Limited space operator positioning method and device, equipment and storage medium

Abstract

The invention discloses a limited space operator positioning method, device and equipment and a storage medium, and the method comprises the steps: collecting the point cloud data of a target limited space, and constructing a three-dimensional digital model of the target limited space based on the point cloud data; generating initial positioning information of the operator based on the communication data of the UWB base station network and the positioning tag; adjusting the initial positioning information according to the signal arrival time and the signal strength of each UWB base station in the target limited space to obtain target positioning information; and mapping the target positioning information to the three-dimensional digital model, and displaying the position and the movement track of the operator in real time. The initial positioning information is adjusted according to the signal arrival time and the signal intensity of each UWB base station, and the obtained target positioning information is mapped to the three-dimensional digital model constructed through the point cloud data, so that compared with the prior art, the positioning accuracy of the limited space operation personnel and the safety of the limited space operation are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of safety management of limited space operation, and in particular to a limited space operator positioning method, device, equipment and storage medium. BACKGROUND

[0002] The limited space refers to a space that is closed or partially closed, is not designed as a fixed work place, personnel can enter the operation, and is easy to cause accumulation of toxic and harmful, flammable and explosive substances or insufficient oxygen content. Limited space operation must be implemented under the supervision system, and the rapid searching and positioning of the operator in the limited space, trajectory query and playback are very crucial for improving the personnel management efficiency in the limited space. However, the limited space operation site is usually closed or semi-closed, and the external supervisors cannot observe the specific position of the operator in the limited space in real time, which leads to untimely rescue or unnecessary casualties caused by blind rescue.

[0003] However, the existing operator positioning in the limited space usually adopts the positioning technology based on GPS and the WiFi / Bluetooth beacon positioning technology. The positioning technology based on GPS has the problem of signal attenuation in the closed or semi-closed space, and the positioning error is often more than 10 meters, which cannot meet the safety monitoring demand of centimeter-level precision in the limited space. The WiFi / Bluetooth beacon positioning technology can solve the signal coverage problem, but is easily interfered by the multipath effect such as metal structure and equipment shielding, which leads to the jump of the positioning trajectory (typical error of 3-5 meters).

[0004] Therefore, there is an urgent need for an operator positioning method in the limited space, which can realize the accurate positioning of the operator in the limited space, so as to improve the safety of the limited space operation. SUMMARY

[0005] The main purpose of the present application is to provide a limited space operator positioning method, device, equipment and storage medium, which aims to solve the technical problem of insufficient positioning accuracy of the operator in the limited space in the prior art, which leads to the reduction of safety of the limited space operation.

[0006] To achieve the above purpose, the present application provides a limited space operator positioning method, which comprises the following steps:

[0007] Collecting point cloud data of a target limited space, and constructing a three-dimensional digital model of the target limited space based on the point cloud data;

[0008] Generating initial positioning information of an operator based on the communication data of a UWB base station network and a positioning tag, the UWB base station network comprising a plurality of UWB base stations, the UWB base stations being installed in the target limited space, and the positioning tag being worn on the operator;

[0009] Adjust the initial positioning information according to the signal arrival time and signal strength of each UWB base station in the target limited space, and obtain target positioning information;

[0010] Map the target positioning information to the three-dimensional digital model, and display the position and motion trajectory of the worker in real time.

[0011] Optionally, the step of collecting point cloud data of the target limited space and constructing a three-dimensional digital model of the target limited space based on the point cloud data comprises:

[0012] Emit a probe light beam modulated by a miniaturized MEMS grating array in the target limited space, so that the probe light beam forms multiple reflections in the target limited space;

[0013] Collect the light signal sequence returned during the reflection process, and determine the distance information corresponding to the light signal sequence according to the light signal sequence;

[0014] Perform folding operation on the distance information to obtain folding path data, and generate point cloud data of the target limited space based on the folding path data;

[0015] Construct a three-dimensional digital model of the target limited space based on the point cloud data.

[0016] Optionally, the step of adjusting the initial positioning information according to the signal arrival time and signal strength of each UWB base station in the target limited space to obtain target positioning information further comprises:

[0017] Input the target positioning information into a convolutional neural network to obtain a residual compensation amount;

[0018] Residual compensation is performed on the target positioning information based on the residual compensation amount to obtain corrected target positioning information.

[0019] Optionally, the step of inputting the target positioning information into a convolutional neural network to obtain a residual compensation amount comprises:

[0020] Input the target positioning information into a signal strength matrix in the convolutional neural network to obtain an input matrix;

[0021] Convolve the input matrix through four convolutional layers in the convolutional neural network to obtain convolutional features;

[0022] Flatten the convolutional features to obtain a one-dimensional feature vector, and pass the one-dimensional feature vector through two fully connected layers and an output layer in the convolutional neural network to obtain a residual compensation amount.

[0023] Optionally, the step of generating initial positioning information of the worker based on the communication data between the UWB base station network and the positioning tag comprises:

[0024] When the positioning signal of the positioning tag is received by the UWB base station network, the positioning signal is recorded;

[0025] When the positioning signal is within the detection range of the UWB base station network, the real-time distance between the positioning signal and the UWB base station is determined according to a preset detection period;

[0026] The positioning signal and the real-time distance are mapped to the local coordinate system corresponding to the UWB base station to determine the local coordinate position of the positioning signal in the local coordinate system;

[0027] The local coordinate position is sorted based on a timestamp sequence of the preset detection period to generate the initial positioning information of the worker.

[0028] Optionally, the step of adjusting the initial positioning information according to the signal arrival time and signal strength of each UWB base station in the target limited space to obtain target positioning information comprises:

[0029] The position representation of the worker is determined by a multilateration algorithm according to the signal arrival time and signal strength of each UWB base station in the target limited space;

[0030] The position representation is compared with the deployment topology of each UWB base station in the UWB base station network to generate a correction factor;

[0031] The position representation is corrected using the correction factor to obtain a corrected position representation;

[0032] The initial positioning information is adjusted based on the corrected position representation to obtain target positioning information.

[0033] Optionally, after the step of mapping the target positioning information to the three-dimensional digital model to display the position and motion trajectory of the worker in real time, the method further comprises:

[0034] The real-time positioning data of the worker is integrated and linked with the monitoring video, and it is determined whether the worker has an abnormal action state;

[0035] If the worker has an abnormal action state, the monitoring video lens is automatically scheduled based on the abnormal action state of the worker, and a target object is locked for shooting to obtain a target monitoring screen;

[0036] The target monitoring screen and the target object's location data are uploaded to the backend via data transmission for early warning processing.

[0037] Furthermore, to achieve the above objectives, the present invention also proposes a positioning device for personnel working in confined spaces, the device comprising:

[0038] A digital model building module is used to collect point cloud data of a target finite space and build a three-dimensional digital model of the target finite space based on the point cloud data.

[0039] The positioning information generation module is used to generate the initial positioning information of the operator based on the communication data between the UWB base station network and the positioning tag. The UWB base station network includes multiple UWB base stations, which are installed in the target confined space, and the positioning tag is worn on the operator.

[0040] The positioning information adjustment module is used to adjust the initial positioning information according to the signal arrival time and signal strength of each UWB base station within the target limited space to obtain target positioning information;

[0041] The positioning information mapping module is used to map the target positioning information onto the three-dimensional digital model, and to display the position and movement trajectory of the operator in real time.

[0042] Furthermore, to achieve the above objectives, the present invention also proposes a confined space worker positioning device, the device comprising: a memory, a processor, and a confined space worker positioning program stored in the memory and executable on the processor, the confined space worker positioning program being configured to implement the steps of the confined space worker positioning method described above.

[0043] In addition, to achieve the above objectives, the present invention also proposes a storage medium storing a confined space worker positioning program, wherein when the confined space worker positioning program is executed by a processor, it implements the steps of the confined space worker positioning method described above.

[0044] The application discloses collecting point cloud data of a target limited space, and constructing a three-dimensional digital model of the target limited space based on the point cloud data; generating initial positioning information of a worker based on communication data of a UWB base station network and a positioning tag, the UWB base station network comprising a plurality of UWB base stations, the UWB base stations being installed in the target limited space, and the positioning tag being worn on the worker; adjusting the initial positioning information according to signal arrival time and signal strength of each UWB base station in the target limited space to obtain target positioning information; and mapping the target positioning information to the three-dimensional digital model to display the position and motion track of the worker in real time. Since the three-dimensional digital model is constructed based on the point cloud data of the target limited space, the initial positioning information is adjusted according to the signal arrival time and signal strength of each UWB base station, and the obtained target positioning information is mapped to the three-dimensional digital model, compared with the prior art, the positioning accuracy of the worker in the limited space is effectively improved, the accurate matching and mapping of the positioning data and the space structure are realized, and the safety of the limited space operation is improved. BRIEF DESCRIPTION OF DRAWINGS

[0045] Figure 1 A flowchart of a first embodiment of the limited space worker positioning method of the application is shown in the figure.

[0046] Figure 2 A flowchart of a second embodiment of the limited space worker positioning method of the application is shown in the figure.

[0047] Figure 3 A flowchart of a third embodiment of the limited space worker positioning method of the application is shown in the figure.

[0048] Figure 4 A structure block diagram of a first embodiment of the limited space worker positioning device of the application is shown in the figure.

[0049] Figure 5 A structure diagram of the limited space worker positioning device related to the hardware running environment of the embodiment scheme of the application is shown in the figure.

[0050] The implementation, functional features and advantages of the application will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0051] It should be understood that the specific embodiments described herein are intended to explain the application, but not to limit the application.

[0052] The embodiment of the application provides a limited space worker positioning method, referring to Figure 1 , Figure 1 A flowchart of a first embodiment of the limited space worker positioning method of the application is shown in the figure.

[0053] In this embodiment, the limited space worker positioning method comprises steps S10-S40:

[0054] Step S10: Collect point cloud data of the target limited space, and construct a three-dimensional digital model of the target limited space based on the point cloud data.

[0055] It should be noted that the execution subject of the present embodiment can be a computer server device with data processing, network communication and program running functions applied in the limited space worker positioning scene, such as servers, tablets, personal computers, etc., or an electronic device (such as a limited space worker positioning device) capable of realizing the above functions. The following will take the system (hereinafter referred to as the system) containing the limited space worker positioning device as an example to illustrate the present embodiment and the following embodiments.

[0056] It should be understood that the point cloud data is a collection of discrete points collected by a three-dimensional scanning device (such as a laser radar, a structured light scanning system, etc.), each point containing at least three-dimensional coordinate information, and some data can also contain additional information such as color, reflectivity or normal vector.

[0057] It can be understood that the three-dimensional digital model is a model that accurately describes the shape, structure and other characteristics of the target limited space using digital technology. It is constructed by a series of processing of point cloud data, including data filtering (removing noise points), gridding (converting point cloud data into regular grid structures such as triangles or quadrilaterals), texture mapping (mapping the collected image texture information to the grid model), etc.

[0058] In specific implementation, the point cloud data of the target limited space can be collected by a laser radar, and then an initial three-dimensional digital model is generated based on the point cloud data. The initial three-dimensional digital model is then optimized for precision to make the model precision reach a predetermined level, and the three-dimensional digital model of the target limited space is obtained.

[0059] Step S20: Generate initial positioning information of the worker based on the communication data of the UWB base station network and the positioning tag, the UWB base station network comprising a plurality of UWB base stations, the UWB base stations being installed in the target limited space, and the positioning tag being worn on the worker.

[0060] It should be understood that the UWB base station network is a system composed of multiple UWB base stations for positioning. In a target limited space, these UWB base stations are strategically installed at different locations. Their role is similar to a node of a positioning network. For example, in an underground parking lot, a limited space, evenly distributed UWB base stations can form a network covering the entire area. Each UWB base station has the ability to receive and send UWB signals, and by receiving the signals emitted by the positioning tag, combined with its own location information, it can cooperatively calculate the position of the positioning tag (i.e. the worker).

[0061] It should be explained that the communication data between the UWB base station network and the positioning tag refers to the signal information transmitted between the UWB base station and the positioning tag for determining the position. These data contain time stamps, signal strength and other key information. For example, when the positioning tag emits a signal, the UWB base station will record the time when the signal is received, and this time information will be included in the communication data. At the same time, the strength of the signal will also be recorded, because the signal strength can assist in determining the distance between the positioning tag and the base station, and the stronger the signal usually means the closer the distance between the two.

[0062] It should be understood that the initial positioning information is generated by the communication data between the UWB base station network and the positioning tag, which is a preliminary judgment of the position of the worker. It is a position coordinate data that represents the approximate position of the worker in the target limited space.

[0063] It should be noted that the positioning tag is a small electronic device that can be worn on the worker's body. Its main function is to emit UWB signals to be received by UWB base stations. These tags are usually designed to be lightweight and easy to carry for workers. For example, it can be attached to the worker's clothing like a badge, or integrated into a small wearable device. The positioning tag will periodically send UWB signals containing identity information and other information during work, so that the UWB base station network can identify different workers and determine their positions through signal characteristics.

[0064] In a specific implementation, when the UWB base station network receives a positioning signal of a positioning tag, the positioning signal can be recorded; when the positioning signal is within the detection range of the UWB base station network, the real-time distance between the positioning signal and the UWB base station can be determined according to a preset detection period; the positioning signal and the real-time distance can be mapped to a local coordinate system corresponding to the UWB base station to determine a local coordinate position of the positioning signal in the local coordinate system; and the local coordinate position can be sorted based on a time stamp sequence of the preset detection period to generate initial positioning information of a worker.

[0065] It can be understood that the above-mentioned preset detection period can be customized according to specific application scenarios, and the embodiment does not limit this.

[0066] Step S30: adjusting the initial positioning information according to the signal arrival time and signal strength of each UWB base station in the target limited space to obtain target positioning information.

[0067] It should be explained that the signal arrival time is the time when the signal emitted by the positioning tag arrives at the UWB base station. In the UWB positioning system, the accuracy of time can reach nanoseconds. For example, the UWB base station can accurately record the time value of the instant when the positioning tag signal is received. This time information is crucial for determining the distance between the positioning tag and the UWB base station. Assuming that the speed of signal propagation in the air is known (about the speed of light), by measuring the signal arrival time, the distance of signal propagation can be calculated, thereby helping to determine the position of the positioning tag.

[0068] The signal strength is the strength of the signal emitted by the positioning tag when it arrives at the UWB base station, which can assist in determining the distance between the positioning tag and the UWB base station. In some positioning algorithms, signal strength and signal arrival time can be combined to improve positioning accuracy. For example, when the signal strength is low, it may mean that there is an obstruction or the distance between the positioning tag and the UWB base station is far, at which time the signal arrival time can be combined to more accurately estimate the distance, or the signal strength of multiple UWB base stations can be weighted and averaged to optimize the positioning result.

[0069] It should be noted that in order to improve the positioning accuracy of the limited space worker, in the specific implementation, the position representation of the worker can be determined by a multilateration algorithm according to the signal arrival time and signal strength of each UWB base station in the target limited space; the deployment topology of each UWB base station in the UWB base station network is compared to generate a correction factor; the position representation is corrected using the correction factor to obtain a corrected position representation; the initial positioning information is adjusted based on the corrected position representation to obtain target positioning information.

[0070] Step S40: mapping the target positioning information to the three-dimensional digital model to display the position and motion trajectory of the worker in real time.

[0071] It should be noted that the target positioning information can be mapped to the three-dimensional digital model, and the three-dimensional digital model can be dynamically rendered by a real-time rendering engine, and the position and motion trajectory of the worker can be visualized and displayed in combination with lighting, shadow and perspective effects.

[0072] It should be noted that, in order to improve the efficiency of emergency response in the limited space and minimize the loss and harm caused by the accident, the alarm signal from the positioning tag can be received; the position of the corresponding worker is locked based on the alarm signal; and the alarm personnel position is highlighted on the three-dimensional digital model.

[0073] It should be noted that, in order to effectively improve the efficiency and accuracy of safety monitoring in the target limited space and reduce the risk of accidents, after step S40, steps S50-S70 are further included:

[0074] Step S50: integrate and link the real-time positioning data of the worker with the monitoring video, and determine whether the worker has an abnormal action state.

[0075] Step S60: If the worker has an abnormal action state, automatically dispatch the monitoring video lens based on the abnormal action state of the worker, lock the target object for shooting, and obtain the target monitoring picture.

[0076] Step S70: upload the target monitoring picture and the positioning data of the target object to the background through data transmission for early warning processing.

[0077] It should be understood that when the abnormal action state is detected, the system can automatically dispatch the monitoring video lens to lock the target object and shoot the target monitoring picture. This allows the monitoring personnel to obtain clear and accurate on-site pictures in the first time, quickly understand the specific details of the abnormal situation, such as the position of the worker, the surrounding environment, and the performance of the abnormal behavior, etc. Based on these detailed information, more accurate emergency response can be performed, and timely rescue, evacuation or other corresponding measures can be taken to minimize the loss and harm caused by the accident.

[0078] The embodiment discloses collecting point cloud data of a target limited space, and constructing a three-dimensional digital model of the target limited space based on the point cloud data; generating initial positioning information of a worker based on communication data of a UWB base station network and a positioning tag, the UWB base station network comprising a plurality of UWB base stations, the UWB base stations being installed in the target limited space, and the positioning tag being worn on the worker; adjusting the initial positioning information according to signal arrival times and signal strengths of the UWB base stations in the target limited space to obtain target positioning information; and mapping the target positioning information to the three-dimensional digital model to display positions and motion trajectories of the worker in real time. Compared with the prior art, the embodiment effectively improves positioning accuracy of a worker in a limited space, and realizes accurate matching and mapping of positioning data and a space structure, thereby improving safety of work in a limited space.

[0079] Reference Figure 2 , Figure 2 is a flowchart of a second embodiment of a method for positioning a worker in a limited space.

[0080] Based on the first embodiment, in the embodiment, the step S10 comprises steps S101-S104.

[0081] Step S101: Emitting a detection light beam modulated by a miniaturized MEMS grating array in a target limited space, so that the detection light beam forms multiple reflections in the target limited space.

[0082] Step S102: Collecting a light signal sequence returned in the reflection process, and determining distance information corresponding to the light signal sequence according to the light signal sequence.

[0083] Step S103: Performing a folding operation on the distance information to obtain folding path data, and generating point cloud data of the target limited space based on the folding path data.

[0084] Step S104: Constructing a three-dimensional digital model of the target limited space based on the point cloud data.

[0085] It should be noted that the miniaturized MEMS grating array is an optical element based on micro-electro-mechanical system (MEMS) technology. It is composed of a large number of small grating structures, which can move and modulate quickly under the action of electricity. Each grating can be regarded as a small optical element, which can diffract and modulate light.

[0086] It needs to be explained that the miniaturized MEMS grating array can quickly perform beam scanning, and combined with the light field folding algorithm, efficient laser path reconstruction can be realized. This enables the rapid acquisition of a large amount of point cloud data in a limited space, shortens the data acquisition time, improves the work efficiency, and can meet the needs of real-time or rapid modeling, such as playing an important role in emergency rescue, rapid mapping and the like.

[0087] In addition, the miniaturized MEMS grating array has stronger adaptability to environmental changes and better anti-interference ability. It can work stably under different light conditions, temperature conditions and other complex environments, ensuring the accuracy and continuity of data acquisition and the reliability of three-dimensional digital model construction.

[0088] The embodiment discloses emitting a detection beam modulated by a miniaturized MEMS grating array in a target limited space, so that the detection beam forms multiple reflections in the target limited space; collecting a light signal sequence returned in the reflection process, and determining distance information corresponding to the light signal sequence according to the light signal sequence; performing folding operation on the distance information to obtain folding path data, and generating point cloud data of the target limited space based on the folding path data; and constructing a three-dimensional digital model of the target limited space based on the point cloud data. Since the embodiment constructs a three-dimensional digital model of a target limited space by collecting point cloud data of the target limited space through a miniaturized MEMS grating array, compared with the prior art, the embodiment not only improves the point cloud data acquisition speed and efficiency to meet the rapid modeling requirement, but also ensures the reliability of three-dimensional digital model construction.

[0089] Reference Figure 3 , Figure 3 It is the flowchart of the third embodiment of the positioning method for the limited space operation personnel of the present application.

[0090] Based on the above embodiments, in the present embodiment, after the step S30, it further includes steps S311-S312:

[0091] Step S311: input the target positioning information into a convolutional neural network to obtain a residual compensation amount.

[0092] Step S312: residual compensation is performed on the target positioning information based on the residual compensation amount to obtain corrected target positioning information.

[0093] It should be understood that the convolutional neural network (CNN) is a deep learning model specially used to process data with grid structure, and is named after the convolution operation in the convolution layer. CNN can automatically extract features in data, reducing the workload of manual feature extraction.

[0094] In a specific implementation, the target positioning information can be input into a signal strength matrix in a convolutional neural network to obtain an input matrix; the input matrix can be convolved through four convolutional layers in the convolutional neural network to obtain convolutional features; the convolutional features can be flattened to obtain a one-dimensional feature vector, and the one-dimensional feature vector can pass through two fully connected layers and an output layer in the convolutional neural network to obtain a residual compensation amount.

[0095] It should be noted that the input layer in the convolutional neural network is an 8*8 UWB signal strength matrix, which then sequentially passes through four convolutional layers for convolution and two fully connected layers. The convolutional layers extract features in the input matrix through convolution kernels, and each convolutional layer can extract different levels of features. The convolutional features are flattened to obtain a one-dimensional feature vector. The flattening operation converts a multi-dimensional feature map into a one-dimensional vector to facilitate input into the fully connected layer. The one-dimensional feature vector passes through two fully connected layers and an output layer to obtain a residual compensation amount.

[0096] It can be understood that, in the positioning process, the target positioning information can be affected by various factors and thus have errors. The convolutional neural network can be used to analyze the target positioning information to obtain a residual compensation amount. Based on the residual compensation amount, the target positioning information can be adjusted to more accurately determine the actual position of the target and obtain corrected target positioning information, thereby further improving the positioning accuracy of the personnel working in the limited space.

[0097] The embodiment discloses that the target positioning information is input into a signal strength matrix in a convolutional neural network to obtain an input matrix; the input matrix is convolved through four convolutional layers in the convolutional neural network to obtain convolutional features; the convolutional features are flattened to obtain a one-dimensional feature vector, and the one-dimensional feature vector passes through two fully connected layers and an output layer in the convolutional neural network to obtain a residual compensation amount; and the target positioning information is compensated based on the residual compensation amount to obtain corrected target positioning information. Compared with the prior art, the embodiment further improves the positioning accuracy of the personnel working in the limited space by analyzing the target positioning information through the convolutional neural network to obtain a residual compensation amount, compensating the target positioning information based on the residual compensation amount, and obtaining corrected target positioning information.

[0098] In addition, the embodiment of the present application also provides a storage medium, wherein the storage medium stores a personnel working in a limited space positioning program, and the personnel working in a limited space positioning program is executed by a processor to realize the steps of the personnel working in a limited space positioning method as described above.

[0099] Reference Figure 4 , Figure 4 is a structure block diagram of the first embodiment of the personnel working in a limited space positioning device of the present application.

[0100] As Figure 4 shown, the limited space worker positioning device provided by the embodiment of the application comprises a digital model construction module 501, a positioning information generation module 502, a positioning information adjustment module 503 and a positioning information mapping module 504.

[0101] The digital model construction module 501 is configured to collect point cloud data of a target limited space, and construct a three-dimensional digital model of the target limited space based on the point cloud data.

[0102] The positioning information generation module 502 is configured to generate initial positioning information of a worker based on communication data of a UWB base station network and a positioning tag, wherein the UWB base station network comprises a plurality of UWB base stations, the UWB base stations are installed in the target limited space, and the positioning tag is worn on the worker.

[0103] The positioning information adjustment module 503 is configured to adjust the initial positioning information according to signal arrival time and signal strength of each UWB base station in the target limited space, and obtain target positioning information.

[0104] The positioning information mapping module 504 is configured to map the target positioning information to the three-dimensional digital model, and display the position and motion trajectory of the worker in real time.

[0105] The positioning information generation module 502 is further configured to record a positioning signal of the positioning tag when the positioning signal is received by the UWB base station network; determine real-time distance between the positioning signal and the UWB base station according to a preset detection period when the positioning signal is within a detection range of the UWB base station network; map the positioning signal and the real-time distance to a local coordinate system corresponding to the UWB base station, and determine a local coordinate position of the positioning signal in the local coordinate system; sort the local coordinate position based on a time stamp sequence of the preset detection period, and generate initial positioning information of the worker.

[0106] The positioning information adjustment module 503 is further configured to determine a position representation of the worker by a multilateral positioning algorithm according to signal arrival time and signal strength of each UWB base station in the target limited space; compare the position representation with a deployment topology of each UWB base station in the UWB base station network, and generate a correction factor; correct the position representation by using the correction factor, and obtain a corrected position representation; adjust the initial positioning information based on the corrected position representation, and obtain target positioning information.

[0107] The positioning information mapping module 504 is further configured to integrate and link the real-time positioning data of the worker with the monitoring video, and determine whether the worker has an abnormal action state; if the worker has an abnormal action state, automatically dispatch a monitoring video lens based on the abnormal action state of the worker, lock a target object for shooting, and obtain a target monitoring picture; and upload the target monitoring picture and the positioning data of the target object to the background for early warning processing through data transmission.

[0108] The device embodiment discloses collecting point cloud data of a target limited space, and constructing a three-dimensional digital model of the target limited space based on the point cloud data; generating initial positioning information of a worker based on communication data of a UWB base station network and a positioning tag, the UWB base station network comprising a plurality of UWB base stations, the UWB base stations being installed in the target limited space, and the positioning tag being worn on the worker; adjusting the initial positioning information according to signal arrival time and signal strength of each UWB base station in the target limited space to obtain target positioning information; and mapping the target positioning information to the three-dimensional digital model to display the position and motion trajectory of the worker in real time. Compared with the prior art, the device embodiment effectively improves the positioning accuracy of the worker in the limited space, and realizes accurate matching and mapping of the positioning data and the space structure, thereby improving the safety of the limited space operation.

[0109] Based on the first embodiment of the limited space worker positioning device, the second embodiment of the limited space worker positioning device is proposed.

[0110] In the embodiment, the digital model construction module 501 is further configured to emit a detection light beam modulated by a miniaturized MEMS grating array in the target limited space, so that the detection light beam forms multiple reflections in the target limited space; collect a light signal sequence returned in the reflection process, and determine distance information corresponding to the light signal sequence according to the light signal sequence; perform folding operation on the distance information to obtain folding path data, and generate point cloud data of the target limited space based on the folding path data; and construct a three-dimensional digital model of the target limited space based on the point cloud data.

[0111] Other embodiments or specific implementation manners of the limited space worker positioning device can refer to the above-mentioned method embodiments, which will not be described here again.

[0112] The application provides a limited space worker positioning device, which comprises at least one processor and a memory connected with the at least one processor; the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the limited space worker positioning method in the first embodiment.

[0113] Reference will be made to the following drawings Figure 5 which shows a structural diagram of a limited space worker positioning device suitable for implementing the embodiments of the application. The limited space worker positioning device in the embodiments of the application can include, but is not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (for example, vehicle-mounted navigation terminals), and the like, and fixed terminals such as digital TVs, desktop computers, and the like. Figure 5 The limited space worker positioning device shown is only an example, and should not bring any limitation to the functions and use range of the embodiments of the application.

[0114] As Figure 5As shown, the limited space worker positioning device can include a processing device 1001 (e.g., a central processing unit, a graphics processing unit, etc.) that can perform various appropriate actions and processes according to programs stored in a read-only memory 1002 or loaded from a storage device 1003 into a random access memory 1004. Various programs and data required for the operation of the limited space worker positioning device are also stored in the random access memory 1004. The processing device 1001, the read-only memory 1002, and the random access memory 1004 are connected to each other through a bus 1005. An input / output interface 1006 is also connected to the bus. Generally, the following systems can be connected to the input / output interface 1006: input devices 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; the storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the limited space worker positioning device to communicate wirelessly or by wire with other devices to exchange data. Although the limited space worker positioning device with various systems is shown in the figure, it should be understood that all the shown systems are not required to be implemented or possessed. More or fewer systems can be alternatively implemented or possessed.

[0115] In particular, according to the embodiments disclosed in the present application, the processes described above with reference to the flowcharts can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product comprising a computer program carried on a computer readable medium, the computer program containing program codes for executing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network through the communication device, or installed from the storage device 1003, or installed from the read-only memory 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the methods of the embodiments disclosed in the present application are performed.

[0116] The limited space worker positioning device provided by the present application adopts the limited space worker positioning method in the above-mentioned embodiments, and can solve the technical problem of insufficient positioning accuracy of limited space workers in the prior art, which leads to reduced safety of limited space work. Compared with the prior art, the limited space worker positioning device provided by the present application has the same beneficial effects as the limited space worker positioning method provided by the above-mentioned embodiments, and other technical features in the limited space worker positioning device are the same as the features disclosed in the previous embodiment method, which will not be described here.

[0117] It should be understood that various parts of the present application can be realized in hardware, software, firmware, or a combination thereof. In the above description of embodiments, specific functional, structural, material or characteristic features are combined in a manner that is appropriate for the particular embodiment.

[0118] The above description is merely illustrative of the application and is not intended to limit the scope of the application. Any variations and modifications that are obvious to those skilled in the art are intended to be within the scope of the application. The scope of the application is defined by the claims.

[0119] It should be noted that the terms "comprising", "including", or any other variation thereof, are intended to cover a non-exclusive inclusion, such that processes, methods, articles, or systems that comprise a list of elements do not include only those elements but can also include other elements not expressly listed or inherent to such processes, methods, articles, or systems. Without further limitation, an element defined by the phrase "comprising a" does not exclude the presence of additional identical elements in the process, method, article, or system that includes the element.

[0120] The above-mentioned embodiment numbers of the application are only for description and do not represent the advantages or disadvantages of the embodiments.

[0121] From the above description of the embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be realized by means of software and necessary general hardware platforms, of course, they can also be realized by hardware, but in many cases the former is a better embodiment. Based on such understanding, the technical solutions of the present application or the parts that contribute to the prior art can be embodied in the form of software products, which are stored in a storage medium (such as a read-only memory / random access memory, a magnetic disk, an optical disk) and include a number of instructions to make a terminal device (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) execute the methods described in various embodiments of the present application.

[0122] The above is only the preferred embodiment of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation, or direct or indirect application in other related technical fields, is also included in the patent protection scope of the present application.

Claims

1. A method for locating personnel working in a confined space, characterized in that, The method includes: Collect point cloud data of a finite space of the target, and construct a three-dimensional digital model of the finite space of the target based on the point cloud data; Initial location information of the worker is generated based on communication data between the UWB base station network and the positioning tag. The UWB base station network includes multiple UWB base stations, which are installed in the target confined space. The positioning tag is worn by the worker. The initial positioning information is adjusted based on the signal arrival time and signal strength of each UWB base station within the target confined space to obtain the target positioning information; The target positioning information is mapped onto the three-dimensional digital model to display the position and movement trajectory of the operator in real time.

2. The method for locating personnel in confined spaces as described in claim 1, characterized in that, The step of acquiring point cloud data of a finite space of the target and constructing a three-dimensional digital model of the finite space of the target based on the point cloud data includes: A probe beam modulated by a miniaturized MEMS grating array is emitted within a limited space of the target, so that the probe beam undergoes multiple reflections within the limited space of the target. The optical signal sequence returned during the reflection process is collected, and the distance information corresponding to the optical signal sequence is determined based on the optical signal sequence; Perform a folding operation on the distance information to obtain folded path data, and generate point cloud data of the target finite space based on the folded path data; A three-dimensional digital model of the target finite space is constructed based on the point cloud data.

3. The method for locating personnel in confined spaces as described in claim 1, characterized in that, After the step of adjusting the initial positioning information based on the signal arrival time and signal strength of each UWB base station within the target confined space to obtain the target positioning information, the method further includes: The target localization information is input into a convolutional neural network to obtain the residual compensation amount; Based on the residual compensation amount, residual compensation is performed on the target positioning information to obtain the corrected target positioning information.

4. The method for locating personnel in confined spaces as described in claim 3, characterized in that, The step of inputting the target localization information into a convolutional neural network to obtain the residual compensation amount includes: The target localization information is input into the signal intensity matrix in the convolutional neural network to obtain the input matrix; The input matrix is ​​convolved by the four convolutional layers in the convolutional neural network to obtain convolutional features. The convolutional features are flattened to obtain a one-dimensional feature vector, and the one-dimensional feature vector is passed through two fully connected layers and an output layer in the convolutional neural network to obtain the residual compensation amount.

5. The method for locating personnel in confined spaces as described in claim 1, characterized in that, The step of generating initial location information for workers based on communication data between the UWB base station network and the location tag includes: When the UWB base station network receives the positioning signal from the positioning tag, the positioning signal is recorded; When the positioning signal is within the detection range of the UWB base station network, the real-time distance between the positioning signal and the UWB base station is determined according to a preset detection period; The positioning signal and the real-time distance are mapped to the local coordinate system corresponding to the UWB base station to determine the local coordinate position of the positioning signal in the local coordinate system. The local coordinate positions are sorted based on the timestamp sequence of the preset detection period to generate the initial positioning information of the operators.

6. The method for locating personnel in confined spaces as described in claim 1, characterized in that, The step of adjusting the initial positioning information based on the signal arrival time and signal strength of each UWB base station within the target confined space to obtain target positioning information includes: Based on the signal arrival time and signal strength of each of the UWB base stations within the target confined space, the location representation of the operator is determined by a multilateral positioning algorithm. The location representation is compared with the deployment topology of each UWB base station in the UWB base station network to generate a correction factor; The position representation is corrected using the correction factor to obtain the corrected position representation; The initial positioning information is adjusted based on the corrected position representation to obtain the target positioning information.

7. The method for locating personnel in confined spaces as described in any one of claims 1-6, characterized in that, After the step of mapping the target positioning information to the three-dimensional digital model and displaying the position and movement trajectory of the worker in real time, the method further includes: The real-time location data of the workers is integrated and linked with the monitoring video to determine whether the workers have any abnormal behavior. If the operator exhibits abnormal behavior, the monitoring video camera will be automatically scheduled based on the abnormal behavior of the operator, and the target object will be locked and filmed to obtain the target monitoring image. The target monitoring screen and the target object's location data are uploaded to the backend via data transmission for early warning processing.

8. A personnel positioning device for confined space operations, characterized in that, The device includes: A digital model building module is used to collect point cloud data of a target finite space and build a three-dimensional digital model of the target finite space based on the point cloud data. The positioning information generation module is used to generate the initial positioning information of the operator based on the communication data between the UWB base station network and the positioning tag. The UWB base station network includes multiple UWB base stations, which are installed in the target confined space, and the positioning tag is worn on the operator. The positioning information adjustment module is used to adjust the initial positioning information according to the signal arrival time and signal strength of each UWB base station within the target limited space to obtain target positioning information; The positioning information mapping module is used to map the target positioning information onto the three-dimensional digital model, and to display the position and movement trajectory of the operator in real time.

9. A personnel positioning device for confined space operations, characterized in that, The device includes: a memory, a processor, and a confined space worker positioning program stored in the memory and executable on the processor, the confined space worker positioning program being configured to implement the steps of the confined space worker positioning method as described in any one of claims 1 to 7.

10. A storage medium, characterized in that, The storage medium stores a confined space worker positioning program, which, when executed by a processor, implements the steps of the confined space worker positioning method as described in any one of claims 1 to 7.

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