An intelligent car door handle assembly manufacturing analysis system

Abstract

The application discloses a kind of intelligent car's door handle accessory manufacturing analysis system, it is related to manufacturing analysis technical field, including: drive connection module, for in the injection mold cavity of door handle accessory, piezoelectric film is embedded, resistance wire is set on the back of injection mold cavity, piezoelectric film is connected voltage ripple drive circuit, resistance wire is connected resistance wire drive circuit;Timing synchronization module, for the voltage ripple component of bus voltage as the driving source of voltage ripple drive circuit, according to the pulse timing of voltage ripple component, the thermal excitation control timing of resistance wire drive circuit is handled synchronously;Signal calibration module, for calculating the real-time amplitude sequence of piezoelectric film, according to the time phase calibration of instantaneous heat flow of resistance wire to pulse timing, obtain the synchronous heat flow sequence of resistance wire;Correlation calculation module, for the cross-correlation calculation of synchronous heat flow sequence and real-time amplitude sequence, obtain correlation value.

Description

Technical Field

[0001] This invention relates to the field of manufacturing analysis technology, and in particular to a manufacturing analysis system for door handle components of intelligent vehicles. Background Technology

[0002] As intelligent vehicles evolve towards lightweighting and personalization, door handles, as high-frequency components for vehicle interaction, directly impact the overall vehicle quality and user tactile experience through their appearance, micro-texture, and assembly precision. Currently, the industry commonly employs micro-injection molding to form door handle components, and deploys multi-physics field excitation and sensing units within the mold cavity to simultaneously complete material filling, micro-texture replication, and dimension locking within a millisecond-level dynamic window.

[0003] However, existing injection molding quality control still suffers from the following shortcomings: traditional processes generally separate the mechanical vibration source and the thermal compensation unit, each relying on independent drive circuits and phase-locking mechanisms, making it difficult to maintain periodic-level synchronization between the thermal and force fields. Simultaneously, bus voltage ripple is often filtered out rather than utilized, causing the system to lose a natural synchronization reference, resulting in a mismatch between piezoelectric amplitude, local mold cavity temperature, and melt solidification window. When the vibration phase lags or the thermal compensation advances, micro-texture depth deviation and overall dimensional deviation are amplified, increasing scrap rates and delaying machine setup, failing to meet the stringent requirements of high-end intelligent car door handles for sub-micron-level texture consistency and tolerance closed-loop control. Therefore, there is an urgent need for a manufacturing analysis system that can synchronously drive the piezoelectric film and resistance wire using bus voltage ripple and predict deviations in real time during the molding cycle, eliminating the inherent phase difference in multi-physics field collaborative control and improving the timeliness and accuracy of quality prediction. Summary of the Invention

[0004] The purpose of this invention is to address the shortcomings of existing technologies in meeting the stringent requirements of submicron-level texture consistency and tolerance closed-loop for high-end smart car door handles, and to propose a manufacturing analysis system for smart car door handle components.

[0005] To address the problems existing in the prior art, the present invention adopts the following technical solution:

[0006] A manufacturing analysis system for door handle components of a smart car, comprising:

[0007] The drive connection module is used to embed a piezoelectric film in the injection mold cavity of the door handle accessory, and to set a resistance wire on the back of the injection mold cavity. The piezoelectric film is connected to the voltage ripple drive circuit, and the resistance wire is connected to the resistance wire drive circuit.

[0008] The timing synchronization module is used to use the voltage ripple component of the bus voltage as the driving source of the voltage ripple drive circuit, and to synchronize the thermal excitation control timing of the resistance wire drive circuit according to the pulse timing of the voltage ripple component.

[0009] The signal calibration module is used to calculate the real-time amplitude sequence of the piezoelectric film and to perform time phase calibration on the instantaneous heat flow of the resistance wire according to the pulse timing to obtain the synchronous heat flow sequence of the resistance wire.

[0010] The correlation calculation module is used to perform cross-correlation calculations on the synchronous heat flow sequence and the real-time amplitude sequence to obtain the correlation value;

[0011] The deviation prediction module is used to calculate the root mean square value of the voltage ripple component, and calculate the predicted micro-texture depth deviation and predicted size deviation of the door handle accessory based on the root mean square value and the correlation value.

[0012] The manufacturing decision module is used to determine whether to manufacture the door handle component based on the predicted microtexture depth deviation and the predicted dimensional deviation.

[0013] Preferably, the voltage ripple component of the bus voltage is used as the driving source of the voltage ripple driving circuit, including:

[0014] Within a preset time period, the bus voltage is collected at a fixed sampling frequency to obtain multiple sample voltage values ​​of the bus voltage.

[0015] The sample voltage values ​​are summed to obtain the total sample voltage of the bus voltage. The total sample voltage is then divided by the total number of sample voltage values ​​to obtain the average base voltage of the bus voltage.

[0016] The voltage ripple component of the bus voltage is obtained by subtracting the average base voltage from the bus voltage, and this voltage ripple component is used as the driving source for the voltage ripple drive circuit.

[0017] Preferably, the thermal excitation control timing of the resistance wire drive circuit is synchronized according to the pulse timing of the voltage ripple component, including:

[0018] The pulse timing features are extracted from the voltage ripple component using the Fast Fourier Transform, where the pulse timing features include the pulse frequency and duty cycle.

[0019] The pulse frequency is used as the thermal excitation reference frequency for the resistance wire drive circuit.

[0020] The duty cycle is converted into the pulse width modulation parameter of the resistance wire drive circuit, and the pulse width modulation parameter controls the energizing time of the resistance wire in each cycle.

[0021] Preferably, calculating the real-time amplitude sequence of the piezoelectric thin film includes:

[0022] Obtain the piezoelectric constant of the piezoelectric thin film;

[0023] Based on the linear relationship of the piezoelectric effect, the piezoelectric constant is multiplied by the voltage ripple component to obtain the instantaneous amplitude value at each sampling time;

[0024] Arrange all instantaneous amplitude values ​​in chronological order to obtain the real-time amplitude sequence.

[0025] Preferably, the instantaneous heat flux of the resistance wire is calibrated in time phase according to the pulse timing to obtain a synchronous heat flux sequence of the resistance wire, including:

[0026] To obtain the instantaneous heat flux of the resistance wire;

[0027] Calculate the phase shift of the instantaneous heat flux on the time axis based on the pulse timing;

[0028] Based on the phase offset, the instantaneous heat flow of the resistance wire is calibrated in time phase using a digital delay method to obtain the synchronous heat flow sequence of the resistance wire.

[0029] Preferably, cross-correlation calculations are performed on the synchronous heat flow sequence and the real-time amplitude sequence to obtain correlation values, including:

[0030] The cross-correlation coefficient algorithm is used to calculate the cross-correlation coefficient between the synchronous heat flux sequence and the real-time amplitude sequence. The formula for calculating the cross-correlation coefficient is as follows:

[0031]

[0032] In the formula, It is the cross-correlation coefficient. It is the first of the synchronous heat flow sequence A heat flux value, It is the mean of all heat flux values ​​in the synchronous heat flux sequence. It is the first of the real-time amplitude sequence An instantaneous amplitude value, It is the mean of all instantaneous amplitude values ​​in the real-time amplitude sequence. It is the total of heat flux value and instantaneous amplitude value. It is an identifier for heat flow value and instantaneous amplitude value.

[0033] Preferably, calculating the root mean square value of the voltage ripple component includes:

[0034] The discrete points of the voltage ripple component are extracted at fixed time intervals, and the discrete points are determined as the instantaneous values ​​of the voltage ripple component.

[0035] Square each instantaneous value to obtain the squared value, sum all the squared values ​​to obtain the summation result;

[0036] Divide the summation result by the total number of instantaneous values ​​to obtain the square mean of the voltage ripple component;

[0037] The root mean square of the squared mean is taken to obtain the root mean square value of the voltage ripple component.

[0038] Preferably, the predicted microtexture depth deviation and predicted size deviation of the door handle component are calculated based on the root mean square value and correlation value, including:

[0039] Set empirical coefficients for microtexture depth and size deviation;

[0040] Substituting the empirical coefficient of microtexture depth, root mean square value, and correlation value into the preset depth deviation formula, the predicted microtexture depth deviation is obtained. The preset depth deviation formula is as follows:

[0041]

[0042] In the formula, It predicts the depth deviation of microtextures. It is an empirical coefficient for microtexture depth. It is the root mean square value. It is the absolute value of the correlation value;

[0043] Substituting the empirical coefficient of dimensional deviation, the root mean square value, and the correlation value into the preset dimensional deviation formula, the predicted dimensional deviation is obtained. The preset dimensional deviation formula is as follows:

[0044]

[0045] In the formula, It predicts dimensional deviations. It is an empirical coefficient for dimensional deviation. It is the root mean square value. It is the absolute value of the correlation value.

[0046] Preferably, determining whether to manufacture the door handle component based on the predicted microtexture depth deviation and the predicted dimensional deviation includes:

[0047] Compare the predicted microtexture depth deviation with the first difference of the preset depth deviation threshold;

[0048] Compare the predicted size deviation with the second difference between the preset size deviation threshold;

[0049] If both the first and second differences are within the tolerance range, the predicted quality of the door handle component is deemed to be qualified, and the manufacturing of the door handle component is carried out.

[0050] If the first and second differences exceed the tolerance range, the predicted quality of the door handle component is deemed unqualified, and the manufacturing process for the door handle component will not be executed.

[0051] Compared with the prior art, the beneficial effects of the present invention are:

[0052] 1. In this invention, by embedding a piezoelectric thin film in the injection mold cavity and laying a resistance wire on the back, the voltage ripple signal in the injection molding machine bus is used as a common driving source and natural synchronization reference for both. This fundamentally eliminates the phase difference problem caused by the vibration actuator and thermal compensation unit relying on independent circuits in traditional processes. After extracting the pulse frequency and duty cycle of the voltage ripple using fast Fourier transform, it is directly mapped to the piezoelectric vibration frequency and resistance wire pulse width modulation parameters. This ensures that the force field and thermal field maintain a strict and consistent timing in each molding cycle, avoiding micro-texture distortion and dimensional drift caused by local overcooling or overheating, and realizing the co-source driving and synchronous control of multiple physical fields.

[0053] 2. Based on synchronous control, this invention further acquires the piezoelectric film amplitude sequence and the calibrated resistance wire heat flow sequence in real time, and quantifies the degree of coordination between the two through a cross-correlation algorithm. Then, it establishes a prediction model by combining the root mean square value of voltage ripple, and converts the energy intensity and coordination deviation into quantitative estimates of micro-texture depth deviation and overall size deviation. This model can complete online calculations by relying only on periodic signals, which significantly shortens the decision delay compared with traditional methods that rely on the entire pressure curve or offline big data training, and solves the pain point of existing technologies that are difficult to detect microscale forming defects in a timely manner.

[0054] 3. The system uses preset depth and dimensional tolerance thresholds as judgment criteria and directly feeds the prediction results back to the manufacturing decision-making level: when both deviations are within the allowable range, the part is automatically released; if they exceed the limits, a machine stop or parameter adaptive adjustment is immediately triggered. Through this closed-loop mechanism, the present invention achieves prior quality screening before part forming and dynamic compensation during the process, reducing scrap rate and machine setup time, and ensuring that intelligent car door handle accessories maintain submicron-level texture consistency and assembly accuracy under high-cycle production conditions. This solves the key problems of force-thermal coupling mismatch, quality prediction lag, and excessively long control cycle time in the background technology. Attached Figure Description

[0055] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0056] Figure 1 This is a functional block diagram of a manufacturing analysis system for door handle components of an intelligent vehicle, provided as an embodiment of the present invention. Detailed Implementation

[0057] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0058] Example: This example provides a manufacturing analysis system for door handle components of intelligent vehicles. See [link / reference]. Figure 1 ,include:

[0059] The drive connection module is used to embed a piezoelectric film in the injection mold cavity of the door handle accessory, and to set a resistance wire on the back of the injection mold cavity. The piezoelectric film is connected to the voltage ripple drive circuit, and the resistance wire is connected to the resistance wire drive circuit.

[0060] In detail, a piezoelectric film is embedded in the injection mold cavity of the door handle component, and the electrical interface of the piezoelectric film is electrically connected to the output terminal of the voltage ripple drive circuit to form a two-phase voltage ripple drive structure. During the processing of the injection mold cavity of the door handle component, the piezoelectric film is precisely embedded in a specific installation area of ​​the mold cavity, the electrical interface of the piezoelectric film is processed, and it is electrically connected to the output terminal of the voltage ripple drive circuit through a matching conductive connection component to ensure the reliability and stability of the connection. This allows the voltage ripple drive circuit to stably output a voltage signal to the piezoelectric film, and then utilizes the characteristics of the piezoelectric film in conjunction with the voltage ripple drive circuit to construct a two-phase voltage ripple drive structure.

[0061] In detail, the dual-phase voltage ripple drive structure is a power electronic drive architecture applied to the manufacturing of automotive door handle components. After a piezoelectric film is embedded in the injection mold cavity of the door handle component, two voltage ripple drive units with a specific phase relationship (e.g., a 180° phase difference) are constructed and electrically connected to the piezoelectric film's electrical interface to form a synergistic system. Utilizing the phase difference characteristics of the dual-phase voltage ripple drive units, the two ripple currents are staggered, offsetting some electrical signal fluctuations and reducing ripple interference during piezoelectric film vibration and heat flow compensation. This results in smoother piezoelectric film vibration and more uniform heat flow compensation; the distribution of the two drive energy paths can be adjusted according to the complex working conditions of automotive door handle manufacturing.

[0062] In detail, a phase change alloy microchannel is set on the back of the injection mold cavity, and a resistance wire is implanted within the microchannel. The two ends of the resistance wire are connected to the control terminal of the resistance wire drive circuit. The inlet and outlet of the phase change alloy microchannel are connected to the phase change material circulation system to form a pulse-synchronized thermal compensation channel. Using precision machining equipment, fine groove structures are milled or etched on the back of the injection mold cavity according to the planned path and dimensions for thermal compensation requirements of the door handle molding. Then, the phase change alloy material is placed into the grooves through casting, filling, or other methods. After curing and polishing, the alloy is tightly bonded to the back of the mold cavity, and the surface is smooth, forming a phase change alloy microchannel that can efficiently conduct and store heat. Next, a resistance wire is implanted inside the microchannel. During implantation, it is necessary to ensure that the resistance wire is neatly arranged and fits well against the inner wall of the microchannel to avoid short circuits or poor contact. Finally, the two ends of the resistance wire are led out and reliably connected to the control terminal of the resistance wire drive circuit to ensure stable signal transmission and precise control of the heating state of the resistance wire. Meanwhile, the inlet and outlet of the phase change alloy microchannel are connected to the phase change material circulation system to ensure that the phase change material can circulate smoothly in the microchannel. Through the heat absorption and release characteristics of the phase change material, combined with the active heating of the resistance wire, a pulse synchronous thermal compensation channel is formed. During the injection molding process of the door handle parts, thermal compensation is precisely applied according to the real-time thermal state to ensure the uniformity and stability of the temperature field in the mold cavity and meet the thermal environment requirements for the molding of the parts.

[0063] The timing synchronization module is used to use the voltage ripple component of the bus voltage as the driving source of the voltage ripple drive circuit, and to synchronize the thermal excitation control timing of the resistance wire drive circuit according to the pulse timing of the voltage ripple component.

[0064] In an embodiment of the present invention, the voltage ripple component of the bus voltage is used as the driving source of the voltage ripple driving circuit, including:

[0065] Within a preset time period, the bus voltage is collected at a fixed sampling frequency to obtain multiple sample voltage values ​​of the bus voltage.

[0066] The sample voltage values ​​are summed to obtain the total sample voltage of the bus voltage. The total sample voltage is then divided by the total number of sample voltage values ​​to obtain the average base voltage of the bus voltage.

[0067] The voltage ripple component of the bus voltage is obtained by subtracting the average base voltage from the bus voltage, and this voltage ripple component is used as the driving source for the voltage ripple drive circuit.

[0068] In detail, the bus voltage signal includes a base voltage component that maintains the basic operation of the system, and a voltage ripple component used to achieve functions such as precise driving of the piezoelectric film and thermal compensation coordinated control. The average base voltage reflects the average level of the bus voltage over a stable operating cycle, representing the basic voltage value required for normal system operation. By subtracting the pre-calculated average base voltage from the acquired real-time bus voltage, the basic stable component in the bus voltage can be removed, separating the voltage ripple component that reflects voltage fluctuation characteristics and is used to achieve multi-physics field coordinated control. The voltage ripple component strips away the basic stable component in the bus voltage, precisely retaining the signal that reflects the dynamic fluctuation characteristics of the voltage, which are highly compatible with the driving requirements of the piezoelectric film. The piezoelectric film requires a voltage signal with specific frequency and amplitude variations to generate corresponding vibrations, achieving precise embossing of the microtexture of the door handle. The dynamic characteristics of the voltage ripple component can directly provide a matching driving signal for the piezoelectric film, ensuring that the vibration frequency and amplitude of the piezoelectric film match the requirements of the microtexture forming process.

[0069] In embodiments of the present invention, the thermal excitation control timing of the resistance wire drive circuit is synchronized according to the pulse timing of the voltage ripple component, including:

[0070] The pulse timing features are extracted from the voltage ripple component using the Fast Fourier Transform, where the pulse timing features include the pulse frequency and duty cycle.

[0071] Specifically, the discretized voltage ripple component time-domain data is used as input, and a Fast Fourier Transform (FFT) algorithm is employed for spectral analysis. The FFT converts the time-domain signal into a frequency-domain signal, decomposing the voltage ripple component into a superposition of different frequency components. The amplitude and phase information of each frequency component are calculated. Based on the frequency component with the largest amplitude in the spectrum, the pulse frequency of the voltage ripple is determined, corresponding to the number of periodic changes in the voltage ripple. Based on the obtained frequency information, combined with the time-domain waveform of the voltage ripple component, the duration for which the voltage value exceeds a set threshold within a unit period is statistically analyzed and compared with the entire period duration to calculate the pulse duty cycle. This allows for the complete extraction of pulse timing features, including pulse frequency and duty cycle, from the voltage ripple component.

[0072] The pulse frequency is used as the thermal excitation reference frequency for the resistance wire drive circuit.

[0073] Specifically, the pulse frequency of the voltage ripple reflects the periodic change pattern of the voltage signal, which is closely related to the vibration frequency of the piezoelectric film and determines the rhythm of microtexture embossing. As a key component for thermal compensation, the thermal excitation generated by the resistance wire needs to match the vibration of the piezoelectric film and the microtexture forming process. Setting the pulse frequency as the thermal excitation reference frequency can keep the heating and cooling rhythm of the resistance wire synchronized with the vibration frequency of the piezoelectric film. This ensures that the resistance wire can provide timely thermal compensation during the critical stage of microtexture embossing of the door handle by the piezoelectric film, effectively avoiding the problem of local overheating or uneven cooling of the material caused by the asynchronous thermal excitation and mechanical vibration, and reducing the deviation in microtexture depth and size.

[0074] The duty cycle is converted into the pulse width modulation parameter of the resistance wire drive circuit, and the pulse width modulation parameter controls the energizing time of the resistance wire in each cycle.

[0075] In detail, the duty cycle characterizes the proportion of the high-level duration in the voltage ripple signal within one cycle, directly reflecting the intensity and duration of the energy input. The resistance wire drive circuit adjusts the output power through pulse width modulation (PWM) technology, and the PWM parameter determines the ratio between the resistance wire's energizing time and the cycle duration. Converting the duty cycle into PWM parameters allows the heating power of the resistance wire to match the energy characteristics of the voltage ripple. When the piezoelectric film is used to imprint microtextures on the car door handle, the energizing time and power output of the resistance wire can be precisely controlled based on the energy intensity represented by the duty cycle, achieving on-demand thermal compensation.

[0076] Specifically, the core of controlling the energizing time of the resistance wire in each cycle is to achieve precise regulation of the resistance wire's heat output by controlling the pulse width modulation (PWM) parameter. PWM technology adjusts the average power of the load by changing the duration of the high-level pulse signal, i.e., the pulse width. In the resistance wire drive circuit, the PWM parameter is directly related to the high-level percentage of the pulse signal, and this parameter value determines the energizing time of the resistance wire in a complete operating cycle. When the PWM parameter increases, the high-level duration of the corresponding pulse signal lengthens, the energizing time of the resistance wire increases, and the heat generated per unit cycle increases; conversely, when the parameter decreases, the energizing time of the resistance wire shortens, and the heat output decreases.

[0077] In summary, synchronizing the thermal excitation control timing of the resistance wire drive circuit based on the pulse timing of the voltage ripple component fundamentally eliminates the phase difference problem caused by the independent drive circuits of the thermal compensation unit and the vibration actuator in traditional processes. Using the pulse frequency as the thermal excitation reference frequency of the resistance wire drive circuit ensures strict synchronization between the heating rhythm of the resistance wire and the vibration frequency of the piezoelectric film, preventing localized overheating or uneven cooling of the material. Converting the duty cycle into a pulse width modulation parameter precisely controls the energizing time of the resistance wire in each cycle, matching the heat flow output power with the voltage ripple energy characteristics. This method achieves strict timing consistency between the thermal field and the force field in each forming cycle, effectively avoiding distortion of microtextures caused by asynchronous heat flow and vibration, as well as dimensional drift caused by localized temperature anomalies. It improves the accuracy of multi-physics field collaborative control and ensures the molding quality of door handle components.

[0078] The signal calibration module is used to calculate the real-time amplitude sequence of the piezoelectric film and to perform time phase calibration on the instantaneous heat flow of the resistance wire according to the pulse timing to obtain the synchronous heat flow sequence of the resistance wire.

[0079] In an embodiment of the present invention, calculating the real-time amplitude sequence of the piezoelectric thin film includes:

[0080] Obtain the piezoelectric constant of the piezoelectric thin film;

[0081] Based on the linear relationship of the piezoelectric effect, the piezoelectric constant is multiplied by the voltage ripple component to obtain the instantaneous amplitude value at each sampling time;

[0082] Arrange all instantaneous amplitude values ​​in chronological order to obtain the real-time amplitude sequence.

[0083] Specifically, the piezoelectric constant is an inherent property of piezoelectric thin film materials, reflecting the strength of their piezoelectric effect. It can be obtained through material property testing or by consulting relevant standard parameters. Based on the linear relationship of the piezoelectric effect, the obtained piezoelectric constant is calculated with the voltage ripple component. Since the voltage ripple component contains voltage fluctuation information at different sampling times, the instantaneous amplitude value of the piezoelectric thin film at each sampling time can be obtained by multiplying the piezoelectric constant with the voltage value at each sampling time in the voltage ripple component. Finally, all the calculated instantaneous amplitude values ​​are arranged and combined in chronological order to form a real-time amplitude sequence that reflects the amplitude change of the piezoelectric thin film over a continuous period of time.

[0084] In an embodiment of the present invention, the instantaneous heat flux of the resistance wire is time-phase calibrated according to the pulse timing sequence to obtain a synchronous heat flux sequence of the resistance wire, including:

[0085] To obtain the instantaneous heat flux of the resistance wire;

[0086] Specifically, a suitable temperature sensor is placed on the surface of the resistance wire or its surrounding area where thermal radiation has a significant impact. The temperature sensor continuously collects temperature data of the resistance wire and its surroundings. By combining the collected temperature data, the physical parameters of the resistance wire, and the heat dissipation coefficient of the mold cavity, the temperature signal is converted into a heat flow signal through calculations of physical formulas related to heat conduction and heat radiation, thereby obtaining the instantaneous heat flow data of the resistance wire at various moments in real time.

[0087] Calculate the phase shift of the instantaneous heat flux on the time axis based on the pulse timing;

[0088] Specifically, based on the determined pulse timing, the correspondence between the instantaneous heat flow and the pulse timing signal on the time axis is analyzed. By calculating the differences in time parameters such as the start time and periodic characteristics of the two, the phase offset of the instantaneous heat flow on the time axis is determined. This offset reflects the time difference between the heat flow output and the pulse timing requirement.

[0089] Based on the phase offset, the instantaneous heat flow of the resistance wire is calibrated in time phase using a digital delay method to obtain the synchronous heat flow sequence of the resistance wire.

[0090] Specifically, the sign and magnitude of the phase offset are determined. If the instantaneous heat flow fluctuation phase leads the voltage ripple pulse timing phase, the offset is positive; otherwise, it is negative. The required delay time is calculated based on the phase offset, which is equal to the ratio of the phase offset to the pulse period multiplied by the pulse period. Using a timer or delay module in the digital controller, a delay trigger time t1 is set. After detecting the trigger signal of the voltage ripple pulse timing, the system waits for t1 before sending a heat flow output control signal to the resistance wire drive circuit. After the resistance wire drive circuit receives the delayed control signal, it generates an instantaneous heat flow according to the preset heat flow output parameters, making the calibrated heat flow phase consistent with the voltage ripple pulse timing phase, thus completing the time phase calibration.

[0091] In summary, by calculating the real-time amplitude sequence using the linear relationship between the piezoelectric constant and the voltage ripple component, the vibration state of the piezoelectric film at each sampling moment can be accurately reflected, providing dynamic force field parameters for multi-physics field collaborative control. On the other hand, by calculating the heat flow phase offset through pulse timing and implementing digital delay calibration, the time difference between the resistance wire heat flow output and the voltage ripple pulse timing can be eliminated, ensuring that the heat flow sequence and amplitude sequence are strictly synchronized on the time axis. This ensures that the thermal field and force field signals work synergistically during the micro-texture imprinting process, avoiding uneven material curing or texture replication distortion caused by phase deviation, improving the consistency of micro-texture depth and dimensional accuracy of door handle accessories, and solving the molding quality problems caused by the asynchrony of multi-physics field signals in traditional processes.

[0092] The correlation calculation module is used to perform cross-correlation calculations on the synchronous heat flow sequence and the real-time amplitude sequence to obtain the correlation value;

[0093] In an embodiment of the present invention, cross-correlation calculations are performed on the synchronous heat flow sequence and the real-time amplitude sequence to obtain correlation values, including:

[0094] The cross-correlation coefficient algorithm is used to calculate the cross-correlation coefficient between the synchronous heat flux sequence and the real-time amplitude sequence. The formula for calculating the cross-correlation coefficient is as follows:

[0095]

[0096] In the formula, It is the cross-correlation coefficient. It is the first of the synchronous heat flow sequence A heat flux value, It is the mean of all heat flux values ​​in the synchronous heat flux sequence. It is the first of the real-time amplitude sequence An instantaneous amplitude value, It is the mean of all instantaneous amplitude values ​​in the real-time amplitude sequence. It is the total of heat flux value and instantaneous amplitude value. It is an identifier for heat flow value and instantaneous amplitude value.

[0097] In detail, the cross-correlation coefficient algorithm is a mathematical method used to measure the similarity and linear correlation between two signals or datasets. It calculates the normalized results of their covariance and standard deviation at different times or locations to obtain a coefficient between -1 and 1, where 1 indicates perfect positive correlation, -1 indicates perfect negative correlation, and 0 indicates no linear correlation. It is commonly used in signal processing, image matching, and data analysis.

[0098] Specifically, the synchronous heat flow sequence reflects the real-time output characteristics of the resistance wire thermal compensation, while the real-time amplitude sequence reflects the dynamic changes in the piezoelectric film vibration. These two parameters correspond to key state parameters of the thermal and force fields during the manufacturing process, respectively. Through cross-correlation calculations, the linear correlation between the heat flow output rhythm and intensity and the piezoelectric film amplitude changes can be accurately measured: if the correlation value approaches 1, it indicates a high degree of coordination between the heat flow and amplitude in terms of timing and intensity, demonstrating good multi-physics field synchronous control, which helps ensure the molding accuracy and dimensional stability of the microtexture in the door handle; if the correlation value deviates from the ideal range, it indicates a coordination deviation between the thermal and force fields, requiring timely adjustment of the thermal compensation or vibration drive parameters.

[0099] The deviation prediction module is used to calculate the root mean square value of the voltage ripple component, and calculate the predicted micro-texture depth deviation and predicted size deviation of the door handle accessory based on the root mean square value and the correlation value.

[0100] In an embodiment of the present invention, calculating the root mean square value of the voltage ripple component includes:

[0101] The discrete points of the voltage ripple component are extracted at fixed time intervals, and the discrete points are determined as the instantaneous values ​​of the voltage ripple component.

[0102] Square each instantaneous value to obtain the squared value, sum all the squared values ​​to obtain the summation result;

[0103] Divide the summation result by the total number of instantaneous values ​​to obtain the square mean of the voltage ripple component;

[0104] The root mean square of the squared mean is taken to obtain the root mean square value of the voltage ripple component.

[0105] In detail, the root mean square (RMS) value of the voltage ripple component reflects the intensity characteristics of the driving energy, directly correlated with the basic level of the piezoelectric film vibration amplitude and thermal compensation energy output; while the correlation value between the synchronous heat flow sequence and the real-time amplitude sequence quantifies the degree of coordination between the thermal field and the force field, reflecting the effect of multi-physics synchronous control. When the RMS value is abnormal, the vibration amplitude and heat flow output intensity of the piezoelectric film will deviate from the process requirements, causing changes in the microtexture imprinting depth and the molding size of the parts; a poor correlation value means that the coordination between the thermal field and the force field is deviated, resulting in interference with the material curing and molding process. By constructing a quantitative correlation model between the RMS value, the correlation value, and the deviations in microtexture depth and size, changes in energy intensity and coordination state can be transformed into deviation prediction results.

[0106] In an embodiment of the present invention, the predicted microtexture depth deviation and predicted size deviation of the door handle component are calculated based on the root mean square value and correlation value, including:

[0107] Set empirical coefficients for microtexture depth and size deviation;

[0108] Specifically, setting empirical coefficients for microtexture depth and dimensional deviation requires extensive process experiments and historical data. This involves conducting manufacturing experiments with different combinations of process parameters, collecting data on microtexture depth deviation, dimensional deviation, and corresponding process parameters such as voltage ripple, heat flow, and amplitude. Data analysis methods are then used to explore the quantitative relationship between deviations and key parameters, and significant influencing factors are screened. Based on the influence weights, empirical coefficients are determined through fitting calculations and iterative optimization, and verified and corrected through multiple rounds of experiments. This ensures that the coefficients can accurately calculate and predict deviations by combining parameters such as root mean square values ​​and correlation values, thus assisting in quality control.

[0109] Substituting the empirical coefficient of microtexture depth, root mean square value, and correlation value into the preset depth deviation formula, the predicted microtexture depth deviation is obtained. The preset depth deviation formula is as follows:

[0110]

[0111] In the formula, It predicts the depth deviation of microtextures. It is an empirical coefficient for microtexture depth. It is the root mean square value. It is the absolute value of the correlation value;

[0112] Substituting the empirical coefficient of dimensional deviation, the root mean square value, and the correlation value into the preset dimensional deviation formula, the predicted dimensional deviation is obtained. The preset dimensional deviation formula is as follows:

[0113]

[0114] In the formula, It predicts dimensional deviations. It is an empirical coefficient for dimensional deviation. It is the root mean square value. It is the absolute value of the correlation value.

[0115] Specifically, from the perspective of physical mechanisms and parameter correlation, the root mean square value reflects the energy intensity of voltage ripple, directly affecting the vibration amplitude and basic level of heat flow output of the piezoelectric film. The stronger the energy, the easier it is to cause fluctuations in the depth and size of microtextures; the absolute value of the correlation value reflects the degree of coordination between heat flow and amplitude. The quantification of coordination bias indicates that the worse the coordination, the more... The smaller the value, the higher the risk of deviation accumulation. The empirical coefficients for microtexture depth and dimensional deviation are process adaptation coefficients obtained by fitting a large amount of experimental data. They are used to calibrate the influence weights of energy intensity and cooperative deviation on actual deviations. The formula transforms electrical signal characteristics and multi-field cooperative states into quantifiable deviation prediction values ​​through the correlation of "energy intensity × cooperative deviation × process coefficient", which is consistent with the manufacturing logic of "energy-driven, cooperative control and deviation formation" in terms of mechanism.

[0116] The manufacturing decision module is used to determine whether to manufacture the door handle component based on the predicted microtexture depth deviation and the predicted dimensional deviation.

[0117] In embodiments of the present invention, determining whether to manufacture the door handle component based on the predicted microtexture depth deviation and the predicted size deviation includes:

[0118] Compare the predicted microtexture depth deviation with the first difference of the preset depth deviation threshold;

[0119] Compare the predicted size deviation with the second difference between the preset size deviation threshold;

[0120] If both the first and second differences are within the tolerance range, the predicted quality of the door handle component is deemed to be qualified, and the manufacturing of the door handle component is carried out.

[0121] If the first and second differences exceed the tolerance range, the predicted quality of the door handle component is deemed unqualified, and the manufacturing process for the door handle component will not be executed.

[0122] In detail, the preset depth deviation threshold and size deviation threshold were determined through multiple sets of manufacturing tests and data analysis of car door handle parts: tests covering different process parameters were designed to collect actual deviation data of micro-texture depth and size; combined with quality standard requirements and process stability requirements, statistical fitting and iterative verification were used to screen out the maximum allowable deviation that can ensure the qualified quality of the parts, which were used as depth and size deviation thresholds for quality pre-control before manufacturing.

[0123] In general, a closed-loop quality control mechanism is constructed before manufacturing by comparing the predicted deviation with preset thresholds. Specifically, the first difference between the predicted micro-texture depth deviation and the preset depth deviation threshold, and the second difference between the predicted dimensional deviation and the preset dimensional deviation threshold are calculated. If both differences are within the tolerance range, the quality is deemed acceptable and manufacturing is executed; otherwise, the process is immediately suspended. This method can screen out potential defective products before part forming, avoiding scrap caused by micro-texture distortion or dimensional deviation. At the same time, by providing real-time feedback on the prediction results, it can trigger adaptive parameter adjustments, shortening machine setup time and ensuring that door handle components maintain sub-micron-level texture consistency and assembly accuracy during high-rate production. This solves the problems of lagging quality prediction and high scrap rate in traditional processes, improving manufacturing efficiency and product qualification rate.

[0124] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A manufacturing analysis system for door handle components of an intelligent vehicle, characterized in that, include: The drive connection module is used to embed a piezoelectric film in the injection mold cavity of the door handle accessory, and to set a resistance wire on the back of the injection mold cavity. The piezoelectric film is connected to the voltage ripple drive circuit, and the resistance wire is connected to the resistance wire drive circuit. The timing synchronization module is used to use the voltage ripple component of the bus voltage as the driving source of the voltage ripple drive circuit, and to synchronize the thermal excitation control timing of the resistance wire drive circuit according to the pulse timing of the voltage ripple component. The signal calibration module is used to calculate the real-time amplitude sequence of the piezoelectric film and to perform time phase calibration on the instantaneous heat flow of the resistance wire according to the pulse timing to obtain the synchronous heat flow sequence of the resistance wire. The correlation calculation module is used to perform cross-correlation calculations on the synchronous heat flow sequence and the real-time amplitude sequence to obtain the correlation value; The deviation prediction module is used to calculate the root mean square value of the voltage ripple component, and calculate the predicted micro-texture depth deviation and predicted size deviation of the door handle accessory based on the root mean square value and the correlation value. The manufacturing decision module is used to determine whether to manufacture the door handle component based on the predicted microtexture depth deviation and the predicted dimensional deviation.

2. The intelligent vehicle door handle component manufacturing analysis system according to claim 1, characterized in that, Using the voltage ripple component of the bus voltage as the driving source for the voltage ripple drive circuit includes: Within a preset time period, the bus voltage is collected at a fixed sampling frequency to obtain multiple sample voltage values ​​of the bus voltage. The sample voltage values ​​are summed to obtain the total sample voltage of the bus voltage. The total sample voltage is then divided by the total number of sample voltage values ​​to obtain the average base voltage of the bus voltage. The voltage ripple component of the bus voltage is obtained by subtracting the average base voltage from the bus voltage, and this voltage ripple component is used as the driving source for the voltage ripple drive circuit.

3. The intelligent vehicle door handle component manufacturing analysis system according to claim 1, characterized in that, The thermal excitation control timing of the resistance wire drive circuit is synchronized based on the pulse timing of the voltage ripple component, including: The pulse timing features are extracted from the voltage ripple component using the Fast Fourier Transform, where the pulse timing features include the pulse frequency and duty cycle. The pulse frequency is used as the thermal excitation reference frequency for the resistance wire drive circuit. The duty cycle is converted into the pulse width modulation parameter of the resistance wire drive circuit, and the pulse width modulation parameter controls the energizing time of the resistance wire in each cycle.

4. The intelligent vehicle door handle component manufacturing analysis system according to claim 1, characterized in that, Calculate the real-time amplitude sequence of the piezoelectric thin film, including: Obtain the piezoelectric constant of the piezoelectric thin film; Based on the linear relationship of the piezoelectric effect, the piezoelectric constant is multiplied by the voltage ripple component to obtain the instantaneous amplitude value at each sampling time; Arrange all instantaneous amplitude values ​​in chronological order to obtain the real-time amplitude sequence.

5. The intelligent vehicle door handle component manufacturing analysis system according to claim 1, characterized in that, Based on the pulse timing sequence, the instantaneous heat flux of the resistance wire is calibrated in time phase to obtain the synchronous heat flux sequence of the resistance wire, including: To obtain the instantaneous heat flux of the resistance wire; Calculate the phase shift of the instantaneous heat flux on the time axis based on the pulse timing; Based on the phase offset, the instantaneous heat flow of the resistance wire is calibrated in time phase using a digital delay method to obtain the synchronous heat flow sequence of the resistance wire.

6. The intelligent vehicle door handle component manufacturing analysis system according to claim 1, characterized in that, Cross-correlation calculations were performed on the synchronous heat flux sequence and the real-time amplitude sequence to obtain the correlation values, including: The cross-correlation coefficient algorithm is used to calculate the cross-correlation coefficient between the synchronous heat flux sequence and the real-time amplitude sequence. The formula for calculating the cross-correlation coefficient is as follows: In the formula, It is the cross-correlation coefficient. It is the first of the synchronous heat flow sequence A heat flux value, It is the mean of all heat flux values ​​in the synchronous heat flux sequence. It is the first of the real-time amplitude sequence An instantaneous amplitude value, It is the mean of all instantaneous amplitude values ​​in the real-time amplitude sequence. It is the total of heat flux value and instantaneous amplitude value. It is an identifier for heat flow value and instantaneous amplitude value.

7. The intelligent vehicle door handle component manufacturing analysis system according to claim 1, characterized in that, Calculate the root mean square value of the voltage ripple component, including: The discrete points of the voltage ripple component are extracted at fixed time intervals, and the discrete points are determined as the instantaneous values ​​of the voltage ripple component. Square each instantaneous value to obtain the squared value, sum all the squared values ​​to obtain the summation result; Divide the summation result by the total number of instantaneous values ​​to obtain the square mean of the voltage ripple component; The root mean square of the squared mean is taken to obtain the root mean square value of the voltage ripple component.

8. The intelligent vehicle door handle component manufacturing analysis system according to claim 1, characterized in that, The predicted microtexture depth deviation and predicted size deviation of the door handle component are calculated based on the root mean square value and correlation value, including: Set empirical coefficients for microtexture depth and size deviation; Substituting the empirical coefficient of microtexture depth, root mean square value, and correlation value into the preset depth deviation formula, the predicted microtexture depth deviation is obtained. The preset depth deviation formula is as follows: In the formula, It predicts the depth deviation of microtextures. It is an empirical coefficient for microtexture depth. It is the root mean square value. It is the absolute value of the correlation value; Substituting the empirical coefficient of dimensional deviation, the root mean square value, and the correlation value into the preset dimensional deviation formula, the predicted dimensional deviation is obtained. The preset dimensional deviation formula is as follows: In the formula, It predicts dimensional deviations. It is an empirical coefficient for dimensional deviation. It is the root mean square value. It is the absolute value of the correlation value.

9. The intelligent vehicle door handle component manufacturing analysis system according to claim 1, characterized in that, The determination of whether to manufacture door handle components is based on predicted microtexture depth deviation and predicted dimensional deviation, including: Compare the predicted microtexture depth deviation with the first difference of the preset depth deviation threshold; Compare the predicted size deviation with the second difference between the preset size deviation threshold; If both the first and second differences are within the tolerance range, the predicted quality of the door handle component is deemed to be qualified, and the manufacturing of the door handle component is carried out. If the first and second differences exceed the tolerance range, the predicted quality of the door handle component is deemed unqualified, and the manufacturing process for the door handle component will not be executed.

Images