Photovoltaic panel damage detection method and system

Abstract

The invention discloses a photovoltaic panel damage detection method and system, and the system comprises a track system which is disposed above or on the side of a photovoltaic panel array and is used for guiding a pulley to move along the photovoltaic panel array; the tackle is mounted on the track and comprises a resonance electromagnetic wave generator used for emitting electromagnetic waves in a specific frequency range to excite atomic vibration of the photovoltaic panel material; the atomic vibration detector is used for detecting a vibration response signal of the photovoltaic panel under electromagnetic wave excitation; the reference vibration unit is used for collecting a vibration response signal of the lossless area of the photovoltaic panel; the resonance comparison module is used for comparing the vibration response signals of the target area and the reference area so as to identify damage characteristics; the distance adjusting device is used for keeping a constant distance between the pulley and the surface of the photovoltaic panel; the method and the system are remarkably improved in the aspects of accurate detection, dynamic adaptation, multi-dimensional feature analysis, visualization, intelligence and the like.

Description

Technical Field

[0001] The present invention belongs to the field of wind power generation equipment maintenance and fault prediction, and specifically relates to a photovoltaic panel damage detection method and system. Background Art

[0002] With the rapid development of the global photovoltaic industry, the large-scale application of photovoltaic panels has become an important part of renewable energy. However, photovoltaic panels are inevitably affected by environmental factors (such as wind and sand, temperature difference, humidity, ultraviolet radiation, etc.) during long-term operation, and may suffer structural damage such as microcracks, voids, and interlayer separation. These damages will not only reduce the conversion efficiency of photovoltaic panels, but may also cause serious equipment failures, threatening the safe operation of the entire photovoltaic array. Therefore, damage detection technology for photovoltaic panels has become a key technology to ensure the reliability of photovoltaic systems and extend their service life.

[0003] At present, the main technologies for photovoltaic panel damage detection include: Thermal imaging detection: Infrared thermal imaging equipment is used to detect the surface temperature distribution of photovoltaic panels and locate damaged areas (such as hot spots). However, it can only identify temperature anomalies caused by obvious electrical faults (such as short circuits and open circuits), and it is difficult to detect structural damage (such as microcracks and delamination).

[0004] Current-voltage characteristic detection (IV characteristic method): Measure the current-voltage curve of the photovoltaic panel and identify electrical performance damage through abnormal points on the curve. It requires complex connection and power-off operations and is difficult to apply to real-time online detection of large-scale photovoltaic arrays.

[0005] Visual inspection: Detect visible damage on the surface of photovoltaic panels (such as surface cracks and contamination) through high-resolution camera equipment. It relies on external lighting conditions, is difficult to detect microscopic cracks or internal structural damage, and is easily affected by environmental interference. Summary of the invention

[0006] The purpose of the present invention is to provide a photovoltaic panel damage detection method and system, which have significant improvements in accurate detection, dynamic adaptation, multi-dimensional feature analysis, visualization and intelligence.

[0007] The technical solution adopted by the present invention is as follows: a photovoltaic panel damage detection system, the system comprising: A track system, which is arranged above or to the side of the photovoltaic panel array and is used to guide the trolley to move along the photovoltaic panel array; A trolley, mounted on a track, comprising: A resonant electromagnetic wave generator for emitting electromagnetic waves within a specific frequency range to excite atomic vibrations in photovoltaic panel materials; Atomic vibration detector, used to detect the vibration response signal of photovoltaic panels under electromagnetic wave excitation; A reference vibration unit is used to collect vibration response signals of intact areas of the photovoltaic panel; A resonance comparison module is used to compare the vibration response signals of the target area with those of the reference area to identify damage characteristics; A distance adjustment device for maintaining a constant distance between the pulley and the surface of the photovoltaic panel; Vibration isolation device, used to reduce the interference of the trolley movement on the detector; Damage identification and analysis module, used to process and analyze vibration response signals and resonance comparison data to determine the location, type and severity of damage to the photovoltaic panel; Central control system, used to control the movement path and detection process of the rail trolley, and centrally process the damage detection data; The environmental parameter compensation module is used to collect environmental parameters such as temperature, humidity and light intensity, and to correct the vibration signal.

[0008] Wherein, the resonance contrast module comprises: A signal feature extraction unit, used to extract characteristic parameters such as vibration frequency, amplitude and phase of the target area and the reference area; The difference analysis unit compares the resonance signal characteristics of the target area and the reference area through spectrum analysis to identify minor damage; The adaptive threshold unit dynamically adjusts the judgment threshold of the resonance contrast based on the photovoltaic panel material characteristics and the detection environment.

[0009] Among them, the resonant electromagnetic wave generator adopts wide-band excitation technology, covering the frequency range from MHz to THz, and has pulse frequency modulation and partition dynamic scanning functions.

[0010] Wherein, the atomic vibration detector comprises: Highly sensitive interferometer to capture tiny vibration signals of photovoltaic panels; A multi-signal accumulation module is used to superimpose multiple detection signals to improve the signal-to-noise ratio; The noise suppression module uses wavelet noise reduction algorithm and Kalman filtering algorithm to remove environmental interference.

[0011] Wherein, the damage identification and analysis module includes: Deep learning models to analyze vibration response signals and resonance contrast data and identify damage features; Dynamic modeling module, which establishes a dynamic threshold adjustment model based on the lossless state of photovoltaic panels; Standardized damage signature database, including data on cracks, microcracks, voids and fatigue damage types.

[0012] Wherein, the central control system comprises: A path planning module is used to design the moving path of the trolley according to the layout of the photovoltaic panel array; Data analysis module, used to process vibration signals and resonance comparison data in real time, and predict damage trends in combination with historical data; The wireless communication module is used to upload the detection data to the remote server to realize remote monitoring and analysis.

[0013] A photovoltaic panel damage detection method comprises the following steps: (1) The track system guides the trolley to move along the photovoltaic panel array and maintains a constant distance between the trolley and the photovoltaic panel surface; (2) The resonant electromagnetic wave generator emits electromagnetic waves of a specific frequency range to the photovoltaic panel to stimulate the atomic vibration of the material; (3) The atomic vibration detector collects vibration response signals of the target area and reference area of ​​the photovoltaic panel; (4) Compare the vibration signals of the target area and the reference area through the resonance comparison module to identify the damage location, type and severity of the photovoltaic panel; (5) The damage identification and analysis module conducts in-depth analysis of the resonance comparison results and generates a damage detection report for the photovoltaic panel; (6) The central control system combines the environmental parameter compensation module to correct the vibration signal and optimize the detection path.

[0014] Wherein, in the step (3), the vibration response signals of the reference area and the target area are collected in real time, and the resonance difference between the two is quantified using the spectrum difference method.

[0015] In the step (4), the resonance difference signal is analyzed iteratively multiple times based on the dynamic modeling module to enhance the recognition capability of complex damage features.

[0016] In the step (5), the damage detection report generated can be combined with the resonance comparison result to intuitively display the damage distribution and severity of the photovoltaic panel using three-dimensional graphics.

[0017] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: 1. Accurate multi-band resonance excitation The frequency adaptive resonant electromagnetic wave generator emits electromagnetic waves covering a wide frequency band, which can effectively stimulate the resonance characteristics of different materials and structures of photovoltaic panels. Adaptive frequency adjustment ensures matching with the specific material characteristics of photovoltaic panels without manual parameter adjustment in advance. Significantly improve the excitation efficiency, so that the material characteristics of photovoltaic panels (such as cracks, voids, interlayer separation, etc.) can be fully demonstrated, especially for multi-layer composite materials; 2. Detailed signal acquisition and dynamic comparison By using atomic vibration detectors to collect the resonance response signals of the target area and the surrounding normal area, high-resolution vibration characteristic data can be obtained in real time. Minor damage in the target area can be highlighted by comparing the resonance difference with the normal area, thereby significantly reducing false alarms and missed detections. It is particularly suitable for detecting hidden damage in large-area photovoltaic arrays to avoid missing small cracks and tiny structural defects; 3. Comprehensive frequency, amplitude and phase difference extraction The resonance comparison module can extract complex damage features through multi-dimensional comparison of frequency, amplitude and phase; Frequency difference: reflects the change in rigidity or density of the material in the target area; Amplitude differences: reveal abnormal attenuation or enhancement of vibration energy in the target area; Phase Difference: Identify changes in vibration propagation characteristics caused by structural changes; This method can distinguish different types of damage (such as cracks, voids, delamination, etc.) through multi-dimensional feature extraction. The comprehensive diagnostic capability of complex damage is significantly improved, and it is particularly suitable for high-performance, multi-layer photovoltaic panels; 4. Efficient damage identification and trend prediction The damage identification and analysis module compares data to identify the damage location, type and severity of the target area, and combines historical data to make trend predictions. Combined with deep learning algorithms, a dynamic damage feature library can be established to support the extended identification of unknown damage patterns. The dynamic trend prediction function helps the operation and maintenance team to discover potential hidden dangers of the photovoltaic array in advance and avoid serious failures. 5. Visualized test reports and intelligent maintenance The automatically generated inspection report includes a 2D thermal map of the damage distribution, a 3D model, and specific numerical analysis. Combined with the trend prediction function of historical data, it can intuitively display the health of the photovoltaic panels and provide targeted maintenance suggestions. The visual form of the report makes it easier for the operation and maintenance team to quickly locate the problem area and determine the maintenance priority. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 Schematic diagram of the detection method of the present invention. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0020] See also Figure 1, a photovoltaic panel damage detection system, the system comprising: A track system, which is arranged above or to the side of the photovoltaic panel array and is used to guide the trolley to move along the photovoltaic panel array; A trolley, mounted on a track, comprising: A resonant electromagnetic wave generator for emitting electromagnetic waves within a specific frequency range to excite atomic vibrations in photovoltaic panel materials; Atomic vibration detector, used to detect the vibration response signal of photovoltaic panels under electromagnetic wave excitation; A reference vibration unit is used to collect vibration response signals of intact areas of the photovoltaic panel; A resonance comparison module is used to compare the vibration response signals of the target area with those of the reference area to identify damage characteristics; A distance adjustment device for maintaining a constant distance between the pulley and the surface of the photovoltaic panel; Vibration isolation device, used to reduce the interference of the trolley movement on the detector; Damage identification and analysis module, used to process and analyze vibration response signals and resonance comparison data to determine the location, type and severity of damage to the photovoltaic panel; Central control system, used to control the movement path and detection process of the rail trolley, and centrally process the damage detection data; The environmental parameter compensation module is used to collect environmental parameters such as temperature, humidity and light intensity, and to correct the vibration signal.

[0021] Among them, the track system, distance adjustment device and vibration isolation device all adopt existing mature technologies or products.

[0022] The track system is used to support the trolley and guide it to move smoothly along the photovoltaic panel array. The linear guide rail components produced by Hiwin Technology or THK's Chinese subsidiary can be selected. The material is high-hardness alloy steel and has been treated with corrosion and wear resistance. The track system is divided into fixed track and detachable modular track. The fixed track is suitable for large-scale fixed photovoltaic scenes; the modular track is made of lightweight aluminum alloy, which is easy to disassemble and assemble quickly and is suitable for temporary inspection scenes.

[0023] The distance adjustment device is used to maintain a constant distance between the trolley and the surface of the photovoltaic panel. It includes a laser distance measurement module, real-time feedback control and safety redundancy design. The distance sensor uses an industrial-grade laser distance measurement sensor, such as the LR-F series, with a measurement range of 0.1 m~2 m and an accuracy of ±0.2 mm. The sensor has high anti-interference performance and can adapt to outdoor strong light environments.

[0024] The output signal of the laser distance measurement module is connected to the PLC controller (PLC system provided by Chint Electric or Delta Electric) to drive the stepper motor to control the height adjustment of the pulley. The lifting mechanism adopts a ball screw lifting device, manufactured by Bot Precision, which provides high load capacity and stable dynamic response.

[0025] When the laser ranging module fails, the device is equipped with Hall sensor limit protection to ensure the safety of the pulley movement.

[0026] Furthermore, the resonance contrast module includes: A signal feature extraction unit, used to extract characteristic parameters such as vibration frequency, amplitude and phase of the target area and the reference area; The difference analysis unit compares the resonance signal characteristics of the target area and the reference area through spectrum analysis to identify minor damage; The adaptive threshold unit dynamically adjusts the judgment threshold of the resonance contrast based on the photovoltaic panel material characteristics and the detection environment.

[0027] Furthermore, the resonant electromagnetic wave generator adopts a wide-band excitation technology, covers a frequency range from MHz to THz, and has pulse frequency modulation and partition dynamic scanning functions.

[0028] Furthermore, the atomic vibration detector comprises: Highly sensitive interferometer to capture tiny vibration signals of photovoltaic panels; A multi-signal accumulation module is used to superimpose multiple detection signals to improve the signal-to-noise ratio; The noise suppression module uses wavelet noise reduction algorithm and Kalman filtering algorithm to remove environmental interference.

[0029] Furthermore, the damage identification and analysis module includes: Deep learning models to analyze vibration response signals and resonance contrast data and identify damage features; Dynamic modeling module, which establishes a dynamic threshold adjustment model based on the lossless state of photovoltaic panels; Standardized damage signature database, including data on cracks, microcracks, voids and fatigue damage types.

[0030] Furthermore, the central control system includes: A path planning module is used to design the moving path of the trolley according to the layout of the photovoltaic panel array; Data analysis module, used to process vibration signals and resonance comparison data in real time, and predict damage trends in combination with historical data; The wireless communication module is used to upload the detection data to the remote server to realize remote monitoring and analysis.

[0031] A photovoltaic panel damage detection method comprises the following steps: (1) The track system guides the trolley to move along the photovoltaic panel array and maintains a constant distance between the trolley and the photovoltaic panel surface. The trolley stops at the smooth panel to be inspected. (2) The resonant electromagnetic wave generator emits electromagnetic waves of a specific frequency range to the photovoltaic panel to stimulate the atomic vibration of the material; Specifically, the following steps are included: ① Determine the resonant frequency range of photovoltaic materials Different materials have different resonant frequencies, which usually depend on the crystal structure of the material. Using single crystal silicon as an example, the resonant frequency of the lattice vibration (optical phonon frequency) is usually in the range of 10~100 THz. For other types of photovoltaic materials (such as perovskites), their vibration frequencies may be different, usually in the range of 1~100 THz; The resonant frequency matching formula of electromagnetic waves and photovoltaic materials is: ;in, : The resonant frequency of the material; V: The speed of sound or the speed of light (the speed of sound wave propagation of the material, unit: m / s); λ The lattice constant of the material, or the vibration wavelength (unit: m) For silicon material, the speed of sound is approximately V≈8430m / s, and the lattice constant According to the formula, the corresponding resonant frequency can be calculated: ; ②Electromagnetic wave emission The electromagnetic waves generated in a specific frequency range are effectively transmitted to the photovoltaic panel through the antenna to stimulate the atomic vibration of the material; Power and antenna selection: The power output of electromagnetic waves needs to be adjusted according to the response of the photovoltaic panel. Assume that a power amplifier is used to amplify the power of the signal source to a certain value, and the common power range is 10 W~100 W. In the calculation, the power can be determined by the gain of the power amplifier and the power of the input signal; The propagation of electromagnetic waves is closely related to distance and power. The electric field strength formula is used to describe the propagation of electromagnetic waves: ; Where, E: electric field strength (unit: V / m); Transmitted power (unit: W); r: distance from the transmitting point to the receiving point (unit: m); When electromagnetic waves are radiated through the antenna, the antenna gain G will affect the propagation effect. Therefore, the antenna gain is adjusted to make the electromagnetic waves radiate to the photovoltaic panel. The gain is closely related to the antenna design (such as the radiation pattern); ③Material response and excitation effect When photovoltaic materials are stimulated by electromagnetic waves, their atoms or molecules will vibrate. The effect of this process is related to the frequency and power of the electromagnetic waves and the absorption characteristics of the material. Absorption characteristics of materials: The absorption characteristics of materials can be expressed by the absorption coefficient α. The absorption coefficient of silicon is obtained experimentally. In this frequency range; Excitation intensity calculation: The excitation intensity I of the material can be estimated by the following formula: ; Where, I: excitation intensity received by the material surface (unit: W / m2); Transmitted power (unit: W); α: Absorption coefficient of the material; r: Distance of electromagnetic wave propagation (unit: m); Through the above steps, an electromagnetic wave generator system is realized, which can accurately select and emit electromagnetic waves in a specific frequency range to stimulate the atomic vibration of photovoltaic panel materials. It is necessary to select an appropriate frequency range according to the resonant frequency characteristics of the material, and optimize the transmission effect of the electromagnetic wave through power regulation and antenna design to achieve the purpose of exciting the material; (3) The atomic vibration detector collects vibration response signals of the target area and reference area of ​​the photovoltaic panel; the vibration response signals of the reference area and the target area are collected in real time, and the spectrum difference method is used to quantify the resonance difference between the two; The specific steps are: ①Signal acquisition and data preprocessing Use high sampling frequency , satisfies the Nyquist sampling theorem: ;in, : Sampling frequency (unit: Hz). : Upper limit of excitation frequency (unit: Hz); Number of sampling points N: ;in, : Sampling time (unit S), set to 0.01~0.1 seconds. N: Number of sampling points, used for resolution control of time domain signals; ②Signal preprocessing Filtering: Use a bandpass filter to remove noise in non-target frequency ranges.

[0032] Filter range: ; Window function segmentation: Apply Hanninq window for segmentation processing and define the window function as: ;in, : Window function weight. : Window length (unit: s), set to 0.01~0.05 seconds; ③Convert to frequency domain Perform fast Fourier transform (FFT) on the time domain signal X(t) to obtain the frequency domain signal X(f): ; Where, X(f): frequency domain signal, representing the vibration amplitude of each frequency component (unit V). f: frequency (unit Hz); (4) The vibration signals of the target area and the reference area are compared through the resonance comparison module to identify the damage location, type and severity of the photovoltaic panel; the resonance difference signal is analyzed multiple times based on the dynamic modeling module to enhance the recognition ability of complex damage characteristics; The specific steps are: ①Resonance signal comparison Data input and spectrum calculation: The frequency domain signals obtained from the target area and the reference area are: , ;in, : Spectrum signal of the target area. : Spectrum signal of the reference area. f: frequency (unit: Hz); Spectrum difference calculation: Calculate the spectrum difference between the target area and the reference area: ;in, : The spectrum difference between the target area and the reference area; Resonance Frequency Shift: The resonance frequency shift is used to quantify the change in the resonance frequency of the target area compared to the reference area. ;in, : Resonance frequency offset (unit: Hz); , The main resonant frequencies of the target area and the reference area; Amplitude variation: The amplitude difference of the vibration signal is normalized by integration: ; the one among them, : Amplitude change, representing energy difference (dimensionless). , Analyze frequency range; Threshold determination: Set the threshold and For preliminary assessment of damage, if > or > It is determined that there is damage in the target area. : The threshold of frequency deviation; : Threshold value of amplitude change; ②Dynamic modeling module Dynamic modeling basis: Dynamic modeling builds a response characteristic model of the target area and performs fitting and iterative analysis based on multiple spectrum comparison results. Model equation: ; Wherein, Y(t): dynamic response characteristic value of the target area (dimensionless). Model parameters. : The resonant frequency shift of the tth comparison. : The amplitude change of the tth comparison. Noise term; Parameter update: Use the least squares method (LSM) to fit the dynamic model: ; T: total number of iterations. Update parameters ,Optimize the fitting model; Multiple Iteration Analysis: Multiple iterations are performed on the resonance difference signal to update the model parameters. After each iteration, the new model is used to predict the characteristic values ​​of complex damage; ③ Determination of injury type and severity Damage type identification: Based on the resonant frequency shift and amplitude change, the damage type is classified: Crack: small frequency shift, significant amplitude change; Holes: significant frequency shifts, low amplitude changes; Delamination: Both frequency shift and amplitude change are moderate; Severity calculation: Quantify the severity using the predicted value Y(t) from the dynamic model: ; Where, S: severity (dimensionless). Dynamic characteristic values ​​of the reference area; Heat map output: Map the damage severity to the PV panel 2D plane to generate a heat map: High: Darker color, indicating areas of severe damage; Low: lighter in color, indicating areas of minor damage; The damage identification and analysis module conducts in-depth analysis on the resonance comparison results and generates a damage detection report for the photovoltaic panel. The generated damage detection report can combine the resonance comparison results and use three-dimensional graphics to intuitively display the damage distribution and severity of the photovoltaic panel. The specific implementation process is: ①Data input and organization Data Input: Receive the following data from the resonance contrast module: The resonance frequency offset between the target area and the reference area (in Hz); : The amplitude change between the target area and the reference area (dimensionless). Area coordinates : The two-dimensional coordinates of the photovoltaic panel (unit: m). : Injury severity score of each area (dimensionless); Data gridding: The photovoltaic panel is divided into M×N small areas, and the coordinates of each small area are , corresponding to a damage data point M, N: The number of rows and columns of the grid, set according to the size and resolution of the photovoltaic panel; ②In-depth analysis Normalization of injury severity: The injury score Convert to normalized values ​​between 0 and 1: ;in, : Normalized severity score of the ith region (dimensionless). , the minimum and maximum severity scores in all regions; Type determination: According to and Determine the type of damage: crack: Small; big; Hollow: big, Small; Layering: and medium; Decision rules: ; in, : Damage type of the ith region. , : Thresholds for frequency deviation and amplitude change; Mean smoothing: Smoothing the damage data to reduce the impact of noise: ;in, : The smoothed severity score of the ith region. N(i): The neighborhood of the ith region (including the surrounding K regions); ③ Three-dimensional graphics generation Coordinate mapping: convert grid coordinates and severity of injury Mapping to three-dimensional space: ;in, : The corresponding injury severity value; Heatmap generation: is the two-dimensional plane coordinate, The severity of the injury is indicated by color: Blue: no damage; Red: severe damage; 3D model drawing: Draw the PV panel damage distribution in 3D space: X and Y axes represent the physical size of the PV panel. Z axis represents the severity of damage; ④ Damage detection report generation Damage statistics: Damage area: ;in, :Total damaged area (unit: m2). : the area of ​​the ith region; Damage type distribution: count the number and proportion of each type of damage area; Report content: Thermal map and 3D model: intuitively display the damage distribution of photovoltaic panels. Data table: including the damage type, severity and specific coordinates of each area. Damage statistics: total damage area, type distribution and proportion; (6) The central control system combines the environmental parameter compensation module to correct the vibration signal and optimize the detection path; The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A photovoltaic panel damage detection system, characterized in that: The system includes: A track system, which is arranged above or to the side of the photovoltaic panel array and is used to guide the trolley to move along the photovoltaic panel array; A trolley, mounted on a track, comprising: A resonant electromagnetic wave generator for emitting electromagnetic waves within a specific frequency range to excite atomic vibrations in photovoltaic panel materials; Atomic vibration detector, used to detect the vibration response signal of photovoltaic panels under electromagnetic wave excitation; A reference vibration unit is used to collect vibration response signals of intact areas of the photovoltaic panel; A resonance comparison module is used to compare the vibration response signals of the target area with those of the reference area to identify damage characteristics; A distance adjustment device for maintaining a constant distance between the pulley and the surface of the photovoltaic panel; Vibration isolation device, used to reduce the interference of the trolley movement on the detector; Damage identification and analysis module, used to process and analyze vibration response signals and resonance comparison data to determine the location, type and severity of damage to the photovoltaic panel; Central control system, used to control the movement path and detection process of the rail trolley, and centrally process the damage detection data; The environmental parameter compensation module is used to collect environmental parameters such as temperature, humidity and light intensity, and to correct the vibration signal.

2. A photovoltaic panel damage detection system according to claim 1, characterized in that: The resonance contrast module comprises: A signal feature extraction unit, used to extract characteristic parameters such as vibration frequency, amplitude and phase of the target area and the reference area; The difference analysis unit compares the resonance signal characteristics of the target area and the reference area through spectrum analysis to identify minor damage; The adaptive threshold unit dynamically adjusts the judgment threshold of the resonance contrast based on the photovoltaic panel material characteristics and the detection environment.

3. A photovoltaic panel damage detection system according to claim 1, characterized in that: The resonant electromagnetic wave generator adopts a wide-band excitation technology, covers a frequency range from MHz to THz, and has pulse frequency modulation and partition dynamic scanning functions.

4. A photovoltaic panel damage detection system according to claim 1, characterized in that: The atomic vibration detector comprises: Highly sensitive interferometer to capture tiny vibration signals of photovoltaic panels; A multi-signal accumulation module is used to superimpose multiple detection signals to improve the signal-to-noise ratio; The noise suppression module uses wavelet noise reduction algorithm and Kalman filtering algorithm to remove environmental interference.

5. A photovoltaic panel damage detection system according to claim 1, characterized in that: The damage identification and analysis module includes: Deep learning models to analyze vibration response signals and resonance contrast data and identify damage features; Dynamic modeling module, which establishes a dynamic threshold adjustment model based on the lossless state of photovoltaic panels; Standardized damage signature database, including data on cracks, microcracks, voids and fatigue damage types.

6. A photovoltaic panel damage detection system according to claim 1, characterized in that: The central control system comprises: A path planning module is used to design the moving path of the trolley according to the layout of the photovoltaic panel array; Data analysis module, used to process vibration signals and resonance comparison data in real time, and predict damage trends in combination with historical data; The wireless communication module is used to upload the detection data to the remote server to realize remote monitoring and analysis.

7. A photovoltaic panel damage detection method, comprising the following steps: (1) The track system guides the trolley to move along the photovoltaic panel array and maintains a constant distance between the trolley and the photovoltaic panel surface; (2) The resonant electromagnetic wave generator emits electromagnetic waves of a specific frequency range to the photovoltaic panel to stimulate the atomic vibration of the material; (3) The atomic vibration detector collects vibration response signals of the target area and reference area of ​​the photovoltaic panel; (4) Compare the vibration signals of the target area and the reference area through the resonance comparison module to identify the damage location, type and severity of the photovoltaic panel; (5) The damage identification and analysis module conducts in-depth analysis of the resonance comparison results and generates a damage detection report for the photovoltaic panel; (6) The central control system combines the environmental parameter compensation module to correct the vibration signal and optimize the detection path.

8. A photovoltaic panel damage detection method according to claim 7, characterized in that: In the step (3), the vibration response signals of the reference area and the target area are collected in real time, and the resonance difference between the two is quantified using the spectrum difference method.

9. A photovoltaic panel damage detection method according to claim 7, characterized in that: In the step (4), the resonance difference signal is analyzed iteratively multiple times based on the dynamic modeling module to enhance the recognition capability of complex damage features.

10. A photovoltaic panel damage detection method according to claim 7, characterized in that: In the step (5), the damage detection report generated can be combined with the resonance comparison result to intuitively display the damage distribution and severity of the photovoltaic panel using three-dimensional graphics.

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