Power equipment inspection and health scoring robot

Abstract

The invention relates to the technical field of power equipment inspection, and discloses a power equipment inspection and health scoring robot, a moving mechanism comprises a walking chassis and a control mainboard, a storage cavity is arranged in the walking chassis, and the control mainboard is arranged in the storage cavity; the detection mechanism comprises a mechanical arm, an ultrasonic sensor and a vibration sensor, one end of the mechanical arm is connected with the robot body, and the ultrasonic sensor and the vibration sensor are arranged at the end, away from the robot body, of the mechanical arm; the head mechanism comprises a holder, an infrared sensor and a camera, and the infrared sensor and the camera are arranged on the two sides of the holder respectively; the control mainboard further comprises a data fusion module, and the data fusion module is electrically connected with the ultrasonic sensor, the vibration sensor, the infrared sensor and the camera in sequence. The data fusion module adopts a weighted fusion algorithm to perform deep analysis and comprehensive processing on data acquired by each sensor so as to ensure the accuracy of health scoring of the power equipment.

Description

Technical Field

[0001] The present invention relates to the technical field of power equipment inspection, and particularly to a robot for power equipment inspection and health scoring. Background Art

[0002] Power equipment refers to electrical devices and facilities used in power generation, transmission, transformation, distribution, and consumption. It is the core tool for realizing the production, transmission, distribution, and use of electric energy in the power system. Its scope covers various devices and installations in the entire power flow process from power plants to end-users. In the power industry, equipment inspection and fault diagnosis are undoubtedly the core links to ensure the stable operation of the power system. In a vast power network, the operating states of various equipment such as transformers, switchgear, and transmission lines are directly related to the stable supply of electricity.

[0003] Currently, the traditional manual inspection method has long been undertaking this important task. However, it has many drawbacks that cannot be ignored. During manual inspection, inspectors need to spend a large amount of time and energy shuttling in a complex power facility environment, which leads to low inspection efficiency and makes it difficult to conduct frequent and comprehensive inspections of power equipment. Moreover, manual inspection relies on the experience and subjective judgment of inspectors. Due to significant differences in professional levels and attentiveness among different personnel, there are errors in the accuracy of power equipment fault diagnosis, resulting in uneven health scoring results for the overall power equipment. This situation is like a hidden reef behind the stable operation of the power system, bringing many potential risks to the long-term development of the power industry. Summary of the Invention

[0004] The purpose of the present invention is to provide a robot for power equipment inspection and health scoring, which effectively solves the problems of low inspection efficiency, low accuracy of fault diagnosis, and inability to accurately obtain the health score of power equipment existing in the traditional manual inspection method.

[0005] To achieve the above object, the present invention provides an inspection and health scoring robot for power equipment, which includes a robot main body, a moving mechanism, a detection mechanism and a head mechanism; the moving mechanism includes a walking chassis and a control main board, a storage cavity is arranged inside the walking chassis, and the control main board is arranged inside the storage cavity; the detection mechanism includes a robotic arm, an ultrasonic sensor and a vibration sensor, one end of the robotic arm is connected to the robot main body, and the ultrasonic sensor and the vibration sensor are both arranged at the end of the robotic arm away from the robot main body; the head mechanism includes a pan-tilt, an infrared sensor and a camera, one end of the pan-tilt is rotatably connected to the robot main body, and the infrared sensor and the camera are respectively arranged on both sides of the pan-tilt; wherein, the control main board further includes a data fusion module, and the data fusion module is electrically connected to the ultrasonic sensor, the vibration sensor, the infrared sensor and the camera in sequence, and the data fusion module performs weighted fusion on the high-frequency impact vibration characteristics obtained by the ultrasonic sensor, the crack frequency band signal characteristics obtained by the vibration sensor, the temperature distribution characteristics obtained by the infrared sensor, and the appearance characteristics obtained by the camera, so as to generate a comprehensive health status score of the power equipment.

[0006] In one embodiment, the detection mechanism is arranged in the middle of the robot main body, the vibration sensor is used to detect the mechanical wear of the power equipment to obtain the high-frequency impact vibration characteristics of the power equipment, and the vibration sensor transmits the high-frequency impact vibration characteristics to the data fusion module; the ultrasonic sensor is used to detect the micro-cracks inside the power equipment to obtain the crack frequency band signal characteristics of the power equipment, and the ultrasonic sensor transmits the crack frequency band signal characteristics to the data fusion module.

[0007] In one embodiment, the head mechanism is arranged on the top of the robot main body, the infrared sensor is used to detect the temperature distribution image of the power equipment to obtain the temperature distribution characteristics of the power equipment, and the infrared sensor transmits the temperature distribution characteristics to the data fusion module; the camera is used to capture the appearance image of the power equipment to obtain the appearance characteristics of the power equipment, and the camera transmits the appearance characteristics to the data fusion module.

[0008] In one embodiment, the control main board further includes a preprocessing module, which is used to perform preprocessing after receiving the data of the sensors, and adopts the Kalman filtering algorithm to preprocess the characteristics obtained by the camera, the infrared sensor, the vibration sensor and the ultrasonic sensor according to the characteristics and weights of different sensor data.

[0009] In one embodiment, the control main board further includes an AI diagnosis system, which is electrically connected to the data fusion module. The AI diagnosis system analyzes the health score of the power equipment obtained by the data fusion module through weighted fusion to obtain the fault type of the power equipment.

[0010] In one embodiment, a mobile detection unit is provided at the front end of the walking chassis. The mobile detection unit is electrically connected to the control main board and is used to obtain the environmental information around the power equipment. The mobile detection unit includes a vision sensor and a radar. The vision sensor is used to capture images of the surrounding environment in real time, and the radar is used to sense the positions of objects in the surrounding environment.

[0011] In one embodiment, the control main board includes an autonomous navigation module, which is electrically connected to the vision sensor and the radar respectively. The autonomous navigation module is used to process the environmental information fed back by the vision sensor and the radar, construct an environmental map, and control the movement mechanism to move.

[0012] In one embodiment, the movement mechanism further includes an antenna, which is provided at the rear end of the walking chassis. The antenna is electrically connected to the control main board and is used to transmit the information sent by the control main board to the outside world.

[0013] In one embodiment, the movement mechanism further includes universal wheels, which are respectively provided on both sides of the walking chassis. One end of the universal wheels is in contact with the ground, and the universal wheels are used to drive the movement of the robot body.

[0014] In one embodiment, a battery module is further provided inside the walking chassis. The number of battery modules is multiple, and the multiple battery modules are respectively provided on both sides of the control main board. The battery modules are used to provide power for the operation of the robot.

[0015] Compared with the prior art, the power equipment inspection and health scoring robot in the embodiment of the present invention has the following beneficial effects: The robot is equipped with a variety of sensors such as ultrasonic sensors, vibration sensors, infrared sensors, and cameras, which detect power equipment from different dimensions. The ultrasonic sensor can accurately capture the high-frequency impact vibration characteristics inside the equipment, effectively detecting internal potential problems such as partial discharge and insulation faults; the vibration sensor focuses on the signal characteristics of the crack frequency band on the surface of the equipment, and can detect fine cracks in time to avoid serious faults caused by crack expansion; the infrared sensor obtains the temperature distribution characteristics of the equipment in real time, accurately judging whether there are abnormalities such as overheating and poor contact in the equipment; the camera clearly records the appearance characteristics of the equipment, including rust, deformation, foreign object attachment, etc. The multiple sensors work together to provide comprehensive and accurate data support for equipment health assessment; the data fusion module in the control mainboard uses a weighted fusion algorithm to deeply analyze and comprehensively process the data collected by each sensor. According to the importance of different sensor data for equipment health status assessment, this algorithm reasonably allocates weights, effectively reducing the errors and limitations that may exist in the data of a single sensor, making the comprehensive score of the power equipment health status finally generated more accurate and reliable, providing a solid basis for equipment maintenance decisions, and effectively avoiding the influence of human factors such as the professional level, work experience, and work attitude of inspection personnel on the detection results during the manual inspection process, resulting in uneven detection accuracy. The robot of the present invention strictly performs data collection and analysis according to the preset program and algorithm, is not interfered by human factors, and can always maintain a high-precision and consistent detection level, ensuring the objectivity and accuracy of power equipment inspection. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 is a schematic diagram of the overall structure of the power equipment inspection and health scoring robot in the embodiment of the present invention.

[0017] Figure 2 is a front view of the power equipment inspection and health scoring robot in the embodiment of the present invention.

[0018] Figure 3 is a side view of the power equipment inspection and health scoring robot in the embodiment of the present invention.

[0019] Figure 4 is a schematic diagram of the structure of the moving mechanism in the power equipment inspection and health scoring robot in the embodiment of the present invention.

[0020] Figure 5 is a top view of the moving mechanism in the power equipment inspection and health scoring robot in the embodiment of the present invention.

[0021] In the figure, 10 is the robot main body;

[0022] 20. Moving mechanism; 21. Traveling chassis; 211. Battery module; 22. Control main board; 23. Movement detection unit; 231. Vision sensor; 232. Radar; 24. Antenna; 25. Universal wheel;

[0023] 30. Detection mechanism; 31. Manipulator; 32. Ultrasonic sensor; 33. Vibration sensor;

[0024] 40. Head mechanism; 41. Pan-tilt head; 42. Infrared sensor; 43. Camera. Detailed implementation manners

[0025] The following combines the accompanying drawings and embodiments to further describe in detail the specific implementation manners of the present invention. The following embodiments are used to illustrate the present invention, but are not used to limit the scope of the present invention.

[0026] In the description of the present invention, it should be understood that when an element is referred to as "fixed to" or "disposed on" another element, it can be directly on the other element or indirectly on the other element. When an element is referred to as "connected to" another element, it can be directly connected to the other element or indirectly connected to the other element. The terms "mounted", "connected", and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the internal communication of two elements or the interaction relationship between two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0027] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by the terms "height", "upper", "lower", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. in the present invention is based on the orientation or positional relationship shown in the accompanying drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation to the present invention.

[0028] As Figures 1 to 5As shown in the figure, the embodiment of the present invention preferably provides a power equipment inspection and health scoring robot, which includes a robot main body 10, a moving mechanism 20, a detection mechanism 30, and a head mechanism 40; the moving mechanism 20 includes a walking chassis 21 and a control main board 22. A storage cavity is arranged inside the walking chassis 21, and the control main board 22 is arranged inside the storage cavity; the detection mechanism 30 includes a robotic arm 31, an ultrasonic sensor 32, and a vibration sensor 33. One end of the robotic arm 31 is connected to the robot main body 10, and both the ultrasonic sensor 32 and the vibration sensor 33 are arranged at one end of the robotic arm 31 away from the robot main body 10; the head mechanism 40 includes a pan-tilt 41, an infrared sensor 42, and a camera 43. One end of the pan-tilt 41 is rotatably connected to the robot main body 10, and the infrared sensor 42 and the camera 43 are respectively arranged on both sides of the pan-tilt 41; wherein, the control main board 22 further includes a data fusion module, and the data fusion module is electrically connected to the ultrasonic sensor 32, the vibration sensor 33, the infrared sensor 42, and the camera 43 in sequence. The data fusion module performs weighted fusion on the high-frequency impact vibration characteristics obtained by the ultrasonic sensor 32, the crack frequency band signal characteristics obtained by the vibration sensor 33, the temperature distribution characteristics obtained by the infrared sensor 42, and the appearance characteristics obtained by the camera 43 to generate a comprehensive health status score of the power equipment.

[0029] Based on the above technical features, the robot in the embodiment of the present invention is equipped with a variety of sensors such as an ultrasonic sensor 32, a vibration sensor 33, an infrared sensor 42, and a camera 43 to detect power equipment from different dimensions. The ultrasonic sensor 32 can accurately capture the high-frequency impact vibration characteristics inside the equipment and effectively detect internal potential problems such as partial discharge and insulation faults; the vibration sensor 33 focuses on the crack frequency band signal characteristics on the surface of the equipment and can timely detect fine cracks to avoid serious faults caused by crack expansion; the infrared sensor 42 obtains the temperature distribution characteristics of the equipment in real time to accurately judge whether there are abnormalities such as overheating and poor contact in the equipment; the camera 43 clearly records the appearance characteristics of the equipment, including rust, deformation, foreign object attachment, etc. The multiple sensors work together to provide comprehensive and accurate data support for equipment health assessment; the data fusion module in the control main board 22 uses a weighted fusion algorithm to deeply analyze and comprehensively process the data collected by each sensor. This algorithm reasonably allocates weights according to the importance of different sensor data for equipment health status assessment, effectively reducing the errors and limitations that may exist in the data of a single sensor, making the final generated comprehensive health status score of the power equipment more accurate and reliable, providing a solid basis for equipment maintenance decisions, and effectively avoiding the influence of human factors such as the professional level, work experience, and work attitude of inspection personnel during the manual inspection process, resulting in uneven detection accuracy.

[0030] Furthermore, to improve the intelligence level of the power equipment inspection and health scoring robot, this solution designs a device health status evaluation mechanism that integrates multi-source data. This mechanism realizes multi-dimensional perception of the operating status of key equipment on the inspection robot body by deploying various types of sensors, including ultrasonic sensor 32, vibration sensor 33, infrared sensor 42, and camera 43. Since there are problems such as time synchronization error, inconsistent dimension, and noise interference in the data collected by different sensors, in order to ensure the reliability and analysis effectiveness of the fused data, the system uses the Kalman filter algorithm to process the original data. The Kalman filter is an optimal estimation algorithm based on the idea of linear system prediction and correction. By continuously predicting the device state and combining the real-time sensor observation results for correction, it gradually approaches the true state value. This algorithm can significantly reduce the impact of environmental noise on the monitoring results during the fusion process, improve the accuracy and stability of state estimation, and lay a data foundation for the accurate generation of subsequent health scores.

[0031] Furthermore, based on the fused data, this system further constructs a device health scoring model for practical applications. This model comprehensively analyzes the key sensing information after filtering, extracts state features that reflect the operating quality of the device, such as temperature rise rate, vibration amplitude change, current fluctuation trend, abnormal audio frequency, etc., and sets weights according to the importance of each feature for weighted calculation to generate a standardized scoring result. The device health score uses a 100-point system from 0 to 100, where the higher the score, the better the device state. The scoring results are divided into five grade intervals, corresponding to the states of "healthy", "sub-healthy", "slightly abnormal", "moderately abnormal", and "severely abnormal" respectively. The system can automatically generate maintenance suggestions based on the score value. For example, when the score is between 65 and 85, the system will prompt that the device has a tendency to deviate slightly from the normal operating condition, and it is recommended that the operation and maintenance personnel pay key attention and conduct regular rechecks; if the score is lower than 45, the system will trigger an early warning mechanism and recommend arranging on-site maintenance or replacing key components. This scoring mechanism can not only significantly improve the efficiency and accuracy of identifying the operating state of the device, but also facilitate the formation of a data foundation for the life cycle management of the device, and contribute to the integrated coordination of intelligent inspection, state-based maintenance, and remote early warning.

[0032] As some embodiments of the present invention, such as Figures 1 to 3As shown, the detection mechanism 30 is disposed in the middle of the robot body 10. The vibration sensor 33 is used to detect the mechanical wear of the power equipment to obtain the high-frequency impact vibration characteristics of the power equipment. The vibration sensor 33 transmits the high-frequency impact vibration characteristics to the data fusion module. The ultrasonic sensor 32 is used to detect the micro-cracks inside the power equipment to obtain the crack frequency band signal characteristics of the power equipment. The ultrasonic sensor 32 transmits the crack frequency band signal characteristics to the data fusion module. The detection mechanism 30 is arranged in the middle of the robot body 10. This layout enables the robot to have better structural stability when moving and performing detection tasks, ensuring that the vibration sensor 33 and the ultrasonic sensor 32 always maintain a stable working posture, thereby accurately collecting relevant data of the power equipment and improving the accuracy and reliability of the detection results. The vibration sensor 33 is specifically used to detect the mechanical wear of the power equipment. By obtaining the high-frequency impact vibration characteristics of the equipment, it can deeply understand the operating state of the internal mechanical components of the equipment. The high-frequency impact vibration characteristics contain rich equipment operation information. By deeply analyzing these characteristics, the degree, location, and development trend of mechanical wear can be judged. After receiving the high-frequency impact vibration characteristics transmitted by the vibration sensor 33, the data fusion module can combine other sensor data for comprehensive evaluation, more accurately predict the possible fault types and times of the equipment, send out early warning signals in advance, enabling the operation and maintenance personnel to have enough time to formulate maintenance plans and take corresponding maintenance measures to avoid the further expansion of equipment failures, reduce maintenance costs and power outage risks. The ultrasonic sensor 32 focuses on detecting the micro-cracks inside the power equipment. Relying on the characteristics of ultrasonic wave propagation in the medium, it can penetrate the equipment shell and penetrate into the internal structure of the equipment to detect micro-cracks that are difficult to detect with the naked eye. The crack frequency band signal characteristics reflect the existence state and development trend of the internal cracks of the equipment. The ultrasonic sensor 32 transmits the obtained crack frequency band signal characteristics to the data fusion module, and performs fusion analysis with other sensor data to more accurately judge the nature, size, location of the crack, and the degree of influence on the equipment safety. This multi-dimensional data fusion analysis method greatly improves the accuracy and reliability of equipment fault diagnosis, provides a scientific basis for equipment maintenance decisions, and avoids improper handling of equipment failures caused by misjudgment or missed judgment.

[0033] As some embodiments of the present invention, such as Figures 1 to 3As shown in the figure, the head mechanism 40 is disposed on the top of the robot body 10. The infrared sensor 42 is used to detect the temperature distribution image of the power equipment to obtain the temperature distribution characteristics of the power equipment, and the infrared sensor 42 transmits the temperature distribution characteristics to the data fusion module; the camera 43 is used to capture the appearance image of the power equipment to obtain the appearance characteristics of the power equipment, and the camera 43 transmits the appearance characteristics to the data fusion module. After comprehensively processing and analyzing the multi-source data, the data fusion module generates a comprehensive health status score of the power equipment. This score intuitively reflects the health degree of the equipment in a quantitative form, providing a scientific and reliable decision-making basis for the operation and maintenance personnel. The operation and maintenance personnel can reasonably arrange the equipment maintenance plan according to the score result, give priority to dealing with the equipment with poor health status, and optimize the allocation of maintenance resources. At the same time, by analyzing and mining a large amount of equipment health score data, the operation rules and potential problem trends of the equipment can also be found, providing guidance for the preventive maintenance of the equipment, realizing the transformation from traditional experience-based maintenance to data-based intelligent maintenance, improving the efficiency and effectiveness of operation and maintenance management, and reducing the operation cost of the power system.

[0034] As some embodiments of the present invention, as Figures 1 to 3 shown in the figure, the control main board 22 further includes a preprocessing module. After receiving the data of the sensors, the preprocessing module performs preprocessing and adopts the Kalman filtering algorithm to preprocess the characteristics obtained by the camera 43, the infrared sensor 42, the vibration sensor 33 and the ultrasonic sensor 32 according to the characteristics and weights of different sensor data. The on-site environment for power equipment inspection is complex, with various noise sources such as electromagnetic interference, mechanical vibration interference, and environmental temperature fluctuations. These noises will seriously affect the accuracy of the data collected by the sensors. The preprocessing module adopts the Kalman filtering algorithm, which can effectively denoise the image data obtained by the camera 43, the temperature data of the infrared sensor 42, the vibration data of the vibration sensor 33, and the crack feature data of the ultrasonic sensor 32 according to the characteristics of different sensor data. The preprocessing module effectively eliminates the outliers in the feature data and enhances the data stability.

[0035] As some embodiments of the present invention, as Figures 1 to 3As shown, the control main board 22 further includes an AI diagnosis system, which is electrically connected to the data fusion module. The AI diagnosis system analyzes the power equipment health score obtained by the data fusion module through weighted fusion to obtain the fault type of the power equipment. The fused data is transmitted to the AI diagnosis system; this system uses ResNet-50 to classify image data to determine whether there are fault features on the appearance of the equipment; uses XGBoost to predict time-series data (such as temperature and vibration data changing over time) to analyze the operation trend of the equipment; combines a fault inference engine constructed based on a knowledge graph, comprehensively considers various aspects of information, automatically identifies and classifies the fault type of the equipment, and predicts the development trend of the fault; for example, when the thermal imager detects that the local temperature of the equipment rises abnormally, and the vision camera 43 captures a discoloration sign at the corresponding position, the intelligent diagnosis system will combine historical data and fault inference rules to judge the possible fault causes, such as poor contact, overload, etc., and predict the possible development direction of the fault, such as a continuous rise in temperature may cause serious faults such as a short circuit.

[0036] As some embodiments of the present invention, as Figures 4 to 5 As shown, a mobile detection unit 23 is provided at the front end of the walking chassis 21. The mobile detection unit 23 is electrically connected to the control main board 22. The mobile detection unit 23 is used to obtain the environmental information around the power equipment. The mobile detection unit 23 includes a vision sensor 231 and a radar 232. The vision sensor 231 is used to capture images of the surrounding environment in real time, and the radar 232 is used to sense the positions of items in the surrounding environment. The radar 232 can accurately sense the positions and distances of items in the surrounding environment and draw a three-dimensional map of the environment by emitting and receiving electromagnetic waves. The combination of the two enables the robot to accurately model the surrounding environment, clearly understand its own position and the distribution of surrounding obstacles, providing a reliable basis for the robot's autonomous navigation. At the same time, during the movement, the vision sensor 231 and the radar 232 can monitor the changes in the surrounding environment in real time. When a new obstacle appears ahead, the radar 232 can quickly and accurately measure the distance and azimuth of the obstacle, and the vision sensor 231 can further identify the type and characteristics of the obstacle. Based on this information, the robot can quickly respond, adjust the moving direction and speed, and achieve real-time obstacle avoidance.

[0037] As some embodiments of the present invention, as Figures 4 to 5As shown, the control main board 22 includes an autonomous navigation module. The autonomous navigation module is electrically connected to the vision sensor 231 and the radar 232 respectively. The autonomous navigation module is used to process the environmental information fed back by the vision sensor 231 and the radar 232, construct an environmental map, and control the movement of the moving mechanism 20. The autonomous navigation module is electrically connected to the vision sensor 231 and the radar 232, and can receive and process the environmental information they feed back in real time. Based on the constructed three-dimensional environmental map, the autonomous navigation module can use advanced algorithms for intelligent path planning. It will, according to the requirements of the inspection task, such as the list of equipment to be detected, the inspection sequence, etc., combine the information in the environmental map to plan an optimal moving path to ensure that the robot can complete the inspection task in the shortest time and with the least energy consumption. At the same time, the autonomous navigation module controls the moving mechanism 20 to move along the planned path in real time, and adjusts the moving direction and speed in a timely manner according to environmental changes to achieve efficient and accurate autonomous inspection.

[0038] As some embodiments of the present invention, as Figures 4 to 5 shown, the moving mechanism 20 further includes an antenna 24. The antenna 24 is arranged at the rear end of the walking chassis 21. The antenna 24 is electrically connected to the control main board 22. The antenna 24 is used to transmit the information sent by the control main board 22 to the outside world. The antenna 24 is arranged at the rear end of the walking chassis 21 and is electrically connected to the control main board 22, and can timely and accurately transmit the information sent by the control main board 22, such as the equipment status data collected by the sensor, the operating parameters of the robot itself, etc. to the outside world, which enables the monitoring personnel to obtain the operating conditions of the power equipment and the working status of the robot in real time remotely without on-site inspection, greatly improving the monitoring efficiency.

[0039] As some embodiments of the present invention, as Figures 4 to 5 shown, the moving mechanism 20 further includes universal wheels 25. The universal wheels 25 are respectively arranged on both sides of the walking chassis 21. One end of the universal wheels 25 is in contact with the ground. The universal wheels 25 are used to drive the movement of the robot body 10. The universal wheels 25 are respectively arranged on both sides of the walking chassis 21. Their unique design enables the robot to achieve flexible omnidirectional steering. In a complex power equipment inspection environment, such as a substation with a compact equipment layout and narrow passages, the robot can quickly adjust the moving direction according to actual needs, easily bypass obstacles, and smoothly reach each inspection point.

[0040] As some embodiments of the present invention, as Figures 4 to 5As shown, a battery module 211 is further provided inside the walking chassis 21. The number of the battery modules 211 is multiple, and the multiple battery modules 211 are respectively arranged on both sides of the control main board 22. The battery module 211 is used to provide power for the operation of the robot. The multiple battery modules 211 are respectively arranged on both sides of the control main board 22, which can provide strong and stable power support for the operation of the robot. When the robot performs the inspection task, whether it is driving the walking chassis 21 to move, driving the detection mechanism 30 to work, or maintaining the rotation of the pan-tilt 41 and the sensor, a large amount of electric energy is consumed. The multiple battery modules 211 are used in parallel or in series, which can provide sufficient current and voltage to ensure the normal operation of each component of the robot and avoid task interruption due to insufficient power.

[0041] Further, as some embodiments of the present invention, the control main board 22 further includes a dual-mode communication module. The dual-mode communication module supports automatic switching between 5G / LoRa networks, and the switching threshold is determined in real time based on the signal strength monitoring module. Once the intelligent diagnosis system determines that there is a fault in the device, the robot will upload the fault information to the cloud analysis platform in real time through the dual-mode communication module (preferably using the 5G network, and automatically switching to the LoRa network if the 5G signal is poor); after receiving the data, the cloud platform will, on the one hand, push the fault information to the central monitoring system to notify the operation and maintenance personnel to handle it in time; on the other hand, deeply analyze the fault data to provide decision-making support for subsequent equipment maintenance and management.

[0042] Further, as some embodiments of the present invention, both the sensor and the calculator unit adopt standard interfaces (USB-C, RS485, PCIe), support plug and play, and the maintenance cycle is shortened by 60%.

[0043] Further, during the entire inspection and fault handling process, all data collected by the robot, as well as information such as fault diagnosis results and handling processes, are completely recorded on the cloud platform; the operation and maintenance personnel and technicians can regularly analyze these data, summarize the laws and trends of equipment faults, evaluate the inspection and diagnosis effects of the robot, and provide data support for optimizing the algorithm of the robot, adjusting the inspection strategy, and improving the design and maintenance plan of the power equipment, so as to continuously improve the operation reliability and stability of the power system.

[0044] In summary, compared with the prior art, the power equipment inspection and health scoring robot provided by the embodiments of the present invention has the following beneficial effects: The robot is equipped with a variety of sensors such as an ultrasonic sensor 32, a vibration sensor 33, an infrared sensor 42, and a camera 43, which detect power equipment from different dimensions. The ultrasonic sensor 32 can accurately capture the high-frequency impact vibration characteristics inside the equipment, effectively detecting internal potential problems such as partial discharge and insulation faults; the vibration sensor 33 focuses on the signal characteristics of the crack frequency band on the surface of the equipment, and can timely detect fine cracks to avoid serious faults caused by crack propagation; the infrared sensor 42 obtains the temperature distribution characteristics of the equipment in real time, accurately judging whether there are abnormalities such as overheating and poor contact in the equipment; the camera 43 clearly records the appearance characteristics of the equipment, including rust, deformation, foreign object attachment, etc. The multiple sensors work together to provide comprehensive and accurate data support for equipment health assessment; the data fusion module in the control main board 22 uses a weighted fusion algorithm to deeply analyze and comprehensively process the data collected by each sensor. According to the importance of different sensor data for equipment health status assessment, this algorithm reasonably allocates weights, effectively reducing the errors and limitations that may exist in the data of a single sensor, making the final comprehensive score of the power equipment health status more accurate and reliable, providing a solid basis for equipment maintenance decisions, and effectively avoiding the influence of human factors such as the professional level, work experience, and work attitude of inspection personnel on the detection results during the manual inspection process, resulting in uneven detection accuracy. The robot of the present invention strictly performs data collection and analysis according to the preset program and algorithm, is not interfered by human factors, and can always maintain a high-precision and consistent detection level, ensuring the objectivity and accuracy of power equipment inspection.

[0045] The above are only the preferred embodiments of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the technical principle of the present invention, several improvements and substitutions can be made, and these improvements and substitutions should also be regarded as the protection scope of the present invention.

Claims

1. A power equipment inspection and health scoring robot, characterized in that include: Robot body, moving mechanism, detection mechanism and head mechanism; The mobile mechanism includes a walking chassis and a control mainboard, the walking chassis is provided with a storage cavity inside, and the control mainboard is arranged inside the storage cavity; The detection mechanism includes a mechanical arm, an ultrasonic sensor and a vibration sensor, one end of the mechanical arm is connected to the robot body, and the ultrasonic sensor and the vibration sensor are both arranged at one end of the mechanical arm away from the robot body; The head mechanism includes a pan-tilt platform, an infrared sensor and a camera, one end of the pan-tilt platform is rotatably connected to the robot body, and the infrared sensor and the camera are respectively arranged on both sides of the pan-tilt platform; Among them, the control main board also includes a data fusion module, and the data fusion module is electrically connected to the ultrasonic sensor, vibration sensor, infrared sensor and camera in sequence. The data fusion module performs weighted fusion on the high-frequency impact vibration characteristics obtained by the ultrasonic sensor, the crack frequency band signal characteristics obtained by the vibration sensor, the temperature distribution characteristics obtained by the infrared sensor and the appearance characteristics obtained by the camera to generate a comprehensive score of the health status of the power equipment.

2. The power equipment inspection and health scoring robot according to claim 1, wherein The detection mechanism is arranged in the middle part of the robot body. The vibration sensor is used to detect the mechanical wear of the power equipment to obtain the high-frequency impact vibration characteristics of the power equipment, and the vibration sensor transmits the high-frequency impact vibration characteristics to the data fusion module; the ultrasonic sensor is used to detect tiny cracks inside the power equipment to obtain the crack frequency band signal characteristics of the power equipment, and the ultrasonic sensor transmits the crack frequency band signal characteristics to the data fusion module.

3. The power equipment inspection and health scoring robot according to claim 2, wherein, The head mechanism is arranged on the top of the robot body, the infrared sensor is used to detect the temperature distribution image of the power equipment to obtain the temperature distribution characteristics of the power equipment, and the infrared sensor transmits the temperature distribution characteristics to the data fusion module; the camera is used to capture the appearance image of the power equipment to obtain the appearance characteristics of the power equipment, and the camera transmits the appearance characteristics to the data fusion module.

4. The power equipment inspection and health scoring robot according to claim 3, characterized in that, The control main board also includes a preprocessing module, which is used to perform preprocessing after receiving the sensor data, and use a Kalman filter algorithm to preprocess the features obtained by the camera, the infrared sensor, the vibration sensor and the ultrasonic sensor according to the characteristics and weights of different sensor data.

5. The power equipment inspection and health scoring robot according to claim 4, characterized in that The control main board also includes an AI diagnostic system, which is electrically connected to the data fusion module. The AI diagnostic system analyzes the health score of the power equipment obtained by weighted fusion of the data fusion module to obtain the fault type of the power equipment.

6. The power equipment inspection and health scoring robot according to claim 1, wherein A mobile detection unit is provided at the front end of the walking chassis. The mobile detection unit is electrically connected to the control main board. The mobile detection unit is used to obtain the environmental information around the power equipment. The mobile detection unit includes a vision sensor and a radar. The vision sensor is used to capture images of the surrounding environment in real time, and the radar is used to sense the positions of objects in the surrounding environment.

7. The power equipment inspection and health scoring robot according to claim 6, wherein The control main board includes an autonomous navigation module. The autonomous navigation module is electrically connected to the vision sensor and the radar respectively. The autonomous navigation module is used to process the environmental information fed back by the vision sensor and the radar, construct an environmental map, and control the movement mechanism to move.

8. The power equipment inspection and health scoring robot according to claim 1, wherein The movement mechanism further includes an antenna. The antenna is provided at the rear end of the walking chassis. The antenna is electrically connected to the control main board. The antenna is used to transmit the information sent by the control main board to the outside world.

9. The power equipment inspection and health scoring robot according to claim 8, characterized in that, The movement mechanism further includes universal wheels. The universal wheels are respectively provided on both sides of the walking chassis. One end of the universal wheel is in contact with the ground. The universal wheels are used to drive the movement of the robot body.

10. The power equipment inspection and health scoring robot according to claim 9, wherein, A battery module is further provided inside the walking chassis. The number of the battery modules is multiple. The multiple battery modules are respectively provided on both sides of the control main board. The battery module is used to provide power for the operation of the robot.

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