Current sensor pin bending processing control system and processing equipment

Abstract

The invention discloses a current sensor pin bending processing control system and processing equipment, and relates to the technical field of current sensor pin bending processing, and the current sensor pin bending processing control system comprises the following steps: fusing and collecting three types of disturbance parameters with different physical dimensions and response mechanisms, namely bending acceleration ZWa, pin surface contact impedance disturbance ZBd and friction sound spectrum response ZMc; the sensing coverage range of the system on the multi-source abnormal phenomenon in the machining process is remarkably expanded, the recognition blind area of a traditional system depending on a single force or displacement signal is made up, and the sensitivity to non-dominant disturbance characteristics is improved. Non-linear interaction modeling is carried out on the three disturbance factors through the perturbation coupling strength index psi, and the system not only can recognize single-variable fluctuation, but also can capture the co-evolution trend among variables. According to the structure, the system has the capability of recognizing disturbance structural imbalance and coupling activation trend in advance, and has higher fault perspectiveness and active response capability.

Description

Technical Field

[0001] The present invention relates to the technical field of current sensor pin bending processing, in particular to a current sensor pin bending processing control system and processing equipment. Background Art

[0002] During the packaging of electrical detection devices, pins often serve as the key physical terminals for connecting to external circuits. Their morphology plays a decisive role in subsequent soldering, electrical performance consistency, and assembly reliability. Especially in the mass packaging of current sensors, pin bending must not only achieve dimensional consistency but also ensure dynamic response stability and real-time control during the process.

[0003] Existing current sensor pin bending equipment generally uses a motion control method based on a fixed trajectory template, completing the bending task through statically set path instructions. Although this method is simple in structure, it is highly sensitive to factors such as pin material variations, process errors, and environmental disturbances. This makes it prone to problems such as slight deviations in the bending angle, end position drift, and process instability during processing.

[0004] The root cause of this phenomenon is that existing systems generally lack the ability to perceive the "perturbation behavior" of the bending process in real time, failing to establish a traceable disturbance model or trajectory deviation response mechanism. Under high-speed machining conditions, the stitch structure may experience transient torque disturbances due to factors such as material elasticity differences, local stress release, and machining inertia lag. These disturbances are not detected or modeled in conventional control models, resulting in the inability to actively correct subsequent trajectory control, causing state drift such as "slip delay" or "inertia deflection" in the bending path. Summary of the Invention

[0005] In view of the deficiencies in the prior art, the present invention provides a current sensor pin bending processing control system and processing equipment, which solve the problems mentioned in the background technology.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a current sensor pin bending processing control system, including a disturbance signal acquisition and preprocessing module, a perturbation energy modeling and spectrum generation module, a bending path error mapping module, a real-time correction control module, a feedback trend analysis and steady-state evaluation module, and an optimization strategy switching and task scheduling module;

[0007] The disturbance signal acquisition and preprocessing module samples the real-time state data of the current sensor pin processing process through the sensor, fits it into the original data set SM, and performs preprocessing to obtain the pin data set ZM;

[0008] The perturbation energy modeling and atlas generation module analyzes the pin dataset ZM, constructs a perturbation energy atlas, and calculates and obtains the perturbation energy offset function D;

[0009] The bending path error mapping module receives the current machining trajectory data according to the obtained pin dataset ZM, performs a spatial error mapping with the pre-stored standard trajectory, and obtains the spatial error E;

[0010] The real-time correction control module calculates and obtains the correction amplitude F according to the obtained energy offset function D and spatial error E; the feedback trend analysis and steady-state evaluation module processes the continuous change trend of the correction amplitude F within a fixed period T, obtains the continuous stability evaluation function G, and identifies whether it enters the high-perturbation and critical instability regions;

[0011] The optimization strategy switching and task scheduling module fuses the obtained perturbation energy offset function D, correction amplitude F, and continuous stability evaluation function G, calculates the strategy response index function H, and executes dynamic bending strategy switching.

[0012] Preferably, the perturbation signal acquisition and preprocessing module includes a perturbation state signal acquisition unit and a cleaning and normalization unit;

[0013] The perturbation state signal acquisition unit is responsible for collecting state data through sensors during the pin bending process, including the bending acceleration ZWa, the pin surface contact impedance perturbation ZBd, and the friction sound spectrum response ZMc, and fitting them into the original dataset SM;

[0014] Among them, the bending acceleration ZWa is sampled by a high-frequency laser displacement sensor and obtained through first-order differentiation;

[0015] The bending acceleration ZWa is obtained through the following formula:

[0016] ;

[0017] In the formula, x(t + Δt) represents the displacement at time t + Δt, x(t) represents the displacement at time t, x(t - Δt) represents the displacement at time t - Δt, and Δt represents the time interval;

[0018] The pin surface contact impedance perturbation ZBd is obtained through a current and voltage composite probe and by collecting the instantaneous change in Ohm's value;

[0019] The pin surface contact impedance perturbation ZBd is obtained through the following formula:

[0020] ;

[0021] In the formula, V(t) represents the voltage value at time t, I(t) represents the current value at time t, and Ro represents the no-load initial contact resistance;

[0022] The frictional acoustic spectrum response ZMc is collected by a piezoelectric acoustic emission sensor and the frequency spectrum intensity is obtained after FFT;

[0023] The frictional acoustic spectrum response ZMc is obtained by the following formula:

[0024] ;

[0025] Wherein, f1 and f2 represent the defined target frequency range, 1.5 kHz–10 kHz, for machining contact friction, F{Sraw(t)} represents the Fourier transform of the original acoustic signal, and max represents taking the point with the largest spectrum amplitude within the frequency range [f1, f2], in order to capture the resonance or abnormal amplitude increase peak in a certain frequency band;

[0026] The cleaning and normalization unit performs noise reduction and normalization processing on the obtained original data set SM to obtain the pin data set ZM;

[0027] Noise reduction is performed by using a sliding filtering method to remove noise from the original data set SM;

[0028] Normalization processing is performed by using the Min-Max linear normalization method on the original data set SM to obtain the pin data set ZM;

[0029] The pin data set ZM is obtained by the following formula:

[0030] ;

[0031] Wherein, ZMo represents the o-th item of data in the pin data set ZM, SMo represents the o-th item of data in the original data set SM, minSMo represents the valley value of the o-th item of data in the original data set SM, and maxSMo represents the peak value of the o-th item of data in the original data set SM.

[0032] Preferably, the perturbation energy modeling and spectrum generation module includes a perturbation coupling index construction unit and a perturbation energy offset function generation unit;

[0033] The perturbation coupling index construction unit constructs a non-linear interaction function based on the obtained pin data set ZM, captures the joint coupling behavior among three perturbation quantities, and obtains the perturbation coupling strength index Ψ;

[0034] The perturbation coupling strength index Ψ is obtained by the following formula:

[0035] ;

[0036] Where d represents the derivative symbol, ZWa(t) represents the bending acceleration at time t, ZBd(t) represents the contact impedance disturbance of the pin surface at time t, ZMc(t) represents the friction acoustic spectrum response at time t, and cos() represents the cosine function. All of them come from the disturbance signal acquisition and preprocessing module and are processed by sliding filtering for noise reduction and Min-Max normalization to have a unified dimension. The constructed perturbation coupling intensity index Ψ is a dimensionless coupling trend index, which is used to qualitatively analyze the disturbance intensity trend and construct the control criterion.

[0037] Specifically, the bending acceleration ZWa, the pin surface contact impedance disturbance ZBd, and the friction acoustic spectrum response ZMc have all been uniformly normalized through the disturbance signal acquisition and preprocessing module before entering the construction of the perturbation coupling intensity index Ψ. All variables are dimensionless disturbance trend factors. The constructed coupling terms are only used to qualitatively reflect the coupling change trend of the disturbance path rather than the direct physical and mechanical values, ensuring the comparability and integration of disturbance terms from different sources.

[0038] The perturbation coupling strength index Ψ does not point to a specific physical value, but is used to comprehensively reflect the nonlinear linkage trend between acceleration fluctuations, contact resistance anomalies and acoustic spectrum changes during the processing process. It is a trend perturbation index for normalized modeling and is suitable for constructing perturbation evolution maps and stability assessment models.

[0039] The perturbation energy offset function generation unit integrates and models the perturbation behavior according to the obtained perturbation coupling strength index Ψ, obtains the perturbation energy offset function D, and compares it with the preset offset threshold TD to construct an energy spectrum;

[0040] The perturbation energy offset function D is obtained by the following formula:

[0041] ;

[0042] Where, represents the steady-state disturbance accumulation coefficient, represents the dynamic perturbation evolution coefficient, Ψ(t) represents the perturbation coupling strength index at time t;

[0043] Specific, steady-state disturbance accumulation coefficient and dynamic perturbation evolution coefficient , the control parameters with engineering adjustment significance do not originate from fixed physical constants, but are empirically configured according to the sensitivity requirements of the system's response to perturbations; specifically, β1 is used to adjust the response degree of the system to the perturbation coupling strength index Ψ itself, and the generally recommended initial setting range is 0.8 to 1.2 to ensure that the system can timely identify the gradual accumulation of steady-state perturbations; while β2 is used to adjust the dynamic response ability of the system to the perturbation change rate dΨ(t) / dt, and the recommended initial setting range is 0.3 to 0.8 to enhance the system's ability to identify the state mutation caused by the critical perturbation trend;

[0044] The energy map is obtained by matching in the following way:

[0045] When the perturbation energy offset function D ≤ the offset threshold TD, it indicates that the offset is stable and the energy map is a stable straight line;

[0046] When the perturbation energy offset function D > the offset threshold TD, it indicates that the offset is abnormal and the energy map shows a cumulative trend and is an ascending straight line.

[0047] Preferably, the bending path error mapping module includes a trajectory reconstruction and attitude synchronization unit and a spatial error calculation unit;

[0048] The trajectory reconstruction and attitude synchronization unit records the acquisition trajectory of the pin dataset ZM, and performs dynamic attitude reconstruction and standard spatio-temporal alignment on the trajectory point data during pin processing to obtain the trajectory point sequence Pact;

[0049] The trajectory point sequence Pact is obtained through the following formula:

[0050] Pact(t) = {xi(t), yi(t), zi(t)|i = 1, 2,..., N};

[0051] In the formula, Pact(t) represents the trajectory point sequence at time t, (xi(t), yi(t), zi(t)) represents the three-dimensional spatial position of the pin end during the bending process, i represents the sampling serial number, and N represents the number of trajectory points;

[0052] By introducing the local rotation registration matrix XR and the displacement vector XT, rigid registration processing of the pin path and the standard trajectory is carried out, and the processing formula is as follows:

[0053] .

[0054] Preferably, the spatial error calculation unit, according to the trajectory point sequence Pact(t) at the indicated time t, evaluates the geometric offset intensity ep of each point through the Euclidean space difference, and introduces a path deformation sensitive index function to non-linearly amplify the high-error section to obtain the spatial error E;

[0055] Construct a three-dimensional error vector based on the three-dimensional spatial position (xi(t), yi(t), zi(t)) of the pin end during the bending process , and obtain the offset intensity ep;

[0056] Three-dimensional error vector is obtained through the following formula:

[0057] ;

[0058] In the formula, represents the three-dimensional error vector of the i-th trajectory point at time t, and (oxi(t), oyi(t), ozi(t)) represents the spatial coordinates of the i-th point in the standard reference trajectory;

[0059] The offset intensity ep is obtained through the following formula:

[0060] ;

[0061] In the formula, epi(t) represents the offset intensity of the i-th trajectory point at time t;

[0062] The spatial error E is obtained through the following formula:

[0063] ;

[0064] In the formula, k represents the path deformation amplification coefficient, and sin represents the sine function.

[0065] Specifically, the path deformation amplification coefficient k can be set based on the empirical values of the process conditions or according to the spatial distribution density of the trajectory error during the processing. This coefficient is used to enhance the error response weight in the middle section of the path. By default, the path deformation amplification coefficient k can be set to 1.0, that is, twice the weight is given to the offset of the middle section trajectory; for the case of concentrated stress or middle section springback, the path deformation amplification coefficient k can be set to 1.5 - 2.0 to enhance the error perception sensitivity of the key section of the processing path deformation. The parameter setting has a clear adjustment logic and engineering feasibility, and those skilled in the art can quickly configure or fine-tune according to the actual working conditions.

[0066] Preferably, the real-time correction control module includes a dynamic correction intensity calculation unit and a correction trigger determination and fine-tuning unit;

[0067] The dynamic correction intensity calculation unit calculates and obtains the correction amplitude F according to the obtained energy offset function D and spatial error E;

[0068] The correction amplitude F is obtained through the following formula:

[0069] ;

[0070] In the formula, λ represents the control adjustment sensitivity coefficient, μ represents the evolution trend response weight, D(t) represents the energy offset function at time t, E(t) represents the spatial error at time t, and QE represents a non-zero constant.

[0071] Specifically, the control adjustment sensitivity coefficient λ is used to control the sensitivity of the overall system to disturbances. The higher the value, the faster the system responds to disturbance fluctuations. The recommended initial value is 1.0. In scenarios where the control system has low rigidity or a high beat, it can be increased to 1.2 - 1.5 to improve the trajectory correction speed; in a high-rigidity system, it can be set to 0.8 to avoid mis-triggering correction behaviors.

[0072] The evolution trend response weight μ is used to reflect the degree of attention of the system to the change rate of the disturbance dD(t) / dt. For processing conditions with significant disturbance acceleration and prominent evolution trends, μ is set to 0.7 - 0.9 to enhance the trend-dominated intervention mechanism; for processing scenarios with stable disturbances and constant rhythms, it can also be set to 0.3 - 0.5 to suppress misjudgment behaviors of ineffective fluctuations.

[0073] The introduction of the spatial error suppression constant QE is used to prevent the denominator term in the formula from approaching zero when the error is extremely small, resulting in an abnormal amplification of the correction amplitude.

[0074] Preferably, the correction trigger determination and fine-tuning unit compares the obtained correction amplitude F with a preset amplitude threshold TF to determine whether to trigger trajectory correction;

[0075] Whether to trigger trajectory correction is obtained through the following matching method:

[0076] When the correction amplitude F < amplitude threshold TF, the trajectory correction is not triggered;

[0077] When the correction amplitude F ≥ amplitude threshold TF, the trajectory correction is triggered;

[0078] When the trajectory correction is triggered, a correction control vector CX is generated according to the correction amplitude F to adjust the angle θ, speed v, and acceleration a of the next bending point;

[0079] Specifically, when the system jointly determines the correction condition based on the disturbance energy offset function and the spatial error, it will generate a correction control vector CX for adjusting the control parameters of the next bending action to be executed. This control vector contains three parameters, namely the bending angle θ, bending speed v, and bending acceleration a, and the system automatically makes a linkage adjustment of these three parameters according to the level of disturbance intensity to achieve dynamic compensation for trajectory errors or mechanical disturbances.

[0080] When the system determines that the current disturbance intensity is high, it will moderately increase the bending angle θ, so that the actual angle of the pin after forming is slightly larger than the original set value, thus offsetting the end error caused by material springback or path deviation.

[0081] At the same time, the bending speed v will also be synchronously increased, aiming to complete the forming quickly under the condition of a short continuous action time of the disturbance, so as to reduce the influence of dynamic disturbance on the trajectory formation.

[0082] In addition, the system will also correspondingly increase the acceleration a, so that the bending action has a stronger inertial response ability in the initial stage, effectively hedging the initial path deviation caused by interference fluctuations.

[0083] The correction control vector CX is obtained through the following formula:

[0084] ;

[0085] In the formula, Co represents the initial control reference vector, which is the default control value combination adopted by the system without correction requirements under normal circumstances. kz represents the control gain factor, and tanh represents the hyperbolic tangent function.

[0086] Specifically, the initial control reference vector Co = [θ, v, a] is usually pre-loaded and obtained by the system during the task initialization stage. Its sources can include the standard parameter configuration provided by the manufacturing execution system, the historical average value extracted based on the trajectories of qualified batches, or the settings provided by the control program in the numerical control machine tool, which has repeatability and an industrial operation basis;

[0087] The initial control reference vector Co = [θ, v, a] represents the default control parameter combination preset by the system for each bending point without disturbance correction requirements, that is, the set of the standard bending angle θ, speed v, and acceleration a.

[0088] The control gain factor kz is used to adjust the response intensity of the disturbance correction instruction to the control vector. Its value can be set by the process engineer according to the material properties and equipment characteristics, generally selected in the range of 0.1 - 1.0 to ensure that the system has good flexible regulation ability and response adaptability.

[0089] Adjustment angle θ: Offset the standard bending angle to compensate for the target angle error caused by disturbance or springback;

[0090] Adjustment speed v: Appropriately decelerate to stabilize the control output and avoid exacerbating the disturbance during rapid processing;

[0091] Adjustment acceleration a: Reduce the sudden change of system inertia and control the dynamic stability of the bending power process.

[0092] Preferably, within a fixed period T, the feedback trend analysis and steady-state evaluation module collects and statistically processes the correction amplitude F in time series, extracts its volatility and stability characteristics, and outputs a continuous stability evaluation function G;

[0093] The stability evaluation function G is obtained through the following formula:

[0094] ;

[0095] In the formula, F(t) represents the correction amplitude at time t, and pF represents the average correction amplitude within the fixed period T;

[0096] Based on the historical evolution trend of the stability evaluation function G, compare it with the preset slight fluctuation boundary threshold Glow and critical instability boundary threshold Ghig to identify the perturbation region where the system is located, and automatically divide the current state into operating intervals;

[0097] The division of the operating interval is obtained through the following matching method:

[0098] When the stability evaluation function G < the slight fluctuation boundary threshold Glow, it represents the first operating interval, the steady state area;

[0099] When the slight fluctuation boundary threshold Glow ≤ the stability evaluation function G < the critical instability boundary threshold Ghig, it represents the second operating interval, the high perturbation response area;

[0100] When the stability evaluation function G ≥ the critical instability boundary threshold Ghig, it represents the third operating interval, the critical instability evolution area.

[0101] Preferably, the optimization strategy switching and task scheduling module fuses the obtained perturbation energy offset function D, correction amplitude F, and continuous stability evaluation function G to construct a composite strategy response index function H for reflecting the system operation;

[0102] Normalize the obtained perturbation energy offset function D, correction amplitude F, and continuous stability evaluation function G, convert them into dimensionless indexes together with log(D + 1), and perform harmonic weighing through the coefficient AO to ensure the consistency of the function H at the numerical calculation and physical interpretation levels;

[0103] The strategy response index function H is obtained through the following formula:

[0104] ;

[0105] In the formula, log represents the logarithmic function, and AO represents the evaluation trend response proportion coefficient;

[0106] Specifically, the strategic response exponential function H is a normalized trend function used to fuse processing perturbations, execution feedback intensity, and control trend stability, representing the response urgency of the current system operating state. All functions involved in the calculation (perturbation energy offset function D, correction amplitude F, and continuous stability evaluation function G) have unified the expression scale through dynamic constraint methods. Therefore, H can be used as an evaluation basis for determining whether to trigger a strategy switch for the current processing task.

[0107] Compare the obtained strategic response exponential function H with the preset low strategic response threshold Hth1 and high strategic response threshold Hth2, and dynamically select the strategy execution mode;

[0108] The selection of the strategy execution mode is obtained through the following matching method:

[0109] When the strategic response exponential function H < low strategic response threshold Hth1, it represents the standard mode, and no strategy switch needs to be executed;

[0110] When the low strategic response threshold Hth1 ≤ strategic response exponential function H < high strategic response threshold Hth2, it represents the compensation mode, and the angle θ, speed v, and acceleration a are corrected, and the processing beat is reduced to suppress the accumulation of perturbations;

[0111] When the high strategic response threshold Hth2 ≥ strategic response exponential function H, it represents the delay mode, pauses compensation, and monitors the correction trend.

[0112] The current sensor pin bending processing control device includes a bending control device body and a controller. The controller includes a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, the functions of the system are realized.

[0113] Specifically, the perturbation parameters and decision functions used by each control module of the present invention are all constructed based on the collectable original physical quantities, and the index dimensions are unified through normalization and exponential coupling methods. The correction amplitude F, continuous stability evaluation function G, and strategic response exponential function H output by the system are all explicit numerical values, and are equipped with threshold decision rules and strategic response mechanisms.

[0114] The present invention provides a current sensor pin bending processing control system and processing equipment, which have the following beneficial effects:

[0115] (1) During the operation of the system, through the synchronous acquisition and cleaning of non-contact perturbation signals such as bending acceleration ZWa, pin surface contact impedance perturbation ZBd, and friction sound spectrum response ZMc by the perturbation signal acquisition and preprocessing module, the system can obtain the core state information reflecting structural abnormalities and deformation trends without interrupting the processing, thus avoiding the problem of delayed response caused by the traditional system's inability to perceive early perturbations.

[0116] The perturbation energy modeling and atlas generation module establishes a perturbation atlas based on multi-source dynamic signals, comprehensively reflecting the energy aggregation process and evolution trend, enabling the system to identify "precursors of instability that have not yet manifested as offsets" and achieving early intervention for subtle anomalies in the processing operation. The bending path error mapping module significantly improves the positioning ability of the key points of the bending trajectory deformation through the dynamic mapping of spatial errors and the mid-section enhancement recognition strategy, solves the problem that the error judgment of existing equipment is too average, and thus improves the shaping accuracy and structural consistency.

[0117] (2) By fusing and collecting three types of perturbation parameters with different physical dimensions and response mechanisms, namely the bending acceleration ZWa, the perturbation of the pin surface contact impedance ZBd, and the friction sound spectrum response ZMc, the perception coverage of the system for multi-source abnormal phenomena in the processing process is significantly expanded, making up for the recognition blind spots of traditional systems relying on single force or displacement signals, and enhancing the sensitivity to non-explicit perturbation characteristics. Through the non-linear interaction modeling of the three perturbation factors by the perturbation coupling strength index Ψ, the system can not only identify single-variable fluctuations but also capture the co-evolution trend between variables. This structure enables the system to have the ability to identify the trends of structural imbalance and coupling intensification of perturbations in advance, with higher fault foresight and active response capabilities.

[0118] (3) By introducing a non-linear weighting function in the error calculation, the system gives higher detection weights to the errors in the deformation-sensitive areas of the bending path, such as the mid-bending section and the turning point, solves the problem that the traditional average error index is insensitive at key positions, ensures that the errors in key areas can be amplified and recognized, and improves the risk recognition accuracy. The system can output a quantitative spatial error index according to the dynamic comparison results of each processing trajectory and the standard model, which is particularly suitable for the dynamic analysis of different trajectories under multiple batches, multiple models or different elastic materials, effectively solving the problem that traditional static templates are difficult to adapt to the needs of flexible manufacturing. The spatial error E is not only used as an independent evaluation index but also as the input basis for subsequent correction amplitude functions and trend evaluation functions. The high-precision and high-dimensional error data stream constructs a precise and controllable feedback closed-loop mechanism for the entire control system, improving the response agility of the system to small offsets.

[0119] (4) By performing temporal sampling and fluctuation analysis on the correction amplitude within a fixed period T, the system can extract the stability change trend from the perspective of overall evolution and achieve quantitative modeling of the disturbance volatility. This processing mechanism enables the system to no longer rely solely on instantaneous state judgment, but to gain insights into the evolution pattern of disturbances over a longer period, thereby identifying in advance the potential risks of small fluctuations accumulating to instability. By comparing the stability function G with the boundary threshold to divide into three operating states: steady state, high disturbance response, and critical instability, the system realizes the dynamic classification and perception of the operating environment, providing a basis for the differential triggering of subsequent control actions. This mechanism breaks through the drawbacks of traditional control systems such as "single state and rigid response", and strengthens the elastic response ability to different disturbance intensities. BRIEF DESCRIPTION OF THE DRAWINGS

[0120] Figure 1 is a schematic diagram of the block diagram process of the current sensor pin bending processing control system of the present invention;

[0121] Figure 2 is a framework diagram of the current sensor pin bending processing control device of the present invention;

[0122] Figure 3 is a schematic diagram of the process for obtaining the strategy response index of the present invention;

[0123] Figure 4 is a line graph of the micro-perturbation coupling strength index of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0124] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0125] Embodiment 1

[0126] The present invention provides a current sensor pin bending processing control system. Please refer to Figures 1 to 4 , which includes a disturbance signal acquisition and preprocessing module, a micro-perturbation energy modeling and spectrum generation module, a bending path error mapping module, a real-time correction control module, a feedback trend analysis and steady-state evaluation module, and an optimization strategy switching and task scheduling module;

[0127] The disturbance signal acquisition and preprocessing module samples the real-time state data during the processing of the current sensor pins through a sensor, fits it into the original data set SM, and performs preprocessing to obtain the pin data set ZM;

[0128] The perturbation energy modeling and atlas generation module analyzes the pin dataset ZM, constructs a perturbation energy atlas, and calculates and obtains the perturbation energy offset function D;

[0129] The bending path error mapping module receives the current machining trajectory data according to the obtained pin dataset ZM, performs a spatial error mapping with the pre-stored standard trajectory, and obtains the spatial error E;

[0130] The real-time correction control module calculates and obtains the correction amplitude F according to the obtained energy offset function D and spatial error E; the feedback trend analysis and steady-state evaluation module processes the continuous change trend of the correction amplitude F within a fixed period T, obtains the continuous stability evaluation function G, and identifies whether it enters the high-perturbation and critical instability regions;

[0131] The optimization strategy switching and task scheduling module fuses the obtained perturbation energy offset function D, correction amplitude F, and continuous stability evaluation function G, calculates the strategy response index function H, and executes dynamic bending strategy switching.

[0132] In this embodiment, through the synchronous acquisition and cleaning of non-contact perturbation signals such as the bending acceleration ZWa, the pin surface contact impedance perturbation ZBd, and the friction sound spectrum response ZMc by the perturbation signal acquisition and preprocessing module, the system can obtain the core state information reflecting the structural abnormality and deformation trend without interrupting the machining, thus avoiding the problem of delayed response caused by the traditional system's inability to perceive early perturbations.

[0133] The perturbation energy modeling and atlas generation module establishes a perturbation atlas based on multi-source dynamic signals, comprehensively reflecting the energy aggregation process and evolution trend, enabling the system to identify "the precursor of instability that has not yet manifested as an offset" and realizing early intervention for subtle abnormalities in the machining operation. The bending path error mapping module significantly improves the positioning ability of the key points of the bending trajectory deformation through the dynamic mapping of spatial errors and the mid-section enhancement recognition strategy, solves the problem of overly average error judgment of existing equipment, and thus improves the shaping accuracy and structural consistency.

[0134] The real-time correction control module constructs a correction instruction by combining energy perturbation and geometric error, realizing a self-adjusting mechanism of "running while compensating". Compared with the traditional rigid control scheme that requires shutdown and debugging, this system supports flexible dynamic correction and has strong anti-perturbation stability. The feedback trend analysis and steady-state evaluation module evaluates the volatility of the correction behavior within a fixed period, can capture the critical turning point of the perturbation evolution trend in real time, prevent the "latent cumulative perturbation" from turning into a sudden abnormality, and thus improve the robustness and predictability of the overall system operation.

[0135] Embodiment 2

[0136] This embodiment is an explanatory description based on Embodiment 1. Please refer toFigure 1 and Figure 4 , specifically: the perturbation signal acquisition and preprocessing module includes a perturbation state signal acquisition unit and a cleaning and normalization unit;

[0137] The perturbation state signal acquisition unit is responsible for collecting state data through sensors during the pin bending process, including bending acceleration ZWa, pin surface contact impedance perturbation ZBd, and friction sound spectrum response ZMc, and fitting them into the original data set SM;

[0138] Among them, the bending acceleration ZWa is sampled by a high-frequency laser displacement sensor and obtained through first-order differentiation;

[0139] The pin surface contact impedance perturbation ZBd is obtained through a current and voltage composite probe and by collecting the instantaneous change in ohmic value;

[0140] The friction sound spectrum response ZMc is collected by a piezoelectric acoustic emission sensor and obtained through the frequency spectrum intensity after FFT;

[0141] The cleaning and normalization unit performs noise reduction and normalization processing on the obtained original data set SM to obtain the pin data set ZM;

[0142] Noise reduction is achieved by using a sliding filtering method to remove noise from the original data set SM;

[0143] Normalization processing is performed on the original data set SM using the Min-Max linear normalization method to obtain the pin data set ZM;

[0144] The pin data set ZM is obtained through the following formula:

[0145] ;

[0146] In the formula, ZMo represents the o-th item of data in the pin data set ZM, SMo represents the o-th item of data in the original data set SM, minSMo represents the valley value of the o-th item of data in the original data set SM, and maxSMo represents the peak value of the o-th item of data in the original data set SM.

[0147] The perturbation energy modeling and spectrum generation module includes a perturbation coupling index construction unit and a perturbation energy offset function generation unit;

[0148] The perturbation coupling index construction unit constructs a non-linear interaction function based on the obtained pin data set ZM to capture the joint coupling behavior among the three perturbation quantities and obtain the perturbation coupling strength index Ψ;

[0149] The perturbation coupling strength index Ψ is obtained through the following formula:

[0150] ;

[0151] In the formula, d represents the derivative symbol, ZWa(t) represents the bending acceleration at time t, ZBd(t) represents the pin surface contact impedance perturbation at time t, ZMc(t) represents the frictional sound spectrum response at time t, and cos() represents the cosine function;

[0152] Specific example:

[0153] Table 1: Perturbation coupling strength index calculation table;

[0154] Time step Bending acceleration ZWa Pin surface contact impedance perturbation ZBd Frictional sound spectrum response ZMc Perturbation coupling strength index Ψ t1 0.45 0.60 0.70 0.459 t2 0.48 0.58 0.72 0.436 t3 0.50 0.55 0.75 0.403 t4 0.52 0.53 0.74 0.391 t5 0.49 0.57 0.71 0.433

[0155] The perturbation energy offset function generation unit performs integral modeling on the perturbation behavior according to the obtained perturbation coupling strength index Ψ, obtains the perturbation energy offset function D, and compares it with the preset offset threshold TD to construct an energy map;

[0156] The perturbation energy offset function D is obtained through the following formula:

[0157] ;

[0158] In the formula, represents the steady-state perturbation accumulation coefficient, represents the dynamic perturbation evolution coefficient, and Ψ(t) represents the perturbation coupling strength index at time t;

[0159] The energy map is obtained through the following matching method:

[0160] When the perturbation energy offset function D ≤ the offset threshold TD, it indicates that the offset is stable, and the energy map is a stable straight line;

[0161] When the perturbation energy offset function D > the offset threshold TD, it indicates that the offset is abnormal, and the energy map shows a cumulative trend and is an ascending straight line.

[0162] In this embodiment, by fusing and collecting three types of perturbation parameters with different physical dimensions and response mechanisms, namely the bending acceleration ZWa, the pin surface contact impedance perturbation ZBd, and the frictional sound spectrum response ZMc, the perception coverage of the system for multi-source abnormal phenomena during the processing process is significantly expanded, the recognition blind area of the traditional system relying on a single force or displacement signal is compensated, and the sensitivity to non-explicit perturbation characteristics is improved. Through the non-linear interaction modeling of the three perturbation factors by the perturbation coupling strength index Ψ, the system can not only identify single-variable fluctuations but also capture the co-evolution trend between variables. This structure enables the system to have the ability to identify the structural imbalance and coupling intensification trend of perturbations in advance, and has higher fault foresight and active response capabilities.

[0163] After the original signal is collected, sliding filtering and noise reduction as well as Min-Max normalization processing are introduced, effectively suppressing the influence of signal spike noise, sampling errors, and unit differences on the stability of the model, thereby ensuring the comparability and computational reliability of the data used in perturbation modeling and enhancing the engineering practicability of the system. The system expresses the cumulative trend of disturbances during the processing in the form of a spectrum, not only quantifying the "stable" and "unstable" states of the processing, but also enabling the control system to have the ability to autonomously identify the offset trend based on the spectrum morphology. Compared with the traditional control logic that relies on threshold judgment, the energy spectrum has more intuitive, continuous, and evolving recognition advantages.

[0164] This embodiment can continuously acquire and update the disturbance spectrum without pausing the processing or relying on manual intervention, ensuring that the system can stably identify the offset evolution trend even under high-speed processing conditions, realizing the true meaning of "identifying while running" and significantly reducing the risk of missed detection. The disturbance energy offset function, as the quantitative discrimination index in the first stage of the system, directly serves the subsequent spatial trajectory correction and strategy switching judgment modules, providing strong support for forming a closed-loop process with physical rationality, data logical continuity, and control predictability for the entire control system.

[0165] Embodiment 3

[0166] This embodiment is an explanatory description based on Embodiment 2. Please refer to Figure 1 , specifically: The bending path error mapping module includes a trajectory reconstruction and attitude synchronization unit and a spatial error calculation unit;

[0167] The trajectory reconstruction and attitude synchronization unit records the acquisition trajectory of the pin dataset ZM, and performs dynamic attitude reconstruction and standard spatio-temporal alignment on the trajectory point data during pin processing to obtain the trajectory point sequence Pact;

[0168] The trajectory point sequence Pact is obtained through the following formula:

[0169] Pact(t) = {xi(t), yi(t), zi(t)|i = 1, 2,..., N};

[0170] In the formula, Pact(t) represents the trajectory point sequence at time t, (xi(t), yi(t), zi(t)) represents the three-dimensional spatial position of the pin end during the bending process, i represents the sampling serial number, and N represents the number of trajectory points;

[0171] By introducing the local rotation registration matrix XR and the displacement vector XT, rigid registration processing of the pin path and the standard trajectory is carried out, and the processing formula is as follows:

[0172] .

[0173] The spatial error calculation unit evaluates the geometric offset intensity ep of each point through the Euclidean space difference based on the trajectory point sequence Pact(t) at the indicated time t, and introduces a path deformation sensitivity exponential function to nonlinearly amplify the high-error section to obtain the spatial error E.

[0174] According to the three-dimensional spatial position (xi(t), yi(t), zi(t)) of the pin end during the bending process, a three-dimensional error vector is constructed , and the offset intensity ep is obtained;

[0175] Three-dimensional error vector is obtained through the following formula:

[0176] ;

[0177] In the formula, represents the three-dimensional error vector of the i-th trajectory point at time t, and (oxi(t), oyi(t), ozi(t)) represents the spatial coordinates of the i-th point in the standard reference trajectory;

[0178] The offset intensity ep is obtained through the following formula:

[0179] ;

[0180] In the formula, epi(t) represents the offset intensity of the i-th trajectory point at time t;

[0181] The spatial error E is obtained through the following formula:

[0182] ;

[0183] In the formula, k represents the path deformation amplification coefficient, and sin represents the sine function.

[0184] In this embodiment, through the trajectory reconstruction and attitude synchronization unit, the real-time spatial motion trajectory of the pin end is recorded and dynamically restored. The system can completely restore the actual motion path during the processing, avoid data breakpoints or distortions caused by sensor delays or spatial drifts, and enhance the stability of trajectory recognition under dynamic changing conditions.

[0185] In this embodiment, by introducing a rotation matrix and a displacement vector to perform rigid registration on the trajectory point sequence, the processing trajectory and the standard trajectory achieve consistent coordinate systems in the three-dimensional space, thereby avoiding the false deviation caused by coordinate drift in traditional error judgment, and significantly improving the credibility and traceability of error measurement. By constructing a three-dimensional error vector point by point and calculating its spatial offset intensity, the system can not only obtain the overall trajectory error, but also accurately identify the abnormal offset of a specific trajectory point during the processing, realizing the technological evolution from "overall error judgment" to "local dynamic recognition".

[0186] In this embodiment, by introducing a non - linear weighting function into the error calculation, the system gives a higher detection weight to the errors in the deformation - sensitive areas of the bending path, such as the middle section of the bend and the turning point, etc., solving the problem that the traditional average - type error index is insensitive at key positions, ensuring that the errors in key areas can be amplified and recognized, and improving the risk - recognition accuracy. The system can output a quantitative spatial error index according to the dynamic comparison results of each processing trajectory and the standard model, which is especially suitable for the dynamic analysis of different trajectories under multiple batches, multiple models or different elastic materials, effectively solving the problem that traditional static templates are difficult to adapt to the needs of flexible manufacturing. The spatial error E is not only used as an independent evaluation index, but also can be used as the input basis for subsequent correction - amplitude functions and trend - evaluation functions. The high - precision and high - dimensional error data stream constructs a precise and controllable feedback closed - loop mechanism for the entire control system, improving the system's response agility to small offsets.

[0187] Embodiment 4

[0188] This embodiment is an explanatory description carried out in Embodiment 3. Please refer to Figure 1 and Figure 3 , specifically: The real - time correction control module includes a dynamic correction intensity calculation unit and a correction trigger determination and fine - tuning unit;

[0189] The dynamic correction intensity calculation unit calculates and obtains the correction amplitude F according to the obtained energy offset function D and spatial error E;

[0190] The correction amplitude F is obtained through the following formula:

[0191] ;

[0192] In the formula, λ represents the control - adjustment sensitivity coefficient, μ represents the evolution - trend response weight, D(t) represents the energy offset function at time t, E(t) represents the spatial error at time t, and QE represents a non - zero constant.

[0193] The correction trigger determination and fine - tuning unit compares the obtained correction amplitude F with a preset amplitude threshold TF to determine whether to trigger trajectory correction;

[0194] Whether to trigger trajectory correction is obtained through the following matching method:

[0195] When the correction amplitude F < amplitude threshold TF, the trajectory correction is not triggered;

[0196] When the correction amplitude F ≥ amplitude threshold TF, the trajectory correction is triggered;

[0197] When the trajectory correction is triggered, a correction control vector CX is generated according to the correction amplitude F to adjust the angle θ, speed v, and acceleration a of the next bending point.

[0198] The corrected control vector CX is obtained through the following formula:

[0199] ;

[0200] In the formula, Co represents the initial control reference vector, kz represents the control gain factor, and tanh represents the hyperbolic tangent function.

[0201] In this embodiment, the energy disturbance behavior and the spatial error trajectory behavior in the processing process are coupled and judged, avoiding the problems of slight errors being mis-triggered or superposition instability being ignored, and fundamentally improving the judgment accuracy and logical scientificity of correction triggering. By introducing regulation parameters such as control sensitivity and response weight, the system realizes continuous quantitative evaluation of the correction amplitude, enables the control strategy to have the ability of "gradual adjustment", breaks through the previous binary correction logic of "either this or that", and shows higher robustness and flexible control level in complex processing scenarios.

[0202] This embodiment sets up an accurate discrimination mechanism between the dynamic correction intensity and the amplitude threshold, filters false feedback caused by tiny disturbances from the source, enables the system to truly focus on the actual deviation scenarios that need to be intervened, and effectively improves the execution efficiency and processing rhythm rationality of the control system. When the system triggers a correction, it can automatically generate a new control vector based on the correction intensity, comprehensively adjust the angle, speed, and acceleration of the next bending point, and form a "precision control chain" dominated by data, breaking through the control defects of only being able to adjust a single angle or only based on static set values in the past.

[0203] In the process of constructing the control instruction, this embodiment introduces a non-linear function to adjust the gain amplitude, so that the system can maintain smooth and stable control output even under high disturbance intensity, avoid a new round of errors or mechanical fatigue caused by excessive correction, and thus improve the service life and long-term stability of the equipment. All correction behaviors are completed based on online calculation and prediction generation. The entire process does not require interrupting the processing process or pausing the mechanical action, and can automatically adjust the control parameters before each bending point, greatly improving the operation efficiency and intelligent level of the system, which is a key manifestation of the transition from "post-response compensation" to "predictive pre-adjustment".

[0204] Embodiment 5

[0205] This embodiment is an explanatory description based on Embodiment 4. Please refer to Figure 3 , specifically: within a fixed period T, the feedback trend analysis and steady-state evaluation module conducts time-series collection and statistical processing on the correction amplitude F, extracts its volatility and stability characteristics, and outputs a continuous stability evaluation function G;

[0206] The stability evaluation function G is obtained through the following formula:

[0207] ;

[0208] Wherein, F(t) represents the correction amplitude at time t, and pF represents the average correction amplitude within the fixed period T;

[0209] Based on the historical evolution trend of the stability evaluation function G, compare it with the preset slight fluctuation boundary threshold Glow and the critical instability boundary threshold Ghig to identify the perturbation region where the system is located, and automatically divide the current state into an operating interval;

[0210] The division of the operating interval is obtained by matching in the following way:

[0211] When the stability evaluation function G < the slight fluctuation boundary threshold Glow, it represents the first operating interval, the steady state region;

[0212] When the slight fluctuation boundary threshold Glow ≤ the stability evaluation function G < the critical instability boundary threshold Ghig, it represents the second operating interval, the high perturbation response region;

[0213] When the stability evaluation function G ≥ the critical instability boundary threshold Ghig, it represents the third operating interval, the critical instability evolution region.

[0214] The optimization strategy switching and task scheduling module fuses the obtained perturbation energy offset function D, correction amplitude F, and continuous stability evaluation function G to construct a composite strategy response index function H for reflecting the system operation;

[0215] The strategy response index function H is obtained by the following formula:

[0216] ;

[0217] Wherein, log represents the logarithmic function, and AO represents the evaluation trend response ratio coefficient;

[0218] Compare the obtained strategy response index function H with the preset low strategy response threshold Hth1 and high strategy response threshold Hth2, and dynamically select the strategy execution mode;

[0219] The selection of the strategy execution mode is obtained by matching in the following way:

[0220] When the strategy response index function H < the low strategy response threshold Hth1, it represents the standard mode, and no strategy switching needs to be executed;

[0221] When the low strategy response threshold Hth1 ≤ the strategy response index function H < the high strategy response threshold Hth2, it represents the compensation mode, and the angle θ, speed v, and acceleration a are corrected;

[0222] When the high strategy response threshold Hth2 ≥ the strategy response exponential function H, it indicates the delay mode, pauses compensation, and monitors the correction trend.

[0223] In this embodiment, by performing sequential sampling and fluctuation analysis on the correction amplitude within a fixed period T, the system can extract the stability change trend from the perspective of overall evolution and achieve quantitative modeling of the disturbance volatility. This processing mechanism enables the system to no longer rely solely on instantaneous state judgment but to gain insight into the evolution pattern of disturbances over a longer period, thereby identifying in advance the potential risks of small fluctuations accumulating to instability. By comparing the stability function G with the boundary threshold to divide into three operating states: steady state, high disturbance response, and critical instability, the system realizes the dynamic classification and perception of the operating environment, providing a basis for the differential triggering of subsequent control actions. This mechanism breaks through the drawbacks of traditional control systems such as "single state and rigid response" and enhances the elastic response ability to different disturbance intensities.

[0224] The system integrates three core elements, namely the disturbance energy D, the correction intensity F, and the stability evaluation function G, into the control logic to construct a composite response index H that reflects the comprehensive state of the operating environment, effectively enhancing the control decision-making layer's ability to integrate and judge multi-source data and upgrading the strategy switching logic from "single-factor driven" to "multi-factor fusion and collaborative driven". The system dynamically matches different operating modes according to the level of the response index H, including the standard mode, the compensation mode, and the delay mode. It can not only perform control responses of different depths according to the disturbance degree but also automatically switch to the observation and buffering state when identifying the instability evolution trend, preventing the system from entering the abnormal working condition area of excessive correction or frequent oscillation and enhancing the robustness of the overall control system.

[0225] In this embodiment, by connecting the stability feedback function with the correction strategy execution mechanism, a full-process linkage control closed-loop of "disturbance monitoring - trend analysis - strategy generation - execution control" for the processing system is realized. This mechanism endows the system with the ability of self-regulation, self-diagnosis, and self-correction in the face of a changing environment, which is a typical embodiment of the upgrade from "single-loop control" to "multi-level intelligent closed-loop control". By using the stable trend function and the logarithmic response index model in combination, the system can identify and quantify sudden disturbances and critical precursors in the short term, providing sufficient reaction time for delay strategy switching and enhancing the system's anti-sudden disturbance and adaptive recovery capabilities, which is a key technical means to ensure the stable operation of high-precision processing processes.

[0226] Embodiment 6

[0227] For the current sensor pin bending processing control system and processing equipment, please refer to Figure 2, specifically: it includes a bending control device body and a controller. The controller includes a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, the functions of the system are realized.

[0228] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. Current sensor pin bending processing control system, characterized in that: It includes a disturbance signal acquisition and preprocessing module, a perturbation energy modeling and spectrum generation module, a bending path error mapping module, a real-time correction control module, a feedback trend analysis and steady-state evaluation module, and an optimization strategy switching and task scheduling module; The disturbance signal acquisition and preprocessing module samples the real-time state data during the pin machining process of the current sensor through a sensor, fits it into the original data set SM, and performs preprocessing to obtain the pin data set ZM; The perturbation energy modeling and spectrum generation module analyzes the pin data set ZM, constructs a perturbation energy spectrum, and calculates and obtains the perturbation energy offset function D; The bending path error mapping module receives the current machining trajectory data according to the obtained pin data set ZM, and performs a spatial error mapping with the pre-stored standard trajectory to obtain the spatial error E; The real-time correction control module calculates and obtains the correction amplitude F according to the obtained energy offset function D and spatial error E; The feedback trend analysis and steady-state evaluation module processes the continuous change trend of the correction amplitude F within a fixed period T, obtains the continuous stability evaluation function G, and identifies whether it enters the high perturbation and critical instability regions; The optimization strategy switching and task scheduling module fuses the obtained perturbation energy offset function D, correction amplitude F, and continuous stability evaluation function G, calculates the strategy response index function H, and executes dynamic bending strategy switching.

2. The current sensor pin bending processing control system according to claim 1, characterized in that: The disturbance signal acquisition and preprocessing module includes a disturbance state signal acquisition unit and a cleaning and normalization unit; The disturbance state signal acquisition unit is responsible for collecting state data through a sensor during the pin bending process, including the bending acceleration ZWa, the pin surface contact impedance perturbation ZBd, and the friction sound spectrum response ZMc, and fitting it into the original data set SM; Among them, the bending acceleration ZWa is sampled by a high-frequency laser displacement sensor and obtained through order differentiation; The pin surface contact impedance perturbation ZBd is obtained by a current and voltage composite probe and collecting the instantaneous Ohm value change; The friction sound spectrum response ZMc is collected by a piezoelectric acoustic emission sensor and obtained through the frequency spectrum intensity after FFT; The cleaning and normalization unit performs noise reduction and normalization processing on the obtained original data set SM to obtain the pin data set ZM; The noise reduction is performed by using a sliding filtering method to remove noise from the original data set SM; The normalization processing is performed by using the Min-Max linear normalization method to normalize the original data set SM to obtain the pin data set ZM; The pin data set ZM is obtained through the following formula: ； In the formula, ZMo represents the o-th data in the pin data set ZM, SMo represents the o-th data in the original data set SM, minSMo represents the valley value of the o-th data in the original data set SM, and maxSMo represents the peak value of the o-th data in the original data set SM.

3. The current sensor pin bending processing control system according to claim 2, wherein: The perturbation energy modeling and spectrum generation module includes a perturbation coupling index construction unit and a perturbation energy offset function generation unit; The perturbation coupling index construction unit constructs a non-linear interaction function according to the obtained pin data set ZM, captures the joint coupling behavior between the three perturbation quantities, and obtains the perturbation coupling strength index Ψ; The perturbation coupling strength index Ψ is obtained through the following formula: ； In the formula, d represents the derivative symbol, ZWa(t) represents the bending acceleration at time t, ZBd(t) represents the pin surface contact impedance perturbation at time t, ZMc(t) represents the friction sound spectrum response at time t, and cos() represents the cosine function; The perturbation energy offset function generation unit performs integral modeling on the perturbation behavior according to the obtained perturbation coupling strength index Ψ to obtain the perturbation energy offset function D, and compares it with the preset offset threshold TD to construct an energy spectrum; The perturbation energy offset function D is obtained through the following formula: ； In the formula, represents the steady-state perturbation accumulation coefficient, represents the dynamic perturbation evolution coefficient, and Ψ(t) represents the perturbation coupling strength index at time t; The energy spectrum is obtained through the following matching method: When the perturbation energy offset function D ≤ the offset threshold TD, it indicates that the offset is stable, and the energy spectrum is a stable straight line; When the perturbation energy offset function D > the offset threshold TD, it indicates that the offset is abnormal, and the energy spectrum shows a cumulative trend and is an ascending straight line.

4. The current sensor pin bending processing control system according to claim 1, characterized in that: The bending path error mapping module includes a trajectory reconstruction and attitude synchronization unit and a spatial error calculation unit; The trajectory reconstruction and attitude synchronization unit records the acquisition trajectory of the pin dataset ZM, and performs dynamic attitude reconstruction and standard spatio-temporal alignment on the trajectory point data during pin processing to obtain the trajectory point sequence Pact; The trajectory point sequence Pact is obtained through the following formula: Pact(t) = {xi(t), yi(t), zi(t)|i = 1, 2,..., N}; In the formula, Pact(t) represents the trajectory point sequence at time t, (xi(t), yi(t), zi(t)) represents the three-dimensional spatial position of the pin end during the bending process, i represents the sampling serial number, and N represents the number of trajectory points; By introducing the local rotation registration matrix XR and the displacement vector XT, rigid registration processing of the pin path and the standard trajectory is performed, and the processing formula is as follows: 。 5. The current sensor pin bending processing control system according to claim 4, characterized in that: The spatial error calculation unit evaluates the geometric offset intensity ep of each point according to the trajectory point sequence Pact(t) at time t through the Euclidean space difference, and introduces a path deformation sensitive index function to non-linearly amplify the high-error section to obtain the spatial error E; Construct a three-dimensional error vector based on the three-dimensional spatial position (xi(t), yi(t), zi(t)) of the pin end during the bending process , and obtain the offset intensity ep; Three-dimensional error vector Obtained by the following formula: ； wherein, represents the three-dimensional error vector of the i-th trajectory point at time t, and (oxi(t), oyi(t), ozi(t)) represents the spatial coordinates of the i-th point in the standard reference trajectory; The offset intensity ep is obtained through the following formula: ； In the formula, epi(t) represents the offset intensity of the i-th trajectory point at time t; The spatial error E is obtained through the following formula: ； In the formula, k represents the path deformation amplification coefficient, sin represents the sine function, π represents the pi, and its value is 3.

14.

6. The current sensor pin bending processing control system according to claim 5, wherein: The real-time correction control module includes a dynamic correction intensity calculation unit and a correction trigger determination and fine-tuning unit; The dynamic correction intensity calculation unit calculates and obtains the correction amplitude F according to the obtained energy offset function D and spatial error E; The correction amplitude F is obtained through the following formula: ； In the formula, λ represents the control adjustment sensitivity coefficient, μ represents the evolution trend response weight, D(t) represents the energy offset function at time t, E(t) represents the spatial error at time t, and QE represents a non-zero constant.

7. The current sensor pin bending processing control system according to claim 6, characterized in that: The correction trigger determination and fine-tuning unit compares the obtained correction amplitude F with the preset amplitude threshold TF to determine whether to trigger trajectory correction; Whether the trajectory correction is triggered is obtained through the following matching method: When the correction amplitude F < the amplitude threshold TF, the trajectory correction is not triggered; When the correction amplitude F ≥ amplitude threshold TF, trajectory correction is triggered; When trajectory correction is triggered, a correction control vector CX is generated according to the correction amplitude F to adjust the angle θ, speed v, and acceleration a of the next bending point; The correction control vector CX is obtained through the following formula: ； In the formula, Co represents the initial control reference vector, kz represents the control gain factor, and tanh represents the hyperbolic tangent function.

8. The current sensor pin bending processing control system according to claim 7, characterized in that: The feedback trend analysis and steady-state evaluation module collects and statistically processes the correction amplitude F in a fixed period T, extracts its volatility and stability characteristics, and outputs a continuous stability evaluation function G; The stability evaluation function G is obtained through the following formula: ； In the formula, F(t) represents the correction amplitude at time t, and pF represents the average correction amplitude within the fixed period T; Based on the historical evolution trend of the stability evaluation function G, it is compared with the preset slight fluctuation boundary threshold Glow and critical instability boundary threshold Ghig to identify the perturbation region where the system is located, and the current state is automatically divided into operating intervals; The division of the operating interval is obtained by matching in the following way: When the stability evaluation function G < slight fluctuation boundary threshold Glow, it represents the first operating interval, the steady-state region; When the slight fluctuation boundary threshold Glow ≤ stability evaluation function G < critical instability boundary threshold Ghig, it represents the second operating interval, the high-perturbation response region; When the stability evaluation function G ≥ critical instability boundary threshold Ghig, it represents the third operating interval, the critical instability evolution region.

9. The current sensor pin bending processing control system according to claim 8, wherein: The optimization strategy switching and task scheduling module fuses the obtained perturbation energy offset function D, correction amplitude F, and stability evaluation function G to construct a composite strategy response index function H for reflecting the system operation; The strategy response index function H is obtained through the following formula: ； In the formula, log represents the logarithmic function, and AO represents the evaluation trend response proportion coefficient; The obtained strategy response index function H is compared with the preset low strategy response threshold Hth1 and high strategy response threshold Hth2, and the strategy execution mode is dynamically selected; The selection of the strategy execution mode is obtained by matching in the following way: When the strategy response index function H < low strategy response threshold Hth1, it represents the standard mode, and no strategy switching needs to be executed; When the low strategy response threshold Hth1 ≤ strategy response index function H < high strategy response threshold Hth2, it represents the compensation mode, and the angle θ, speed v, and acceleration a are corrected; When the high strategy response threshold Hth2 ≥ strategy response index function H, it represents the delay mode, pauses compensation, and monitors the correction trend.

10. Current sensor pin bending and processing control equipment, characterized in that: It includes the bending control device body and a controller. The controller includes a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it realizes the functions of the current sensor pin bending processing control system as described in any one of claims 1 to 9.

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