Offset detection method and system of power transmission pole climbing anti-falling device
By analyzing the vibration data and displacement change rate of the clamping block in real time, dynamically calculating the offset anomaly degree, and generating an adaptive threshold, the problems of false alarms and missed alarms in traditional methods are solved, and efficient and safe detection of the transmission pole climbing anti-fall device is realized.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- SHANDONG GUANGDA LINE EQUIP CO LTD
- Filing Date
- 2026-01-15
- Publication Date
- 2026-04-14
AI Technical Summary
Traditional methods for detecting the offset of power pole climbing fall arrest devices rely on static offset thresholds, which can lead to false locking or slow response under normal worker actions or external interference, affecting detection accuracy.
By acquiring the vibration data and displacement of the clamping block in real time, analyzing the synchronization between vibration extremes and displacement change rate, dynamically calculating the offset anomaly degree, and generating an adaptive offset threshold, false alarms and missed alarms are avoided.
It enables intelligent and accurate detection of offsets, improving detection accuracy and avoiding security risks caused by false alarms and missed alarms.
Smart Images
Figure CN121855441A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of offset detection technology, specifically to an offset detection method and system for a power transmission pole climbing anti-fall device. Background Technology
[0002] The power pole climbing fall protection device is a safety protection device used for high-altitude operations. When workers use the fall protection device to climb, the device's internal offset detection module obtains the worker's dynamic parameter information in real time, thereby assessing the risk of the worker falling. Therefore, the accuracy of the offset detection module is the key to this device.
[0003] Traditional fall risk assessment methods rely on static offset thresholds, but these methods have inherent flaws in practical applications: normal large movements by workers or external disturbances such as strong winds often cause transient exceedances of the offset, leading to false locking of the device and seriously affecting work efficiency; conversely, if the threshold is increased to avoid false alarms, the slow response when a real fall occurs will endanger worker safety. In summary, the traditional static offset threshold method reduces the accuracy of offset detection for fall protection devices on power poles. Summary of the Invention
[0004] To address the aforementioned technical problems, the purpose of this application is to provide a method and system for detecting the offset of a power transmission pole climbing and fall prevention device. The specific technical solution adopted is as follows: In a first aspect, embodiments of this application provide a method for detecting the offset of a power transmission pole climbing and fall prevention device, the method comprising the following steps: Real-time acquisition of vibration data, displacement, and offset of the clamping blocks on the power transmission pole climbing and fall prevention device; Extract the extreme values from the vibration data of all times within a preset time period before each time. By analyzing the difference between any extreme value and the average level of extreme values, the first and second characteristic times are selected from the preset time period before each time. Analyze the differences in vibration data between each first characteristic time and its adjacent first characteristic time, and between each second characteristic time and its adjacent second characteristic time, to determine the vibration anomaly degree of the clamp at each time. By analyzing the difference between the instantaneous displacement change rate and the instantaneous offset change rate at all times within a preset time period before each time, the difference characteristic value of the clamping block at each time is determined, and combined with the vibration anomaly degree, the offset anomaly degree of the clamping block at each time is determined. Based on the offset anomaly, offset thresholds are determined at each time point to detect the offset at each time point.
[0005] Preferably, the step of selecting the first and second characteristic moments from a preset time period prior to each moment includes: Within a preset time period before each moment, calculate the mean of all extreme values greater than 0 and the mean of all extreme values less than 0, and record them as the first mean and the second mean, respectively. The time corresponding to the extreme value greater than the first mean is recorded as the first characteristic time, and the time corresponding to the extreme value less than the second mean is recorded as the second characteristic time.
[0006] Preferably, determining the vibration anomaly degree of the clamp at each time point includes: Within a preset time period before each moment, the differences in vibration data between each first characteristic moment and its adjacent first characteristic moment, and the differences in vibration data between each second characteristic moment and its adjacent second characteristic moment are analyzed respectively, so as to determine the upper vibration anomaly coefficient and the lower vibration anomaly coefficient of each first characteristic moment, thereby determining the upper vibration anomaly degree and the lower vibration anomaly degree at each moment. The vibration anomaly of the clamping block at each time point is positively correlated with the upper vibration anomaly and the lower vibration anomaly, respectively.
[0007] Preferably, determining the upper vibration anomaly coefficient at each first characteristic time and the lower vibration anomaly coefficient at each second characteristic time includes: The results of calculating the difference ratio of vibration data between each first characteristic moment and its adjacent first characteristic moment to the corresponding time interval, and the results of the difference ratio of vibration data between each second characteristic moment and its adjacent second characteristic moment to the corresponding time interval, are respectively denoted as the upper vibration anomaly coefficient of each first characteristic moment and the lower vibration anomaly coefficient of each second characteristic moment.
[0008] Preferably, determining the upper vibration anomaly degree and lower vibration anomaly degree at each time point includes: Calculate the mean of the normalized values of the upper vibration anomaly coefficients for all first characteristic moments within a preset time period before each moment, and the mean of the normalized values of the lower vibration anomaly coefficients for all second characteristic moments, and record them as the upper vibration anomaly degree and the lower vibration anomaly degree at each moment, respectively.
[0009] Preferably, the difference characteristic value of the clamping block at each time moment is the DTW distance between the normalized value of the instantaneous displacement change rate at all times within a preset time period before each time moment and the normalized value of the instantaneous offset change rate at all times.
[0010] Preferably, the offset anomaly of the clamping block at each time point is positively correlated with the vibration anomaly and the difference characteristic value, respectively.
[0011] Preferably, the expression for the offset threshold at each time point is: In the formula, This represents the offset threshold of the clamp block at time i; This indicates the degree of anomaly in the offset at time i; This indicates the preset base offset threshold.
[0012] Preferably, the detection of the offset at each time point includes: If the offset at the current moment is greater than the offset threshold at the current moment, the offset is abnormal; otherwise, the offset is normal.
[0013] Secondly, embodiments of this application also provide an offset detection system for a power pole climbing anti-fall device, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of the offset detection method for a power pole climbing anti-fall device described in any of the above-mentioned embodiments.
[0014] This application has at least the following beneficial effects: This application quantifies vibration anomaly by analyzing the severe impact characteristics in vibration data. Specifically, it selects vibration extreme points exceeding the average level as characteristic moments and calculates the relationship between vibration intensity and time interval between these characteristic moments to assess the severity and instability of the vibration. This method effectively captures strong impacts caused by worker actions or external disturbances, while ignoring gentle vibrations caused by equipment malfunctions. This allows for accurate assessment of the complexity and intensity of the current vibration environment, providing crucial decision-making basis for subsequent dynamic adjustment of offset thresholds and avoiding false alarms and missed alarms. Furthermore, this application quantifies the difference characteristic value by calculating the DTW distance between displacement and offset change rate to assess the synchronicity of their changes. By combining vibration anomaly degree, a comprehensive offset anomaly degree is finally generated. This method can effectively distinguish between synchronous offsets caused by normal climbing and asynchronous "pseudo-offsets" caused by external interference, thereby accurately determining whether the current offset is due to real risk or interference. This provides a core basis for dynamically adjusting the safety threshold and achieving a balance between preventing false alarms and missed alarms. Finally, this application generates an offset threshold that can be adaptively adjusted in real time by multiplying the dynamically calculated offset anomaly degree with a preset basic threshold. This threshold automatically widens when interference is strong to avoid false alarms and automatically tightens when the environment is stable to ensure high sensitivity. This achieves intelligent and accurate detection of offsets and improves the accuracy of offset detection for power pole climbing fall arrest devices. Attached Figure Description
[0015] To more clearly illustrate the technical solutions and advantages in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0016] Figure 1 A flowchart illustrating the steps of a method for detecting the offset of a power transmission pole climbing and fall prevention device according to an embodiment of this application; Figure 2 This is a flowchart of offset anomaly detection provided in one embodiment of this application. Detailed Implementation
[0017] To further illustrate the technical means and effects adopted by this application to achieve the intended purpose of the invention, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a method and system for detecting the offset of a power transmission pole climbing anti-fall device proposed in this application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.
[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.
[0019] The following description, in conjunction with the accompanying drawings, details the specific scheme of the offset detection method and system for a power pole climbing and fall prevention device provided in this application.
[0020] Please see Figure 1 The diagram illustrates a flowchart of a method for detecting the offset of a power transmission pole climbing anti-fall device according to an embodiment of this application. The method includes the following steps: Step S1: Real-time acquisition of vibration data, displacement, and offset of the clamping blocks on the power pole climbing and fall prevention device.
[0021] Vibration data of the clamping blocks on the power pole climbing fall protection device are obtained using vibration sensors, and the displacement and offset of the clamping blocks on the power pole climbing fall protection device are obtained in real time using strain gauge displacement sensors. In this embodiment, the sampling frequency of vibration data, displacement and offset are all set to 1kHz. The sampling frequency is set manually. In actual application, as other implementation methods, implementers can also set it according to specific circumstances. This embodiment does not impose any special restrictions.
[0022] The collected data is preprocessed by interpolating the vibration data, displacement, and offset to reconstruct a continuous time signal. In this embodiment, the interpolation method used is sinc interpolation. In practical applications, as other implementation methods, the implementer may also use other interpolation methods such as median interpolation depending on the specific circumstances. This embodiment does not impose any special restrictions on the selection of interpolation methods.
[0023] The process of interpolating data using the sinc interpolation method is a well-known technique. Therefore, the specific process of interpolating displacement and vibration data using the sinc interpolation method will not be described in detail.
[0024] Step S2: By analyzing the fluctuations of vibration extreme values and the synchronicity of displacement and offset changes, the vibration anomaly and consistency characteristics of the clamping block were evaluated, thereby dynamically calculating the offset anomaly at each time point.
[0025] Offset detection refers to the abnormal directional deviation of the clamping block on the power pole climbing fall arrestor when it fails to move along the preset trajectory. For example, if the preset trajectory of the clamping block is vertical up and down, but there is an excessive lateral deviation, the clamping block may not be able to accurately reach the designated position. This will cause the power pole climbing fall arrestor to fail to maintain normal safe operation. Traditional offset detection methods issue warnings by detecting whether the magnitude of the clamping block's deviation in the abnormal direction exceeds a fixed threshold. However, considering that the worker's movement and wind interference during high-altitude operations can cause the clamping block to deviate and vibrate in the abnormal direction, resulting in a large deviation, the measured deviation of the clamping block may exceed the preset threshold, leading to a misjudgment of the actual operating status of the power pole climbing fall arrestor and causing unnecessary warnings and maintenance.
[0026] To address the aforementioned issues, this embodiment analyzes the fluctuations of vibration extreme values and the synchronicity of displacement and offset changes, respectively, and evaluates the vibration anomaly and consistency characteristics of the clamping block. This allows for the dynamic calculation of the offset anomaly at each moment, providing early warning for offset and improving the accuracy of offset detection. The specific process is as follows: S2.1: Extract the extreme values from the vibration data of all times within the preset time period before each time. By analyzing the difference between any extreme value and the average level of extreme values, the first and second characteristic times are selected from the preset time period before each time. Analyze the difference between each first characteristic time and its adjacent first characteristic time, and each second characteristic time and its adjacent second characteristic time in the vibration data, to determine the vibration anomaly degree of the clamp at each time.
[0027] When the clamping blocks in the power pole climbing fall arrestor deform due to wear and long-term use, they will not follow the preset ideal trajectory during the climbing process. This causes the measured offset to be too large or even exceed the safety threshold for a period of time. In this case, the clamping block will show a continuous and slowly increasing lateral offset that is correlated with the displacement data. This offset will not show a rapid jump in a short period of time, nor will it vibrate rapidly back and forth. Therefore, the vibration data of the clamping block at this time does not have the characteristics of high-frequency vibration. It is characterized by slow oscillation with small amplitude and low frequency, without obvious abrupt vibration peaks.
[0028] When the clamping block in the power pole climbing fall arrestor is in normal condition, the deviation and vibration caused by the worker's movement posture and external interference as described above during the climbing process will result in a relatively strong vibration signal, accompanied by obvious transient impact and periodic high-frequency oscillation when the clamping block collides with the slide rail.
[0029] Therefore, based on the above analysis, this embodiment extracts the extreme values from the vibration data at all times within a preset time period before each time. By analyzing the difference between any extreme value and the average level of extreme values, the first and second characteristic times are selected from the preset time period before each time. The differences in vibration data between each first characteristic time and its adjacent first characteristic time, and between each second characteristic time and its adjacent second characteristic time, are analyzed to determine the vibration anomaly degree of the clamp at each time. Specifically: First, extract the extreme values from the vibration data at all times within a preset time period before each time point. By analyzing the difference between any extreme value and the average level of extreme values, the first and second characteristic times are selected from the preset time period before each time point. Specifically: Within a preset time period before each moment, calculate the mean of all extreme values greater than 0 and the mean of all extreme values less than 0, and record them as the first mean and the second mean, respectively. The time corresponding to the extreme value greater than the first mean is recorded as the first characteristic time, and the time corresponding to the extreme value less than the second mean is recorded as the second characteristic time. The first characteristic time refers to the time corresponding to the extreme value whose amplitude exceeds the average of all positive extreme values within the preset time period. It is used to capture and analyze strong, transient upward vibrations caused by collisions between the clamp and the slide rail, impacts from worker movements, etc. The second characteristic time refers to the time corresponding to the extreme value whose amplitude is lower than the average of all negative extreme values within the preset time period. It is used to capture and analyze strong, transient downward vibrations generated when the clamp rebounds after impact or is subjected to a reverse force.
[0030] It should be noted that the preset duration is set manually. In this embodiment, the preset duration is 5 seconds. The reason for setting it to 5 seconds is that it usually takes 2 to 5 seconds for a worker to complete a complete action cycle of "stepping-lifting-body stabilization-preparing for the next step" on the power transmission pole. Therefore, the preset duration is set to 5 seconds in this embodiment. However, this time may vary from person to person. Therefore, in actual application, as other implementation methods, implementers can also set it according to specific circumstances. This embodiment does not impose any special restrictions.
[0031] Furthermore, this embodiment analyzes the differences in vibration data between each first characteristic moment and its adjacent first characteristic moment, and between each second characteristic moment and its adjacent second characteristic moment, to determine the vibration anomaly degree of the clamp at each moment. Specifically: The results of calculating the difference ratio of vibration data between each first characteristic moment and its adjacent first characteristic moment to the corresponding time interval, and the results of the difference ratio of vibration data between each second characteristic moment and its adjacent second characteristic moment to the corresponding time interval, are respectively denoted as the upper vibration anomaly coefficient of each first characteristic moment and the lower vibration anomaly coefficient of each second characteristic moment.
[0032] It should be noted that there are many methods to measure the differences between data. In this embodiment, the absolute difference between each first characteristic moment and its adjacent first characteristic moment in the vibration data is taken as the difference between each first characteristic moment and its adjacent first characteristic moment in the vibration data. In practical applications, as other implementation methods, implementers may also use other methods such as the square of the difference to measure the differences in combination with the specific situation. This embodiment does not impose any special restrictions on the selection of methods for measuring data differences.
[0033] Furthermore, the mean value of the normalized value of the upper vibration anomaly coefficient at all first characteristic moments within the preset time period before each moment, and the mean value of the normalized value of the lower vibration anomaly coefficient at all second characteristic moments are calculated respectively, and are denoted as the upper vibration anomaly degree and the lower vibration anomaly degree at each moment.
[0034] It should be noted that there are many commonly used normalization methods. In this embodiment, the maximum-minimum normalization method is used to normalize the upper vibration anomaly coefficients at all first characteristic times and the lower vibration anomaly coefficients at all second characteristic times. In practical applications, as other implementation methods, implementers may also use other normalization methods such as z-score normalization method according to specific circumstances. This embodiment does not impose any special restrictions on the selection of normalization methods.
[0035] Among them, the maximum-minimum normalization method is a well-known technique, and the specific process of using it to normalize data will not be elaborated here.
[0036] Based on the upper and lower vibration anomalies at each time point, it can be understood that the upper vibration anomaly is used to characterize the intensity and instability of the positive vibration of the clamping block within a preset time period. It reflects the intensity and frequency of upward impact vibrations caused by worker work or external interference. If the upper vibration anomaly at the current time point is larger, it indicates that the upward impacts that occurred within the preset time period before the current time point, such as the clamping block suddenly hitting the top of the slide rail more frequently, with greater intensity differences and shorter intervals, indicate that there was significant external interference or violent operation by the worker within the preset time period before the current time point, and the interference on the clamping block offset detection was more severe. Conversely, if the upper vibration anomaly at the current time point is smaller, it indicates that the upward movement of the clamping block was stable within the preset time period before the current time point. At this time, the clamping block offset detection is less affected by vibration factors, and the measured offset data can better reflect the true movement state of the clamping block and has higher reliability.
[0037] The downward vibration anomaly is used to characterize the severity and instability of negative vibration, reflecting the intensity of the clamping block's downward rebound or reverse impact after impact. The larger the downward vibration anomaly at the current moment, the more severe the downward impact and rebound, which also indicates that there is significant interference in the detection of the current clamping block offset. Conversely, the smaller the downward vibration anomaly at the current moment, the more stable the downward movement of the clamping block is. In this case, the clamping block offset detection is less affected by negative vibration factors, and the measured offset data can better reflect the true motion state of the clamping block, with higher reliability.
[0038] Furthermore, based on the upper vibration anomaly degree and the lower vibration anomaly degree, it can be seen that the vibration anomaly degree of the clamping block at each time point is positively correlated with the upper vibration anomaly degree and the lower vibration anomaly degree, respectively.
[0039] It should be understood that a positive correlation means that the dependent variable increases as the independent variable increases, and the dependent variable decreases as the independent variable decreases. The specific relationship can be additive or multiplicative, etc., and is determined by the actual application. This application does not impose any special restrictions.
[0040] Preferably, as one implementation method, in this embodiment, the average of the upper vibration anomaly degree and the lower vibration anomaly degree at each time moment is taken as the vibration anomaly degree of the clamping block at each time moment. In actual application, as another implementation method, the implementer may also adopt other positive correlation calculation methods such as sum or product according to the specific situation. This embodiment does not impose any special restrictions.
[0041] Based on the vibration anomaly of the clamping block at each time point, it can be understood that the vibration anomaly is used to characterize the complexity and abnormality of the overall vibration of the clamping block within a preset time period. It directly reflects the intensity of the influence of external interference or internal fault on the movement state of the current power pole climbing anti-fall device. The vibration anomaly is jointly determined by the upper vibration anomaly and the lower vibration anomaly. If the upper vibration anomaly is larger at the current time point, it means that the clamping block is subjected to more severe impact from the incense, which will directly lead to an increase in the vibration anomaly. This indicates that the clamping block is experiencing strong and irregular mechanical impact at the current time point, which seriously affects the accuracy of the offset detection. At the same time, if the lower vibration anomaly is larger, it means that the clamping block is subjected to more severe downward impact and rebound. Similarly, the corresponding vibration anomaly is larger, indicating that the clamping block is subjected to significant dynamic interference. Conversely, if the abnormality of both the upper and lower vibrations at the current moment is smaller, it indicates that the overall vibration of the clamping block within the preset time period is more gentle and regular. This indicates that the clamping block's motion state is stable at the current moment, the external interference is minimal, the accuracy of the offset detection is high, and the measured data can truly reflect the operating status of the power transmission pole climbing anti-fall device.
[0042] Thus, this embodiment quantifies vibration anomaly by analyzing the severe impact characteristics in vibration data. Specifically, it selects vibration extreme points that exceed the average level as characteristic moments and calculates the relationship between vibration intensity and time interval between these characteristic moments to assess the severity and instability of vibration. This method can effectively capture strong impacts caused by worker actions or external interference, while ignoring gentle vibrations caused by equipment failures. This allows for accurate judgment of the complexity and interference intensity of the current vibration environment, providing a crucial decision-making basis for subsequent dynamic adjustment of offset thresholds and avoiding false alarms and missed alarms.
[0043] S2.2: By analyzing the difference between the instantaneous displacement change rate and the instantaneous offset change rate at all times within the preset time period before each time, the difference characteristic value of the clamping block at each time is determined, and combined with the vibration anomaly degree, the offset anomaly degree of the clamping block at each time is determined.
[0044] The climbing motion of workers on power transmission poles is not a continuous, uniform vertical ascent. Instead, it involves rapid ascents and brief pauses with each step on the stairs. Consequently, the displacement data of the clamping block, driven by the worker, rises in this pattern, exhibiting a stepped upward movement over a period of time. Similarly, the offset data also changes with the movement of the clamping block. In other words, both the displacement and offset data show the same stepped upward trend. Conversely, if the offset data changes due to abnormal swinging movements of the clamping block or external interference, the lateral offset signal will not show a stepped change but rather an irregular and chaotic movement pattern.
[0045] Based on the above analysis, this embodiment determines the difference characteristic value of the clamping block at each moment by analyzing the difference between the instantaneous displacement change rate and the instantaneous offset change rate at all moments within a preset time period before each moment, and combines it with the vibration anomaly degree to determine the offset anomaly degree of the clamping block at each moment. Specifically: First, the DTW distance between the normalized value of the instantaneous displacement change rate at all times within the preset time period before each time and the normalized value of the instantaneous offset change rate at all times is used as the difference characteristic value of the clamp at each time.
[0046] Since the dimensions of displacement and offset are significantly different, they are normalized separately.
[0047] It should be noted that the calculation methods for the instantaneous displacement change rate and the instantaneous offset change rate are as follows: The expression for the instantaneous displacement change rate at any given moment is: In the formula, Represents the rate of change of instantaneous displacement at time t; , These represent the displacements of the clamping block at times t and t-1, respectively. This represents the time interval between time t and time t-1; similarly, the expression for the rate of change of instantaneous offset at any given time is: In the formula, Represents the rate of change of instantaneous displacement at time t; , These represent the displacements of the clamping block at times t and t-1, respectively. This represents the time interval between time t and time t-1.
[0048] It should be noted that there are many commonly used normalization methods. In this embodiment, the instantaneous displacement change rate and the instantaneous offset change rate at all times are normalized using the maximum-minimum value normalization method. In practical applications, as other implementation methods, implementers may also use other normalization methods such as z-score normalization method according to specific circumstances. This embodiment does not impose any special restrictions on the selection of normalization methods.
[0049] The calculation method for DTW is a well-known technique, and its specific calculation process will not be elaborated here.
[0050] Based on the differential characteristic values of the clamp at each moment, it can be understood that the differential characteristic values are used to characterize the synchronicity of the change pattern between the preset direction displacement and the unconventional direction offset of the clamp, reflecting whether the lateral offset is caused by normal climbing action. On the tree branch, the differential characteristic value is reflected as the DTW distance between the normalized instantaneous displacement change rate and the instantaneous offset change rate. If the differential characteristic value of the clamp at the current moment is larger, it indicates that the synchronicity between the preset direction displacement and the unconventional direction offset is lower, indicating that the lateral offset of the clamp is disconnected from its vertical upward movement and is not synchronized. It is very likely that it is a pseudo offset caused by external factors such as abnormal swinging of the worker or sudden gusts of wind. Conversely, if the differential characteristic value of the clamp at the current moment is smaller, it indicates that the synchronicity between the preset direction displacement and the unconventional direction offset is higher, indicating that the lateral offset of the clamp closely follows its vertical climbing action. The two present a coordinated step-like change pattern, and this offset is part of the normal movement.
[0051] Furthermore, based on the vibration anomaly degree and the difference characteristic value, the offset anomaly degree of the clamping block at each time point is determined, specifically: In this embodiment, the offset anomaly of the clamping block at each time point is positively correlated with the vibration anomaly and the difference characteristic value, respectively.
[0052] Preferably, as one implementation method, the expression for the offset anomaly degree of the clamp block at each time point in this embodiment is: In the formula, This indicates the degree of anomaly in the offset of the clamp block at time i; This indicates the degree of vibration anomaly of the clamp at time i; Let represent the difference characteristic value of the clip at time i; exp[ ] represents the exponential function with the natural constant as the base. The offset anomaly degree ranges from 1 to 1. .
[0053] Based on the anomaly degree of the clamp block's offset at each time point, it can be understood that the anomaly degree is used to characterize whether the displacement generated by the clamp block at the current time is caused by a real risk (such as a failure of the anti-fall device for climbing power transmission poles) or a false anomaly (such as external interference). If the vibration anomaly degree of the clamp block is larger at the current time point, it indicates that the vibration mode is more complex, indicating a higher probability of external interference. This will lead to an increase in the offset anomaly degree, reflecting that the current offset is likely caused by interference, and the offset threshold needs to be increased to avoid false alarms. At the same time, if the difference characteristic value of the clamp block is larger at the current time point, it indicates that the synchronization between displacement and offset is worse, indicating that the lateral offset is more likely to be interference. This will also lead to a larger offset anomaly degree, indicating that the current offset is more likely to be a false anomaly, and the offset threshold needs to be increased to avoid false alarms. Conversely, if the vibration anomaly and difference characteristic value of the clamping block are smaller at the current moment, it indicates that the clamping block moves smoothly and the displacement and offset height are synchronized. This suggests that the current offset is more likely to be a real risk rather than caused by external interference. This will lead to a reduction in the offset anomaly and a more stringent offset threshold will be adopted, thereby maintaining high sensitivity to any offset that exceeds the norm and ensuring that the real fall risk can be captured in time.
[0054] Thus, this embodiment quantifies the difference characteristic value by calculating the DTW distance of the rate of change of displacement and offset to assess the synchronicity of their changes. Combined with the vibration anomaly degree, the offset anomaly degree is finally generated. This method can effectively distinguish between synchronous offset generated by normal climbing and asynchronous "pseudo-offset" caused by external interference, thereby accurately determining whether the current offset is a real risk or caused by interference. This provides a core basis for dynamically adjusting the safety threshold and achieving a balance between preventing false alarms and preventing missed alarms.
[0055] Step S3: Based on the offset anomaly, determine the offset threshold at each time point to detect the offset at each time point.
[0056] Based on the dynamic offset anomaly degree obtained in step S2, this embodiment further determines the offset threshold at each time step based on the offset anomaly degree, so as to detect the offset at each time step. Specifically: Offset threshold at time i The expression is: In the formula, This indicates the degree of anomaly in the offset of the clamp block at time i; This indicates the preset base offset threshold.
[0057] Based on the offset threshold, it can be understood that if the offset anomaly at the current moment is greater, it indicates that there is strong vibration interference in the current environment. In this case, the safety boundary will be relaxed and the offset threshold will be increased, allowing the clamp to generate a larger offset without triggering an alarm. Conversely, if the offset anomaly at the current moment is smaller, it indicates that the current environment is stable and there is less interference. The safety boundary will be tightened and the offset threshold will be lowered to restore it to or close to a more stringent standard, thereby maintaining high sensitivity to any offset that exceeds the norm, so as to ensure that an alarm can be triggered in a timely and accurate manner when a real fall risk occurs.
[0058] It should be noted that the preset basic offset threshold value is set manually. In this embodiment, the basic offset threshold value is 50mm. This value is an empirical value obtained from a large number of experiments. In actual application, as other implementation methods, implementers can also set it themselves according to specific circumstances. This embodiment does not impose any special restrictions.
[0059] If the current offset is greater than the current offset threshold, the offset is abnormal. The pole climbing and fall prevention device is locked to ensure the safety of the inspection workers and avoid the risk of falling. Otherwise, the offset is normal.
[0060] Preferably, the offset anomaly detection flowchart provided in this embodiment is as follows: Figure 2 As shown.
[0061] Thus, this embodiment generates an offset threshold that can be adaptively adjusted in real time by multiplying the dynamically calculated offset anomaly degree by a preset basic threshold. This threshold automatically widens when there is strong interference to avoid false alarms and automatically tightens when the environment is stable to ensure high sensitivity, thereby realizing intelligent and accurate detection of offset and improving the accuracy of offset detection for power transmission pole climbing anti-fall devices.
[0062] Based on the same inventive concept as the above method, this application embodiment also provides an offset detection system for a power pole climbing anti-fall device, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any one of the above-described offset detection methods for a power pole climbing anti-fall device.
[0063] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, specific embodiments of this specification have been described above. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.
[0064] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.
[0065] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the principles of this application should be included within the protection scope of this application.
Claims
1. A method for detecting the offset of a power transmission pole climbing and fall prevention device, characterized in that, The method includes the following steps: Real-time acquisition of vibration data, displacement, and offset of the clamping blocks on the power transmission pole climbing and fall prevention device; Extract the extreme values from the vibration data of all times within a preset time period before each time. By analyzing the difference between any extreme value and the average level of extreme values, the first and second characteristic times are selected from the preset time period before each time. Analyze the differences in vibration data between each first characteristic time and its adjacent first characteristic time, and between each second characteristic time and its adjacent second characteristic time, to determine the vibration anomaly degree of the clamp at each time. By analyzing the difference between the instantaneous displacement change rate and the instantaneous offset change rate at all times within a preset time period before each time, the difference characteristic value of the clamping block at each time is determined, and combined with the vibration anomaly degree, the offset anomaly degree of the clamping block at each time is determined. Based on the offset anomaly, offset thresholds are determined at each time point to detect the offset at each time point.
2. The method for detecting the offset of a power transmission pole climbing and fall prevention device as described in claim 1, characterized in that, The step of selecting the first and second characteristic moments from a preset time period prior to each moment includes: Within a preset time period before each moment, calculate the mean of all extreme values greater than 0 and the mean of all extreme values less than 0, and record them as the first mean and the second mean, respectively. The time corresponding to the extreme value greater than the first mean is recorded as the first characteristic time, and the time corresponding to the extreme value less than the second mean is recorded as the second characteristic time.
3. The method for detecting the offset of a power transmission pole climbing and fall prevention device as described in claim 1, characterized in that, Determining the vibration anomaly degree of the clamp at each time point includes: Within a preset time period before each moment, the differences in vibration data between each first characteristic moment and its adjacent first characteristic moment, and the differences in vibration data between each second characteristic moment and its adjacent second characteristic moment are analyzed respectively, so as to determine the upper vibration anomaly coefficient and the lower vibration anomaly coefficient of each first characteristic moment, thereby determining the upper vibration anomaly degree and the lower vibration anomaly degree at each moment. The vibration anomaly of the clamping block at each time point is positively correlated with the upper vibration anomaly and the lower vibration anomaly, respectively.
4. The method for detecting the offset of a power transmission pole climbing and fall prevention device as described in claim 3, characterized in that, The determination of the upper vibration anomaly coefficient at each first characteristic time and the lower vibration anomaly coefficient at each second characteristic time includes: The results of calculating the difference ratio of vibration data between each first characteristic moment and its adjacent first characteristic moment to the corresponding time interval, and the results of the difference ratio of vibration data between each second characteristic moment and its adjacent second characteristic moment to the corresponding time interval, are respectively denoted as the upper vibration anomaly coefficient of each first characteristic moment and the lower vibration anomaly coefficient of each second characteristic moment.
5. The method for detecting the offset of a power transmission pole climbing and fall prevention device as described in claim 3, characterized in that, The determination of the upper vibration anomaly degree and the lower vibration anomaly degree at each time point includes: Calculate the mean of the normalized values of the upper vibration anomaly coefficients for all first characteristic moments within a preset time period before each moment, and the mean of the normalized values of the lower vibration anomaly coefficients for all second characteristic moments, and record them as the upper vibration anomaly degree and the lower vibration anomaly degree at each moment, respectively.
6. The method for detecting the offset of a power transmission pole climbing and fall prevention device as described in claim 1, characterized in that, The difference characteristic value of the clamping block at each time point is the DTW distance between the normalized value of the instantaneous displacement change rate at all times within the preset time period before each time point and the normalized value of the instantaneous offset change rate at all times.
7. The method for detecting the offset of a power transmission pole climbing and fall prevention device as described in claim 1, characterized in that, The offset anomaly of the clamping block at each time point is positively correlated with the vibration anomaly and the difference characteristic value, respectively.
8. The method for detecting the offset of a power transmission pole climbing and fall prevention device as described in claim 1, characterized in that, The expression for the offset threshold at each time point is: In the formula, This represents the offset threshold of the clamp block at time i; This indicates the degree of anomaly in the offset at time i; This indicates the preset base offset threshold.
9. The method for detecting the offset of a power transmission pole climbing and fall prevention device as described in claim 1, characterized in that, The detection of the offset at each time point includes: If the offset at the current moment is greater than the offset threshold at the current moment, the offset is abnormal; otherwise, the offset is normal.
10. A system for detecting the offset of a power transmission pole climbing and fall prevention device, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the offset detection method for a power pole climbing anti-fall device as described in any one of claims 1-9.