Small diesel engine connecting rod stress measurement system based on strain type pressure sensor

Abstract

The application discloses a small diesel engine connecting rod stress measurement system based on a strain type pressure sensor and particularly relates to the field of small diesel engine stress measurement, and comprises a follow-up measurement unit integrated on a connecting rod body, which is composed of a multi-source signal synchronous acquisition module, an online processing and compensation module, a stress reconstruction and fusion module and a wireless data transceiving module. The system realizes multi-channel signal synchronous acquisition through strain and temperature sensors arranged at dangerous sections of the connecting rod, adopts an FPGA-driven parallel ADC architecture to ensure sampling synchronism, improves data precision and anti-interference capacity through a dynamic temperature drift compensation and an adaptive filtering algorithm, reconstructs a connecting rod surface dynamic stress distribution field based on a finite element model and a stress mapping matrix, and realizes an adaptive wireless transmission strategy according to a crankshaft phase signal, wherein high stress intervals are preferentially transmitted and low stress intervals are energy-savingly operated. The system has the characteristics of high precision, high reliability and low power consumption.

Description

Technical Field

[0001] This invention relates to the field of stress measurement technology for small diesel engines, and more specifically, to a stress measurement system for connecting rods of small diesel engines based on strain gauge pressure sensing. Background Technology

[0002] During diesel engine operation, the connecting rod, as a key moving component, bears alternating gas pressure and inertial loads. Its stress state directly affects the engine's reliability, lifespan, and safety. Therefore, real-time and accurate stress monitoring of the connecting rod is of great significance. Currently, most existing connecting rod stress measurement methods employ wired strain gauge measurement systems, which use strain gauges connected to external static acquisition equipment via wires. However, these methods still have some drawbacks in practical use, such as: complex wiring that interferes with normal engine operation; difficulty in achieving strict synchronous acquisition of multi-channel signals, leading to phase errors; lack of an effective real-time temperature drift compensation mechanism, resulting in measurement results being greatly affected by ambient temperature; inability to accurately reflect the full-field characteristics of stress distribution on the connecting rod surface; and reliance on wired data transmission, which is unsuitable for high-speed rotation conditions, and also results in high system power consumption and low integration.

[0003] On the other hand, although existing systems have attempted to introduce wireless transmission functions, they often lack adaptive transmission strategies based on operating conditions, making it difficult to achieve a good balance between data real-time performance and system power consumption. They also lack remote online configuration and optimization capabilities, which limits their application effectiveness in practical engineering. Summary of the Invention

[0004] To overcome the aforementioned deficiencies of the prior art, embodiments of the present invention provide a small diesel engine connecting rod stress measurement system based on strain gauge pressure sensing, which solves the problems of large interference, low accuracy, limited information, and lack of intelligence mentioned in the background art through the following solutions.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a small diesel engine connecting rod stress measurement system based on strain gauge pressure sensing, comprising a follow-up measurement unit integrated on the connecting rod body, the unit comprising:

[0006] Multi-source signal synchronous acquisition module: directly connected to the strain sensor group, temperature sensor and acquisition component for monitoring the crankshaft motion state of the diesel engine arranged at the critical section of the connecting rod, used to synchronously acquire and process the signals of each sensor and the crankshaft phase signal and real-time speed signal output by the acquisition component to generate multi-channel digital signals;

[0007] Online processing and compensation module: Connects to the multi-source signal synchronous acquisition module, receives multi-channel digital signals, processes them through built-in algorithms, performs dynamic temperature drift compensation on the data of each strain channel based on temperature sensor data, and generates standard strain data;

[0008] Stress Reconstruction and Fusion Module: Integrated into the online processing and compensation module, it is used to receive standard strain data, perform spatial domain fusion analysis, and reconstruct the dynamic stress distribution field on the connecting rod surface;

[0009] Wireless data transceiver module: Connects to the stress reconstruction and fusion module, receives dynamic stress distribution field data, and transmits stress distribution information to an external monitoring terminal.

[0010] Preferably, the multi-source signal synchronous acquisition module includes an FPGA-based parallel sampling control unit, which configures an independent analog-to-digital converter for each sensing channel and drives all ADCs to start sampling synchronously through a global clock signal generated inside the FPGA.

[0011] Preferably, the process of the online processing and compensation module performing dynamic temperature drift compensation includes:

[0012] A sensor characteristic model is established with temperature as the independent variable and strain measurement error as the dependent variable; based on the synchronously acquired real-time temperature data, the sensor characteristic model is called to calculate the instantaneous compensation value at the current temperature; the instantaneous compensation value is applied to the raw data of the strain channel to generate standard strain data;

[0013] The parameters of the sensor characteristic model are obtained by pre-calibrating the sensing system globally under a temperature-controlled environment.

[0014] Preferably, the online processing and compensation module further includes adaptive filtering processing, which dynamically adjusts the cutoff frequency of the digital filter based on the real-time speed signal of the diesel engine output by the multi-source signal synchronous acquisition module.

[0015] Preferably, the process of reconstructing the dynamic stress distribution field by the stress reconstruction and fusion module includes:

[0016] A parametric finite element model of the connecting rod is pre-established and modified through modal testing to obtain a high-precision stress mapping matrix. The standard strain data generated by the online processing and compensation module is used as input. Using the stress mapping matrix, the stress distribution over the entire surface of the connecting rod is solved through a single matrix operation. The solution results are then visualized and reconstructed to generate dynamic stress cloud map data.

[0017] Preferably, the transmission strategy of the wireless data transceiver module is optimized based on the diesel engine crankshaft phase signal, specifically including:

[0018] Within the crankshaft rotation angle range where the connecting rod is subjected to the maximum tensile and compressive stress, high-speed, high-priority data packet transmission is initiated. In the low-stress range, a low-speed energy-saving mode is adopted, thereby achieving adaptive wireless transmission based on working condition awareness.

[0019] Preferably, the encapsulation housing of the follow-up measurement unit is made of a high thermal conductivity ceramic material, and its outer surface is designed to conformally fit the surface contour of the connecting rod. The internal electronic components are connected to the housing through thermal conductive gel, forming an efficient heat dissipation path from the inside to the outside.

[0020] Preferably, the external monitoring terminal generates control commands based on the received stress distribution field data and sends them wirelessly to the follow-up measurement unit; the online processing and compensation module can dynamically adjust its filtering parameters or compensation coefficients according to the control commands to realize online remote configuration and adaptive optimization of the measurement system.

[0021] Preferably, the control commands specifically include:

[0022] Filter parameter adjustment command: used to dynamically set the cutoff frequency and filter order of the adaptive filtering algorithm;

[0023] Compensation model selection command: Used to select a specific set of parameters suitable for the current operating condition from a set of pre-stored sensor characteristic model parameters;

[0024] Data acquisition trigger command: Used to control the multi-source signal synchronous acquisition module to perform high-speed acquisition within the crankshaft angle range of 170-190 degrees and 350-370 degrees;

[0025] Transmission mode switching command: Used to configure the wireless data transceiver module to switch between high-power high-speed transmission mode and low-power intermittent transmission mode.

[0026] The technical effects and advantages of this invention are as follows:

[0027] 1. This invention adopts a parallel synchronous acquisition architecture based on FPGA, which ensures strict synchronization of multi-channel signal sampling and eliminates phase error; through the third-order polynomial temperature drift compensation model established by global calibration and the adaptive filtering algorithm based on rotational speed, the interference of temperature change and high-frequency noise is effectively suppressed, and the accuracy and reliability of strain data are significantly improved.

[0028] 2. By combining a finite element model corrected by modal testing, this invention systematically reconstructs the strain data of a finite number of measuring points into a dynamic stress distribution field over the entire surface of the connecting rod in real time using a pre-solved stress mapping matrix, and generates a visualized stress cloud map. This overcomes the limitation of traditional methods that can only obtain discrete point data, and provides more comprehensive and intuitive data support for connecting rod stress analysis.

[0029] 3. This invention integrates four major functional modules into a conformally fitted ceramic housing, achieving miniaturization, lightweighting, and high reliability of the servo measurement unit; the wireless transmission strategy is intelligently optimized based on the crankshaft phase signal, adopting a high-speed, high-reliability mode in the high-stress range and switching to a low-speed, low-power mode in the low-stress range, thereby achieving adaptive balance of system power consumption and extending working time while ensuring that key data is not lost. Attached Figure Description

[0030] Figure 1 This is a schematic diagram of the overall structure of the present invention;

[0031] Figure 2 This is a schematic diagram of the dynamic temperature drift compensation and adaptive filtering process of the present invention;

[0032] Figure 3 This is a schematic diagram of the adaptive wireless transmission strategy process of the present invention. Detailed Implementation

[0033] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0034] As attached Figure 1-3 The small diesel engine connecting rod stress measurement system based on strain gauge pressure sensing shown includes:

[0035] The servo measurement unit, integrated on the connecting rod body, contains four main functional modules: a multi-source signal synchronous acquisition module, an online processing and compensation module, a stress reconstruction and fusion module, and a wireless data transceiver module. Each module is integrated into a sealed housing made of high thermal conductivity aluminum nitride ceramic using three-dimensional stacking and system-level packaging technology.

[0036] Multi-source signal synchronous acquisition module: directly connected to the strain sensor group, temperature sensor and acquisition component for monitoring the crankshaft motion state of the diesel engine arranged at the critical section of the connecting rod, used to synchronously acquire and process the signals of each sensor and the crankshaft phase signal and real-time speed signal output by the acquisition component to generate multi-channel digital signals.

[0037] It should be further noted that the strain sensor group uses metal foil strain gauges with a sensitivity coefficient K=2.10±0.02 and a grid length of 3mm, and is arranged at the three critical sections of the connecting rod.

[0038] Small end transition zone, section A, bearing concentrated reciprocating inertial force: 2 pieces, symmetrically arranged along the connecting rod axis, measuring points 1 and 2;

[0039] The large-head transition zone, section B, bears concentrated burst pressure: 2 pieces, arranged radially, measuring points 3 and 4;

[0040] The middle section of the pole, section C, has the greatest bending stress: 4 pieces are used to form a full bridge measurement, with measuring points 5-8, to eliminate the cross-influence of temperature.

[0041] The temperature sensor is a PT1000 platinum resistance thermometer with Class A accuracy and an error of ≤±0.15℃ within the range of -40-120℃. It is placed close to the strain gauge at section B and next to measuring point 3, with the temperature consistent with the strain sensing environment.

[0042] The acquisition component for monitoring the motion status of the diesel engine crankshaft is a Hall sensor adapted to the 60-2 gear plate of the crankshaft. The operating temperature is -40 to 150℃, the response frequency is ≥10kHz, and it is installed inside the crankcase of the diesel engine near the 60-2 gear plate. The gap between the sensor sensing surface and the tooth tip of the gear plate is controlled within 0.5 to 1mm.

[0043] It should be noted that the multi-source signal synchronous acquisition module includes an FPGA-based parallel sampling control unit. This unit configures an independent analog-to-digital converter for each sensing channel and drives all ADCs to start sampling synchronously through a global clock signal generated inside the FPGA.

[0044] It should be further noted that the FPGA has 9 sensing channels, including 8 strain ADCs and 1 temperature ADC, each configured with an independent 16-bit ADC and a sampling rate f. ADC ≥1MSPS, full-scale voltage V FS =±5V; The sampling trigger terminal of each ADC is directly connected to the global clock pin of the FPGA, and the global synchronization clock CLK is generated by the internal phase-locked loop of the FPGA, with a frequency f CLK =50MHz, duty cycle 50%, sampling delay difference of all ADCs ≤10ns.

[0045] It should be further explained that the FPGA receives the crankshaft phase signal through the GPIO port, which is generated by the Hall sensor monitoring the crankshaft 60-2 gear, with a resolution of 0.5 degrees crankshaft rotation angle; the acquisition trigger condition is defined as triggering one multi-channel synchronous sampling every 1 degree crankshaft rotation angle, i.e., the sampling interval is... ,in The real-time speed of the diesel engine is calculated using the crankshaft phase signal period. ,in This is the time it takes for the crankshaft to rotate one revolution.

[0046] For each ADC's digital output D, the corresponding analog voltage value Where n is the ADC resolution, n=16, a fixed value. The voltage across the ADC's full scale is given by , and D is the digital output of the ADC in real time; the original strain measurement value is also given. Derived from the characteristics of a full-bridge strain gauge circuit, where K is the strain gauge sensitivity coefficient. This is the excitation voltage for the strain bridge circuit.

[0047] Online processing and compensation module: Connects to the multi-source signal synchronous acquisition module, receives multi-channel digital signals, processes them through built-in algorithms, performs dynamic temperature drift compensation on the data of each strain channel based on temperature sensor data, and generates standard strain data.

[0048] It should be specifically noted that the process of dynamic temperature drift compensation performed by the online processing and compensation module includes:

[0049] A sensor characteristic model is established with temperature as the independent variable and strain measurement error as the dependent variable; based on the synchronously acquired real-time temperature data, the sensor characteristic model is called to calculate the instantaneous compensation value at the current temperature; the instantaneous compensation value is applied to the raw data of the strain channel to generate standard strain data;

[0050] The parameters of the sensor characteristic model are obtained by pre-calibrating the sensing system globally under a temperature-controlled environment.

[0051] It should be further noted that the sensor characteristic model is established using a third-order polynomial model to describe the relationship between temperature T and strain measurement error. Relationship ,in , , , Here, T represents the model coefficients, and T is the real-time temperature collected. After real-time acquisition of T, it is substituted into the model to calculate the standard strain. .

[0052] It should be further explained that global calibration includes:

[0053] Calibration environment: Fix the connecting rod and the follow-up measurement unit to a high and low temperature control chamber, with a temperature range of [temperature range missing]. to Temperature control accuracy ±0.5℃, the other end of the connecting rod is fixed to the tensile testing machine, and the loading accuracy ±1N.

[0054] Calibration steps: Set the temperature of the temperature control chamber to [value missing]. Where k is the temperature sampling number, , For temperature intervals, The tensile testing machine applies standard strain. Where m is the standard strain level index. , , , , Ten raw strain measurements were collected at each strain point. Take the average value Calculate the error at this temperature. .

[0055] Coefficient fitting: The least squares method was used for all... , Fitting, to obtain , , , .

[0056] It should be specifically noted that the online processing and compensation module also includes adaptive filtering, which dynamically adjusts the cutoff frequency of the digital filter according to the real-time speed signal of the diesel engine to suppress high-frequency noise that is unrelated to engine speed, while preserving the dynamic characteristics of the stress signal.

[0057] It should be further noted that in the selection of the filtering algorithm, an FIR filter with linear phase characteristics is used to avoid phase distortion of the stress signal. The filter order M is set to M=32 by default, and its unit impulse response is... Through the design of the Hanning window, the expression is: ,in This is the filter cutoff frequency. Here, i represents the FPGA global clock frequency, and i is the filter coefficient index. ; Filter cutoff frequency The frequency is dynamically adjusted based on the dominant frequency of the stress signal. It is positively correlated with the diesel engine speed, and the calculation formula is as follows: , where s is the diesel engine stroke coefficient (s=2 for four-stroke, s=1 for two-stroke, a fixed value). For real-time rotational speed; to balance noise suppression and signal integrity, the filter cutoff frequency... Take 1.3 times the main frequency, that is The filtering calculation process is implemented in the FPGA. A FIFO buffer of depth M is allocated within the FPGA to store the most recent M standard strains. Strain after filtering Where t is the current time, The sampling interval is denoted as .

[0058] Stress Reconstruction and Fusion Module: Integrated with the online processing and compensation module in the same processing unit, it is used to receive standard strain data, perform spatial domain fusion analysis, and reconstruct the dynamic stress distribution field on the connecting rod surface.

[0059] It should be specifically noted that the process of reconstructing the dynamic stress distribution field by the stress reconstruction and fusion module includes:

[0060] A parametric finite element model of the connecting rod is pre-established and modified through modal testing to obtain a high-precision stress mapping matrix. The standard strain data generated by the online processing and compensation module is used as input. Using the stress mapping matrix, the stress distribution over the entire surface of the connecting rod is solved through a single matrix operation. The solution results are then visualized and reconstructed to generate dynamic stress cloud map data.

[0061] It should be further noted that in the construction of the basic model, a parametric model of the connecting rod was established using general-purpose finite element analysis software. The material is 40Cr steel, and its parameters are taken from the standard values ​​in the material handbook, including density. elastic modulus Poisson's ratio The mesh generation uses tetrahedral elements suitable for stress analysis of complex structures, and the model has a total of [number of elements]. Number of nodes The mesh was further refined at the critical sections A, B, and C, with a unit size of 0.5 mm.

[0062] Modal testing was conducted to improve model accuracy. A vibration hammer, an accelerometer with a sensitivity of 100 mV / g, and a data acquisition instrument were used, with the sampling rate and number of channels adapted for modal signal acquisition. During the test, the connecting rod was freely suspended, and a vibration hammer struck the middle of the rod. An accelerometer was attached to the top of the small end of the rod to collect the 1st to 5th natural frequencies. (m=1~5), by comparing the frequency calculated by finite element method Compared with test values The elastic modulus E is corrected, with an adjustment range of ±5%, until the frequency errors of all orders meet the requirements. The corrected elastic modulus is E=203GPa.

[0063] Based on the modified model, the stress mapping matrix is ​​further solved, and the strain vector after 8-way filtering is defined. With the stress vector of all nodes of the link The linear mapping relationship between them is Where A is A dimensional stress mapping matrix, elements Let represent the mapping coefficient of the i-th node to the j-th strain path; to solve matrix A, unit strain is applied sequentially to the eight strain measurement points in the finite element model. The direction is consistent with the strain gauge sensing grid, and the stress values ​​of all nodes under each working condition are calculated. Then, matrix A is constructed and stored in the Block RAM of the FPGA.

[0064] In dynamic stress reconstruction and visualization, FPGA receives... Then, matrix operations are performed in real time using a hardware multiplier array. The calculation time is no more than 1 μs; range constraints are applied to the calculated nodal stresses. , Corresponding to the yield strength of 40Cr steel, outliers outside the range are replaced with the stress values ​​of the nearest neighbor nodes. Subsequently, the stress data σ and the node coordinates (x, y, z) are packaged in a general visualization data format that supports 3D rendering to generate dynamic stress cloud map data. A frame of data is generated every 10 degrees of crankshaft rotation. The frame structure includes: frame header, number of nodes, coordinates of each node and stress data, and CRC16 checksum, for subsequent wireless transmission.

[0065] Wireless data transceiver module: Connects to the stress reconstruction and fusion module, receives dynamic stress distribution field data, and transmits stress distribution information to an external monitoring terminal.

[0066] It should be specifically noted that the transmission strategy of the wireless data transceiver module is optimized based on the diesel engine crankshaft phase signal, specifically including:

[0067] Within the crankshaft rotation angle range where the connecting rod is subjected to the maximum tensile and compressive stress, high-speed, high-priority data packet transmission is initiated. In the low-stress range, a low-speed energy-saving mode is adopted, thereby achieving adaptive wireless transmission based on working condition awareness.

[0068] It should be further explained that the module uses a 2.4GHz wireless transceiver chip with GFSK modulation, a maximum transmission rate of ≥2Mbps, and implements an adaptive transmission strategy based on the crankshaft phase signal to balance the system's low power consumption and high reliability requirements. The core of the transmission strategy is to divide the crankshaft rotation angle range according to the stress level: bench tests determine that the maximum compressive stress range occurs within a 180-degree crankshaft rotation angle ±10 degrees during the burst pressure period of the connecting rod. During the period of reciprocating inertial force, the maximum tensile stress range occurs within a 360-degree crankshaft rotation angle of ±10 degrees. The union of these two values, namely crankshaft rotation angles of 170-190 degrees and 350-370 degrees, is defined as the high-stress range. The remaining areas are low-stress areas. .

[0069] For different intervals, the system employs configurable transmission mode parameters: In The interval uses high-speed mode with a transmission rate of v=2Mbps, a data packet size of S=256 bytes, containing stress data, phase information, and status words, a transmission interval of T=1ms, and an operating current of I=15mA; The interval is switched to low-speed mode, v=250kbps, S=64Byte, T=10ms, I=3mA; all default values ​​of transmission parameters are pre-stored in MCU Flash, supporting flexible configuration.

[0070] The execution of the transmission strategy depends on the MCU's control over the crankshaft phase signal. Real-time analysis: when Upon entering the high-stress zone, the high-speed mode is immediately triggered, configuring the wireless chip register to enable high-speed transmission and automatic retransmission mechanism, retransmitting 3 times with a delay of 250μs to ensure a packet loss rate ≤0.1%; when When in the low stress range, it switches to low speed mode and disables retransmission to significantly reduce power consumption, thereby achieving an adaptive balance between power consumption and transmission reliability.

[0071] It should be specifically noted that the external monitoring terminal generates control commands based on the received stress distribution field data and sends them wirelessly to the follow-up measurement unit; the online processing and compensation module can dynamically adjust its filtering parameters or compensation coefficients according to the control commands to realize online remote configuration and adaptive optimization of the measurement system.

[0072] It should be further explained that the control commands specifically include:

[0073] Filter parameter adjustment command: used to dynamically set the cutoff frequency and filter order of the adaptive filtering algorithm;

[0074] Compensation model selection command: Used to select a specific set of parameters suitable for the current operating condition from a set of pre-stored sensor characteristic model parameters;

[0075] Data acquisition trigger command: Used to control the multi-source signal synchronous acquisition module to perform high-speed acquisition within the crankshaft angle range of 170-190 degrees and 350-370 degrees;

[0076] Transmission mode switching command: Used to configure the wireless data transceiver module to switch between high-power high-speed transmission mode and low-power intermittent transmission mode.

[0077] It should be further explained that the triggering conditions for the external monitoring terminal to generate control commands are divided into three categories, all based on the received stress distribution field data and real-time analysis of the system operating conditions, as detailed below:

[0078] Stress data anomaly trigger: When the maximum stress value of any critical section in five consecutive frames of stress cloud maps exceeds the configurable normal threshold range (default σ∈[-250MPa,180MPa]), and sensor faults are ruled out through multi-point data consistency verification, if the current temperature T deviates from the adaptation range of the currently enabled compensation model, a compensation model selection command is generated to switch to the model adapted to the current T; if the current temperature T is still within the adaptation range of the current model, it is determined that the anomaly is caused by noise interference, and a filter parameter adjustment command is generated to increase the filter order M; when the stress at a certain measuring point is detected to fluctuate more than 5 times and the fluctuation amplitude is greater than 50MPa within one working cycle, it is determined to be high-frequency noise interference, and a filter parameter adjustment command is generated to increase the cutoff frequency. .

[0079] Operating condition change trigger: Real-time monitoring of diesel engine speed at the terminal With ambient temperature T, when When the change in speed exceeds 500 r / min within 10 seconds, the terminal automatically calculates the optimal filtering parameters under the new operating condition. It generates filter parameter adjustment instructions; when the temperature change is greater than 15°C within 5 minutes, the terminal selects an appropriate compensation model based on the new temperature range and generates a compensation model selection instruction; when entering special operating conditions, the terminal generates data acquisition trigger instructions and transmission mode switching instructions, and starts high-speed acquisition within the crankshaft angle range of 0-360 degrees. .

[0080] User-initiated configuration trigger: Through the manual configuration interface provided by the terminal software, users can input target parameters according to testing needs. When high-precision mode is selected, the terminal generates filter parameter adjustment instructions, M=64. And a transmission mode switching command, forcing high-speed mode; when low-power mode is selected, a filter parameter adjustment command is generated, M=16. The terminal generates a data acquisition trigger command when the user clicks the parameter calibration button. The data acquisition is initiated within a specific crankshaft angle range, such as 180 degrees ± 5 degrees, to calibrate the compensation coefficient.

[0081] After receiving the control command, the online processing and compensation module of the servo measurement unit executes the dynamic adjustment parameters in sequence. The wireless data transceiver module transmits the command data to the MCU through the SPI interface. The MCU first performs CRC8 verification. If the verification fails, the command is discarded and an error signal is sent back to the terminal. After the verification passes, the command type and parameters are parsed. The parsing result is temporarily stored in the MCU's RAM buffer. Subsequently, the MCU sends a message that the command was successfully received.

[0082] For filter parameter adjustment, the MCU uses the AXI-Lite interface to... M is written to the corresponding register in the FPGA, and M is converted into 8-bit binary data and written to the filter order register. The FPGA adjusts the FIFO buffer depth accordingly. The data is converted to 16-bit binary data and written to the cutoff frequency register. The FPGA calculates the new FIR filter coefficients in real time based on the specified formula and updates the filter coefficient buffer. After the update is completed, the FPGA sends a filter parameter activation interrupt signal to the MCU. The MCU records the parameters and time for traceability.

[0083] If the instruction is for compensation model selection, the MCU will... The pre-stored compensation coefficients a0-a3 are read from Flash and then written to the FPGA's compensation coefficient register in 32-bit floating-point format via SPI. The FPGA directly calls the new coefficients in the temperature drift compensation calculation, while the MCU simultaneously updates the backup in RAM. Subsequently, the MCU acquires the current temperature T and substitutes it into the new model for calculation. Compared with the previous model: if the error is ≤2με, the feedback compensation model will take effect; otherwise, it will revert to the original model and trigger an alarm.

[0084] After the parameters were adjusted, the system continuously collected 10 sets of data. , The data is used to calculate the stability indicators before and after the adjustment. If the indicators meet the standards, the MCU sends a "parameter adjustment successful" signal to the terminal containing the parameter values ​​and indicators. If the indicators do not meet the standards, the MCU will automatically retry up to 3 times. If the MCU still fails, it will trigger an alarm on the terminal and prompt manual intervention.

[0085] It should be specifically noted that the encapsulation housing of the follow-up measurement unit is made of high thermal conductivity ceramic material, and its outer surface is designed to conformally fit the surface contour of the connecting rod. The internal electronic components are connected to the housing through thermal conductive gel, forming an efficient heat dissipation path from the inside to the outside.

[0086] It should be further noted that the shell material is aluminum nitride ceramic, with a thermal conductivity λ=170W / (m・K) and a bending strength ≥300MPa. The connecting rod surface contour was 3D scanned with an accuracy of 0.01mm. The shell is CNC machined into an arc-shaped fit structure with a gap ≤0.1mm between it and the connecting rod surface; the shell thickness d=2mm and the weight ≤15g; the bottom of the internal electronic components is coated with a high thermal conductivity gel, with a thermal conductivity of... With a thickness δ=0.5mm, the gel adheres tightly to the inner wall of the shell, forming a heat dissipation path of component-thermal conductive gel-AlN shell-air; heat dissipation rate ,in Where S is the temperature of the component relative to the environment, and S is the heat dissipation area of ​​the component. The thermal conductivity of AlN is... d and d represent the thickness of the gel and the shell, respectively.

[0087] Secondly: The accompanying drawings of the embodiments disclosed in this invention only involve the structures involved in the embodiments disclosed in this invention. Other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of this invention can be combined with each other.

[0088] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A small diesel engine connecting rod stress measurement system based on a strain gauge pressure sensor, characterized by, The application relates to a real-time monitoring system for a connecting rod of a diesel engine. The system comprises: a multi-source signal synchronous acquisition module connected with a strain sensor group arranged at a dangerous section of the connecting rod, a temperature sensor and an acquisition assembly for monitoring the motion state of a diesel engine crankshaft, for synchronously acquiring and processing the signals of the sensors and the crankshaft phase signal and the real-time rotating speed signal output by the acquisition assembly, and for generating multi-channel digital signals; the multi-source signal synchronous acquisition module comprises an FPGA-based parallel sampling control unit, which is provided with independent analog-to-digital converters for each sensing channel and drives all the ADCs to synchronously start sampling through a global clock signal generated in the FPGA; an online processing and compensation module connected with the multi-source signal synchronous acquisition module, receives the multi-channel digital signals and processes the signals through built-in algorithms, dynamically compensates the strain channel data based on the temperature sensor data and generates standard strain data; the online processing and compensation module comprises the following steps for dynamically compensating the strain channel data: a sensor characteristic model is established with temperature as the independent variable and strain measurement error as the dependent variable; based on the real-time temperature data synchronously acquired, the sensor characteristic model is called to calculate the instantaneous compensation value under the current temperature; and the instantaneous compensation value is applied to the original data of the strain channel to generate standard strain data; the parameters of the sensor characteristic model are obtained by globally calibrating the sensing system in a temperature-controlled environment in advance; a stress reconstruction and fusion module receives the standard strain data generated by the online processing and compensation module, performs spatial domain fusion analysis and reconstructs a dynamic stress distribution field of the connecting rod surface; the stress reconstruction and fusion module comprises the following steps for reconstructing the dynamic stress distribution field: a parameterized finite element model of the connecting rod is established in advance and is corrected through a modal test to obtain a high-precision stress mapping matrix; the standard strain data generated by the online processing and compensation module is taken as input, the stress mapping matrix is used to solve the stress distribution of the connecting rod surface through one-time matrix operation, the solving result is visualized and reconstructed to generate dynamic stress cloud data; a wireless data transceiver module connected with the stress reconstruction and fusion module receives the dynamic stress distribution field data and transmits the stress distribution information to an external monitoring terminal.

2. A compact diesel engine connecting rod stress measurement system based on a strain gauge pressure sensor according to claim 1, characterized in that: The online processing and compensation module further comprises adaptive filtering processing which dynamically adjusts the cut-off frequency of a digital filter according to the real-time rotating speed signal of the diesel engine output by the multi-source signal synchronous acquisition module.

3. A compact diesel engine connecting rod stress measurement system based on a strain gauge pressure sensor according to claim 1, characterized in that: The transmission strategy of the wireless data transceiver module is optimized based on the crankshaft phase signal of the diesel engine, and specifically comprises: in the crankshaft rotation angle interval in which the connecting rod bears the maximum tensile and compressive stress, high-speed and high-priority data packet transmission is started, and in the low stress interval, a low-speed energy-saving mode is adopted, so that adaptive wireless transmission based on working condition sensing is realized.

4. The compact diesel engine connecting rod stress measurement system based on a strain gauge pressure sensor of claim 1, characterized in that: The packaging shell of the follow-up measurement unit is made of high-thermal-conductivity ceramic material, the outer surface of the packaging shell is designed to conform to the surface profile of the connecting rod, and the internal electronic components are connected with the shell through thermal conductive gel to form a high-efficiency heat dissipation path from the inside to the outside.

5. The compact diesel engine connecting rod stress measurement system based on a strain gauge pressure sensor of claim 1, wherein: The external monitoring terminal generates control instructions according to the received stress distribution field data and transmits the control instructions to the follow-up measuring unit through wireless mode; the online processing and compensation module can dynamically adjust filter parameters or compensation coefficients according to the control instructions, so as to realize online remote configuration and adaptive optimization of the measuring system.

6. A compact diesel engine connecting rod stress measurement system based on a strain gauge pressure sensor according to claim 5, characterized in that: The control instructions specifically include: Filter parameter adjustment instructions: used for dynamically setting the cut-off frequency and filter order of the adaptive filter algorithm; Compensation model selection instructions: used for selecting a parameter group suitable for the current working condition from a plurality of groups of pre-stored sensor characteristic model parameters; Data acquisition trigger instructions: used for controlling the multi-source signal synchronous acquisition module to perform high-speed acquisition in the 170-190 degree and 350-370 degree crank angle interval; Transmission mode switching instructions: used for configuring the wireless data transceiver module to switch between the high-power high-speed transmission mode and the low-power intermittent transmission mode.

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