CN-122015764-A - Dynamic monitoring and early warning method for sedimentation of photovoltaic bracket

CN122015764ACN 122015764 ACN122015764 ACN 122015764ACN-122015764-A

Abstract

The application relates to the technical field of photovoltaic support monitoring, in particular to a dynamic monitoring and early warning method for photovoltaic support settlement. The method comprises the steps of collecting displacement, acceleration and temperature at each moment of a monitoring position of a photovoltaic support, obtaining residual errors of the displacement and the acceleration at each moment of the monitoring position, respectively obtaining short-term residual error variance and long-term residual error variance of the displacement at the current moment of the monitoring position, fusing to obtain self-adaptive observation noise, correcting the temperature at the current moment of the monitoring position to obtain corrected self-adaptive observation noise of the displacement at the current moment, obtaining corrected self-adaptive observation noise of the acceleration at the current moment in a similar way, filtering the displacement and the acceleration at the current moment by using Kalman filtering to obtain filtered displacement and acceleration at the current moment, and carrying out sedimentation monitoring on the monitoring position of the photovoltaic support according to the filtered displacement and the acceleration at the current moment. The application can improve the accuracy of sedimentation monitoring of the photovoltaic bracket.

Inventors

GAO HANG
LIANG CHENGSHUN
LEI XILIANG

Assignees

陕西科大高新智慧能源科技有限公司

Dates

Publication Date: 20260512
Application Date: 20260204

Claims (7)

1. The dynamic monitoring and early warning method for the sedimentation of the photovoltaic bracket is characterized by comprising the following steps of: Acquiring the displacement, acceleration and temperature of a photovoltaic bracket at each moment of a monitoring position; acquiring a short-term residual error weighted average value and a long-term residual error weighted average value of the displacement at each moment of the monitoring position, acquiring a short-term residual error variance of the displacement at the current moment by utilizing the residual error of the displacement at the current moment and the short-term residual error weighted average value of the displacement at the previous moment of the current moment; acquiring a normalized short-term weight by utilizing a short-term residual error variance of displacement at the current moment and a short-term residual error variance of displacement at the moment before the current moment, acquiring adaptive observation noise of displacement at the current moment by utilizing the normalized short-term weight, the short-term residual error variance and the long-term residual error variance of displacement at the current moment, correcting the adaptive observation noise of displacement at the current moment by utilizing the temperature at the current moment of the monitoring position to acquire corrected adaptive observation noise of displacement at the current moment, and acquiring the corrected adaptive observation noise of acceleration at the current moment in a similar way; The displacement and the acceleration at the current moment are filtered by utilizing Kalman filtering based on the corrected adaptive observation noise of the displacement and the corrected adaptive observation noise of the acceleration at the current moment of the monitoring position to obtain the filtered displacement and acceleration at the current moment; and carrying out settlement monitoring on the monitoring position of the photovoltaic bracket according to the filtered displacement and acceleration at the current moment.
2. The method for dynamically monitoring and pre-warning sedimentation of a photovoltaic bracket according to claim 1, wherein the obtaining the short-term residual variance of the displacement at the current moment by using the residual of the displacement at the current moment and the short-term residual weighted average of the displacement at the moment before the current moment comprises: Setting a first weight and a second weight, taking the first weight as the weight of the short-term residual variance of the displacement at the moment before the current moment and the second weight as the weight of the short-term residual variance square, and carrying out weighted summation to obtain the short-term residual variance of the displacement at the current moment of the monitoring position.
3. The method for dynamically monitoring and pre-warning sedimentation of a photovoltaic bracket according to claim 1, wherein the step of obtaining the long-term residual variance of the displacement at the current moment by using the weighted average of the residual of the displacement at the current moment and the long-term residual of the displacement at the previous moment of the current moment of the monitoring position comprises the following steps: Setting a third weight and a fourth weight, taking the third weight as the weight of the long-term residual error variance of the displacement at the moment before the current moment and the fourth weight as the weight of the long-term residual error variance square, and carrying out weighted summation to obtain the long-term residual error variance of the displacement at the current moment of the monitoring position.
4. The method for dynamically monitoring and pre-warning sedimentation of a photovoltaic bracket according to claim 1, wherein the obtaining the normalized short-term weight by using the short-term residual variance of the displacement at the current time and the time before the current time comprises: and obtaining the difference absolute value of the short-term residual variance of the displacement between the current moment and the moment before the current moment of the monitoring position, and obtaining the normalized short-term weight by comparing the difference absolute value with the sum of the short-term residual variance of the displacement before the current moment and the super-parameters.
5. The method for dynamically monitoring and pre-warning sedimentation of a photovoltaic bracket according to claim 1, wherein the obtaining the adaptive observation noise of the displacement at the current moment by using the normalized short-term weight, the short-term residual variance and the long-term residual variance of the displacement at the current moment comprises: taking the normalized short-term weight as the weight of the short-term residual error variance of the displacement of the current moment of the monitoring position, taking the difference value of the first preset value and the normalized short-term weight as the weight of the long-term residual error variance of the displacement of the current moment of the monitoring position, and carrying out weighted summation on the short-term residual error variance and the long-term residual error variance of the displacement of the current moment of the monitoring position to obtain the self-adaptive observation noise of the displacement of the current moment.
6. The method for dynamically monitoring and early warning the sedimentation of a photovoltaic bracket according to claim 1, wherein the correcting the adaptive observation noise of the displacement at the current moment by using the temperature at the current moment of the monitoring position to correct the adaptive observation noise of the displacement at the current moment comprises the following steps: The method comprises the steps of taking the average value of temperatures at all moments of a monitoring position as a reference temperature of the monitoring position, obtaining the difference value of the maximum value and the minimum value of the temperatures at all moments of the monitoring position as the maximum temperature fluctuation range of the monitoring position, obtaining a temperature correction coefficient according to the temperature at the current moment of the monitoring position, the reference temperature of the monitoring position and the maximum temperature fluctuation range of the monitoring position, and multiplying the obtained temperature correction coefficient of the maximum temperature fluctuation range with the adaptive observation noise of the displacement at the current moment to obtain the corrected adaptive observation noise of the displacement at the current moment.
7. The method for dynamically monitoring and pre-warning sedimentation of a photovoltaic bracket according to claim 6, wherein the step of obtaining a temperature correction coefficient according to the temperature of the current moment of the monitoring position, the reference temperature of the monitoring position and the maximum temperature fluctuation range of the monitoring position comprises the following steps: and obtaining a temperature change coefficient by multiplying the maximum temperature fluctuation range of the monitoring position by the absolute value ratio of the difference between the temperature at the current moment of the monitoring position and the reference temperature of the monitoring position and the correction coefficient, and obtaining the temperature correction coefficient by subtracting the temperature change coefficient from a first preset value.

Description

Dynamic monitoring and early warning method for sedimentation of photovoltaic bracket Technical Field The invention relates to the technical field of photovoltaic support monitoring, in particular to a dynamic monitoring and early warning method for photovoltaic support settlement. Background The photovoltaic bracket is usually installed in an open and direct sunlight environment, and the temperature difference between day and night in the areas is large, wind load is obvious, the environment change is complex, and the micro deformation of the structure and the sensing measurement fluctuation are easily caused. In order to ensure the long-term safety and operation reliability of the photovoltaic system, the structural health state needs to be mastered in real time by a high-precision displacement or sedimentation monitoring means. At present, a Kalman filtering algorithm is generally adopted for a monitoring system of photovoltaic and similar light structures to smooth and noise inhibit observed data. The Kalman filtering has the characteristics of strong recursion, high instantaneity and capability of simultaneously estimating the system state and the observation error, and is widely applied to the fields of structural health monitoring and dynamic signal processing. The algorithm can effectively inhibit random noise, remarkably improve the accuracy and stability of data, and has good reliability and engineering adaptability in long-term monitoring of the system operation stage. However, in the construction and early running stages of the photovoltaic bracket, the field environment is complex and changeable, and the noise level of an observation signal is dynamically changed along with time due to factors such as mechanical vibration, wind load disturbance, construction operation and the like, so that the photovoltaic bracket has obvious non-stationary characteristics. The traditional Kalman filtering algorithm generally assumes that the variance of system noise and observed noise is fixed in application, when noise characteristics suddenly change or rapidly fluctuate, the filtering weight of the noise cannot be timely adjusted, and problems such as response lag, estimation offset or filtering divergence are easy to occur, so that the real-time performance and reliability of monitoring results are affected. Especially in the construction scene that the noise source is complicated and the signal fluctuation is frequent, the transient change rule of the observed data is difficult to be accurately reflected by the fixed noise model, and the filter has contradiction between noise suppression and dynamic response maintenance. Disclosure of Invention In order to solve the technical problems, the invention aims to provide a dynamic monitoring and early warning method for sedimentation of a photovoltaic bracket, which adopts the following technical scheme: the embodiment of the invention provides a dynamic monitoring and early warning method for photovoltaic bracket settlement, which comprises the following steps: Acquiring the displacement, acceleration and temperature of a photovoltaic bracket at each moment of a monitoring position; acquiring a short-term residual error weighted average value and a long-term residual error weighted average value of the displacement at each moment of the monitoring position, acquiring a short-term residual error variance of the displacement at the current moment by utilizing the residual error of the displacement at the current moment and the short-term residual error weighted average value of the displacement at the previous moment of the current moment; acquiring a normalized short-term weight by utilizing a short-term residual error variance of displacement at the current moment and a short-term residual error variance of displacement at the moment before the current moment, acquiring adaptive observation noise of displacement at the current moment by utilizing the normalized short-term weight, the short-term residual error variance and the long-term residual error variance of displacement at the current moment, correcting the adaptive observation noise of displacement at the current moment by utilizing the temperature at the current moment of the monitoring position to acquire corrected adaptive observation noise of displacement at the current moment, and acquiring the corrected adaptive observation noise of acceleration at the current moment in a similar way; The displacement and the acceleration at the current moment are filtered by utilizing Kalman filtering based on the corrected adaptive observation noise of the displacement and the corrected adaptive observation noise of the acceleration at the current moment of the monitoring position to obtain the filtered displacement and acceleration at the current moment; and carrying out settlement monitoring on the monitoring position of the photovoltaic bracket according to the filtered displacement and acceleration at the curr