Displacement sensor signal correction method of transverse displacement unlocking coupling system

Abstract

The invention discloses a displacement sensor signal correction method of a transverse displacement unlocking coupling system, and particularly relates to the technical field of signal correction. Acquiring original displacement signal sequences of the coupling system in different states; constructing a reference displacement model based on a structural gap, a friction coefficient and a micro-motion characteristic; calculating the deviation between the original signal and the reference model, and extracting a correction coefficient; establishing a dynamic correction function combining the historical deviation and the change rate; performing segmented correction on the initial and operation stage signals by using the correction coefficient and the dynamic function to obtain a corrected displacement signal sequence; the correction signal is input into a coupling system control module, the coupling state and the transverse displacement degree are recognized, and dynamic feedback regulation and control are completed; according to the invention, the accuracy and stability of displacement signals are improved, intelligent coupling of signal correction and structure control is realized, and the method is suitable for a high-precision displacement monitoring and control system in various complex structure projects.

Description

Technical Field

[0001] This invention relates to the field of signal correction technology, and more specifically to a method for correcting displacement sensor signals in a lateral displacement unlocking coupling system. Background Technology

[0002] In large-scale structural engineering, bridge engineering, and equipment connection parts, lateral displacement coupling structures are often used to mitigate relative displacement between structures and improve system stability. To achieve accurate monitoring of lateral displacement in the coupled system, displacement sensors are typically installed to acquire displacement data in real time during structural operation. However, due to external interference factors such as installation location, changes in coupling gaps, temperature drift, and structural deformation, the displacement signals acquired by the sensors often have deviations, making it difficult to accurately reflect the actual lateral displacement process, thus affecting the reliability and response accuracy of the coupled system's control strategy. Especially when the coupled system is in an unlocked or initial sliding state, the sensors are susceptible to interference from local micro-motions or no-load responses, leading to abnormal fluctuations in the displacement response signal. Existing technologies mostly rely on static calibration or simple filtering algorithms for correction, which are insufficient to meet the high-precision correction requirements under dynamic operating conditions. Summary of the Invention

[0003] The purpose of this invention is to provide a method for correcting displacement sensor signals in a lateral displacement unlocking coupling system, so as to overcome the shortcomings in the prior art.

[0004] To achieve the above objectives, the present invention provides the following technical solution: a method for correcting displacement sensor signals in a lateral displacement unlocking coupling system, comprising: Acquire the original displacement signal sequence of the displacement sensor under different working states of the coupling system, including the initial displacement signal in the unlocked state and the continuous displacement signal in the running state; A reference displacement model for the unlocking phase is constructed. The reference displacement model is based on the structural gap, friction coefficient and fretting characteristics of the coupling mechanism in the initial stage to determine the theoretical expected displacement response. Based on the deviation between the theoretically expected displacement response and the initial displacement signal, a correction coefficient is determined to correct the initial signal error. A dynamic correction function is established under running conditions, and the original displacement signal sequence is corrected using the correction coefficient and the dynamic correction function to obtain the corrected displacement signal sequence. The corrected displacement signal sequence is input to the coupling system control module to determine the coupling state and the degree of lateral displacement, thereby completing dynamic feedback control.

[0005] Preferably, the acquisition of the original displacement signal sequence of the displacement sensor under different operating states of the coupling system includes: The output signals of the displacement sensors installed in the coupling system are continuously acquired within a preset time window to form the original signal time series Draw, and the control status identification information of the coupling system is recorded simultaneously. Based on the control state identifiers of the coupled system, the Draw is segmented into states, and the signal segment corresponding to the unlocking phase is extracted as the initial displacement signal. The signal segments during the operation phase are extracted into continuous displacement signals. n is the total number of displacement signals; right and The original displacement signal sequence D is obtained by performing outlier removal and noise filtering respectively.

[0006] Preferably, the reference displacement model for constructing the unlocking phase includes: Obtain the structural boundary parameters of the coupling mechanism during the initial unlocking phase, including the structural gap value, contact surface preload, and contact stiffness; Based on the structural boundary parameters, and combined with the friction coefficient and fretting response curve, a nonlinear response relationship describing the initial stage of contact slip is established. The nonlinear response relationship is transformed into a time-domain displacement expression to form a theoretically expected displacement response curve, which serves as a reference displacement model for the unlocking stage and as a benchmark for correcting the initial displacement signal.

[0007] Preferably, a correction coefficient is determined to correct the initial signal error: Align and compare the initial displacement signal with the theoretical expected displacement response in the reference displacement model, calculate the discrete point difference sequence over the entire unlocking time period, and form the deviation dataset ΔD. Statistical analysis was performed on the deviation dataset ΔD to extract the main offset feature value representing the initial signal error; Based on the main offset feature value, and combined with the sensor's sensitivity coefficient and the response weight of the reference displacement model, a correction coefficient is constructed to adjust the initial displacement signal.

[0008] Preferably, a dynamic correction function is established during runtime, including: Acquire continuous displacement signal sequence under operating conditions The time derivative is used to construct the displacement change rate curve and identify the response characteristics of the coupled system in different dynamic stages of slip, rebound and buffering. Combining historical deviation trend data with the current displacement change rate, a dynamic correction function f(t) is constructed using the weighted time window method.

[0009] Preferably, the original displacement signal sequence is corrected using the correction coefficient and the dynamic correction function to obtain the corrected displacement signal sequence: The original displacement signal sequence is divided into an initial stage and an operating stage according to the control state information of the coupled system, and correction coefficients and dynamic correction functions are applied as correction basis respectively. The displacement signal in the initial stage is corrected by applying a correction coefficient to perform overall offset correction. The displacement signal in the running stage is then corrected by calling the dynamic correction function f(t) according to the time step to perform point-by-point dynamic compensation and generate a correction increment sequence. The correction increment is superimposed on the original displacement signal to form the corrected displacement signal sequence.

[0010] Preferably, the corrected displacement signal sequence is input to the coupled system control module: The corrected displacement signal sequence is input into the control module, and through signal trend analysis and multi-level threshold judgment, the current coupling mechanism is identified as being in an unlocked, sliding, buffered, or stable state. Based on the identified coupling state, combined with the lateral displacement amplitude, velocity and trend of change in the correction signal, the degree of lateral coupling is determined and control command parameters are generated. Based on the control command parameters, the driving coupling system performs corresponding adjustment operations in real time, including structural preload adjustment, displacement tolerance compensation, or coupling state locking.

[0011] The technical effects and advantages provided by the present invention in the above technical solution are as follows: 1. This invention achieves precise correction of the original displacement signal in a lateral displacement unlocking coupling system throughout the entire process and across multiple stages by constructing a reference displacement model for the unlocking phase, extracting deviation correction coefficients, establishing a dynamic correction function under operating conditions, and combining sensor sensitivity and structural response characteristics. This method effectively overcomes the problems of insufficient identification capability, correction lag, or residual errors in traditional static calibration and single filtering methods under complex working conditions, significantly improving the authenticity and stability of displacement data.

[0012] 2. This invention introduces the corrected displacement signal into the coupled system control module. Through state recognition, displacement trend judgment, and feedback control, it achieves intelligent response and closed-loop regulation of the dynamic behavior of the coupled structure. This technology not only improves the safety, reliability, and adjustment accuracy of system operation, but also has good adaptability and scalability, making it suitable for engineering scenarios with strict requirements for high-precision lateral displacement control, such as bridges, equipment connections, and rail transit. Attached Figure Description

[0013] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0014] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0015] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0016] For examples, please refer to Figure 1 As shown in this embodiment, a method for correcting displacement sensor signals in a lateral displacement unlocking coupling system includes: Acquire the original displacement signal sequence of the displacement sensor under different working states of the coupling system, including the initial displacement signal in the unlocked state and the continuous displacement signal in the running state; A reference displacement model for the unlocking phase is constructed. The reference displacement model is based on the structural gap, friction coefficient and fretting characteristics of the coupling mechanism in the initial stage to determine the theoretical expected displacement response. Based on the deviation between the theoretically expected displacement response and the initial displacement signal, a correction coefficient is determined to correct the initial signal error. A dynamic correction function is established under running conditions, and the original displacement signal sequence is corrected using the correction coefficient and the dynamic correction function to obtain the corrected displacement signal sequence. The corrected displacement signal sequence is input to the coupling system control module to determine the coupling state and the degree of lateral displacement, thereby completing dynamic feedback control.

[0017] To better achieve the goal of accurately correcting the displacement sensor signal of the lateral displacement unlocking coupling system in this invention, it is necessary to first obtain the original displacement signal sequence with high quality.

[0018] First, within a preset time window, displacement signal data output by the displacement sensors installed in the coupling system are continuously acquired. This preset time window can be flexibly set according to the actual engineering application scenario, typically encompassing a complete coupling cycle including the unlocking and operation phases. The displacement sensors installed in the system should have sufficiently high sampling accuracy and time resolution to ensure signal integrity and continuity. During the acquisition process, the current control status identification information of the coupling system is simultaneously recorded as a synchronization reference for the signal data. This control status identification information can be issued by the system controller or provided by the status sensing unit, indicating whether the coupling mechanism is currently in the unlocking phase, rigid contact phase, or sliding operation phase, etc.

[0019] This step generates a complete raw signal time series, denoted as "Draw". This signal series not only contains the raw displacement values ​​continuously acquired by the sensor, but also corresponds to the synchronously recorded control state information, thus providing a basis for subsequent state identification and data classification processing.

[0020] Secondly, based on the control state identification information of the coupled system, the original signal time series Draw is segmented into states. Specifically, according to the changing trend of the control state and the boundary conditions, the Draw signal sequence is logically divided along the time axis. The signal segment in the unlocked state is extracted as the "initial displacement signal," denoted as "...". "; Continuous displacement signal segments in the running state phase are extracted as " "to" The term "n" represents the total number of displacement signal segments in the operating state. The unlocked state refers to the pre-tightening or micro-motion stage where the coupling mechanism has not yet achieved actual structural contact or force transmission. The displacement signal in this stage reflects the initial response characteristics of the sensor and the loosening status of the system, and has important reference value. The operating state, on the other hand, includes dynamic processes such as actual structural displacement, contact, coupling, or slippage, and its signals are more complex and change more frequently.

[0021] In practice, control status identification information can be encoded as logical flag bits, for example, "0" represents the unlocked state and "1" represents the running state. During signal segmentation processing, the system extracts the signal segments within the corresponding status segment according to the time index, thereby generating the corresponding... and Data structures were used to complete the initial state-aware segmentation.

[0022] Secondly, for the extracted and Each signal segment undergoes preprocessing to eliminate outliers and high-frequency interference introduced by sensor noise, system disturbances, or data acquisition errors. Preprocessing includes two parts: Sliding window analysis or statistical thresholding is used to identify and remove abrupt changes and outliers in the signal sequence. Specifically, for each signal sequence, its local moving average and standard deviation are calculated, and a fluctuation amplitude threshold is set; if the amplitude change at a certain point exceeds the threshold, it is considered an outlier and is replaced or deleted.

[0023] Low-pass filtering, weighted moving average, or median filtering are used to smooth the high-frequency components in the signal sequence, thereby obtaining more representative and stable displacement data. The filtering parameters can be adaptively adjusted according to the sampling frequency and the system response frequency to achieve optimal signal fidelity.

[0024] The above preprocessing steps can effectively suppress signal fluctuations caused by environmental noise, sampling errors and transient interference, improve the signal-to-noise ratio of the original data, and provide a reliable data foundation for subsequent displacement correction and model fitting.

[0025] After processing, the obtained initial displacement signal Continuous displacement signal during operation to The signals are uniformly organized as "original displacement signal sequence D". This signal sequence has clear working condition labels, high signal quality and stability, and can be directly input into the subsequent correction model for model fitting and displacement error compensation.

[0026] In order to accurately characterize the nonlinear micro-motion behavior generated by the coupled system during the unlocking phase and provide theoretical support for subsequent sensor signal correction, this invention proposes a reference displacement model construction method based on structural gaps, friction characteristics and micro-motion response.

[0027] Before the coupled structure begins to operate, no substantial contact or movement has yet formed within it; the system is in a micro-gap free state or a pre-tightened static state. To describe the potential response characteristics of the structure in this state, the structural boundary parameters of the coupled mechanism must first be collected. These include the following three items: Structural gap value: refers to the initial non-contact distance between two coupled contacting bodies, which can be measured through structural design data or laser ranging. This gap determines the initial sensitivity of the system response.

[0028] Contact surface preload: In structural design, some coupling mechanisms may apply a small clamping force in advance through components such as springs, bolts, or pressure plates to constrain early fretting. This preload affects the force threshold in the initial stage of fretting and needs to be obtained through load testing or manufacturing parameters.

[0029] Contact stiffness: reflects the elastic response capability of the contact interface in the initial stage of stress. It can usually be modeled by Hertzian contact theory, or the stiffness characteristics of local contact surface elements can be extracted by finite element simulation. The numerical unit is the ratio of force to displacement.

[0030] The three boundary parameters mentioned above constitute the basic description of the structural characteristics during the unlocking phase and can define the initial mechanical state of the coupled system.

[0031] After the structural gaps disappear, the coupling mechanism will undergo a fretting and sliding process. This process exhibits typical nonlinear frictional hysteresis characteristics and cannot be simply described using an ideal spring model. Therefore, based on the structural boundary parameters obtained in the first step, this invention further introduces the friction factor and fretting response behavior to construct the nonlinear response relationship during the unlocking phase.

[0032] This nonlinear response model mainly considers the following factors: Coefficient of friction: Reflects the relative sliding resistance between contact surfaces. It can be selected by referring to tables, experiments or specifications based on the material pair (such as metal-metal, metal-rubber). It includes two parts: static friction coefficient and dynamic friction coefficient.

[0033] Fretting response curves: The force-displacement relationship in the fretting stage often exhibits an "S"-shaped hysteresis characteristic, with multiple stages including the initial static friction hysteresis stage, the slip transition stage, and the stabilization stage. Displacement response models can be established using mathematical expressions such as hyperbolic tangent functions, exponential decay functions, or piecewise power functions.

[0034] For example, a typical nonlinear response relationship can be expressed as follows: the fretting response force is equal to the upper limit of friction multiplied by a nonlinear function that varies with time or displacement, where the function grows exponentially in the initial stage and then gradually stabilizes, simulating the sliding contact process.

[0035] Loading path dependency: Micro-motion responses typically exhibit hysteresis, meaning the response depends not only on the current loading value but also on historical loading paths. This invention can introduce a memory factor or incremental stacking method to guide the model to possess loading path recognition capabilities.

[0036] Through the above modeling method, the present invention constructs a nonlinear force-displacement response function that can characterize the entire process of the structure from micro-motion triggering to sliding transition in the unlocked state, and truly reflects the nonlinear coupling characteristics between the initial structural contact behavior and the sensor response.

[0037] To enable subsequent comparison and correction with the actual acquired sensor signals, the established nonlinear response relationship needs to be transformed into a time-domain displacement expression that can be analyzed and quantified. This invention maps the nonlinear force-displacement relationship onto the time axis by introducing an initial loading rate, a friction critical threshold, and contact stiffness boundary conditions.

[0038] The specific steps include: Set an initial loading time range, and discretize the response process into several time steps according to the sampling frequency; Within each time step, the current displacement increment is calculated based on the current loading rate and the response state at the previous moment, and the complete response curve is formed by iterative process. The displacement-time series is constructed into a theoretically expected displacement response curve, which serves as the reference response model for the unlocking phase and is denoted as the "reference displacement curve".

[0039] To achieve accurate correction of the displacement sensor output signal in the unlocked state, this invention establishes a deviation dataset by comparing and analyzing the original displacement signal output by the sensor in the initial stage with the theoretically expected displacement response, and then determines a dynamic correction coefficient based on this dataset to correct systematic errors and improve the authenticity and reliability of the displacement signal.

[0040] First, the initial displacement signal (hereinafter referred to as "initial signal", denoted as "initial signal") collected during the unlocking phase will be used as the initial signal. The theoretical expected displacement response curve in the aforementioned constructed reference displacement model (hereinafter referred to as "reference response", denoted as...) Time-domain alignment is performed. The alignment process can be synchronized based on the system control timestamp or sampling time sequence to ensure that the two sets of signals are compared within the same time interval.

[0041] After alignment, using the time series as a reference, the values ​​of the initial signal and the reference response at each discrete sampling point are subtracted point by point to obtain the instantaneous deviation value at each time point. The deviation values ​​of all sampling points are arranged in chronological order to form a complete deviation dataset, denoted as ΔD.

[0042] The deviation dataset ΔD reflects the error distribution between the original signal and the theoretical response throughout the unlocking process. Its magnitude and distribution trend reveal the systematic drift, zero-point offset, or error characteristics of the sensor output caused by environmental disturbances.

[0043] For example, if the reference response is 5 mm at a certain moment and the initial signal is 4.6 mm, then the deviation at that moment is -0.4 mm. This point-by-point interpolation method can generate a sequence of error signals with practical engineering significance, providing fundamental data for subsequent statistical analysis.

[0044] After obtaining the complete deviation dataset ΔD, this invention further performs statistical analysis on it to identify and extract the key values ​​that best represent systematic errors: the principal offset eigenvalue. This value will serve as the core basis for constructing the correction coefficients.

[0045] The specific analysis method is as follows: First, the mean of the deviation dataset ΔD is calculated to obtain the average level of deviation throughout the entire unlocking phase, denoted as μΔD. This mean is used to characterize the central trend of the overall deviation and is suitable for judging systematic drift or zero-point offset.

[0046] Further calculation of the standard deviation σΔD of ΔD is performed to assess the dispersion of the deviation and identify the presence of non-systematic interferences such as high-frequency noise and short-term disturbances. If the standard deviation is significantly small, it indicates that the deviation is relatively stable and a static correction coefficient is suitable; if the standard deviation is large, piecewise modeling or a sliding window dynamic correction can be considered.

[0047] Perform a first- or second-order polynomial trend fitting on ΔD and analyze the trend of the deviation over time. If the fitted curve is close to a horizontal straight line, it indicates that the deviation is relatively stable; if it shows a monotonic trend, there may be problems such as initial signal response delay or reference model bias, and a time decay term or slope adjustment factor needs to be introduced into the correction coefficient.

[0048] Through the above statistical process, a principal offset feature value can be extracted, which is usually selected as the mean deviation μΔD, and can be supplemented by a trend factor or weight correction term to guide the determination of the correction coefficient.

[0049] After obtaining the main offset eigenvalue, in order to effectively apply this error to the initial signal correction process, this invention introduces a correction coefficient α, which is used to adjust the initial signal... Perform linear or nonlinear compensation.

[0050] When constructing the correction coefficient α, in addition to directly using the principal offset eigenvalues, the following two important factors are also considered: Sensor sensitivity coefficient S: This represents the sensor's responsiveness to actual displacement changes, and is measured as the ratio of the output signal change to the actual displacement change. If the sensor has insufficient sensitivity or excessive amplification, directly using the offset value for correction may result in overcompensation or undercompensation. Therefore, the main offset value needs to be normalized using a sensitivity factor.

[0051] Weighting coefficient W of the reference response: Considering the accuracy and applicability of the reference model itself, a weighting factor W (usually ranging from 0 to 1) can be introduced to adjust the correction magnitude. For example, for a reference model obtained from high-precision simulation or experimental fitting, its W value can be set close to 1; if the model is an approximate empirical model, the W value can be appropriately reduced.

[0052] The final correction factor α can be expressed as: Apply this correction factor to the initial displacement signal. The corrected signal can be obtained through weighted superposition. The expression is: This correction process can be performed directly in a linear system, or it can be dynamically compensated by incorporating a time variable when there is a dynamic trend.

[0053] After the coupling mechanism enters the actual operation phase, the system continuously acquires the continuous signal sequence output by the displacement sensor, denoted as... to , where n is the total number of signals, and the sampling frequency is set synchronously with the control system.

[0054] To reveal the dynamic state changes of a coupled system during operation, this invention performs time derivative calculations on the continuous signal, that is, calculates the difference between the displacement values ​​at two adjacent time sampling points to obtain the instantaneous displacement rate of change. Assume the displacement values ​​of the sensor at each time point are as follows: and If the sampling interval is Δt, then the rate of change This can be expressed as: Arranging the rates of change of all sampling points in chronological order will form a continuous displacement rate of change curve, denoted as V(t).

[0055] This curve reflects the dynamic response characteristics of the system at each stage, where: When the rate of change is consistently positive and large, it usually corresponds to the slip acceleration phase; When the rate of change decreases rapidly or even turns negative, structural rebound or reverse slip may occur. When the rate of change approaches zero or the oscillations become smaller, it may enter a buffer or stable phase.

[0056] By analyzing the shape and fluctuation pattern of the rate of change curve, a preliminary identification of the dynamic state of the system can be achieved, providing a basis for subsequent correction strategies.

[0057] Based on identifying the current operating stage of the structure, this invention further integrates historical deviation trend data with current rate of change information to construct a correction function f(t) that can dynamically change over time.

[0058] First, the historical deviation trend data originates from the corrected residuals of the previous stage, namely, the sequence of differences between the theoretical reference displacement response and the actual sensor signal recorded by the system during the initial unlocking phase and early operation phase. This trend data can be extracted using methods such as moving average or exponentially weighted moving average (EWMA) to represent the error evolution characteristics of the system in different time periods.

[0059] Secondly, at the current moment, the known rate of displacement change v(t) of the system, as a dynamic factor reflecting the real-time motion characteristics, can be used to adjust the sensitivity of the correction function to the response at different stages.

[0060] To achieve dynamic adaptive correction, this invention introduces a weighted time window method. This method weights and superimposes the historical deviation trend over a period of time with the current rate of change to construct a correction function f(t). Its basic expression is: ;in: This represents the weighted average of historical deviations centered on the current moment. This represents the rate of change of displacement at the current moment; and The weighting coefficients set for experience satisfy the condition that the sum is 1, and can be adjusted according to the sensitivity of different coupling mechanisms.

[0061] To achieve accurate correction of the output signal of the displacement sensor in the coupled system, after obtaining the correction coefficient and establishing the dynamic correction function, it is necessary to effectively combine the two and apply them to the original displacement signal sequence to complete the error compensation.

[0062] In practical applications, the operation of a coupled system can be divided into at least two typical stages: the initial unlocking stage and the normal operation stage. Since the structural behavior, signal characteristics, and error sources differ significantly between these two stages, the correction methods also need to be differentiated.

[0063] This invention uses control status identification information recorded in the system control module to logically divide the original displacement signal sequence D into two sub-sequences: Initial stage signal sequence : Corresponds to the sensor response when the structure is in an unlocked, relaxed, or non-contact state; Operation phase signal sequence : Corresponds to the response of the structure during dynamic motion processes such as coupling contact, slippage, and buffering.

[0064] Control status information may include timestamps, status flags (such as "unlocked", "coupled", "movement") or event trigger signals recorded by the controller. The signal sequence is precisely divided along the time axis through state machine logic to ensure that subsequent correction strategies match the state.

[0065] After the signal stages are divided, corresponding correction methods are applied to the signals in different stages: Initial stage signal correction (static offset compensation) For the initial stage signal sequence Then, the correction coefficient α calculated earlier is used to perform overall static offset correction. The correction process is as follows: This holistic translation correction is suitable for the initial stage where the source of deviation is stable and mainly affected by structural loosening or zero-point drift, and can effectively remove systematic errors.

[0066] Signal sequence during operation to Point-by-point compensation is performed using a dynamic correction function f(t). f(t) is a time-dependent function whose value changes dynamically with the structural state, displacement rate of change, and historical deviation trend, and has been determined in the previous modeling stage.

[0067] Let the initial displacement value at time point i in the operation phase signal be... The corresponding dynamic correction function value is The correction increment at that point is: ; Calculate all time points sequentially to obtain a set of... Equal-length modified increment sequence .

[0068] This point-by-point correction based on dynamic functions has good time-varying and adaptive capabilities, and can accurately compensate for nonlinear errors caused by structural slip velocity, loading state or environmental disturbances.

[0069] Obtaining initial stage correction results and the incremental sequence of corrections during operation. Subsequently, the present invention superimposes the correction increment onto the original signal sequence. The corrected operation phase signal sequence is obtained. .

[0070] Specifically, it can be expressed as follows: (where i ∈ [1, n]); At this point, the correction signals from the two stages have been processed and updated separately, ultimately resulting in... and Combined, they form a complete corrected displacement signal sequence D′: .

[0071] To ensure the physical rationality and engineering safety of the correction results, this invention also introduces a limiting control mechanism during the correction superposition stage, setting a maximum correction amplitude threshold Δ_max to prevent the correction from exceeding the actual displacement boundary of the structure due to misidentification or extreme errors. The correction increment satisfies the following constraint: If ,but ;in express The positive and negative signs are used. This amplitude limiting control not only enhances the system's anti-interference capability but also improves its safety and fault tolerance during actual deployment.

[0072] In coupled systems, displacement sensor signals are not only used for data monitoring and structural analysis, but more importantly, they provide accurate state identification and control decision support for the control system. After a series of error correction processes proposed in this invention, the resulting corrected displacement signal sequence possesses high accuracy and good dynamic stability, and can serve as a reliable input source for the coupled system's control module.

[0073] To achieve intelligent adjustment and real-time feedback control of structural operation, this invention inputs the corrected displacement signal sequence into the coupled system control module, further conducts signal state analysis, coupling degree identification and control command generation, and ultimately drives the actual coupled execution structure to achieve adaptive regulation.

[0074] After the corrected displacement signal sequence (denoted as D′) is input into the control module, the current operating state of the coupling mechanism is first identified through trend analysis and hierarchical judgment logic. The coupling state typically includes, but is not limited to, the following four typical types: Unlocked state: The structure has not yet been contacted or has just started, and the displacement signal changes very little; Slipping state: The structure slides relative to each other, and the displacement increases or decreases monotonically and rapidly; Buffer state: After slippage, micro-oscillations occur, and the displacement exhibits periodic micro-amplitude fluctuations; Steady state: The structure enters full coupling, and the displacement signal tends to stabilize.

[0075] To accurately determine these states, this invention employs two types of analysis methods: Trend analysis: By calculating the first derivative (i.e., the rate of change of displacement) and the second derivative (i.e., the rate of change of the rate of change), the direction of change and acceleration characteristics of the signal can be determined. For example: The rate of change of displacement is close to zero and changes slowly: this may indicate a steady state. A large rate of change in displacement, which increases or decreases continuously, may indicate a slip condition. The rate of change of displacement oscillates periodically between positive and negative values: this may indicate a buffer state.

[0076] Multi-level threshold judgment: Set threshold ranges corresponding to different states, including: Low amplitude threshold (used to identify unlock status). High-rate threshold (used to determine slip state); Joint threshold for fluctuation amplitude and frequency (used to identify buffer state). Steady-state deviation threshold (used to determine a steady state).

[0077] The threshold can be calibrated using structural design data, historical monitoring data, or simulation models. The control module analyzes the changing trend of the correction signal D′ in real time and matches it with the preset threshold, outputting the state identification result S(t) as the input condition for subsequent control logic.

[0078] After completing the coupling state identification, the control module will further evaluate the current lateral motion intensity and coupling tightness of the coupled structure based on the lateral displacement amplitude, change rate and change trend in the correction signal D′.

[0079] The evaluation process includes the following three dimensions: Amplitude analysis: Extract the maximum displacement value at the current moment and within a past period to determine whether the structure exceeds the design allowable range. For example, if the current lateral displacement exceeds the preset maximum tolerance Δ_max, the structure is considered to be in a strongly coupled or abnormal slip state.

[0080] Velocity analysis: The displacement change rate V(t) is calculated using the first derivative to determine the dynamic activity level of the coupled motion. If the velocity continues to rise, it may be in an unstable slip phase; if the velocity approaches zero and fluctuates little, it may be in a stable locked phase.

[0081] Trend analysis: Using regression or trend fitting methods, the future predicted direction of displacement signals is analyzed to predict in advance whether the coupled structure is prone to instability or rebound.

[0082] Based on the above analysis results, the control module generates the corresponding control command parameter set P(t), the contents of which include: Current coupling status indicator (e.g., sliding, locking); Lateral displacement correction amount; Adjust the recommended preload; Does it trigger tolerance compensation? Whether the coupling state requires locking or unlocking, etc.

[0083] This set of control parameters is an important input basis for subsequent control execution units.

[0084] Finally, the control module drives the coupled system to perform corresponding adjustment operations according to the control command parameter set P(t), thus completing closed-loop control.

[0085] Control actions include, but are not limited to, the following typical operation forms: Structural preload adjustment: When the coupling state is determined to be too loose or too tight, the preload device (such as a helical spring, pneumatic / hydraulic device, etc.) is automatically controlled to apply or release the preload to adjust the structural contact stiffness and improve coupling stability.

[0086] Displacement tolerance compensation: When the lateral displacement exceeds the dynamic tolerance range set by the system, the system will make fine adjustments and compensation through controllable limit mechanisms, flexible connectors or guide rail offset control to prevent structural instability or mechanical interference.

[0087] Coupling state locking and unlocking: When the structural stability state is identified, the control module can trigger the mechanical locking mechanism to lock; when the slippage trend is detected to be increasing, the lock can be released to enter the free operation mode, thereby improving the structural flexibility.

[0088] All of the above operations are automatically completed based on the real-time monitoring and analysis of displacement signals by the control module, forming a complete closed-loop logic, which greatly improves the system's response capability and intelligence level.

[0089] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A method for correcting displacement sensor signals in a lateral displacement unlocking coupling system, characterized in that: include: Acquire the original displacement signal sequence of the displacement sensor under different working states of the coupling system, including the initial displacement signal in the unlocked state and the continuous displacement signal in the running state; A reference displacement model for the unlocking phase is constructed. The reference displacement model is based on the structural gap, friction coefficient and fretting characteristics of the coupling mechanism in the initial stage to determine the theoretical expected displacement response. Based on the deviation between the theoretically expected displacement response and the initial displacement signal, a correction coefficient is determined to correct the initial signal error. A dynamic correction function is established under running conditions, and the original displacement signal sequence is corrected using the correction coefficient and the dynamic correction function to obtain the corrected displacement signal sequence. The corrected displacement signal sequence is input to the coupling system control module to determine the coupling state and the degree of lateral displacement, thereby completing dynamic feedback control.

2. The displacement sensor signal correction method for a lateral displacement unlocking coupling system according to claim 1, characterized in that: The acquisition of the original displacement signal sequence of the displacement sensor under different operating states of the coupling system includes: The output signals of the displacement sensors installed in the coupling system are continuously acquired within a preset time window to form the original signal time series Draw, and the control status identification information of the coupling system is recorded simultaneously. Based on the control state identifiers of the coupled system, the Draw is segmented into states, and the signal segments corresponding to the unlocking phase are extracted as initial displacement signals. The signal segments during the operation phase are extracted into continuous displacement signals. n is the total number of displacement signals; right and The original displacement signal sequence D is obtained by performing outlier removal and noise filtering respectively.

3. The method for correcting displacement sensor signals in a lateral displacement unlocking coupling system according to claim 2, characterized in that: The reference displacement model for the construction unlocking phase includes: Obtain the structural boundary parameters of the coupling mechanism during the initial unlocking phase, including the structural gap value, contact surface preload, and contact stiffness; Based on the structural boundary parameters, and combined with the friction coefficient and fretting response curve, a nonlinear response relationship describing the initial stage of contact slip is established. The nonlinear response relationship is transformed into a time-domain displacement expression to form a theoretically expected displacement response curve, which serves as a reference displacement model for the unlocking stage and as a benchmark for correcting the initial displacement signal.

4. The method for correcting displacement sensor signals in a lateral displacement unlocking coupling system according to claim 3, characterized in that: Determine the correction coefficients to correct for initial signal errors: Align and compare the initial displacement signal with the theoretical expected displacement response in the reference displacement model, calculate the discrete point difference sequence over the entire unlocking time period, and form the deviation dataset ΔD. Statistical analysis was performed on the deviation dataset ΔD to extract the main offset feature value representing the initial signal error; Based on the main offset feature value, and combined with the sensor's sensitivity coefficient and the response weight of the reference displacement model, a correction coefficient is constructed to adjust the initial displacement signal.

5. The method for correcting displacement sensor signals in a lateral displacement unlocking coupling system according to claim 4, characterized in that: Establish dynamic correction functions during runtime, including: Acquire continuous displacement signal sequence under operating conditions The time derivative is used to construct the displacement change rate curve and identify the response characteristics of the coupled system in different dynamic stages of slip, rebound and buffering. Combining historical deviation trend data with the current displacement change rate, a dynamic correction function f(t) is constructed using the weighted time window method.

6. The method for correcting displacement sensor signals in a lateral displacement unlocking coupling system according to claim 5, characterized in that: The original displacement signal sequence is corrected using the aforementioned correction coefficients and dynamic correction function to obtain the corrected displacement signal sequence: The original displacement signal sequence is divided into an initial stage and an operating stage according to the control state information of the coupled system, and correction coefficients and dynamic correction functions are applied as correction basis respectively. The displacement signal in the initial stage is corrected by applying a correction coefficient to perform overall offset correction. The displacement signal in the running stage is then corrected by calling the dynamic correction function f(t) according to the time step to perform point-by-point dynamic compensation and generate a correction increment sequence. The correction increment is superimposed on the original displacement signal to form the corrected displacement signal sequence.

7. The method for correcting displacement sensor signals in a lateral displacement unlocking coupling system according to claim 6, characterized in that: The corrected displacement signal sequence is input to the coupled system control module: The corrected displacement signal sequence is input into the control module, and through signal trend analysis and multi-level threshold judgment, the current coupling mechanism is identified as being in an unlocked, sliding, buffered, or stable state. Based on the identified coupling state, combined with the lateral displacement amplitude, velocity and trend of change in the correction signal, the degree of lateral coupling is determined and control command parameters are generated. Based on the control command parameters, the driving coupling system performs corresponding adjustment operations in real time, including structural preload adjustment, displacement tolerance compensation, or coupling state locking.

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