Intelligent wrench and tightening control method based on torque angle method

Abstract

The present invention discloses a smart wrench and tightening control method based on the torque angle method, including a microcontroller, a torque measurement module electrically connected to the microcontroller, an angle measurement module, a memory and a working power supply; the torque measurement module is used to measure the torque of the smart wrench, the angle measurement module adopts an inertial sensor, and is used to measure the deflection angle of the smart wrench. The inertial sensor includes a gyroscope, an accelerometer and a magnetometer, and the microcontroller adopts the torque angle method to control the tightening of the smart wrench. The present invention does not use the conventional method of solving the angle attitude of the quaternion of the inertial device, but only reduces the tedious calculation and performs attitude solution by establishing a wrench coordinate system based on the torque wrench, and has the characteristics of high calculation efficiency, high precision, low cost, low power consumption and long battery life.

Description

Technical Field

[0001] The present invention relates to an intelligent wrench, and in particular to an intelligent wrench and a tightening control method based on a torque angle method. Background Art

[0002] A torque wrench is a tightening tool that acts on the bolt head. It tightens bolts of different types by applying different torques to ensure the reliability of mechanical equipment connections. In the fields of ships, railways, aviation, etc., the number of applications of threaded fasteners is increasing, and their role is becoming more and more important. Due to the commonness and potential severity of threaded fastener failures, it is particularly important to ensure the reliability of bolted connections. The reliability of bolted connections is related to the preload, and the size of the preload is determined by the tightening method. The torque method is more common in bolt tightening methods. The torque method obtains a mathematical model based on the relationship between tightening torque and preload, and then obtains the tightening torque range under different preloads. However, a large preload will cause the bolt to enter the plastic deformation zone, and the torque and preload are not linearly related at this time. Therefore, in some fields with a large demand for preload, the torque method is not applicable. At this time, the torque angle method is used. This method can more effectively reduce the dispersion of the bolt preload, so as to improve the reliability of the bolt connection, reduce torque deviation, and meet higher bolt preload requirements. The torque angle method is essentially a step-by-step tightening strategy. First, the bolt is tightened to an initial torque, and then tightened to a certain angle based on this initial torque. In order to implement the torque angle method, the functions of measuring torque and angle are required.

[0003] There are various methods for measuring torque, which can be divided into three categories according to the measurement principle: balanced force method, energy conversion method, and transfer method. Among them, the transfer method is widely used in various torque measurement scenarios. When transmitting torque, the physical parameters of the elastic shaft will change. The change of physical parameters reflects the change of torque. The transfer method measures torque by measuring the change of these physical parameters. These changing physical parameters can be divided into three categories according to the way the signal is generated: deformation type, stress type and strain type. The deformation type mainly includes capacitive, optical, magnetoelectric, photoelectric, and mechanical types; the stress type is mainly divided into photoelastic and magnetoelastic; the strain type torque measurement method mainly refers to the resistance strain gauge measurement method. The strain effect of resistance refers to the corresponding change in the resistance value of the conductor or semiconductor material when it is mechanically deformed under the action of external force. The resistance strain measurement method measures torque based on the strain effect of resistance. The strain gauge is pasted on the rotating shaft. When there is torque acting on the rotating shaft, the strain gauge can detect the torque size according to the change in resistance value.

[0004] The solution for measuring angles mainly uses inertial sensors, which are mainly divided into gyroscopes and accelerometers. However, the existing inertial sensor angle measurement solutions mostly rely on a single sensor. It is difficult to obtain accurate angle measurement results by relying solely on the measurement data of a single sensor, so it is necessary to use algorithms to fuse the data of multiple sensors, and the selection of chips is mainly based on the integration of multiple inertial sensors. An existing digital display angle torque wrench adopts the torque angle method and uses the DMP integrated in the control chip to solve the angle attitude. The DMP attitude solution directly outputs the quaternion based on the data collected by the gyroscope, without filtering and correction, and the accuracy is not high. The quaternion angle attitude algorithm that adds the data of the accelerometer for complementary filtering correction solves the absolute coordinates in the northeast sky coordinate system. The solution process is cumbersome, resulting in low solution efficiency. When the wrench posture changes rapidly, it cannot be solved in time, and data lag will occur, which will affect the rotation angle accuracy during the use of the wrench. At the same time, due to the ever-changing posture of the wrench during use, there are special working states that cannot be described using the northeast sky coordinate system. Therefore, this method has a "dead zone" where the posture cannot be described. Secondly, the angle measurement error of the torque structure of the electronic wrench currently available is about ±3% when rotating in the horizontal direction, and the angle measurement error of the torque tool with the best accuracy is as high as ±6.2% when rotating in the vertical direction. The actual use of the wrench is not limited to horizontal tightening, and there are many occasions where bolts need to be tightened at multiple angles. It can be seen that the existing torque tools with angle measurement function cannot meet the needs of actual applications. Summary of the invention

[0005] Purpose of the invention: In view of the above problems, the present invention proposes an intelligent wrench and tightening control method based on the torque angle method, which is used in scenarios with high requirements for bolt preload. It can improve the solution efficiency of angle measurement, and the measurement of rotation angle during wrench operation can achieve higher accuracy standards.

[0006] Technical solution: The technical solution adopted by the present invention is a smart wrench based on the torque angle method, including: a microcontroller, a torque measurement module electrically connected to the microcontroller, an angle measurement module, a memory and a working power supply; the torque measurement module is used to measure the torque of the smart wrench, and the angle measurement module adopts an inertial sensor to measure the deflection angle of the smart wrench. The inertial sensor includes a gyroscope, an accelerometer and a magnetometer. It also includes a communication module for transmitting data to the PC, as well as a display screen and buttons, and an audio and video alarm module for interaction. The microcontroller adopts the torque angle method to control the tightening of the smart wrench. The measurement of the deflection angle of the smart wrench in the torque angle method includes the following steps:

[0007] (1) Using the wrench coordinate system, the gyroscope, accelerometer and magnetometer collect attitude data respectively, among which the heading angular acceleration collected by the gyroscope is integrated to obtain the heading angle α';

[0008] (2) After Kalman filtering the attitude data collected by the accelerometer and gyroscope, the pitch angle and roll angle are calculated;

[0009] (3) calculating the heading angle α by combining the pitch angle and the roll angle with the attitude data collected by the magnetometer;

[0010] (4) Complementary filtering is performed on the heading angle α obtained by analyzing the magnetometer data and the heading angle α' output by the gyroscope to obtain a corrected heading angle α1, which is the deflection angle of the smart wrench.

[0011] A smart wrench tightening control method is also proposed. The method uses a torque angle method to control the tightening of the wrench. The measurement of the deflection angle of the smart wrench in the torque angle method includes the following steps:

[0012] (1) Using the wrench coordinate system, the gyroscope, accelerometer and magnetometer collect attitude data respectively, among which the heading angular acceleration collected by the gyroscope is integrated to obtain the heading angle α';

[0013] (2) After Kalman filtering the attitude data collected by the accelerometer and gyroscope, the pitch angle and roll angle are calculated;

[0014] (3) calculating the heading angle α by combining the pitch angle and the roll angle with the attitude data collected by the magnetometer;

[0015] (4) Complementary filtering is performed on the heading angle α obtained by analyzing the magnetometer data and the heading angle α' output by the gyroscope to obtain a corrected heading angle α1, which is the deflection angle of the smart wrench.

[0016] Among them, the differential formula of the complementary filtering is:

[0017] α1=Aα+(1-A)[α0+α']

[0018] Wherein, α1 is the heading angle after fusion at the current moment, A is the complementary filter coefficient, A=KT / (1+KT), K is the weight factor in the filter transfer function expression, T is the time constant, α is the heading angle obtained by analyzing the magnetometer data, α0 is the heading angle after complementary filtering at the previous moment, and α' is the heading angle output by the gyroscope.

[0019] When the magnetometer is not in a horizontal position, the magnetic induction intensity data measured by the magnetometer needs to be compensated:

[0020]

[0021] Where: M x 、M y 、M z They are the three axis data output by the magnetometer, H′ x and H′ y They are the corrected magnetic induction intensity data of the X-axis and Y-axis respectively.

[0022] Beneficial effect: Compared with the prior art, the present invention has the following advantages: the present invention does not use the conventional method of solving the quaternion angle attitude of the inertial device, but only reduces the cumbersome calculation and performs attitude solution by establishing a wrench coordinate system based on the torque wrench. Since the wrench coordinate system is a relative position coordinate system, it responds faster and more accurately to changes, and can significantly improve the efficiency and accuracy of angle attitude solution. The measurement scheme designed by the present invention has been experimentally verified to have the ability to measure angles. Whether it is static or dynamic, the measurement scheme significantly improves the measurement accuracy and suppresses the random walk and zero drift of the gyroscope. Secondly, most of the similar products on the market are expensive and have high production costs. The present invention is developed based on STM32, has basic digital display functions, button control, sound and light warning, and data storage and transmission functions, and has the characteristics of low cost, low power consumption, and long battery life. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 This is the overall structural diagram of the smart wrench;

[0024] Figure 2 Schematic diagrams of two coordinate systems of the smart wrench of the present invention;

[0025] Figure 3 is a flow chart of the tightening control method of the present invention;

[0026] Figure 4 It is a schematic diagram of the basic principle of complementary filtering described in the present invention;

[0027] Figure 5 It is the heading angle change data of the smart wrench of the present invention when it is stationary and placed horizontally;

[0028] Figure 6 The heading angle change data of the smart wrench of the present invention when it is stationary and tilted;

[0029] Figure 7 It is the heading angle change data of the smart wrench of the present invention when it moves horizontally in dynamic state;

[0030] Figure 8 It is the heading angle change data of the smart wrench described in the present invention when it moves freely in dynamic state. DETAILED DESCRIPTION

[0031] The technical solution of the present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0032] The intelligent wrench based on the torque angle method of the present invention has a structural block diagram as shown in FIG. Figure 1 As shown, it includes a microcontroller MCU, a memory electrically connected to the MCU, and various modules electrically connected to the MCU: a torque measurement module, an angle measurement module, and a working power supply. It also includes a display screen and buttons for interaction, and an audio and visual alarm module. In this embodiment, a communication module is used to realize the data transmission function.

[0033] In the selection of the controller, DSP and FPGA are expensive and large in size, which do not meet the design requirements of low cost and convenience. The STM32L433RBT6 contains a variety of industrial applications such as PWM, ADC and a variety of communication interfaces such as SPI, I2C, CAN, Ethernet, and its ultra-low power consumption meets the needs of stable battery life. Therefore, it is selected as the microcontroller unit (MCU) in this design.

[0034] The power supply circuit provides a reliable working power supply for the system, ensuring the normal and stable operation of the smart wrench, and is an important part of the smart wrench. Considering the portability of the torque wrench, the system uses a rechargeable lithium battery for power supply. Compared with traditional zinc-manganese dry batteries, rechargeable lithium batteries can avoid frequent battery replacement, and have the advantages of low self-discharge rate, long cycle life, high energy density, and more environmentally friendly. The specific model of the power management chip is LD39015M33R. Its ultra-low voltage drop, low quiescent current and low noise characteristics make it suitable for low-power battery-powered applications. This ceramic capacitor can ensure that the battery can still work normally when the power is low. And the shutdown mode can be turned on by enabling logic control. Through this feature, a controllable power supply design is adopted for the power supply of other functional modules. When these modules are needed to work, the MCU controls the power supply of these modules to turn on, and the module power supply starts to work. When these modules are not needed to work, the MCU controls the power supply of these modules to turn off, and the system enters a low power consumption state.

[0035] The torque measurement module uses a resistive strain gauge. The resistive strain gauge can measure the deformation of the object through resistance changes, thereby obtaining the size of the torque. It has a simple structure, can adapt to harsh environments, is low-cost, and has high reliability. Other transfer measurement methods are not suitable for the present invention in their own ways: the magnetoelectric measurement method has a large sensor size and weight, the capacitive measurement method is not applicable when the shaft size is too large, the optical fiber measurement method is difficult to debug, and the magnetic sensitive measurement method has low measurement accuracy. Some new measurement technologies, such as wireless surface acoustic wave measurement technology, are not yet mature, and the laser Doppler measurement method is relatively expensive. Considering that the development of strain gauges has been very mature, most of the common digital torque wrenches on the market also use resistive strain gauge measurement methods to measure torque. Therefore, in the torque measurement part of the present invention, resistive strain gauges are used to measure torque. Strain gauges are generally connected in the form of a bridge. What is collected in the bridge circuit is a voltage signal, which is an analog signal, and the signal needs to be converted to A / D. The present invention selects a low-power, small-signal, 24-bit AD conversion chip ADS1220 as a processing chip for the torque module, and the voltage difference of the bridge formed by the strain gauge is input to the ADS1220, and then the digital quantity is sent to the MCU for data processing through the SPI communication interface to complete the torque measurement.

[0036] As for the selection of angle measurement modules, there are many products on the market that can meet the requirements of angle measurement. Six-axis products mainly include: ICM-20600, ICM-20649, ICM-20689, MPU-6000, etc. Nine-axis products mainly include: ICM-20948, MPU-9250, etc. Many torque wrenches on the market that can measure angles rely on the DMP of MPU6050 (six-axis series) for attitude calculation. This design requires the use of a magnetometer, and the accuracy is improved by adding a magnetometer to assist in the measurement. Therefore, the nine-axis series MPU9250 is selected. MPU9250 has a 3-axis MEMS gyroscope, a 3-axis MEMS accelerometer, and a 3-axis magnetometer.

[0037] The smart wrench has the following functions: (1) Angle and torque measurement. Angle measurement is performed after torque measurement, and the angle measurement range is 0 to ±720°. The measurement error should be kept within ±1.5%. (2) Key control and data display. A total of four keys are set, namely the up and down keys, the A key and the B key. The up and down keys are used for menu selection and value addition and subtraction, the A key indicates confirmation, and the B key is used for return. Long press can switch between the working state and the low power state. The OLED display screen is used to realize data display. (3) Sound and light warning. When using the wrench, an early warning prompt is given for the torque value or angle value that is about to reach the set value. This is completed by a combination of a buzzer and an LED indicator. (4) Data storage and data transmission. The measured and processed data is stored. The design uses a read-only memory (EEPROM), and the wrench communicates with the PC through WIFI to upload data. (5) The power supply can be charged continuously. The system has a power management function, no switch is set, and is operated by a low-power MCU control system. At the same time, the system is powered by rechargeable lithium batteries to meet low power consumption requirements, reduce the frequency of battery replacement, and is environmentally friendly.

[0038] The tightening control method of the present invention has a flow chart as shown in Figure 3 As shown, the following process is included:

[0039] (1) Using the wrench coordinate system, the gyroscope, accelerometer and magnetometer collect attitude data respectively, and the gyroscope outputs the heading angle α'.

[0040] The data collected by the gyroscope, accelerometer and magnetometer do not use the northeast sky coordinate system, but the torque tool coordinate system (i.e. the wrench coordinate system). The new coordinate system is established in the attached Figure 2 Since the posture of the wrench changes constantly during use, it is impossible to describe the working state in the northeastern sky coordinate system. Therefore, this design does not use the quaternion method to solve the angle posture. It only reduces the tedious calculation and posture solution by establishing a wrench coordinate system based on the torque wrench. Figure 2 As shown, the xyz coordinate system is the internal coordinate system of the angle detection sensor, with the origin at the center of the chip; the XYZ coordinate system is the torque wrench coordinate system, with the origin at the center of the rotation axis. The X-axis of the XYZ coordinate system is parallel to the x-axis in the xyz coordinate system, and is set to pass through the center of the rotation axis and the central axis of the rigid structure. The Y-axis of the XYZ coordinate system is parallel to the y-axis in the xyz coordinate system, and the direction is set to be perpendicular to the central axis on the horizontal plane of the rotation axis. The Z-axis of the XYZ coordinate system is parallel to the z-axis in the xyz coordinate system, and the direction of all angles is defined with the counterclockwise direction facing the origin as negative and the clockwise direction as positive.

[0041] It can be seen that the coordinate system of the MPU is parallel to the three axes of the torque tool coordinate system. In this way, the angle of rotation around the X-axis is consistent with the angle of rotation around the x-axis, the angle of rotation around the Y-axis is consistent with the angle of rotation around the y-axis, and the angle of rotation around the Z-axis is consistent with the angle of rotation around the z-axis. Then, the angle of rotation around the XYZ axis can be obtained by measuring the angle of rotation around the xyz axis. In this coordinate system, the angle of rotation of the torque wrench is simplified to the angle of rotation around the Z axis, that is, the angle of rotation of the sensor around the z-axis, the heading angle α. This definition of coordinate axes solves the influence of the working posture of the torque wrench on the rotation angle, and also realizes the decoupling of the xyz three axes, avoiding a large number of calculation tasks such as calculating quaternions, Euler angles, direction cosines, etc., but when designing circuits and installing circuit boards, it is necessary to ensure the parallelism of the three pairs of axes of the two coordinate systems.

[0042] In actual use of the wrench, due to the inherent characteristics of the gyroscope, as the measurement time increases, it will cause integration errors and data drift. To improve the accuracy of angle measurement and long-term use, it is not enough to rely solely on the measurement data of a single sensor. It is necessary to fuse the data of multiple sensors through algorithms. This design uses magnetometer data and gyroscope data fusion to increase measurement accuracy.

[0043] This design proposes a joint algorithm of Kalman filtering and complementary filtering. First, the data measured by the accelerometer and the gyroscope are subjected to Kalman filtering, and then substituted into equations (11) and (12) to obtain the heading angle α calculated by the magnetometer. The heading angle α and the heading angle α′ output by the gyroscope are then complementary filtered to finally obtain a more accurate heading angle.

[0044] (2) The data measured by the accelerometer and gyroscope are subjected to Kalman filtering to calculate more accurate pitch angle ρ and roll angle φ data.

[0045] Kalman filtering is a data processing method that performs well in linear systems for optimal estimation. This design uses the Kalman filtering algorithm to fuse the accelerometer and gyroscope data, remove the interference caused by random noise, and obtain accurate pitch angle ρ and roll angle φ. First, the measurement process is approximated as a linear system, and the state equation and measurement equation are established as follows:

[0046] Equation of state:

[0047] x k =Ax k -1+BU k +w k (1)

[0048] Measurement equation:

[0049] y k =Hx k +vk (2)

[0050] Where: x k is the state vector; U k The input control vector of the system; w k is the system process white noise; yk is the observation vector; v k To measure system noise.

[0051] Assuming that the noise obeys the normal distribution, the five core formulas are as follows.

[0052] Estimation of state quantity:

[0053]

[0054] Current status estimate:

[0055]

[0056] Error covariance estimation:

[0057] P k|k-1 =APk-1A T +Q (5)

[0058] Kalman gain:

[0059] K k =P k|k-1 H T (HP k|k-1 H T +R) -1 (6)

[0060] Error covariance:

[0061] P k =(IK k H)P k|k-1 (7)

[0062] in: is the true value of the current state K k estimates; K is the estimated value of k times based on k-1 times; k For observation bias The modified weight of P k is the covariance matrix of the current state estimate; P k|k-1 The error covariance matrix before estimation; Q is the covariance of the system process white noise, and R is the covariance of the measurement system noise.

[0063] In order to further suppress the drift of the gyroscope, it is necessary to process the angular velocity offset of the gyroscope. Equation (3) can be described as follows:

[0064]

[0065] Where: T s is the sampling period; ω k represents the angular velocity of the gyroscope at time k.

[0066] The gyroscope measures the angular velocity of rotation, which needs to be integrated to get the corresponding angle value, as shown in formula (9):

[0067] θ k =(ω k -ω bias_k )dt+θ k-1 (9)

[0068] Where: θ k With θ k-1 is the angle value at adjacent moments; ω k is the angular velocity of rotation; ω bias_k is the offset of the angular velocity of rotation.

[0069] The accelerometer can obtain the acceleration components of three axes, which need to be solved for angle using equation (10).

[0070]

[0071] Among them: A x , A y , A z are the acceleration components of the three axes respectively; ρ is the pitch angle; φ is the roll angle.

[0072] (3) The calculated attitude angles ρ and φ are combined with the magnetometer data to calculate the heading angle α.

[0073] The magnetometer mainly measures the three-axis magnetic induction intensity. In a horizontal position, the heading angle can be obtained by formula (11).

[0074]

[0075] Among them, H x and H y are the magnetic induction intensity data of the X-axis and Y-axis measured by the magnetometer. When the magnetometer is not in a horizontal position, equation (11) is required for compensation:

[0076]

[0077] Where: M x 、M y 、M z They are the 3-axis data output by the magnetometer.

[0078] When the wrench is used for a long time, the heading angle output by the gyroscope is not accurate enough and has low reference value, while the heading angle value calculated by the magnetometer is relatively accurate. The complementary filtering algorithm can use the magnetometer to correct the gyroscope, improve the accuracy of the information, and effectively suppress the drift of the gyroscope.

[0079] (4) Complementary filtering is performed on the heading angle α and the heading angle α' output by the gyroscope to finally obtain a more accurate heading angle, which is the deflection angle obtained.

[0080] The basic principle of complementary filtering is as follows Figure 4 As shown in the figure, θ is the actual rotation angle; ω is the angular velocity measured by the gyroscope; θ1 is the angle value obtained by the magnetometer, is the angle value estimated after complementary filtering algorithm; n1 is the high-frequency noise introduced in magnetometer measurement; n2 is the low-frequency noise introduced in gyroscope measurement. The high-frequency noise n1 in the magnetometer is eliminated by low-pass filter G1(s), and the low-frequency noise n2 in the gyroscope is eliminated by high-pass filter G2(s). The transfer functions of the two filters are designed as shown in equations (13) and (14).

[0081]

[0082]

[0083] The selected filter transfer function must satisfy G1(s)+G2(s)=1. By selecting a suitable weight factor K value, the high-pass and low-pass filters in the system can have a suitable cutoff rate. The following equation is established:

[0084]

[0085] Then the estimated value of the attitude angle θ after processing is:

[0086]

[0087] The corresponding difference formula of formula (16) is:

[0088]

[0089] Where A = KT / (1+KT); T is the time constant; θ1(k) is the angle value calculated by the gyroscope at time k; θ2(k) is the angle data after the magnetometer resolves.

[0090] The difference formula can be written as:

[0091] α1=Aa+(1-A)[α0+α'] (18)

[0092] Among them: α0 is the heading angle after filtering at the previous moment; α1 is the heading angle after fusion at the current moment; α' is the heading angle solved by the gyroscope; α is the heading angle analyzed based on the magnetometer data, and α1 is the final solved wrench angle.

[0093] Solution effectiveness test:

[0094] Figure 5 and Figure 6 These are the heading angle change data when the wrench is placed horizontally and tilted when it is stationary. It can be seen that the magnetometer has a certain zero bias phenomenon, and the overall fluctuation is around the zero bias value, with a deviation within the range of ±0.5; the gyroscope has an obvious drift phenomenon, and the cumulative error obtained by the integrated angle gradually increases over time; the heading angle curve after joint filtering is smooth and stable, with a deviation within the range of ±0.1, indicating that the angle measurement algorithm of this scheme suppresses the drift of the gyroscope and improves the angle accuracy of the measurement.

[0095] Figure 7 and Figure 8 It is the heading angle change data of the wrench in horizontal movement and free movement. It can be seen that in the motion state, the gyroscope and magnetometer can track the angle change in time. Comparing the two curves, it can be seen that in the motion state, the gyroscope has a better dynamic response, while the magnetometer has obvious noise and a certain lag. Figure 7 Under free motion, the magnetometer still fluctuates greatly after algorithm compensation, but the curve after complementary filtering is smooth and stable, which suppresses the noise of the magnetometer, reduces the angle error, and significantly improves the accuracy.

[0096] Comparative test experiment:

[0097] The present invention conducts a precision comparison test with two common angle wrenches on the market, which are marked as A and B. A uses the DMP carried by the gyroscope chip for attitude calculation, while B uses the MPU6050 with integrated Kalman filter algorithm. The comparison test is completed using a torque test stand.

[0098] The torque wrench is fixed on a turntable. The rotational angular velocity provided by the turntable is the rotational angular velocity of the torque wrench, so that different wrenches can rotate at the same angular velocity. The experiment was carried out at a rotation speed of 30dps, and four test points of 45°, 90°, 135° and 180° were taken. The test data is shown in the following table. Table 1 is the measured difference between the rotation angle under horizontal placement and the measured angle of the wrench, and Table 2 is the measured difference between the rotation angle under tilted placement and the measured angle of the wrench.

[0099] Table 1 Measurement difference under horizontal placement

[0100] A B MY 45° 0.36 0.41 0.36 90° 2.41 1.42 0.32 135° 2.36 0.39 0.39 180° 2.38 1.42 0.38

[0101] Table 2 Measurement difference under tilted placement

[0102] A B MY 45° 1.39 0.37 0.34 90° 1.38 0.39 0.39 135° 1.36 1.36 0.36 180° 3.34 1.39 -0.64

[0103] In the table, A and B are two common angle wrenches on the market. A uses the DMP carried by the gyroscope chip for attitude calculation, and B uses the MPU6050 with an integrated Kalman filter algorithm. MY is the wrench designed by the present invention. As can be seen from the above table, whether it is placed horizontally or tilted, the difference measured at the four test points of the smart wrench designed in this article is smaller. The error calculated by the error formula is within ±1%, which meets the original intention of the design accuracy, proving that it has the best performance in angle measurement function and has certain competitiveness compared to similar products.

Claims

1. An intelligent wrench based on torque angle method, characterized in that: The invention comprises a microcontroller, a torque measurement module electrically connected to the microcontroller, an angle measurement module, a memory and a working power supply; the torque measurement module is used to measure the torque of the smart wrench, the angle measurement module adopts an inertial sensor, and is used to measure the deflection angle of the smart wrench. The inertial sensor comprises a gyroscope, an accelerometer and a magnetometer. The microcontroller adopts a torque angle method to control the tightening of the smart wrench. The measurement of the deflection angle of the smart wrench in the torque angle method comprises the following steps: (1) Using the wrench coordinate system, the gyroscope, accelerometer and magnetometer collect attitude data respectively, among which the heading angular acceleration collected by the gyroscope is integrated to obtain the heading angle α'; (2) After Kalman filtering the attitude data collected by the accelerometer and gyroscope, the pitch angle and roll angle are calculated; (3) The pitch angle and the roll angle are combined with the attitude data collected by the magnetometer to calculate the heading angle α, which is calculated as follows: In the formula, H x and H y They are the magnetic induction intensity data of the X-axis and Y-axis measured by the magnetometer; When the magnetometer is not in a horizontal position, the magnetic induction intensity data measured by the magnetometer is compensated: Where: M x 、M y 、M z They are the three axis data output by the magnetometer, H′ x and H′ y are the corrected magnetic induction intensity data of the X-axis and Y-axis respectively; ρ is the pitch angle; Φ is the roll angle; (4) Complementary filtering is performed on the heading angle α obtained by analyzing the magnetometer data and the heading angle α' output by the gyroscope to obtain a corrected heading angle α1, which is the deflection angle of the smart wrench; The differential formula of the complementary filtering is: α1=Aα+(1-A)[α0+α'] Wherein, α1 is the corrected heading angle, A is the complementary filter coefficient, A=KT / (1+KT), K is the weight factor in the filter transfer function expression, T is the time constant, α0 is the heading angle after complementary filtering at the previous moment, and α' is the heading angle output by the gyroscope.

2. The intelligent wrench based on the torque angle method according to claim 1 is characterized in that: It also includes a communication module for transmitting data to a PC.

3. The intelligent wrench based on the torque angle method according to claim 1 is characterized in that: It also includes a display screen and buttons for interaction, and an audible and visual alarm module.

4. A smart wrench tightening control method, characterized in that: The method adopts a torque angle method to control the tightening of the wrench. The measurement of the deflection angle of the smart wrench in the torque angle method includes the following steps: (1) Using the wrench coordinate system, the gyroscope, accelerometer and magnetometer collect attitude data respectively, among which the heading angular acceleration collected by the gyroscope is integrated to obtain the heading angle α'; (2) After Kalman filtering the attitude data collected by the accelerometer and gyroscope, the pitch angle and roll angle are calculated; (3) The pitch angle and the roll angle are combined with the attitude data collected by the magnetometer to calculate the heading angle α, which is calculated as follows: In the formula, H x and H y They are the magnetic induction intensity data of the X-axis and Y-axis measured by the magnetometer; When the magnetometer is not in a horizontal position, the magnetic induction intensity data measured by the magnetometer is compensated: Where: M x 、M y 、M z They are the three axis data output by the magnetometer, H′ x and H′ y are the corrected magnetic induction intensity data of the X-axis and Y-axis respectively; ρ is the pitch angle; φ is the roll angle; (4) Complementary filtering is performed on the heading angle α obtained by analyzing the magnetometer data and the heading angle α' output by the gyroscope to obtain a corrected heading angle α1, which is the deflection angle of the smart wrench; The differential formula of the complementary filtering is: α1=Aα+(1-A)[α0+α'] Wherein, α1 is the corrected heading angle, A is the complementary filter coefficient, A=KT / (1+KT), K is the weight factor in the filter transfer function expression, T is the time constant, α0 is the heading angle after complementary filtering at the previous moment, and α' is the heading angle output by the gyroscope.

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