Power distribution room equipment automatic modeling method based on point cloud data

Abstract

A kind of equipment automatic modeling method in power distribution room based on point cloud data, including establishing equipment database, collecting the overall data inside power distribution room, data acquisition is carried out to the internal connection structure of incoming line cabinet, metering cabinet, PT cabinet, outgoing line cabinet, contact cabinet and isolation cabinet, form original point cloud data, obtain processing data, form detailed data inside power distribution room, obtain data after denoising and import software to complete modeling several steps.By using point cloud data to the equipment inside power distribution room Data acquisition and processing mode, the efficiency and accuracy of the equipment modeling inside power distribution room can be improved, at the same time, by using the automatic calling mode of database, the automation degree of modeling can be improved, the efficiency of overall modeling is effectively guaranteed, the modeling time is shortened, the modeling accuracy is improved, after point cloud data acquisition, by comparing the calling of equipment in database, the accuracy of calling equipment when calling can also be effectively guaranteed, which provides effective guarantee for modeling.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of point cloud data application, and particularly relates to an equipment automatic modeling method in a power distribution room based on point cloud data. BACKGROUND

[0002] The power distribution room refers to a room for distributing electric energy, and can play a role in protecting, metering and distributing electric energy. The power distribution room usually comprises an incoming line cabinet, a metering cabinet, a PT cabinet, an outgoing line cabinet, a contact cabinet and an isolation cabinet.

[0003] The incoming line cabinet is a switch cabinet for introducing power from the outside, which is composed of a vacuum circuit breaker, a disconnector, three sets of three-coil current transformers, an arrester, a live display, a voltage transformer, a wire and the like. The main function is to distribute electric energy. The incoming line cabinet is usually provided with a vacuum circuit breaker for breaking. The vacuum circuit breaker has the protection functions of short-circuit and overcurrent prevention. In addition, a disconnector is provided for the safety of maintenance personnel. In addition, the incoming line cabinet is also provided with a current transformer and a voltage transformer, and the current and voltage values are measured. Therefore, the incoming line cabinet has the functions of protection, metering and monitoring, and can realize more comprehensive functions.

[0004] The metering cabinet is usually composed of a current transformer, a fuse, a voltage transformer of VV wiring and a live display, and is a kind of electric energy metering device. The metering device adopts the mode of high supply and high metering, and reflects the power consumption and load through the metering device such as a current transformer, a voltage transformer and an electric energy meter. The metering device installed at the user is responsible for protection by the user, and the device itself is not damaged or lost.

[0005] The PT cabinet is mainly composed of a voltage transformer, an isolation knife, a fuse and an arrester, and is used for voltage measurement. The voltage loop of the measurement meter is provided, and the operating box operating power supply and the like are also provided.

[0006] In addition, the outgoing line cabinet, the contact cabinet and the isolation cabinet have their special compositions and functions.

[0007] In the power distribution room, there are many devices due to the complex composition. With the further promotion of the electrification era, people's dependence on electricity is getting higher and higher. Many power equipment cannot be terminated at will once the equipment starts to operate. Therefore, in order to guarantee the power supply of the power equipment, the power distribution room needs to be monitored. The existing monitoring mode has changed from manual on-site monitoring mode to digital management mode. The digital management mode needs to model the equipment in the power distribution room. The existing modeling mode is relatively cumbersome, and the performance indicators and other factors of the equipment components need to be input one by one. The equipment parameters are manually adjusted, and automatic rapid modeling cannot be realized. SUMMARY

[0008] The purpose of the present invention is to provide an automated modeling method for equipment in a distribution room based on point cloud data, so as to solve the problems raised in the above background technology.

[0009] To achieve the above object, the present invention provides the following technical solutions:

[0010] An automated modeling method for equipment in a power distribution room based on point cloud data comprises the following steps:

[0011] The first step is to establish an equipment database, summarize the relevant performance parameters of the equipment involved in the power distribution room, enter them into the equipment database, and uniformly number them;

[0012] The second step is to collect the overall data inside the power distribution room, including the external structure and connection methods of the incoming cabinet, metering cabinet, PT cabinet, outgoing cabinet, contact cabinet and isolation cabinet;

[0013] The third step is to collect data on the internal connection structure of the incoming cabinet, metering cabinet, PT cabinet, outgoing cabinet, contact cabinet and isolation cabinet;

[0014] The fourth step is to aggregate the collected data in the second and third steps to form the original point cloud data;

[0015] The fifth step is to simplify the original point cloud data obtained in the fourth step. The simplified processing includes simplifying the point cloud data between the cabinets inside the power distribution room and simplifying the point cloud data inside each cabinet to obtain processed data.

[0016] The sixth step is to register the processed data obtained in the fifth step. After the registration is completed, the equipment data in the first step is called and the registered data is corrected. The overall data inside the power distribution room is then combined with the internal data of the incoming line cabinet, metering cabinet, PT cabinet, outgoing line cabinet, contact cabinet, and isolation cabinet to form the detailed data inside the power distribution room.

[0017] Step 7: De-noising the detailed data after kneading in step 6 to obtain de-noised data;

[0018] In the eighth step, the denoised data content is imported into the modeling software. At the same time, the equipment database established in the first step is also imported into the modeling software. The denoised data is compared with the equipment database. After the comparison is completed, the corresponding equipment is called. After the call is completed, the model is automatically formed to complete the modeling.

[0019] As a further solution of the present invention: the data collection in the second and third steps is performed using an I-Site8200ER three-dimensional laser scanner produced by MAPTEK, an Australian company.

[0020] As a further solution of the present invention: in the fifth step, the point cloud data simplification processing adopts a point cloud data simplification method of distance filtering for filtering.

[0021] As a further solution of the present invention: the distance-filtered point cloud data simplification method comprises the following steps:

[0022] The first step is to set the threshold of the sampling distance;

[0023] In the second step, the data points are judged according to the threshold set in the first step. If the spatial distance between a data point and the next data point in its arrangement direction is greater than the set value of the threshold, the point is retained. If the spatial distance between a data point and the next data point in its arrangement direction is less than the set value of the threshold, the point is deleted.

[0024] As a further solution of the present invention: the modeling software in the eighth step is 3dsMax software.

[0025] Compared with the prior art, the present invention has the following beneficial effects:

[0026] The present invention uses point cloud data to collect and process data of equipment inside the distribution room, which can improve the efficiency and accuracy of modeling of equipment inside the distribution room. At the same time, the automatic call of the database is adopted to improve the degree of automation of modeling, effectively ensure the efficiency of the overall modeling, shorten the modeling time, and improve the accuracy of modeling. After the point cloud data is collected, the call of the equipment in the database is completed through comparison, and the accuracy of the called equipment during the call can be effectively guaranteed, providing effective protection for modeling. DETAILED DESCRIPTION

[0027] The following is a clear and complete description of the technical solutions in the embodiments of the present invention. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of the present invention.

[0028] In addition, when an element in the present invention is referred to as being "fixed to" or "disposed on" another element, it may be directly on the other element or there may be an intermediate element. When an element is referred to as being "connected to" another element, it may be directly connected to the other element or there may be an intermediate element. The terms "vertical," "horizontal," "left," "right," and similar expressions used herein are for illustrative purposes only and do not represent the only implementation method.

[0029] In an embodiment of the present invention, a method for automatically modeling equipment in a power distribution room based on point cloud data is provided, comprising the following steps:

[0030] The first step is to establish an equipment database, summarize the relevant performance parameters of the equipment involved in the power distribution room, enter them into the equipment database, and uniformly number them. By establishing an equipment database, equipment data can be collected in advance to prepare for the subsequent automated comparison and call;

[0031] The second step is to collect the overall data inside the power distribution room, including the external structure and connection methods of the incoming cabinet, metering cabinet, PT cabinet, outgoing cabinet, contact cabinet and isolation cabinet;

[0032] The third step is to collect data on the internal connection structure of the incoming cabinet, metering cabinet, PT cabinet, outgoing cabinet, contact cabinet and isolation cabinet;

[0033] The fourth step is to aggregate the collected data in the second and third steps to form the original point cloud data;

[0034] The fifth step is to simplify the original point cloud data obtained in the fourth step. The simplified processing includes simplifying the point cloud data between the cabinets inside the power distribution room and simplifying the point cloud data inside each cabinet to obtain processed data.

[0035] The sixth step is to register the processed data obtained in the fifth step. After the registration is completed, the equipment data in the first step is called and the registered data is corrected. The overall data inside the power distribution room is then combined with the internal data of the incoming line cabinet, metering cabinet, PT cabinet, outgoing line cabinet, contact cabinet, and isolation cabinet to form the detailed data inside the power distribution room.

[0036] Step 7: De-noising the detailed data after kneading in step 6 to obtain de-noised data;

[0037] In the eighth step, the denoised data content is imported into the modeling software. At the same time, the equipment database established in the first step is also imported into the modeling software. The denoised data is compared with the equipment database. After the comparison is completed, the corresponding equipment is called. After the call is completed, the model is automatically formed to complete the modeling.

[0038] The data collection in the second and third steps is performed using an I-Site8200ER 3D laser scanner produced by MAPTEK, an Australian company.

[0039] In the fifth step, the point cloud data is simplified by using a distance filtering point cloud data simplification method.

[0040] The distance-filtered point cloud data simplification method comprises the following steps:

[0041] The first step is to set the threshold of the sampling distance;

[0042] Secondly, according to the threshold set in the first step, the data points are judged, if the spatial distance between a data point and the next data point in the arrangement direction is greater than the set value of the threshold, the point is reserved, if the spatial distance between a data point and the next data point in the arrangement direction is less than the set value of the threshold, the point is deleted.

[0043] The modeling software in the eighth step is 3dsMax software.

[0044] In the application, a device database is established in advance, data of the device is collected, then the I-Site8200ER three-dimensional laser scanner produced by the Australian MAPTEK company is used to scan the point cloud data of the device in the power distribution room, then the point cloud data is filtered by the distance filtering point cloud data simplification method, after the filtering is completed, the data is imported into the modeling software 3dsMax software, the point cloud data is compared with the database data, the device model is confirmed through the comparison, then the device is called, and the corresponding automatic modeling operation is completed.

[0045] The application can improve the efficiency and accuracy of the internal device modeling of the power distribution room by using the point cloud data to collect and process the data of the internal device of the power distribution room, meanwhile, the automatic calling of the database is adopted, which can improve the automation degree of the modeling, effectively ensure the efficiency of the overall modeling, shorten the modeling time, improve the modeling accuracy, after the point cloud data is collected, the calling of the device in the database is completed through the comparison, which can also effectively ensure the accuracy of the called device, and provide effective protection for the modeling.

[0046] It is apparent to those skilled in the art that the application is not limited to the details of the foregoing exemplary embodiments, and that the application can be implemented in other particular forms without departing from the spirit or essential characteristics of the application. Therefore, the embodiments should be considered as exemplary only, and not limiting, and the scope of the application is defined by the appended claims rather than by the foregoing description, and it is intended to include all changes falling within the meaning and scope of the equivalent elements of the claims.

[0047] In addition, it should be understood that, although the present specification is described in terms of embodiments, not every embodiment contains only one independent technical solution, and the description manner of the specification is only for the sake of clarity, those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can be combined appropriately to form other embodiments which can be understood by those skilled in the art.

Claims

1. A method for automatic modeling of equipment in a power distribution room based on point cloud data, characterized in that: The following steps are involved: The first step is to establish an equipment database, summarize the relevant performance parameters of the equipment involved in the power distribution room, enter them into the equipment database, and uniformly number them; The second step is to collect the overall data inside the power distribution room, including the external structure and connection methods of the incoming cabinet, metering cabinet, PT cabinet, outgoing cabinet, contact cabinet and isolation cabinet; The third step is to collect data on the internal connection structure of the incoming cabinet, metering cabinet, PT cabinet, outgoing cabinet, contact cabinet and isolation cabinet; The fourth step is to aggregate the collected data in the second and third steps to form the original point cloud data; The fifth step is to simplify the original point cloud data obtained in the fourth step. The simplified processing includes simplifying the point cloud data between the cabinets inside the power distribution room and simplifying the point cloud data inside each cabinet to obtain processed data. The sixth step is to register the processed data obtained in the fifth step. After the registration is completed, the equipment data in the first step is called and the registered data is corrected. The overall data inside the power distribution room is then combined with the internal data of the incoming line cabinet, metering cabinet, PT cabinet, outgoing line cabinet, contact cabinet, and isolation cabinet to form the detailed data inside the power distribution room. Step 7: De-noising the detailed data after kneading in step 6 to obtain de-noised data; In the eighth step, the denoised data content is imported into the modeling software. At the same time, the device database established in the first step is also imported into the modeling software. The denoised data is compared with the device database. After the comparison is completed, the corresponding device is called. After the call is completed, the model is automatically formed to complete the modeling; In the fifth step, the point cloud data is simplified by using a distance filtering point cloud data simplification method. The distance-filtered point cloud data simplification method comprises the following steps: The first step is to set the threshold of the sampling distance; In the second step, the data points are judged according to the threshold set in the first step. If the spatial distance between a data point and the next data point in its arrangement direction is greater than the set value of the threshold, the point is retained. If the spatial distance between a data point and the next data point in its arrangement direction is less than the set value of the threshold, the point is deleted.

2. The method for automatic modeling of equipment in a power distribution room based on point cloud data according to claim 1 is characterized in that: The data collection in the second and third steps is performed using an I-Site8200ER 3D laser scanner produced by MAPTEK, an Australian company.

3. The method for automatic modeling of equipment in a power distribution room based on point cloud data according to claim 1, characterized in that: The modeling software in the eighth step is 3ds Max software.