Power equipment maintenance auxiliary monitoring system

Abstract

The invention discloses a power equipment maintenance auxiliary monitoring system, which is characterized in that an isolation assembly is composed of a plurality of modular units which are detachably connected, is made of an insulating material, is provided with a reflective mark on the surface, and is used for isolating a maintenance area containing power-off equipment in a maintenance process; the wearable device is integrated with an RFID tag for storing identity, work type and authority information and a reminding assembly, the wearable device is a safety helmet or work clothes, and the reminding assembly adopts a vibration module or a buzzer; the plurality of RFID card readers are dispersedly distributed on the isolation assembly; the data processing unit is configured to calculate the position and the terrain clearance of the wearable device through combination of RFID signal strength and a triangulation positioning algorithm, and verify personnel authority; the control assembly is used for triggering the reminding assembly to give an alarm when the wearable device crosses the border or the authority is not consistent. Through a four-layer protection framework of spatial isolation, personnel positioning, environment perception and intelligent early warning, maintenance personnel can be prevented from mistakenly entering a non-maintenance area without power failure for maintenance operation, and the safety can be improved.

Description

Technical Field

[0001] The present invention relates to the field of power equipment maintenance, and in particular to an auxiliary monitoring system for power equipment maintenance. Background Art

[0002] During power equipment maintenance operations, temporary fences are used to isolate de-energized equipment awaiting repair from surrounding live areas. Existing technologies suffer from the following key flaws: Fence boundary control is ineffective. Traditional removable fences rely on physical isolation but lack dynamic monitoring, failing to prevent personnel from accidentally entering live areas. For example, if the fence is not promptly restored after maintenance or the markings are unclear, personnel may accidentally touch nearby live equipment. Climbing behavior monitoring is also lacking. Existing technology cannot identify maintenance personnel illegally climbing equipment at height, such as those working without a safety rope, which poses a risk of falling from height. This urgently requires improvement. Summary of the Invention

[0003] In order to solve the technical problems existing in the background technology, the present invention proposes an auxiliary monitoring system for power equipment maintenance, comprising:

[0004] Isolation components, consisting of multiple detachably connected modular units, are made of insulating material and have reflective markings on the surface, and are used to isolate the maintenance area containing the de-energized equipment during maintenance;

[0005] Wearable devices, integrated with RFID tags that store identity, job type, and permission information, and reminder components. The wearable devices are helmets or work clothes, and the reminder components use vibration modules or buzzers.

[0006] Multiple RFID readers are distributed on the isolation components;

[0007] a data processing unit configured to calculate the position and height of the wearable device from the ground by combining RFID signal strength with a triangulation positioning algorithm, and to verify personnel authority;

[0008] The control component is used to trigger the reminder component to alarm when the wearable device exceeds the boundary or the permission is inconsistent.

[0009] Furthermore, it also includes: a safety device, the safety device includes a safety rope, a gyroscope, a safety hook with an automatic locking function is provided at the end of the safety rope, the gyroscope is installed on the safety rope and is used to detect the swinging state of the safety rope, the data processing unit determines the state of the free end of the safety rope by analyzing the gyroscope data, and triggers a dual alarm mechanism in combination with the height of the wearable device from the ground.

[0010] Furthermore, the data processing unit adopts a cloud computing platform or edge computing equipment, has data storage and historical trajectory tracing functions, and can generate a three-dimensional visual maintenance log including personnel location and operation time.

[0011] Furthermore, the dual alarm mechanism is specifically as follows: an alarm is triggered when the height of the wearable device from the ground exceeds a preset threshold and no gyroscope data is detected and / or the safety rope is in a single-end free state.

[0012] Furthermore, a quick-connect electromagnetic lock mechanism is used between the modular units, which has the characteristics of self-locking when powered on and quick separation when powered off.

[0013] Furthermore, the RFID tag adopts a flexible antenna design, which is embedded between the protective layer and the inner lining of the wearable device, and has an IP67 protection level and anti-electromagnetic interference characteristics.

[0014] Furthermore, the reminder component has a graded alarm function: the first-level alarm is an interval vibration prompt; the second-level alarm is a continuous buzzing; and the third-level alarm synchronously triggers the sound and light barrier of the isolation component.

[0015] Furthermore, it also includes an environmental monitoring module, which integrates temperature, humidity and gas concentration sensors and is communicated with the data processing unit. When it is detected that the environmental parameters exceed the standard, the linkage control component starts the emergency ventilation system.

[0016] Furthermore, the safety rope has a built-in strain sensor array to monitor the tension distribution in real time. The data processing unit uses a machine learning algorithm to identify abnormal stress patterns, predict the risk of falling and provide early warning.

[0017] The present invention uses a four-layer protection architecture of spatial isolation, personnel positioning, environmental perception, and intelligent early warning to prevent maintenance personnel from mistakenly entering non-maintenance areas where the power is not cut off to perform maintenance operations. This can improve safety, reduce the rate of high-altitude fall accidents, and increase the timeliness of handling abnormal environmental parameters. DETAILED DESCRIPTION

[0018] The present invention provides an auxiliary monitoring system for power equipment maintenance, comprising:

[0019] Isolation components, consisting of multiple detachably connected modular units, are made of insulating material and have reflective markings on the surface, and are used to isolate the maintenance area containing the de-energized equipment during maintenance;

[0020] Wearable devices, integrated with RFID tags that store identity, job type, and permission information, and reminder components. The wearable devices are helmets or work clothes, and the reminder components use vibration modules or buzzers.

[0021] Multiple RFID readers are distributed on the isolation components;

[0022] a data processing unit configured to calculate the position and height of the wearable device from the ground by combining RFID signal strength with a triangulation positioning algorithm, and to verify personnel authority;

[0023] The control component is used to trigger the reminder component to alarm when the wearable device exceeds the boundary or the permission is inconsistent.

[0024] The modular units are made of polycarbonate insulation material and covered with 3M high-reflective film. Adjacent modular units are connected by snap-on electromagnetic locks (magnetically closed when powered on and automatically unlocked when powered off). The wearable device is specifically a hard hat with a built-in flexible PCB board integrated with an RFID tag. The RFID tag encrypts and stores the personnel ID, work code, and authority level. The vibration module uses an eccentric rotor motor. The buzzer decibel value exceeds the preset value. The positioning algorithm is based on RSSI signal strength and uses an improved Chan algorithm to achieve three-dimensional spatial positioning. The height above the ground is corrected in combination with air pressure sensor data. Modular isolation walls achieve dual protection of physical isolation and electronic fencing, which can reduce the risk of maintenance personnel accidentally entering non-maintenance live areas. The three-dimensional positioning accuracy meets the needs of complex substation scenarios, and the completeness rate of personnel trajectory tracing is high.

[0025] The monitoring system also includes a safety device, consisting of a safety rope and a gyroscope. The rope's end features an automatic locking hook. The gyroscope is mounted on the rope and monitors its swing status. A data processing unit analyzes gyroscope data to determine the rope's free end status and, combined with the wearable device's height above the ground, triggers a dual alarm mechanism. The rope is constructed of a braided aramid fiber layer with a polyurethane coating. The gyroscope measures the angular velocity of the rope's swing. If the angular velocity exceeds a preset value and persists for a period exceeding the preset value, the free end is deemed out of control, indicating that the maintenance personnel improperly secured the rope. The data processing unit compares the height above the ground with the rope's status to determine whether to trigger an alarm. This dual judgment (height + rope status) reduces false alarms for high-altitude operations. The aramid material's high-temperature resistance (maximum temperature of 260°C) is well-suited for the maintenance environment of substation equipment. Furthermore, the data processing unit utilizes a cloud computing platform or edge computing device, providing data storage and historical tracking capabilities, generating a three-dimensional visual maintenance log that includes personnel locations and work times. Log files contain personnel coordinates (latitude, longitude, and elevation), action type (climbing, stopping, or crossing the boundary), and equipment operation records. Localized edge computing reduces network reliance and response latency, while 3D logs enable the restoration of operational scenarios during incident recovery.

[0026] Furthermore, the dual alarm mechanism specifically triggers an alarm when the wearable device's height above the ground exceeds a preset threshold and no gyroscope data is detected and / or the safety tether is in a free state at one end. If the gyroscope data is missing for a preset time or the tension at one end of the safety tether is less than a preset value, it is determined that the safety device is not being worn or is not properly secured.

[0027] Furthermore, the modular units utilize a quick-connect electromagnetic locking mechanism, which features self-locking when powered on and quick release when powered off. The quick-connect electromagnetic lock incorporates a Hall effect sensor, self-locking when powered on and releasing when powered off. The lock body is nickel-plated for low contact resistance and electromagnetic shielding. Modular assembly improves fence assembly efficiency, and the electromagnetic shielding effectively suppresses ultra-high frequency interference generated by GIS equipment.

[0028] Furthermore, the RFID tag utilizes a flexible antenna design, embedded between the wearable device's protective layer and inner lining. It boasts an IP67 rating and excellent electromagnetic interference resistance. Printed with silver nanowire conductive ink, the flexible antenna offers wide operating frequency coverage and an adjustable read distance. The tag is encapsulated using silicone injection molding, ensuring dust and water resistance. It maintains a read success rate exceeding 98% even in SF6 gas leak scenarios.

[0029] Furthermore, the reminder component features a tiered alarm system: Level 1 provides intermittent vibrations; Level 2 provides a continuous beep; and Level 3 simultaneously triggers the isolation component's light and sound barrier. Level 1 involves three vibrations at 0.5-second intervals, escalating to a higher level if not corrected for 10 seconds. Level 3 simultaneously triggers the isolation component's LED flash (4Hz frequency) and siren (105dB sound pressure level). The light barrier covers a 270° angle and has an effective warning range of 50 meters. Progressive alarms prevent sudden high-decibel noise from disrupting precision equipment commissioning. Multimodal alerts (tactile, auditory, and visual) ensure high awareness in diverse operating environments.

[0030] Furthermore, the system includes an environmental monitoring module with integrated temperature, humidity, and gas concentration sensors, which communicate with the data processing unit. When environmental parameters exceed specified limits, the control component activates the emergency ventilation system. The gas sensor array measures SF6 concentration, oxygen content, and humidity; once the emergency ventilation system is activated, air can be exchanged. SF6 leak detection is highly sensitive, and when environmental parameters exceed specified limits, an alert is sent to the dispatch center, shortening emergency response time.

[0031] Furthermore, the safety rope is equipped with a built-in strain sensor array to monitor tension distribution in real time. A data processing unit uses a machine learning algorithm to identify abnormal stress patterns, predicting fall risks and providing early warnings. The strain sensor array collects microstrain data from the safety rope. This data is de-noised using a wavelet transform and then fed into an LSTM neural network. The model training set includes various pre-fall patterns (such as sudden weightlessness and abnormal swing frequency), enabling early prediction of falls. The machine learning model has a low false alarm rate and is suitable for a variety of scenarios, including high-voltage towers and GIS rooms.

[0032] The above are only preferred specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with this technical field, within the technical scope disclosed by the present invention, who makes equivalent replacements or changes based on the technical solutions and inventive concepts of the present invention, should be covered by the scope of protection of the present invention.

Claims

1. An auxiliary monitoring system for power equipment maintenance, characterized in that: include: Isolation components, consisting of multiple detachably connected modular units, are made of insulating material and have reflective markings on the surface, and are used to isolate the maintenance area containing the de-energized equipment during maintenance; Wearable devices, integrated with RFID tags that store identity, job type, and permission information, and reminder components. The wearable devices are helmets or work clothes, and the reminder components use vibration modules or buzzers. Multiple RFID readers are distributed on the isolation components; a data processing unit configured to calculate the position and height of the wearable device from the ground by combining RFID signal strength with a triangulation positioning algorithm, and to verify personnel authority; The control component is used to trigger the reminder component to alarm when the wearable device exceeds the boundary or the permission is inconsistent.

2. The system according to claim 1, characterized in that Also includes: The safety device includes a safety rope and a gyroscope. A safety hook with an automatic locking function is provided at the end of the safety rope. The gyroscope is installed on the safety rope and is used to detect the swinging state of the safety rope. The data processing unit determines the state of the free end of the safety rope by analyzing the gyroscope data and triggers a dual alarm mechanism in combination with the height of the wearable device from the ground.

3. The system according to claim 1, characterized in that The data processing unit uses a cloud computing platform or edge computing equipment, has data storage and historical trajectory tracing functions, and can generate a three-dimensional visual maintenance log including personnel location and operation time.

4. The system according to claim 2, characterized in that The dual alarm mechanism is specifically as follows: an alarm is triggered when the height of the wearable device from the ground exceeds a preset threshold and no gyroscope data is detected and / or the safety rope is in a single-end free state.

5. The system according to claim 1, characterized in that The modular units use a quick-connect electromagnetic lock mechanism, which has the characteristics of self-locking when powered on and quick separation when powered off.

6. The system according to claim 1, characterized in that The RFID tag adopts a flexible antenna design and is embedded between the protective layer and the lining of the wearable device. It has an IP67 protection level and anti-electromagnetic interference characteristics.

7. The system according to claim 1, characterized in that The reminder component has a graded alarm function: the first-level alarm is an interval vibration prompt; the second-level alarm is a continuous buzzing; the third-level alarm synchronously triggers the sound and light barrier of the isolation component.

8. The system according to claim 1, characterized in that It also includes an environmental monitoring module with integrated temperature, humidity and gas concentration sensors, which is connected to the data processing unit for communication. When it is detected that the environmental parameters exceed the standard, the linkage control component starts the emergency ventilation system.

9. The system according to claim 2, characterized in that The safety rope has a built-in strain sensor array to monitor the tension distribution in real time. The data processing unit uses machine learning algorithms to identify abnormal stress patterns, predict fall risks and provide early warnings.