A steel wire rope real-time online monitoring method and system based on intelligent sensors

Abstract

The application discloses a kind of steel wire rope real-time online monitoring method and system based on intelligent sensor, it is related to steel wire rope monitoring technical field, the method is by setting multiple collection points on steel wire rope path, and combining time synchronization correction, band-pass filtering, tension difference extraction and Z-score standardization etc., establishes the pulsation source effective energy level index Elive capable of reflecting the pulsation energy characteristic of deep-sea giant tuna live body.The peak-peak value P2P is used to construct the pulsation amplitude term, and the standard deviation of real-time tension difference sequence is used to construct the dispersion term, and the ratio of the two is used as the expression structure of the pulsation source effective energy level index, so that the application can significantly improve the identification ability of live body pulsation on steel wire rope tension, and effectively distinguish from sea state disturbance, ship body swing and other pseudo signals.The processing method not only overcomes the defect that the existing technology only relies on single-point tension or RMS index to identify non-uniform pulsation type load.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of steel wire rope monitoring, in particular to a steel wire rope real-time online monitoring method and system based on intelligent sensors. BACKGROUND

[0002] With the continuous development of marine operation equipment, deep-sea scientific research equipment and ocean fishing equipment, the electric winch system as a typical traction and winding mechanism is further widely used in deep-sea fishing gear, marine towing system and ship hoisting equipment and other scenes. With the continuous expansion of the operation scale of deep-sea longline fishing gear, the steel wire rope as the main load-bearing element of the electric winch system needs to bear multiple source changing loads such as sea state disturbance, winch mechanical driving and struggle of large deep-sea tuna live body during operation, among which the non-uniform pulsating stress generated by large deep-sea fish is more instantaneous, sudden and irregular. Therefore, in the operation process of the electric winch of the deep-sea fishing gear, it is urgent to solve the core technical problems of the equipment to realize real-time collection of the dynamic characteristics of the steel wire rope tension, effective identification of the live body pulsation mode, and timely judgment of the possible overload risk.

[0003] At present, in the existing deep-sea fishing equipment, the monitoring of the state of the steel wire rope still mainly relies on single-point tension measurement, winch current monitoring or visual observation, etc., which can only reflect the macro tension change and cannot identify the intermittent, sudden and nonlinear pulsating load caused by the struggle of large deep-sea tuna. The existing monitoring technology cannot distinguish between "live body pulsation signal" and "sea wave disturbance, ship body swing, winch mechanical noise" and other non-operation source noises, so that the monitoring data often appears misjudgment or false alarm in actual use. In addition, the traditional system lacks the detection ability of "local tension difference caused by live body power", cannot identify the tension difference change between the middle section of the steel wire rope and the winch end, cannot judge the energy level of the pulsation signal, and is more difficult to be used for predicting the fatigue risk and overload risk of the steel wire rope. Therefore, the existing technology cannot effectively meet the needs of fine, multi-dimensional and real-time risk identification of the state of the steel wire rope in deep-sea fishing operation.

[0004] The above deficiencies mainly result from the fact that the prior art lacks a model basis for the special load form of "deep-sea biological living body pulsation", does not perform differential analysis on the dynamic tension changes generated by the steel wire rope at different positions, and lacks a real-time judgment mechanism capable of coupling "living body pulsation energy" with "winch instantaneous load state". Since the deep-sea giant tuna generates highly irregular, transient strong impact non-uniform loads when struggling, these loads are directly transmitted to the winch motor through the steel wire rope, which can easily cause abnormal conditions such as instantaneous overload, motor current fluctuation, and rapid accumulation of local fatigue of the steel wire rope. If such pulsation impact is not identified in time, it can lead to serious consequences such as steel wire rope breakage, hook damage, winch overload shutdown, and even winding structure jamming, which not only affects the success rate of fishing, but also can cause safety hazards to equipment and personnel. Therefore, the lack of timely identification and risk assessment of "living body pulsation type load" is a key technical bottleneck in the field of deep-sea fishing tool electric winch. SUMMARY

[0005] In view of the deficiencies of the prior art, the present application provides a steel wire rope real-time online monitoring method and system based on intelligent sensors, which solves the problems mentioned in the background art.

[0006] To achieve the above purpose, the present application is implemented by the following technical solutions:

[0007] S1, a plurality of collection points are arranged on the steel wire rope path of the electric winch, real-time pulsation operation data is collected, and the collected winch operation data is transmitted to the central controller of the electric winch, and the winch operation data is preprocessed in the central controller to obtain original monitoring data;

[0008] S2, based on the original monitoring data, the pulsation source effective energy level index Elive is calculated, the pulsation source effective energy level index Elive is compared with the preset pulsation reference interval threshold value for preliminary evaluation, and the steel wire rope tension pulsation condition is judged;

[0009] S3, when the preliminary evaluation judges that the steel wire rope tension pulsation is abnormal, the winch risk analysis mechanism is triggered at this time, the winch risk analysis mechanism extracts the load data of the winch motor, combines the pulsation source effective energy level index Elive, and calculates the comprehensive risk index Rcomb;

[0010] S4, the risk interval threshold value is compared with the comprehensive risk index Rcomb for secondary comparative evaluation, and a self-adaptive coupling control strategy is executed based on the secondary comparative evaluation result.

[0011] Preferably, the S1 includes S11;

[0012] S11, by setting multiple collection points on the electric winch and the steel wire of the deep-sea fishing gear, and installing corresponding sensors in each collection point, triggering the collection task when the steel wire is extended to 3 meters from the electric winch, collecting the pulsation operation data in real time, and connecting the sensors and the central controller of the electric winch through wireless Bluetooth, and transmitting the real-time collected pulsation operation data to the central controller;

[0013] The collection points include a first tension collection point A, a second tension collection point B, and a load collection point C;

[0014] The first tension collection point A is set at the steel wire guide position at the outlet of the electric winch;

[0015] The second tension collection point B is set at the steel wire middle guide position close to the sea surface but not immersed in seawater;

[0016] The clamping type steel wire tension sensor is used at the first tension collection point A and the second tension collection point B respectively to obtain the first tension TA and the second tension TB in real time, and the first tension TA and the second tension TB at each moment are collected in time sequence to obtain the pulsation operation data;

[0017] The load collection point C is set at the driving end of the electric winch, which is in a default static state, and a current sensor is installed at the motor of the electric winch, and an encoder is installed at the rotating shaft of the electric winch.

[0018] Preferably, the S1 further comprises S12;

[0019] S12, in the central controller, real-time receiving the pulsation operation data, and pre-processing the pulsation operation data to obtain the original monitoring data, the pre-processing including time synchronization correction, noise filtering, real-time tension difference extraction, and standardization processing;

[0020] The original monitoring data includes the real-time tension difference Tdiff sequence of the first tension collection point A and the second tension collection point B at each moment;

[0021] The time synchronization correction aligns all parameters in the pulsation operation data collected by all sensors to the same time axis according to the unified clock maintained in the central controller;

[0022] The noise filtering filters the pulsation operation data after time synchronization correction through the band-pass filter FIR; eliminates the low-frequency drift caused by sea conditions, the medium-frequency noise caused by winch vibration, and the pulse noise caused by motor current jump;

[0023] The real-time tension difference extraction is obtained by calculating the difference between the first tension TA and the second tension TB collected by the first tension collection point A and the second tension collection point B on the same time axis, and outputting the real-time tension difference Tdiff(t) at time t;

[0024] The standardization processing is obtained by using the Z-score standardization method to standardize the real-time tension difference Tdiff(t) at time t, and eliminating the unit dimension influence of the real-time tension difference Tdiff(t) at time t;

[0025] Then, the real-time tension difference Tdiff at each time is integrated according to the time sequence to obtain the real-time tension difference Tdiff sequence.

[0026] Preferably, the S2 comprises S21;

[0027] The S21 extracts the maximum value and the minimum value in the real-time tension difference Tdiff sequence at each time based on the real-time tension difference Tdiff sequence at each time in the original monitoring data, calculates the difference between the maximum value and the minimum value to obtain a pulsation amplitude term, and calculates the standard deviation of the real-time tension difference Tdiff(t) at time t as a dispersion term to output the pulsation source effective energy level index Elive.

[0028] The pulsation source effective energy level index Elive is calculated and output by the following algorithm formula:

[0029] In the formula, T represents the total number of real-time tension differences Tdiff in the collection task triggering time, max(Tdiff(t)) represents the maximum value of the real-time tension difference Tdiff(t) at time t, and min(Tdiff(t)) represents the minimum value of the real-time tension difference Tdiff(t) at time t.

[0030] Preferably, the S2 further comprises S22;

[0031] The S22 sets a pulsation reference interval threshold value by statistically analyzing the real-time tension difference Tdiff sequence in multiple safe fishing operations, and the pulsation reference interval threshold value comprises a normal reference threshold value Elive safe and a suspicious threshold value Elive mid ;

[0032] In the formula, the upper limit value of the pulsation source effective energy level index obtained in the stable mechanical winding state is taken as the normal reference threshold value Elive safe , and the upper limit of the characteristic interval of the pulsation source effective energy level index causing a slight tension abnormality of the steel wire rope but not causing an overload risk in a historical pulsation event is taken as the suspicious threshold value Elivemid And based on the real-time acquisition of the pulsation source effective energy level index Elive and the pulsation reference interval threshold, the steel wire rope tension pulsation is judged;

[0033] Wherein: when the pulsation source effective energy level index Elive≤normal reference threshold Elive safe , it is determined as ordinary fluctuation, at this time the winch continues to work at the present set speed, and does not trigger any protection strategy;

[0034] When the normal reference threshold Elive safe <pulsation source effective energy level index Elive<suspicious threshold Elive mid , it is determined as mild pulsation, at this time the current electric winch speed is reduced by 5%, avoiding sudden tension of the steel wire rope when the pulsation just rises,

[0035] When the pulsation source effective energy level index Elive≥suspicious threshold Elive mid , it is determined as severe pulsation, at this time the winch risk analysis mechanism is triggered.

[0036] Preferably, the S3 comprises S31;

[0037] S31, after triggering the winch risk analysis mechanism again, the load acquisition point C is started, a current sensor is installed at the end of the winch driving motor to obtain the winch motor current IC at each moment in real time, and an encoder is installed on the winch rotating shaft to obtain the winch winding speed VD at each moment in real time;

[0038] And transmit to the central controller, after time synchronization correction, noise filtering and standardization processing, the corresponding moment load data is obtained by integration;

[0039] Wherein, the standardization processing is carried out by adopting the maximum and minimum standardization method according to the maximum motor current of the electric winch and the maximum value of the winch winding speed, to standardize the current winch motor current IC and the winch winding speed VD at each moment, eliminating the influence of unit dimension;

[0040] The load data comprises the winch motor current IC(t) at t moment and the winch winding speed VD(t) at t moment.

[0041] Preferably, the S3 further comprises S32;

[0042] S32, the statistical upper bound of the pulsation source effective energy level index Elive in the historical monitoring window without overload in the history of safe fishing and catching operation is taken as the reference value Eref; the rated maximum continuous working current provided by the winch driving motor manufacturer is taken as the winch rated maximum safe current Imax; and then the load data is combined to calculate the comprehensive risk index Rcomb.

[0043] The comprehensive risk index Rcomb is calculated by the following algorithm formula output;

[0044] ; wherein the reference value Eref and the winch rated maximum safe current Imax are both dimensionless.

[0045] Preferably, the S4 includes S41;

[0046] S41, set risk interval thresholds based on historical comprehensive risk index Rcomb, the risk interval thresholds include risk warning threshold Rwarn and risk shutdown threshold Rstop; and based on the real-time calculation of the comprehensive risk index Rcomb, secondary comparison and evaluation are carried out to judge the load risk situation of the winch motor, and the specific evaluation content is as follows:

[0047] When the comprehensive risk index Rcomb is less than or equal to the risk warning threshold Rwarn, it is determined that the current steel wire rope stress state is in a safe interval;

[0048] When the comprehensive risk index Rwarn is less than the comprehensive risk index Rcomb and the comprehensive risk index Rcomb is less than the risk shutdown threshold Rstop, it is determined that the steel wire rope stress state is in a risk buffer interval;

[0049] When the comprehensive risk index Rcomb is greater than or equal to the risk shutdown threshold Rstop, it is determined that the steel wire rope stress state is in a shutdown risk interval.

[0050] Preferably, the S4 further includes S42;

[0051] S42, based on the judgment of the load wind situation of the winch motor, the corresponding adaptive coupling control strategy is executed, and the specific content is as follows:

[0052] When it is determined that the current steel wire rope stress state is in a safe interval, the winch motor works according to the current winch winding speed VD, continues to monitor, does not intervene, and the central controller updates the comprehensive risk index Rcomb every 100ms, and then executes secondary comparison and evaluation again;

[0053] When it is determined that the steel wire rope stress state is in a risk buffer interval, the winch winding speed VD is dynamically decelerated based on the output value of the current comprehensive risk index Rcomb, and the specific control is as follows:

[0054] When the comprehensive risk index Rcomb exceeds 0%-20% of the risk warning threshold Rwarn, the winding speed is reduced by 3%-6%;

[0055] When the comprehensive risk index Rcomb exceeds 20%-60% of the risk warning threshold Rwarn, the winding speed is reduced by 6%-18%;

[0056] When the comprehensive risk index Rcomb exceeds 40%-100% of the risk warning threshold Rwarn, the winding speed is reduced by 18%-30%;

[0057] When it is determined that the steel wire rope stress state is in the shutdown risk interval, the central controller controls the winch motor to issue a dangerous pulsation warning, and when the comprehensive risk index Rcomb is greater than the risk shutdown threshold Rstop for 1 second, the winding is automatically paused.

[0058] A steel wire rope real-time online monitoring system based on intelligent sensors, comprising a central collection module, a pulsation effective analysis module, a winch risk analysis module and a self-adaptive coupling control module.

[0059] The central collection module collects pulsation operation data in real time by setting multiple collection points on the steel wire rope path of the electric winch, and transmits the collected winch operation data to the central controller of the electric winch, and preprocesses the winch operation data in the central controller to obtain original monitoring data.

[0060] The pulsation effective analysis module calculates the pulsation source effective energy level index Elive based on the original monitoring data, preliminarily evaluates according to the pulsation source effective energy level index Elive and the preset pulsation reference interval threshold, and judges the steel wire rope tension pulsation condition.

[0061] When the winch risk analysis module preliminarily evaluates that the steel wire rope tension pulsation is abnormal, the winch risk analysis mechanism is triggered, which extracts the load data of the winch motor and combines the pulsation source effective energy level index Elive to calculate the comprehensive risk index Rcomb.

[0062] The self-adaptive coupling control module compares and evaluates the risk interval threshold and the comprehensive risk index Rcomb twice, and executes the self-adaptive coupling control strategy based on the secondary comparison and evaluation result.

[0063] The present application provides a kind of steel wire rope real-time online monitoring method and system based on intelligent sensors. With the following beneficial effects:

[0064] (1) The method sets multiple collection points on the steel wire rope path, and combines time synchronization correction, band pass filtering, tension difference extraction and Z-score standardization and other preprocessing methods to establish an effective energy level index Elive of the pulsation source which can reflect the characteristics of the deep-sea giant tuna live pulsation energy. By using the peak-to-peak value P2P to construct the pulsation amplitude term, and using the standard deviation of the real-time tension difference sequence to construct the dispersion term, and taking the ratio of the two as the expression structure of the effective energy level index of the pulsation source, the present application can significantly improve the recognition ability of the live pulsation to the steel wire rope tension, and realize the effective differentiation from the sea state disturbance, ship body swing, winch structure vibration and other pseudo signals. This processing method not only overcomes the defect that the existing technology only relies on single-point tension or RMS index to identify non-uniform pulsation type load, but also can accurately capture the transient impact energy change of live pulsation, so as to realize real-time, accurate and low-misjudgment identification of the steel wire rope tension pulsation state.

[0065] (2) The method introduces the winch motor load data obtained by the current sensor and the encoder on the basis of the effective energy level index Elive of the pulsation source, and constructs a comprehensive risk index Rcomb based on the improved Euclidean distance model, so that the steel wire rope stress state can be constrained and evaluated in two dimensions of “live pulsation energy” and “winch driving force state”. The present application integrates Elive and the normalized winch motor current IC, so that the load source coupling relationship not considered in traditional steel wire rope monitoring is quantitatively expressed. Relying on the partition judgment of risk warning threshold Rwarn and risk shutdown threshold Rstop, the present application can dynamically execute different levels of adaptive coupling control strategies such as speed reduction regulation, intermittent winding and fatigue suppression according to the change of the comprehensive risk index Rcomb, so as to effectively reduce the instantaneous impact, reduce the winch overload risk and inhibit the steel wire rope fatigue accumulation, and significantly improve the operation safety and control intelligent level of the deep-sea fishing reel electric winch.

[0066] (3) The method dynamically links the effective energy level index Elive of the pulsation source with the comprehensive risk index Rcomb. When the steel wire rope has a severe living pulsation, the load risk analysis mechanism is triggered in real time, so that the application can not only identify the real source of the non-uniform pulsation type load of the deep-sea giant tuna, but also perform coupled risk assessment based on the pulsation intensity, winch load, motor current change and other multi-dimensional data, and immediately execute the adaptive coupling control strategy of the corresponding level. Through this "coordinated chain of identifying living power first, then coupling load analysis to finally executing control", a real-time dynamic safety management and control system that cannot be realized by traditional technology is formed. Compared with the existing fishing tackle system which relies on single-point tension alarm or fixed deceleration strategy, the application can intervene in time before the impact caused by the explosive struggle of the fish body is transmitted to the winch, thereby fundamentally reducing the probability of high-risk events such as instantaneous rupture of the steel wire rope, overload of the winch, and jamming of the winding structure, and greatly improving the success rate of deep-sea fishing operations and the service life of the equipment. BRIEF DESCRIPTION OF DRAWINGS

[0067] Figure 1 A step schematic diagram of the steel wire rope real-time online monitoring method based on the intelligent sensor is provided.

[0068] Figure 2 A flowchart of the steel wire rope real-time online monitoring system based on the intelligent sensor is provided.

[0069] Figure 3 A diagram of the acquisition point and the hardware structure. DETAILED DESCRIPTION

[0070] The technical solutions in the embodiments of the application will be described clearly and completely below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, rather than all the embodiments. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the application.

[0071] Embodiment 1

[0072] Please refer to Figure 1 The application provides a steel wire rope real-time online monitoring method based on an intelligent sensor. To achieve the above object, the application is implemented by the following technical solutions: comprising the following steps:

[0073] S1, multiple acquisition points are arranged on the steel wire rope path of the electric winch, living pulsation data is collected in real time, the collected winch operation data is transmitted to the central controller of the electric winch, and the winch operation data is preprocessed in the central controller to obtain original monitoring data.

[0074] S2, based on the original monitoring data, the pulsation source effective energy level index Elive is calculated, and the pulsation source effective energy level index Elive is preliminarily evaluated according to a preset pulsation reference interval threshold value, and it is judged whether the steel wire rope tension pulsation is abnormal;

[0075] S3, when the preliminary evaluation judges that the steel wire rope tension pulsation is abnormal, the winch risk analysis mechanism is triggered at this time, the winch risk analysis mechanism extracts the load data of the winch motor, combines the pulsation source effective energy level index Elive, and calculates the comprehensive risk index Rcomb;

[0076] S4, the risk interval threshold value is set and compared with the comprehensive risk index Rcomb for secondary comparative evaluation, and an adaptive coupling control strategy is executed based on the secondary comparative evaluation result.

[0077] In this embodiment, the method synchronously obtains the real propagation of the deep-sea fish body tension at different positions by setting multiple collection points on the steel wire rope path and collecting the pulsation operation data in real time, so as to timely identify the non-uniform pulsation type stress caused by the instantaneous struggle of the deep-sea giant tuna. If only relying on the single point tension of the steel wire rope, the sea wave, the ship body swing or the winch itself vibration is easily misjudged as the fish body pulsation, resulting in the risk of false intervention or missed judgment, so the multi-point collection and real-time transmission is to obtain the dynamic parameters closest to the real force source. Based on the pre-processed original monitoring data, the pulsation source effective energy level index Elive is calculated, which can directly quantify the energy effectiveness of the fish body pulsation. This is because the pulsation of deep-sea fish has the typical peak impact characteristic, and the ordinary sea state disturbance often has low amplitude and high dispersion. If the joint analysis of peak-to-peak value and standard deviation is not performed, the real pulsation and background noise cannot be distinguished. The role of the index lies in identifying the rapid rise of the pulsation intensity in advance, so as to avoid the initial energy impact on the steel wire rope without protection. When the pulsation source effective energy level index Elive reaches an abnormal state, the winch risk analysis mechanism is triggered, and the integrated risk index Rcomb is calculated by coupling the winch motor load data and Elive. The reason why the motor load must be introduced when the pulsation is abnormal is that only the pulsation intensity is not enough to represent the risk of rupture; the real cause of the steel wire rope rupture is the superposition effect of the simultaneous rise of “pulsation energy” and “winch driving force”. If the coupling analysis is not performed, the situation that the pulsation is mild but the winch is overloaded, or the pulsation is severe but the winch load is normal, may occur, resulting in false triggering of the control strategy. The present embodiment realizes stronger protection when the two risk sources rise simultaneously through Rcomb, and the physical meaning is to judge whether the system enters a dangerous composite stress state. Finally, the system compares and evaluates the integrated risk index Rcomb and the risk interval threshold value again, and executes the corresponding adaptive coupling control strategy, so as to ensure that the steel wire rope obtains the most suitable protection measures in different risk intervals. For example, when Rcomb just exceeds the warning threshold value, only light deceleration is performed to weaken the initial pulsation energy; and when approaching the shutdown threshold value, significant speed reduction and intermittent winding are performed, so that the steel wire rope has “buffering” capability, avoiding the instantaneous impact directly transmitted to the winch inside. The reason for such setting is that the explosive struggle of the deep-sea giant tuna belongs to millisecond, nonlinear impact, and if the system still winds at a fixed speed, the instantaneous stress of the steel wire rope may jump to the rupture interval. Through the above implementation process, the present application can capture the real pulsation source in the initial stage of the pulsation, and perform coupling analysis on the pulsation and the winch load, and then implement different degrees of speed adjustment and buffering actions according to the risk level. The final effects include: reducing the instantaneous impact peak value of the steel wire rope, improving the overload resistance of the winch, reducing the fatigue accumulation speed of the steel wire rope, significantly reducing the risk of rope breaking, jamming and equipment overload, and improving the overall safety and success rate of deep-sea fishing operations.

[0078] Embodiment 2

[0079] Please refer to Figure 1 and Figure 3 Specifically, S1 includes S11;

[0080] S11, by setting multiple collection points on the electric winch and the steel wire of the deep-sea fishing gear, and installing corresponding sensors in each collection point, triggering the collection task when the steel wire is extended to 3 meters from the electric winch, collecting the pulsation operation data in real time, and connecting the sensors and the central controller of the electric winch through wireless Bluetooth, and transmitting the real-time collected pulsation operation data to the central controller;

[0081] The collection points include a first tension collection point A, a second tension collection point B, and a load collection point C;

[0082] The first tension collection point A is set at the steel wire guide position at the outlet of the electric winch;

[0083] The second tension collection point B is set at the steel wire middle guide position close to the sea surface but not immersed in seawater;

[0084] A clamping type steel wire tension sensor is used at the first tension collection point A and the second tension collection point B respectively to obtain the first tension TA and the second tension TB in real time, and the first tension TA and the second tension TB at each moment are collected in time sequence to obtain the pulsation operation data;

[0085] The load collection point C is set at the driving end of the electric winch, which is in a default state of rest, and a current sensor is installed at the motor of the electric winch, and an encoder is installed at the rotating shaft of the electric winch.

[0086] S1 also includes S12;

[0087] S12, in the central controller, real-time receiving the pulsation operation data, and preprocessing the pulsation operation data to obtain the original monitoring data, the preprocessing including time synchronization correction, noise filtering, real-time tension difference extraction, and standardization processing;

[0088] The original monitoring data include the real-time tension difference Tdiff sequence of the first tension collection point A and the second tension collection point B at each moment;

[0089] The time synchronization correction aligns all the timestamps of all parameters in the pulsation operation data collected by all sensors to the same time axis according to the unified clock maintained in the central controller;

[0090] The noise filtering filters the pulsation operation data after time synchronization correction through a band-pass filter FIR, eliminates low-frequency drift caused by sea conditions, medium-frequency noise caused by winch vibration, and pulse noise caused by motor current jump;

[0091] The real-time tension difference extraction calculates the difference between the first tension TA and the second tension TB collected by the first tension collection point A and the second tension collection point B on the same time axis, and outputs the real-time tension difference Tdiff(t) at time t;

[0092] The standardization processing uses the Z-score standardization method to standardize the real-time tension difference Tdiff(t) at time t, eliminating the unit dimension influence of the real-time tension difference Tdiff(t) at time t;

[0093] Then, the real-time tension difference Tdiff at each time is integrated according to the time sequence to obtain the real-time tension difference Tdiff sequence.

[0094] In this embodiment, the method is to set the first tension acquisition point A and the second tension acquisition point B at the electric winch outlet position and the middle section of the steel wire rope respectively, the purpose is to obtain the real difference characteristics of the fish body pulsation transmitted along the steel wire rope. If only a single point acquisition is set at the winch end, the sea waves, ship body sway and winch mechanical vibration will be mixed with the fish body pulsation, which makes the system unable to judge the real force source, and through the "distance difference" formed by the two acquisition points several meters apart, the propagation attenuation of the live body pulsation at different positions of the steel wire rope can be directly reflected, which physically isolates the background disturbance signal. This structural design can avoid the common problems in traditional systems such as "mistaking sea conditions as pulsation" or "triggering false alarm due to vibration noise". Each acquisition point keeps real-time communication with the central controller through wireless Bluetooth, so that the pulsation running data is sent to the control end in milliseconds, but the significance of this is not only in transmission, but also in starting acquisition after a 3-meter extension condition is triggered. This is because the initial impact of deep-sea giant tuna often occurs after the fish hook sinks a certain distance, if data is collected when the steel wire rope just leaves the winch, the transient noise and starting jitter of the system will be included in the analysis, which will damage the identification accuracy, therefore, setting the trigger distance can avoid false acquisition of system disturbance. The reason why the preprocessing step in the central controller must include time synchronization correction, band-pass filtering and Z-score standardization is that multi-point data is not naturally comparable. For example, if there is a tens of milliseconds offset in the time stamp of two sensors, it will directly lead to "misplaced signal" in the scene of deep-sea fish with burst peak value pulsation, making the tension difference Tdiff calculated by the system appear false fluctuation. By unifying the time axis, it can be ensured that the data of each sensor belongs to the same physical time. Band-pass filtering is used to eliminate the low-frequency fluctuations caused by sea conditions, the middle-frequency noise caused by winch structure vibration, and the pulse interference caused by motor jump, otherwise these noises will be mistaken for pulsation peaks, directly amplifying the risk of misjudgment. The role of Z-score standardization is to unify the values of different sensors and different sampling times into dimensionless parameters, so that the subsequent calculation of tension difference sequence Tdiff is not affected by the absolute value scale, and only reflects "pulsation strength itself". Through the above steps, the present embodiment realizes a key effect: separating the deep-sea live body pulsation from the complex marine environment noise and forming a high-quality real-time tension difference sequence that can be used for subsequent energy level judgment. This not only avoids the false trigger caused by noise in traditional systems, but also ensures that the pulsation analysis is based on reliable data, providing the necessary physical reality and signal stability for subsequent pulsation energy calculation and risk index analysis, thereby significantly improving the accuracy and reliability of the steel wire rope online monitoring.

[0095] Embodiment 3

[0096] See Figure 1 , specifically: S2 includes S21;

[0097] S21, based on the real-time tension difference Tdiff sequence at each time in the original monitoring data, the maximum value and the minimum value in the real-time tension difference Tdiff sequence at each time are extracted for difference calculation, the pulsation amplitude term is obtained, and the standard deviation of the real-time tension difference Tdiff (t) at the t time is taken as the dispersion term, the pulsation source effective energy level index Elive is calculated and output, and the significant degree and energy effectiveness of the deep-sea giant tuna live pulsation propagation in the steel wire rope are quantitatively analyzed;

[0098] The pulsation source effective energy level index Elive is calculated and output by the following algorithm formula;

[0099] In the formula, T represents the total number of real-time tension differences Tdiff in the collection task triggering time, max(Tdiff(t)) represents the maximum value of the real-time tension difference Tdiff (t) at the t time, and min(Tdiff(t)) represents the minimum value of the real-time tension difference Tdiff (t) at the t time;

[0100] The numerator of the formula represents the pulsation amplitude term, and the denominator represents the dispersion term;

[0101] The pulsation amplitude term is derived from the commonly used “peak-to-peak value (P2P)” concept in the fields of physics and signal processing, and is used to: describe the instantaneous intensity of the signal and reflect the maximum energy of the vibration or disturbance;

[0102] The dispersion term is derived from classical statistics, and is used to measure the dispersion degree of data. The standard deviation is used to describe: the fluctuation strength, data stability and vibration uniformity;

[0103] The reason for taking the ratio is that if only the peak-to-peak value is taken, the “sea wave + mast swing” may be misjudged as a pulsation signal

[0104] If only the standard deviation is taken: the peak impact characteristics of the pulsation cannot be captured;

[0105] Therefore, the physical meaning given by the ratio is: the numerator is large, and the denominator is moderate, so that the strong pulsation (real signal) is amplified; the numerator is small, and the denominator is large, so that the noise (pseudo signal) is greatly suppressed.

[0106] S2 also includes S22;

[0107] S22, by statistically analyzing the real-time tension difference Tdiff sequence in the multiple safe fishing and catching operations, a pulsation reference interval threshold is set, and the pulsation reference interval threshold includes a normal reference threshold Elive safe and a suspicious threshold Elive mid ;

[0108] Wherein: the upper limit value of the pulsation source effective energy level index obtained in the stable mechanical winding state is taken as the normal reference threshold Elive safe The upper limit of the characteristic interval of the pulsation source effective energy level index that causes a slight tension abnormality of the steel wire rope in the historical pulsation event but does not cause an overload risk is taken as the suspicious threshold Elive mid And based on the real-time obtained pulsation source effective energy level index Elive and the pulsation reference interval threshold, the steel wire rope tension pulsation condition is judged;

[0109] Wherein: when the pulsation source effective energy level index Elive≤ normal reference threshold Elive safe , it is determined as ordinary fluctuation, indicating that the disturbance of the input of the winch by the sea conditions and the hull swing is weak, at this time the winch continues to work at the present set speed, and any protection strategy is not triggered;

[0110] When the normal reference threshold Elive safe < pulsation source effective energy level index Elive< suspicious threshold Elive mid , it is determined as slight pulsation, indicating that the pulsation energy has not reached a dangerous level, it is the initial or medium stage of the tuna struggle, the steel wire rope load appears slight fluctuation, and it is not yet to cause fatigue accumulation acceleration or risk of rope breaking, at this time the current electric winch speed is reduced by 5%, avoiding that the steel wire rope is subjected to sudden pull-up when the pulsation just rises;

[0111] When the pulsation source effective energy level index Elive≥ suspicious threshold Elive mid , it is determined as severe pulsation, at this time the winch risk analysis mechanism is triggered, indicating that the fish body is in explosive struggle, the steel wire rope stiffness cannot completely absorb the impact, and the driving system of the winch bears severe short-time load, which is easy to lead to: steel wire rope breaking, hook damage, winch overload, winding structure jamming.

[0112] In this embodiment, the method extracts the peak-to-peak value and calculates the standard deviation of the real-time tension difference Tdiff at each time point, with the purpose of identifying the instantaneous impact strength of the deep-sea giant tuna live body from the overall tension change. If only the original tension sequence is used to judge the force on the steel wire rope, the sea wave disturbance, ship body swing and winch vibration will often produce similar amplitude fluctuations in the low frequency band, which is easy to misjudge. The peak-to-peak value can accurately reflect the maximum instantaneous energy of the pulsation, and the standard deviation is used to measure whether the energy belongs to the persistent disturbance, and the two are combined to form the pulsation source effective energy level index Elive. Its true physical meaning is: the more obvious the live pulsation, the larger the peak-to-peak value and the more reasonable the dispersion, so that the ratio increases significantly; the stronger the noise, the larger the dispersion, which reduces the ratio, thereby filtering out false signals. Therefore, this index enables the system to distinguish between "real fish pulsation" and "background noise disturbance" at a millisecond level of accuracy. Further, by statistically analyzing Elive in multiple safe fishing operations, set the normal reference threshold Elive safe and the suspicious threshold Elive mid , the purpose is to establish a quantifiable risk classification for pulsations of different intensities. Without threshold reference, the system cannot determine whether the pulsation is in the initial disturbance, mild struggle or explosive impact stage. For example, deep-sea tuna will produce tension waveforms with smaller amplitude but higher frequency in the early struggle stage. If the system does not distinguish, it will frequently trigger intervention in a risk-free state, reducing operation efficiency. Through threshold classification, the system can distinguish between ordinary sea state fluctuations, mild pulsation and severe pulsation, so that the control logic has a clear boundary. Finally, by comparing the threshold value with Elive in real time, this embodiment can reduce the winch speed in the early stage of pulsation, avoid the sudden tightening of the steel wire rope before the pulsation energy is fully released, and thus avoid stress concentration caused by instantaneous tension increase; when Elive reaches the threshold of severe pulsation, the risk analysis mechanism is triggered, which can prevent explosive impact from being directly transmitted to the winch motor and prevent the steel wire rope from breaking, the hook from being damaged or the winding structure from being stuck due to short-time high load. Through the above implementation, the present application realizes a core effect: early identification of deep-sea live body pulsation, early reduction of impact energy, and early blocking of overload risk formation. Compared with the traditional method of only monitoring tension or current, the present application significantly improves the accuracy, sensitivity and real-time response capability of dynamic safety monitoring of the steel wire rope.

[0113] Embodiment 4

[0114] Please refer to Figure 1 , specifically: S3 includes S31;

[0115] S31, after triggering the winch risk analysis mechanism again, start the load collection point C, install a current sensor at the end of the winch drive motor to obtain the winch motor current IC at each moment in real time, and install an encoder on the winch shaft to obtain the winch winding speed VD at each moment in real time;

[0116] And transmit to the central controller, after time synchronization correction, noise filtering and standardization processing, integrate to obtain the load data at the corresponding moment;

[0117] Among them, the standardization processing is to standardize the current winch motor current IC and winch winding speed VD at each moment by using the maximum minimum standardization method according to the maximum motor current of the electric winch and the maximum value of the winch winding speed, eliminating the influence of unit dimension;

[0118] The load data includes the winch motor current IC(t) at time t and the winch winding speed VD(t) at time t.

[0119] S3 also includes S32;

[0120] S32, based on the statistical upper bound of the effective energy level index Elive of the pulsating source in the historical monitoring window in which no overload occurred in the historical safe fishing operation as the reference value Eref; taking the rated maximum continuous working current provided by the winch drive motor manufacturer as the rated maximum safe current Imax of the winch; and combining the load data, calculating the output comprehensive risk index Rcomb;

[0121] The comprehensive risk index Rcomb is calculated by the following algorithm formula;

[0122] ; wherein the reference value Eref and the rated maximum safe current Imax of the winch are both dimensionless;

[0123] The formula is derived from the Euclidean distance model in multi-factor risk evaluation, which is widely used in engineering safety index, multi-variable quantitative evaluation, mechanical load comprehensive evaluation and statistical distance measurement; this formula is not simply using the Euclidean distance, but has two key innovations, the traditional steel wire rope monitoring only detects: tension, peak tension and tension RMS, and never evaluates the living pulsating source energy level Elive and the winch instantaneous current IC(t) jointly, this application first proposes the coupling risk model of the two;

[0124] Dimension consistency analysis, real-time tension difference Tdiff is a dimensionless parameter, so the pulsating source effective energy level index Elive is a dimensionless parameter, the winch motor current IC is also a dimensionless parameter after standardization processing, so the comprehensive risk index Rcomb is a dimensionless parameter.

[0125] In this embodiment, the method starts the load acquisition point C after triggering the winch risk analysis mechanism, and the core purpose is to master the real load change of the winch motor side in real time. If the system only monitors the steel wire rope tension without introducing the motor current IC(t) and the winding speed VD(t), it cannot identify whether the winch has entered the high load working interval. For example, when a deep-sea giant tuna struggles violently, although the tension of the steel wire rope can reflect the external impact, the load increase inside the winch motor is also an important factor leading to overload or jamming, so it is necessary to synchronously collect this part of data at the first time when the struggle anomaly occurs.

[0126] After transmitting the winch motor current and winding speed to the central controller, time synchronization correction and noise filtering are performed to eliminate the pulse noise caused by motor magnetic field change, driver commutation jump and shaft micro-vibration. If this process is not performed, a large amount of high-frequency disturbance of non-load origin will be mixed in the current sequence, causing the system to mistakenly believe that the winch load has increased sharply, and then triggering the false protection strategy. The purpose of the maximum and minimum normalization process is to convert physical parameters of different dimensions and different ranges into dimensionless evaluation values, so that subsequent coupling calculation with the live struggle source effective energy level index Elive has a unified scale, ensuring the stability and comparability of the risk index model. On this basis, by taking the monitoring window in which no overload occurs in the historical safe fishing operation as the reference value Eref, and taking the rated maximum motor current provided by the manufacturer as the rated maximum safe current Imax of the winch, a set of real, stable and industrially meaningful risk benchmarks can be formed. If the historical window data and the upper limit of the rated current are not introduced, the system will lack the boundary awareness of "normal load" and "dangerous load", and thus cannot accurately identify the rising trend of the compound risk. For example, when the peak value of deep-sea fish struggle is large but the winch motor is still in a light load state, it does not belong to the overload risk, while when the struggle is moderate but the motor current has reached the rated limit, it is easy to cause motor damage. By introducing Eref and Imax for dimensionless fusion, the "double load relationship" in the real physical situation can be restored mathematically. Finally, through the comprehensive risk index Rcomb constructed based on the Euclidean distance model, the present embodiment can realize the synchronous evaluation of "struggle intensity + winch load", avoiding the misjudgment or omission caused by the traditional system only focusing on any single dimension. Its real physical meaning is that only when the fish struggle energy and the winch load increase simultaneously, the steel wire rope is really in a high fracture risk interval, so it must be judged by the compound index. This implementation process enables the system to take deceleration, buffering or shutdown measures in time before the overload risk is formed, effectively avoiding the sudden rupture of the steel wire rope, the damage of the hook and the jamming of the winding structure, thereby significantly improving the overall safety and equipment life of deep-sea fishing operations.

[0127] Embodiment 5

[0128] Please refer toFigure 1 Specifically, S4 includes S41;

[0129] S41, setting a risk interval threshold based on the historical comprehensive risk index Rcomb, the risk interval threshold including a risk warning threshold Rwarn and a risk shutdown threshold Rstop; wherein: taking the upper limit of the stable interval of the historical comprehensive risk index Rcomb as the risk warning threshold Rwarn, and taking the statistical lower limit of the comprehensive risk index Rcomb corresponding to the occurrence of the steel wire rope high load impact or the winch motor current sharp rise event as the risk shutdown threshold Rstop; and based on the real-time calculated comprehensive risk index Rcomb, a secondary comparative evaluation is performed to judge the load risk situation of the winch motor, and the specific evaluation content is as follows:

[0130] When the comprehensive risk index Rcomb is less than or equal to the risk warning threshold Rwarn, it is determined that the current steel wire rope stress state is in a safe interval;

[0131] When the comprehensive risk index Rwarn is less than the comprehensive risk index Rcomb and the comprehensive risk index Rcomb is less than the risk shutdown threshold Rstop, it is determined that the steel wire rope stress state is in a risk buffer interval;

[0132] When the comprehensive risk index Rcomb is greater than or equal to the risk shutdown threshold Rstop, it is determined that the steel wire rope stress state is in a shutdown risk interval.

[0133] S4 also includes S42;

[0134] S42, based on the judgment of the load risk situation of the winch motor, a corresponding adaptive coupling control strategy is executed, and the specific content is as follows:

[0135] When it is determined that the current steel wire rope stress state is in a safe interval, the winch motor works at the current winch winding speed VD, continues to monitor, and does not intervene, and the central controller updates the comprehensive risk index Rcomb every 100ms, and then performs a secondary comparative evaluation;

[0136] When it is determined that the steel wire rope stress state is in a risk buffer interval, the winch winding speed VD is dynamically controlled based on the output value of the current comprehensive risk index Rcomb, and the specific control is as follows:

[0137] When the comprehensive risk index Rcomb exceeds 0%-20% of the risk warning threshold Rwarn, the winding speed is reduced by 3%-6%;

[0138] When the comprehensive risk index Rcomb exceeds 20%-60% of the risk warning threshold Rwarn, the winding speed is reduced by 6%-18%;

[0139] When the comprehensive risk index Rcomb exceeds 40%-100% of the risk warning threshold Rwarn, the winding speed is reduced by 18%-30%;

[0140] The upper limit of 30% reduction is based on not affecting the normal power output of the winch, and can significantly improve the transient impact absorption capacity;

[0141] When it is determined that the steel wire rope stress state is in the shutdown risk interval, the winch motor is controlled by the central controller to issue a dangerous pulsation warning, and when the comprehensive risk index Rcomb is greater than the risk shutdown threshold Rstop for 1 second, the winding is automatically paused.

[0142] In this embodiment, the method performs statistical analysis on the historical comprehensive risk index Rcomb and sets risk warning threshold Rwarn and risk shutdown threshold Rstop, the purpose of which is to establish clear risk level boundaries for the winch operation. Without these two thresholds, the system cannot determine whether the current risk is in the "controllable fluctuation" or "close to the risk of rope breakage". For example, before the deep-sea tuna struggles fiercely, it usually appears a short but increasing frequency of tension fluctuations, if this stage is not identified in advance, the winch is still running at high speed, and the subsequent explosive impact will be superimposed on the steel wire rope in an instant, which can easily lead to accelerated fatigue accumulation or instantaneous rupture. Therefore, Rwarn is used to discover the rising trend of risk in advance, and Rstop is used to identify the dangerous state that makes the steel wire rope enter the limit stress interval. Based on the real-time calculation of the comprehensive risk index Rcomb, secondary comparison and evaluation are performed, in order to execute completely different control strategies under different risk levels, so as to ensure that the intervention action is neither delayed nor excessive. When Rcomb is lower than Rwarn, no intervention is performed, in order to ensure the operation efficiency and prevent the winch from being frequently slowed down due to slight sea state disturbance; when Rcomb falls into the buffer interval, dynamic speed reduction is started, in order to reduce the impact energy transmission when the struggle begins to strengthen, so that the steel wire rope has a "force relief window" to avoid direct tensioning leading to stress concentration; and when Rcomb reaches Rstop, the winch is immediately shut down, in order to block the superimposed risk of "struggle energy + winch load" from continuing to rise, and prevent the steel wire rope from entering the critical stress state that will be broken. In the adaptive coupling control strategy, by performing hierarchical correspondence between "the percentage of Rcomb exceeding Rwarn" and "the reduction percentage of the winch winding speed", a linear adjustment method of "the higher the risk, the stronger the control" can be realized. For example, when the percentage exceeding Rwarn is still in a small range, the speed is only reduced by 3%-6%, in order to maintain sufficient power and avoid false triggering of protection; and when the exceeding percentage is as high as 80%-100%, the speed is reduced to 70%-82% of the original, which can greatly weaken the struggle impact. This design can avoid the situation that the winch winding is instantaneously stressed multiple times due to the explosive struggle of deep-sea fish, thereby effectively avoiding the rupture accident caused by the stress peak of the steel wire rope. Finally, through this implementation, the system can make the winch respond with different intensities at different risk stages: maintain efficiency in the safe zone, actively absorb impact in the buffer zone, and immediately cut off power in the shutdown zone. The real physical meaning of this process is that the explosive struggle of the living body, which is originally difficult to predict, is transformed into a controllable, adjustable, and preventable stress state through quantization, thresholding, and hierarchical response mechanism. Compared with the traditional method of "seeing the exception and then passively shutting down", this implementation significantly improves the impact suppression capability of the steel wire rope, the overload protection capability of the winch, and the safety and reliability of the overall deep-sea fishing operation.

[0143] Embodiment 6

[0144] See Figure 1 andFigure 2 A steel wire rope real-time online monitoring system based on intelligent sensors, comprising a central collection module, a pulsation effective analysis module, a winch risk analysis module and a self-adaptive coupling control module;

[0145] The central collection module collects pulsation operation data in real time by setting multiple collection points on the steel wire rope path of the electric winch, and transmits the collected winch operation data to the central controller of the electric winch, and preprocesses the winch operation data in the central controller to obtain original monitoring data;

[0146] The pulsation effective analysis module calculates the pulsation source effective energy level index Elive based on the original monitoring data, preliminarily evaluates the pulsation source effective energy level index Elive and the preset pulsation reference interval threshold, and judges the steel wire rope tension pulsation condition;

[0147] When the winch risk analysis module judges that the steel wire rope tension pulsation is abnormal, the winch risk analysis mechanism is triggered, the winch risk analysis mechanism extracts the load data of the winch motor, combines the pulsation source effective energy level index Elive, and calculates the comprehensive risk index Rcomb;

[0148] The self-adaptive coupling control module compares and evaluates the risk interval threshold and the comprehensive risk index Rcomb again, and executes the self-adaptive coupling control strategy based on the comparison and evaluation result.

[0149] Although the embodiments of the present application have been shown and described, it can be understood by those skilled in the art that various changes, modifications, replacements and variations can be made to the embodiments without departing from the principles and spirits of the present application.

Claims

1. A method for real-time online monitoring of steel wire ropes based on intelligent sensors, characterized in that: Includes the following steps: S1. Set up multiple collection points on the wire rope path of the electric winch to collect pulsation operation data in real time, and transmit the collected winch operation data to the central controller of the electric winch. The central controller preprocesses the winch operation data to obtain the raw monitoring data. S2. Based on the original monitoring data, calculate the effective energy level index Elive of the pulsation source. Based on the effective energy level index Elive of the pulsation source and the preset pulsation reference interval threshold, conduct a preliminary assessment to determine the tension pulsation of the wire rope. S1 includes S11; S11. By setting multiple collection points on the electric winch and steel wire rope of the deep-sea fishing tackle, and installing corresponding sensors at each collection point, the collection task is triggered when the steel wire rope extends from the electric winch to 3 meters, the pulsation operation data is collected in real time, and the sensors are wirelessly connected to the central controller of the electric winch via Bluetooth, and the real-time collected pulsation operation data is transmitted to the central controller. The acquisition points include a first tension acquisition point A, a second tension acquisition point B, and a load acquisition point C; The first tension acquisition point A is located at the wire rope guide position set at the outlet of the electric winch; The second tension acquisition point B is positioned at a guide position in the middle of a steel wire rope that is close to the sea surface but not submerged in seawater; Clamped wire rope tension sensors are used at the first tension acquisition point A and the second tension acquisition point B to acquire the first tension TA and the second tension TB in real time. The first tension TA and the second tension TB at each moment are summarized according to the time series to obtain pulsation operation data. The load acquisition point C is set at the drive end of the electric winch, and is in a stationary state by default. A current sensor is installed at the motor of the electric winch, and an encoder is installed at the shaft of the electric winch. S3. When the initial assessment determines that the wire rope tension pulsation is abnormal, the winch risk analysis mechanism is triggered. The winch risk analysis mechanism calculates the comprehensive risk index Rcomb by extracting the load data of the winch motor and combining it with the effective energy level index Elive of the pulsation source. S4. A secondary comparative evaluation is conducted by setting a risk interval threshold and the comprehensive risk index Rcomb, and an adaptive coupling control strategy is executed based on the results of the secondary comparative evaluation.

2. The method for real-time online monitoring of steel wire rope based on intelligent sensors according to claim 1, characterized in that: S1 further includes S12; S12. In the central controller, pulsation operation data is received in real time, and the pulsation operation data is preprocessed to obtain raw monitoring data. The preprocessing includes time synchronization correction, noise filtering, real-time tension difference extraction and standardization processing. The original monitoring data includes the real-time tension difference Tdiff sequence of the first tension acquisition point A and the second tension acquisition point B at each moment. The time synchronization correction is achieved by aligning the timestamps of all parameters in the pulsation data collected by all sensors to the same time axis, based on a unified clock maintained inside the central controller. The noise filtering process uses a bandpass filter (FIR) to filter the time-synchronized and corrected pulsation data. Eliminate low-frequency drift caused by sea conditions, medium-frequency noise caused by winch vibration, and pulse noise caused by motor current fluctuations; The real-time tension difference extraction is achieved by calculating the difference between the first tension TA and the second tension TB collected from the first tension acquisition point A and the second tension acquisition point B on the same time axis, and outputting the real-time tension difference Tdiff(t) at time t. The standardization process uses the Z-score standardization method to standardize the real-time tension difference Tdiff(t) at time t, thereby eliminating the influence of the unit dimension of the real-time tension difference Tdiff(t) at time t. Then, the real-time tension difference Tdiff at each moment is integrated according to the time series to obtain the real-time tension difference Tdiff sequence.

3. The method for real-time online monitoring of steel wire rope based on intelligent sensors according to claim 2, characterized in that: S2 includes S21; S21. Based on the real-time tension difference Tdiff sequence at each moment in the original monitoring data, extract the maximum and minimum values ​​in the real-time tension difference Tdiff sequence at each moment to calculate the difference, obtain the pulsation amplitude term, and use the standard deviation of the real-time tension difference Tdiff(t) at time t as the dispersion term to calculate and output the effective energy level index Elive of the pulsation source. The effective energy level index Elive of the pulsation source is calculated and output using the following algorithm formula; In the formula, T represents the total number of real-time tension differences Tdiff within the time frame of the data acquisition task. Let Tdiff represent the average value of the real-time tension difference Tdiff sequence at each time step, max(Tdiff(t)) represents the maximum value of the real-time tension difference Tdiff(t) at time t, and min(Tdiff(t)) represents the minimum value of the real-time tension difference Tdiff(t) at time t.

4. The method for real-time online monitoring of steel wire rope based on intelligent sensors according to claim 3, characterized in that: S2 further includes S22; S22. By statistically analyzing the real-time tension difference (Tdiff) sequence during multiple safe fishing operations, a pulsation reference interval threshold is set. This pulsation reference interval threshold includes the normal reference threshold Elive. safe and suspicious threshold Elive mid ; Wherein: the upper bound of the effective energy level index of the pulsating source obtained under stable mechanical winding state is used as the normal reference threshold. safe The upper limit of the characteristic range of the effective energy level index of the pulsation source that caused slight tension abnormalities in the wire rope but did not pose an overload risk in historical pulsation events was used as the suspicion threshold. mid Based on the real-time acquired effective energy level index Elive of the pulsation source and the pulsation reference interval threshold, a preliminary assessment is made to determine the tension pulsation of the wire rope. Where: when the effective energy level index of the pulsation source Elive ≤ the normal reference threshold Elive safe When this occurs, it is determined to be a normal fluctuation. At this time, the winch continues to work at the currently set speed without triggering any protection strategy. When the normal reference threshold Elive safe <Effective energy level index of pulsating source Elive <Suspicious threshold Elive mid If a mild pulsation is detected, the current speed of the electric winch should be reduced by 5%. When the effective energy level index of the pulsation source Eliive ≥ the suspicious threshold Eliive mid When the heartbeat is detected, it is determined to be a violent pulsation, which triggers the winch risk analysis mechanism.

5. The method for real-time online monitoring of steel wire rope based on intelligent sensors according to claim 1, characterized in that: S3 includes S31; S31. After triggering the winch risk analysis mechanism, start the load acquisition point C, install a current sensor at the end of the winch drive motor to obtain the winch motor current IC at each moment in real time, and install an encoder on the winch shaft to obtain the winch winding speed VD at each moment in real time. The data is then transmitted to the central controller, where it undergoes time synchronization correction, noise filtering, and standardization before being integrated to obtain the load data for the corresponding time. The standardization process involves using the maximum and minimum standardization method based on the maximum motor current of the electric winch and the maximum winding speed of the winch to standardize the current motor current IC and the winding speed VD at each moment, thereby eliminating the influence of unit dimensions. The load data includes the winch motor current IC(t) at time t and the winch winding speed VD(t) at time t.

6. The method for real-time online monitoring of steel wire rope based on intelligent sensors according to claim 5, characterized in that: S3 further includes S32; S32. The statistical upper bound of the effective energy level index Elive of the pulsating source within the historical monitoring window where no overload occurred during historical safe fishing operations is used as the reference value Eref; the rated maximum continuous operating current provided by the winch drive motor manufacturer is used as the rated maximum safe current Imax of the winch; and combined with the load data, the comprehensive risk index Rcomb is calculated and output. The comprehensive risk index Rcomb is calculated and output using the following algorithm formula; The reference value Eref and the rated maximum safe current Imax of the winch are both dimensionless.

7. A real-time online monitoring method for steel wire rope based on intelligent sensors according to claim 6, characterized in that: S4 includes S41; S41. Set risk interval thresholds based on the historical comprehensive risk index Rcomb, whereby the risk interval thresholds include a risk warning threshold Rwarn and a risk shutdown threshold Rstop; and perform a secondary comparative evaluation based on the real-time calculated comprehensive risk index Rcomb to determine the load risk of the winch motor. The specific evaluation content is as follows: When the comprehensive risk index Rcomb ≤ the risk warning threshold Rwarn, the current stress state of the wire rope is determined to be within the safe range; When the comprehensive risk index Rwarn < comprehensive risk index Rcomb and comprehensive risk index Rcomb < risk shutdown threshold Rstop, the wire rope is determined to be in the risk buffer zone. When the comprehensive risk index Rcomb is greater than or equal to the risk shutdown threshold Rstop, the wire rope is determined to be in the shutdown risk range.

8. The method for real-time online monitoring of steel wire rope based on intelligent sensors according to claim 7, characterized in that: S4 further includes S42; S42. Based on the judgment of the load wind condition of the winch motor, execute the corresponding adaptive coupling control strategy, the details of which are as follows: When it is determined that the current stress state of the wire rope is within the safe range, the winch motor operates at the current winch winding speed VD, continues to monitor, and does not intervene. At the same time, the central controller updates the comprehensive risk index Rcomb every 100ms and then performs a second comparative evaluation. When the wire rope stress state is determined to be within the risk buffer zone, the winch winding speed VD is dynamically decelerated based on the output value of the current comprehensive risk index Rcomb, as follows: When the comprehensive risk index Rcomb exceeds the risk warning threshold Rwarn by 0%-20%, the winding speed is reduced by 3%-6%; When the comprehensive risk index Rcomb exceeds the risk warning threshold Rwarn by 20%-60%, the winding speed is reduced by 6%-18%. When the comprehensive risk index Rcomb exceeds 40%-100% of the risk warning threshold Rwarn, the winding speed is reduced by 18%-30%. When the wire rope is determined to be in the shutdown risk range, the central controller controls the winch motor to issue a dangerous pulsation warning. When the comprehensive risk index Rcomb is greater than the risk shutdown threshold Rstop for 1 second in a row, the winding will be automatically stopped.

9. A real-time online monitoring system for steel wire rope based on intelligent sensors, applied to the real-time online monitoring method for steel wire rope based on intelligent sensors as described in any one of claims 1-8, characterized in that: It includes a central acquisition module, a pulse effective analysis module, a winch risk analysis module, and an adaptive coupling control module; The central acquisition module collects pulsation operation data in real time by setting multiple acquisition points on the wire rope path of the electric winch, and transmits the collected winch operation data to the central controller of the electric winch. The central controller then preprocesses the winch operation data to obtain the raw monitoring data. The effective pulsation analysis module calculates the effective energy level index Elive of the pulsation source based on the original monitoring data, and makes a preliminary assessment based on the effective energy level index Elive of the pulsation source and the preset pulsation reference interval threshold to determine the tension pulsation of the wire rope. When the winch risk analysis module determines that the wire rope tension pulsation is abnormal through preliminary assessment, the winch risk analysis mechanism is triggered. The winch risk analysis mechanism calculates the comprehensive risk index Rcomb by extracting the load data of the winch motor and combining it with the effective energy level index Elive of the pulsation source. The adaptive coupling control module performs a secondary comparative evaluation by setting a risk interval threshold and a comprehensive risk index Rcomb, and executes the adaptive coupling control strategy based on the secondary comparative evaluation results.

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