Wind power gear box endoscopy and fault analysis training system

Abstract

The invention provides a wind power gear box endoscopy and fault analysis practical training system, and relates to the technical field of wind power generation, the wind power gear box endoscopy and fault analysis practical training system comprises a gear box model, the exterior of the gear box model is provided with a cooling device model and a lubricating device model, and the interior of the gear box model is provided with defective parts with various fault features; the endoscope is used for detecting the gearbox; the operation table is made of wear-resistant steel materials and has a manual turning function so that the interior of the gear box can be observed conveniently. And through the intelligent analysis unit, various defective parts in the gearbox can be automatically identified, and a corresponding detection report is generated. Compared with the prior art which mainly depends on manual analysis of images or videos shot by the endoscope, the method has the advantages that the detection accuracy is greatly improved, and the influence of human factors is reduced. According to the method, a machine learning algorithm is integrated, the inspection process of the endoscope can be optimized according to historical fault data, and the detection efficiency and accuracy are improved.

Description

Technical Field

[0001] The invention relates to the technical field of wind power generation, and in particular to a wind power gearbox endoscope inspection and fault analysis training system. Background Art

[0002] Wind power generation is a clean energy with advantages such as environmental protection and renewable energy. It is widely used in the global energy structure. One of the core components of a wind turbine is the gearbox, which converts the low-speed and high-torque mechanical energy output by the wind turbine into high-speed and low-torque mechanical energy to drive the generator to generate electricity. However, during the operation of the gearbox, due to the long-term influence of factors such as alternating loads, corrosion, fatigue, etc., various faults are prone to occur, such as gear tooth breakage, gear pitting, gear plastic deformation, gear wear and gear bonding. If these faults are not discovered and handled in time, they will seriously affect the normal operation of the wind turbine and even cause major safety accidents. Mechanical equipment detection technology is a technology that uses physical or chemical methods to inspect, test and analyze mechanical equipment to evaluate its performance and safety. Endoscopic inspection technology is a non-destructive detection technology that uses an endoscope to intuitively observe the internal structure of mechanical equipment and find defects therein. This technology has the advantages of simple operation, high detection accuracy, and no impact on the normal operation of the equipment. It is widely used in the detection of various mechanical equipment.

[0003] The existing wind turbine gearbox inspection method is mainly carried out through regular disassembly and inspection. Although this method can detect some obvious faults, it is difficult to effectively detect some early or hidden faults. In addition, this method requires the gearbox to be disassembled, which not only wastes time and manpower, but may also affect the structure and performance of the gearbox. In the field of mechanical equipment inspection, there are already some devices and systems that use endoscopes for inspection, but these devices and systems are mainly for general mechanical equipment. For large and complex equipment such as wind turbine gearboxes, there is a lack of specialized endoscope inspection equipment and systems.

[0004] There are some shortcomings in the existing wind turbine gearbox inspection methods: First, the traditional periodic disassembly and inspection methods are time-consuming and labor-intensive, and cannot detect early or hidden faults in a timely manner. Secondly, the existing endoscopic inspection equipment and systems are mainly aimed at general mechanical equipment. For large and complex equipment such as wind turbine gearboxes, there is a lack of specialized endoscopic inspection equipment and systems, which makes it difficult to meet actual needs. In addition, existing endoscopic inspection equipment and systems usually do not have intelligent analysis functions, and require manual analysis and judgment, which is inefficient and easily affected by human factors. Therefore, how to develop an endoscopic inspection and fault analysis training system specifically for wind turbine gearboxes is an important issue currently facing this field. Summary of the invention

[0005] 1. Technical issues to be solved

[0006] In view of the shortcomings of the prior art, the present invention provides a wind turbine gearbox endoscopic inspection and fault analysis training system, which solves the problem that the existing endoscopic inspection equipment and systems usually do not have intelligent analysis functions, require manual analysis and judgment, are inefficient and easily affected by human factors.

[0007] (II) Technical solution

[0008] To achieve the above objectives, the present invention provides the following technical solutions: a wind turbine gearbox endoscopic inspection and fault analysis training system, comprising:

[0009] The gearbox model is equipped with a cooling device model and a lubricating device model on the outside and defective parts with various fault characteristics on the inside;

[0010] Endoscope, used for gearbox inspection;

[0011] The operating table is made of wear-resistant steel and has a manual turning function to facilitate observation of the interior of the gearbox;

[0012] Lighting equipment to support the effective use of endoscopes.

[0013] Preferably, the gearbox model includes defective parts such as gear tooth breakage, gear pitting, gear plastic deformation, gear wear and gear bonding, and the defective parts of the gearbox model are designed to be replaceable, so as to facilitate the simulation of different fault types during the training process;

[0014] The gearbox model is also equipped with sensors inside, which can monitor the operating status of the gearbox in real time and transmit the data to the operating console for display and analysis.

[0015] Preferably, the endoscope inspection and fault analysis training system further includes a display module for displaying the structure, composition and function of the gearbox, so as to enhance the trainees' understanding of the internal structure of the gearbox;

[0016] The endoscope has an intelligent analysis unit, which can automatically identify various defective parts inside the gear box and generate corresponding inspection reports.

[0017] Preferably, the endoscope supports tooth end face damage detection, high-speed and medium-speed tooth surface detection, and medium and low-speed gear tooth surfaces, and can quickly detect wear, rust, dents and pitting corrosion defects.

[0018] Preferably, the endoscopic detection function is implemented through AR, which can superimpose information on the internal structure of the gearbox and fault analysis on the endoscope display screen to provide real-time guidance.

[0019] Preferably, the endoscopy inspection and fault analysis training system integrates a digital twin, which can automatically adjust the teaching content according to the training operation and provide personalized learning feedback;

[0020] The endoscope inspection and fault analysis training system also integrates machine learning, which can optimize the endoscope inspection process based on historical fault data and improve detection efficiency and accuracy.

[0021] Preferably, the endoscope inspection and fault analysis training system supports multiple trainees to operate and learn simultaneously, and is equipped with multiple endoscopes and operating tables to improve training efficiency.

[0022] Preferably, the operating console is provided with a variety of interfaces, which can be linked with other detection equipment to achieve more comprehensive fault analysis and diagnosis functions;

[0023] The operating console and endoscope are also equipped with a data sharing unit that can update inspection records in real time to support subsequent analysis and training improvements.

[0024] (III) Beneficial effects

[0025] The present invention provides a wind turbine gearbox endoscope inspection and fault analysis training system. It has the following beneficial effects:

[0026] 1. The present invention can automatically identify various defective parts inside the gearbox and generate corresponding inspection reports through an intelligent analysis unit. Compared with the prior art that mainly relies on manual analysis of images or videos taken by an endoscope, the present invention greatly improves the accuracy of detection and reduces the influence of human factors. The present invention integrates a machine learning algorithm, which can optimize the inspection process of the endoscope based on historical fault data and improve detection efficiency and accuracy. Compared with the algorithms in the prior art that require a large amount of data training, the machine learning algorithm of the present invention is more efficient and can adapt to different fault characteristics more quickly.

[0027] 2. The present invention supports multiple trainees to operate and learn at the same time, and is equipped with multiple endoscopes and operating tables to improve the training efficiency. Compared with the existing training system that can only support single-person operation and learning, the present invention greatly improves the training efficiency and meets the learning needs of more trainees.

[0028] 3. The present invention enhances the trainees' understanding of the internal structure of the gearbox through a display module. Compared with the prior art that lacks a display of the gearbox structure, composition and function, the present invention better helps trainees master the relevant knowledge. The endoscopic detection function of the present invention is realized through AR, which can superimpose the information of the internal structure and fault analysis of the gearbox on the endoscope display screen to provide real-time guidance. Compared with the prior art training system that cannot provide real-time guidance, the present invention better assists trainees in fault analysis and diagnosis.

[0029] 4. The present invention integrates digital twins, which can automatically adjust teaching content according to practical training operations and provide personalized learning feedback. Compared with the existing training system that lacks adaptive teaching content, the present invention better meets the learning needs of different students. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 It is a basic flow chart of the present invention. DETAILED DESCRIPTION

[0031] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0032] Example:

[0033] like Figure 1 As shown, an embodiment of the present invention provides a wind turbine gearbox endoscope inspection and fault analysis training system, comprising:

[0034] The gearbox model is a scaled-down design of the gearbox structure of a megawatt-class doubly-fed wind turbine. It is equipped with a cooling device model and a lubrication device model on the outside, and has defective parts with various fault characteristics on the inside.

[0035] The endoscope has a 5-inch display, a resolution of 1280*720, a memory of 32G, a 6mm lens, 1 million pixels, a detection depth of 2m, a camera depth of 400mm, and an IP67 protection level. It is used for the inspection of gearboxes. The endoscope has high-definition images and excellent color reproduction, making it easier to find defects on the gearbox model and is more portable to use.

[0036] The operating table is made of wear-resistant steel and has a manual turning function to facilitate observation of the interior of the gearbox;

[0037] Lighting equipment to support the effective use of endoscopes.

[0038] The gearbox model includes different defective parts such as broken gear, gear pitting, gear plastic deformation, gear wear, gear bonding, etc. The defective parts of the gearbox model are designed to be replaceable, which is convenient for simulating different types of faults during the training process;

[0039] The gearbox model is also equipped with sensors that can monitor the operating status of the gearbox in real time and transmit the data to the operating console for display and analysis;

[0040] The endoscope inspection and fault analysis training system also includes a display module for demonstrating the structure, composition and function of the gearbox, which enhances the trainees’ understanding of the internal structure of the gearbox;

[0041] The endoscope has an intelligent analysis unit that can automatically identify different types of defects inside the gearbox and generate corresponding inspection reports;

[0042] The endoscope supports tooth end face damage detection, high-speed and medium-speed tooth surface detection, and medium- and low-speed gear tooth surface, and can quickly detect wear, rust, dents, pitting corrosion and other defects;

[0043] The endoscope inspection function is realized through AR, which can superimpose the information of the internal structure and fault analysis of the gearbox on the endoscope display screen to provide real-time guidance;

[0044] The endoscopy and fault analysis training system integrates digital twins, which can automatically adjust teaching content according to training operations and provide personalized learning feedback;

[0045] The endoscope inspection and fault analysis training system also integrates machine learning, which can optimize the endoscope inspection process based on historical fault data and improve detection efficiency and accuracy;

[0046] The endoscope inspection and fault analysis training system supports multiple trainees to operate and learn at the same time, and is equipped with multiple endoscopes and operating tables to improve training efficiency;

[0047] The operation console is equipped with multiple interfaces, which can be linked with other testing equipment to achieve more comprehensive fault analysis and diagnosis functions;

[0048] The operating console and endoscope are also equipped with a data sharing unit that can update inspection records in real time to support subsequent analysis and training improvements.

[0049] First, the wind turbine gearbox endoscopic inspection and fault analysis training system of the present invention can greatly improve the operating efficiency and safety of wind turbine gearboxes. By real-time monitoring and diagnosis of faults inside the gearbox, repairs and replacements can be carried out in a timely manner to avoid downtime caused by faults, thereby improving the operating efficiency of the wind turbine. At the same time, it can also provide a scientific basis for the maintenance and care of wind turbines and extend the service life of wind turbines. Secondly, it can also be used as an advanced tool for mechanical equipment detection technology. Through intelligent analysis units and machine learning algorithms, it can automatically identify the fault characteristics inside the gearbox and generate corresponding detection reports, thereby improving the efficiency and accuracy of detection.

[0050] In addition, the present invention can also be linked with other detection equipment to achieve more comprehensive fault analysis and diagnosis functions, providing new ideas and methods for the development of mechanical equipment detection technology. Finally, the present invention uses AR technology to superimpose information on the internal structure of the gearbox and fault analysis on the endoscope display screen, providing real-time guidance and improving the efficiency and accuracy of endoscopic inspection. At the same time, the present invention also integrates digital twins and machine learning technologies, which can automatically adjust the teaching content according to the actual training operation, provide personalized learning feedback, and improve the teaching effect of endoscopic inspection technology.

[0051] In general, the present invention can not only improve the operating efficiency and safety of wind turbine gearboxes, but also promote the development of mechanical equipment detection technology and endoscopic inspection technology, and has broad market demand and application prospects.

[0052] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A wind turbine gearbox endoscope inspection and fault analysis training system, characterized in that: include: The gearbox model is equipped with a cooling device model and a lubricating device model on the outside and defective parts with various fault characteristics on the inside; Endoscope, used for gearbox inspection; The operating table is made of wear-resistant steel and has a manual turning function to facilitate observation of the interior of the gearbox; Lighting equipment to support the effective use of endoscopes.

2. The wind turbine gearbox endoscope inspection and fault analysis training system according to claim 1 is characterized by: The gearbox model includes defective parts such as broken gear, pitting, plastic deformation, wear and bonding of gears. The defective parts of the gearbox model are designed to be replaceable, which is convenient for simulating different types of faults during training. The gearbox model is also equipped with sensors inside, which can monitor the operating status of the gearbox in real time and transmit the data to the operating console for display and analysis.

3. The wind turbine gearbox endoscope inspection and fault analysis training system according to claim 1 is characterized by: The endoscope inspection and fault analysis training system also includes a display module for displaying the structure, composition and function of the gearbox, so as to enhance the trainees' understanding of the internal structure of the gearbox; The endoscope has an intelligent analysis unit, which can automatically identify various defective parts inside the gear box and generate corresponding inspection reports.

4. The wind turbine gearbox endoscope inspection and fault analysis training system according to claim 1 is characterized by: The endoscope supports tooth end face damage detection, high-speed and medium-speed tooth surface detection, and medium and low-speed gear tooth surfaces, and can quickly detect wear, rust, dents and pitting corrosion defects.

5. The wind turbine gearbox endoscope inspection and fault analysis training system according to claim 1 is characterized by: The endoscopic inspection function is realized through AR, which can superimpose information on the internal structure of the gearbox and fault analysis on the endoscope display screen to provide real-time guidance.

6. The wind turbine gearbox endoscope inspection and fault analysis training system according to claim 5 is characterized by: The endoscopy inspection and fault analysis training system integrates digital twins, which can automatically adjust the teaching content according to the training operations and provide personalized learning feedback; The endoscope inspection and fault analysis training system also integrates machine learning, which can optimize the endoscope inspection process based on historical fault data and improve detection efficiency and accuracy.

7. The wind turbine gearbox endoscope inspection and fault analysis training system according to claim 1 is characterized by: The endoscope inspection and fault analysis training system supports multiple trainees to operate and learn at the same time and is equipped with multiple endoscopes and operating tables to improve training efficiency.

8. The wind turbine gearbox endoscope inspection and fault analysis training system according to claim 1 is characterized by: The operation console is provided with a variety of interfaces, which can be linked with other detection equipment to achieve more comprehensive fault analysis and diagnosis functions; The operating console and endoscope are also equipped with a data sharing unit that can update inspection records in real time to support subsequent analysis and training improvements.

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