Multi-parameter on-line monitoring system for aging failure of insulating scaffold and preparation method of multi-parameter on-line monitoring system

Abstract

The invention discloses a multi-parameter online monitoring system for aging failure of an insulating scaffold and a preparation method of the multi-parameter online monitoring system. The monitoring system comprises the insulating scaffold; the monitoring sensor is arranged on the insulating scaffold and is used for acquiring various state parameters of the insulating scaffold; the communication module is connected with the monitoring sensor and is used for transmitting the various state parameters; the on-line monitoring all-in-one machine is connected with the communication module and is used for carrying out data acquisition and comprehensive processing analysis on the signal data of the various state parameters so as to monitor the state of the insulating scaffold in real time and evaluate the aging failure risk of the insulating scaffold; the system can monitor the operation state of the scaffold in a multi-dimensional and real-time manner, and comprehensively analyzes the change trend of the parameters, so that the aging process and failure risk of the scaffold material can be more accurately judged, the abnormality can be timely found, the early warning can be performed in advance, and the occurrence of safety accidents can be prevented.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of online monitoring devices, and particularly relates to a multi-parameter online monitoring system for aging failure of an insulating scaffold and a preparation method thereof. BACKGROUND

[0002] During long-term operation of electrical equipment, regular testing, inspection and maintenance are necessary. In some areas with complex terrain and harsh operating environment, scaffolds become an important support to ensure smooth operation. Currently, glass fiber tube insulating scaffolds are commonly used in the market, but their cost is relatively high and there is still room for improvement in some aspects. Traditional bamboo scaffolds have been gradually eliminated due to their low safety in construction and their inability to meet modern high-standard safety requirements. In view of these shortcomings, a new type of steel core insulating scaffold has been developed. This scaffold not only inherits the advantages of high strength and good durability of steel, but also significantly improves the overall insulation performance through advanced insulation materials and design, effectively blocking current conduction and greatly reducing the risk of electric shock and fire. At the same time, the new steel core insulating scaffold optimizes the insulation margin and insulation distance, improving the safety protection during construction. More importantly, under the premise of ensuring high safety, its cost is much lower than that of existing glass fiber tube insulating scaffolds, facilitating large-scale deployment and application, thereby greatly improving construction efficiency and economic benefits. Based on the above advantages, the new steel core insulating scaffold has broad market prospects and promotional value, and is an inevitable choice to meet the growing demand for current electrical facility maintenance.

[0003] New insulating scaffolds are usually used in outdoor or industrial sites, where the environmental conditions are complex and variable, especially extreme conditions such as high temperature and high humidity, which pose a severe test to material performance. In hot summer, high temperature can accelerate the molecular chain rupture of the polymer inside the insulating coating, leading to a decrease in coating hardness and an increase in brittleness, and then causing the generation of micro-cracks. Moreover, in humid environments, water can easily penetrate into the coating interface through small defects, causing the insulating material to swell due to water absorption, reducing its electrical insulation performance and accelerating chemical degradation. In addition, repeated changes in temperature can cause thermal expansion and contraction of the coating, forming thermal mechanical stress, which can further exacerbate the fatigue aging of the coating under long-term cyclic action. External factors such as dust and corrosive gases in complex environments can also cause physical and chemical reactions with the coating surface, leading to local peeling or deterioration of the coating. Considering these harsh working conditions, the insulating coating of the new insulating scaffold is prone to performance degradation or even failure, directly affecting the safety and service life of the scaffold. Therefore, monitoring and early warning of coating aging failure under complex working conditions are particularly important.

[0004] The new type of insulated scaffold often faces challenges of complex and changeable environmental conditions in practical application, such as high temperature, high humidity, dust, corrosive gas and the like, which are combined with multiple factors, and these complex working conditions are prone to cause multiple forms of aging and failure of the insulation coating and structural materials. The monitoring of a single parameter is often difficult to comprehensively reflect the health status of the scaffold, and potential safety hazards are easily missed.

[0005] In the prior art, although some insulated scaffolds are equipped with online monitoring devices, the functions and monitoring signal types thereof are relatively single, and it is difficult to meet the comprehensive safety management requirements. First, the existing scaffold online monitoring devices mainly focus on the monitoring of electrical leakage signals, mainly using current sensors to monitor leakage current, but lack of synchronous monitoring of environmental parameters, and cannot comprehensively reflect the influence of scaffold material state and environment on the insulation performance. Second, although a few systems increase temperature or humidity sensors, they mainly monitor a single environmental factor, lack of monitoring of key environmental indicators such as dew point, and lead to lagging warning of possible moisture or performance reduction of the insulation layer. In addition, the existing monitoring devices generally lack multi-sensor data fusion and intelligent analysis capability, so that the monitoring data is scattered, and an accurate judgment of the overall insulation state of the scaffold cannot be made, which reduces the monitoring effect and maintenance efficiency.

[0006] Therefore, the scaffold online monitoring device in the prior art has obvious deficiencies in the types of monitoring signals, coverage and data processing capability, and it is difficult to realize comprehensive, accurate and real-time monitoring of the insulation performance of the scaffold. SUMMARY

[0007] In view of the above technical problems, the present application provides a multi-parameter online monitoring system for aging and failure of an insulated scaffold and a preparation method thereof, which can multi-dimensionally and real-timely monitor the running state of the scaffold, and can more accurately judge the aging process and failure risk of the scaffold material by comprehensively analyzing the change trend of these parameters, so as to timely find abnormalities, give early warning and prevent safety accidents; such multi-parameter real-time monitoring not only improves the accuracy and reliability of the monitoring, but also provides more scientific decision basis for maintenance personnel, thereby effectively prolonging the service life of the scaffold, ensuring construction safety and stable operation of equipment.

[0008] To achieve the above technical purposes, the technical scheme adopted by the present application is as follows: the multi-parameter online monitoring system for aging and failure of an insulated scaffold comprises: an insulated scaffold; a monitoring sensor disposed on the insulated scaffold and used for acquiring multiple state parameters of the insulated scaffold; a communication module connected with the monitoring sensor and used for transmitting the multiple state parameters; An online monitoring integrated machine connected with the communication module is used for data collection and comprehensive processing analysis of the signal data of the multiple state parameters, so as to monitor the state of the insulating scaffold in real time and evaluate the aging failure risk thereof.

[0009] The monitoring sensor is arranged on the insulating scaffold, and the multiple state parameters acquired by the monitoring sensor are transmitted to the real-time monitoring integrated machine through the communication module. The online monitoring integrated machine collects and processes the transmitted multiple state parameters, can multi-dimensionally and in real time monitor the running state of the scaffold, can more accurately judge the aging process and failure risk of the scaffold material by comprehensively analyzing the change trend of the parameters, can timely find the abnormality, give early warning, and prevent safety accidents.

[0010] Further, the monitoring sensor comprises a micro-current sensor, a temperature sensor, a humidity sensor and a dew point sensor.

[0011] The micro-current sensor, the temperature sensor, the humidity sensor and the dew point sensor are integrated, four data of leakage current, temperature, humidity and dew point can be monitored in real time during the use of the insulating scaffold, the running state of the scaffold can be multi-dimensionally and in real time monitored, and the health condition of the insulating scaffold can be predicted and analyzed through the analysis of the four data.

[0012] Further, the insulating scaffold adopts a metal scaffold as a base material, and an epoxy resin insulation layer is coated on the surface of the metal scaffold; the micro-current sensor is arranged on the metal part of the insulating scaffold; and the temperature sensor, the humidity sensor and the dew point sensor are arranged on the surface of the epoxy resin insulation layer of the insulating scaffold.

[0013] Further, the micro-current sensor is arranged in an environment free of conductive dust, corrosive gas, strong impact and vibration, so as to prevent external environmental interference; and the connecting line used for the arrangement of the micro-current sensor is shielded to avoid electromagnetic interference; when the temperature sensor, the humidity sensor and the dew point sensor are arranged, the direct sunlight, strong wind and areas close to high-voltage power lines are avoided, so as to prevent external environmental interference, the on-site environmental temperature is kept between-20 DEG C and 60 DEG C, and the relative humidity is not more than 95%, so as to avoid the influence of sensor dew on reading stability, and shockproof and shock-absorbing measures are adopted to ensure firm arrangement.

[0014] Further, when the online monitoring all-in-one machine starts the self-checking program, the current output of the micro-current sensor is 0-10 muA, and the fluctuation is kept within ±0.1 muA, ensuring the sensitivity and accuracy; the error of the temperature reading of the temperature sensor is not more than ±0.5℃, the error of the humidity reading of the humidity sensor is within ±2% relative humidity range; the data sampling frequency range of the online monitoring all-in-one machine is 0.1 Hz-10 Hz, and the collection time is not less than 10 minutes.

[0015] Further, when the current data of the micro-current sensor jumps over the set early warning threshold value 10 mA and the duration exceeds 10 seconds, the system sends an early warning prompt; when it exceeds the alarm threshold value 15 mA, the system immediately sends an alarm; when the humidity data of the humidity sensor exceeds 95% and the duration exceeds 10 seconds, the system automatically sends an alarm prompt; when the temperature data of the temperature sensor exceeds 70℃ and the duration exceeds 10 seconds, the system sends an early warning signal; when the dew point data of the dew point sensor is below 0℃ and the duration exceeds 10 seconds, the system sends an early warning signal.

[0016] Further, the communication module is connected through an RS485 converter.

[0017] Further, the online monitoring all-in-one machine comprises a data acquisition module, a monitoring touch screen and a neural network analysis module; the data acquisition module is connected with the monitoring sensor through the communication module; the monitoring touch screen is used for the man-machine interaction of the operator and the online monitoring all-in-one machine; and the neural network analysis module is used for the comprehensive data processing of the multiple state parameters, so as to analyze and predict the health degree of the insulating scaffold.

[0018] The application also provides a preparation method of the multi-parameter online monitoring system for the aging failure of the insulating scaffold.

[0019] To achieve the technical purpose, the technical scheme adopted is that the preparation method comprises the following steps: S1: preparing an insulating scaffold: taking a metal scaffold as a base material, polishing and cleaning the surface, then coating an insulating epoxy resin coating, and forming an insulating scaffold after curing; S2: arranging the monitoring sensor of the multiple state parameters on the insulating scaffold, and connecting the monitoring sensor with the online monitoring all-in-one machine through the communication module; the communication module transmits the multiple state parameters acquired by the monitoring sensor to the online monitoring all-in-one machine. S3: The online monitoring all-in-one machine is preheated, self-checked, and data of the multi-state parameter signal is collected according to a set sampling frequency and time, and is displayed in real time on a touch screen of the online monitoring all-in-one machine, and a signal is sent when the monitoring data exceeds a set threshold value; S4: A plurality of data is collected, a neural network in the online monitoring all-in-one machine is trained, and then the neural network is modularly packaged, so as to predict and analyze the health degree of the insulating scaffold, and a signal is sent when the prediction data exceeds a set threshold value; S5: The surface of the monitoring sensor is cleaned regularly, and the integrity of the connecting wire and the interface in the system is checked; the system is tested and calibrated comprehensively regularly, standardized adjustment is performed by using a professional calibration device, and the reliability and stability of the measurement data are ensured.

[0020] Further, in the step S1, curing is performed by baking at a temperature ranging from 80 to 90 DEG C; after the insulating epoxy resin paint is completely cured, the surface of the scaffold is sprayed with the insulating epoxy resin paint again until the thickness of the epoxy resin insulating layer on the surface of the scaffold is greater than 2 mm.

[0021] Compared with the prior art, the beneficial effects of the present application are that by integrating a plurality of state parameter monitoring sensors, synchronous and real-time monitoring of the leakage current and environmental parameters on the surface of the scaffold is realized; by using a computer system to intelligently analyze the collected data, the change of the insulating performance of the scaffold and the environmental influencing factors can be accurately judged, and the deterioration or abnormal state of the insulating layer can be found in time; the online monitoring capability of the safety performance of the scaffold is effectively improved, which helps to prevent electrical safety hazards caused by insulating failure, and ensures the safety of personnel and equipment at the construction site. In addition, the service life of the scaffold is prolonged, the maintenance cost is reduced, and the efficiency and reliability of the site safety management are significantly improved through early warning and scientific maintenance guidance. BRIEF DESCRIPTION OF DRAWINGS

[0022] The present application will be further described in detail below in combination with the drawings and embodiments of the present application: Figure 1 is a schematic diagram of the multi-parameter online monitoring system for the aging failure of the insulating scaffold of the present application Figure 1 ; Figure 2 is a schematic diagram of the multi-parameter online monitoring system for the aging failure of the insulating scaffold of the present application Figure 2 ; Figure 3 is a visual interface diagram of the touch screen of the online monitoring all-in-one machine of the present application Figure 1 ; Figure 4 is a visual interface diagram of the touch screen of the online monitoring all-in-one machine of the present applicationFigure 2 ; Figure 5 is a schematic diagram of a neural network derived prediction module of the present application; Figure 6 is a schematic diagram of partial collection data of leakage current in the present application; Figure 7 is a schematic diagram of the predicted value of the leakage current collection data under 1 mA in the present application; Figure 8 is a schematic diagram of partial collection data of temperature, humidity, dew point in the present application; Figure 9 is a schematic diagram of the predicted value of temperature, humidity, dew point collection data under 22℃, 50RH, 0℃ respectively in the present application. DETAILED DESCRIPTION

[0023] In order to deepen the understanding of the present application, the present application will be further described in detail below in combination with the drawings and examples, which are only used to explain the present application and do not constitute a limitation on the protection scope of the present application.

[0024] As shown in Figures 1-9 , the present application is directed to a multi-parameter online monitoring system for aging failure of an insulating scaffold, comprising: an insulating scaffold; a monitoring sensor, which is arranged on the insulating scaffold, for acquiring a plurality of state parameters of the insulating scaffold; a communication module, which is connected with the monitoring sensor, for transmitting the plurality of state parameters; an online monitoring all-in-one machine, which is connected with the communication module, for collecting and comprehensively processing and analyzing signal data of the plurality of state parameters, so as to monitor the state of the insulating scaffold in real time and evaluate the aging failure risk thereof.

[0025] The present application can monitor the running state of the scaffold in multiple dimensions and in real time by arranging the monitoring sensor on the insulating scaffold, transmitting the plurality of state parameters acquired by the monitoring sensor to the real-time monitoring all-in-one machine through the communication module, and collecting, processing and analyzing the plurality of state parameters transmitted by the online monitoring all-in-one machine, and can more accurately judge the aging process and failure risk of the scaffold material by comprehensively analyzing the change trend of these parameters, timely discover abnormalities, give early warning, and prevent safety accidents from occurring.

[0026] The monitoring sensor comprises a micro-current sensor, a temperature sensor, a humidity sensor and a dew point sensor. In the present embodiment, the temperature sensor, the humidity sensor and the dew point sensor are integrated all-in-one sensors.

[0027] The insulating scaffold is based on a metal scaffold, and an epoxy resin insulation layer is coated on the surface of the metal scaffold; the micro-current sensor is arranged on the metal part of the insulating scaffold; and the temperature sensor, the humidity sensor and the dew point sensor are arranged on the surface of the epoxy resin insulation layer of the insulating scaffold.

[0028] Further, the multi-parameter online monitoring system further comprises an acousto-optic alarm arranged on the insulating scaffold and connected to the online monitoring all-in-one machine through a communication module, as shown in Figures 1-2

[0029] The micro-current sensor is arranged in an environment free of conductive dust, corrosive gas, strong impact and vibration to prevent external environmental interference; and the connecting line used for the arrangement of the micro-current sensor is shielded to avoid electromagnetic interference; when the temperature sensor, the humidity sensor and the dew point sensor are arranged, sunlight, strong wind and areas close to high-voltage power lines are avoided to prevent external environmental interference, the field environment temperature is kept between -20℃ and 60℃, and the relative humidity is not more than 95% to avoid the influence of sensor dew on reading stability, and shock absorption measures are adopted to ensure firm arrangement.

[0030] When the online monitoring all-in-one machine starts the self-checking program, the current output of the micro-current sensor is 0~10 μA, and the fluctuation is kept within ±0.1 μA, to ensure the sensitivity and accuracy; the error of the temperature reading of the temperature sensor is not more than ±0.5℃, and the error of the humidity reading of the humidity sensor is within ±2% relative humidity; the data sampling frequency range of the online monitoring all-in-one machine is 0.1 Hz~10 Hz, and the collection time is not less than 10 minutes.

[0031] When the current data jump of the micro-current sensor exceeds the set early warning threshold value 10 mA and the duration exceeds 10 seconds, the system issues a pre-warning prompt; when the alarm threshold value 15 mA is exceeded, an alarm is immediately issued; when the humidity data of the humidity sensor exceeds 95% and the duration exceeds 10 seconds, the system automatically issues an alarm prompt; when the temperature data of the temperature sensor exceeds 70℃ and the duration exceeds 10 seconds, the system issues a pre-warning signal; in this embodiment, the alarm threshold value of the dew point sensor is set at 0℃, and when the temperature is lower than 0℃ and the duration exceeds 10 seconds, the system issues a pre-warning signal, and the value range of this threshold value depends on the initial dew point value collected at the time.

[0032] The communication module is connected in communication through an RS485 converter.

[0033] ​The online monitoring all-in-one machine comprises a data acquisition module, a monitoring touch screen and a neural network analysis module; the data acquisition module is connected with the monitoring sensor through the communication module; the monitoring touch screen is used for human-computer interaction between the operator and the online monitoring all-in-one machine, and can display the monitoring data of multiple parameters in real time and compare with historical data, as shown in Figures 3-4 The neural network analysis module is used for comprehensive data processing of the multiple state parameters, so as to analyze and predict the health degree of the insulating scaffold, as shown in Figure 5 The figure is a schematic diagram of the prediction module derived by the neural network.

[0034] In this embodiment, the preparation method of the multi-parameter online monitoring system for the aging failure of the insulating scaffold comprises the following steps: S1: preparing an insulating scaffold: taking a metal scaffold as a base material, polishing and cleaning the surface, then coating an insulating epoxy resin coating, and forming an insulating scaffold after curing; S2: arranging monitoring sensors of multiple state parameters on the insulating scaffold, and connecting the monitoring sensors with the online monitoring all-in-one machine through the communication module; the communication module transmits the multiple state parameters acquired by the monitoring sensors to the online monitoring all-in-one machine; S3: the online monitoring all-in-one machine is preheated, self-checked, and data acquisition of the multiple state parameter signal data is performed according to the set sampling frequency and time, and is displayed in real time on the touch screen of the online monitoring all-in-one machine; when the monitoring data exceeds the set threshold, the system sends a signal prompt; S4: collecting several times of data, training the neural network in the online monitoring all-in-one machine, then modularizing the neural network, so as to predict and analyze the health degree of the insulating scaffold; when the prediction data exceeds the set threshold, the system sends a signal prompt; S5: regularly cleaning the surface of the monitoring sensor, and checking the integrity of the connecting lines and interfaces in the system; regularly performing overall performance test and correction of the system, using professional calibration equipment for standardized adjustment, to ensure the reliability and stability of the measurement data.

[0035] The specific method of step S1 is as follows: Traditional steel scaffolding is selected as the base material, and its surface is ground using mechanical equipment to remove rust and impurities. After grinding, the scaffolding surface is cleaned to ensure it is dust-free and oil-free. Then, a layer of insulating epoxy resin coating is evenly sprayed to cover the entire scaffolding surface. After coating, the scaffolding is placed in an oven for curing. The oven temperature is set at 80-90℃, preferably 80℃ in this embodiment. After the epoxy resin is completely cured, the surface is sprayed again until the epoxy coating thickness on the scaffolding surface is greater than 2 mm. The cured scaffolding surface is covered with a continuous and complete insulating layer, exhibiting excellent electrical insulation properties, thus forming an insulated scaffolding that meets relevant safety standards.

[0036] In step S2, the monitoring sensors include a micro-current sensor, a temperature sensor, a humidity sensor, and a dew point sensor. Specifically, the micro-current sensor is installed on the protruding metal part at the bottom of the insulated scaffold. The installation and use environment should be free of conductive dust, corrosive gases, strong impacts, and vibrations to prevent external environmental interference. The micro-current sensor converts the current signal into a standard RS485 output, which is connected to the all-in-one machine via a USB interface. The micro-current sensor has input overload protection, output overcurrent limiting protection, and overvoltage limit protection functions. The temperature, humidity, and dew point sensors should be installed on the epoxy layer of the insulated scaffolding. The installation location should avoid direct sunlight, strong winds, and proximity to high-voltage power lines to prevent external environmental interference. The ambient temperature should be maintained between -20℃ and 60℃, and the relative humidity should not exceed 95% to prevent condensation on the sensors from affecting reading stability. The sensors should be securely fixed with shock-absorbing measures. The sensors should be reliably connected to the data acquisition system (i.e., the data acquisition module) via a standard interface to ensure lossless data transmission.

[0037] In step S3, after the monitoring sensor installation in step S2 is completed, the hardware system of the online monitoring unit is started and preheated and self-tested. After turning on the power of the monitoring sensor and acquisition device (i.e., data acquisition module), the system should preheat for at least two minutes to reach a stable operating temperature. When starting the self-test program, it is necessary to focus on confirming whether the measurement range of the micro-current sensor is normal, and the current output should be within the range of 0 to 10 μA with fluctuations within ±0.1 μA to ensure sensitivity and accuracy. Any signal that exceeds the normal error range should be paused, the cause investigated, and the test repeated. Furthermore, when starting the self-test program, the humidity reading error of the temperature and humidity dew point sensor should be controlled within ±2% relative humidity, and the temperature reading error should not exceed ±0.5℃; any signal exceeding the normal error range requires pausing the experiment, identifying the cause, and then retesting. The data acquisition process requires setting reasonable parameters to ensure data integrity and timeliness. Preferably, the sampling frequency is once per second (1 Hz), which can be adjusted to the range of 0.1 Hz to 10 Hz depending on the specific application. The acquisition time should not be less than 10 minutes to ensure data representativeness. The range and sensitivity of the microcurrent sensor should be matched according to the actual current level on site to avoid signal saturation or signal noise interference. In this embodiment, the measurement range of the microcurrent sensor is 0 mA to 20 mA. The temperature, humidity and dew point sensor should operate within its measurement range. The temperature measurement range is -40℃ to 85℃, the relative humidity measurement range is 0% to 95%, and the dew point temperature is calculated in real time by the sensor's internal algorithm, with a measurement range of -60℃ to 75℃. Upon entering the monitoring operation phase, the system begins to continuously and automatically collect micro-current signals from the scaffold surface, as well as ambient temperature, humidity, and dew point data. The data values ​​are displayed in real-time on the monitoring interface. Operators need to observe changes in sensor values, especially minute fluctuations in micro-current and abnormal rises and falls in temperature and humidity. Operators should perform on-site calibration of the sensors every hour using a standard current source to ensure accuracy during long-term operation. During monitoring, if a drastic jump in micro-current data exceeds the set warning threshold of 10 mA for more than 10 seconds, the system will automatically issue a warning, notifying maintenance personnel to take timely intervention measures. Once the alarm threshold of 15 mA is exceeded, an alarm will be issued immediately. If humidity exceeds 95% for more than 10 seconds, the system will automatically issue an alarm, notifying maintenance personnel to take timely intervention measures. If temperature exceeds 70℃ for more than 10 seconds, the system will issue a warning signal. If dew point is below 0℃ for more than 10 seconds, the system will issue a warning signal (the actual dew point threshold range depends on the initial dew point value collected). Figure 6 , 8 As shown, Figure 6 Here is an example of test monitoring data for leakage current. Figure 8 Examples of test monitoring data for temperature, humidity, and dew point.

[0038] In step S4, multiple data collections are used to train the neural network, which is then modularly encapsulated. During data collection, the system automatically stores CSV or TXT format data files in real time, and simultaneously uses the neural network to predict and analyze the health status of the collected data. Data processing includes filtering the microcurrent signal to remove high-frequency noise, and performing average, maximum, and trend analysis on the temperature and humidity data. For the predicted data, if the microcurrent data jumps sharply beyond the set warning threshold of 10 mA for more than 10 seconds, the system automatically issues a warning. Once the alarm threshold of 15 mA is exceeded, an alarm is immediately issued. If the humidity exceeds 95% for more than 10 seconds, the system automatically issues an alarm. If the temperature exceeds 70°C for more than 10 seconds, the system issues a warning signal. Simultaneously, the system analyzes the environmental humidity level through dew point data to determine whether there is a risk of condensation, providing decision support for equipment protection and production environment optimization. In this embodiment, if the dew point is below 0°C for more than 10 seconds, the system issues a warning signal (the actual dew point threshold range depends on the initial dew point value collected at that time). Figure 7 , 9 As shown, Figure 7 For the above Figure 6 Predictive data based on test monitoring data, Figure 9 For the above Figure 8 The predictive data is based on the test monitoring data.

[0039] In step S5, equipment maintenance is crucial for ensuring the long-term stable operation of the entire monitoring system. The sensor surface is cleaned weekly to prevent dust and water droplets from accumulating and causing measurement errors. The integrity of the connecting cables and interfaces is checked regularly to avoid signal interruption due to cable aging or poor contact. A comprehensive performance test and calibration are performed every six months, and standardized adjustments are made using professional calibration equipment to ensure the reliability and stability of the measurement data.

[0040] This invention integrates micro-current sensors, temperature and humidity sensors, and dew point sensors to achieve synchronous, real-time monitoring of leakage current and environmental parameters on the scaffold surface. Utilizing an integrated online monitoring system, the collected data is intelligently analyzed to accurately determine changes in the scaffold insulation performance and its environmental influencing factors, promptly detecting insulation degradation or abnormal conditions. This effectively enhances the online monitoring capability of scaffold safety performance, helps prevent electrical safety hazards caused by insulation failure, and ensures the safety of personnel and equipment at construction sites. Furthermore, this invention extends the service life of scaffolding, reduces maintenance costs, and significantly improves the efficiency and reliability of on-site safety management through early warning and scientific maintenance guidance.

[0041] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A multi-parameter online monitoring system for aging failure of insulated scaffolding, characterized in that, include: Insulated scaffolding; Monitoring sensors are deployed on the insulated scaffolding to acquire various state parameters of the insulated scaffolding; A communication module, which is connected to the monitoring sensor, is used to transmit the various state parameters; The online monitoring unit is connected to the communication module and is used to collect and process the signal data of the various state parameters in order to monitor the status of the insulated scaffolding in real time and assess its aging and failure risk.

2. The multi-parameter online monitoring system for aging failure of insulated scaffolding according to claim 1, characterized in that, The monitoring sensors include a microcurrent sensor, a temperature sensor, a humidity sensor, and a dew point sensor.

3. The multi-parameter online monitoring system for aging failure of insulated scaffolding according to claim 2, characterized in that, The insulated scaffolding uses metal scaffolding as the base material, and its surface is coated with an epoxy resin insulation layer; the microcurrent sensor is installed on the metal part of the insulated scaffolding; the temperature sensor, humidity sensor and dew point sensor are installed on the surface of the epoxy resin insulation layer of the insulated scaffolding.

4. The multi-parameter online monitoring system for aging failure of insulated scaffolding according to claim 3, characterized in that, The microcurrent sensor is installed in an environment free from conductive dust, corrosive gases, strong impacts, and vibrations, and the connecting wires used for its installation are shielded. When installing the temperature sensor, humidity sensor, and dew point sensor, direct sunlight, strong winds, and areas close to high-voltage power lines should be avoided. The ambient temperature should be maintained between -20°C and 60°C, and the relative humidity should not exceed 95%. Anti-vibration and shock-absorbing measures should be adopted to ensure that the installation is secure.

5. The multi-parameter online monitoring system for aging failure of insulated scaffolding according to claim 3, characterized in that, When the online monitoring unit starts its self-test program, the current output of the microcurrent sensor is 0~10 μA, and the fluctuation is kept within ±0.1 μA; the temperature reading error of the temperature sensor does not exceed ±0.5℃, and the humidity reading error of the humidity sensor is within ±2% relative humidity; the data sampling frequency range of the online monitoring unit is 0.1 Hz~10 Hz, and the acquisition time is not less than 10 minutes.

6. The multi-parameter online monitoring system for aging failure of insulated scaffolding according to claim 3, characterized in that, If the current data of the microcurrent sensor fluctuates above the set warning threshold of 10 mA for more than 10 seconds, the system will issue a warning; if it exceeds the alarm threshold of 15 mA, an alarm will be issued immediately; if the humidity data of the humidity sensor exceeds 95% for more than 10 seconds, the system will automatically issue an alarm; if the temperature data of the temperature sensor exceeds 70°C for more than 10 seconds, the system will issue a warning signal; if the dew point data of the dew point sensor is below 0°C for more than 10 seconds, the system will issue a warning signal.

7. The multi-parameter online monitoring system for aging failure of insulated scaffolding according to claim 1, characterized in that, The communication module establishes a communication connection via an RS485 converter.

8. The multi-parameter online monitoring system for aging failure of insulated scaffolding according to claim 1, characterized in that, The online monitoring integrated machine includes a data acquisition module, a monitoring touch screen, and a neural network analysis module; the data acquisition module is connected to the monitoring sensor through the communication module; the monitoring touch screen is used for human-computer interaction between the operator and the online monitoring integrated machine; the neural network analysis module is used to perform comprehensive data processing on the various state parameters, thereby performing health analysis and prediction of the insulated scaffolding.

9. A method for preparing a multi-parameter online monitoring system for aging failure of insulated scaffolding, characterized in that, Includes the following steps: S1: Preparation of insulated scaffolding: Using metal scaffolding as the base material, its surface is polished and cleaned, then coated with an insulating epoxy resin coating, which is cured to form an insulated scaffolding; S2: Multi-state parameter monitoring sensors are deployed on the insulated scaffolding, and the monitoring sensors are connected to the online monitoring unit through a communication module. The communication module transmits the multi-state parameters acquired by the monitoring sensors to the online monitoring unit. S3: The online monitoring unit performs preheating and self-test, and collects data on the multi-state parameter signal data according to the set sampling frequency and time, and displays it on the touch screen of the online monitoring unit in real time. When the monitoring data exceeds the set threshold, the system issues a signal prompt. S4: Collect data several times, train the neural network in the online monitoring all-in-one machine, and then modularly encapsulate the neural network to predict and analyze the health of the insulated scaffold. When the predicted data exceeds the set threshold, the system issues a signal prompt. S5: Regularly clean the surface of the monitoring sensor and check the integrity of the connection wires and interfaces in the system; regularly conduct comprehensive system performance tests and calibrations, and use professional calibration equipment for standardized adjustments to ensure the reliability and stability of the measurement data.

10. The method for preparing a multi-parameter online monitoring system for aging failure of insulated scaffolding according to claim 9, characterized in that, In step S1, curing is performed by baking at a temperature range of 80~90℃; after the insulating epoxy resin coating has completely cured, the insulating epoxy resin coating is sprayed again on the surface of the scaffold until the thickness of the epoxy resin insulation layer on the surface of the scaffold is greater than 2 mm.

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