Intelligent safety rope with height detection function

Abstract

The invention discloses an intelligent safety rope with a height detection function. The intelligent safety rope comprises a safety rope body, a control module, a height detection module and an early warning module. The height detection module comprises an air pressure sensor and a satellite positioning module, and the control module corrects air pressure data through temperature compensation, processes satellite data by adopting Kalman filtering, and dynamically weights and fuses double-source data according to a satellite signal-to-noise ratio to obtain an accurate fusion height. And the identification and early warning of the low-hanging and high-use state are realized through continuous period judgment. A tension sensor and a buffer braking module are further arranged in the safety rope body, the control module identifies the falling risk by monitoring the fusion height falling rate and real-time tension double criteria, controls the buffer braking module to execute the graded braking process after falling is judged, and sequentially outputs increasing multi-stage braking force till stable stopping is achieved. And active early warning for low hanging and high use in high-altitude operation and intelligent buffering braking during falling are integrally achieved, and the initiative and reliability of safety protection are remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of safety protection technology, and in particular to an intelligent safety rope with height detection that integrates intelligent detection and active early warning functions. Background Technology

[0002] In high-altitude operations in industries such as power, construction, and telecommunications, safety ropes are core equipment for ensuring the safety of workers. Traditional safety ropes and harnesses primarily rely on the physical strength of their materials (such as the breaking tensile strength of the braided fibers) and the mechanical locking structure of the hooks to provide passive protection. This type of equipment only functions by absorbing the impact force during a fall, and cannot provide early warning of potential risks before an accident occurs, nor can it take active steps to reduce injury during the fall.

[0003] Specifically, the existing technology has the following main drawbacks:

[0004] Unable to monitor and prevent low-hook, high-use operations in real time: Low-hook, high-use is a common and dangerous operation in high-altitude work, where the worker's safety rope is hooked and fixed below their center of gravity. In the event of a fall, the distance the person falls and the impact load will increase significantly, greatly increasing the risk of injury and even secondary accidents. Traditional safety ropes are completely unable to detect and warn of this unsafe condition in real time.

[0005] The lack of accurate and reliable methods for monitoring operational altitude is a significant issue. While some attempts have been made to incorporate altitude sensors into safety equipment, these solutions are often simplistic and lack sufficient reliability. For example, using a barometer alone is susceptible to interference from ambient temperature and weather changes, resulting in significant accuracy drift. Using satellite positioning alone can lead to signal loss or fluctuations in obstructed environments such as indoors or under bridges. Current technology lacks a fusion monitoring solution capable of continuously and stably outputting accurate altitude information in complex operational environments.

[0006] Lack of intelligent fall detection and graded braking capabilities: Existing safety ropes' buffering or braking mechanisms are mostly purely mechanically triggered, resulting in delayed response and abrupt, uncontrollable braking processes that may cause additional injury to workers. They cannot perform rapid and accurate intelligent identification based on the dynamic characteristics of the initial stage of a fall (such as sudden descent rate and a surge in tension), nor can they achieve smooth, graded braking to maximize the absorption of impact energy and protect personnel safety.

[0007] Lack of management functions: Traditional safety ropes are information silos, and safety managers cannot remotely monitor the safety status of on-site workers in real time (such as whether they are used at a high altitude or whether the rope is under stress), making it difficult to conduct effective remote supervision and centralized dispatch.

[0008] In summary, existing safety protection technologies suffer from problems such as passive monitoring, lack of early warning, abrupt braking, and a disconnect between management and operational practices. Therefore, there is an urgent need for intelligent safety protection equipment capable of proactively monitoring operational status, providing intelligent risk warnings, and implementing effective intervention in emergency situations to fundamentally improve the safety level of high-altitude operations. Summary of the Invention

[0009] To address the problems existing in the prior art, the main objective of this invention is to provide an intelligent safety rope with height detection. This invention aims to overcome the shortcomings of existing safety ropes, which provide passive protection and cannot warn of the risks of low-hanging and high-use. By integrating air pressure and satellite dual-source height data and processing them with a specific algorithm, this invention achieves real-time, accurate, and reliable monitoring of the worker's height. This allows for the automatic and timely identification of the dangerous state of low-hanging and high-use, and the proactive issuance of an alarm through a local early warning module. This transforms passive protection into proactive early warning, preventing fall accidents caused by improper hook placement from the source.

[0010] The present invention also aims to provide an intelligent safety rope with height detection, which further solves the problem that the braking method of existing safety ropes is rough and uncontrollable after a fall. The present invention intelligently identifies the risk of fall and triggers a phased and gradual braking process to achieve orderly and stable absorption of the impact energy of the fall, minimize the risk of secondary injury to the workers during the braking process, and reduce the impact load on the suspension point and the safety rope itself.

[0011] To achieve the above objectives, the present invention adopts the following technical solution: A smart safety rope with height detection includes a safety rope body, with a working end hook and a personnel end hook connected to both ends of the safety rope body, and a control module, a height detection module and an early warning module provided on the safety rope body; The altitude detection module includes a barometric pressure sensor and a satellite positioning module; The control module is electrically connected to the height detection module and the early warning module respectively; The control module is configured to perform the following steps to detect a low-load, high-use status: Receive raw barometric altitude data from the barometric sensor and raw satellite altitude data from the satellite positioning module; The original barometric altitude data is corrected by temperature compensation based on real-time ambient temperature to obtain the corrected barometric altitude. The raw satellite altitude data is filtered using a Kalman filter algorithm to obtain the filtered satellite altitude. Based on the signal-to-noise ratio output by the satellite positioning module, weighting coefficients are dynamically selected, and a weighted fusion algorithm is used to calculate the fusion height. The control module obtains the hook attachment point height and safety threshold, and determines whether the following conditions are met: the fused height minus the hook attachment point height is greater than the safety threshold. When the condition is met in multiple consecutive sampling periods, the control module determines that the device is in a low-hanging-high-use state and controls the early warning module to activate the alarm.

[0012] Optionally, the formula used for temperature compensation correction of the original barometric altitude data based on real-time ambient temperature is as follows: , Among them, H' p To correct for barometric altitude, H p The original barometric altitude data is given, k is the temperature compensation coefficient, T is the real-time ambient temperature, and T0 is the reference temperature; the reference temperature is in the range of 20℃ to 30℃, and the temperature compensation coefficient is in the range of 0.02 m / s to 0.04 m / s.

[0013] Optionally, the step of dynamically selecting weighting coefficients based on the signal-to-noise ratio output by the satellite positioning module and calculating the fusion height using a weighted fusion algorithm includes: The control module compares the signal-to-noise ratio with at least two preset signal-to-noise ratio thresholds, and selects one of a plurality of preset weight values ​​as the weight coefficient based on the comparison result.

[0014] Optionally, the at least two preset signal-to-noise ratio (SNR) thresholds include a first threshold and a second threshold, wherein the first threshold is greater than the second threshold; the plurality of preset weight values ​​include a first value, a second value, and a third value corresponding to different SNR intervals; wherein, the first value is selected when the SNR is not lower than the first threshold, the second value is selected when the SNR is lower than the first threshold but not lower than the second threshold, and the third value is selected when the SNR is lower than the second threshold; wherein, the first threshold is in the range of 25 to 35 dB, and the second threshold is in the range of 15 to 25 dB; the first value, the second value, and the third value are in the range of 0 to 1, wherein the first value is less than the second value, and the second value is less than the third value.

[0015] Optionally, the step of filtering the original satellite altitude data using a Kalman filter algorithm to obtain the filtered satellite altitude includes: The control module calls the built-in Kalman filter algorithm to process the data sequence output in real time by the satellite positioning module, so as to eliminate positioning noise and filter abnormal data jumps caused by instantaneous signal blockage, thereby outputting smooth and continuous filtered satellite altitude data.

[0016] Optionally, the safety rope body is further provided with a tension sensor; the control module is also configured to perform the following steps to identify fall risk, including: The control module is used to determine that a fall has occurred and trigger braking when the state of simultaneously detecting that the descent rate calculated based on the fusion height exceeds a descent rate threshold and the real-time tension value detected by the tension sensor exceeds a preset tension threshold continues for a minimum determination time; Optionally, the safety rope body also includes a buffer braking module; when braking is triggered, the control module is further configured to perform the following steps to execute a graded braking process: when a fall is determined to have occurred, the buffer braking module is controlled to execute a graded braking process; the graded braking process includes: During the first braking phase, the braking device controlling the buffer braking module outputs a first-level braking force; In the subsequent second braking phase, the output braking force of the braking device is increased to a secondary braking force; In the subsequent third braking phase, the output braking force of the braking device is maintained at level three until the descent rate is detected to be lower than a safe speed value.

[0017] Optionally, the first predetermined time period is in the range of 300 milliseconds to 700 milliseconds; the duration from the trigger braking to the end of the second predetermined time period is in the range of 800 milliseconds to 1200 milliseconds; The total buffer stroke of the buffer in the buffer braking module is in the range of 300 mm to 800 mm, and the braking response time of the braking device is no more than 150 milliseconds.

[0018] Optionally, the warning module is integrated into the personnel-end hook and includes a warning light and a speaker; when it is determined to be in a low-hanging-high-use state, the warning light is controlled to flash at a first frequency and the speaker is controlled to play a first voice prompt; when a fall braking occurs, the warning light is controlled to flash at a second frequency higher than the first frequency and the speaker is controlled to play a second voice prompt. The safety rope body is also equipped with a 4G mobile communication module, which is used to transmit the height data obtained by the height detection module to the remote monitoring platform in real time, and to receive control commands from the remote monitoring platform.

[0019] Optionally, the multiple consecutive sampling periods specifically refer to 2 to 5 consecutive sampling periods; the data sampling frequency of the height detection module is in the range of 5 to 20 Hz; and the safety threshold is adjustable in the range of 0.5 to 3 meters. The barometric pressure sensor has a detection range of -50 meters to 1000 meters and an absolute error of no more than ±0.1 meters; the satellite positioning module is a module that supports BeiDou-3 dual-mode positioning, with a positioning update frequency of no less than 10Hz and a positioning error of no more than ±0.5 meters. The enclosure protection rating of the height detection module is not lower than IP65; the control module also includes a data storage unit for cyclically storing no less than 15 days of historical working data.

[0020] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0021] (1) In this invention, a dual-source altitude detection module consisting of a barometric pressure sensor and a satellite positioning module is used to achieve complementary altitude information in complex environments, overcoming the problem of insufficient reliability of a single sensor. Specifically, real-time temperature compensation is applied to the barometric pressure data to improve its long-term stability; Kalman filtering is applied to the satellite data to effectively filter out noise and abnormal jumps; and the fusion weight is dynamically adjusted according to the satellite signal-to-noise ratio to ensure that the most reliable fused altitude can be output under any working condition. The control module adopts a continuous multi-cycle judgment strategy to effectively filter out interference from normal actions, significantly reduce the false alarm rate, and ensure that the real dangerous state is reliably captured. Once it is determined to be low-mounted and high-used, an early warning is immediately triggered to guide the operators to make on-site adjustments, thereby forming an active safety closed loop and eliminating potential safety hazards from the source. Overall, it realizes intelligent detection and real-time early warning of low-mounted and high-used states with high precision, high reliability, and strong environmental adaptability, fundamentally endowing the safety rope with active protection capabilities.

[0022] (2) In this invention, furthermore, the entire process from risk perception to smooth braking is optimized through synergistic action. It employs a dual criterion based on the fusion of descent rate and real-time tension for fall detection, effectively avoiding false triggering and providing a rapid response in the initial stages of a fall. Once a fall is detected, the system initiates a graded braking process: first, a smaller braking force is output for buffering intervention; then, the braking force is linearly increased for smooth deceleration; and finally, a moderate braking force is maintained until a safe stop. This graded timing control strategy decomposes and gradually applies the enormous impact force, significantly reducing the peak impact load and the risk of secondary injury to the human body. Overall, combined with the early warning function, a complete intelligent protection system of pre-warning and in-process intervention is constructed, greatly improving the comprehensive protective performance of the safety rope. Attached Figure Description

[0023] Figure 1 This is a three-dimensional structural diagram of an intelligent safety rope with height detection according to an embodiment of the present invention; Figure 2 This is a functional block diagram of an intelligent safety rope with height detection according to an embodiment of the present invention; Figure 3 This is a first process diagram of an intelligent safety rope with height detection according to an embodiment of the present invention; Figure 4 This is a schematic diagram of the second process of an intelligent safety rope with height detection according to an embodiment of the present invention.

[0024] Reference numerals: 1. Safety rope body; 2. Working end hook; 3. Personnel end hook; 4. Control module; 5. Height detection module; 6. Barometric pressure sensor; 7. Satellite positioning module; 8. 4G communication module; 9. Early warning module; 10. Microprocessor; 11. Buffer braking module; 12. Preset safe height threshold module; 13. Safety rule algorithm module; 14. Audible and visual alarm; 15. Vibration alarm. Detailed Implementation

[0025] To better illustrate the objectives, technical solutions, and advantages of the present invention, the specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and are not intended to limit the scope of the invention.

[0026] like Figure 1 and Figure 2 The diagram shows an intelligent safety rope with height detection according to an embodiment of the present invention. The intelligent safety rope includes a safety rope body 1 with a certain length and strength. Hook structures are provided at both ends of the safety rope body 1. One hook structure is defined as a working end hook 2, used for fixing to a reliable support point for high-altitude operations. The other hook structure is defined as a personnel end hook 3, used for connecting to the safety belt worn by the worker. The safety rope body 1 is typically woven from high-strength fibers. Functional modules such as a height detection module 5, a control module 4, and an early warning module 9 are integrated into the interior or surface of the safety rope body 1.

[0027] Specifically, the control module 4 is a microcomputer system embedded within the safety rope. Its core is a high-performance microprocessor 10, responsible for all data processing, judgment, and control. Height detection modules 5 are fixed near the working end hook 2 and the personnel end hook 3, respectively. Each height detection module 5 includes a barometric pressure sensor 6 and a satellite positioning module 7. The warning module 9 includes an audible and visual alarm 14 and a vibration alarm 15, typically compactly integrated into the personnel end hook 3. The audible and visual alarm 14 includes a high-brightness red warning light (such as an LED) and a speaker. The control module 4 establishes an electrical connection via internal wiring to the height detection module 5, the warning module 9, and other sensors and braking modules mentioned later. The vibration alarm 15 uses a flat, miniature vibration motor, which is compact and easy to integrate. This alarm is directly fixed to the inside of the personnel end hook 3 or the grip area, ensuring that the vibration generated when the hook is connected to the personnel's safety belt or held by the personnel is directly transmitted to the worker's hand or body, making it easily perceptible. The vibration alarm (15) is electrically connected to the designated drive interface of the control module 4 via a wire. In addition, a 4G communication module 8 (4G, fourth-generation mobile communication) is integrated inside the safety rope to realize wireless data exchange with a remote Internet server.

[0028] In this embodiment, reference Figure 3 The control module 4 is programmed to execute the following core algorithm flow to detect the low-load, high-use state: S11. Data Acquisition. This process begins with data acquisition. Control module 4 simultaneously reads raw measurement data from barometric pressure sensor 6 and satellite positioning module 7 at a set frequency. The data obtained from barometric pressure sensor 6 is unprocessed raw barometric altitude data, while the data obtained from satellite positioning module 7 is raw satellite altitude data. For example, data from the altitude detection modules 5 at the work site and personnel end are read synchronously at a sampling frequency of 10 Hz. Specifically, raw barometric altitude data H is obtained from barometric pressure sensor 6 at the work site. p1 The raw satellite altitude data H is obtained from the satellite positioning module 7 at the operation end. s1 Raw barometric altitude data H is obtained from the barometric pressure sensor 6 at the personnel end. p2 Raw satellite altitude data H is obtained from the satellite positioning module 7 at the personnel end. s2 .

[0029] S12, Height Calculation and Preprocessing.

[0030] S121: After acquiring the raw barometric altitude data, control module 4 performs a series of preprocessing steps aimed at improving accuracy. For barometric altitude data, since atmospheric pressure values ​​are significantly affected by ambient temperature, direct use will lead to measurement errors. Therefore, the system introduces a temperature compensation algorithm. One form of this formula is that the corrected barometric altitude equals the raw barometric altitude multiplied by a coefficient, which is the product of a temperature compensation coefficient and the difference between the real-time ambient temperature and the reference temperature. The raw barometric altitude data H at the work end and the personnel end... p1 and H p2 Perform temperature compensation. Adjust the original barometric altitude data H' p1 The compensation formula is: , Among them, H' p1 The corrected working end air pressure altitude is given by k1, which is the temperature compensation coefficient, calibrated to 0.03 m / ℃ through experiments, and T is the real-time ambient temperature (measured by the built-in thermometer of the air pressure sensor 6). o For reference temperature, 25℃ is used; For the original barometric altitude data H' p2 The compensation formula is: , Among them, H' p2 To correct the personnel end air pressure altitude, k2 is the temperature compensation coefficient, set to the same value as k1, i.e. 0.03 m / ℃, T is the real-time ambient temperature (measured by the built-in thermometer of the air pressure sensor 6), and To is the reference temperature, set to 25℃.

[0031] S122: After acquiring the raw satellite altitude data, the H at the work end and the personnel end... s1 and H s2 Kalman filtering is performed separately. Control module 4 has a built-in Kalman filter, with H... s1 and H s2 As an observation, by iteratively performing prediction and update steps, signal jumps are filtered out, and a smooth filtered satellite altitude H' is output. s1 and H' s2 .

[0032] Specifically, the satellite altitude data from the satellite positioning module 7 constitutes a data sequence. [0], ,... These raw data typically contain two main types of interference: one is random measurement noise caused by ionospheric disturbances, receiver thermal noise, etc., which manifests as small high-frequency fluctuations in the data near the true value; the other is transient anomalous jumps caused by partial obstruction by trees or buildings or multipath reflection of the signal, which manifests as sudden, significant, and transient erroneous values ​​in the data that deviate significantly from the trend.

[0033] During the initialization phase, the control module 4 sets the following parameters and initial state for its built-in Kalman filter: (1) State vector: , where H is the estimated height and V is the estimated rate of vertical change (the first derivative of the height). The initial state X0 can be set to the first raw measurement value Hs_raw[0] and the initial velocity 0.

[0034] (2) State transition matrix: , where Δt is the sampling period (0.1 seconds), and this matrix is ​​used to predict the state at the current time based on the state at the previous time.

[0035] (3) Process noise covariance matrix: Q, used to model the uncertainty of the system itself (such as the randomness of personnel movement), its value can be calibrated by experiments, and it is a small positive definite matrix.

[0036] (4) Observation matrix: This indicates that the height H can be directly observed, but the velocity V cannot be directly observed.

[0037] (5) Measurement noise covariance: R, the value of which is based on the accuracy statistics of satellite positioning module 7 under static conditions (e.g., variance is ). The setting reflects the uncertainty of the measurement.

[0038] In each sampling period k, the filtering algorithm iteratively executes the following two core steps: First, perform the prediction step, based on the optimal estimated state at the previous time k-1. Given the state transition matrix F, predict the prior state estimate for the current time k: .

[0039] Simultaneously, update the prior estimate error covariance: This step is equivalent to making a theoretical calculation of height and velocity based on the system's motion model.

[0040] Then, the update step is performed to obtain the actual observed value at the current time k, that is, the original altitude output by satellite positioning module 7. .

[0041] Calculate Kalman gain It determines the weight of the predicted and observed values ​​in the final result: .

[0042] By using the Kalman gain and actual observations, the prior state estimate is corrected to obtain the posterior state estimate (i.e., the optimal estimate) at the current time k. .in This is called a news item, which is the difference between the observed value and the predicted value.

[0043] Finally, update the posterior estimation error covariance: This prepares for the next iteration.

[0044] This step introduces the actual measurement, which contains noise, and uses it to correct the purely theoretical prediction. The Kalman gain is automatically adjusted: when the measured noise R is very small (signal quality is good), the gain K... k It will increase, and the algorithm will trust new observations more; when the measurement noise R is large (poor signal quality), the gain K will increase. k As the value decreases, the algorithm places greater trust in the predictions of the system model.

[0045] In step S122, the control module 4 outputs the optimal estimated altitude obtained from each iteration as the filtered satellite altitude for the current moment. Compared to the original input sequence, this output sequence has higher continuity, smoothness, and reliability, providing a high-quality altitude information source for subsequent data fusion steps.

[0046] S13. Dual-Source Data Fusion. Control module 4 needs to fuse the two pre-processed height data sources into a more reliable composite height value. An adaptive weighted fusion strategy is used here. Specifically, the job-side fused height H... f1 High integration with personnel f2 Determined by the following formula: , , where α is a dynamically selected weighting coefficient.

[0047] The key to this embodiment is that the fusion weights are not fixed, but dynamically depend on the quality of the current output signal of the satellite positioning module 7. A key indicator of signal quality is the signal-to-noise ratio (SNR). The current SNR output by the satellite positioning module 77 is read, and the unit is decibels (dB).

[0048] Specifically, the control module 4 presets two signal-to-noise ratio thresholds, such as the first threshold SN. Rref1 The second threshold SNR is 30 dB. ref2 The threshold is 20 dB. Based on the comparison between the real-time signal-to-noise ratio and these two thresholds, the system dynamically selects a weighting coefficient between zero and one. The dynamic selection of the weighting coefficient follows these rules: If SNR This indicates that the satellite signal is excellent. In this case, a small weighting coefficient is selected, such as a first value of 0.3. ; like The signal quality is moderate. In this case, a moderate weighting coefficient is selected, such as a second value of 0.5. ; like If the signal quality is poor, a larger weighting coefficient should be selected, such as a first value of 0.8. .

[0049] Ultimately, the fused altitude is calculated by multiplying the corrected barometric altitude by the weighting factor, and then adding the filtered satellite altitude multiplied by one minus the weighting factor.

[0050] It is understandable that, among them, the first threshold SNR ref1 Within the range of 25 to 35 dB, the second threshold SNR ref2 Within the range of 15 to 25 dB; correspondingly, the first, second, and third values ​​are within the range of 0 to 1, and the first value is less than the second value, and the second value is less than the third value.

[0051] S14. Low-hanging-high-use judgment and early warning. After obtaining the fused height, the control module 4 compares it with a pre-set or acquired hook attachment point height. The hook attachment point height is the height of the position of the hook 2 at the working end, which can be obtained through a positioning record of the satellite positioning module 7 at the start of the operation, or it can be manually input. The difference between the two is obtained. ,like The system has a preset safety threshold ΔH, for example, 1.5 meters. This value can be adjusted within the range of 0.5 meters to 3 meters depending on the type of work, such as by using the 4G communication module 8. The control module 4 will determine whether the current height difference exceeds the safety threshold ΔH, for example, by determining whether... .

[0052] To avoid false alarms caused by minor normal personnel movements or single data fluctuations, the system employs a continuous judgment logic. That is, only when the condition that the height difference is greater than the safety threshold is met for multiple consecutive sampling cycles, such as three consecutive height measurement cycles (corresponding to 0.3 seconds), will the control module 4 ultimately determine that the current situation is a dangerous state of low mounting and high usage.

[0053] S15, First Alarm. Once a low-hanging, high-use configuration is detected, control module 4 immediately sends a command to warning module 9. Warning module 9 then activates, the warning light is controlled to flash at a frequency of 1 Hz, and simultaneously, control module 4 calls and plays an audio file identified as "Audio_Alert1," which is played by the speaker. This audio file contains a clearly recorded voice message: "Low-hanging, high-use configuration, please adjust the hook position." The playback mode is loop playback, and the volume is also set to [unspecified value]. Simultaneously, control module 4 activates the vibration alarm, providing tactile alerts to workers in hazardous conditions to enhance the warning effect, especially in noisy or brightly lit working environments to ensure reliable perception of the warning information. This local alarm can immediately remind workers of the risks and take corrective measures. When control module 4 detects that the height difference Δ has been less than the safety threshold ΔH for M cycles (e.g., M=2), it automatically stops the warning mode, the warning light turns off, and the speaker is muted.

[0054] At the same time, through the 4G communication module 8, real-time integrated height data, hook height, alarm status and other information are sent to the remote monitoring platform, enabling safety management personnel to grasp the on-site situation.

[0055] In this embodiment, reference Figure 4 The control module 4 is programmed to execute the following core algorithm flow to perform fall risk monitoring and provide active fall protection capabilities. For this purpose, a tension sensor is integrated within the safety rope body 1 to monitor the tension of the rope in real time. Simultaneously, the safety rope body 1 also integrates a buffer braking module 11, which typically includes a mechanical buffer and a braking device controllable by an electrical signal. The buffer can employ a multi-segment spring structure, with a total buffer stroke designed in the range of 300 to 800 mm, for example, 500 mm. The braking device needs to have a fast response capability; its response time from receiving a command to generating effective braking should not exceed 150 milliseconds, for example, 100 milliseconds. The fall risk monitoring and active fall protection capabilities specifically include the following steps: S21. Fall Detection. Control module 4 monitors for risk using a parallel fall detection algorithm. Fall detection is based on a dual-condition judgment. The first condition is the speed condition, which is the descent rate calculated in real time based on the aforementioned fused height. The second condition is the force condition, which is that the real-time tension value detected by the tension sensor exceeds a preset threshold. The system requires that both conditions be met simultaneously, and that this simultaneous satisfaction must last for the shortest possible time. Only when all these requirements are met will control module 4 confirm that a fall event requiring intervention has occurred and immediately trigger braking.

[0056] Specifically: the fusion height H calculated based on the above embodiments f For example, the high degree of integration of personnel. f1 Real-time calculation of fusion height H f Rate of change, i.e., rate of decrease It identifies falls by setting two conditions.

[0057] Condition 1 (Speed ​​Criterion): (That is, the descent rate exceeds 2 meters per second); Condition 2 (Tension Criterion): Tension Sensor Reading (That is, exceeding 60% of the rated tensile force).

[0058] When conditions one and two are met simultaneously and the duration is greater than 100 milliseconds, control module 4 determines that a fall has occurred and immediately triggers braking.

[0059] S22. Staged Braking Process. The braking process does not apply maximum force all at once, but rather employs a staged, gradual, staged braking process. In the initial stage after braking is triggered, control module 4 controls the braking device to output the first-level braking force. This force is relatively small, and its purpose is to allow the buffer to gently absorb energy, reduce the descent acceleration, and avoid rigid impact. In the following second stage, control module 4 controls the output braking force of the braking device to linearly increase from the first level to a larger second-level braking force, achieving a smooth transition in the deceleration process. In the third stage, control module 4 maintains the braking force at a relatively stable third-level level until the system detects that the descent rate has fallen below a preset safe speed value. At this point, the fall is considered to have been stopped, and the braking process ends.

[0060] Specifically: Phase 1 (Buffer Intervention Period, 0-500 milliseconds): The control braking device outputs a small braking force (approximately 30% of the maximum braking force). At this time, the buffer begins to undergo elastic deformation, absorbing the initial impact energy and initially and gently suppressing the fall acceleration.

[0061] The second stage (linear force increase period, 500-1000 milliseconds): The output braking force of the control braking device increases linearly from the first stage to the second stage (reaching 60% of the maximum braking force). The buffer continues to compress. This stage achieves a smooth transition, avoiding sudden changes in braking force.

[0062] The third stage (stable holding period, after 1000 milliseconds): The output braking force of the control braking device is maintained at the third level (approximately 80% of the maximum braking force) until the descent rate v is detected to be below 0.1 m / s. At this point, it is considered that the personnel have basically stopped and the braking ends.

[0063] S23, Second Alarm. When control module 4 determines that a fall has occurred, warning module 9 is activated. The warning light is controlled to flash at a frequency of 5Hz. Simultaneously, control module 4 calls and plays an audio file identified as "Audio_Alert2". The speaker plays this audio file, which is a clearly recorded voice message: "Fall risk, braking in progress." The playback mode is loop playback, and the volume is also set to [missing information]. This local alarm can immediately alert operators to risks and allow them to take corrective action. When the braking process ends, i.e., control module 4 detects that the descent rate v is lower than the safe speed v_safe (e.g., ...), ... After that, the warning mode will automatically stop.

[0064] To facilitate post-event analysis and equipment maintenance, control module 4 also includes a data storage unit. This unit can cyclically store key operational data over a period of time, such as fusion height, tension value, alarm event records, and brake trigger records for the most recent 15 or 30 days. This stored data can be automatically uploaded to the cloud via 4G communication module 8, or exported locally via physical interfaces on the device, such as a universal serial bus interface.

[0065] In summary, this specific embodiment details the structure and working mechanism of an intelligent safety rope integrating highly intelligent detection and active protection functions. Through the combination of dual-sensor data fusion and specific algorithms, accurate early warning of low-hanging-high-use conditions is achieved. Through dual-criteria identification and graded braking control, effective intervention in fall events is realized, thus forming a complete safety protection system from risk prevention to accident mitigation.

[0066] In this embodiment, a preset safety parameter module is configured, and the control module 4 pre-stores a set of benchmark parameters for safety determination. This set mainly includes the hook hanging point height H. h Safety threshold ΔH (default 1.5 meters, adjustable remotely from 0.5 to 3.0 meters), fall detection descent rate threshold v th (-2.0 m / s), drop test tension threshold F th (15.0 kN), shortest duration decision time t min (100 milliseconds) and the safe speed value v used to determine whether the braking process can end. safe (e.g., setting v) safe =0.1 m / s, etc.). These parameters constitute the quantitative benchmark for the system to make all automated safety judgments.

[0067] Hook hanging point height H h It can be set in two ways: (a) Automatic calibration: After the operation starts and the hook is fixed, the operator presses the "Set" button on the equipment. At this time, the control module records the current height detection module's fusion output value as H_h; (b) Remote setting: The value of H_h can be set directly by receiving instructions from the remote monitoring platform through the 4G communication module.

[0068] The safety threshold ΔH (maximum allowable height difference) represents the maximum permissible height difference between the worker's center of gravity and the hook attachment point. This threshold can be remotely adjusted via the 4G communication module according to different operating procedures or risk levels, with an adjustment range, for example, between 0.5 meters and 3.0 meters.

[0069] In this embodiment, a safety rule algorithm module 13 is also configured. The control module 4 has a built-in safety rule algorithm, which is responsible for scheduling data processing and executing core logic judgments. This algorithm first performs continuous periodic comparisons of the fusion height. Only when the real-time height difference Δ continuously exceeds the safety threshold ΔH for a preset number of periods (e.g., 3 periods) is it determined to be a low-mounted-high-use state and a level one alarm is triggered. Simultaneously, the algorithm monitors the descent rate and tension in parallel. Only when v... <v th With F>F th Both conditions are met simultaneously and the duration exceeds t. min Only when a fall is detected will the braking process and a level two emergency alarm be immediately initiated. This algorithm ensures that fall events receive the highest priority.

[0070] Through the above supplements, the embodiments clearly demonstrate how the preset safety height threshold module 12 provides a configurable judgment benchmark, and how the safety rule algorithm module 13, like a rigorous safety judge, executes a multi-step, false-judgment-preventing, and prioritized logical judgment based on real-time data and preset rules, thereby driving warning and braking actions. This enables those skilled in the art to fully understand the complete technology chain of the intelligent safety rope from perception and judgment to execution.

[0071] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0072] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A smart safety rope with height detection, comprising a safety rope body, wherein a working end hook and a personnel end hook are respectively connected to both ends of the safety rope body, characterized in that, The safety rope body is equipped with a control module, a height detection module, and an early warning module; The altitude detection module includes a barometric pressure sensor and a satellite positioning module; The control module is electrically connected to the height detection module and the early warning module respectively; The control module is configured to perform the following steps to detect a low-load, high-use status: Receive raw barometric altitude data from the barometric sensor and raw satellite altitude data from the satellite positioning module; The original barometric altitude data is corrected by temperature compensation based on real-time ambient temperature to obtain the corrected barometric altitude. The raw satellite altitude data is filtered using a Kalman filter algorithm to obtain the filtered satellite altitude. Based on the signal-to-noise ratio output by the satellite positioning module, weighting coefficients are dynamically selected, and a weighted fusion algorithm is used to calculate the fusion height. The control module obtains the hook attachment point height and safety threshold, and determines whether the following conditions are met: the fused height minus the hook attachment point height is greater than the safety threshold. When the condition is met in multiple consecutive sampling periods, the control module determines that the device is in a low-hanging-high-use state and controls the early warning module to activate the alarm.

2. The intelligent safety rope with height detection according to claim 1, characterized in that, The formula used for temperature compensation correction of the original barometric altitude data based on real-time ambient temperature is as follows: ， Among them, H' p To correct for barometric altitude, H p The original barometric altitude data is given, k is the temperature compensation coefficient, T is the real-time ambient temperature, and T0 is the reference temperature; the reference temperature is in the range of 20℃ to 30℃, and the temperature compensation coefficient is in the range of 0.02 m / s to 0.04 m / s.

3. The intelligent safety rope with height detection according to claim 1, characterized in that, The step of dynamically selecting weighting coefficients based on the signal-to-noise ratio output by the satellite positioning module and calculating the fusion height using a weighted fusion algorithm includes: The control module compares the signal-to-noise ratio with at least two preset signal-to-noise ratio thresholds, and selects one of a plurality of preset weight values ​​as the weight coefficient based on the comparison result.

4. The intelligent safety rope with height detection according to claim 3, characterized in that, The at least two preset signal-to-noise ratio (SNR) thresholds include a first threshold and a second threshold, wherein the first threshold is greater than the second threshold; the plurality of preset weight values ​​include a first value, a second value, and a third value corresponding to different SNR intervals; wherein, the first value is selected when the SNR is not lower than the first threshold, the second value is selected when the SNR is lower than the first threshold but not lower than the second threshold, and the third value is selected when the SNR is lower than the second threshold; wherein, the first threshold is in the range of 25 to 35 dB, and the second threshold is in the range of 15 to 25 dB; the first value, the second value, and the third value are in the range of 0 to 1, wherein the first value is less than the second value, and the second value is less than the third value.

5. The intelligent safety rope with height detection according to claim 1, characterized in that, The process of filtering the original satellite altitude data using the Kalman filter algorithm to obtain the filtered satellite altitude includes: The control module calls the built-in Kalman filter algorithm to process the data sequence output in real time by the satellite positioning module, so as to eliminate positioning noise and filter abnormal data jumps caused by instantaneous signal blockage, thereby outputting smooth and continuous filtered satellite altitude data.

6. The intelligent safety rope with height detection according to claim 1, characterized in that, The safety rope body also includes a tension sensor; the control module is further configured to perform the following steps to identify fall risk, including: The control module is configured to determine that a fall has occurred and trigger braking when the state of simultaneously detecting that the descent rate calculated based on the fusion height exceeds a descent rate threshold and the real-time tension value detected by the tension sensor exceeds a preset tension threshold continues for a minimum determination time.

7. The intelligent safety rope with height detection according to claim 6, characterized in that, The safety rope body also includes a buffer braking module; when braking is triggered, the control module is further configured to perform the following steps to execute a graded braking process: upon determining that a fall has occurred, the buffer braking module is controlled to execute a graded braking process; the graded braking process includes: During the first braking phase, the braking device controlling the buffer braking module outputs a first-level braking force; In the subsequent second braking phase, the output braking force of the braking device is increased to a secondary braking force; In the subsequent third braking phase, the output braking force of the braking device is maintained at level three until the descent rate is detected to be lower than a safe speed value.

8. The intelligent safety rope with height detection according to claim 7, characterized in that, The first predetermined time period is in the range of 300 milliseconds to 700 milliseconds; the duration from the trigger braking to the end of the second predetermined time period is in the range of 800 milliseconds to 1200 milliseconds; The total buffer stroke of the buffer in the buffer braking module is in the range of 300 mm to 800 mm, and the braking response time of the braking device is no more than 150 milliseconds.

9. The intelligent safety rope with height detection according to claim 6, characterized in that, The warning module is integrated on the personnel-end hook and includes a warning light and a speaker. When it is determined to be in a low-hanging-high-use state, the warning light is controlled to flash at a first frequency, and the speaker is controlled to play a first voice prompt. When a fall braking occurs, the warning light is controlled to flash at a second frequency higher than the first frequency, and the speaker is controlled to play a second voice prompt. The safety rope body is also equipped with a 4G mobile communication module, which is used to transmit the height data obtained by the height detection module to the remote monitoring platform in real time, and to receive control commands from the remote monitoring platform.

10. The intelligent safety rope with height detection according to claim 1, characterized in that, The aforementioned consecutive sampling cycles specifically refer to 2 to 5 consecutive sampling cycles; the data sampling frequency of the height detection module is in the range of 5 to 20 Hz; the safety threshold is adjustable in the range of 0.5 to 3 meters. The barometric pressure sensor has a detection range of -50 meters to 1000 meters and an absolute error of no more than ±0.1 meters; the satellite positioning module is a module that supports BeiDou-3 dual-mode positioning, with a positioning update frequency of no less than 10Hz and a positioning error of no more than ±0.5 meters. The enclosure protection rating of the height detection module is not lower than IP65; the control module also includes a data storage unit for cyclically storing no less than 15 days of historical working data.

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