Turntable-free calibration method for triaxial MEMS (Micro Electro Mechanical System) accelerometer while drilling

Abstract

The invention discloses a while-drilling triaxial MEMS accelerometer turntable-free calibration method. The method comprises the following steps: establishing an error model of a triaxial MEMS accelerometer according to inter-axis crosstalk influence; designing a turntable-free arrangement scheme of the triaxial MEMS accelerometer; collecting measurement data according to the turntable-free arrangement scheme; constructing a calibration model of the triaxial MEMS accelerometer according to the turntable-free arrangement scheme; solving the calibration model through an improved particle swarm optimization algorithm to obtain error parameters; and completing static calibration of the triaxial MEMS accelerometer according to the error parameters. According to the method, the error model of the triaxial MEMS accelerometer is established through the inter-axis crosstalk influence such as the triaxial scale factor, the triaxial zero offset, the installation error angle and the inter-axis crosstalk factor, the modeling accuracy of the error model is improved, the error parameters are identified based on the calibration model of the turntable-free arrangement scheme and by using the improved particle swarm algorithm, and the error model is more accurate. And a new method for calibrating the triaxial MEMS accelerometer while drilling without the rotary table is formed.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of accelerometer, in particular to a no-turntable calibration method for a triaxial MEMS accelerometer while drilling. BACKGROUND

[0002] The MEMS accelerometer has the characteristics of small volume, low power consumption, cost-effectiveness and convenient use, and can be used for drilling tool posture measurement system and for collecting gravity information. However, the MEMS accelerometer is easily affected by errors and noises, and needs to be statically calibrated before measurement. According to the different places or times of calibration, the static calibration of the MEMS accelerometer can be divided into factory calibration, laboratory calibration and field calibration. Since the MEMS accelerometer will increase errors after being used for a period of time, it is necessary to periodically calibrate it in the field.

[0003] In the field of oil and gas field drilling, the existing static calibration of the MEMS accelerometer while drilling does not consider the influence of inter-axis crosstalk, and relies on precise equipment such as a turntable for multi-position excitation, which has the problems of limited calibration accuracy and low calibration efficiency. SUMMARY

[0004] The present application provides a no-turntable calibration method for a triaxial MEMS accelerometer while drilling, to solve the problem that the existing static calibration of the MEMS accelerometer while drilling does not consider the influence of inter-axis crosstalk, and relies on precise equipment such as a turntable for multi-position excitation, which has the problems of limited calibration accuracy and low calibration efficiency.

[0005] In one aspect, the present application provides a no-turntable calibration method for a triaxial MEMS accelerometer while drilling, comprising:

[0006] establishing an error model of the triaxial MEMS accelerometer according to the influence of inter-axis crosstalk;

[0007] designing a no-turntable arrangement scheme of the triaxial MEMS accelerometer;

[0008] collecting measurement data according to the no-turntable arrangement scheme;

[0009] constructing a calibration model of the triaxial MEMS accelerometer according to the no-turntable arrangement scheme;

[0010] solving the calibration model to obtain error parameters by an improved particle swarm optimization algorithm;

[0011] completing the static calibration of the triaxial MEMS accelerometer according to the error parameters.

[0012] In one possible implementation, the establishing an error model of the triaxial MEMS accelerometer according to the influence of inter-axis crosstalk comprises:

[0013] The error model is established according to three-axis scale factors, three-axis zero offsets, mounting error angles and inter-axis crosstalk factors of the three-axis MEMS accelerometer.

[0014] In a possible implementation, the error model is expressed as:

[0015] a c = S a K a a s + b a

[0016] The and are measurement values and true values of the three-axis MEMS accelerometer respectively;

[0017] The b a = (b aX , b aY , b aZ ) T are the three-axis zero offsets;

[0018] The three-axis scale factors and the inter-axis crosstalk factors together form scale factors S a .

[0019] All the mounting error angles of the three-axis MEMS accelerometer form mechanical mounting errors K a .

[0020] In a possible implementation, the design of the turntable-free programming scheme of the three-axis MEMS accelerometer includes:

[0021] The turntable-free programming scheme is arranged according to six directions of x-up, x-down, y-up, y-down, z-up and z-down of the coordinates of the three-axis MEMS accelerometer.

[0022] In a possible implementation, the collection of measurement data according to the turntable-free programming scheme includes:

[0023] Data collection is performed according to the six directions of x-up, x-down, y-up, y-down, z-up and z-down.

[0024] In a possible implementation, the construction of the calibration model of the three-axis MEMS accelerometer according to the turntable-free programming scheme includes:

[0025] The calibration model is constructed according to the six positions in the turntable-free programming scheme;

[0026] The calibration model is expressed as:

[0027]

[0028] the and respectively represent the estimated value of the X-axis true value of the MEMS accelerometer when the X-axis is upward and downward respectively;

[0029] the and respectively represent the estimated value of the X-axis true value of the MEMS accelerometer when the Y-axis is upward and downward respectively;

[0030] the and respectively represent the estimated value of the X-axis true value of the MEMS accelerometer when the Z-axis is upward and downward respectively;

[0031] the and respectively represent the estimated value of the X-axis, Y-axis and Z-axis true value of the accelerometer respectively;

[0032] the n represents the number of data collected at each position;

[0033] the g represents the reference value of the gravitational acceleration.

[0034] In a possible implementation, the error parameter obtained by solving the calibration model through the improved particle swarm optimization algorithm comprises:

[0035] the weight factor ω in the particle swarm optimization algorithm is improved to obtain an improved weight factor ω;

[0036] the calibration model is solved according to the improved weight factor ω to obtain the error parameter.

[0037] In a possible implementation, the improvement of the weight factor ω in the particle swarm optimization algorithm to obtain the improved weight factor ω comprises:

[0038] the calculation method of the weight factor ω in the particle swarm optimization algorithm is improved, and the improved weight factor is as follows:

[0039] ω = ω min + r(λ)(ω max - ω min ) + [1-r(λ)]h(λ)

[0040] wherein, the ω max and ωmin are the upper and lower limits of the weight factor, λ is the current iteration number, r(λ) and h(λ) are the first adjustment functions of the weight factor respectively.

[0041] r(λ) = τ[cos(λ / M)]

[0042] Wherein, the tau is a random number in the interval, the M is the maximum iteration number.

[0043]

[0044] Wherein, the L is the Levy flight function, the gbest m And x m Respectively, the group optimal position and the particle current position, the g(lambda) is the quadratic adjustment function.

[0045] G(lambda)=[log(M-lambda+2) / logM] 2

[0046] Wherein, the is the current iteration number, the M is the maximum iteration number.

[0047] In a possible implementation, the static calibration of the triaxial MEMS accelerometer according to the error parameter further comprises the following steps:

[0048] The calibration effect of the static calibration is obtained according to the output module value of the triaxial MEMS accelerometer before and after the static calibration.

[0049] The triaxial MEMS accelerometer while drilling non-rotating table calibration method in the application has the following advantages:

[0050] (1) The triaxial scale factor, triaxial zero offset, installation error angle and inter-axis crosstalk factor and other inter-axis crosstalk effects are used to establish a triaxial MEMS accelerometer error model, which improves the accuracy of the error model modeling.

[0051] (2) The calibration model based on the non-rotating table arrangement scheme is used, and the improved particle swarm algorithm is used to identify the error parameter, forming a new method for non-rotating table calibration of the triaxial MEMS accelerometer while drilling. BRIEF DESCRIPTION OF DRAWINGS

[0052] In order to more clearly illustrate the technical solutions in the embodiments of the application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiment or prior art description. Obviously, the drawings in the following description are only some embodiments of the application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0053] Figure 1 A flow chart of a triaxial MEMS accelerometer while drilling non-rotating table calibration method provided by the embodiment of the application is provided.

[0054] Figure 2 A position arrangement scheme schematic diagram of a triaxial MEMS accelerometer while drilling non-rotating table calibration method provided by the embodiment of the application is provided.

[0055] Figure 3 A three-axis MEMS accelerometer no-platform calibration method for drilling provided by an embodiment of the present application, a three-axis measurement data graph of a MEMS accelerometer collected in an embodiment of the present application is shown in the figure;

[0056] Figure 4 A convergence curve graph in an embodiment of the three-axis MEMS accelerometer no-platform calibration method for drilling provided by the present application is shown in the figure;

[0057] Figure 5 A comparison graph of output module values of the accelerometer before and after calibration in an embodiment of the three-axis MEMS accelerometer no-platform calibration method for drilling provided by the present application is shown in the figure;

[0058] Figure 6 A comparison graph of well inclination measurement values before and after calibration in an embodiment of the three-axis MEMS accelerometer no-platform calibration method for drilling provided by the present application is shown in the figure. DETAILED DESCRIPTION

[0059] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0060] Figure 1 A flowchart of a three-axis MEMS accelerometer no-platform calibration method for drilling provided by an embodiment of the present application is shown in the figure. The present application provides a three-axis MEMS accelerometer no-platform calibration method for drilling, which comprises: establishing an error model of a three-axis MEMS accelerometer according to the influence of inter-axis crosstalk;

[0061] designing a no-platform arrangement scheme of the three-axis MEMS accelerometer;

[0062] collecting measurement data according to the no-platform arrangement scheme;

[0063] constructing a calibration model of the three-axis MEMS accelerometer according to the no-platform arrangement scheme;

[0064] solving the calibration model to obtain error parameters by using an improved particle swarm optimization algorithm;

[0065] completing static calibration of the three-axis MEMS accelerometer according to the error parameters.

[0066] The error model of the three-axis MEMS accelerometer according to the influence of inter-axis crosstalk comprises:

[0067] The error model is established according to three-axis scale factors, three-axis zero offsets, mounting error angles and inter-axis crosstalk factors of the three-axis MEMS accelerometer.

[0068] The error model is expressed as:

[0069] a c = S a K a a s + b a

[0070] The and are measured values and true values of the three-axis MEMS accelerometer respectively;

[0071] The b a = (b aX , b aY , b aZ ) T is the three-axis zero offset;

[0072] The three-axis scale factors and the inter-axis crosstalk factors together constitute scale factors S a .

[0073] All mounting error angles of the three-axis MEMS accelerometer constitute mechanical mounting errors K a .

[0074] The design of the turntable-free programming scheme of the three-axis MEMS accelerometer includes:

[0075] The turntable-free programming scheme is arranged according to six directions of x-axis up, x-axis down, y-axis up, y-axis down, z-axis up and z-axis down of coordinates of the three-axis MEMS accelerometer.

[0076] The collection of measurement data according to the turntable-free programming scheme includes:

[0077] Data collection is performed according to the six directions of x-axis up, x-axis down, y-axis up, y-axis down, z-axis up and z-axis down.

[0078] The construction of the calibration model of the three-axis MEMS accelerometer according to the turntable-free programming scheme includes:

[0079] The calibration model is constructed according to six positions in the turntable-free programming scheme;

[0080] The calibration model is expressed as:

[0081]

[0082] The and respectively represent the estimated values of the true values of the MEMS accelerometer X axis when the X axis is upward and downward respectively;

[0083] the and respectively represent the estimated values of the true values of the MEMS accelerometer X axis when the Y axis is upward and downward respectively;

[0084] the and respectively represent the estimated values of the true values of the MEMS accelerometer X axis when the Z axis is upward and downward respectively;

[0085] the and respectively represent the estimated values of the true values of the MEMS accelerometer X axis, Y axis and Z axis respectively;

[0086] the n represents the number of data collected at each position;

[0087] the g represents the reference value of the gravitational acceleration.

[0088] the error parameters obtained by solving the calibration model through the improved particle swarm optimization algorithm include:

[0089] the weight factor ω in the particle swarm optimization algorithm is improved to obtain an improved weight factor ω;

[0090] the calibration model is solved according to the improved weight factor ω to obtain error parameters.

[0091] the weight factor ω in the particle swarm optimization algorithm is improved to obtain an improved weight factor ω includes:

[0092] the calculation method of the weight factor ω in the particle swarm optimization algorithm is improved, and the improved weight factor is as follows:

[0093] ω = ω min + r(λ)(ω max - ω min ) + [1-r(λ)]h(λ)

[0094] wherein, the ω max and ωmin are the upper and lower limits of the weight factor, λ is the current iteration number, and the r(λ) and h(λ) are the first adjustment functions of the weight factor.

[0095] r(λ) = τ[cos(λ / M)]

[0096] wherein, the τ is a random number in the interval, and the M is the maximum iteration number.

[0097]

[0098] Wherein, the L is Levy flight function, the gbest m and x m are the group optimal position and particle current position respectively, and the g(λ) is a quadratic adjustment function.

[0099] g(λ) = [log(M-λ+2) / logM] 2

[0100] Wherein, the is the current iteration number of λ, and the M is the maximum iteration number.

[0101] The static calibration of the three-axis MEMS accelerometer according to the error parameter further comprises:

[0102] The calibration effect of the static calibration is obtained according to the output module value of the three-axis MEMS accelerometer before and after the static calibration.

[0103] Exemplarily, the scale factor S a is specifically represented as:

[0104]

[0105] Wherein, S aX , S aY and S aZ are three-axis scale factors, S aXY , S aXZ , S aYX , S aYZ , S aZX and S aZY are cross-axis sensitivities.

[0106] The mechanical installation error K a is specifically represented as:

[0107]

[0108] Wherein, θ XY , θ XZ , θ YX , θ YZ , θ ZX and θ ZY are installation error angles.

[0109] In order to simplify the MEMS accelerometer data collection position arrangement scheme and improve the calibration efficiency, a non-rotating table arrangement scheme is adopted. For example, Figure 2As shown, first, the MEMS accelerometer is placed horizontally at position 1 with the X axis downward, and the three-axis output data is recorded after being static; then, the MEMS accelerometer is placed horizontally at position 2 with the X axis upward, and the three-axis output data is recorded after being static. The static measurement data of the MEMS accelerometer at six positions is collected in the order of X axis downward, X axis upward, Y axis downward, Y axis upward, Z axis downward, and Z axis upward.

[0110] A calibration model of the three-axis MEMS accelerometer is constructed.

[0111]

[0112] wherein, and respectively represent the estimated values of the X axis true value of the MEMS accelerometer when the X axis is upward and downward, and respectively represent the estimated values of the X axis true value of the MEMS accelerometer when the X axis is upward and downward, and respectively represent the estimated values of the X axis true value of the MEMS accelerometer when the X axis is upward and downward, and respectively represent the estimated values of the X axis, Y axis, and Z axis accelerometer true value; n represents the number of data collected at each position, and g represents the reference value of the gravitational acceleration.

[0113] The estimated value of the three-axis MEMS accelerometer true value is represented as:

[0114]

[0115] wherein, is the estimated value of the three-axis MEMS accelerometer true value, is the measurement value of the three-axis MEMS accelerometer.

[0116] The improved particle swarm optimization algorithm is used to solve the calibration model of the three-axis MEMS accelerometer.

[0117] The calculation method of the weight factor ω in the improved particle swarm optimization algorithm is improved, and the improved weight factor is as follows:

[0118] ω = ω min + r(λ)(ω max - ω min ) + [1 - r(λ)]h(λ) (5)

[0119] wherein, ω max and ωmin are the upper and lower limits of the weight factor, λ is the current iteration number, r(λ) and h(λ) are the weight factor first adjustment functions defined in the application.

[0120] The first adjustment function r(λ) is expressed as:

[0121] r(λ) = τ [cos(λ / M)] (6)

[0122] wherein τ is a random number in the interval [0, 1], and M is the maximum number of iterations.

[0123] The first adjustment function h(λ) is expressed as:

[0124]

[0125] wherein L is a Levy flight function, gbest m and x m are the global optimal position and the current position of the particle, respectively, and g(λ) is the second adjustment function.

[0126] The second adjustment function g(λ) is expressed as:

[0127] g(λ) = [log(M-λ+2) / logM] 2 (8)

[0128] wherein λ is the current number of iterations, and M is the maximum number of iterations.

[0129] The population size and the maximum number of iterations are set to 200 and 500, respectively, and the error parameters obtained in the first iteration are shown in Table 1:

[0130] Table 1 Error parameters in the first iteration

[0131]

[0132] The convergence curve of the objective function value F in the iteration process is shown in Figure 4 After 500 iterations, the change curve of the objective function value is stably converged to 799.64 by using the improved particle swarm optimization algorithm to solve the calibration model.

[0133] The error parameters obtained in the 500th iteration are shown in Table 2:

[0134] Table 2 Error parameters in the 500th iteration

[0135]

[0136] The static calibration of the three-axis MEMS accelerometer is completed according to the obtained error parameters, and the comparison results of the output module values of the accelerometer before and after the calibration are shown in Figure 5 The relative error between the output module value of the accelerometer after the calibration and the reference value is less than 0.06%.

[0137] The comparison results of the inclination angle measurement values before and after the calibration are shown in Figure 6As shown, the post-calibration borehole inclination measurement error is less than 0.2°.

[0138] While the preferred embodiments of the application have been described, additional variations and modifications can be made to the embodiments by those skilled in the art once they learn of the basic inventive concepts. Therefore, the appended claims are intended to encompass within their scope all such variations and modifications as are included within the scope of the application.

[0139] Obviously, numerous modifications and variations of the present application are possible in light of the above teachings. It is therefore to be understood that within the scope of the appended claims and their equivalents, the application can be practiced otherwise than as specifically described.

Claims

1. A method for calibration of a tri-axial MEMS accelerometer while drilling without a turntable, characterized in that, The method comprises the following steps: establishing an error model of a three-axis MEMS accelerometer according to the influence of inter-axis crosstalk; designing a turntable-free arrangement scheme of the three-axis MEMS accelerometer; collecting measurement data according to the turntable-free arrangement scheme; constructing a calibration model of the three-axis MEMS accelerometer according to the turntable-free arrangement scheme; solving the calibration model to obtain error parameters by using an improved particle swarm optimization algorithm; and completing static calibration of the three-axis MEMS accelerometer according to the error parameters.

2. The no-rotary-table calibration method for a tri-axial MEMS accelerometer while drilling according to claim 1, wherein, The step of establishing the error model of the three-axis MEMS accelerometer according to the influence of inter-axis crosstalk comprises: establishing the error model according to three-axis scale factors, three-axis zero offsets, installation error angles and inter-axis crosstalk factors of the three-axis MEMS accelerometer.

3. The no-rotary-table calibration method for a tri-axial MEMS accelerometer while drilling according to claim 2, wherein, The error model is expressed as: a c = S a K a a s + b a The and are the measured and true values, respectively, of the tri-axial MEMS accelerometer The b a = (b aX , b aY , b aZ ) T is the three-axis zero offset; The three-axis scale factor and the inter-axis crosstalk factor together make up a scale factor S a ; All the mounting error angles of the tri-axis MEMS accelerometer constitute a mechanical mounting error K a .

4. The no-rotary-table calibration method for a tri-axial MEMS accelerometer while drilling according to claim 1, wherein, The step of designing the turntable-free arrangement scheme of the three-axis MEMS accelerometer comprises: setting the turntable-free arrangement scheme according to six directions of x-up, x-down, y-up, y-down, z-up and z-down of coordinates of the three-axis MEMS accelerometer.

5. The no-rotary-table calibration method for a tri-axial MEMS accelerometer while drilling according to claim 4, wherein, The step of collecting measurement data according to the turntable-free arrangement scheme comprises: collecting data according to the six directions of x-up, x-down, y-up, y-down, z-up and z-down.

6. The no-rotary-table calibration method for a tri-axial MEMS accelerometer while drilling according to claim 1, wherein, The step of constructing the calibration model of the three-axis MEMS accelerometer according to the turntable-free arrangement scheme comprises: constructing a calibration model according to six positions in the turntable-free arrangement scheme. The calibration model is expressed as: The and respectively represent the estimated value of the true value of the X-axis of the MEMS accelerometer when the X-axis is upward and downward. The and respectively represent the estimated value of the true value of the X-axis of the MEMS accelerometer when the Y-axis is upward and downward. The and respectively represent the estimated value of the true value of the X axis of the MEMS accelerometer when the Z axis is upward and downward. The and respectively represent the estimated values of the X-axis, Y-axis, and Z-axis accelerometer true values; n represents the number of data collected at each position; g represents a reference value of gravitational acceleration.

7. The no-rotary-table calibration method of a tri-axial MEMS accelerometer while drilling according to claim 1, wherein, The step of solving the calibration model to obtain error parameters by using the improved particle swarm optimization algorithm comprises: improving a weight factor ω in the particle swarm optimization algorithm to obtain an improved weight factor ω; solving the calibration model according to the improved weight factor ω to obtain error parameters.

8. The no-rotary-table calibration method of a triaxial MEMS accelerometer while drilling according to claim 7, wherein, The step of improving the weight factor ω in the particle swarm optimization algorithm to obtain the improved weight factor ω comprises: improving a calculation method of the weight factor ω in the particle swarm optimization algorithm, and the improved weight factor is as follows: ω = ω min + r(λ)(ω max - ω min ) + [1 - r(λ)]h(λ) wherein the ω max and ωminare upper and lower limits of the weight factor, respectively, λ is the current iteration number, and r(λ) and h(λ) are first order adjustment functions of the weight factor, respectively. r(λ)=τ[cos(λ / M)] wherein τ is a random number in an interval, and M is a maximum iteration number. wherein L is a Levy flight function, gbest m and x m are the global best position and the current position of the particle, respectively, and g(λ) is a quadratic adjustment function. g(A) = [log(M - A + 2) / log M] 2 wherein λ is a current iteration number, and M is a maximum iteration number.

9. The no-rotary-table calibration method of a tri-axial MEMS accelerometer while drilling according to claim 1, wherein, The method further comprises the following step after the step of completing static calibration of the three-axis MEMS accelerometer according to the error parameters: obtaining calibration effects of the static calibration according to output mode values of the three-axis MEMS accelerometer before and after the static calibration.

Images