An intelligent monitoring bolt integrated with a piezoelectric sensing module and a pre-tightening force real-time detection system

Abstract

The embodiment of the application provides a kind of integrated piezoelectric sensing module's intelligent monitoring bolt and pre-tightening force real-time detection system, comprising: bolt body, sensing module, the present application is to solve the prior art only can carry out production stage's automobile bolt pre-tightening force monitoring, cannot effectively monitor the automobile bolt pre-tightening force and / or life when automobile works;The application can realize by embedding sensor to automobile bolt, realize its automobile driving / after factory, still can effectively monitor the purpose of pre-tightening force and / or life to automobile bolt, greatly improve the reliability and safety in the process of automobile driving, reduce the situation that accident is caused by bolt body loosening, damage and lead to shortened service life / damage.

Description

Technical Field

[0001] This invention relates to the field of automotive bolt detection technology, and in particular to an intelligent monitoring system for bolts and real-time detection of preload force that integrates a piezoelectric sensing module. Background Technology

[0002] During the production process, the bolts between the leaf springs of the vehicle suspension and the axle and balance suspension supports are tightened by monitoring the preload. However, the existing preload monitoring process does not cover the dynamic loosening of the bolts throughout their entire life cycle. In other words, the existing monitoring data cannot effectively detect the bolt preload / life during the vehicle's operation. It lacks effective monitoring throughout the entire life cycle and cannot combine real-time load spectrum to quantitatively assess fatigue damage and predict the remaining life of the fasteners. Summary of the Invention

[0003] This invention provides an intelligent monitoring system for real-time detection of bolt preload and preload by integrating a piezoelectric sensing module. This addresses the limitation of existing technologies, which can only monitor the preload of automotive bolts during the production stage and cannot effectively monitor the preload and / or lifespan of bolts during vehicle operation. This invention enables effective monitoring of bolt preload and / or lifespan even after the vehicle has been driven or left the factory, by embedding sensors within the bolts. This significantly improves the reliability and safety of vehicles during operation and reduces accidents caused by bolt loosening or damage leading to shortened service life or failure.

[0004] This invention provides a real-time preload detection system, comprising: The bolt body has an axial accommodating cavity inside, which is used to install the sensing module; The sensing module is used to collect piezoelectric signals, temperature, and vibration parameters generated by the bolt under stress. The production stage calibration module is used to collect piezoelectric signals and preload data during bolt assembly and establish a mapping relationship to obtain the initial preload and calibration parameters. The data processing module is used to perform feature extraction and compensation processing on the piezoelectric signal; The controller is used to calculate the current preload based on the calibration parameters and compensation signals, determine the loosening and deformation state of the bolts based on the changes in preload, calculate the remaining service life based on the changes in preload and environmental parameters, and output abnormal alarm information to the alarm module.

[0005] Preferably, the assembly load and the sensing signal of the bolt body are correlated and calibrated, and an initial mapping relationship is established; Acquire the raw sensing signals collected by the sensing module; The original inductive signal is compensated to obtain the corrected load data; The working condition of the bolt body is evaluated based on the corrected load data; The calibration of the association between assembly load and sensing signal includes: synchronously collecting the torque value applied to the bolt body and the charge signal output by the sensing module during the assembly stage, and establishing the torque and piezoelectric mapping curve as the initial mapping relationship.

[0006] Preferably, based on the corrected load data, the damage degree of the bolt body is calculated using a linear cumulative damage model, and the remaining fatigue life is predicted.

[0007] Preferably, it further includes: a signal conditioning circuit, electrically connected to the sensing module, for preprocessing the sensed signal; and for compensating the preprocessed signal through the controller, and performing load monitoring or lifetime assessment based on the compensated signal; The charge amplification module is used to convert the high-impedance charge signal output by the sensing module into a low-impedance voltage signal and perform filtering.

[0008] Preferably, the sensing module includes a piezoelectric sensing unit, a temperature and humidity sensing unit, and a triaxial accelerometer unit. The piezoelectric sensing unit is a piezoelectric ceramic ring or a piezoelectric film. The piezoelectric sensing unit is set in the axial cavity of the bolt body by interference fit and contacts the stress guiding structure set in the bolt body to obtain the radial pressure generated therefrom. The temperature and humidity sensing unit is used to collect temperature and humidity data of the bolt body and transmit the collected temperature and humidity data to the controller. The three-axis accelerometer unit is used to collect vibration signals generated by the bolt body during its operation.

[0009] Preferably, a linear mapping relationship between the voltage signal and the preload is established, and the calibration coefficient k is calculated. When the temperature and humidity sensing unit detects that the temperature deviates from the calibrated temperature, it corrects the voltage signal based on the temperature compensation coefficient α. Specifically, if the current temperature exceeds the preset value, the original voltage will be corrected using a temperature compensation coefficient. Furthermore, based on the acceleration amplitude detected by the vibration sensor, the vibration compensation coefficient β is used for correction; the corrected voltage value is calculated with the calibration coefficient k to obtain the current real-time preload value; and the bolt body is graded for loosening based on the preload value.

[0010] Preferably, the current preload is compared with the initial preload in real time; When the current preload drops to the first preset threshold of the initial preload, it is determined to be a slight looseness; When the current preload drops below the second preset threshold of the initial preload, it is determined to be severely loose; and the frequency domain energy of the piezoelectric signal is judged. When the proportion of low-frequency energy increases by more than 30%, it is judged that the stiffness of the fastener connection has decreased, that is, plastic deformation or loosening tends to occur.

[0011] Preferably, the fluctuation amplitude of the preload is divided into different levels, and the damage value of the bolt body is calculated using a linear cumulative damage model based on the SN curve of the bolt material. When the real-time temperature exceeds the third preset value or the vibration acceleration continues to exceed the N value, the damage weighting coefficient for the corresponding time period will be increased by 1.5 times. When the cumulative damage value reaches the fourth preset value, an early warning is issued to replace the bolt body, and the remaining driving mileage is predicted.

[0012] This invention provides an intelligent monitoring bolt with an integrated piezoelectric sensing module. The preload real-time detection system described above is used to monitor the preload of automotive bolts throughout their entire life cycle, and the bolt loosening and / or service life are assessed based on the monitoring results.

[0013] Preferably, it includes a bolt body, which has an axially accommodating cavity inside; A stress guiding structure, installed on the bolt body, is used to convert the axial force borne by the bolt body into radial pressure. The sensing module includes a piezoelectric sensing unit, a temperature and humidity sensing unit, and a triaxial acceleration unit; Among them, the piezoelectric sensing unit is set in the axial accommodating cavity to sense the radial pressure collected by the stress guiding structure and transmit the electrical signal corresponding to the pressure to the controller; The temperature and humidity sensing unit is used to collect temperature and humidity data of the bolt body and transmit the collected temperature and humidity data to the controller. The three-axis accelerometer unit is used to collect vibration signals generated by the bolt body during operation and transmit them to the controller.

[0014] The working principle and beneficial effects of this invention are as follows: This invention provides a real-time preload detection system, comprising: a bolt body having an axial accommodating cavity inside, wherein a sensing module is installed within the axial accommodating cavity; The sensing module is used to collect piezoelectric signals, temperature, and vibration parameters generated by the bolt under stress. The production stage calibration module is used to collect piezoelectric signals and preload data during bolt assembly and establish a mapping relationship to obtain the initial preload and calibration parameters. The data processing module is used for feature extraction and compensation processing of piezoelectric signals; The controller is used to calculate the current preload based on the calibration parameters and compensation signals, determine the loosening and deformation state of the bolts based on the changes in preload, calculate the remaining service life based on the changes in preload and environmental parameters, and output abnormal alarm information to the alarm module.

[0015] This invention addresses the limitation of existing technologies, which can only monitor the preload of automotive bolts during the production stage and cannot effectively monitor the preload and / or lifespan of automotive bolts during vehicle operation. This invention enables effective monitoring of the preload and / or lifespan of automotive bolts even after the vehicle has been driven or left the factory, by embedding sensors within the bolts. This significantly improves the reliability and safety of vehicles during operation and reduces accidents caused by bolt loosening or damage leading to shortened service life or other issues.

[0016] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description and the accompanying drawings.

[0017] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0018] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings: Figure 1 This is a schematic diagram of the structure of the present invention; Figure 2 This is a schematic diagram of an embodiment of the present invention.

[0019] Among them, 1-bolt body, 2-axial accommodating cavity, 3-stress guiding structure, 4-sensing module, 5-bolt head, 6-spring preload, 43-piezoelectric sensing unit, 42-temperature and humidity sensing unit, 41-triaxial acceleration unit. Detailed Implementation

[0020] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0021] according to Figure 1 As shown, an embodiment of the present invention provides a real-time preload detection system, comprising: The bolt body 1 has an axial accommodating cavity 2 inside, which is used to install the sensing module 4. Sensing module 4 is used to collect piezoelectric signals, temperature and vibration parameters generated by the bolt under stress; The production stage calibration module is used to collect piezoelectric signals and preload data during bolt assembly and establish a mapping relationship to obtain the initial preload and calibration parameters. The data processing module is used for feature extraction and compensation processing of piezoelectric signals; The controller is used to calculate the current preload based on the calibration parameters and compensation signals, determine the loosening and deformation state of the bolts based on the changes in preload, calculate the remaining service life based on the changes in preload and environmental parameters, and output abnormal alarm information to the alarm module.

[0022] This invention addresses the limitation of existing technologies, which can only monitor the preload of automotive bolts during the production stage and cannot effectively monitor the preload and / or lifespan of automotive bolts during vehicle operation. This invention enables effective monitoring of the preload and / or lifespan of automotive bolts even after the vehicle has been driven or left the factory, by embedding sensors within the bolts. This significantly improves the reliability and safety of the vehicle during operation and reduces accidents caused by shortened service life or damage to the bolt body due to loosening or damage.

[0023] Specifically, this embodiment provides a real-time preload detection system, which is applied to fastener condition monitoring during the automobile assembly stage and the vehicle service stage (when the vehicle is working / driving); The real-time preload detection system provided in this case includes a bolt body 1, a stress guiding structure 3, a sensing module 4, a signal conditioning circuit, a production calibration module, a data processing module, a condition assessment module, and a controller.

[0024] The bolt body 1 is made of alloy steel, and an axial accommodating cavity 2 is formed on its central axis. The axial accommodating cavity 2 is used to accommodate the piezoelectric sensing unit 41 and auxiliary sensing components.

[0025] The stress guiding structure 3 is disposed on the outer periphery of the bolt body 1, and its axial position corresponds to the piezoelectric sensing unit 41 in the axial accommodating cavity 2.

[0026] In this invention, when the bolt body 1 is subjected to axial tensile force during assembly or service, according to the Poisson effect in mechanics of materials, the bolt body 1 will undergo axial elongation and radial contraction. The stress guiding structure 3 weakens the local cross-sectional area, making the area a stress concentration zone, thereby amplifying the radial contraction deformation.

[0027] The radial deformation acts on the piezoelectric sensing unit 41 within the axially accommodating cavity 2, causing it to generate a charge signal proportional to the pressure.

[0028] The charge signal is converted into a voltage signal by the charge amplifier in the signal conditioning circuit, and then the noise is reduced by the filtering module.

[0029] During the automobile production and assembly stage, when torque is applied to the bolt body 1, torque signals and piezoelectric output signals are collected simultaneously to establish a mapping relationship between preload and voltage signals and obtain calibration parameters.

[0030] When the vehicle is in the working / driving stage, the piezoelectric signal of the bolt body 1 is continuously collected by the sensing module 4. The piezoelectric signal of the bolt body 1 is compensated by combining temperature and vibration data to obtain the real-time preload value.

[0031] Next, the real-time preload is compared with the initial preload using the condition assessment module. Based on the comparison results, the loosening status of the bolts can be determined. Finally, the fatigue life of the bolts is predicted and evaluated using load cycle data.

[0032] In this invention, the environmental parameters are temperature and vibration parameters; the feature extraction and compensation processing includes low-pass filtering, temperature compensation, and vibration compensation. In this embodiment, the bolt body 1 is the main load-bearing component, used to provide fastening force; the bolt body 1 and the connected parts are connected by threads, with a fit tolerance of 6g / 6H; The piezoelectric ceramic element is installed inside the axial accommodating cavity 2 by the elastic pressure interference fit of the spring preload 6, and the contact stress is not less than 2MPa. The conductive leads are connected to both ends of the piezoelectric ceramic by ultrasonic welding and lead out through the sealing encapsulation layer; The sealing and encapsulation layer is chemically bonded to the inner wall of the axial accommodating cavity 2 to ensure no displacement under 20g vibration; In this invention, when the bolt is tightened, the bolt body 1 is subjected to axial tensile force and produces a slight elongation, and the stress guiding structure 3 causes a significant increase in local stress at the bottom of the axial accommodating cavity 2.

[0033] The stress is transmitted to the piezoelectric ceramic element through the spring preload 6. The piezoelectric ceramic generates an electric charge signal that is proportional to the pressure based on the piezoelectric effect. The charge signal is converted into a voltage signal of 0-5V through the built-in charge amplification circuit. When the automotive bolt (bolt body 1) is subjected to a maximum preload of 100kN, the strain in the sensing area is amplified by 1.5 times, so that the system can identify preload changes as low as 0.5kN.

[0034] The NTC thermistor in the environmental sensing module monitors the bolt temperature in real time. When the temperature rises from 25°C to 100°C, the resistance of the thermistor changes. The control unit compensates for the linear attenuation of the piezoelectric voltage based on this change to ensure that the output preload value is not affected by thermal expansion.

[0035] This invention enables monitoring of automotive bolts throughout their entire lifecycle, from production and assembly to operational monitoring, avoiding the limitations of traditional technologies that rely solely on assembly stage control and fail to reflect problems encountered during the operation / driving process of automotive bolts.

[0036] In one embodiment, according to Figure 1-2 As shown, the system is based on the control method embedded in the controller, and uses the production stage calibration module to perform assembly load and induction signal correlation calibration on the bolt body 1, and establish an initial mapping relationship. Acquire the raw sensing signal collected by sensing module 4; The original inductive signal is compensated to obtain the corrected load data; The working condition of bolt body 1 is evaluated based on the corrected load data; The calibration of the association between assembly load and sensing signal includes: synchronously collecting the torque value applied to the bolt body 1 and the charge signal output by the sensing module 4 during the assembly stage, and establishing the torque and piezoelectric mapping curve as the initial mapping relationship.

[0037] Based on the corrected load data, the damage level of bolt body 1 is calculated using a linear cumulative damage model, and the remaining fatigue life is predicted.

[0038] In this embodiment, a linear mapping curve between torque and piezoelectric voltage is established to form an initial mapping relationship, and this curve is used as the initial mapping relationship. In this embodiment, the stress guiding structure 3 is a ring structure with an internal groove structure. The groove has a V-shaped cross-section, a groove angle of 60°, and a groove depth of about 30% of the bolt diameter.

[0039] The stress guiding structure 3 is located in the middle region of the axial accommodating cavity 2, so that its axis is coaxially aligned with the piezoelectric sensing unit 41.

[0040] In this embodiment, when the bolt is subjected to axial tensile load, the stress guiding structure 3 has a reduced cross-sectional area and a decreased local stiffness, resulting in a significant stress concentration in the area.

[0041] Furthermore, the transverse strain in the stress concentration region will be significantly greater than that in the non-concentration region, thus increasing the radial shrinkage. This radial shrinkage then acts directly on the piezoelectric sensing unit 41 through the inner wall of the bolt, causing it to output a higher amplitude charge signal.

[0042] The annular groove is formed in one step by CNC turning, with the machining accuracy controlled within ±0.01mm to ensure the consistency of stress concentration effect.

[0043] In this embodiment, the stress guiding structure 3 is set to effectively amplify the minute radial deformation, thereby enabling the piezoelectric sensing unit 41 to identify preload changes as low as 0.5kN, significantly improving the detection sensitivity.

[0044] In this embodiment, a spring preload 6 is provided at the bottom of the axial accommodating cavity 2. The wave spring is made of 65Mn spring steel, with a free height of 4mm and a preload force of 50N.

[0045] The piezoelectric sensing unit 41 is a piezoelectric ceramic element, which is positioned above the wave spring and maintains close contact with the inner wall of the cavity.

[0046] After assembly, the spring preload 6 is in a compressed state, continuously applying preload to the piezoelectric ceramic element to keep it in close contact with the stressed area.

[0047] During vehicle operation, even with high-frequency vibration or impact loads, the pre-tightening structure can maintain the contact stability between the piezoelectric ceramic element and the cavity, thereby avoiding signal interruption or contact resistance fluctuations.

[0048] The spring preload 6 provided in this embodiment effectively solves the problem of traditional piezoelectric ceramic elements being prone to loosening in a vibration environment, improves the stability and repeatability of signal transmission, and ensures the reliability of long-term monitoring.

[0049] In one embodiment, it further includes: a signal conditioning circuit electrically connected to the sensing module 4, used to preprocess the sensed signal; and to compensate the preprocessed signal through a controller, and to perform load monitoring or lifetime assessment based on the compensated signal.

[0050] The charge amplification module is used to convert the high-impedance charge signal output by the sensing module 4 into a low-impedance voltage signal and perform filtering.

[0051] In this embodiment, the signal conditioning circuit includes a charge amplification module and a low-pass filter module. The charge amplification module uses a high input impedance operational amplifier to convert the charge signal output by the piezoelectric sensing unit 41 into a voltage signal.

[0052] The low-pass filter module adopts a fourth-order Butterworth filter structure with a cutoff frequency set at 200Hz.

[0053] The signal output by piezoelectric ceramic elements is a high-impedance charge signal, which is susceptible to electromagnetic interference.

[0054] After impedance matching via a charge amplifier, the signal is converted into a stable voltage signal.

[0055] Noise signals above the cutoff frequency are then filtered out, while the effective load change signal is retained.

[0056] The signal conditioning circuit provided in this embodiment can significantly improve the signal-to-noise ratio, suppress high-frequency vibration noise and electromagnetic interference generated during vehicle operation, and make the output signal smoother and more stable.

[0057] In one embodiment, the sensing module 4 includes a piezoelectric sensing unit 41, a temperature and humidity sensing unit 42, and a triaxial acceleration unit 43. The piezoelectric sensing unit 41 is a piezoelectric ceramic ring or a piezoelectric film. The piezoelectric sensing unit 41 is disposed in the axial accommodating cavity 2 of the bolt body 1 by means of interference fit, and contacts the stress guiding structure 3 provided on the bolt body 1 to obtain the radial pressure generated therefrom. The temperature and humidity sensing unit 42 is used to collect temperature and humidity data of the bolt body 1 and transmit the collected temperature and humidity data to the controller. The three-axis acceleration unit 43 is used to collect vibration signals generated during the operation of the bolt body 1.

[0058] Furthermore, a linear mapping relationship between the voltage signal and the preload is established, and the calibration coefficient k is calculated. When the temperature and humidity sensing unit 42 detects that the temperature deviates from the calibrated temperature, it corrects the voltage signal based on the temperature compensation coefficient α. Specifically, if the current temperature exceeds the preset value, the original voltage will be corrected using a temperature compensation coefficient. Furthermore, based on the acceleration amplitude detected by the vibration sensor, the vibration compensation coefficient β is called for correction; the corrected voltage value is calculated with the calibration coefficient k to obtain the current real-time preload value; and the bolt body 1 is graded for loosening based on the preload value.

[0059] Next, the current preload is compared with the initial preload in real time; When the current preload drops to the first preset threshold of the initial preload, it is determined to be a slight looseness; When the current preload drops below the second preset threshold of the initial preload, it is determined to be severely loose; and the frequency domain energy of the piezoelectric signal is judged. When the proportion of low-frequency energy increases by more than 30%, it is judged that the stiffness of the fastener connection has decreased, that is, plastic deformation or loosening tends to occur.

[0060] Furthermore, the fluctuation amplitude of the preload is divided into different levels, and the damage value of the bolt body 1 is calculated using a linear cumulative damage model based on the SN curve of the bolt material. When the real-time temperature exceeds the third preset value or the vibration acceleration continues to exceed the N value, the damage weighting coefficient for that period is increased by 1.5 times. When the cumulative damage value reaches the fourth preset value, an early warning is issued to replace the bolt body 1, and the remaining driving mileage is predicted.

[0061] In this embodiment, the output characteristics of the piezoelectric material drift with temperature changes, and vibration introduces additional noise.

[0062] The real-time temperature is obtained by a temperature sensor, and the temperature difference ΔT is calculated. The voltage signal is corrected by a temperature compensation coefficient α. At the same time, a vibration compensation coefficient β is introduced based on the vibration acceleration A.

[0063] During the calculation process, the original voltage signal is first normalized and then corrected by a compensation formula to obtain a stable preload calculation value. This effectively reduces the impact of temperature changes and vibration environment on measurement accuracy, allowing the system to maintain high accuracy in the range of -40℃ to 120℃.

[0064] By establishing an initial preload benchmark value, the real-time preload is compared and analyzed.

[0065] When the preload drops to 85% of the initial value, it is considered slightly loose; when it drops below 70%, it is considered severely loose.

[0066] In this embodiment, a graded judgment method enables maintenance personnel to identify risks in advance and avoid sudden failures.

[0067] By extracting the load cycles and combining them with the material's SN curve, fatigue damage at each stress level is calculated.

[0068] Next, the total damage value is calculated based on the cumulative damage model, and an early warning is issued when the damage value approaches the threshold, realizing the transformation from passive alarm to active prediction.

[0069] In this embodiment, firstly, personalized calibration and data binding of automotive bolts can be achieved during the production and assembly stage; specifically, on the automotive chassis assembly line, when torque is applied to the bolts, the torque value fed back by the tightening gun and the charge signal output by the bolt's built-in piezoelectric sensing module are collected.

[0070] In this embodiment, a linear mapping relationship between voltage signal and preload is established through multi-stage loading, and the calibration coefficient k (unit: kN / V) and initial preload F0 are calculated.

[0071] The calibration coefficient k and the initial preload F0 are bound to the bolt's unique RFID electronic tag ID and uploaded to the memory for storage, and then called by the controller.

[0072] Among them, multi-stage loading can be referenced from 0kN to 120% of the design preload, with a step of 10kN; In this embodiment, the calibration coefficient k and initial preload data of the corresponding automotive bolt are obtained by using the tightening torque signal (20Nm-150Nm) and the piezoelectric raw signal (0V-5V); In this embodiment, during vehicle startup, the signal processing module acquires the original voltage signal from the piezoelectric sensing module at a sampling rate of 500Hz.

[0073] Real-time filtering is performed using a low-pass filter with a cutoff frequency set to 200Hz to filter out high-frequency electromagnetic interference and mechanical noise generated by engine operation and road surface unevenness; the filtered signal is then used as the reference input for subsequent calculations.

[0074] In this embodiment, a smooth voltage signal can be obtained by low-pass filtering the original piezoelectric voltage signal.

[0075] Next, based on environmental compensation and real-time preload calculation, the preload of the vehicle bolts during driving is further monitored in real time. In this embodiment, the preset value is the calibrated temperature of 25°C. Specifically, when the temperature sensor detects that the temperature deviates from the calibrated temperature (25°C, i.e., the preset temperature threshold), the voltage signal is corrected according to the temperature compensation coefficient α; where α ranges from 0.001 to 0.005°C.

[0076] If the current temperature is 85°C and the temperature difference is 60°C, then the original voltage is calculated using the temperature compensation coefficient. The formula for calculating the temperature-compensated voltage signal Vt is as follows: .

[0077] Furthermore, based on the acceleration amplitude detected by the vibration sensor (when it is greater than 5g), the vibration compensation coefficient β is used for correction.

[0078] Furthermore, the corrected voltage value is multiplied by the calibration coefficient k stored in step a to obtain the current real-time preload value F(t).

[0079] In this embodiment, the corrected real-time preload value is obtained by filtering voltage, ambient temperature, and vibration acceleration.

[0080] Next, the current preload F(t) is compared with the initial preload to obtain the bolt condition assessment and loosening identification results. Based on the assessment results or loosening identification results, the corresponding alarm is triggered. Specifically, the current preload F(t) is compared with the initial preload F0 in real time. When F(t) drops to 85% of F0, it is considered a minor loosening; When F(t) drops below 70% of F0, it is considered severely loose.

[0081] At the same time, the frequency domain energy of the piezoelectric signal is judged. When the proportion of energy in the low frequency band (10Hz-50Hz) increases by more than 30%, it is determined that the stiffness of the fastener connection has decreased, that is, plastic deformation or loosening tends to occur.

[0082] In this embodiment, the loosening state is graded by judging the real-time preload F(t), wherein the loosening state is graded at least into three levels: normal, warning, and alarm.

[0083] Finally, based on the load spectrum, the remaining life is predicted to achieve the goal of monitoring the entire life cycle of automotive bolts; Specifically, the life prediction module records the number of load cycles n experienced by the bolt; The preload fluctuation amplitude is divided into different levels, and the damage value D is calculated using a linear cumulative damage model in combination with the SN curve of the bolt material.

[0084] When the real-time temperature exceeds 120°C or the vibration acceleration continuously exceeds 10g, the damage weighting coefficient for that period is increased by 1.5 times.

[0085] When the cumulative damage value D reaches 0.8, a warning is issued suggesting the replacement of the car bolts, and the remaining mileage is predicted.

[0086] In this embodiment, the remaining service life percentage and early warning signals are obtained by using load cycle data and temperature / vibration spectrum, thereby achieving effective monitoring of the entire life cycle of automotive bolts.

[0087] Furthermore, in this embodiment, if the piezoelectric sensing module fails, the present invention can also automatically switch to the calculation mode based on the historical trend of tightening torque as an emergency backup.

[0088] Furthermore, in environments without an onboard gateway, the data required for calibration parameters can be stored in an embedded storage module on top of the bolt and read via NFC near-field communication.

[0089] The calibration coefficient k is 10.0~50.0 kN / V, preferably 25.0 kN / V, which is the conversion ratio between piezoelectric voltage signal and axial preload. The temperature compensation coefficient α ranges from 0.0005 to 0.0080 °C, preferably 0.0025 °C, and is used to correct the sensitivity drift of piezoelectric materials as temperature increases; The loosening alarm threshold ranges from 60% to 90%, preferably 75%, which is the lower limit of the current preload to the initial preload. The sampling frequency ranges from 100 to 2000 Hz, preferably 1000 Hz, which is the data acquisition frequency during the production calibration stage.

[0090] The present invention also provides an intelligent monitoring bolt with an integrated piezoelectric sensing module, which uses the aforementioned real-time preload detection system to monitor the preload of automotive bolts throughout their entire life cycle, and assesses bolt loosening and / or service life based on the monitoring results.

[0091] In this invention, the intelligent monitoring bolt with integrated piezoelectric sensing module includes a bolt body 1, which has an axial accommodating cavity 2 inside; The stress guiding structure 3 is set on the bolt body 1 and is used to convert the axial force borne by the bolt body 1 into radial pressure. Sensing module 4 includes a piezoelectric sensing unit 41, a temperature and humidity sensing unit 42, and a triaxial acceleration unit 43; Among them, the piezoelectric sensing unit 41 is disposed in the axial accommodating cavity 2, and is used to sense the radial pressure collected by the stress guiding structure 3 and transmit the electrical signal corresponding to the pressure to the controller. The temperature and humidity sensing unit 42 is used to collect temperature and humidity data of the bolt body 1 and transmit the collected temperature and humidity data to the controller. The three-axis acceleration unit 43 is used to collect the vibration signals generated by the bolt body 1 during operation and transmit them to the controller.

[0092] This invention addresses the limitation of existing technologies, which can only monitor the preload of automotive bolts during the production stage and cannot effectively monitor the preload and / or lifespan of automotive bolts during vehicle operation. This invention enables effective monitoring of the preload and / or lifespan of automotive bolts even after the vehicle has been driven or left the factory, by embedding sensors within the bolts. This significantly improves the reliability and safety of the vehicle during operation and reduces accidents caused by shortened service life or damage to the bolt body due to loosening or damage.

[0093] Specifically, this embodiment provides an intelligent monitoring bolt integrating a piezoelectric sensing module, which monitors the preload of automotive bolts throughout their entire lifecycle using a real-time preload detection system. This system is used to monitor the service life, working condition, and fatigue level of automotive bolts. The system includes: The bolt body 1 has an axial accommodating cavity 2 inside. The bolt body 1 has a stress guiding structure 3 on its outer periphery. The stress guiding structure 3 is an annular groove with a groove angle of 60° and a groove depth of 30% of the bolt diameter. It is used to convert the axial tensile force borne by the bolt into radial contraction deformation and amplify it by 1.5 times. The axial accommodating cavity 2 is located at the bolt head 5.

[0094] The piezoelectric sensing unit 41 is installed in the axial accommodating cavity 2 by interference fit or spring preload 6 and is correspondingly arranged with the stress guiding structure 3 to sense radial pressure and generate charge signal. Temperature sensing unit for real-time acquisition of bolt temperature; Vibration sensing unit is used to collect bolt vibration acceleration in real time; The production stage calibration module is used to load torque at multiple levels (from 0kN to 120% of the design preload, in 10kN increments) during bolt assembly, synchronously acquire piezoelectric signals and establish a linear mapping relationship to obtain the calibration coefficient k (unit kN / V) and the initial preload F0. The signal conditioning circuit, including a charge amplification module and a low-pass filter with a cutoff frequency of 200Hz, is used to convert the charge signal into a voltage signal and filter it. The data processing module is used to calculate the temperature ΔT collected by the temperature sensing unit according to the compensation formula. Temperature compensation is performed, where α = 0.0025 / ℃. This is the original voltage; The temperature difference is calculated as the difference between the current real-time temperature and the calibrated temperature; where, As a compensation factor; When ΔT = 0 (i.e., current temperature = 25°C), no compensation is needed; When ΔT > 0 (temperature increases), the compensation factor increases, the voltage signal after temperature compensation decreases, and the compensation sensitivity decreases. When ΔT < 0 (temperature decreases), the compensation factor decreases, the voltage signal after temperature compensation increases, and the compensation sensitivity increases. Next, based on the acceleration A > 5g collected by the vibration sensing unit, the vibration compensation coefficient β = 1.2 is used for correction to obtain the compensation voltage. ; Controller used to calculate real-time preload. ,when Minor loosening is judged when the loosening rate is ≤70%, severe loosening is judged when the loosening rate is ≤70%, and the connection stiffness is judged to have decreased when the energy proportion of 10-50Hz in the piezoelectric signal frequency domain increases by more than 30%. Load levels are classified based on the preload fluctuation amplitude, and the damage value D is calculated using a linear cumulative damage model based on the bolt material's SN curve. When the real-time temperature is >120℃ or the vibration acceleration is >10g, the damage weight of the corresponding time period will be increased by 1.5 times. When D≥0.8, a replacement warning and remaining driving range will be output.

[0095] The intelligent monitoring bolt with integrated piezoelectric sensing module provided by this invention is applied to fastener status monitoring during the automobile assembly stage and the vehicle service stage (when the vehicle is working / driving). The real-time preload detection system provided in this case includes a bolt body 1, a stress guiding structure 3, a sensing module 4, a signal conditioning circuit, a production calibration module, a data processing module, a condition assessment module, and a controller.

[0096] The bolt body 1 is made of 10.9 grade alloy steel, and an axial accommodating cavity 2 is formed on its central axis. The axial accommodating cavity 2 is used to accommodate the piezoelectric sensing unit 41 and auxiliary sensing components.

[0097] The stress guiding structure 3 is disposed on the outer periphery of the bolt body 1, and its axial position corresponds to the piezoelectric sensing unit 41 in the axial accommodating cavity 2.

[0098] In this invention, when the bolt body 1 is subjected to axial tensile force during assembly or service, according to the Poisson effect in mechanics of materials, the bolt body 1 will undergo axial elongation and radial contraction. The stress guiding structure 3 weakens the local cross-sectional area, making the area a stress concentration zone, thereby amplifying the radial contraction deformation.

[0099] The radial deformation acts on the piezoelectric sensing unit 41 within the axially accommodating cavity 2, causing it to generate a charge signal proportional to the pressure.

[0100] The charge signal is converted into a voltage signal by the charge amplifier in the signal conditioning circuit, and then the noise is reduced by the filtering module.

[0101] During the automobile production and assembly stage, when torque is applied to the bolt body 1, torque signals and piezoelectric output signals are collected simultaneously to establish a mapping relationship between preload and voltage signals and obtain calibration parameters.

[0102] When the vehicle is in the working / driving stage, the piezoelectric signal of the bolt body 1 is continuously collected by the sensing module 4. The piezoelectric signal of the bolt body 1 is compensated by combining temperature and vibration data to obtain the real-time preload value.

[0103] Next, the real-time preload is compared with the initial preload using the condition assessment module. Based on the comparison results, the loosening status of the bolts can be determined. Finally, the fatigue life of the bolts is predicted and evaluated using load cycle data.

[0104] This invention enables monitoring of automotive bolts throughout their entire lifecycle, from production and assembly to operational monitoring, avoiding the limitations of traditional technologies that rely solely on assembly stage control and fail to reflect problems encountered during the operation / driving process of automotive bolts.

[0105] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A real-time preload detection system, characterized in that, include: The bolt body has an axial accommodating cavity inside, which is used to install the sensing module; The sensing module is used to collect piezoelectric signals, temperature, and vibration parameters generated by the bolt under stress. The production stage calibration module is used to collect piezoelectric signals and preload data during bolt assembly and establish a mapping relationship to obtain the initial preload and calibration parameters. The data processing module is used to perform feature extraction and compensation processing on the piezoelectric signal; The controller is used to calculate the current preload based on the calibration parameters and compensation signals, determine the loosening and deformation state of the bolts based on the changes in preload, calculate the remaining service life based on the changes in preload and environmental parameters, and output abnormal alarm information to the alarm module.

2. The real-time preload detection system as described in claim 1, characterized in that, Based on the production stage calibration module, the assembly load and induction signal of the bolt body are correlated and calibrated, and an initial mapping relationship is established. Acquire the raw sensing signals collected by the sensing module; The original inductive signal is compensated to obtain the corrected load data; The working condition of the bolt body is evaluated based on the corrected load data; The calibration of the association between assembly load and sensing signal includes: synchronously collecting the torque value applied to the bolt body and the charge signal output by the sensing module during the assembly stage, and establishing the torque and piezoelectric mapping curve as the initial mapping relationship.

3. The real-time preload detection system as described in claim 2, characterized in that, Based on the corrected load data, the damage level of the bolt body is calculated using a linear cumulative damage model, and the remaining fatigue life is predicted.

4. The real-time preload detection system as described in claim 3, characterized in that, Also includes: The signal conditioning circuit, electrically connected to the sensing module, is used to preprocess the sensed signal; The controller compensates for the preprocessed signal and performs load monitoring or lifetime assessment based on the compensated signal. The charge amplification module is used to convert the high-impedance charge signal output by the sensing module into a low-impedance voltage signal and perform filtering.

5. The real-time preload detection system as described in claim 4, characterized in that, The sensing module includes a piezoelectric sensing unit, a temperature and humidity sensing unit, and a triaxial accelerometer unit. The piezoelectric sensing unit is a piezoelectric ceramic ring or a piezoelectric film. The piezoelectric sensing unit is set in the axial cavity of the bolt body by interference fit and contacts the stress guiding structure set in the bolt body to obtain the radial pressure generated therefrom. The temperature and humidity sensing unit is used to collect temperature and humidity data of the bolt body and transmit the collected temperature and humidity data to the controller. The three-axis accelerometer unit is used to collect vibration signals generated by the bolt body during its operation.

6. The real-time preload detection system as described in claim 5, characterized in that, Establish a linear mapping relationship between voltage signal and preload force, and calculate the calibration coefficient k. When the temperature and humidity sensing unit detects that the temperature deviates from the calibrated temperature, it corrects the voltage signal based on the temperature compensation coefficient α. Specifically, if the current temperature exceeds the preset value, the original voltage will be corrected using a temperature compensation coefficient. Furthermore, based on the acceleration amplitude detected by the vibration sensor, the vibration compensation coefficient β is used for correction; the corrected voltage value is calculated with the calibration coefficient k to obtain the current real-time preload value; and the bolt body is graded for loosening based on the preload value.

7. The real-time preload detection system as described in claim 6, characterized in that, Real-time comparison of current preload with initial preload; When the current preload drops to the first preset threshold of the initial preload, it is determined to be a slight looseness; When the current preload drops below the second preset threshold of the initial preload, it is determined to be severely loose; and the frequency domain energy of the piezoelectric signal is judged. When the proportion of low-frequency energy increases by more than 30%, it is judged that the stiffness of the fastener connection has decreased, that is, plastic deformation or loosening tends to occur.

8. The real-time preload detection system as described in claim 1, characterized in that, The fluctuation amplitude of the preload is divided into different levels, and the damage value of the bolt body is calculated using a linear cumulative damage model based on the SN curve of the bolt material. When the real-time temperature exceeds the third preset value or the vibration acceleration continues to exceed the N value, the damage weighting coefficient for the corresponding time period will be increased by 1.5 times. When the cumulative damage value reaches the fourth preset value, an early warning is issued to replace the bolt body, and the remaining driving mileage is predicted.

9. A smart monitoring bolt integrating a piezoelectric sensing module, which uses the system described in any one of claims 1-8 to monitor the preload of automotive bolts throughout their entire life cycle, and assesses bolt loosening and / or service life based on the monitoring results.

10. The intelligent monitoring bolt with an integrated piezoelectric sensing module as described in claim 9, characterized in that, Includes the bolt body, which has an axial accommodating cavity inside; A stress guiding structure, installed on the bolt body, is used to convert the axial force borne by the bolt body into radial pressure. The sensing module includes a piezoelectric sensing unit, a temperature and humidity sensing unit, and a triaxial acceleration unit; Among them, the piezoelectric sensing unit is set in the axial accommodating cavity to sense the radial pressure collected by the stress guiding structure and transmit the electrical signal corresponding to the pressure to the controller; The temperature and humidity sensing unit is used to collect temperature and humidity data of the bolt body and transmit the collected temperature and humidity data to the controller. The three-axis accelerometer unit is used to collect vibration signals generated by the bolt body during operation and transmit them to the controller.

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