Closed equipment fault detection method based on mixed reality

Abstract

The invention provides a closed equipment fault detection method based on mixed reality, and belongs to the technical field of closed equipment fault detection. The technical problem to be solved is to provide a closed equipment fault detection method based on mixed reality. According to the technical scheme, the method comprises the steps that a three-dimensional model is established for the closed equipment, all parts in the closed equipment are classified according to the fault occurrence probability, the corresponding parts in the three-dimensional model are colored with different colors according to different probability grade division in the classification result, and the closed equipment is obtained. The position of a fault component is positioned through visual identification or combination with the width of the sensor; dividing the established three-dimensional model into a desktop model and a physical model to realize fixed switching; correcting spatial positioning of the obtained physical model by adopting a spatial anchor point positioning method, and freely configuring spatial anchor points of all parts in the closed equipment to obtain fault high-incidence points; the method is applied to closed equipment fault detection.

Description

Technical Field

[0001] The present invention provides a closed equipment fault detection method based on mixed reality, belonging to the technical field of closed equipment fault detection. Background Art

[0002] With the continuous development of power equipment, there are many types of substation equipment in use and a wide range of applications. As a result, substation equipment fails frequently and the causes of failures are complex, which greatly increases the maintenance work. When troubleshooting, it is necessary to quickly locate the position of the faulty components inside the substation equipment. It is crucial to ensure the safe and stable power supply by quickly troubleshooting.

[0003] However, in order to reduce the footprint, the new substation equipment currently in use adopts a small space combined structure. While reducing the space, it also brings difficulties to fault locating. In addition, unlike open equipment, the distribution of conductive parts of the substation with a concealed structure cannot be directly seen, and the entire structure inside the shell cannot be fully understood with the help of drawings, such as the conductive connection parts of the bolted connections, the distribution positions of the insulating pillars, and the equipment positions of important equipment. While this type of substation equipment improves convenience, it also puts higher requirements on equipment fault locating. Even with the help of sensors, infrared temperature measurement, sound wave detection and other detection methods, due to the unknown internal structure of the equipment, it is impossible to complete the fault location and fault characterization work at the same time, resulting in the inability to accurately and comprehensively complete fault detection and subsequent diagnosis work, which will bring problems such as misjudgment, insufficient spare parts, and insufficient live protection to the subsequent work.

[0004] Currently, this detection problem can be addressed by testing and confirming the equipment after a power outage, or by inspecting and repairing the spare equipment using a patchwork approach. Although this solves the problem temporarily, it cannot be handled with high quality when resources are tight and the power supply safety level is high. Summary of the Invention

[0005] In order to overcome the deficiencies in the prior art, the present invention aims to provide a closed equipment fault detection method based on mixed reality.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is: a closed equipment fault detection method based on mixed reality, comprising the following fault detection steps: Step 1: Create a 3D model of the enclosed equipment and classify the components within the enclosed equipment according to the probability of failure. Based on the different probability levels in the classification results, color the corresponding components in the 3D model with different colors. Locate the position of the faulty component through visual identification or by combining the sensor width. Step 2: Divide the established 3D model into a desktop model and a physical model to achieve fixed switching; Step 3: Use the spatial anchor point positioning method to correct the spatial positioning of the physical model obtained in step 2. Freely configure the spatial anchor points of each component inside the closed equipment to obtain high-incidence points of failures and adjust the spatial position of the faulty components for subsequent modification. Step 4: The inspector wears the smart wearable device to obtain the positioning coordinates and dimension data of each component of the equipment, and views and operates them in the established physical model. When the equipment is operating normally, the equipment is disassembled using spatial anchor points combined with structural classification to quickly locate the position of the faulty component and prepare replacement components to assist in subsequent maintenance work.

[0007] The specific method of step 1 is: each component of the equipment is divided into three categories according to the probability of failure: The main substation equipment is colored orange; The conductive connectors are colored yellow, red, and green according to the phase sequence; Supporting structural parts, colored gray; Then, each component is constructed into a completely identical three-dimensional model according to the actual situation, and has the function of independent disassembly. A control system is set up to distinguish each component according to the insulation support, insulation package, metal bracket, equipment body, equipment accessories, fixing bolts, operating structure, and five-protection locking.

[0008] The specific steps of using the spatial anchor point positioning method in step 3 are: Set the red cross reference point as the initial position of the spatial anchor point to ensure that the 3D model is aligned with the real object at this position; Set up spatial operation buttons to provide displacement, rotation, and scaling functions to adjust the overall spatial position of the 3D model; The three-dimensional model is simplified and the number of triangles is controlled within 100,000. The excess parts are cut and displayed in blocks, and the non-operational parts are replaced with only shells and low-polygon models.

[0009] The beneficial effects of the present invention compared with the prior art are as follows: the fault detection scheme provided by the present invention includes dividing equipment components according to the fault probability level, fixed switching between desktop and physical models, and configuration of spatial anchor points. First, the component structure division of the equipment is completed, the color structure of the three-dimensional model is distinguished, and the fault position is visually identified or located in combination with the sensor width. Secondly, models of two sizes, desktop and physical, are formed to facilitate both indoor and outdoor work needs. Finally, with the help of spatial anchor points and degree of freedom configuration, combined with the previous two steps, the high-incidence points of faults are obtained, and the spatial position is flexibly adjusted to confirm the transformation plan; each detection step adopted by the present invention provides convenience for subsequent work, and the overall positioning obtains the external structural dimensions of the equipment, provides data support for the external metal shell, fixed steel frame, etc., presents the overall structure of the internal space, and facilitates conductor preparation, insulation replacement, and new equipment size. The disassembly of each component can provide a new method for troubleshooting, which can be completed in a live state, which is impossible with traditional full power outage and non-contact measurement. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The present invention will be further described below with reference to the accompanying drawings: Figure 1 This is an operational effect diagram of the present invention for classifying the structure of equipment components; Figure 2 This is a diagram showing the effect of the operation of the physical model before spatial correction is performed by the present invention; Figure 3 This is a diagram showing the effect of the present invention performing spatial correction on the physical model. DETAILED DESCRIPTION

[0011] The present invention provides a closed equipment fault detection method based on mixed reality, which can be applied to the fault detection, maintenance and optimization of substation switchgear, GIS combination electrical appliances, transformers and other substation equipment and other closed equipment with concealed structures. Using this method, the three-dimensional structure of the switchgear is specifically divided into three categories according to the level of fault probability. The equipment is disassembled by adopting spatial anchor points combined with structural classification, which can quickly locate the fault part. It is more suitable for equipment with complex internal structure and high importance that cannot be shut down for maintenance. The present invention can locate the position of specific internal fault components when the equipment is operating normally, which facilitates and assists in subsequent maintenance work, so as to reasonably prepare replacement parts and prevent electric shock accidents caused by accidentally touching live parts.

[0012] The closed equipment fault detection method provided by the present invention specifically includes the following steps: Step 1: Structural classification of closed equipment according to the probability of failure: The existing power outage maintenance cannot be applied to important equipment, such as 10kV incoming line switchgear. A power outage will cause the entire busbar to be out of power, and at the same time affect multiple power supply lines on the busbar. In addition, the existing drawings cannot accurately and intuitively locate the live position and fault position. For example, the upper and lower compartments of the switchgear and the five-protection baffles are internal structures and are different. Once the equipment casing is entered for maintenance, the adjacent live positions become a life-threatening safety hazard, which brings a lot of inconvenience to the daily operation and maintenance of such equipment.

[0013] like Figure 1 As shown, in order to quickly locate the fault position from the established three-dimensional model, the present invention classifies equipment components according to the probability of fault occurrence, mainly into three categories: main substation equipment (orange for bushing-type CT), conductive connectors (yellow, red, and green according to phase sequence), and supporting structural components (gray for steel structure brackets). Structural segmentation and color differentiation are performed according to function, and each component is constructed into a completely identical three-dimensional model according to actual conditions, with the function of independent disassembly. In a production environment, the black symbol is the spatial anchor point positioning mark, and the right side is the fine-tuning operation selection. With the help of the physical model, more spatial positioning freedom requirements such as fault spatial positioning, collision judgment after modification, and feasibility correction of the new position are carried out. At the same time, a control system is set to distinguish each component according to insulating pillars, insulating envelopes, metal brackets, equipment bodies, equipment accessories, fixing bolts, operating structures, and five-protection locks. According to the needs of operation and maintenance, the above categories are independently operated to control their appearance and hiding.

[0014] The use of component classification is a prerequisite for rapid location of equipment failures, dynamic update of sensor data, and accurate positioning of command and deployment. What distinguishes this invention from the current application of three-dimensional model detection is that the three-dimensional model is classified and processed according to the actual operation and maintenance. This avoids problems such as low flexibility in manual customization, inability of sensor access to follow the flexible adjustment of modules, insufficient visual intuitiveness and unclear priorities.

[0015] Step 2: Divide the created 3D models into two categories: desktop models and physical models: Since the three-dimensional model used for operation is too large to be convenient to use when formulating operation and maintenance strategies, a miniature model with equal proportions is produced to show the overall conductive connection status of the distribution room and the above-mentioned structural classification; work needs can be met by establishing desktop models and physical models, and excessive operations will lead to attention diversion and redundant operations; the present invention can construct the switch cabinet assembly of the distribution room and its internal components into two types: desktop models and real-life models that are easy to use in work, and quickly switch to reduce unnecessary operations; the provided desktop model is used on ordinary office desks indoors, and the real-life model can be used in the actual environment of production equipment in conjunction with step three.

[0016] For example, in 220kV GIS combined electrical equipment, the exterior is entirely wrapped in high-pressure steel pipes, the interior is filled with high-pressure SF6 gas, the conductors are close together, there are many types of insulation supports, and the operation and maintenance requirements are different. After structural division, a physical model is used for 1:1 three-dimensional presentation, and the key fault locations can be quickly obtained through the outer shell with the help of structural classification methods.

[0017] Based on mixed reality MR, the present invention uses the two types of models, desktop models and physical models, to serve both office and field operation work needs, avoid redundant operations on three-dimensional models, and improve the efficiency of quickly obtaining key equipment results during work. Combined with step one, the key fault parts in the equipment can be quickly located indoors and outdoors, which is a clear division of three-dimensional model operation methods based on production practice.

[0018] Step 3: Perform spatial correction on the physical model: Since traditional simulations cannot be superimposed with real objects, and AR superposition has the disadvantages of drifting and being uncontrollable, the present invention adopts a spatial anchor point positioning method to develop a stacking and fine-tuning method suitable for spatial positioning.

[0019] In production practice, the correction of 3D models using automatic graphic adjustment suffers from inaccurate positioning in Class II environments and limited freedom of manual adjustment. For example, in the comparison before and after the transformation of the distribution room, the cost of manual customization is too high, and graphic recognition can only position the 3D model on the existing physical object.

[0020] To address this problem, the present invention provides a spatial positioning method with higher degrees of freedom. With the help of spatial anchor points and a fine-tuning operation interface, manual correction methods can be used in various working conditions to obtain the spatial model position configuration required in practice. like Figure 2 and Figure 3 As shown, specifically by setting the red cross reference point as the initial position of the spatial anchor point, ensuring that the position has made the three-dimensional model fit the real object relatively well; then setting the spatial operation button to provide displacement, rotation, and scaling functions to adjust the overall spatial position of the three-dimensional structure; in order to improve operational stability and obtain a quick response, simplified production requirements for the three-dimensional model are also formulated, controlling the number of triangles within 100,000, and the excess part is displayed in blocks by cutting, and the non-operation part is replaced only with the shell and the low-polygon model.

[0021] Through the above-mentioned operations such as anchor points, fine-tuning, low-polygon replacement, and device cutting display, it is possible to ensure that the spatial stacking is completely consistent, thereby reducing problems such as drift, jamming, and uncertainty in the fitting position. Different from graphic recognition, it has more degrees of freedom and can be manually adjusted to the new installation position after the equipment is modified. It can also be freely configured according to the actual environmental conditions, and the foundation settlement, object obstruction, conductive reliability, etc. can be judged according to the spatial effect to form a modification plan.

[0022] The present invention not only overcomes the drawbacks of low feasibility, poor safety and low efficiency of traditional detection methods, but also can reuse various data of the equipment, improve the problem of inaccurate data through data reuse rate, and has the characteristics of intuitive visualization and convenient operation. The operator only needs to wear a smart wearable device to view the operation.

[0023] In an embodiment of the present invention, through the on-site practical application of fault detection and diagnosis of 230-segment GIS combination electrical appliances in a 220kV local substation, fault location, spare parts storage, and maintenance process formulation are efficiently completed. The abnormal noise diagnosis application of the incoming line interval of the switch cabinet in the 10kV distribution room of a 110kV local substation can quickly locate the position of the insulating sleeve and formulate a plan for replacing adjacent conductors.

[0024] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A closed equipment fault detection method based on mixed reality, characterized in that: The following fault detection steps are included: Step 1: Establish a 3D model for the closed equipment, classify the components inside the closed equipment according to the probability of failure, color the corresponding components in the 3D model with different colors according to the different probability levels in the classification results, and locate the position of the faulty component through visual intuitive identification or combined with the sensor width; Step 2: Divide the established 3D model into a desktop model and a physical model to achieve fixed switching; Step 3: Use the spatial anchor point positioning method to correct the spatial positioning of the physical model obtained in step 2, freely configure the spatial anchor points of each component inside the closed equipment, obtain the high-incidence points of failures, and adjust the spatial position of the faulty components for subsequent transformation; Step 4: The inspectors wear smart wearable devices to obtain the positioning coordinates and dimension data of each component of the equipment, view and operate them in the established physical model, and disassemble the equipment using spatial anchor points combined with structural classification when the equipment is operating normally, quickly locate the position of the faulty components, and prepare replacement components to assist in subsequent maintenance work.

2. The closed equipment fault detection method based on mixed reality according to claim 1, characterized in that: The specific method of step 1 is: the various components of the equipment are divided into three categories according to the probability of failure: The main substation equipment is colored orange; The conductive connectors are colored yellow, red, and green according to the phase sequence; Supporting structural parts, colored gray; Then, each component is built into a completely identical three-dimensional model according to the actual situation, and has the function of independent disassembly. A control system is set up to distinguish the components according to the insulating pillars, insulating envelopes, metal brackets, equipment bodies, equipment accessories, fixing bolts, operating structures, and five-protection locks.

3. The closed equipment fault detection method based on mixed reality according to claim 1, characterized in that: The specific steps of using the spatial anchor point positioning method in step 3 are: Set the red cross reference point as the initial position of the spatial anchor point to ensure that the 3D model and the real object are aligned at this position; Set up spatial operation buttons to provide displacement, rotation, and scaling functions to adjust the overall spatial position of the 3D model; The 3D model is simplified and the number of triangles is controlled within 100,000. The excess parts are cut and displayed in blocks, and the non-operating parts are replaced only with shells and low-polygon models.

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