A photovoltaic water pump inverter operating state analysis method and system

Abstract

The application discloses a photovoltaic water pump inverter operation state analysis method and system, relates to the photovoltaic system monitoring technical field, and is used for solving the problem of high false alarm rate of fault identification under complex working conditions. First, the direct current side steady-state power supply component and the dynamic ripple component are extracted through frequency domain separation to construct equivalent impedance and mechanical vibration characteristics. Then, the power-impedance sensitivity is analyzed to define the power supply side gradient characteristic interval. At the same time, the linear coupling degree of electromechanical energy is used to accurately distinguish the linear drift of light and the physical nonlinear distortion. Finally, based on the sensitivity interval and the coupling degree evolution state, multi-dimensional logic judgment is performed to realize the accurate classification of the normal, overload stuck and no-load dry running state of the water pump motor, and the fault diagnosis precision and environmental adaptability of the photovoltaic power supply system are improved.

Description

Technical Field

[0001] This invention relates to the field of photovoltaic system monitoring technology, specifically to a method and system for analyzing the operating status of a photovoltaic water pump inverter. Background Technology

[0002] Photovoltaic water pump systems, as an application that directly drives water pumps using solar energy, are widely used in agricultural irrigation, desertification control, and domestic water supply in remote areas. The inverter, as the core control unit connecting the photovoltaic array and the pump unit, directly determines the water pumping efficiency and system lifespan. Since photovoltaic water pump systems are typically deployed in unattended outdoor environments, and the output power of the photovoltaic array exhibits significant nonlinear fluctuations due to factors such as sunlight intensity and temperature, real-time and accurate monitoring of the inverter's operating status is crucial for ensuring continuous and stable system operation and reducing maintenance costs.

[0003] Existing condition monitoring methods for photovoltaic water pump inverters typically rely on setting fixed thresholds for single electrical parameters such as voltage and current. However, this monitoring approach has substantial drawbacks in practical applications. First, under conditions of drastic changes in sunlight intensity or cloud cover, normal maximum power point tracking adjustments can cause significant fluctuations in electrical parameters. These fluctuations are easily misinterpreted as system faults by existing methods, leading to unnecessary downtime. Second, current technologies often overlook the mechanical load characteristics inherent in electrical signals, making it difficult to effectively establish a deep correlation between electrical parameters and the mechanical state of the water pump. This results in low sensitivity in identifying early mechanical faults such as pump dry running or impeller jamming. Protection is usually only triggered after the fault evolves into a severe overcurrent or shutdown, failing to achieve early warning and accurate fault location. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a method and system for analyzing the operating status of photovoltaic water pump inverters, thus solving the problems mentioned in the background.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a method for analyzing the operating status of a photovoltaic water pump inverter, comprising the following steps: S1. Continuously sampling the voltage and current signals on the DC side of the photovoltaic water pump inverter, extracting the steady-state DC component characterizing the power supply level of the photovoltaic array and the dynamic ripple component characterizing the mechanical torque characteristics of the water pump unit through frequency domain separation, constructing an equivalent impedance evolution value based on the steady-state DC component, and extracting the mechanical load vibration amplitude based on the dynamic ripple component; S2. Simultaneously monitoring the changing trends of the equivalent impedance evolution value and the power value in the steady-state DC component, constructing a power-impedance sensitivity characteristic reflecting the output characteristics of the power supply side, and identifying whether the current power-impedance sensitivity characteristic is in a negative gradient characteristic range or a zero gradient characteristic range; S3. Establishing the electromechanical energy linear coupling degree between the mechanical load vibration amplitude and the power value in the steady-state DC component, and monitoring the electromechanical energy linear coupling degree. The evolution of the coupling degree over time is used to distinguish between the linear drift characteristics caused by changes in light irradiance and the nonlinear distortion characteristics caused by changes in the physical structure of the pump unit; S4. Based on the characteristic range of the power-impedance sensitivity characteristic and the evolution of the electromechanical energy linear coupling degree, the operating state logic is executed: when the power-impedance sensitivity characteristic is in the negative gradient characteristic range and the electromechanical energy linear coupling degree shows a linear drift characteristic, the system is determined to be in normal operation; when the power-impedance sensitivity characteristic is in the zero gradient characteristic range and the electromechanical energy linear coupling degree shows a monotonically increasing nonlinear distortion characteristic, the system is determined to be in the pump mechanical overload or foreign object jamming state; when the power-impedance sensitivity characteristic is in the negative gradient characteristic range but the power value continues to drop and the electromechanical energy linear coupling degree drops sharply until it disappears, the system is determined to be in the pump no-load dry running or inlet suction state.

[0006] Furthermore, the specific process of continuously sampling the voltage and current signals on the DC side of the photovoltaic water pump inverter, and extracting the steady-state DC component characterizing the power supply level of the photovoltaic array and the dynamic ripple component characterizing the mechanical torque characteristics of the water pump unit through frequency domain separation is as follows: A sliding time window containing sampling points of a preset length is established. The DC side voltage and current signals within the sliding time window are input into a digital low-pass filter to filter out high-frequency noise and modulation harmonics above the cutoff frequency, and output steady-state DC voltage and steady-state DC current components. The current operating fundamental frequency of the photovoltaic water pump inverter is tracked synchronously, and a passband range with the operating fundamental frequency as the center frequency is set. The DC side current signal is input into a digital bandpass filter with variable parameters to extract the AC component within the passband range and output the dynamic current ripple component.

[0007] Furthermore, the specific process of constructing the equivalent impedance evolution value based on the steady-state DC component and extracting the mechanical load vibration amplitude based on the dynamic ripple component is as follows: Perform a division operation between the steady-state DC voltage component and the steady-state DC current component to obtain the real-time impedance sampling value; smooth the real-time impedance sampling values ​​of multiple consecutive sampling periods to generate the equivalent impedance evolution value; perform Hilbert transform or absolute value detection operation on the dynamic current ripple component to obtain the instantaneous envelope of the dynamic current ripple component; calculate the effective value of the instantaneous envelope in a single power frequency cycle to generate the mechanical load vibration amplitude.

[0008] Furthermore, the specific process of simultaneously monitoring the changes in the equivalent impedance evolution value and the power value in the steady-state DC component to construct a power-impedance sensitivity characteristic reflecting the output characteristics of the power supply side is as follows: Calculate the product of the steady-state DC voltage component and the steady-state DC current component to obtain the steady-state DC power value, and construct a differential observation window that includes the current time and historical time. Within the differential observation window, calculate the first-order difference component of the steady-state DC power value relative to time, and the first-order difference component of the equivalent impedance evolution value relative to time. Divide the first-order difference component of the steady-state DC power value by the first-order difference component of the equivalent impedance evolution value to obtain the power-impedance sensitivity coefficient characterizing the power response intensity caused by a unit impedance change, and use this coefficient as the power-impedance sensitivity characteristic.

[0009] Furthermore, the specific process for identifying whether the current power-impedance sensitivity characteristic is in the negative gradient characteristic range or the zero gradient characteristic range is as follows: detect the numerical polarity and amplitude range of the power-impedance sensitivity coefficient; if the power-impedance sensitivity coefficient is negative and the amplitude exceeds the preset dead zone threshold, it is determined that the power increases as the impedance decreases, and it is classified as a negative gradient characteristic range; if the amplitude of the power-impedance sensitivity coefficient falls within the preset zero dead zone range, or shows an alternating positive and negative oscillation state near the zero point, it is determined that the power does not change with the impedance or the change is not obvious, and it is classified as a zero gradient characteristic range.

[0010] Furthermore, the specific process for establishing the electromechanical energy linear coupling degree of the mechanical load vibration amplitude relative to the power value in the steady-state DC component, and monitoring the evolution of the electromechanical energy linear coupling degree on the time axis is as follows: Calculate the product of the voltage and current values ​​of the steady-state DC component to obtain the steady-state DC power value; divide the mechanical load vibration amplitude by the steady-state DC power value, or divide the mechanical load vibration amplitude by the nonlinear mapping function value of the steady-state DC power value, to obtain the instantaneous coupling ratio; construct a first-in-first-out circular buffer for storing the instantaneous coupling ratio; at each sampling update, write the latest instantaneous coupling ratio to the head of the buffer and overwrite the oldest data; calculate the arithmetic mean or weighted average of all instantaneous coupling ratios in the buffer to generate the electromechanical energy linear coupling degree, forming a coupling degree evolution sequence that is continuously updated over time.

[0011] Furthermore, the specific process for distinguishing between the linear drift characteristics caused by changes in light irradiance and the nonlinear distortion characteristics caused by changes in the physical structure of the pump unit is as follows: Perform a first-order difference operation or standard deviation statistical operation on the coupling degree evolution sequence to obtain the coupling degree change rate index; if the absolute value of the coupling degree change rate index remains within the preset zero-point drift tolerance range, it is determined that the electromechanical energy linear coupling degree keeps proportionally following the power change, and is marked as a linear drift characteristic; if the absolute value of the coupling degree change rate index exceeds the zero-point drift tolerance range and shows a continuous positive increase or a negative step jump, it is determined that the electromechanical energy linear coupling degree deviates from the proportional constraint of power change, and is marked as a nonlinear distortion characteristic.

[0012] Furthermore, the judgment process for determining the operating state based on the characteristic range of the power-impedance sensitivity feature and the evolution of the electromechanical energy linear coupling degree is as follows: A multi-dimensional state identifier set is constructed, including sensitivity range identifiers, power trend identifiers, and coupling degree feature identifiers; when the sensitivity range identifier corresponds to a negative gradient characteristic range and the coupling degree feature identifier corresponds to a linear drift characteristic, a maximum power point tracking closed-loop control command is output to maintain normal system operation; when the sensitivity range identifier corresponds to a zero gradient characteristic range and the coupling degree feature identifier corresponds to a positive divergence state in the nonlinear distortion characteristic, overload protection logic is activated, and a shutdown alarm signal is output; when the sensitivity range identifier corresponds to a negative gradient characteristic range, the power trend identifier shows a continuously decreasing value, and the coupling degree feature identifier corresponds to a negative step jump state in the nonlinear distortion characteristic, underload protection logic is activated, and a delayed restart action is performed.

[0013] A photovoltaic water pump inverter operation status analysis system includes the following modules: a feature extraction module, used to continuously sample the voltage and current signals on the DC side of the photovoltaic water pump inverter, extract the steady-state DC component characterizing the power supply level of the photovoltaic array and the dynamic ripple component characterizing the mechanical torque characteristics of the water pump unit through frequency domain separation, construct the equivalent impedance evolution value based on the steady-state DC component, and extract the mechanical load vibration amplitude based on the dynamic ripple component; a characteristic identification module, used to simultaneously monitor the changing trends of the equivalent impedance evolution value and the power value in the steady-state DC component, construct a power-impedance sensitivity feature reflecting the output characteristics of the power supply side, and identify whether the current power-impedance sensitivity feature is in the negative gradient characteristic range or the zero gradient characteristic range; and a coupling analysis module, used to establish the electromechanical energy linear coupling degree between the mechanical load vibration amplitude and the power value in the steady-state DC component, and monitor the electromechanical energy linear coupling degree on the time axis. The system is designed to differentiate between linear drift characteristics caused by changes in light irradiance and nonlinear distortion characteristics caused by changes in the physical structure of the pump unit. A state determination module is used to perform operational state logic determination based on the characteristic range of the power-impedance sensitivity characteristic and the evolution of the electromechanical energy linear coupling degree: when the power-impedance sensitivity characteristic is in the negative gradient characteristic range and the electromechanical energy linear coupling degree exhibits linear drift characteristics, the system is determined to be in normal operation; when the power-impedance sensitivity characteristic is in the zero gradient characteristic range and the electromechanical energy linear coupling degree exhibits monotonically increasing nonlinear distortion characteristics, the system is determined to be in a pump mechanical overload or foreign object jamming state; when the power-impedance sensitivity characteristic is in the negative gradient characteristic range but the power value continues to drop, and the electromechanical energy linear coupling degree experiences a step-like decrease until it disappears, the system is determined to be in a pump no-load dry run or inlet suction state.

[0014] The present invention has the following beneficial effects:

[0015] (1) A method for analyzing the operating status of a photovoltaic water pump inverter, which decouples the steady-state DC component representing energy supply from the dynamic ripple component representing mechanical characteristics by performing frequency domain separation on the DC side electrical signal, breaking the limitation of traditional methods that only use mixed signals for analysis. By constructing power-impedance sensitivity characteristics and identifying their gradient characteristic range, it is possible to accurately distinguish whether the system is in the normal adjustment range of maximum power point tracking or in the abnormal range limited by electrical constraints from the physical level of the power supply side output characteristics. This mechanism provides an accurate benchmark for subsequent state analysis and effectively solves the technical problem of difficulty in distinguishing between changes in electrical parameters caused by light fluctuations and parameter anomalies caused by faults.

[0016] (2) A photovoltaic water pump inverter operation status analysis system establishes the electromechanical energy linear coupling degree and monitors its evolution state. Utilizing the physical law that the mechanical vibration amplitude linearly follows power changes under normal operating conditions, it can effectively filter out linear drift interference caused by changes in the lighting environment. Based on the joint logic judgment of the power-impedance sensitivity characteristic range and the evolution state of the electromechanical energy linear coupling degree, it achieves accurate differentiation between three typical states: normal operation, mechanical overload jamming, and no-load dry running. This method not only eliminates false alarms caused by environmental factors but also keenly captures weak fault characteristics such as coupling breakage during dry running and nonlinear distortion during jamming, significantly improving the system's fault diagnosis accuracy and environmental adaptability in complex environments.

[0017] Of course, any product implementing this invention does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0018] Figure 1 This is a flowchart of a photovoltaic water pump inverter operation status analysis method according to the present invention.

[0019] Figure 2 This is a flowchart of a photovoltaic water pump inverter operation status analysis system according to the present invention. Detailed Implementation

[0020] This application provides a method and system for analyzing the operating status of a photovoltaic water pump inverter, which solves the problems of false alarms easily generated under complex weather conditions and the difficulty in accurately identifying mechanical faults of water pumps through electrical signals in the prior art.

[0021] The overall concept of the solution in this application embodiment is as follows:

[0022] First, signal processing techniques are used to separate the steady-state characteristics reflecting the power supply capability of the photovoltaic array and the dynamic characteristics reflecting the mechanical load characteristics of the water pump from a single sampled signal on the DC side of the inverter. Next, the electrical operating range of the power supply side is determined by analyzing the sensitivity relationship between power and impedance in the steady-state characteristics. Simultaneously, the degree of electromechanical energy linear coupling between the dynamic and steady-state characteristics is analyzed to verify the linearity of the mechanical load's response to energy input. Finally, multi-dimensional logical cross-validation is performed between the electrical operating range of the power supply side and the coupled response state of the load side, thereby accurately locking the real-time operating state of the system while eliminating interference from ambient light fluctuations.

[0023] Please see Figure 1This invention provides a technical solution: a method for analyzing the operating status of a photovoltaic water pump inverter, comprising the following steps: S1. Continuously sampling the voltage and current signals on the DC side of the photovoltaic water pump inverter, extracting the steady-state DC component characterizing the power supply level of the photovoltaic array and the dynamic ripple component characterizing the mechanical torque characteristics of the water pump unit through frequency domain separation, constructing the equivalent impedance evolution value based on the steady-state DC component, and extracting the mechanical load vibration amplitude based on the dynamic ripple component; S2. Simultaneously monitoring the changing trends of the equivalent impedance evolution value and the power value in the steady-state DC component, constructing a power-impedance sensitivity characteristic reflecting the output characteristics of the power supply side, and identifying whether the current power-impedance sensitivity characteristic is in a negative gradient characteristic range or a zero gradient characteristic range; S3. Establishing the electromechanical energy linear coupling degree between the mechanical load vibration amplitude and the power value in the steady-state DC component, and monitoring the electromechanical energy linear coupling degree in time... The evolution state on the intermediate axis is used to distinguish between the linear drift characteristics caused by changes in light irradiance and the nonlinear distortion characteristics caused by changes in the physical structure of the pump unit; S4. Based on the characteristic range of the power-impedance sensitivity characteristic and the evolution state of the electromechanical energy linear coupling degree, the operating state logic is executed: when the power-impedance sensitivity characteristic is in the negative gradient characteristic range and the electromechanical energy linear coupling degree shows linear drift characteristics, the system is determined to be in normal operation; when the power-impedance sensitivity characteristic is in the zero gradient characteristic range and the electromechanical energy linear coupling degree shows monotonically increasing nonlinear distortion characteristics, the system is determined to be in the pump mechanical overload or foreign object jamming state; when the power-impedance sensitivity characteristic is in the negative gradient characteristic range but the power value continues to drop and the electromechanical energy linear coupling degree drops in a step until it disappears, the system is determined to be in the pump no-load dry running or inlet suction state.

[0024] In this embodiment, step S1 is mainly used for data preprocessing and physical separation of feature dimensions. This step decouples the single DC-side signal into steady-state information reflecting energy input and dynamic information reflecting load operation using frequency domain methods. The steady-state DC component refers to the average DC voltage and current after filtering out high-frequency interference, representing the current power supply capacity of the photovoltaic array; the dynamic ripple component refers to the weak AC signal superimposed on the DC component, which is a characteristic waveform modulated onto the DC bus by the torque pulsation of the water pump motor during rotation. The technical function of this step is to acquire mechanical vibration information, which usually requires external sensors for measurement, using non-invasive DC-side sampling, and to construct two fundamental physical quantities: the equivalent impedance evolution value and the mechanical load vibration amplitude, providing independent data support for subsequent source-load separation analysis. Step S2 is mainly used to identify the current electrical control state of the system from the perspective of the power supply side. This step constructs a power-impedance sensitivity characteristic by calculating the sensitivity of power to impedance changes, thereby determining whether the system follows the maximum power point tracking control law. The negative gradient characteristic range refers to the region where power increases as impedance decreases, consistent with the normal output characteristics of photovoltaic cells in maximum power point tracking mode. The zero gradient characteristic range refers to the region where power does not change or changes very little with impedance, typically corresponding to abnormal operating conditions where current reaches its limit or the system stalls. The technical purpose of this step is to determine, from an electrical principle perspective, whether the system is performing normal energy regulation or has reached the boundary of electrical operation, thereby quickly eliminating or locking down electrical anomalies. Step S3 is mainly used to verify the physical consistency between energy input and mechanical output. This step quantifies the following relationship between mechanical vibration and electrical power by establishing electromechanical energy linear coupling. Electromechanical energy linear coupling refers to the ratio or correlation coefficient between the mechanical load vibration amplitude and the steady-state DC power value; linear drift characteristic refers to the phenomenon where the coupling remains constant or moves linearly within a small range when power increases or decreases due to changes in illumination; nonlinear distortion characteristic refers to the phenomenon where the coupling changes abruptly or monotonically diverges. The technical function of this step is to utilize the physical law that changes in illumination only alter the amplitude and not the electromechanical coupling ratio, effectively eliminating false alarms caused by weather conditions and accurately pinpointing the real faults caused by changes in the physical structure of the water pump. Step S4 is mainly used to make the final operational status determination based on the logical intersection of the aforementioned characteristics. This step jointly analyzes the electrical range state on the power supply side and the coupling evolution state on the load side. When the system is in the negative gradient range and the coupling degree drifts linearly, it indicates that the electrical regulation is normal and the mechanical response is matched, and it is judged to be in normal operation; when the system is in the zero gradient range and the coupling degree increases nonlinearly, it indicates that the electrical side energy is limited and the mechanical side vibration is aggravated, which is consistent with the physical characteristics of mechanical overload or jamming; when the system is in the negative gradient range but the power drops and the coupling degree step disappears, it indicates that the electrical side is still trying to regulate but the mechanical vibration on the load side is lost, which is consistent with the dry running characteristics of load loss.The technical role of this step is to achieve accurate classification and fault diagnosis of complex operating conditions of photovoltaic water pump systems through the mutual verification of multi-dimensional features.

[0025] Specifically, the process of continuously sampling the voltage and current signals on the DC side of the photovoltaic water pump inverter, and extracting the steady-state DC component representing the power supply level of the photovoltaic array and the dynamic ripple component representing the mechanical torque characteristics of the water pump unit through frequency domain separation is as follows: A sliding time window containing sampling points of a preset length is established. The DC-side voltage and current signals within the sliding time window are input into a digital low-pass filter to filter out high-frequency noise and modulation harmonics above the cutoff frequency, outputting the steady-state DC voltage component and steady-state DC current component. Simultaneously, the current operating fundamental frequency of the photovoltaic water pump inverter is tracked, and a passband range centered on the operating fundamental frequency is set. The DC-side current signal is input into a digital bandpass filter with variable parameters to extract the AC component within the passband range, outputting the dynamic current ripple component.

[0026] In this implementation scheme, the purpose of constructing a sliding time window is to extract statistically significant local segments from the continuous data stream, ensuring both real-time data processing and eliminating potential spectral leakage caused by data truncation. In the low-pass filtering stage, filtering out high-frequency noise and modulation harmonics essentially removes high-frequency interference generated by the inverter's switching devices, thereby restoring the pure DC energy supply level of the photovoltaic array. The core challenge in extracting the dynamic current ripple component lies in the fact that the pump motor's speed fluctuates with changes in sunlight, resulting in an unstable characteristic frequency. Therefore, a variable-parameter digital bandpass filter is used. The key is to dynamically adjust the filter's passband boundary based on the real-time tracked fundamental frequency to ensure that the filter always covers the current mechanical torque pulsation frequency. The boundary frequency calculation model for this passband range is as follows: ; In the formula, The lower cutoff frequency of the passband of a digital bandpass filter; The upper passband cutoff frequency of a digital bandpass filter; The fundamental frequency of the photovoltaic water pump inverter is currently being tracked in real time. The preset passband half-bandwidth is determined by selecting 1.5 to 2 times the rated slip frequency of the water pump motor to ensure that it can accommodate frequency shifts caused by load fluctuations. Through the above dynamic adjustment mechanism, the system can adaptively intercept specific frequency band signals containing rich mechanical load information, providing a high signal-to-noise ratio data source for subsequent feature analysis.

[0027] Specifically, the process of constructing the equivalent impedance evolution value based on the steady-state DC component and extracting the mechanical load vibration amplitude based on the dynamic ripple component is as follows: Perform a division operation between the steady-state DC voltage component and the steady-state DC current component to obtain the real-time impedance sampling value; smooth the real-time impedance sampling values ​​for multiple consecutive sampling periods to generate the equivalent impedance evolution value; perform Hilbert transform or absolute value detection operation on the dynamic current ripple component to obtain the instantaneous envelope of the dynamic current ripple component; calculate the effective value of the instantaneous envelope within a single power frequency cycle to generate the mechanical load vibration amplitude.

[0028] In this implementation scheme, although the direct voltage-to-current ratio can reflect the instantaneous impedance state after obtaining the steady-state DC component, the original ratio often contains glitches due to the randomness of environmental noise. Therefore, smoothing the real-time impedance sampling values ​​is a key step in constructing the equivalent impedance evolution value. This process suppresses random fluctuations by introducing the weight of historical data, thereby outlining the impedance evolution trajectory of the system over a long period of operation. The smoothing process uses an exponentially weighted moving average algorithm, and its calculation formula is as follows: In the formula, The equivalent impedance evolution value calculated at the current sampling time; The equivalent impedance evolution value generated at the previous sampling time; The steady-state DC voltage component output at the current sampling moment; The steady-state DC current component output at the current sampling moment; The smoothing weighting coefficient is determined based on the system sampling frequency and the desired impedance response time constant, typically ranging from 0.01 to 0.1. A smaller value results in a stronger smoothing effect but also a greater response lag. For extracting the amplitude of mechanical load vibration, Hilbert transform or absolute value detection is used to reconstruct the instantaneous intensity variation from the oscillating AC ripple. Compared to simple peak detection, extracting the instantaneous envelope more continuously reflects the energy fluctuations of mechanical torque pulsations. To quantify this energy, calculating the effective value within a single power frequency cycle is necessary, which transforms the fluctuating envelope signal into a stable scalar, i.e., the mechanical load vibration amplitude. The mathematical model for this calculation process is expressed as follows: In the formula, The final generated mechanical load vibration amplitude; The duration of a single power frequency cycle, which is equal to the reciprocal of the current operating fundamental frequency; The instantaneous envelope function obtained after transforming the dynamic current ripple component; The integral variable represents time. Through this series of mathematical transformations, the weak mechanical vibration characteristics originally submerged in electrical signals are transformed into quantifiable numerical indicators, providing a precise mathematical basis for subsequent assessments of the pump's mechanical condition.

[0029] Specifically, the process of simultaneously monitoring the changes in the equivalent impedance evolution value and the power value in the steady-state DC component to construct a power-impedance sensitivity characteristic reflecting the output characteristics of the power supply side is as follows: Calculate the product of the steady-state DC voltage component and the steady-state DC current component to obtain the steady-state DC power value, and construct a differential observation window that includes the current time and historical time. Within the differential observation window, calculate the first-order difference component of the steady-state DC power value relative to time, and the first-order difference component of the equivalent impedance evolution value relative to time. Divide the first-order difference component of the steady-state DC power value by the first-order difference component of the equivalent impedance evolution value to obtain the power-impedance sensitivity coefficient characterizing the power response intensity caused by a unit impedance change, and use this coefficient as the power-impedance sensitivity characteristic.

[0030] In this implementation scheme, the purpose of calculating the steady-state DC power value is to obtain an intuitive indicator reflecting the current energy output capability of the photovoltaic array, which serves as the foundational data for subsequent evaluation of power supply characteristics. The technical role of constructing a differential observation window is to introduce a dynamic perspective in the time dimension. By comparing the state differences between the current moment and historical moments, the interference of static bias is eliminated, thereby focusing on the moving trend of the system's operating point. Based on this, calculating the first-order difference component of the steady-state DC power value and the first-order difference component of the equivalent impedance evolution value essentially quantifies the fluctuation amplitude of energy output and load impedance within an extremely short time interval. Dividing these two values ​​essentially calculates the slope of the tangent line to the power-impedance characteristic curve at the current operating point. This slope accurately characterizes the sensitivity of the power supply side to load changes. The calculation model for this power-impedance sensitivity coefficient is expressed as follows: In the formula, The power-impedance sensitivity coefficient calculated at the current sampling time; : The steady-state DC power value obtained at the current sampling time; The historical steady-state DC power value lagged by L sampling periods within the differential observation window; The equivalent impedance evolution value generated at the current sampling time; The historical equivalent impedance evolution value lagged by L sampling periods within the differential observation window; The time span step of the differential observation window is determined by selecting a number of sampling points that are a minimum integer multiple of the photovoltaic array's maximum power point tracking control cycle. This ensures that the differential operation can span a complete control disturbance step, avoiding the capture of invalid transient noise. The coefficients calculated using this formula linearize the complex nonlinear power supply output characteristics into a specific value at the current moment, providing a direct mathematical basis for subsequent interval division.

[0031] Specifically, the process for identifying whether the current power-impedance sensitivity characteristic is in the negative gradient characteristic range or the zero gradient characteristic range is as follows: detect the numerical polarity and amplitude range of the power-impedance sensitivity coefficient; if the power-impedance sensitivity coefficient is negative and the amplitude exceeds the preset dead zone threshold, it is determined that the power increases as the impedance decreases, and it is classified as the negative gradient characteristic range; if the amplitude of the power-impedance sensitivity coefficient falls within the preset zero dead zone range, or shows an alternating positive and negative oscillation state near the zero point, it is determined that the power does not change with the impedance or the change is not obvious, and it is classified as the zero gradient characteristic range.

[0032] In this implementation scheme, detecting the numerical polarity and amplitude range of the power-impedance sensitivity coefficient is to discretize the continuously changing sensitivity value into a control state interval with clear physical meaning. The technical function of setting a dead zone threshold is to construct a fault-tolerant buffer band to filter out random fluctuations near the zero point caused by sensor measurement errors or calculation truncation errors, preventing the system from repeatedly jumping in the critical state. When a negative coefficient with a significant amplitude is detected, it means that the impedance has decreased (the load has increased), leading to an increase in power. This perfectly matches the output characteristics of photovoltaic cells to the left of the maximum power point, meaning the power supply still has the capacity to output more energy; therefore, it is determined to be a negative gradient characteristic interval. Conversely, when the coefficient falls into the zero-point dead zone or oscillates near zero, it means that regardless of impedance changes, the power remains basically constant. This usually corresponds to current saturation or the system being in some kind of fault-locked state; therefore, it is classified as a zero gradient characteristic interval. The mathematical inequality description of this determination logic is as follows: To be determined as a negative gradient characteristic interval, the following must be satisfied: The region to be determined as having zero gradient characteristics must satisfy the following: In the formula, The preset dead zone threshold is determined by taking a value between 0.5% and 1% of the ratio of the system's rated power to its minimum operating impedance, or by setting it based on three times the standard deviation of the sensitivity coefficient during historical quiet periods, to ensure coverage of background noise. Through this threshold-based logical classification, the system can quickly identify whether the photovoltaic power source is currently in an active, regulated state (negative gradient) or a passive, constrained, inert state (zero gradient), thus providing crucial power-side state constraints for subsequent fault characterization based on mechanical load characteristics.

[0033] Specifically, the process of establishing the electromechanical energy linear coupling degree between the mechanical load vibration amplitude and the power value in the steady-state DC component, and monitoring the evolution of the electromechanical energy linear coupling degree on the time axis is as follows: Calculate the product of the voltage and current values ​​of the steady-state DC component to obtain the steady-state DC power value; divide the mechanical load vibration amplitude by the steady-state DC power value, or divide the mechanical load vibration amplitude by the nonlinear mapping function value of the steady-state DC power value, to obtain the instantaneous coupling ratio; construct a first-in-first-out circular buffer for storing the instantaneous coupling ratio; write the latest instantaneous coupling ratio to the head of the buffer and overwrite the oldest data each time the sampling is updated; calculate the arithmetic mean or weighted average of all instantaneous coupling ratios in the buffer to generate the electromechanical energy linear coupling degree, forming a coupling degree evolution sequence that is continuously updated over time.

[0034] In this implementation scheme, the core purpose of calculating the steady-state DC power value and obtaining the instantaneous coupling ratio is to construct a normalized index that can shield the influence of input energy fluctuations of the photovoltaic array. Since the mechanical vibration intensity of the photovoltaic water pump is usually positively correlated with the input power, directly monitoring the vibration amplitude cannot distinguish whether the increased vibration is due to enhanced sunlight or abnormal vibration caused by mechanical faults. Through division operations or nonlinear mapping, a mechanical response model under unit power is essentially established, i.e., the electromechanical energy linear coupling degree. Introducing a first-in-first-out circular buffer and performing averaging serves to filter out random spikes caused by electrical sampling noise or transient mechanical impacts using statistical principles, ensuring that the generated coupling degree evolution sequence reflects the steady-state trend of the system on a macroscopic time scale, rather than instantaneous fluctuations. The generation process of this electromechanical energy linear coupling degree can be described by the following mathematical model: In the formula, The electromechanical energy linear coupling degree generated at the current sampling moment directly reflects the response efficiency of mechanical load to electrical energy input. The storage depth of the first-in-first-out circular buffer is determined by covering the number of sampling points corresponding to at least 3 to 5 complete mechanical rotation cycles to eliminate the influence of periodic fluctuations. : The lookup index variable in the buffer; The weighting coefficients for the m-th historical data are typically distributed using a Hamming window or triangular window function to give higher weights to recent data and enhance the system's ability to dynamically track state changes. The buffer stores historical mechanical load vibration amplitudes. The buffer stores historical steady-state DC power values. The power nonlinear mapping index is used to correct the nonlinear relationship between torque and power of the pump at different speeds. Its value is typically set to 1.0 to represent a purely linear relationship, or determined by fitting the pump's hydraulic characteristic curve using the least squares method. A typical value range is 0.8 to 1.2. Through the above calculations, the mechanical vibration data, which originally fluctuated drastically with light intensity, is transformed into a dimensionless constant that tends to remain constant under normal operating conditions, providing a stable reference benchmark for subsequent anomaly identification.

[0035] Specifically, the process for distinguishing between linear drift characteristics caused by changes in light irradiance and nonlinear distortion characteristics caused by changes in the physical structure of the pump unit is as follows: Perform a first-order difference operation or standard deviation statistical operation on the coupling degree evolution sequence to obtain the coupling degree change rate index; if the absolute value of the coupling degree change rate index remains within the preset zero-point drift tolerance range, it is determined that the electromechanical energy linear coupling degree keeps proportionally following the power change, and is marked as a linear drift characteristic; if the absolute value of the coupling degree change rate index exceeds the zero-point drift tolerance range and shows a continuous positive increase or a negative step jump, it is determined that the electromechanical energy linear coupling degree deviates from the proportional constraint of power change, and is marked as a nonlinear distortion characteristic.

[0036] In this implementation scheme, the fundamental purpose of performing differential or statistical operations on the coupling degree evolution sequence is to analyze the stability of the electromechanical coupling relationship in the time dimension. During normal operation, although changes in illumination cause simultaneous changes in power and vibration, the ratio between the two (coupling degree) should remain relatively stable; this characteristic of slowly changing with illumination is called linear drift. Conversely, when mechanical failures occur, changes in the physical structure (such as impeller damage or bearing jamming) disrupt the original energy conversion ratio, leading to drastic fluctuations or monotonically shifting coupling degree, i.e., nonlinear distortion. The technical role of calculating the coupling degree change rate index is to quantify the degree of this stability disruption, thereby setting precise boundaries to distinguish between environmental impacts and equipment failures. The calculation model for this coupling degree change rate index is as follows: In the formula, The rate of change of coupling degree calculated at the current moment is used to characterize the degree of fluctuation in the electromechanical coupling relationship. The observation window width for statistical operations should be smaller than the typical duration of a sudden change in illumination (such as cloud cover) to ensure that rapid fault characteristics can be captured. The historical electromechanical energy linear coupling degree value within the observation window; The difference between the historical value and the value at the previous moment constitutes a first-order difference term. Current discrete sampling time index. In the judgment logic based on this index, the preset zero-point drift tolerance range is a key parameter. It is determined by recording the normal operating conditions under different lighting conditions throughout the day during the system installation and commissioning phase. The maximum value is multiplied by a safety factor of 1.2 to 1.5 to obtain a threshold. If the real-time index is lower than this threshold, it indicates that the energy conversion structure of the system has not changed and the vibration change is only caused by illumination; if it exceeds this threshold and exhibits a step or divergence, it is confirmed that the physical structure of the water pump unit has undergone nonlinear distortion.

[0037] Specifically, the judgment process for determining the operating state based on the characteristic range of the power-impedance sensitivity feature and the evolution of the electromechanical energy linear coupling degree is as follows: A multi-dimensional state identifier set is constructed, including sensitivity range identifiers, power trend identifiers, and coupling degree feature identifiers; when the sensitivity range identifier corresponds to a negative gradient characteristic range and the coupling degree feature identifier corresponds to a linear drift characteristic, a maximum power point tracking closed-loop control command is output to maintain normal system operation; when the sensitivity range identifier corresponds to a zero gradient characteristic range and the coupling degree feature identifier corresponds to a positive divergence state in the nonlinear distortion characteristic, overload protection logic is activated, and a shutdown alarm signal is output; when the sensitivity range identifier corresponds to a negative gradient characteristic range, the power trend identifier shows a continuously decreasing value, and the coupling degree feature identifier corresponds to a negative step jump state in the nonlinear distortion characteristic, underload protection logic is activated, and a delayed restart action is performed.

[0038] In this implementation scheme, the core technology of constructing a multi-dimensional state identifier set lies in the orthogonal fusion of the electrical characteristics of the power supply side and the mechanical characteristics of the load side in the time domain, thereby overcoming the limitations of single-dimensional judgment. By mapping sensitivity range, power trend, and coupling characteristics to a unified state space, the system can perform logical operations similar to truth tables, ensuring that each control action is supported by clear physical evidence. To mathematically describe this multi-condition joint decision-making logic process, a state-space mapping function is used to characterize the system's decision-making mechanism. The expression of this function is as follows: In the formula, The final running status determination result and control instructions executed by the system at the current moment; The maximum power point tracking closed-loop control command indicates that the system is in a healthy operating state. Overload protection logic instructions, corresponding to shutdown alarm actions; : Underload protection logic instruction, corresponding to a delayed restart action; The logical AND operator indicates that multiple conditions must be met simultaneously. Sensitivity range identifier variable, used to indicate the power-impedance sensitivity characteristics of the current power supply side; The negative gradient characteristic interval state value indicates that the system is in the adjustable active operating region; The zero gradient characteristic range state value indicates that the system is in the current saturation or electrical confinement region; : Coupling degree characteristic variable, used to indicate the current evolution state of electromechanical energy linear coupling degree; The linear drift characteristic value indicates that the mechanical vibration and electrical power maintain a normal following relationship. The positive divergence state value in the nonlinear distortion characteristics represents an abnormal increase in vibration amplitude relative to power; The negative step jump state value in the nonlinear distortion characteristics represents a cliff-like drop in vibration amplitude relative to power. Power trend indicator variable, reflecting the direction of change in steady-state DC power value; The value continuously decays, determined by summing the first-order power difference components over several control cycles. If this sum is negative and its absolute value exceeds 5% of the rated power, the setting is activated. Through this logic, the system first identifies the normal operating state. When the sensitivity is in the negative gradient range and the coupling degree shows linear drift, it indicates that although the photovoltaic power supply is affected by light fluctuations (leading to changes in power and impedance), it remains within the effective control range of the MPPT algorithm, and the pump's mechanical structure has not changed (vibration changes linearly with power). Therefore, the system maintains MPPT closed-loop control to avoid accidental shutdowns due to weather changes. Secondly, for overload or jamming faults, the system captures the contradictory characteristics of electrical and mechanical components. When the sensitivity enters the zero gradient range, it means the current has reached its limit, and the power supply cannot output more energy. If the coupling degree shows positive divergence at this time, it indicates that the mechanical vibration is abnormally severe under power constraints, which can only be due to impeller jamming or bearing damage causing a surge in mechanical impedance. Based on this logic, overload protection is triggered, effectively preventing motor burnout. Finally, for dry running or cavitation failures, the system utilizes the physical characteristics of a broken energy transfer chain. When power continuously decreases (appearing like weakening light) and sensitivity remains in a negative gradient (indicating the electrical side is still attempting adjustment), but the coupling degree experiences a negative step jump (vibration suddenly disappears), this reveals the absence of the load medium (water). Because in the presence of water, weakening light only leads to a proportional reduction in vibration, not a structural disappearance of the vibration signal. Based on this, the system determines it as dry running and executes underload protection, protecting the pump's mechanical seal and achieving automated unattended operation through a delayed restart mechanism.

[0039] Please see Figure 2A photovoltaic water pump inverter operation status analysis system includes the following modules: a feature extraction module, used to continuously sample the voltage and current signals on the DC side of the photovoltaic water pump inverter, extract the steady-state DC component characterizing the power supply level of the photovoltaic array and the dynamic ripple component characterizing the mechanical torque characteristics of the water pump unit through frequency domain separation, construct the equivalent impedance evolution value based on the steady-state DC component, and extract the mechanical load vibration amplitude based on the dynamic ripple component; a characteristic identification module, used to synchronously monitor the changing trends of the equivalent impedance evolution value and the power value in the steady-state DC component, construct a power-impedance sensitivity feature reflecting the output characteristics of the power supply side, and identify whether the current power-impedance sensitivity feature is in the negative gradient characteristic range or the zero gradient characteristic range; and a coupling analysis module, used to establish the electromechanical energy linear coupling degree between the mechanical load vibration amplitude and the power value in the steady-state DC component, and monitor the electromechanical energy linear coupling degree over time. The system analyzes the evolution of the axis to distinguish between linear drift characteristics caused by changes in light irradiance and nonlinear distortion characteristics caused by changes in the physical structure of the pump unit. A state determination module is used to perform operational state logic determination based on the characteristic range of the power-impedance sensitivity feature and the evolution of the electromechanical energy linear coupling degree: when the power-impedance sensitivity feature is in the negative gradient characteristic range and the electromechanical energy linear coupling degree exhibits linear drift characteristics, the system is determined to be in normal operation; when the power-impedance sensitivity feature is in the zero gradient characteristic range and the electromechanical energy linear coupling degree exhibits monotonically increasing nonlinear distortion characteristics, the system is determined to be in a pump mechanical overload or foreign object jamming state; when the power-impedance sensitivity feature is in the negative gradient characteristic range but the power value continues to drop, and the electromechanical energy linear coupling degree experiences a step-like decrease until it disappears, the system is determined to be in a pump no-load dry run or inlet suction state.

[0040] In this implementation scheme, the feature extraction module serves as the data sensing and preprocessing front-end of the system. Its core function is to reconstruct multi-dimensional physical information through single-point sampling. This module utilizes frequency domain separation technology to decouple the mixed DC-side electrical signals into two independent analytical dimensions: a steady-state DC component reflecting the energy supply capacity of the photovoltaic array, and a dynamic ripple component reflecting the mechanical torque pulsation of the water pump motor. Through this module, the system can simultaneously acquire the equivalent impedance evolution value characterizing the electrical load characteristics and the mechanical load vibration amplitude characterizing the mechanical operating state, based solely on the inverter's internal electrical data, without the need for additional external mechanical sensors. This provides an independent and clean data foundation for subsequent source-load decoupling analysis. The feature identification module primarily undertakes the qualitative analysis of the power supply side's electrical operating range. This module focuses not only on the absolute power value but also on the dynamic trend of power change with impedance, i.e., the power-impedance sensitivity characteristic. By constructing this characteristic, the module can physically identify whether the system is currently within the effective adjustment range of the photovoltaic cell's maximum power point tracking (negative gradient characteristic range) or has reached the current limit or is in an electrical saturation state (zero gradient characteristic range). This identification process provides the necessary electrical environment constraints for the entire fault diagnosis logic, ensuring that subsequent state determination is performed within a clearly defined power output characteristic context. The coupling analysis module verifies the physical consistency between energy input and mechanical output. Based on the principle of electromechanical energy conversion, this module establishes and monitors the linear coupling between mechanical vibration and electrical power. Under normal physical laws, the amplitude of mechanical vibration should change proportionally with the increase or decrease of input power. By monitoring the evolution of this coupling relationship in real time, this module can accurately distinguish between the overall linear drift of data caused by weather changes (light fluctuations) and the nonlinear distortion of the coupling relationship caused by changes in physical structure such as impeller damage and bearing wear. This effectively filters out interference from environmental factors and pinpoints the true mechanical fault characteristics. The state determination module, as the final decision-making center of the system, executes logical decisions based on the intersection of multi-dimensional features. This module orthogonally compares the electrical interval state output by the feature identification module with the mechanical coupling evolution state output by the coupling analysis module. By identifying specific combinations of features, such as a negative gradient interval combined with linear drift indicating normal operation, a zero gradient interval combined with nonlinear divergence indicating stalling, and a negative gradient interval combined with step disappearance indicating dry running, this module achieves accurate classification of the operating status of photovoltaic water pump systems. This judgment logic based on a multi-source evidence chain significantly improves the system's accuracy and robustness in identifying typical faults such as dry running and stalling under complex operating conditions.

[0041] In summary, this application has at least the following effects:

[0042] A method and system for analyzing the operating status of a photovoltaic water pump inverter are disclosed. By frequency-domain decoupling of the inverter's DC-side signal, a power-impedance sensitivity characteristic reflecting the power supply side output characteristics and an electromechanical energy linear coupling degree reflecting the load side response characteristics are constructed. This technical solution can accurately distinguish between linear parameter drift caused by fluctuations in the lighting environment and nonlinear distortion caused by mechanical faults in the water pump at the physical level, effectively solving the technical problem that traditional methods struggle to accurately identify early faults such as dry running and jamming under complex weather conditions. Furthermore, this method eliminates the need for external mechanical sensors, achieving deep perception and multi-dimensional logical judgment of the "source-load" status solely using internal inverter electrical data. This significantly improves the fault diagnosis accuracy, operational stability, and maintenance efficiency of photovoltaic water pump systems in unattended environments.

[0043] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0044] This invention is described with reference to flowchart illustrations and / or block diagrams of systems, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0045] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0046] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0047] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0048] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for analyzing the operating status of a photovoltaic water pump inverter, characterized in that, Includes the following steps: S1. Continuously sample the voltage and current signals on the DC side of the photovoltaic water pump inverter, extract the steady-state DC component that characterizes the power supply level of the photovoltaic array and the dynamic ripple component that characterizes the mechanical torque characteristics of the water pump unit through frequency domain separation, construct the equivalent impedance evolution value based on the steady-state DC component, and extract the mechanical load vibration amplitude based on the dynamic ripple component. S2. Simultaneously monitor the changes in the equivalent impedance evolution value and the power value in the steady-state DC component, construct a power-impedance sensitivity feature that reflects the output characteristics of the power supply side, and identify whether the current power-impedance sensitivity feature is in the negative gradient characteristic range or the zero gradient characteristic range. S3. Establish the electromechanical energy linear coupling degree between the mechanical load vibration amplitude and the power value in the steady-state DC component, and monitor the evolution of the electromechanical energy linear coupling degree on the time axis to distinguish the linear drift characteristics caused by changes in light irradiance from the nonlinear distortion characteristics caused by changes in the physical structure of the water pump unit. S4. Based on the characteristic range of the power-impedance sensitivity feature and the evolution of the electromechanical energy linear coupling degree, the system is judged to be in normal operation. When the power-impedance sensitivity feature is in the negative gradient characteristic range and the electromechanical energy linear coupling degree shows a linear drift characteristic, the system is judged to be in normal operation. When the power-impedance sensitivity feature is in the zero gradient characteristic range and the electromechanical energy linear coupling degree shows a monotonically increasing nonlinear distortion characteristic, the system is judged to be in the state of pump mechanical overload or foreign object jamming. When the power-impedance sensitivity feature is in the negative gradient characteristic range but the power value continues to drop and the electromechanical energy linear coupling degree drops sharply until it disappears, the system is judged to be in the state of pump no-load dry running or water inlet suction. The specific process of simultaneously monitoring the evolution of equivalent impedance and the changing trend of power value in steady-state DC component to construct a power-impedance sensitivity characteristic reflecting the output characteristics of the power supply side is as follows: Calculate the product of the steady-state DC voltage component and the steady-state DC current component to obtain the steady-state DC power value, and construct a differential observation window that includes the current time and historical time. Within the differential observation window, calculate the first-order difference component of the steady-state DC power value with respect to time, and the first-order difference component of the equivalent impedance evolution value with respect to time. Divide the first-order difference component of the steady-state DC power value by the first-order difference component of the equivalent impedance evolution value to obtain the power-impedance sensitivity coefficient characterizing the power response intensity caused by unit impedance change, and use this coefficient as the power-impedance sensitivity feature. The specific process for establishing the electromechanical energy linear coupling degree between the mechanical load vibration amplitude and the power value in the steady-state DC component, and monitoring the evolution of the electromechanical energy linear coupling degree on the time axis is as follows: Calculate the product of the steady-state DC component voltage and current to obtain the steady-state DC power value. Divide the mechanical load vibration amplitude by the steady-state DC power value, or the nonlinear mapping function value of the mechanical load vibration amplitude divided by the steady-state DC power value, to obtain the instantaneous coupling ratio. A first-in-first-out circular buffer is constructed to store the instantaneous coupling ratio. At each sampling update, the latest instantaneous coupling ratio is written to the head of the buffer and the oldest data is overwritten. The arithmetic mean or weighted average of all instantaneous coupling ratios in the buffer is calculated to generate the electromechanical energy linear coupling degree, forming a coupling degree evolution sequence that is continuously updated over time.

2. The method for analyzing the operating status of a photovoltaic water pump inverter according to claim 1, characterized in that: The specific process of continuously sampling the voltage and current signals on the DC side of the photovoltaic water pump inverter, and extracting the steady-state DC component characterizing the power supply level of the photovoltaic array and the dynamic ripple component characterizing the mechanical torque characteristics of the water pump unit through frequency domain separation is as follows: Establish a sliding time window containing sampling points of a preset length, input the DC side voltage signal and current signal within the sliding time window into a digital low-pass filter to filter out high-frequency noise and modulation harmonics above the cutoff frequency, and output steady-state DC voltage component and steady-state DC current component. The current operating fundamental frequency of the photovoltaic water pump inverter is synchronously tracked. A passband range with the operating fundamental frequency as the center frequency is set. The DC side current signal is input to a digital bandpass filter with variable parameters, and the AC component within the passband range is extracted to output the dynamic current ripple component.

3. The method for analyzing the operating status of a photovoltaic water pump inverter according to claim 2, characterized in that: The specific process of constructing the equivalent impedance evolution value based on the steady-state DC component and extracting the mechanical load vibration amplitude based on the dynamic ripple component is as follows: Perform a division operation between the steady-state DC voltage component and the steady-state DC current component to obtain the real-time impedance sampling value. Smooth the real-time impedance sampling values ​​of multiple consecutive sampling periods to generate the equivalent impedance evolution value. Perform Hilbert transform or absolute value detection on the dynamic current ripple component to obtain the instantaneous envelope of the dynamic current ripple component, calculate the effective value of the instantaneous envelope in a single power frequency cycle, and generate the mechanical load vibration amplitude.

4. The method for analyzing the operating status of a photovoltaic water pump inverter according to claim 1, characterized in that: The specific process for identifying whether the current power-impedance sensitivity characteristic is in a negative gradient characteristic range or a zero gradient characteristic range is as follows: The numerical polarity and amplitude range of the power-impedance sensitivity coefficient; If the power-impedance sensitivity coefficient is negative and the amplitude exceeds the preset dead zone threshold, it is determined that the power increases as the impedance decreases, and it is classified as a negative gradient characteristic range. If the amplitude of the power-impedance sensitivity coefficient falls within the preset zero dead zone range, or exhibits an alternating positive and negative oscillation near the zero point, it is determined that the power does not change with impedance or changes only slightly, and is classified as the zero gradient characteristic range.

5. The method for analyzing the operating status of a photovoltaic water pump inverter according to claim 1, characterized in that: The specific process for distinguishing between the linear drift characteristics caused by changes in light irradiance and the nonlinear distortion characteristics caused by changes in the physical structure of the water pump unit is as follows: Perform first-order difference operation or standard deviation statistical operation on the coupling degree evolution sequence to obtain the coupling degree change rate index; If the absolute value of the coupling degree change rate index remains within the preset zero-point drift tolerance range, it is determined that the electromechanical energy linear coupling degree follows the power change proportionally and is marked as a linear drift characteristic. If the absolute value of the coupling degree change rate index exceeds the zero-point drift tolerance range and shows a continuous positive increase or a negative step jump, it is determined that the electromechanical energy linear coupling degree is out of the proportional constraint of power change and is marked as a nonlinear distortion feature.

6. The method for analyzing the operating status of a photovoltaic water pump inverter according to claim 1, characterized in that: The judgment process for determining the operating state logic is as follows, based on the characteristic range of the power-impedance sensitivity feature and the evolution of the linear coupling degree of electromechanical energy: Construct a multi-dimensional state identifier set that includes sensitivity range identifiers, power trend identifiers, and coupling degree feature identifiers; When the sensitivity range identifier corresponds to the negative gradient characteristic range and the coupling degree characteristic identifier corresponds to the linear drift characteristic, the maximum power point tracking closed-loop control command is output to maintain the normal operation of the system. When the sensitivity range identifier corresponds to the zero gradient characteristic range and the coupling degree characteristic identifier corresponds to the positive divergence state in the nonlinear distortion characteristic, the overload protection logic is activated and a shutdown alarm signal is output. When the sensitivity range indicator corresponds to the negative gradient characteristic range, the power trend indicator shows a continuous decrease in value, and the coupling degree characteristic indicator corresponds to the negative step jump state in the nonlinear distortion characteristic, the underload protection logic is activated and a delayed restart action is performed.

7. A photovoltaic water pump inverter operation status analysis system, applied to the photovoltaic water pump inverter operation status analysis method according to any one of claims 1-6, characterized in that, Includes the following modules: The feature extraction module is used to continuously sample the voltage and current signals on the DC side of the photovoltaic water pump inverter. It extracts the steady-state DC component that characterizes the power supply level of the photovoltaic array and the dynamic ripple component that characterizes the mechanical torque characteristics of the water pump unit through frequency domain separation. It constructs the equivalent impedance evolution value based on the steady-state DC component and extracts the mechanical load vibration amplitude based on the dynamic ripple component. The feature identification module is used to simultaneously monitor the changing trends of the equivalent impedance evolution value and the power value in the steady-state DC component, construct a power-impedance sensitivity feature that reflects the output characteristics of the power supply side, and identify whether the current power-impedance sensitivity feature is in the negative gradient characteristic range or the zero gradient characteristic range. The coupling analysis module is used to establish the electromechanical energy linear coupling degree between the mechanical load vibration amplitude and the power value in the steady-state DC component, and to monitor the evolution of the electromechanical energy linear coupling degree on the time axis, so as to distinguish the linear drift characteristics caused by changes in light irradiance and the nonlinear distortion characteristics caused by changes in the physical structure of the water pump unit. The status determination module is used to perform operational status logic determination based on the characteristic range of the power-impedance sensitivity feature and the evolution of the electromechanical energy linear coupling degree: when the power-impedance sensitivity feature is in the negative gradient characteristic range and the electromechanical energy linear coupling degree exhibits linear drift characteristics, the system is determined to be in normal operation; when the power-impedance sensitivity feature is in the zero gradient characteristic range and the electromechanical energy linear coupling degree exhibits monotonically increasing nonlinear distortion characteristics, the system is determined to be in a pump mechanical overload or foreign object jamming state; when the power-impedance sensitivity feature is in the negative gradient characteristic range but the power value continues to drop and the electromechanical energy linear coupling degree undergoes a step drop until it disappears, the system is determined to be in a pump no-load dry running state or inlet end suction state. The specific process of simultaneously monitoring the evolution of equivalent impedance and the changing trend of power value in steady-state DC component to construct a power-impedance sensitivity characteristic reflecting the output characteristics of the power supply side is as follows: Calculate the product of the steady-state DC voltage component and the steady-state DC current component to obtain the steady-state DC power value, and construct a differential observation window that includes the current time and historical time. Within the differential observation window, calculate the first-order difference component of the steady-state DC power value with respect to time, and the first-order difference component of the equivalent impedance evolution value with respect to time. Divide the first-order difference component of the steady-state DC power value by the first-order difference component of the equivalent impedance evolution value to obtain the power-impedance sensitivity coefficient characterizing the power response intensity caused by unit impedance change, and use this coefficient as the power-impedance sensitivity feature. The specific process for establishing the electromechanical energy linear coupling degree between the mechanical load vibration amplitude and the power value in the steady-state DC component, and monitoring the evolution of the electromechanical energy linear coupling degree on the time axis is as follows: Calculate the product of the steady-state DC component voltage and current to obtain the steady-state DC power value. Divide the mechanical load vibration amplitude by the steady-state DC power value, or the nonlinear mapping function value of the mechanical load vibration amplitude divided by the steady-state DC power value, to obtain the instantaneous coupling ratio. A first-in-first-out circular buffer is constructed to store the instantaneous coupling ratio. At each sampling update, the latest instantaneous coupling ratio is written to the head of the buffer and the oldest data is overwritten. The arithmetic mean or weighted average of all instantaneous coupling ratios in the buffer is calculated to generate the electromechanical energy linear coupling degree, forming a coupling degree evolution sequence that is continuously updated over time.

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