Hook height measuring sensor and hook height measuring method

Abstract

The invention discloses a hook height measuring sensor and a hook height measuring method.The sensor comprises a single-chip microcomputer, the single-chip microcomputer is connected with a wireless module, a magnetic rotation air pressure altimeter and a current sampling mutual inductor, and the current sampling mutual inductor is connected with a top drive motor, the magnetic rotation air pressure altimeter, the wireless module and a wireless height controller; the wireless module is connected with the wireless height controller, and the magnetic rotation air pressure altimeter is arranged on a large hook. The measuring method specifically comprises the steps that the top drive motor starts to work, the large hook height measuring sensor automatically operates, the magnetic rotation air pressure altimeter collects the relative position change of the large hook and transmits collected data to the single-chip microcomputer, and the single-chip microcomputer obtains the height of the large hook through a Kalman filtering algorithm; hook height data is transmitted to the wireless height controller through the wireless module to be stored and displayed. The hook height measured by the device is high in precision and stability.

Description

Technical Field

[0001] This invention belongs to the field of drilling instrumentation technology, specifically relating to a sensor for measuring hook height, and also to a method for measuring hook height. Background Technology Currently, the height of the drilling hook at the drilling site is measured using a secondary measurement method with an absolute encoder. However, factors such as electromagnetic interference from the drilling rig, the tension and wear of the wire rope, wire rope replacement or rewinding, and the accuracy and complexity of calibration all affect the measurement accuracy.

[0002] The patent, titled "Oil Drilling Well Depth Measurement System and Method," with application number 2014105405521, includes a winch sensor, a pressure sensor, a weight sensor, a laser rangefinder, a field controller, and a monitoring and operation terminal. During initial system installation and commissioning, the laser rangefinder is fixed on the hook, which moves up and down under the control of the winch. The field controller records the displacement value of the laser rangefinder and the number of winch revolutions in real time, forming a correspondence between the number of revolutions and the displacement value. During normal drilling, the hook height value is automatically read from the number of winch revolutions.

[0003] The patent, titled "Drilling Hook Height Image Measurement System" and with application number 201310569601X, comprises an image acquisition module that acquires drilling hook height image information, a contour recognition module that performs contour recognition on the drilling hook height image information and compares the recognition result with the image contour information, an image correction module that corrects the drilling hook height image information based on the comparison result of the contour recognition module, a feature recognition module that identifies the hook in the corrected drilling hook height image information by comparing it with hook feature information, and a height calculation module that calculates the actual hook height value by comparing the relative position, angle, and distance of the identified hook with reference object information based on geometric principles.

[0004] The patent, titled "Oil Drill Rig Hook Height Measurement System and Calibration and Measurement Method," with application number 2012102615317, includes a winch fixed to the drilling platform, a winch sensor, a guide rope wheel and pulley block mounted on the top of the drilling rig, a hook, and a controller. The steel wire rope wound on the winch is connected to the hook via the guide rope wheel and pulley block. The winch sensor is electrically connected to the controller. A gear is coaxially mounted on the guide rope wheel, and a corresponding gear is mounted on the rotating shaft of the winch sensor. The rotating shaft of the winch sensor and the guide rope wheel are linked through gear meshing. The housing of the winch sensor is fixed to the guide rope wheel's mounting bracket. The system also includes a wireless transmitting module, a wireless receiving module, and a control center. The winch sensor is connected to the wireless transmitting module via the controller, and the wireless receiving module is connected to the control center.

[0005] The aforementioned measurement systems and methods are susceptible to changes such as wire rope replacement or reversal, and inaccurate calibration, resulting in poor accuracy and stability of hook height measurement at the drilling site. Summary of the Invention

[0006] The purpose of this invention is to provide a sensor for measuring the height of a large hook, thereby solving the problems of poor measurement accuracy and stability in existing measurement systems.

[0007] Another object of the present invention is to provide a method for measuring the height of a large hook.

[0008] The technical solution adopted in this invention is a hook height measurement sensor, including a microcontroller. The microcontroller is connected to a wireless module, a magnetic cyclone altimeter, and a current sampling transformer. The current sampling transformer is connected to a top drive motor, a magnetic cyclone altimeter, a wireless module, and a wireless height controller. The wireless module is connected to the wireless height controller. The magnetic cyclone altimeter is mounted on the hook. The invention is further characterized in that, The microcontroller is connected to a backup battery pack, which is connected to a current sampling transformer, a magnetic cyclone barometric altimeter, a wireless module, and a wireless altitude controller.

[0009] The microcontroller model is LLCC66.

[0010] The current sampling transformer is model OPCT160BD.

[0011] The model number of the magnetic cyclone barometric altimeter is HP206C.

[0012] Another technical solution adopted in this invention is a method for measuring the height of the hook. When the top drive motor starts working, the hook height sensor automatically runs. The current sampling transformer samples the working current of the top drive motor to provide power. The microcontroller stores the excess power provided by the current sampling transformer in the backup battery pack. The magnetic cyclone barometric altimeter collects the relative position change of the hook and transmits the collected data to the microcontroller. The microcontroller obtains the hook height through a Kalman filter algorithm and transmits the hook height data to the wireless height controller for storage and display through a wireless module.

[0013] Another feature of the technical solution of the present invention is that, The specific process by which the microcontroller obtains the height of the large hook using the Kalman filter algorithm is as follows: Step 1, according to the definition of the magnetic cyclone barometric altimeter, the parameters of the hook height sensor are as follows: (1) In equation (1), for k The height of the hook at all times, in units of... ; for k The vertical velocity of the hook height at any given moment, in units of... ; for k The absolute error of the magnetic cyclone barometric altimeter measurement at any given time, in units of ; The quantity being estimated; Ignoring the gain control of the magnetic cyclone barometric altimeter, the estimated quantity exist k The state of the hook height sensor at any given time can be represented by a linear stochastic differential equation: (2) In equation (2), for k The prior state estimate of the hook height sensor is measured at each moment; A is the state transition matrix for measuring the hook height sensor. for k The noise of the hook height sensor at any given time; Calculate the prior estimate of the covariance of the hook height sensor. The expression is: (3) In equation (3), Q is the covariance, which is a Gaussian white noise sequence; Let the covariance be at time k-1; Step 2, calculate the posterior estimate of the state of the hook height sensor, expressed as: (4) In equation (4), Kalman gain; To measure the height of the hook sensor k External observations at time t; H is the observation matrix; To measure the posterior estimate of the hook height sensor status; Step 3, update the posterior covariance of the sensor measuring the hook height. The expression is: (5).

[0014] The state transition matrix of the hook height sensor is: ; In the formula, It is a time interval. α These are the coefficients of a first-order Markov process that describes the change in absolute error.

[0015] The sensor for measuring the height of the hook is in k The external observable at time t is:

[0016] In the formula, To measure the readings of the magnetic cyclone barometric altimeter in the hook height sensor; For measuring noise.

[0017] The Kalman gain is:

[0018] In the formula, R is the covariance, which is a Gaussian white noise sequence.

[0019] The beneficial effects of this invention are (1) The power supply of the hook height sensor of the present invention is mainly obtained by sampling of the current transformer. As long as the top drive motor starts to work, the hook height sensor will run automatically. The microcontroller will store the excess power into the backup battery pack as needed, so as to power the entire hook height sensor when the top drive motor is not working. Therefore, the hook height sensor will not run out of power during the entire operation process, and the hook height sensor can run stably. (2) The height sensor for measuring the hook of the present invention has the characteristics of strong anti-interference ability, high speed, low power consumption and wireless transmission of output signal; (3) The hook height measurement method of the present invention adopts the Kalman filtering algorithm to improve the accuracy and fault tolerance of the data. Attached Figure Description

[0020] Figure 1 This is a schematic diagram of the principle of the hook height measuring sensor of the present invention; Figure 2 This is a flowchart of the hook height measurement method of the present invention.

[0021] In the diagram, 1. Microcontroller, 2. Wireless module, 3. Magnetic cyclone barometric altimeter, 4. Current sampling transformer, 5. Backup battery pack, 6. Wireless altitude controller, 7. Top drive motor. Detailed Implementation The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments.

[0022] Example 1 The present invention relates to a height sensor for measuring the hook height, comprising a microcontroller 1, which is connected to a wireless module 2, a magnetic cyclone barometric altimeter 3, and a current sampling transformer 4. The current sampling transformer 4 is connected to a top drive motor 7, the magnetic cyclone barometric altimeter 3, the wireless module 2, and a wireless height controller 6. The wireless module 2 is connected to the wireless height controller 6. The magnetic cyclone barometric altimeter 3 is mounted on the hook.

[0023] The current sampling transformer 4 is used to take the operating current of the top drive motor 7 and convert the sampled current into voltage to power the hook height sensor.

[0024] The magnetic cyclone barometric altimeter 3 is used to collect the relative position changes of the large hook.

[0025] Wireless module 2 is used for wireless communication between microcontroller 1 and wireless height controller 6.

[0026] The microcontroller 1 is used to acquire data collected by the magnetic cyclone barometric altimeter 3, and to obtain the hook height by using the Kalman filter algorithm. At the same time, the obtained hook height is transmitted to the wireless altitude controller 6 through the wireless module 2.

[0027] The wireless height controller 6 is used to store and display the acquired hook height so that users or the system can intuitively understand the current height of the hook.

[0028] Example 2 The present invention relates to a height sensor for measuring the hook, comprising a microcontroller 1, which is connected to a wireless module 2, a magnetic cyclone altimeter 3, a current sampling transformer 4, and a backup battery pack 5. The current sampling transformer 4 is connected to a top drive motor 7, the magnetic cyclone altimeter 3, the wireless module 2, and a wireless height controller 6. The wireless module 2 is connected to the wireless height controller 6. The magnetic cyclone altimeter 3 is mounted on the hook.

[0029] The backup battery pack 5 is connected to the current sampling transformer 4, the magnetic cyclone barometric altimeter 3, the wireless module 2, and the wireless altitude controller 6, respectively.

[0030] The current sampling transformer 4 is used to take the working current of the top drive motor 7 and convert the sampled current into voltage to power the large hook height sensor. Specifically, it powers the microcontroller 1, the top drive motor 7, the magnetic cyclone barometric altimeter 3, the wireless module 2, and the wireless height controller 6. Under the control of the microcontroller 1, the excess power is stored in the backup battery pack 5.

[0031] The current sampling transformer 4 adopts the OPCT160BD open-type current transformer, with a capacity of 1000~6000A / 5A and an accuracy of 0.5 class.

[0032] The magnetic cyclone barometric altimeter 3 is used to collect the relative position changes of the large hook.

[0033] The magnetic cyclone barometric altimeter 3 uses the HP206C high-precision chip to detect air pressure, altitude, and temperature. It can measure pressures ranging from 300 mbar to 1200 mbar, with an ultra-high precision of 0.01 mbar (0.05 m) in ultra-high resolution mode. The chip only accepts input voltages from 1.8V to 3.6V. With the addition of external circuitry, the magnetic cyclone barometric altimeter 3 is compatible with 3.3V and 5V, and can be directly connected to the microcontroller 1 via the I2C bus.

[0034] Wireless module 2 is used for wireless communication between microcontroller 1 and wireless height controller 6.

[0035] The microcontroller 1 is used to acquire data collected by the magnetic cyclone barometric altimeter 3, and to obtain the hook height by using the Kalman filter algorithm. At the same time, the obtained hook height is transmitted to the wireless height controller 6 through the wireless module 2. In addition, the microcontroller 1 can also store the excess power provided by the current sampling transformer 4 into the backup battery pack 5.

[0036] The microcontroller 1 adopts LoRa spread spectrum technology, which has strong anti-interference ability and improves the transmission distance and obstacle avoidance ability by more than 1 times compared with the traditional FSK. It adopts the LLCC66 imported chip, and the transmission speed can reach 62.5kb per second (the traditional one is only 37kb per second). When transmitting data with the same power, the current consumption is 1 / 4 of the traditional method.

[0037] The backup battery pack 5 is used to power the measuring hook height sensor when the top drive motor 7 is not working. Specifically, it includes the microcontroller 1, the top drive motor 7, the magnetic cyclone barometric altimeter 3, the wireless module 2, and the wireless height controller 6. Therefore, the measuring hook height sensor will not run out of power during the entire operation.

[0038] The wireless height controller 6 is used to store and display the acquired hook height so that users or the system can intuitively understand the current height of the hook.

[0039] Example 3 In this invention, the method for measuring the height of the large hook is as follows: When the top drive motor 7 starts working, the sensor for measuring the height of the large hook automatically operates. The current sampling transformer 4 samples the operating current of the top drive motor 7 to power the magnetic cyclone altimeter 3, the microcontroller 1, the wireless module 2, and the wireless height controller 6. The microcontroller 1 stores the excess power provided by the current sampling transformer 4 in the backup battery pack 5. When the top drive motor 7 is not working, the backup battery pack 5 powers the magnetic cyclone altimeter 3, the microcontroller 1, the wireless module 2, and the wireless height controller 6. The magnetic cyclone altimeter 3 collects the relative position change of the large hook and transmits the collected data to the microcontroller 1. The microcontroller 1 obtains the height of the large hook through a Kalman filter algorithm and transmits the height data to the wireless height controller 6 for storage and display through the wireless module 2.

[0040] Example 4 Based on Example 3, the Kalman filter algorithm is divided into two stages: a time update stage and a measurement update stage. In the time update stage, the states of the hook height sensor are predicted. In the measurement update stage, the prediction results from the time update stage are corrected, while retaining covariance information for subsequent prediction and correction. Furthermore, the hook height sensor parameters are initialized before the time update stage, specifically including... , , and These initial values ​​are usually determined based on system characteristics and prior knowledge. Therefore, the specific process by which microcontroller 1 obtains the hook height using the Kalman filter algorithm is as follows: Step 1, define the parameters of the hook height sensor according to the magnetic cyclone barometric altimeter 3 as follows: (1) In equation (1), The quantity being estimated; for k The height of the hook at all times, in units of... ; for k The vertical velocity of the hook height at any given moment, in units of... ; for k The absolute error of the magnetic cyclone barometric altimeter measurement at any given time, in units of Based on the Kalman filtering principle and the characteristics of the sensor for measuring the height of the hook, the absolute error can be described using a first-order Markov algorithm. in,

[0041]

[0042] ; The process of state parameter variation of the hook height sensor is described discretely, and the discrete control process of the hook height sensor is obtained. Ignoring the gain control of the magnetic cyclone barometric altimeter, the estimated quantity is... exist k The state of the hook height sensor at any given time can be represented by a linear stochastic differential equation: (2) In equation (2), for k The prior state estimate of the hook height sensor is measured at each moment; A is the state transition matrix for measuring the hook height sensor. for k The noise of the hook height sensor at a given time is assumed in the Kalman filter equation. The mean is 0; in,

[0043] In the formula, It is a time interval. α These are the coefficients of a first-order Markov process describing the change in absolute error; 0 < α <1 Calculate the prior estimate of the covariance of the hook height sensor. After completing the time update phase, proceed to the test update phase, and execute steps 2 and 3. Prior estimate The expression is: (3) In equation (3), Q is the covariance, which is a Gaussian white noise sequence; Let the covariance be at time k-1. According to Obtain the prior estimate of covariance at time 1 This allows us to obtain the posterior covariance at time 1. And so on, to obtain the covariance at time k-1. ; System status includes , , Three state variables, therefore the prior estimate It is a third-order matrix; Step 2, calculate the posterior estimate of the state of the hook height sensor, expressed as: (4) In equation (4), Kalman gain; To measure the height of the hook sensor k External observations at time t; H is the observation matrix; To measure the posterior estimate of the hook height sensor status; The posterior estimate of the state of the sensor used to measure the hook height is the final hook height. Step 3, update the posterior covariance of the sensor measuring the hook height. This is used for prediction in the next iteration; Posterior covariance The expression is: (5); Steps 1 through 3 constitute one working cycle of the Kalman filter.

[0044] Example 5 Based on Example 4, the hook height sensor measures the height of the hook. k external observables at time The expression is:

[0045] In the formula, To measure the readings of the magnetic cyclone barometric altimeter in the hook height sensor; To measure noise, in Kalman filtering, The expected value is 0; Example 6 Based on Example 5, Kalman gain The expression is:

[0046] In the formula, R is the covariance, which is a Gaussian white noise sequence; Kalman gain This determines the weights of system state prediction and measurement in the optimal estimation.

Claims

1. A sensor for measuring the height of a large hook, characterized in that, The device includes a microcontroller (1), which is connected to a wireless module (2), a magnetic cyclone altimeter (3), and a current sampling transformer (4). The current sampling transformer (4) is connected to a top drive motor (7), a magnetic cyclone altimeter (3), a wireless module (2), and a wireless height controller (6). The wireless module (2) is connected to the wireless height controller (6). The magnetic cyclone altimeter (3) is mounted on the large hook.

2. The hook height measuring sensor according to claim 1, characterized in that, The microcontroller (1) is connected to a backup battery pack (5), which is connected to a current sampling transformer (4), a magnetic cyclone barometer (3), a wireless module (2), and a wireless altitude controller (6).

3. The hook height measuring sensor according to claim 1, characterized in that, The microcontroller (1) is an LLCC66.

4. The hook height measuring sensor according to claim 1, characterized in that, The current sampling transformer (4) is model OPCT160BD.

5. The hook height measuring sensor according to claim 1, characterized in that, The model of the magnetic cyclone barometric altimeter (3) is HP206C.

6. A method for measuring the height of a large hook, characterized in that, When the top drive motor (7) starts working, the hook height sensor starts running automatically. The current sampling transformer (4) samples the working current of the top drive motor (7) to supply power. The microcontroller (1) stores the excess power provided by the current sampling transformer (4) into the backup battery pack (5). The magnetic cyclone barometric altimeter (3) collects the relative position change of the hook and transmits the collected data to the microcontroller (1). The microcontroller (1) obtains the hook height through the Kalman filter algorithm and transmits the hook height data to the wireless height controller (6) through the wireless module (2) for storage and display.

7. The method for measuring the height of the large hook according to claim 6, characterized in that, The specific process by which the microcontroller (1) obtains the height of the large hook through the Kalman filter algorithm is as follows: Step 1, according to the definition of the magnetic cyclone barometric altimeter (3), the parameters of the large hook height sensor are as follows: （1） In equation (1), for k The height of the hook at all times, in units of... ; for k The vertical velocity of the hook height at any given moment, in units of... ; for k The absolute error of the magnetic cyclone barometric altimeter measurement at any given time, in units of ; The quantity being estimated; Ignoring the gain control of the magnetic cyclone barometric altimeter, the estimated quantity exist k The state of the hook height sensor at any given time can be represented by a linear stochastic differential equation: （2） In equation (2), for k The prior state estimate of the hook height sensor is measured at each moment; A is the state transition matrix for measuring the hook height sensor. for k The noise of the hook height sensor at any given time; Calculate the prior estimate of the covariance of the hook height sensor. The expression is: （3） In equation (3), Q is the covariance, which is a Gaussian white noise sequence; Let the covariance be at time k-1; Step 2, calculate the posterior estimate of the state of the hook height sensor, expressed as: （4） In equation (4), Kalman gain; To measure the height of the hook sensor k External observations at time t; H is the observation matrix; To measure the posterior estimate of the hook height sensor status; Step 3, update the posterior covariance of the sensor measuring the hook height. The expression is: （5）。 8. The method for measuring the height of the large hook according to claim 7, characterized in that, The state transition matrix of the hook height sensor is: ； In the formula, It is a time interval. α These are the coefficients of a first-order Markov process that describes the change in absolute error.

9. The method for measuring the height of the large hook according to claim 7, characterized in that, The sensor for measuring the height of the hook is in k The external observable at time t is: In the formula, To measure the readings of the magnetic cyclone barometric altimeter in the hook height sensor; For measuring noise.

10. The method for measuring the height of the large hook according to claim 7, characterized in that, The Kalman gain is: In the formula, R is the covariance, which is a Gaussian white noise sequence.

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