Remote intelligent monitoring system based on wind power installation construction

Abstract

The invention relates to the technical field of construction monitoring, in particular to a remote intelligent monitoring system based on wind power installation construction, and the system is used for collecting environment data and construction data in the construction process, and comprises a wind speed sensor and a wave sensor which are arranged on an installation ship, and an attitude sensor and a vibration sensor which are arranged on a hoisting blade; the data analysis module is connected with the data acquisition module, and is used for calculating and obtaining an environment risk index and a stability index in the blade moving process according to the acquired data, and determining a construction mode based on a comparison result of the environment risk index and a preset risk index, and determining whether the construction is qualified or not or determining a monitoring strategy based on the stability index, and the control module is connected with the data analysis module and is used for adjusting the construction strategy and the monitoring strategy. According to the invention, the construction safety is improved.

Description

Technical Field

[0001] This invention relates to the field of construction monitoring technology, and in particular to a remote intelligent monitoring system based on wind power installation construction. Background Technology

[0002] With the continuous advancement of wind power technology, large-scale and intelligent technologies have become the mainstream trends in the development of wind power equipment. Offshore wind power installation faces harsh construction environments, including challenges from strong winds, giant waves, and ocean currents, placing extremely stringent demands on the stability, precision, and safety of construction equipment. Onshore wind farms, on the other hand, are often located in mountainous or desert areas with complex terrain and poor transportation, presenting numerous difficulties for the transportation and hoisting of large equipment.

[0003] Traditional wind power installation and construction monitoring primarily relies on manual inspections and on-site recording. This model has several drawbacks: Firstly, manual inspections are limited by personnel's physical strength, experience, and working hours, making it difficult to achieve real-time and comprehensive monitoring of the entire construction process. This can easily lead to the omission of critical information, resulting in the failure to promptly identify and address potential safety hazards. Secondly, the accuracy and consistency of on-site recorded data are difficult to guarantee, and data transmission and sharing efficiency is low, hindering construction managers from timely understanding of construction dynamics and making informed decisions. Furthermore, in the face of emergencies, traditional monitoring methods cannot respond quickly and provide effective countermeasures, easily causing serious consequences such as construction delays, equipment damage, and even personal injury or death.

[0004] Chinese Patent Application Publication No. CN117514647A discloses a tilt monitoring system for an offshore wind power installation platform, including a system data terminal, a monitoring system, a floating platform, a wind turbine, a tilt monitoring pan, a monitoring contact cylinder, a monitoring resistor rod, an adjustment sleeve, a diaphragm, and a monitoring liquid bag. The outer ring of the monitoring liquid bag contacts the diaphragm. Using this structure, the system senses the tilt state of the floating platform through the monitoring liquid bag. The uneven distribution of liquid inside the monitoring liquid bag due to tilt affects the force on the diaphragm, thus enabling the adjustment sleeve to rise and fall. The tilt attitude data is obtained by monitoring the change in resistance of the resistor rod. When the floating platform oscillates and shakes, the monitoring liquid bag maintains its original state and follows the oscillation of the floating platform. The data monitored by the resistor rod only fluctuates within the original tilt attitude data without changing the original tilt attitude data. Therefore, it effectively reduces the impact of marine environmental factors on platform tilt monitoring, thereby effectively improving the tilt monitoring effect of offshore wind power platforms.

[0005] However, the existing technology has the following problems: the existing technology does not take into account the impact of environmental factors on the operation during the installation and construction process, resulting in a high risk of construction safety. Summary of the Invention

[0006] To address this issue, the present invention provides a remote intelligent monitoring system based on wind power installation and construction, which overcomes the problem in the prior art that does not consider the impact of environmental factors on the operation during the installation and construction process, resulting in high construction safety risks.

[0007] To achieve the above objectives, the present invention provides a remote intelligent monitoring system based on wind power installation and construction, comprising: The data acquisition module is used to collect environmental and construction data during the construction process, including wind speed and wave sensors installed on the installation vessel, as well as attitude and vibration sensors installed on the lifting blades. The data analysis module, which is connected to the data acquisition module, is used to calculate and obtain the environmental risk index and the stability index during the blade movement process based on the acquired data, and to determine the construction mode based on the comparison result between the environmental risk index and the preset risk index, and to determine whether the construction is qualified or to determine the monitoring strategy based on the stability index. The control module, which is connected to the data analysis module, is used to adjust the construction strategy based on the deviation between the blade load fluctuation frequency and the hull floating frequency, and to adjust the preset risk index based on the difference between the average wind speed and the preset wind speed to adjust the monitoring strategy.

[0008] Furthermore, the data analysis module determines the construction mode based on the comparison between the environmental risk index and the preset risk index, wherein, Based on the comparison results that the environmental risk index is lower than the preset risk index, the construction mode is determined to be the first mode. Based on the comparison results of the environmental risk index being greater than or equal to the preset risk index, the construction mode is determined to be the second mode.

[0009] Furthermore, the environmental risk index is determined based on wind speed and wave height.

[0010] Furthermore, the first mode involves lifting the blade at a first preset speed and determining whether the construction is qualified based on a comparison between the stability index during the blade's movement and the first preset stability index. Based on the comparison result that the stability index is less than the first preset stability index, the construction is deemed unqualified, and the adjustment method of the construction strategy is determined based on the comparison result of the blade load fluctuation frequency and the hull floating frequency.

[0011] Furthermore, the second mode involves lifting the blade at a second preset speed and determining a monitoring strategy based on the stability index during the blade's movement.

[0012] Furthermore, the adjustment methods for the construction strategy in the first mode include: If the deviation between the blade load fluctuation frequency and the hull floating frequency is less than the preset deviation value, the adjustment method of the construction strategy is determined to be to reduce the first preset speed based on the difference between the hull floating frequency and the preset floating frequency. If the deviation between the blade load fluctuation frequency and the hull floating frequency is greater than or equal to the preset deviation value, the adjustment method of the construction strategy is determined to be to reduce the preset risk index based on the difference between the average wind speed and the preset wind speed.

[0013] Furthermore, the adjustment range of the first preset speed is positively correlated with the floating frequency difference, which is the difference between the hull floating frequency and the preset floating frequency.

[0014] Furthermore, the stability index is determined based on the vibration frequency and attitude angle standard deviation of the blade.

[0015] Furthermore, the monitoring strategy in the second mode includes: If the stability index is less than the second preset stability index, the monitoring strategy is determined to start high-frequency monitoring and issue an early warning signal based on the condition that the vibration frequency of the blade is greater than the preset frequency or the standard deviation of the blade's attitude angle is greater than the preset standard deviation. If the stability index is greater than or equal to the second preset stability index, then the monitoring strategy is determined to be to continuously monitor the environmental parameters and construction parameters during the construction process at the first monitoring frequency.

[0016] Furthermore, the adjustment range of the preset risk index is positively correlated with the wind speed difference, which is the difference between the average wind speed and the preset wind speed.

[0017] Compared with existing technologies, the advantages of this invention lie in its ability to collect environmental and construction data comprehensively during the construction process by setting up multiple sensors. This comprehensive data collection method enables construction personnel and systems to accurately grasp the real-time status of the construction site, providing a reliable basis for subsequent analysis and decision-making, and avoiding misjudgments and safety risks caused by incomplete information.

[0018] Furthermore, the data analysis module calculates the environmental risk index and the stability index during blade movement based on the collected data, and determines the construction mode based on the comparison between the environmental risk index and the preset risk index. Through quantitative analysis of environmental factors, the system can scientifically select the appropriate construction mode according to the actual environmental conditions, ensuring that construction can be carried out in the safest and most efficient way under different environments, effectively reducing the risk of construction accidents caused by environmental factors.

[0019] Furthermore, the control module is connected to the data analysis module, enabling dynamic adjustment of construction and monitoring strategies based on data analysis results. In the first mode, if the stability index fails to meet the standard, the system determines the adjustment method for the construction strategy based on the comparison between the blade load fluctuation frequency and the hull floating frequency. In the second mode, different monitoring strategies are determined based on the stability index. This dynamic adjustment mechanism allows the system to respond to changes during the construction process in real time, promptly address various complex situations, and further improve the safety and stability of the construction.

[0020] Furthermore, this invention employs reasonable parameter settings and calculation methods when determining various indices and adjustment strategies. For example, the environmental risk index is determined jointly by wind speed and wave height, the stability index is determined based on the blade vibration frequency and attitude angle standard deviation, the adjustment range of the first preset speed is positively correlated with the difference in floating frequency, and the adjustment range of the preset risk index is positively correlated with the difference in wind speed, etc., ensuring that the system is scientific and accurate in assessing construction risks and adjusting construction strategies, thereby effectively guaranteeing construction safety and quality.

[0021] Furthermore, in the second mode, the present invention determines different monitoring strategies based on the magnitude of the stability index. When the stability index is less than a second preset stability index, high-frequency monitoring is initiated and an early warning signal is issued under specific conditions; when the stability index is greater than or equal to the second preset stability index, continuous monitoring is conducted at a first monitoring frequency. This tiered monitoring and early warning mechanism can rationally allocate monitoring resources according to the urgency of the construction situation, ensuring timely detection and early warning in case of abnormalities, while avoiding unnecessary waste of resources and improving the efficiency of construction management. Attached Figure Description

[0022] Figure 1 This is a schematic diagram of the module connection of a remote intelligent monitoring system based on wind power installation and construction according to an embodiment of the present invention; Figure 2 This is a flowchart illustrating the determination of construction mode based on environmental risk index in an embodiment of the present invention; Figure 3 This is a flowchart illustrating how to determine whether construction is qualified based on the stability index during blade movement, according to an embodiment of the present invention. Figure 4 This is a flowchart illustrating how the adjustment method for the construction strategy is determined based on the comparison results between the blade load fluctuation frequency and the hull floating frequency in an embodiment of the present invention. Detailed Implementation

[0023] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0024] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0025] It should be noted that the data in this embodiment are all derived from a comprehensive analysis and evaluation of historical test data and corresponding historical test results from the three months prior to this test. Those skilled in the art will understand that the determination of the above-mentioned parameters for any single item in this invention can be achieved by selecting the value with the highest percentage based on the data distribution as the preset standard parameter, using weighted summation to obtain the value as the preset standard parameter, substituting each historical data point into a specific formula and using the value obtained from that formula as the preset standard parameter, or other selection methods, as long as the invention can clearly define different specific situations in the single-item judgment process through the obtained values.

[0026] Please see Figure 1 As shown, it is a schematic diagram of the module connection of the remote intelligent monitoring system based on wind power installation and construction according to an embodiment of the present invention; This invention relates to a remote intelligent monitoring system for wind power installation and construction, comprising: The data acquisition module is used to collect environmental and construction data during the construction process, including wind speed and wave sensors installed on the installation vessel, as well as attitude and vibration sensors installed on the lifting blades. The data analysis module, which is connected to the data acquisition module, is used to calculate and obtain the environmental risk index and the stability index during the blade movement process based on the acquired data, and to determine the construction mode based on the comparison result between the environmental risk index and the preset risk index, and to determine whether the construction is qualified or to determine the monitoring strategy based on the stability index. A control module, connected to the data analysis module, is used to adjust the construction strategy and monitoring strategy. The construction strategy includes reducing a first preset speed based on the difference between the hull floating frequency and a preset floating frequency, or reducing a preset risk index based on the difference between the average wind speed and a preset wind speed.

[0027] Specifically, the environmental data includes wind speed information at the installation work surface measured in real time by wind speed sensors installed on the installation vessel, and wave height, wave period, and six-degree-of-freedom motion information of the sea area where the hull is located measured in real time by wave sensors. Based on this, the hull floating frequency can be analyzed. The construction data includes pitch angle, roll angle, and yaw angle information of the blade in space measured in real time by attitude sensors installed on the lifting blade, and vibration acceleration and vibration frequency information of the blade during the lifting process due to wind load, motion, and structural response measured in real time by vibration sensors. By performing spectral analysis on the vibration signal and attitude change, the blade load fluctuation frequency characterizing the dynamic load characteristics of the blade can be extracted.

[0028] Please see Figure 2 As shown, it is a flowchart of determining the construction mode based on the environmental risk index in an embodiment of the present invention; Specifically, the data analysis module determines the construction mode based on the comparison between the environmental risk index and the preset risk index, wherein, Based on the comparison results that the environmental risk index is lower than the preset risk index, the construction mode is determined to be the first mode. Based on the comparison results of the environmental risk index being greater than or equal to the preset risk index, the construction mode is determined to be the second mode.

[0029] Specifically, the environmental risk index is determined by wind speed and wave height. The environmental risk index = first weighting coefficient × average wind speed / wind speed threshold + second weighting coefficient × average wave height / wave height threshold. The average wind speed and average wave height are calculated from data collected over a 5-minute monitoring period. The first weighting coefficient is 0.6, the wind speed threshold is 12 m / s, the second weighting coefficient is 0.4, and the wave height threshold is 1.5 m. It is understood that in this embodiment, the environmental risk index is determined based on wind speed and wave height because wind speed is the core driving force of ocean waves; the higher the wind speed, the higher the upper limit of the wave height it can generate. The currently monitored wave height is introduced as an important indicator of risk assessment because wind speed only manifests in wave height when it accumulates within a certain time frame, i.e., when it exerts a certain wind force. Therefore, wave height reflects the cumulative effect of current environmental risk, while wind speed reflects the magnitude of subsequent environmental risk. Hence, the environmental risk index is determined based on wind speed and wave height.

[0030] In this embodiment of the invention, the initial preset risk index is set to 0.8.

[0031] Please see Figure 3 As shown, it is a flowchart of the present invention for determining whether the construction is qualified based on the stability index during the blade movement process; Specifically, the first mode involves lifting the blade at a first preset speed and determining whether the construction is qualified based on a comparison between the stability index during the blade's movement and the first preset stability index. Based on the comparison result that the stability index is less than the first preset stability index, the construction is deemed unqualified, and the adjustment method of the construction strategy is determined based on the comparison result of the blade load fluctuation frequency and the hull floating frequency. Based on the comparison results where the stability index is greater than or equal to the first preset stability index, the construction is deemed qualified.

[0032] Specifically, the second mode involves lifting the blade at a second preset speed and determining a monitoring strategy based on the stability index during the blade's movement.

[0033] In this embodiment of the invention, the first preset speed is 8 m / min and the second preset speed is 3 m / min. However, the above values ​​are not limited to these. Those skilled in the art can adjust the above values ​​according to specific usage scenarios or actual needs.

[0034] Specifically, the stability index is determined by the blade's vibration frequency and attitude angle standard deviation. The stability index = third weighting coefficient × average blade vibration frequency / vibration frequency threshold + fourth weighting coefficient × average attitude angle standard deviation / attitude angle standard deviation threshold. The average blade vibration frequency and average attitude angle standard deviation are calculated from data collected over 30 seconds. The average attitude angle standard deviation is obtained by arithmetically averaging the standard deviations of the blade's pitch, roll, and yaw angles in space. The third weighting coefficient is 0.4, the vibration frequency threshold is 2.0 Hz, the fourth weighting coefficient is 0.6, and the attitude angle standard deviation threshold is 3°. It can be understood that the vibration frequency reflects the blade's inherent response characteristics under dynamic loads, directly related to structural fatigue and resonance risk; the attitude angle standard deviation quantifies the blade's ability to maintain its spatial attitude, determining the controllability of its trajectory and collision risk. Both correspond to the most critical sources of structural damage and collision risks in offshore lifting operations.

[0035] Understandably, when the environmental risk index is lower than the preset risk index, it indicates that the current wind speed and wave height are relatively low, and the impact of the environment on construction safety is relatively controllable. At this time, the system will adopt the first mode, which allows for higher operating efficiency under conditions of minimal environmental interference, while focusing the core of monitoring and judgment on the dynamic performance of the blades themselves, that is, determining whether the construction is qualified based on the stability index.

[0036] When the environmental risk index is greater than or equal to the preset risk index, it indicates that the combined risk of wind and waves has reached a high level. At this time, the system activates the second mode, reducing dynamic loads by decreasing speed. The system no longer relies on a single fixed threshold for qualification determination, but instead dynamically selects monitoring strategies based on the real-time stability index, thereby enhancing the system's state awareness and strategy flexibility to cope with environmental uncertainties.

[0037] Please see Figure 4 As shown, it is a flowchart of the method for adjusting the construction strategy based on the comparison results of the blade load fluctuation frequency and the hull floating frequency in an embodiment of the present invention. Specifically, the adjustment methods for the construction strategy in the first mode include: If the deviation between the blade load fluctuation frequency and the hull floating frequency is less than the preset deviation value, the adjustment method of the construction strategy is determined to be to reduce the first preset speed based on the difference between the hull floating frequency and the preset floating frequency. If the deviation between the blade load fluctuation frequency and the hull floating frequency is greater than or equal to the preset deviation value, the adjustment method of the construction strategy is determined to be to reduce the preset risk index based on the difference between the average wind speed and the preset wind speed.

[0038] In this embodiment of the invention, the preset deviation value is 8% of the hull floating frequency, but this value is not limited to this, and those skilled in the art can adjust the value according to actual needs.

[0039] Understandably, comparing the blade load fluctuation frequency and the hull floating frequency can help determine whether the primary source of blade instability is waves or wind speed. If the deviation is less than a preset deviation value, it indicates that the blade and hull movements are highly synchronized in frequency. This usually means that resonance or forced vibration coupling has occurred between them. This motion is transmitted to the blade through the hoisting mechanism, significantly amplifying its oscillation amplitude. In this case, the influence of waves is dominant, and the instability is essentially a matching problem of the mechanical system. Therefore, reducing the first preset speed can adjust the dynamic response characteristics of the system, slightly shifting its natural frequency, thereby breaking the resonance condition with the hull floating frequency. At the same time, a slower and smoother motion can reduce the intensity of the hull excitation transmitted to the blade, suppressing oscillation from the energy input perspective.

[0040] If the deviation value is greater than or equal to the preset deviation value, it indicates that the abnormal blade oscillation is mainly caused by aerodynamic excitation, such as non-periodic gusts of wind, vortex shedding, or the aeroelastic response of the blade itself. Based on this, the system adopts a strategy of reducing the preset risk index. This adjustment will immediately trigger the operation mode to automatically switch from the first mode to the more conservative second mode, thereby systematically reducing the lifting speed to the second preset speed and shifting the monitoring focus to a dynamically adaptive monitoring strategy.

[0041] Specifically, the adjustment range of the first preset speed is positively correlated with the floating frequency difference. If the floating frequency difference is less than the preset floating frequency difference, the first preset speed is reduced to the corresponding value using the first speed adjustment coefficient. If the floating frequency difference is greater than or equal to the preset floating frequency difference, the first preset speed is reduced to the corresponding value using the second speed adjustment coefficient; The floating frequency difference is the difference between the hull floating frequency and the preset floating frequency; The adjusted first preset speed is the product of the original first preset speed and the corresponding speed adjustment coefficient.

[0042] In this embodiment of the invention, the preset floating frequency difference is 0.05Hz, the first speed adjustment coefficient is 0.75, and the second speed adjustment coefficient is 0.5. However, the above values ​​are not limited to these, and those skilled in the art can adjust the above values ​​according to actual needs.

[0043] Specifically, the adjustment range of the preset risk index is positively correlated with the wind speed difference. If the wind speed difference is less than the preset wind speed difference, the first index adjustment coefficient is used to reduce the preset risk index to the corresponding value. If the wind speed difference is greater than or equal to the preset wind speed difference, the preset risk index will be reduced to the corresponding value using the second index adjustment coefficient. The wind speed difference is the difference between the average wind speed and the preset wind speed; The adjusted preset risk index is the product of the original preset risk index and the corresponding index adjustment coefficient.

[0044] In this embodiment of the invention, the preset wind speed is 10 m / s, the preset wind speed difference is 2 m / s, the first index adjustment coefficient is 0.85, and the second index adjustment coefficient is 0.72. However, the above values ​​are not limited to these values, and those skilled in the art can adjust the above values ​​according to actual needs.

[0045] Specifically, the monitoring strategy in the second mode includes: If the stability index is less than the second preset stability index, the monitoring strategy is determined to start high-frequency monitoring and issue an early warning signal based on the condition that the vibration frequency of the blade is greater than the preset frequency or the standard deviation of the blade's attitude angle is greater than the preset standard deviation. If the stability index is greater than or equal to the second preset stability index, then the monitoring strategy is determined to be to continuously monitor the environmental parameters and construction parameters during the construction process at the first monitoring frequency.

[0046] In this embodiment of the invention, the second preset stability index is 0.6, the high-frequency monitoring frequency is 10Hz, the preset frequency is 1.2Hz, the preset standard deviation is 5°, and the first monitoring frequency is 1Hz. However, the above values ​​are not limited to these, and those skilled in the art can adjust the above values ​​according to actual needs.

[0047] Understandably, when the stability index is greater than or equal to the second preset stability index, it indicates that the system is in a range where the risk is controllable but requires continuous monitoring. In this case, using a lower first monitoring frequency is sufficient to track the trend changes in environmental and construction parameters, meeting basic monitoring needs while minimizing the system load on data acquisition, transmission, and processing, thus reflecting the project's economic efficiency. Conversely, when the stability index is less than the second preset stability index, it signifies that the system has entered a warning zone of increased risk and potential instability. At this point, high-frequency monitoring needs to be initiated to obtain high-resolution dynamic data, accurately capturing high-frequency vibrations and transient large swings that may trigger accidents, providing a data foundation for early warning.

[0048] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

[0049] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A remote intelligent monitoring system based on wind power installation and construction, characterized in that, include: The data acquisition module is used to collect environmental and construction data during the construction process, including wind speed and wave sensors installed on the installation vessel, as well as attitude and vibration sensors installed on the lifting blades. The data analysis module, which is connected to the data acquisition module, is used to calculate the environmental risk index and the stability index during the blade movement process based on the acquired data, and to determine the construction mode based on the comparison result between the environmental risk index and the preset risk index, and to determine whether the corresponding construction mode is qualified based on the stability index to determine the corresponding monitoring strategy. The control module, which is connected to the data analysis module, is used to adjust the construction strategy based on the deviation between the blade load fluctuation frequency and the hull floating frequency, and to adjust the preset risk index based on the difference between the average wind speed and the preset wind speed to adjust the monitoring strategy.

2. The remote intelligent monitoring system based on wind power installation and construction as described in claim 1, characterized in that, The data analysis module determines the construction mode based on the comparison between the environmental risk index and the preset risk index, wherein... Based on the comparison results that the environmental risk index is lower than the preset risk index, the construction mode is determined to be the first mode. Based on the comparison results of the environmental risk index being greater than or equal to the preset risk index, the construction mode is determined to be the second mode.

3. The remote intelligent monitoring system based on wind power installation and construction according to claim 2, characterized in that, The environmental risk index is determined based on wind speed and wave height.

4. The remote intelligent monitoring system based on wind power installation and construction according to claim 3, characterized in that, The first mode involves lifting the blade at a first preset speed and determining whether the construction is qualified based on a comparison between the stability index during the blade's movement and the first preset stability index. Based on the comparison result that the stability index is less than the first preset stability index, the construction is deemed unqualified, and the adjustment method of the construction strategy is determined based on the comparison result of the blade load fluctuation frequency and the hull floating frequency.

5. The remote intelligent monitoring system based on wind power installation and construction according to claim 4, characterized in that, The second mode involves lifting the blade at a second preset speed and determining a monitoring strategy based on the stability index during the blade's movement.

6. The remote intelligent monitoring system based on wind power installation and construction according to claim 5, characterized in that, The adjustment methods for the construction strategy in the first mode include: If the deviation between the blade load fluctuation frequency and the hull floating frequency is less than the preset deviation value, the adjustment method of the construction strategy is determined to be to reduce the first preset speed based on the difference between the hull floating frequency and the preset floating frequency. If the deviation between the blade load fluctuation frequency and the hull floating frequency is greater than or equal to the preset deviation value, the adjustment method of the construction strategy is determined to be to reduce the preset risk index based on the difference between the average wind speed and the preset wind speed, so as to redetermine the construction mode.

7. The remote intelligent monitoring system based on wind power installation and construction according to claim 6, characterized in that, The adjustment range of the first preset speed is positively correlated with the floating frequency difference, which is the difference between the hull floating frequency and the preset floating frequency.

8. The remote intelligent monitoring system based on wind power installation and construction according to claim 1, 3, or 5, characterized in that, The stability index is determined based on the blade's vibration frequency and attitude angle standard deviation.

9. The remote intelligent monitoring system based on wind power installation and construction according to claim 5, characterized in that, The monitoring strategy in the second mode includes: If the stability index is less than the second preset stability index, the monitoring strategy is determined to start high-frequency monitoring and issue an early warning signal based on the condition that the vibration frequency of the blade is greater than the preset frequency or the standard deviation of the blade's attitude angle is greater than the preset standard deviation. If the stability index is greater than or equal to the second preset stability index, then the monitoring strategy is determined to be to continuously monitor the environmental parameters and construction parameters during the construction process at the first monitoring frequency. The detection frequency of the high-frequency monitoring is more than 5 times that of the first monitoring frequency.

10. The remote intelligent monitoring system based on wind power installation and construction according to claim 9, characterized in that, The adjustment range of the preset risk index is positively correlated with the wind speed difference, which is the difference between the average wind speed and the preset wind speed.

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