Safety helmet vector coordinate positioning early warning method and system for live working

Abstract

The invention discloses a safety helmet vector coordinate positioning early warning method and system for hot-line work, and relates to the technical field of safety, and the method comprises the steps: selecting key parts and sensitive parts of a safety helmet, and laying monitoring points; selecting point locations with stable safety helmet address conditions to arrange reference point locations; field signal receiving base stations are arranged on the opposite sides of the monitoring point positions and the reference point positions; the signal receiving base station processes the collected signals and uploads the signals to the cloud; and the cloud carries out analysis through inversion calculation. By comparing the detected electric field intensity with the preset threshold value, the system can accurately judge whether danger exists or not and give an alarm when necessary, and by establishing the relation model of the electric field intensity and the distance, the system can make more accurate judgment based on actual data, so that the reliability of early warning is improved.

Description

Technical Field

[0001] The invention relates to the field of safety technology, in particular to a method and system for positioning and warning of vector coordinates of a safety helmet for live working. Background Art

[0002] Due to the ever-changing mechanical and geological conditions on the earth's surface, the safety of live working is often affected by various factors, such as earthquakes, rainfall, and geological structures. Especially during the construction and maintenance of high slopes, it is necessary to ensure the stability of the slopes to prevent slope disasters. Therefore, safety can be understood in real time through the vector coordinate positioning of the helmet.

[0003] Live working refers to work performed on equipment or lines without power outages, including the use of special methods for testing, maintenance, inspection and replacement of individual parts. Safety knowledge of live working is extremely important because it is directly related to the life safety of workers and the stable operation of the power system.

[0004] The current live working regulations require that workers must wear a safety helmet. The safety helmet in the prior art is just a simple and bulky protective structure with a certain insulating effect. It can prevent the worker's head from being injured by electric shock caused by falling live objects or wires. However, further research has found that the safety helmet in the prior art lacks real-time and dynamic monitoring means for workers, resulting in the inability to timely discover and prevent potential safety risks. The existing monitoring system has a single function and cannot comprehensively identify and analyze the worker's behavior and the surrounding environment. The worker's perception ability in a complex environment is limited, making it difficult to accurately judge the distance and position between himself and the source of danger. Summary of the invention

[0005] In view of the problems existing in the existing safety helmet vector coordinate positioning early warning method and system for live working, the present invention is proposed.

[0006] Therefore, the problem to be solved by the present invention is how to provide a method and system for early warning of safety helmet vector coordinate positioning during live working.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0008] In a first aspect, an embodiment of the present invention provides a method for positioning and warning of a safety helmet vector coordinates for live working, which includes selecting key parts and sensitive parts of the safety helmet to arrange monitoring points;

[0009] Select points with stable helmet location conditions to set up reference points;

[0010] An on-site signal receiving base station is deployed on the opposite side of the monitoring point and the reference point;

[0011] The signal receiving base station processes the collected signals and uploads them to the cloud;

[0012] The cloud performs analysis through inverse calculations.

[0013] As a preferred solution of the safety helmet vector coordinate positioning early warning method for live working of the present invention, wherein: the key parts and sensitive parts of the safety helmet are selected to arrange monitoring points by establishing a high-precision digital twin model, and the simulation test includes:

[0014] A SIM card slot is arranged on the surface of the annular electrical installation belt located on the front of the helmet body, an on / off key, a lighting key, a camera key and a data interface are arranged on the surface of the annular electrical installation belt located on one side of the helmet body, and an intercom key and an SOS alarm key are arranged on the surface of the annular electrical installation belt located on the other side of the helmet body;

[0015] A charging interface 90 is provided on the surface of the annular electrical installation belt located on the back of the helmet body, and a control main board is provided inside the annular electrical installation belt. The control main board is interfaced with the SIM card slot, the charging interface and the data interface respectively. The control main board is also integrated with the power button, the lighting button, the camera button, the intercom button and the SOS alarm button respectively.

[0016] As a preferred solution of the safety helmet vector coordinate positioning and early warning method for live working of the present invention, wherein: the selection of points with stable safety helmet address conditions to arrange reference points includes collecting real-time video data and position data of the wearer of the safety helmet;

[0017] The real-time video data and the position data are transmitted to the background server and the image processing module, and the real-time video data is subjected to image recognition processing in the background server;

[0018] A boundary detection module is used to generate an electronic fence according to the location data and detect whether the wearer has crossed the boundary of the electronic fence. An alarm module is used to send an alarm signal to the helmet when it is detected that the wearer has crossed the boundary of the electronic fence.

[0019] The control mainboard is used to collect real-time video data and position data of the helmet wearer, transmit the real-time video data and position data to the background server, perform image recognition processing on the real-time video data in the background server, generate an electronic fence according to the position data, detect whether the wearer crosses the boundary of the electronic fence, and send an alarm signal to the helmet when it is detected that the wearer crosses the boundary of the electronic fence.

[0020] As a preferred solution of the safety helmet vector coordinate positioning and early warning method for live working of the present invention, wherein: the selection of points with stable safety helmet address conditions to arrange reference points also includes selecting alternative reference points within different ranges by using the redundant design principle, the minimum number of reference points required for normal operation of the monitoring area is n, and the redundancy coefficient k is increased, then the total number of redundant reference points is: m = n*k;

[0021] When J(θ) is at its maximum range, the reference points are arranged in a cross-shaped coverage range. When m=8, it can be used to monitor the surrounding environment of the point in 360° without blind spots.

[0022] When J(&) is at the minimum range, a cross-shaped coverage range is used to arrange the reference points. When m=4, it can be used to specify the monitoring of the surrounding environment of the point.

[0023] As a preferred solution of the method for vector coordinate positioning and early warning of live working helmets described in the present invention, the on-site signal receiving base station arranged on the opposite side of the monitoring point and the reference point includes setting up a first-level small receiving station and a second-level small receiving station, the first-level small receiving station is responsible for receiving the points arranged in a cross-shaped coverage range, and the second-level small receiving station is responsible for receiving the points arranged in a cross-shaped coverage range.

[0024] As a preferred solution of the safety helmet vector coordinate positioning and early warning method for live working of the present invention, wherein: the signal receiving base station processes the collected signals and uploads them to the cloud, including filtering redundant components in advance by setting a filter to extract streamlined effective information;

[0025] The extracted and simplified effective information includes connecting the control mainboard to the RTK positioning base station or network CORS server through the 4G network, and connecting to the background visualization management and control platform through the wireless network in the substation. The control mainboard adopts a DSP digital signal processor, which is suitable for processing large-scale floating-point calculations and can efficiently run the carrier phase integer ambiguity fixing algorithm. The control mainboard expands the corresponding data communication interface, supports serial port, network port, 4G wireless and GPIO common interfaces, and connects to the Beidou / GPS satellite signal receiver module through the RS232 serial port to complete the acquisition of the mobile terminal's own Beidou / GPS position coordinate information.

[0026] In a second aspect, an embodiment of the present invention provides a safety helmet vector coordinate positioning warning system for live working, which includes: a selection module, which selects key parts and sensitive parts of the safety helmet to arrange monitoring points;

[0027] A positioning module, which selects points with stable helmet address conditions to lay out reference points;

[0028] A monitoring module, which has a field signal receiving base station arranged on the opposite side of the monitoring point and the reference point;

[0029] The upload module, whose signal receiving base station processes the collected signals and uploads them to the cloud;

[0030] The analysis module performs analysis through inversion calculations in the cloud.

[0031] In a third aspect, an embodiment of the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, wherein: when the processor executes the computer program, any step of the above-mentioned safety helmet vector coordinate positioning warning method for live working is implemented.

[0032] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, any step of the above-mentioned safety helmet vector coordinate positioning warning method for live working is implemented.

[0033] The beneficial effects of the present invention are as follows: through the dual detection of electronic fences and electric field strength, the present invention can promptly issue an alarm when the wearer enters a potential danger area, thereby improving the safety of the workplace, continuously monitoring environmental changes, and ensuring that the wearer is always in a monitored state. By comparing the detected electric field strength with a preset threshold, the system can accurately determine whether there is a danger and issue an alarm when necessary. By establishing a relationship model between electric field strength and distance, the system can make more accurate judgments based on actual data, thereby improving the reliability of early warning. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0035] Figure 1 A method and system flow chart of a safety helmet vector coordinate positioning and early warning method for live working is provided as an embodiment of the present invention.

[0036] Figure 2 An internal structural diagram of a computer device of a method and system for positioning and warning of safety helmet vector coordinates for live working provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0037] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0038] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0039] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0040] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0041] At the same time, in the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0042] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0043] Example 1

[0044] Reference Figure 1-2, which is the first embodiment of the present invention, and provides a safety helmet vector coordinate positioning and early warning method for live working, comprising:

[0045] S1: Select key and sensitive parts of the helmet to set up monitoring points.

[0046] The key and sensitive parts of the helmet are selected to set up monitoring points by establishing a high-precision digital twin model and conducting simulation tests including:

[0047] A SIM card slot is arranged on the surface of the annular electrical installation belt located on the front of the helmet body, an on / off key, a lighting key, a camera key and a data interface are arranged on the surface of the annular electrical installation belt located on one side of the helmet body, and an intercom key and an SOS alarm key are arranged on the surface of the annular electrical installation belt located on the other side of the helmet body;

[0048] A charging interface is provided on the surface of the annular electrical installation belt located on the back of the helmet body, and a control main board is provided inside the annular electrical installation belt. The control main board is interfaced with the SIM card slot, the charging interface and the data interface respectively. The control main board is also integrated with the power button, the lighting button, the photo button, the intercom button and the SOS alarm button respectively.

[0049] Furthermore, the NAS neural network search algorithm is used to find the optimal coverage range in the defined search space. The search space directly determines the upper limit and form of the representation capability of the final model. In order to enable the variable-length network architecture to be operated by the parameterized controller, a fixed encoding length is required. The controller is responsible for generating the network architecture, and its parameters need to be continuously learned and optimized to generate the optimal control range.

[0050] Furthermore, the controller is used to optimize and determine the best range. The main boundary conditions considered are terrain boundary, geological boundary and flow boundary. Two different ranges are planned through NAS neural network. One is the large-scale data J(θ), considering that the terrain boundary DEM resolution is 0.1m, the elevation change is 300m, the geological boundary has 10 layers, the shear strength is 1000kpa-10000kpa, the internal friction angle is 25°-40°, the groundwater flow rate of the flow boundary is 0m3 / h-100m3 / h, and the flow direction is mostly complex. , reflecting that the actual situation has a strong degree of complexity. In a large range, α1 is the terrain boundary, α2 is the geological boundary, and α3 is the flow boundary. The other is a small-scale data J(&), which also takes into account the terrain boundary DEM resolution of 1m, the elevation change of 20m, the 3-layer geological boundary, the shear strength of 1000kpa-5000kpa, the internal friction angle of 25°-35°, the groundwater flow rate of the flow boundary of 0m3 / h-10m3 / h, and the flow direction is mostly single distribution, reflecting that the actual situation has a weak degree of complexity.

[0051] Specifically, the terrain boundary DEM is analyzed through the two-dimensional elevation matrix DEM = [[h11,h12,...,h1n], [h21,h22,...,h2n],...[hm1,hm2,...,hmn]], where m,n: represent the number of rows and columns of DEM, that is, the resolution of DEM; hij: represents the elevation value of the pixel in the i-th row and j-th column. For example, for a DEM with 10 rows and 10 columns, it can be expressed as: DEM = [[234,225,223,...,228], [332,331,336, ...,330],...[456,459,452,...,455]], the acquired DEM data can be transformed into coordinates to determine the actual position coordinates (x, y) of each pixel, and correspond to its elevation value h, thereby expressing the two-dimensional terrain information; by drilling and sampling the slope geology and conducting indoor tests, the physical and mechanical parameters of each stratum, such as shear strength and internal friction angle, are obtained to provide a data basis for setting geological boundary conditions; through hydrogeological surveys of the slope area, data such as groundwater flow direction and groundwater level are obtained for setting flow boundary conditions.

[0052] S2: Select points where the helmet address conditions are stable to set up the reference points.

[0053] Among them, selecting points with stable helmet address conditions to set reference points includes collecting real-time video data and location data of the helmet wearer;

[0054] The real-time video data and location data are transmitted to the background server and the image processing module, and the real-time video data is processed by image recognition in the background server;

[0055] A boundary detection module is used to generate an electronic fence according to the location data and detect whether the wearer has crossed the boundary of the electronic fence. An alarm module is used to send an alarm signal to the helmet when it is detected that the wearer has crossed the boundary of the electronic fence.

[0056] The control main board is used to collect real-time video data and position data of the helmet wearer, transmit the real-time video data and position data to the background server, perform image recognition processing on the real-time video data in the background server, generate an electronic fence according to the position data, detect whether the wearer crosses the boundary of the electronic fence, and send an alarm signal to the helmet when it is detected that the wearer crosses the boundary of the electronic fence.

[0057] Furthermore, when J(θ) is in the maximum range, it is necessary to use the Richards equation for seepage calculation, considering the comprehensive reflection of the stress state of the slope by mechanics, and the two are alternately iterated. The seepage results affect the effective stress, and the stress results affect the seepage, and the cycle tends to be stable, so as to achieve the seepage-mechanical coupling monitoring to determine the monitoring point; when J(&) is in the minimum range, the geological parameters such as cohesion and friction of each monitoring point in the slope area are collected, and the slope topography is measured by lidar technology to determine the slope length and sliding surface inclination. The soil layer samples are obtained by drilling, and pressure sensors are arranged at the slope monitoring points to monitor the water pressure intensity of each unit. The above monitoring and actual measurement are brought into the janbu method formula to perform the time domain evolution trend of the slope stability, and the monitoring values ​​at different times are displayed as shown in Table 1 below:

[0058] Table 1 Data table of monitoring values ​​at different times

[0059] Monitoring Points Time1 Time1-5 Time1-10 Time1-15 Time1-20 A1 1.25 1.22 1.20 1.15 1.10 B2 1.35 1.32 1.28 1.21 1.16 C3 1.30 1.25 1.22 1.12 1.05 D4 1.28 1.24 1.20 1.10 1.00 E5 1.32 1.30 1.25 1.18 1.10

[0060] This table monitors the 5 slope monitoring points, and shows the changes in Fs values ​​every 5 days from January 1 to January 20. The Fs value of monitoring point A1 was 1.25 on January 1, and then it showed a slow downward trend and dropped to 1.10 on January 20. The Fs value change trend of monitoring point B2 was similar to that of A1, dropping from 1.35 on January 1 to 1.16 on January 20. The Fs value of monitoring point C3 changed more dramatically, from 1.30 on January 1 to 1.05 on January 20. The monitoring point D4, which had the largest drop, also showed a clear downward trend. The Fs value dropped from 1.28 on January 1 to 1.00 on January 20, close to the critical value of slope instability. The Fs value of point E5 was slightly better than that of A1 and B2, but it also dropped from 1.32 on January 1 to 1.10 on January 20. In general, this table monitored the time changes of Fs values ​​of 5 slope monitoring points within 20 days. The Fs values ​​of each point showed a downward trend, especially C3 and D4, with a large drop, and the slope stability was gradually weakening.

[0061] S3: Deploy a field signal receiving base station on the opposite side of the monitoring point and the reference point.

[0062] Among them, selecting points with stable helmet address conditions to set up reference points also includes selecting alternative reference points within different ranges using the redundant design principle. The minimum number of reference points required for normal operation of the monitoring area is n. Adding the redundancy coefficient k, the total number of redundant reference points is: m = n*k;

[0063] When J(θ) is at its maximum range, the reference points are arranged in a cross-shaped coverage range. When m=8, it can be used to monitor the surrounding environment of the point in 360° without blind spots.

[0064] When J(&) is at the minimum range, a cross-shaped coverage range is used to arrange the reference points. When m=4, it can be used to specify the monitoring of the surrounding environment of the point.

[0065] Furthermore, a hierarchical data convergence network is set up, and a first-level small receiving station and a second-level small receiving station are set up between the monitoring points, and then converged to the total receiving base station to expand the network coverage. The first-level small receiving station is responsible for collecting data from surrounding monitoring points. The first-level receiving station adopts a low-cost miniaturized design, mainly including a simple antenna, a microprocessor and a storage module. The hardware design of the second-level small receiving station is similar to that of the first-level station, but uses a higher-gain antenna, which has a longer transmission distance. The first-level small receiving station transmits to the adjacent second-level small receiving station in a point-to-point manner, and the second-level small receiving station then aggregates and transmits to the total base station at high power. Through the two-level network architecture, the network redundancy and expansion margin can be greatly increased.

[0066] S4: The signal receiving base station processes the collected signals and uploads them to the cloud.

[0067] Among them, the signal receiving base station processes the collected signals and uploads them to the cloud, including filtering out redundant components in advance by setting filters to extract streamlined effective information;

[0068] Extracting concise and effective information includes connecting the control mainboard to the RTK positioning base station or network CORS server through the 4G network, and connecting to the background visualization management and control platform through the wireless network in the substation. The control mainboard adopts a DSP digital signal processor, which is suitable for processing large-scale floating-point calculations and can efficiently run the carrier phase integer ambiguity fixing algorithm. The control mainboard has expanded the corresponding data communication interface, supports serial port, network port, 4G wireless and GPIO common interfaces, and connects to the Beidou / GPS satellite signal receiver module through the RS232 serial port to complete the acquisition of the Beidou / GPS position coordinate information of the mobile terminal itself.

[0069] S5: Analysis is performed in the cloud through inversion calculation.

[0070] The analysis through inversion calculation in the cloud includes establishing a mathematical model in the cloud and using the least squares method for calculation. The specific steps are as follows:

[0071] The mathematical model established in the cloud is:

[0072] y=Ax+n

[0073] Among them, x is the n-dimensional unknown parameter vector, A-dimensional m*n observation matrix;

[0074] The least squares calculation formula is:

[0075] x(k)+((A T *A)-1)*AT *(y - Ax(k))

[0076] Where x(k) is the unknown parameter quantity at the k-th iteration, A T is the transpose of the observation matrix, A is the observation matrix, and Ax(k) is the observed value calculated by the current parameter vector;

[0077] When y < ymin, the parameter is too low, and the system status gives an abnormal alarm;

[0078] When y > ymax, the parameter is too high, and the system status gives an abnormal alarm;

[0079] When ymin ≤ y ≤ ymax, the parameter is normal, and the system status is normal without alarm.

[0080] Furthermore, the monitored slope area mainly includes surface moisture content, groundwater level, horizontal displacement, vertical displacement, and stress. The normal range of surface moisture content is 15% - 30%. Considering increasing the safety margin, the set threshold range is 12% - 35%. The normal range of groundwater level is 8m - 15m. Considering increasing the safety margin, the set threshold is 6m - 18m. The normal range of horizontal displacement is -10mm - 10mm. Considering increasing the safety margin, the set threshold is -15mm - +15mm. The normal range of vertical displacement is -5mm to +5mm. Considering increasing the safety margin, the set threshold is -8mm to +8mm. The normal range of stress is 50kpa - 80kpa. Considering increasing the safety margin, the set threshold is 40kPa - 90kPa.

[0081] In one embodiment, a vector coordinate positioning and warning system for a safety helmet in live working is characterized in that it includes a selection module that selects key parts and sensitive parts of the safety helmet to arrange monitoring points; a positioning module that selects points with stable address conditions of the safety helmet to arrange reference points; a monitoring module that arranges on-site signal receiving base stations on the opposite sides of the monitoring points and the reference points; an upload module that processes the signals collected by the signal receiving base stations and uploads them to the cloud; and an analysis module that analyzes through inversion calculation in the cloud.

[0082] The above-mentioned unit modules can be embedded in the processor of the computer device in hardware form or be independent of it, or can be stored in the memory of the computer device in software form, so as to facilitate the processor to call and execute the operations corresponding to each of the above modules.

[0083] In one embodiment, a computer device is provided. The computer device can be a terminal, and its internal structure diagram can be as Figure 2As shown. The computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0084] In summary, the present invention can promptly issue an alarm when the wearer enters a potentially dangerous area through dual detection of electronic fences and electric field strength, thereby improving workplace safety, continuously monitoring environmental changes, and ensuring that the wearer is always in a monitored state. By comparing the detected electric field strength with a preset threshold, the system can accurately determine whether there is a danger and issue an alarm when necessary. By establishing a relationship model between electric field strength and distance, the system can make more accurate judgments based on actual data, thereby improving the reliability of early warnings.

[0085] Example 2

[0086] Reference Figure 1-2 , which is the second embodiment of the present invention, and this embodiment provides a method for positioning and warning of vector coordinates of safety helmets for live working. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through simulation experiments.

[0087] For surface moisture content, when y is less than 12%, the parameter is too low, the system state is abnormal and an alarm is triggered; when y is greater than 35%, the parameter is too high, the system state is abnormal and an alarm is triggered; when 12%≤y≤35%, it is considered normal and no alarm is triggered; for groundwater level, when y is less than 6m, the parameter is too low, the system state is abnormal and an alarm is triggered; when y is greater than 18m, the parameter is too high, the system state is abnormal and an alarm is triggered; when 6m≤y≤18m, it is considered normal and no alarm is triggered; for horizontal displacement, when y is less than -15mm, the parameter is too low, the system state is abnormal and an alarm is triggered; when y is greater than 15mm, the parameter is too high, the system state is abnormal and an alarm is triggered; when -15mm≤y≤15mm, it is considered normal and no alarm is triggered; for stress, when y is less than 40kPa, the parameter is too low, the system state is abnormal and an alarm is triggered; when y is greater than 90kPa, the parameter is too high, the system state is abnormal and an alarm is triggered; when 40kPa≤y≤90kPa, it is considered normal and no alarm is triggered.

[0088] The table contains four key slope monitoring parameters: surface moisture content, groundwater level, horizontal displacement and stress. The normal range of each parameter, the additional safety margin considered, and the threshold range set after combining the two are given in order. For example, the normal range of surface moisture content is 15%-30%, and a safety margin of ±5% is added. The final threshold range is set to 12%-35%. The normal range of groundwater level is 8m-15m, plus a safety margin of ±3m, and its threshold range is 6m-18m. The threshold ranges of horizontal displacement and stress are also obtained in the same way. The threshold ranges of the four important slope monitoring parameters are set, which provides a basic basis for evaluating the state of the slope. When the monitoring value exceeds the threshold range, it means that the slope state is abnormal and corresponding emergency measures need to be taken. The specific display is shown in Table 2 below:

[0089] Table 2 Data table of value ranges of various parameters

[0090] Monitoring parameters Normal range Margin of safety Threshold Range Surface moisture content 15％-30％ ±5％ 12％-35％ Groundwater level 8m-15m ±3m 6m-18m Horizontal displacement -10mm-+10mm ±5mm -15mm-+15mm stress 50kPa-80kPa ±10kPa 40kPa-90kPa

[0091] 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 preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A safety helmet vector coordinate positioning and early warning method for live working, characterized by: include, Select key and sensitive parts of the helmet to set up monitoring points; Select points with stable helmet location conditions to set up reference points; An on-site signal receiving base station is deployed on the opposite side of the monitoring point and the reference point; The signal receiving base station processes the collected signals and uploads them to the cloud; The cloud performs analysis through inverse calculations.

2. The method for positioning and warning of safety helmet vector coordinates for live working according to claim 1, characterized in that: The key and sensitive parts of the helmet are selected to set up monitoring points by establishing a high-precision digital twin model and conducting simulation tests, including: A SIM card slot is arranged on the surface of the annular electrical installation belt located on the front of the helmet body, an on / off key, a lighting key, a camera key and a data interface are arranged on the surface of the annular electrical installation belt located on one side of the helmet body, and an intercom key and an SOS alarm key are arranged on the surface of the annular electrical installation belt located on the other side of the helmet body; A charging interface is provided on the surface of the annular electrical installation belt located on the back of the helmet body, and a control main board is provided inside the annular electrical installation belt. The control main board is interfaced with the SIM card slot, the charging interface and the data interface respectively. The control main board is also integrated with the power button, the lighting button, the photo button, the intercom button and the SOS alarm button respectively.

3. The method for positioning and warning of safety helmet vector coordinates for live working according to claim 2, characterized in that: The selecting of points with stable helmet address conditions to arrange reference points includes collecting real-time video data and position data of the helmet wearer; The real-time video data and the position data are transmitted to the background server and the image processing module, and the real-time video data is subjected to image recognition processing in the background server; A boundary detection module is used to generate an electronic fence according to the location data and detect whether the wearer has crossed the boundary of the electronic fence. An alarm module is used to send an alarm signal to the helmet when it is detected that the wearer has crossed the boundary of the electronic fence. The control mainboard is used to collect real-time video data and position data of the helmet wearer, transmit the real-time video data and position data to the background server, perform image recognition processing on the real-time video data in the background server, generate an electronic fence according to the position data, detect whether the wearer crosses the boundary of the electronic fence, and send an alarm signal to the helmet when it is detected that the wearer crosses the boundary of the electronic fence.

4. The method for positioning and warning of safety helmet vector coordinates for live working according to claim 3, characterized in that: The method of selecting points with stable helmet address conditions to arrange reference points also includes selecting alternative reference points within different ranges using the principle of redundant design. The minimum number of reference points required for normal operation of the monitoring area is n. The redundancy coefficient k is added, and the total number of redundant reference points is: m=n*k; When J(θ) is at its maximum range, the reference points are arranged in a cross-shaped coverage range. When m=8, it can be used to monitor the surrounding environment of the point in 360° without blind spots. When J(&) is at the minimum range, a cross-shaped coverage range is used to arrange the reference points. When m=4, it can be used to specify the monitoring of the surrounding environment of the point.

5. The method for positioning and warning of safety helmet vector coordinates for live working according to claim 4, characterized in that: The field signal receiving base station arranged on the opposite side of the monitoring point and the reference point includes setting up a first-level small receiving station and a second-level small receiving station. The first-level small receiving station is responsible for receiving points arranged in a cross-shaped coverage range, and the second-level small receiving station is responsible for receiving points arranged in a cross-shaped coverage range.

6. The method for positioning and warning of safety helmet vector coordinates for live working according to claim 5, characterized in that: The signal receiving base station processes the collected signals and uploads them to the cloud, including filtering redundant components in advance through a set filter to extract concise and effective information; The extraction of concise and effective information includes that the control main board is connected to the RTK positioning base station or the network CORS server through the 4G network, and is connected to the background visualization control platform through the wireless network in the substation. The control main board uses a DSP digital signal processor, which is suitable for processing large-scale floating-point calculations and can efficiently run the carrier phase integer ambiguity fixing algorithm. The control main board expands the corresponding data communication interfaces, supporting common interfaces such as serial ports, network ports, 4G wireless, and GPIO. It is connected to the Beidou / GPS satellite signal receiver module through the RS232 serial port to obtain the Beidou / GPS position coordinate information of the mobile terminal itself.

7. The method for positioning and warning of safety helmet vector coordinates for live working according to claim 6, characterized in that: The analysis by the cloud through inversion calculation includes establishing a mathematical model in the cloud and using the least squares method for calculation. The specific steps are as follows: The mathematical model established in the cloud is: y = Ax + n where x is an n-dimensional unknown parameter vector, and A is an m*n observation matrix; The least squares calculation formula: x(k)+((A T *A)-1)*A T *(y-Ax(k)) Among them, x(k) is the unknown parameter at the kth iteration, A T is the transpose of the observation matrix, A is the observation matrix, and Ax(k) is the observation value calculated by the current parameter vector; When y < ymin, the parameter is too low, and the system status issues an abnormal alarm; When y > ymax, the parameter is too high, and the system status issues an abnormal alarm; When ymin ≤ y ≤ ymax, the parameter is normal, and the system status is normal without an alarm.

8. A safety helmet vector coordinate positioning and early warning system for live working, based on the safety helmet vector coordinate positioning and early warning method for live working according to any one of claims 1 to 7, characterized in that: Including, a selection module that selects key and sensitive parts of the safety helmet to arrange monitoring points; a positioning module that selects points with stable address conditions of the safety helmet to arrange reference points; a monitoring module that arranges on-site signal receiving base stations on the opposite sides of the monitoring points and the reference points; an upload module that the signal receiving base station processes the collected signals and uploads them to the cloud; an analysis module that the cloud conducts analysis through inversion calculation.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, it implements the steps of the method for vector coordinate positioning and warning of the safety helmet for live working according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the method for vector coordinate positioning and warning of the safety helmet for live working according to any one of claims 1 to 7.

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