≤±2%). Its sensitive axis is parallel to the optical axis of the four-element confocal lens group and is used to collect the frequency and amplitude of the lens barrel vibration. The barometric pressure sensor (measurement range 80-120kPa, accuracy ±0.1kPa, response time ≤5ms) and the humidity sensor (measurement range 0-100%RH, accuracy ±2%RH, response time ≤8ms) are integrated into the same mounting base and deployed at the front end of the lens barrel near the inner side of the porous phase change protective layer. This avoids direct exposure to extreme environments and ensures that the collected data can reflect the real environmental conditions around the porous phase change protective layer, thereby expanding the dimensions of environmental parameter perception.

[0114] The sensor array establishes linkage with the ARM chip of the confocal control unit via an I2C communication bus, with a communication baud rate of 400kHz and a data acquisition cycle of 100ms. The acquired data is packaged and transmitted in the format of "vibration frequency f_v-vibration amplitude A_v-air pressure P-humidity H", with a transmission delay of ≤1ms. The confocal control unit has a built-in sensor data verification algorithm, which ensures data integrity through CRC32 verification. If the verification fails, it triggers re-acquisition. The multi-parameter fusion sensor array is linked with the confocal control unit.

[0115] The confocal control unit dynamically corrects the optical power of the four-element confocal lens group and the adaptation parameters of the porous phase change protective layer based on data from a multi-parameter fusion sensor array. The correction logic is executed in two steps: the first step is to quantify the influence of environmental parameters on the confocal optical path. The vibration parameters collected by the vibration frequency domain sensor are used to calculate the optical path deviation caused by vibration using the following formula:

[0116]

[0117] in The vibration-optical path conversion coefficient, For time; air pressure and humidity indirectly change the optical path by affecting the refractive index of the lens material. The refractive index correction formula is:

[0118]

[0119] in The refractive index of the lens under standard conditions. The refractive index correction factor is used to derive the optical path deviation:

[0120]

[0121] in This represents the average thickness of the lens.

[0122] The second step is to correct the optical power and the adaptation parameters of the porous phase change protective layer. The optical power correction is achieved by adjusting the driving voltage of the first and fourth lenses. The formula for the voltage correction is:

[0123]

[0124] in This is the optical path-voltage correction factor, ensuring the total optical path deviation after correction. The adaptation parameter correction for the porous phase change protective layer focuses on the dynamic compensation of the volume expansion rate, and the expansion rate calculation model is corrected based on humidity and air pressure data.

[0125]

[0126] in, and The correction coefficients for the expansion rate of the protective layer due to air pressure and humidity are determined through multivariate environmental adaptability experiments: In an environmental simulation chamber, the air pressure (gradient change from 80-120 kPa) and humidity (gradient change from 20%-90% RH) were systematically varied. The dimensional change rate of the porous phase change protective layer under different (P, H) conditions was accurately measured using laser interferometry. The air pressure influence coefficient was obtained by surface fitting of the experimental data using the least squares method. Humidity Influence Coefficient The fitting residual is ≤5%, meeting engineering accuracy requirements. The confocal control unit is based on the corrected expansion rate. The parameters of the porous phase change protective layer-confocal optical path compensation logic are adjusted to ensure that changes in the volume of the porous phase change protective layer do not introduce optical path deviations beyond the allowable range, thereby achieving coordinated adaptation of environmental parameters with confocal accuracy and protective performance.

[0127] The entire process of this monitoring lens from power-on to stable operation can be divided into four stages in chronological order:

[0128] 1. System initialization phase (0-200ms):

[0129] Power-on self-test: Hardware module diagnostics, memory verification, sensor zero-point calibration

[0130] Parameter loading: Loading the 3D confocal parameter library from non-volatile memory into runtime memory

[0131] Benchmark establishment: Based on the current environmental parameters, call the full-dimensional environmental model to set the initial confocal benchmark.

[0132] Device reset: filter array returns to zero, MEMS confocal tuner returns to reference point, lens group voltage initializes.

[0133] 2. Multi-target recognition and parameter preset stage (200-500ms):

[0134] Scene scanning: Rapid scanning and monitoring of the field of view via micro / nano beam splitting-confocal adaptive array

[0135] Target Extraction: Locating Key Monitoring Parts of Power Equipment Based on Image Recognition Algorithms

[0136] Parameter pre-calculation: Based on the target distance and environmental conditions, the optimal configuration of each array element is pre-calculated.

[0137] 3. Steady-state monitoring and adaptive compensation phase (after 500ms):

[0138] Parallel data acquisition: Distributed monitoring probes (50Hz) and environmental sensors (100Hz) operate synchronously.

[0139] Real-time deviation calculation: Multi-field confocal deviation calculation is performed every 20ms.

[0140] Predictive compensation: Based on the fusion prediction model, the deviation trend is predicted 50ms in advance.

[0141] Synchronous driven execution: Coordinating the actions of each actuator in parallel timing according to modules.

[0142] 4. Exception handling and self-maintenance phase (event triggering):

[0143] Confocal instability response: When the deviation exceeds the threshold, a three-level compensation circuit breaker mechanism is applied to respond in stages.

[0144] Wear Repair Trigger: Based on the lens wear condition determination, a graded self-repair mechanism is initiated.

[0145] Environmental Adaptation to Abrupt Changes: Dynamic Reconfiguration of Protective Layer - Confocal Synergistic Strategy in Response to Extreme Environmental Parameter Variations

[0146] The entire workflow is precisely managed through a state machine, enabling seamless switching between stages and ensuring that the system maintains optimal monitoring performance throughout its entire lifecycle.

[0147] The four-element confocal lens group, through the division of optical power and the multi-band optical path matching design of the confocal interferometer film, lays the foundation for multispectral confocal imaging. The three-dimensional arrangement of the distributed confocal monitoring probes can comprehensively capture the confocal deviation at each key location, providing data support for precise control. The confocal control unit, based on heterogeneous hardware, integrates a three-dimensional confocal parameter library to achieve rapid and accurate initialization. Through a multi-field confocal deviation calculation model, it analyzes multi-source interference such as temperature change and vibration, and then combines it with a fusion prediction model to predict the deviation trend in advance, driving the control logic to shift from passive correction to active compensation, effectively reducing the impact of deviation lag.

[0148] The first and fourth lenses employ an integrated design of PMN-PT ceramic material and silicon-based self-healing microcapsules. This design ensures both electrostrictive adjustment of optical power and autonomous performance recovery through a graded repair mechanism when lenses are worn. During the repair process, the lens voltage, MEMS confocal fine-tuner displacement, and second lens displacement are adjusted simultaneously to ensure that the repair action does not compromise confocal accuracy. The porous PEG-graphene composite porous phase change protective layer resists the risk of low-temperature freezing due to its phase change characteristics. The porous structure and thermal conductivity enhancement design balance structural stability and heat transfer efficiency. Combined with environmental data collected by a multi-parameter fusion sensor array, the optical path and the adaptation parameters of the porous phase change protective layer are dynamically corrected by the confocal control unit, enabling synergistic protection of confocal accuracy in extreme environments.

[0149] The multi-unit structure and synchronous driving logic of the micro-nano beam splitter-confocal adaptive array enable the expansion of multi-target parallel monitoring functionality. The independent displacement adjustment capability of the MEMS confocal fine-tuner in each array unit can adapt to different target distances. The correlation control between the micro-filter and the confocal deviation ensures that the band switching and confocal requirements are accurately matched. Furthermore, through the hard constraint of confocal priority and the three-level compensation fuse mechanism, the core position of confocal accuracy is locked when multiple modules work together, avoiding interference from non-critical tasks.

[0150] Each module forms an organic whole through communication interfaces and synchronous timing design: the lens group provides the imaging foundation, the monitoring probe collects real-time data, the confocal control unit coordinates decision-making and adjustment, the porous phase change protective layer and self-healing mechanism ensure long-term stability, and the array expands multi-target adaptation capabilities. Ultimately, through the complementary functions and synergistic linkage of each part, the system achieves a comprehensive effect of multispectral precise confocal focusing, multi-target parallel monitoring, extreme environment adaptation, and long-term stable operation, meeting the core requirements of power equipment monitoring scenarios for imaging accuracy, applicability, and service life.

[0151] The above description is merely a preferred embodiment of this application and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of disclosure in this application is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the foregoing disclosed concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features with similar functions disclosed in this application.

Claims

1. A multispectral confocal synergistic optimization power equipment monitoring lens, characterized in that, It includes a four-element confocal lens group, a confocal control unit, and a porous phase change protective layer arranged sequentially along the optical axis. The four-element confocal lens group, from object to image, consists of a first lens with negative optical power, a second lens with positive optical power, an aperture stop, a third lens with positive optical power, and a fourth lens with negative optical power. The image-side surface of the second lens is coated with a confocal interference film, and the first and fourth lenses integrate self-healing microcapsules. The four-element confocal lens group is equipped with distributed confocal monitoring probes, which are respectively arranged on the image side of the second lens, the object side of the third lens, and the image side of the fourth lens. The confocal control unit is linked with the distributed confocal monitoring probe and the four-element confocal lens group, and is configured to achieve confocal reference initialization and environmental deviation compensation. The porous phase change protective layer covers the front end of the lens barrel and does not conflict with the optical path of the four-element confocal lens group.

2. The multispectral confocal synergistic optimization power equipment monitoring lens according to claim 1, characterized in that, The first and fourth lenses are made of PMN-PT ceramic material. The self-healing microcapsules are silicon-based self-healing microcapsules, which are uniformly doped in the non-optically effective regions of the first and fourth lenses. The confocal interference film is a PDMS-TiO2 composite matrix, formed by alternating deposition of HfO2, SiO2, and TiO2. The porous phase change protective layer is a porous PEG-graphene composite structure.

3. The multispectral confocal synergistic optimization power equipment monitoring lens according to claim 1, characterized in that, It also includes a micro / nano beam-splitting-confocal adaptive array, which is deployed between the aperture stop and the third lens, and matches the confocal optical path of the four-element confocal lens group with the confocal optical path deviation within a preset range. The micro / nano beam splitting-confocal adaptive array is a multi-unit array structure. Each array unit includes a microlens, a micro-filter, and a MEMS confocal fine-tuner. The MEMS confocal fine-tuner is configured to perform independent displacement adjustment.

4. The multispectral confocal synergistic optimization power equipment monitoring lens according to claim 3, characterized in that, The switching control of the microfilter is related to the confocal deviation fed back by the distributed confocal monitoring probe. The displacement of the MEMS confocal fine-tuner is dynamically adjusted based on the target distance and confocal deviation, and the switching of the micro-filter, the displacement of the MEMS confocal fine-tuner, and the optical power adjustment of the four-element confocal lens group are performed synchronously.

5. The multispectral confocal synergistic optimization power equipment monitoring lens according to claim 1, characterized in that, The confocal control unit is equipped with a three-dimensional confocal parameter library and a full-dimensional environmental confocal influence coefficient calculation model. The three-dimensional confocal parameter library is configured to store confocal calibration parameters corresponding to different focal lengths and imaging bands. The full-dimensional environmental confocal influence coefficient calculation model integrates parameters related to salt spray, rainfall, icing, air pressure, humidity and vibration, and fuses them with data from the distributed confocal monitoring probe in real time.

6. The multispectral confocal synergistic optimization power equipment monitoring lens according to claim 5, characterized in that, The confocal control unit is also equipped with a confocal sharpness-spectral dual-target matching algorithm and filter-MEMS confocal fine-tuner synchronous drive logic. The confocal sharpness-spectral dual-target matching algorithm dynamically corrects the target band based on the confocal deviation fed back by the distributed confocal monitoring probe and the image recognition sharpness.

7. The multispectral confocal synergistic optimization power equipment monitoring lens according to claim 5, characterized in that, The confocal control unit is also equipped with a fusion prediction model, a multi-field confocal deviation calculation model, and a second lens predictive compensation displacement algorithm. The fusion prediction model predicts confocal deviation based on historical data from the distributed confocal monitoring probe. The multi-field confocal deviation calculation model covers temperature variation, environment, vibration, surface shape, and nonlinear correlation deviations. The second lens predictive compensation displacement algorithm introduces a focal length-related correction term.

8. The multispectral confocal synergistic optimization power equipment monitoring lens according to claim 1, characterized in that, The self-healing microcapsule's triggering repair mechanism is a graded self-healing mechanism, including ultra-low power pre-repair and precise power emergency repair. The graded self-healing mechanism determines the repair level based on the confocal deviation and lens wear status fed back by the distributed confocal monitoring probe. During the repair process, the voltages of the first and fourth lenses, as well as the displacement of the MEMS confocal fine-tuner and the displacement of the second lens are adjusted simultaneously.

9. The multispectral confocal synergistic optimization power equipment monitoring lens according to any one of claims 1, 2, 3, 5, and 8, characterized in that, The confocal control unit is equipped with a confocal priority hard constraint threshold, module parallel execution timing, and a three-level compensation circuit breaker mechanism. The three-level compensation circuit breaker mechanism is executed in stages in the order of MEMS fine-tuning, second lens displacement, and confocal interference film voltage adjustment.

10. The multispectral confocal synergistic optimization power equipment monitoring lens according to claim 9, characterized in that, It also includes a multi-parameter fusion sensor array, which includes a vibration frequency domain sensor, a barometric pressure sensor, and a humidity sensor. The confocal control unit is also equipped with a porous phase change protective layer-confocal optical path compensation logic, which dynamically corrects the optical power of the four-piece confocal lens group and the adaptation parameters of the porous phase change protective layer based on the data of the multi-parameter fusion sensor array.

Images