Intelligent insulating ladder

Abstract

The invention discloses an intelligent insulating ladder, and relates to the technical field of electric power operation equipment, the intelligent insulating ladder comprises vertical bars, and a plurality of transverse bars arranged at equal intervals are arranged between the two vertical bars; the rear side sensor is arranged on the side, away from the operator, of the vertical bar and used for detecting the vertical hand grabbing condition of the operator; the end face sensor is arranged at the top end of the cross bar and used for detecting the treading condition of an operator; the transverse side sensor is arranged on the side, away from the operator, of the transverse lever and used for detecting the transverse hand grabbing condition of the operator; the controller is arranged on the inner side of the top end of the vertical bar and electrically connected with the rear side sensor, the end face sensor and the transverse side sensor. According to the invention, a set of intelligent guarantee system covering the whole process of operation is constructed and is used for recording and reminding operators, so that nonstandard climbing operation of the operators is prevented, and improvement of construction safety is facilitated.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of electric power operation equipment, in particular to an intelligent insulating ladder. BACKGROUND

[0002] With the rapid development and intelligent upgrading of the electric power industry, the personal safety of electric power operation personnel is raised to a new level. Among them, the insulating ladder as the key equipment to protect the life safety of electric power overhead operation personnel, its use safety is directly related to personal safety. In recent years, with the rapid development of sensor technology, by integrating sensing devices on the insulating ladder, the use state of the ladder can be sensed in real time and information can be stored, and then the non-standard climbing behavior of the operation personnel can be monitored and traced.

[0003] However, the existing conventional insulating ladder has obvious shortcomings in actual application, including the following aspects: 1. State supervision blind area: there is a lack of real-time monitoring of high-risk behaviors during the use of the insulating ladder, and the safety protection mainly depends on the subjective will of the workers to follow the electric power safety operation specification, and it is difficult to supervise in real time when climbing and difficult to trace after operation.

[0004] 2. Use process risk: the stability of the ladder and the operation environment may change, which can easily cause accidents such as falling, overturning, and top support instability.

[0005] 3. Over-reliance on human: experience bias and risk passivation: the use safety is closely related to the experience level, immediate state, environmental perception ability and strict compliance with procedures of the operator, but even experienced employees cannot avoid negligence or misjudgment of the risks brought by the environment.

[0006] 4. Process execution difficult to supervise: the existing monitoring means is difficult to supervise and trace all risk behaviors in real time in a dynamic and complex real operation environment.

[0007] In view of the problems in the related art, no effective solution has been proposed so far. SUMMARY

[0008] Therefore, it is necessary to provide an intelligent insulating ladder aiming at the above technical problems.

[0009] The present application provides an intelligent insulating ladder, comprising: vertical poles, a plurality of equidistantly arranged horizontal poles are arranged between the two vertical poles; A rear sensor is arranged on the side of the vertical pole away from the operator, for detecting the vertical hand grip of the operator; An end face sensor is arranged at the top end of the horizontal pole, for detecting the stepping of the operator; A horizontal edge sensor is arranged on the side of the horizontal pole away from the operator, for detecting the horizontal hand grip of the operator; One-way support base, arranged at the bottom of the vertical rod, for preventing the vertical rod from rotating and sliding in reverse direction; Controller, arranged inside the top end of the vertical rod, electrically connected with the rear sensor, the end surface sensor and the horizontal edge sensor, for providing power supply and intelligent decision control; The controller comprises: The main processing module is configured to collect and process the original signals from the rear sensor, the end surface sensor and the horizontal edge sensor in real time, and detect the climbing detection data of the operator in real time based on the three-point contact principle, and trigger a pre-warning when a violation is detected.

[0010] Further, one side of the top of the vertical rod is provided with an alarm device, and the top of the horizontal rod is provided with anti-skid stripes; The horizontal rod is arranged at the top end of the horizontal rod and the bottom end of the horizontal rod, and the reinforcing rib is fixedly connected with the vertical rod; The horizontal rod vertically divides the vertical rod into different edge detection areas.

[0011] Further, the one-way support base comprises a sleeve arranged at the bottom of the vertical rod, and the sleeve is arranged inside the one-side fixing seat and is movably connected with the one-side fixing seat; The one-side fixing seat is provided with a support base plate at the bottom end, and the support base plate is provided with an anti-skid support pad at the bottom end.

[0012] Further, the controller further comprises: The power management module is configured to provide direct current power supply, and integrate charge and discharge control, power monitoring, low voltage, overload protection and low power alarm function, to prevent data loss and circuit impact; The data storage module is configured to record the time stamp of each climb, the sensor number triggering the pre-warning and the environmental data, to realize the whole life cycle management and intelligent inspection; The human-computer interaction module is configured to display the current climbing state in real time, and provide interactive control function, and drive the alarm device to perform sound and light alarm when receiving the control instruction triggered by the violation; The communication interface module is configured to provide wired communication interface and wireless communication interface, and establish communication connection with the rear sensor, the end surface sensor, the horizontal edge sensor and the intelligent mobile terminal, to realize real-time transmission and sharing of the climbing detection data; The electromagnetic shielding module is configured to provide electromagnetic shielding function to resist electromagnetic interference in the environment; The power management module is connected with the main processing module, the data storage module, the human-computer interaction module, the communication interface module and the electromagnetic shielding module.

[0013] Further, the main processing module comprises: The signal acquisition and fusion module is configured to acquire original signals of the rear sensor, the end surface sensor and the lateral edge sensor synchronously, and generate touch point distribution data through dynamic filtering, contact validity verification and spatial topology correlation. The state modeling and prediction module is configured to construct a ladder body dynamic behavior model based on physical rules and behavior constraints, solve touch point pressure distribution, barycentric offset and overturning risk coefficient of the touch point distribution data in real time, and output a climbing stage mark and an overturning risk coefficient. The compliance determination and decision module is configured to match the touch point distribution data, the climbing stage mark and the overturning risk coefficient in real time based on a pre-set rule violation rule library, and generate a rule violation type and a risk level label. The early warning generation and distribution module is configured to generate a differentiated early warning instruction based on the rule violation type and the risk level label, and distribute the early warning instruction to the human-machine interaction module, and output a decision log to the data storage module for solidification. The coordination and self-check optimization module is configured to monitor running states of the modules, coordinate task scheduling periods, and perform software and hardware self-checks to maintain real-time performance and safety of a processing link. The signal acquisition and fusion module, the state modeling and prediction module, the compliance determination and decision module, the early warning generation and distribution module and the coordination and self-check optimization module are sequentially connected.

[0014] Further, the generation of the touch point distribution data through dynamic filtering, contact validity verification and spatial topology correlation includes: The node clocks of the rear sensor, the end surface sensor and the lateral edge sensor are synchronized by using a precise time protocol, transmission delay compensation processing is performed on the original signals, and the time axis is aligned for low-frequency signals by using a linear interpolation method based on a highest sampling rate. The electromagnetic intensity and vibration frequency in the original signals after the real-time monitoring compensation and the time axis alignment are monitored, a multi-stage filter pipeline is used to perform gain compensation on effective frequency bands, and an enhanced signal is formed. Based on physical constraints and spatiotemporal continuity constraints, invalid touch points with pressure values less than a pre-set threshold value in the enhanced signal are removed to retain valid touch points, and a sliding window method is used to calculate touch point residence time. The valid touch points of the rear sensor, the end surface sensor and the lateral edge sensor are mapped to a three-dimensional coordinate system of the ladder body, a spatial distribution topology graph of hand and foot touch points is constructed, a plurality of touch edge detection regions are formed by dividing the ladder body into intervals with the crossbar as the interval, structured touch point distribution data is output, and a touch point data set is formed.

[0015] Further, the construction of the ladder body dynamic behavior model based on physical rules and behavior constraints, the real-time solving of touch point pressure distribution, barycentric offset and overturning risk coefficient of the touch point distribution data, and the output of a climbing stage mark and an overturning risk coefficient include: Based on the contact distribution data of the current time period in the contact data set, the stage state of the climbing is divided in real time, and the rationality of stage switching is verified combined with the historical contact sequence to filter abnormal jumps in the climbing process; wherein, the stage state includes climbing state, working state and transition state; Based on the contact pressure gradient, the inclination angle of the ladder body and the environmental disturbance parameters, a dynamic behavior model of the ladder body is constructed by fusing the trajectory of the center of gravity offset, and the real-time overturning risk coefficient in the climbing process is solved. Based on the stage state of the current climbing and the solving result of the overturning risk coefficient, a prediction instruction of the climbing stage marker and the overturning risk coefficient is packaged and output to the compliance decision judgment module.

[0016] Further, based on the contact distribution data of the current time period in the contact data set, the stage state of the climbing is divided in real time, and the rationality of stage switching is verified combined with the historical contact sequence to filter abnormal jumps in the climbing process, including: Based on the spatio-temporal distribution characteristics of the contact data set, the hands and feet contacts are dynamically clustered and grouped, the contact combination mode is identified, and a finite state machine model is constructed according to the contact combination mode and the physical rules, and the transition conditions and boundary constraints of the climbing state, the working state and the transition state are set; The migration rule of the historical stage state is counted, the state transition matrix is generated, and the confidence of the current state transition is calculated. If the confidence is less than the preset threshold, it is marked as abnormal jump. For the migration of abnormal jump, the transition state label is forced to be inserted and the contact sampling window is extended until the time sequence is restored to be reasonable.

[0017] Further, based on the contact pressure gradient, the inclination angle of the ladder body and the environmental disturbance parameters, a dynamic behavior model of the ladder body is constructed by fusing the trajectory of the center of gravity offset, and the real-time overturning risk coefficient in the climbing process is solved, including: The pre-acquired inclination angle of the ladder body and the environmental disturbance parameters are time-stamped and unit-normalized with the contact distribution data respectively to generate a spatio-temporally consistent multi-dimensional input data set; Based on the physical correlation of wind speed, vibration and inclination angle of the ladder body, the disturbance of environmental disturbance and inclination angle reading is dynamically decoupled, the net inclination angle change is extracted, and the net inclination angle data is output; Based on the contact distribution data and the net inclination angle data, taking the one-way support base as the fulcrum, the dynamic behavior model of the ladder body based on the lever principle is constructed by fusing the action point coordinates of the contact pressure, the real-time center of gravity coordinates and offset tolerance are calculated, and the overturning risk coefficient is output.

[0018] Further, based on the pre-set violation rule library, the contact distribution data, the climbing stage marker and the overturning risk coefficient are matched in real time to generate violation type and risk level labels, including: Based on the current climbing stage mark dynamic loading corresponding violation judgment rule subset, the contact point distribution data is spatio-temporally aligned with the climbing stage mark and the overturning risk coefficient, input in the violation judgment rule subset for logical matching, and the violation type is generated; Based on the preset violation severity and environmental disturbance intensity, the risk of the violation type is quantified, the risk level label is output, and the violation type and the risk level label are packaged, and the value warning generation distribution module is output.

[0019] The beneficial effects of the present application are: 1. By relying on the excellent insulation performance of glass steel, and combining with the foolproof setting, anti-skid reinforcement, three-point sensing and other safety technologies, an intelligent protection system covering the whole operation is constructed, including ground stable support, step-by-step safe climbing and top reliable anchoring; for recording and reminding the operator, preventing the operator from climbing operation, which helps to improve the construction safety.

[0020] 2. By integrating sensing technology, the contact condition of the worker during climbing is dynamically monitored, when it is detected that the ladder user does not meet three effective contact points during climbing, an immediate and clear danger prompt is sent to the worker through sound and light alarm, and the record is stored, reminding the worker to prevent non-standard climbing behavior. DETAILED DESCRIPTION

[0021] The drawings described herein are used to provide further understanding of the present application, and form a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application, and do not constitute an improper limitation on the present application. In the drawings: Figure 1 is a structural schematic diagram of an intelligent insulating ladder according to an embodiment of the present application; Figure 2 is Figure 1 is a local enlarged view of position A in FIG. 1; Figure 3 is Figure 1 is a local enlarged view of position B in FIG. 1; Figure 4 is a structural schematic diagram of a ladder body of an intelligent insulating ladder according to an embodiment of the present application; Figure 5 is a local structural schematic diagram of an intelligent insulating ladder according to an embodiment of the present application; Figure 6 is a system principle block diagram of a controller in an intelligent insulating ladder according to an embodiment of the present application; Figure 7 is a schematic diagram of a touch edge detection area according to an embodiment of the present application.

[0022] The drawing reference numerals are: 1, vertical pole; 2, horizontal pole; 3, rear sensor; 4, end face sensor; 5, horizontal edge sensor; 6, controller; 7, alarm device; 8, anti-skid stripe; 9, reinforcing rib; 10, one-way support base; 1001, sleeve; 1002, one-side fixing seat; 1003, support base plate; 1004, anti-skid support pad. DETAILED DESCRIPTION

[0023] In order to make the purpose, technical scheme and advantages of the present application more clear, the present application is further described in detail below in combination with the drawings and examples. It should be understood that the specific examples described herein are only used to explain the present application and do not limit the present application.

[0024] Please refer to Figure 1-Figure 5 , an intelligent insulating ladder is provided, comprising: vertical poles 1, a plurality of equidistantly arranged horizontal poles 2 are arranged between the two vertical poles 1.

[0025] The rear sensor 3 is arranged on the side of the vertical pole 1 away from the operator, and is used to detect the vertical hand gripping condition of the operator.

[0026] The end face sensor 4 is arranged at the top end of the horizontal pole 2, and is used to detect the stepping condition of the operator.

[0027] The horizontal edge sensor 5 is arranged on the side of the horizontal pole 2 away from the operator, and is used to detect the horizontal hand gripping condition of the operator.

[0028] The controller 6 is arranged inside the top end of the vertical pole 1, and is used to maintain electrical connection with the rear sensor 3, the end face sensor 4 and the horizontal edge sensor 5, to provide power supply and intelligent decision control. One of the vertical poles 1 is provided with an alarm device 7 on one side of the top.

[0029] The one-way support base 10 is arranged at the bottom of the vertical pole 1, and is used to prevent the vertical pole 1 from being overturned due to reverse rotation and sliding.

[0030] In the description of the present application, the top of the horizontal pole 2 is provided with an anti-skid stripe 8.

[0031] The horizontal pole 2 located at the top end is provided with a reinforcing rib 9 at the bottom, and the horizontal pole 2 located at the bottom end is also provided with a reinforcing rib 9 at the bottom, and the reinforcing rib 9 is fixedly connected with the vertical pole 3.

[0032] The horizontal pole 2 vertically divides the vertical pole 1 into different edge detection areas.

[0033] In the description of the present application, the one-way support base 10 comprises a sleeve 1001 sleeved on the bottom of the vertical pole 1, and the sleeve 1001 is arranged inside the one-side fixing seat 1002 and is movably connected.

[0034] The bottom end of the single-sided fixing seat 1002 is provided with a supporting base plate 1003, and the bottom end of the supporting base plate 1003 is provided with an anti-skid supporting pad 1004.

[0035] It should be noted that the vertical pole 1 and the horizontal pole 2 of the intelligent insulating ladder are both formed by using glass fiber reinforced epoxy resin composite material through high-temperature pultrusion process, wherein the vertical pole 1 (ladder beam) has a square cross section, and the horizontal pole 2 (step) has a trapezoidal cross section, and the two form a hollow profile with a rectangular or trapezoidal shape through structure optimization, and have high specific strength and light weight characteristics. The vertical pole 1 as the core support structure needs to meet the mechanical requirements of compressive strength ≥ 300 MPa and bending strength ≥ 400 MPa to ensure that it does not deform when subjected to overload impact, and the surface is finely treated to eliminate sharp corners and round arcs to avoid work injury; the horizontal pole 2 is integrated with anti-skid design to improve the friction force of the feet to prevent slipping.

[0036] In the description of the present application, Figure 6 As shown in the description of the present application, the controller 6 comprises a main processing module, a power management module, a data storage module, a human-computer interaction module and a communication interface module; wherein the power management module is connected with the main processing module, the data storage module, the human-computer interaction module, the communication interface module and the electromagnetic protection module.

[0037] The main processing module is used for real-time acquisition and processing of original signals from the rear sensor 3, the end face sensor 4 and the lateral edge sensor 5, and real-time detection of the climbing detection data of the operator based on the three-point contact principle, and triggering of the early warning reminder when the violation phenomenon is detected.

[0038] In the description of the present application, the main processing module comprises a signal acquisition fusion module, a state modeling prediction module, a compliance judgment decision module, an early warning generation distribution module and a coordination self-checking optimization module; wherein the signal acquisition fusion module, the state modeling prediction module, the compliance judgment decision module, the early warning generation distribution module and the coordination self-checking optimization module are connected in sequence.

[0039] The signal acquisition fusion module is used for synchronous acquisition of original signals of the rear sensor 3, the end face sensor 4 and the lateral edge sensor 5, and generation of touch point distribution data through dynamic filtering, touch point validity verification and spatial topology association.

[0040] In the description of the present application, the generation of touch point distribution data through dynamic filtering, touch point validity verification and spatial topology association comprises: Step S11, utilize the precise time protocol to synchronize the node clock of the rear sensor 3, the end face sensor 4 and the lateral edge sensor 5, perform transmission delay compensation processing on the original signal, and align the time axis by using linear interpolation method for low frequency signal based on the highest sampling rate.

[0041] Specifically, high-precision crystal oscillator clock sources are assigned to all sensors, and the clocks of each node are synchronized through PTP (Precision Time Protocol) to eliminate initial time deviation. Transmission delays are dynamically calculated according to sensor types, for example, a rear sensor has a transmission delay of 2 ms through RS485, and an end face / edge sensor has a transmission delay of 1 ms through CAN bus, and the time stamp is reversely compensated when the signal is received.

[0042] Finally, the time axis of the low-frequency signal is aligned using linear interpolation based on the highest sampling rate.

[0043] Step S12, the electromagnetic intensity and vibration frequency in the original signal after compensation and time axis alignment are monitored in real time, a multi-stage filter pipeline is used to perform gain compensation on the effective frequency band, and an enhanced signal is formed.

[0044] Specifically, the electromagnetic intensity and vibration frequency are monitored in real time, and the filter parameters are dynamically adjusted. The multi-stage filter pipeline includes three aspects, namely, first-stage filtering: a 50 Hz notch filter is used to eliminate power frequency interference; second-stage filtering: threshold denoising based on wavelet transform is used to separate transient pulses; third-stage filtering: Kalman filtering is used to predict signal trends and suppress random jitter.

[0045] Step S13, based on physical constraints and spatiotemporal continuity constraints, invalid touch points with pressure values less than a preset threshold in the enhanced signal are removed to retain valid touch points, and a sliding window method is used to calculate touch point residence time.

[0046] Specifically, for example, pressure values of rear sensors 3, end face sensors 4, and edge sensors 5 less than 30 N are considered as invalid signals, and touch points need to last for ≥1 second (to prevent false triggering), and a sliding window integration method is used to calculate touch point residence time; and adjacent touch points need to satisfy limb movement speed limits, such as a cross-bar interval ≥0.5 seconds, to avoid jumping false judgments.

[0047] Step S14, the valid touch points of the rear sensors 3, end face sensors 4, and edge sensors 5 are mapped to the three-dimensional coordinate system of the ladder body, a spatial distribution topology graph of hand and foot touch points is constructed, and the cross-bar 2 is used as an interval to divide into several touch edge detection regions, structured touch point distribution data is output, and a touch point data set is formed.

[0048] Specifically, a Cartesian coordinate system is established with the ladder bottom as the origin, the vertical bars divide the AV1-AV4 regions, the cross-bars define the AH1-AH4 logic units, and the reference Figure 7 . Multi-source data binding: end face sensors (vertical pressure) are used to locate the precise position of the feet on the cross-bar (left / middle / right); edge sensors (lateral pressure) and rear sensors (lateral pressure) are used to locate the hand holding height (AV2 or AV3); topology graph generation: output structured touch point data set, including spatial coordinates (such as {AV2, AH3 left})、pressure values and timestamps, providing input for safety analysis.

[0049] A state modeling prediction module is configured to construct a ladder body dynamic behavior model based on physical rules and behavior constraints, to calculate contact pressure distribution, gravity center offset and overturning risk coefficient of the contact distribution data in real time, and to output a climbing stage mark and an overturning risk coefficient.

[0050] In the description of the present application, the construction of the ladder body dynamic behavior model based on physical rules and behavior constraints, the real-time calculation of the contact pressure distribution, the gravity center offset and the overturning risk coefficient of the contact distribution data in the current time period of the contact data set, and the output of the climbing stage mark and the overturning risk coefficient include: In step S21, the stage state of climbing is divided in real time based on the contact distribution data of the current time period in the contact data set, and the rationality of stage switching is verified in combination with the historical contact sequence to filter abnormal jumps in the climbing process. The stage state includes a climbing state, a working state and a transition state.

[0051] Specifically, the contact number and distribution criterion can refer to the following aspects: 1. Climbing state: detecting continuous contact change and effective contact ≥ 3, such as moving from horizontal bar AH1 to AH2, and single hand holding vertical bar + double feet stepping horizontal bar at both ends, triggering the climbing state mark. 2. Working state: double feet continuously stepping the same horizontal bar ≥ 3 seconds and pressure balance, pausing contact detection to reduce false positives. 3. Transition state: identifying short single-point contact, such as single hand changing grip with only 1-2 contacts lasting < 0.5 seconds, marked as transition state to avoid false triggering of warning.

[0052] The rationality of stage switching is verified in combination with the historical contact sequence, such as working state → climbing state requiring contact number transition, filtering abnormal jumps.

[0053] In the description of the present application, the construction of the ladder body dynamic behavior model based on physical rules and behavior constraints, the real-time calculation of the contact pressure distribution, the gravity center offset and the overturning risk coefficient of the contact distribution data in the current time period of the contact data set, and the output of the climbing stage mark and the overturning risk coefficient include: In step S211, based on the space-time distribution characteristics of the contact data set, the hand and foot contacts are dynamically clustered and grouped, the contact combination mode is identified, and a finite state machine model is constructed according to the contact combination mode and physical rules, and the transition conditions and boundary constraints of the climbing state, the working state and the transition state are set.

[0054] Specifically, the contacts in the same time window are grouped according to spatial proximity: the rear sensor contacts are grouped as hand action group, and the end surface / horizontal edge sensor contacts of the same horizontal bar are grouped as foot action group. The pressure balance in the hand and foot groups is verified to exclude non-coordinated action interference, such as false contact with vertical bar.

[0055] For historical contact sequence verification, the current hand and foot group needs to have a time sequence relationship with the previous state group, such as the time difference of the foot group moving from the horizontal bar AH1 to AH2 being greater than or equal to 0.5 seconds, to avoid misjudgment of cross-level jumping.

[0056] The transfer conditions and boundary constraints of the climbing state, the working state and the transition state are as follows: 1. Climbing state trigger: detecting that the hand and foot group valid contact is greater than or equal to 3, such as left hand group AV2+right foot group AH3 left end+left foot group AH3 right end, and the foot group continuously moves up by more than 2 horizontal bars; 2. Working state activation: both feet groups continuously step on the same horizontal bar for more than or equal to 3 seconds, and the pressure fluctuation is less than a threshold; 3. Transition state marking: identifying short-time contact loss and the next state meeting the expected migration, such as recovering the climbing state after the transition.

[0057] If it is detected that the climbing state and the working state are triggered at the same time (logical conflict), the foot group position is verified first: if the foot group crosses the horizontal bar, it is the climbing state, otherwise it is the working state.

[0058] Step S212, the migration rule of the historical phase state is counted, a state transition matrix is generated, and the confidence of the current state transition is calculated, and if the confidence is less than a preset threshold, it is marked as an abnormal jump. For the migration of the abnormal jump, a transition state label is forcibly inserted and the contact sampling window is extended until the time sequence is restored to be reasonable.

[0059] Specifically, the historical state migration rule is counted, such as the probability of climbing state→working state being 0.8 and the probability of climbing state→transition state being 0.2, a state transition matrix P is generated, and the expression is: ; The confidence of the current state transition is calculated C = P （当前状态∣前一状态） , if C <0.1, it is regarded as an abnormal jump, such as the working state directly jumping to the climbing state without transition. For the low-confidence migration, a transition state label is forcibly inserted and the contact sampling window is extended, for example, from 200 ms to 500 ms, until the time sequence is restored to be reasonable.

[0060] Step S22, based on the contact pressure gradient, the ladder body inclination angle and the environmental disturbance parameters, a ladder body dynamic behavior model is constructed by fusing the gravity center offset trajectory, and a real-time overturning risk coefficient in the climbing process is solved.

[0061] In the description of the present application, based on the contact pressure gradient, the ladder body inclination angle and the environmental disturbance parameters, a ladder body dynamic behavior model is constructed by fusing the gravity center offset trajectory, and a real-time overturning risk coefficient in the climbing process is solved. Step S221, the pre-acquired ladder body inclination angle and environmental disturbance parameters are acquired, respectively, time stamp alignment and unit normalization are performed on the contact distribution data, and a spatiotemporally consistent multi-dimensional input data set is generated.

[0062] Specifically, with the controller clock as the reference, the asynchronous data streams of contact pressure (10 ms period), base inclination (20 ms period), and wind speed (50 ms period) are interpolated and resampled to 10 ms time granularity, ensuring time alignment of data points. The wind speed sensor transmits through RS485 with a delay of 5 ms, and the time stamp is corrected in reverse at the receiving end.

[0063] The contact pressure gradient is linearly mapped to [0, 1] according to the sensor range; the base inclination is mapped to [-1, 1] according to ±90°; and the wind speed is normalized to [0, 1] according to the 0-15 m / s range, suppressing modeling deviations caused by dimensional differences.

[0064] Step S222, based on the physical correlation between wind speed, vibration, and ladder inclination, the net inclination change is extracted by dynamically decoupling environmental disturbance and inclination reading interference, and the net inclination data is output.

[0065] Specifically, based on the fluid dynamics formula: ; where, v is the wind speed, k is the wind resistance coefficient, and the inclination offset caused by wind load is calculated in real time.

[0066] A 5Hz low-pass filter is applied to the inclination sensor signal to filter out high-frequency jitter caused by mechanical vibration and retain the static inclination main component; the output compensated inclination is used as the input of physical modeling; in the formula, θ net represents the net inclination data; θ raw represents the reference inclination.

[0067] Step S223, based on the contact distribution data and the net inclination data, taking the one-way support base 10 as the fulcrum, the contact pressure point coordinates are fused to construct a ladder body dynamic behavior model based on the lever principle, calculate the real-time barycenter coordinates and offset tolerance, and output the overturning risk coefficient.

[0068] Specifically, taking the center of the base non-slip pad as the fulcrum O , the contact pressure P i point coordinates are Pos i , and the barycenter coordinates Center xy are calculated as: ; According to the friction angle of the non-slip pad θ friction (measured value) and the net inclination θ net, dynamically calculate the critical value of center of gravity offset: ; Where L is the ladder height.

[0069] Capsizing risk factor R temp The calculation formula is: .

[0070] Step S23: Based on the current climbing stage status and the calculated result of the overturning risk coefficient, a climbing stage mark and a prediction instruction of the overturning risk coefficient are encapsulated and output to the compliance decision-making module.

[0071] The compliance determination and decision-making module is used to match contact point distribution data, climbing stage marks and overturning risk factors in real time based on a pre-set violation rule library to generate violation type and risk level labels.

[0072] In the description of the present invention, based on a pre-set violation rule library, real-time matching of contact point distribution data, climbing stage marks and overturning risk coefficients is performed to generate violation type and risk level labels, including: Step S31: Dynamically load the corresponding violation determination rule subset based on the current climbing stage mark, align the contact distribution data with the climbing stage mark and the overturning risk coefficient in time and space, input it into the violation determination rule subset for logical matching, and generate the violation type.

[0073] Specifically, the corresponding violation judgment rule subset is dynamically loaded according to the current climbing stage mark to achieve accurate matching of rules and behavior status, and avoid invalid rules interfering with decision-making efficiency.

[0074] For the stage-rule mapping, it includes: 1. Climbing state: loading contact number rule and same-side contact prohibition rule; 2. Working state: loading steady-state pressure balance rule and unilateral stepping prohibition rule.

[0075] In addition, when strong winds are detected, additional rules for capsizing risk are automatically injected, such as lowering the center of gravity shift coefficient threshold by 20%.

[0076] The rule engine matches the following: 1. Same-side violation detection: If there are ≥2 touch points on the same vertical bar area (e.g., AV1-AV2), the "Same-side Hand and Foot Concentration" tag is triggered. 2. Quantity violation detection: If there are <3 valid touch points in the climbing state and the duration lasts for >1 second, the "Insufficient Touch Points" tag is triggered. 3. Pressure violation detection: If the pressure on one side of the horizontal bar accounts for >80% in the working state, the "Unilateral Pedaling Imbalance" tag is triggered.

[0077] Step S32: Based on the preset violation severity and environmental disturbance intensity, the violation type is risk quantified, a risk level label is output, and the violation type and risk level label are encapsulated and output to a warning generation and distribution module.

[0078] Specifically, for the risk level label, it can be divided into operational risk (level 1): only rule matching violation, such as abnormal contact distribution, no overturning trend; structural risk (level 2): rule violation superimposed overturning risk coefficient > 0.7, or environmental disturbance triggers reinforcement judgment.

[0079] The early warning generation and distribution module is used to generate differentiated early warning instructions based on the violation type and the risk level label, and distribute them to the man-machine interaction module, and output the decision log to the data storage module for solidification.

[0080] Specifically, the early warning generation and distribution module receives the violation type and the risk level label from the compliance judgment decision module, dynamically generates differentiated early warning instructions according to the preset hierarchical response mechanism, including triggering different levels of sound and light alarm signals and ladder top anti-skid lock control commands, and encapsulates the early warning type, risk level, time stamp and environmental inducement into a standard log data packet, which is distributed to the man-machine interaction module in real time for sound and light alarm and state display, and is transmitted to the data storage module for decision record persistent storage, ensuring the early warning response and traceability closed loop.

[0081] The coordination self-check optimization module is used to monitor the running state of each module, coordinate the task scheduling period, and perform software and hardware self-check to maintain the real-time performance and safety of the processing link.

[0082] Specifically, the running state and resource occupation rate of the signal acquisition, state modeling, compliance judgment and early warning distribution submodules are monitored in real time, and the dynamic task scheduler automatically allocates computing resources and adjusts the sampling frequency according to the system load and climbing activity, while periodically performing sensor link connectivity verification and software and hardware fault diagnosis. If channel abnormalities or data distortion are detected, the fault node is immediately isolated and a local alarm is triggered. In combination with historical false positive rate and performance index feedback, the model parameters and rule library threshold are optimized in a closed loop to maintain the real-time performance and system robustness of the processing link.

[0083] The power management module is used to provide direct current power supply, and integrates charge and discharge control, power monitoring, low voltage, overload protection and low power alarm functions to prevent data loss and circuit impact.

[0084] Specifically, the power management module provides stable direct current power supply for the entire system, and the core functions include efficient power conversion, battery charge and discharge control, real-time power monitoring and low power early warning. At the same time, it integrates multiple circuit protection mechanisms such as overvoltage, undervoltage and overcurrent to prevent data loss or hardware damage caused by power abnormalities. By dynamically adjusting the power consumption strategy, it ensures continuous operation in an environment of -20℃ to 40℃, and supports hot plug replacement of batteries to extend the device battery life.

[0085] The data storage module is used to record the timestamp of each climb, the sensor number that triggered the early warning reminder, and the environmental data to achieve full life cycle management and intelligent operation and maintenance.

[0086] Specifically, it is responsible for recording operation data throughout the entire cycle, including the precise timestamp of each climb, the sensor number that triggered the early warning, such as the abnormality of the rear sensor AV2, and environmental parameters, and stores them in an encrypted log format; the built-in non-volatile memory prevents data loss during power outages, supports rapid retrieval of historical records by time range or event type, provides a traceability basis for intelligent operation and maintenance, and can generate equipment health reports to assist maintenance decisions.

[0087] The human-computer interaction module is used to display the current climbing status in real time and provide interactive control functions. When receiving a control instruction triggered by a violation, it drives the alarm device 7 to execute an audible and visual alarm.

[0088] Specifically, the climbing status, such as the contact distribution map and risk level, is visualized in real time through the OLED display screen, and the user is allowed to adjust the alarm threshold through the touch screen or physical buttons; when the early warning instruction of the compliance judgment module is received, the graded sound and light alarm is automatically triggered - the first-level early warning starts a low-frequency buzzer and a flashing yellow warning light, and the second-level risk activates a high-frequency pulse buzzer and a red flashing light. At the same time, the violation type and handling instructions will pop up on the screen.

[0089] The communication interface module is used to provide a wired communication interface and a wireless communication interface to establish a communication connection with the rear sensor 3, the end face sensor 4, the lateral sensor 5 and the smart mobile terminal to realize the real-time transmission and sharing of climbing detection data.

[0090] Specifically, a dual-mode communication link is integrated: the wired interface directly connects to the vertical edge, end face and horizontal edge sensors to achieve millisecond-level data collection, such as RS485 and CAN bus; the wireless interface establishes a low-latency connection with the smart mobile terminal, and pushes real-time climbing data and early warning notifications to the guardian APP.

[0091] Using differential signal transmission and CRC verification technology to ensure the bit error rate is less than 10⁻ in high-voltage electric field environment 6 , and also supports remote command response, such as forced sleep and parameter configuration update.

[0092] The electromagnetic protection module is used to provide electromagnetic shielding function to resist electromagnetic interference in the environment.

[0093] Specifically, the core circuit is wrapped by a metal shielding shell, combined with a multi-layer board-level paving design and a magnetic ring filtering technology, to effectively suppress power frequency interference and transient electromagnetic pulses, such as substation 50Hz noise; the internal PCB layout adopts a partition isolation strategy, and a TVS tube and a surge protection circuit are added to a sensitive signal path to meet the IEC 61000-4-3 standard and ensure the stability of sensor data acquisition and control instruction transmission in a strong electromagnetic environment.

[0094] The following will supplement the description of the intelligent insulating ladder designed by the application with specific embodiments.

[0095] The working principle of the safety touch edge (rear sensor 3, end surface sensor 4 and horizontal edge sensor 5) is as follows: the safety touch edge is in a high impedance / open circuit state without force, and when a certain value of pressure is applied to it, the component is turned on, and the resistance is negatively related to the pressure, that is, the greater the pressure, the smaller the resistance.

[0096] Usage: apply force to the component to make the outer large end of its sensor contact each other, resulting in changes in current and resistance, and the controller analyzes the input signal.

[0097] The working voltage of the safety touch edge is not higher than 36V; the resistance range is 5-100 ohms, that is, when about 30 Newtons of force is applied to the safety touch edge (about 3KG object is stationary without any impulse, momentum or external force); the pressure range is 30 Newtons (corresponding to about 100 ohms) to 1000 Newtons (corresponding to about 5 ohms).

[0098] Controller operation mode: one end of the safety touch edge is connected to a pull-up resistor, and the other end is connected to ground, and the controller 6 analog input port detects the safety touch edge voltage division size, which can detect whether there is external force and the force size.

[0099] As shown in Figure 7 , during the climbing process of the worker, both hands need to hold the ladder and at least one foot needs to step on the horizontal bar 2; when the worker is working, both feet need to step on the touch edges at both ends of the same horizontal bar 2, and one hand needs to hold the other horizontal bar 2 or vertical bar 1 (whether a third touch point needs to be held is pending discussion).

[0100] Violations: 1. The touch edge detects less than three points; 2. The touch edge detects two points on the same vertical bar 1 of the ladder: for example, only three touch points, AV1, AV2 and AH2 are detected. Since only three touch points are detected, and AV1 and AV2 are on the same vertical bar, it is determined that the operation is not normal; 3. The touch edge detects that the horizontal bar pressure is too small, when the pressure is less than a certain resistance and exceeds 1 second (the time is pending), at this time it is judged that it is not the worker's foot operation, but other objects are placed on the horizontal bar. 4. The distance between the contacts is too large. For example, three contacts AV4, BV1, and AH5 are detected, and the distance between AV4 and BV1 is too large, which is determined to be abnormal operation.

[0101] 5. If both hands or both feet grasp the same side of the horizontal bar, it will be judged as a violation (because this safety touch edge can only detect the amount of pressure and the number of contact points on this same safety touch edge). For example, if both feet stand on the left side of horizontal bar 2 at the same time, only AH4 will be detected as being triggered, and the presence of two feet will not be detected.

[0102] Excluding other phenomena that are not in compliance with the above regulations, the operation is considered normal.

[0103] In addition, at least two safety edges must be installed on the same horizontal bar 2, separated by 10 cm (approximately the width of a foot). A single safety edge can detect pressure magnitude, but cannot simultaneously detect multiple force locations. If multiple points of application are required, multiple safety edges must be used. Furthermore, the safety edges have certain temperature requirements; excessively high or low temperatures may affect measurement accuracy. It is recommended to use the device at room temperature to ensure stability.

[0104] In summary, with the help of the above technical solutions of the present invention, by relying on the excellent insulation performance of fiberglass and integrating safety technologies such as foolproof settings, anti-slip reinforcement, and three-point sensing, a set of intelligent security systems covering the entire operation process is constructed, including stable ground support, safe climbing step by step, and reliable anchoring at the top; it is committed to eliminating the key risks such as non-standard climbing by personnel, which leads to slippage and overturning, stepping errors, and ladder shaking, and creating a truly reliable and safe working platform for high-risk workers in industries such as electricity and communications. Through integrated sensing technology, the contact situation of workers during climbing is dynamically monitored. When it is detected that the ladder user does not meet the three effective contact points when climbing, an immediate and clear danger warning is issued to the staff through sound and light alarms, and the records are stored to remind the workers of non-standard climbing behavior.

[0105] It should be understood that although the steps in the flowcharts of the accompanying drawings are shown in sequence as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some of the steps in the flowcharts of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

Claims

1. An intelligent insulating ladder, characterized in that: include: A vertical bar (1), wherein a plurality of horizontal bars (2) are arranged at equal intervals between two vertical bars (1); A rear sensor (3) is provided on the side of the vertical bar (1) facing away from the operator, and is used to detect the vertical hand gripping condition of the operator; An end surface sensor (4) is provided at the top end of the horizontal bar (2) and is used to detect the stepping condition of the operator; A lateral sensor (5) is provided on the side of the horizontal bar (2) facing away from the operator, and is used to detect the lateral gripping condition of the operator's hand; A controller (6) is arranged on the inner side of the top end of the vertical bar (1), and is electrically connected to the rear sensor (3), the end face sensor (4) and the horizontal edge sensor (5), providing power supply and intelligent decision control; Wherein, the controller (6) comprises: The main processing module is used to collect and process the original signals from the rear sensor (3), the end sensor (4) and the lateral sensor (5) in real time, and based on the three-point contact principle, detect the operator's climbing detection data in real time, and trigger an early warning reminder when a violation is detected.

2. The intelligent insulating ladder according to claim 1, characterized in that: An alarm device (7) is provided on one side of the top of one of the vertical bars (1); The top of the horizontal bar (2) is provided with anti-slip stripes (8); The bottom of the horizontal bar (2) at the top and the bottom of the horizontal bar (2) at the bottom are both provided with reinforcing ribs (9), and the reinforcing ribs (9) are fixedly connected to the vertical bar (3); The horizontal bar (2) vertically divides the vertical bar (1) into different edge detection areas.

3. The intelligent insulating ladder according to claim 1, characterized in that: Also includes: A one-way support base (10) is provided at the bottom of the vertical bar (1) and is used to prevent the vertical bar (1) from rotating in the opposite direction and sliding and overturning; The one-way support base (10) comprises a sleeve (1001) sleeved on the bottom of the vertical bar (1), the sleeve (1001) being arranged inside the one-sided fixed seat (1002) and maintaining a movable connection; a support base plate (1003) is provided at the bottom end of the one-sided fixed seat (1002), and an anti-slip support pad (1004) is provided at the bottom end of the support base plate (1003).

4. The intelligent insulating ladder according to claim 1, characterized in that: The controller (6) further comprises: The power management module provides DC power and integrates charge and discharge control, power monitoring, low voltage, overload protection, and low battery alarm functions to prevent data loss and circuit impact; The data storage module is used to record the timestamp of each climb, the sensor number that triggered the warning, and environmental data to achieve full life cycle management and intelligent operation and maintenance; A human-computer interaction module is used to display the current climbing status in real time, provide interactive control functions, and drive the alarm device (7) to perform sound and light alarms when receiving a control instruction triggered by a violation; A communication interface module, for providing a wired communication interface and a wireless communication interface, and establishing a communication connection with the rear sensor (3), the end sensor (4), the lateral sensor (5), and the intelligent mobile terminal, so as to realize real-time transmission and sharing of climbing detection data; Electromagnetic protection module, used to provide electromagnetic shielding function to resist electromagnetic interference in the environment; The power management module is connected to the main processing module, the data storage module, the human-computer interaction module, the communication interface module and the electromagnetic protection module respectively.

5. The intelligent insulating ladder according to claim 1, characterized in that: The main processing module includes: A signal acquisition and fusion module for synchronously acquiring original signals from the rear sensor (3), the end face sensor (4), and the lateral sensor (5), and generating contact distribution data through dynamic filtering, contact validity verification, and spatial topological association; A state modeling and prediction module is used to construct a dynamic behavior model of the ladder body based on physical rules and behavioral constraints, calculate the contact pressure distribution, center of gravity offset and overturning risk coefficient of the contact distribution data in real time, and output a climbing stage mark and overturning risk coefficient; The compliance decision module is used to match contact point distribution data, climbing stage marks and overturning risk factors in real time based on a pre-set violation rule library to generate violation type and risk level labels; The early warning generation and distribution module is used to generate differentiated early warning instructions based on violation types and risk level labels and distribute them to the human-computer interaction module, and simultaneously output decision logs to the data storage module for solidification; Coordinated self-check optimization module, used to monitor the operating status of each module, coordinate task scheduling cycles, and perform software and hardware self-checks to maintain the real-time and security of the processing link; Among them, the signal acquisition and fusion module, the state modeling and prediction module, the compliance determination and decision module, the early warning generation and distribution module and the coordinated self-inspection optimization module are connected in sequence.

6. The intelligent insulating ladder according to claim 5, characterized in that: The generation of contact distribution data through dynamic filtering, contact validity verification and spatial topological association includes: Synchronizing the node clocks of the rear sensor (3), the end sensor (4), and the lateral sensor (5) using a precise time protocol, performing transmission delay compensation processing on the original signal, and aligning the time axis of the low-frequency signal using a linear interpolation method based on the highest sampling rate; Real-time monitoring of the electromagnetic intensity and vibration frequency in the original signal after compensation and time axis alignment, using a multi-stage filtering pipeline to perform gain compensation on the effective frequency band to form an enhanced signal; Based on physical constraints and spatiotemporal continuity constraints, invalid contacts with pressure values ​​less than a preset threshold in the enhanced signal are eliminated to retain valid contacts, and the sliding window method is used to calculate the contact dwell time; The effective contact points of the rear sensor (3), the end sensor (4), and the horizontal edge sensor (5) are mapped to the three-dimensional coordinate system of the ladder body, a spatial distribution topology of the hand and foot contact points is constructed, and a plurality of edge detection areas are formed by dividing the area with the horizontal bar (2) as an interval, and structured contact distribution data are output to form a contact data set.

7. The intelligent insulating ladder according to claim 5, characterized in that: The ladder dynamic behavior model is constructed based on physical rules and behavioral constraints, the contact pressure distribution, center of gravity offset and overturning risk coefficient of the contact distribution data are calculated in real time, and the climbing stage mark and overturning risk coefficient are outputted, including: Based on the contact distribution data of the current time period in the contact data set, the climbing stage state is divided in real time, and the rationality of the stage switching is verified in combination with the historical contact sequence, and abnormal jumps in the climbing process are filtered out; wherein, the stage state includes climbing state, working state and transition state; Based on the contact pressure gradient, ladder inclination angle, and environmental disturbance parameters, a ladder dynamic behavior model integrating the center of gravity offset trajectory is constructed to calculate the real-time overturning risk coefficient during the climbing process. Based on the current climbing stage status and the calculated result of the overturning risk coefficient, a climbing stage mark and a prediction instruction of the overturning risk coefficient are encapsulated and output to the compliance decision-making module.

8. The intelligent insulating ladder according to claim 7, characterized in that: The method of dividing the climbing stage status in real time based on the contact distribution data of the current time period in the contact data set, verifying the rationality of the stage switching in combination with the historical contact sequence, and filtering abnormal jumps in the climbing process includes: Based on the spatiotemporal distribution characteristics of the contact data set, the hand and foot contacts are dynamically clustered and grouped to identify the contact combination pattern. Based on the contact combination pattern and physical rules, a finite state machine model is constructed to set the transfer conditions and boundary constraints of the climbing state, working state, and transition state. Statistics are collected on the migration patterns of historical states to generate a state transition matrix and calculate the confidence of the current state migration. If the confidence is less than the preset threshold, it is marked as an abnormal jump. For the migration of abnormal jumps, the transition state label is forcibly inserted and the contact sampling window is extended until the timing returns to a reasonable state.

9. The intelligent insulating ladder according to claim 7, characterized in that: The ladder dynamic behavior model integrated with the center of gravity offset trajectory is constructed based on the contact pressure gradient, ladder inclination angle, and environmental disturbance parameters to calculate the real-time overturning risk coefficient during the climbing process. The pre-collected ladder body inclination angle and environmental disturbance parameters are obtained, and timestamp alignment and unit normalization are performed with the contact point distribution data to generate a temporally and spatially consistent multi-dimensional input dataset. Based on the physical relationship between wind speed, vibration and ladder inclination, the net inclination change is extracted by dynamically decoupling the interference between environmental disturbance and inclination reading, and the net inclination data is output; Based on the contact point distribution data and the net inclination angle data, the one-way support base (10) is used as a fulcrum, the coordinates of the contact point pressure are integrated, a dynamic behavior model of the ladder body based on the lever principle is constructed, the real-time center of gravity coordinates and the offset tolerance are calculated, and the overturning risk coefficient is output.

10. The intelligent insulating ladder according to claim 5, characterized in that: The method of matching contact point distribution data, climbing stage marks and overturning risk factors in real time based on a pre-set violation rule library to generate violation type and risk level labels includes: Based on the current climbing stage mark, the corresponding violation judgment rule subset is dynamically loaded, the contact distribution data is spatially and temporally aligned with the climbing stage mark and the overturning risk factor, and then input into the violation judgment rule subset for logical matching to generate the violation type; Based on the preset violation severity and environmental disturbance intensity, the violation type is quantified, the risk level label is output, and the violation type and risk level label are encapsulated, and the output value warning generation and distribution module is generated.

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