A motor status monitoring method and device for automatically and quickly deploying and retracting a tent

Abstract

The present invention discloses a motor status monitoring method and device for an automatic and rapid tent deployment. The method comprises: acquiring a set of operating parameter values ​​of a drive motor for the automatic and rapid tent deployment; the drive motor operating parameter value set comprises an operating value sequence of each parameter; the parameters comprise motor rotor speed and inverter voltage; the operating value sequence is a discrete value acquired at a number of moments; preprocessing the drive motor operating parameter value set to obtain a preprocessing parameter set; and performing status health monitoring processing on the preprocessing parameter set to obtain a motor status monitoring result value for the automatic and rapid tent deployment.

Description

Technical Field

[0001] The present invention relates to the fields of industrial data processing, automatic control evaluation and strategy optimization processing, and in particular to a motor status monitoring method and device for automatically and quickly deploying and retracting a tent. Background Art

[0002] With the increasing demand for quick erection and folding of tents in fields such as outdoor activities and emergency rescue, automatic quick-folding tents have emerged. However, in the existing technology, there are many problems with the monitoring of the operating status of the motor of the automatic quick-folding tent. On the one hand, traditional monitoring methods mostly rely on manual inspections or simple sensor alarms, which cannot obtain the operating parameters of the motor in real time and accurately, and it is difficult to accurately evaluate the status of the motor. On the other hand, in the process of data processing, the existing monitoring technology often ignores the discreteness and dynamic change characteristics of the operating parameters, resulting in insufficient accuracy and reliability of the monitoring results. In addition, there is a lack of effective screening and processing mechanism for abnormal data of the motor operating parameters, which can easily lead to misjudgment of the motor status due to interference from noise data, affecting the normal use and safety of the tent. Therefore, there is an urgent need for a method and device that can efficiently and accurately monitor the status of the motor of the automatic quick-folding tent to meet the needs of actual application scenarios. Summary of the Invention

[0003] The present invention mainly solves the problem of how to quickly and effectively monitor the status of a motor of an automatic and rapid tent deployment. The present invention discloses a method and device for monitoring the status of a motor of an automatic and rapid tent deployment.

[0004] In a first aspect, an embodiment of the present invention discloses a method for monitoring the status of a motor for automatically and quickly deploying and retracting a tent, comprising:

[0005] S1, acquiring a set of operating parameter values ​​of a drive motor for automatically and rapidly deploying and retracting a tent; the set of operating parameter values ​​of the drive motor includes an operating value sequence of each parameter; the parameters include motor rotor speed, inverter voltage, torque, temperature, and power; the operating value sequence is a discrete value of the parameter acquired at a plurality of moments;

[0006] S2, preprocessing the drive motor operating parameter value set to obtain a preprocessing parameter set;

[0007] S3, performing health monitoring processing on the pre-processing parameter set to obtain a status monitoring result value of a motor for automatically and quickly extending and retracting the tent.

[0008] The preprocessing of the drive motor operating parameter value set to obtain a preprocessing parameter set includes:

[0009] S21, performing data filtering processing on the set of operating parameter values ​​of the drive motor to obtain a first data set;

[0010] S22, performing category checking processing on the first data set to obtain a second data set;

[0011] S23: Perform pattern discrimination processing on the second data set to obtain a preprocessing parameter set.

[0012] The performing pattern discrimination processing on the second data set to obtain a preprocessing parameter set includes:

[0013] S231, constructing an approximation matrix using each operating value sequence in the second data set as a row vector; constructing an acquisition matrix using data acquisition information of each operating value sequence as a row vector; constructing a matching optimization model using the approximation matrix as a dependent variable and the acquisition matrix as an independent variable;

[0014] S232, solving the matching optimization model to obtain a matching discrimination model; the matching discrimination model is expressed as f(x)=xA, where x is the input acquisition matrix of the matching discrimination model, and the matrix A is obtained by solving the matching optimization model;

[0015] S233, using the matching discriminant model, calculating and processing the data collection information of each type of operating value sequence to obtain a solution matrix;

[0016] S234, subtracting each data in the solution matrix from the data in the approximation matrix that is in the same row and column as the data in the solution matrix, and calculating the absolute value to obtain a difference value of the data;

[0017] S235, deleting the data whose difference value is greater than the set difference threshold from the second data set;

[0018] S236 , executing S234 to S235 for each data in the solution matrix to obtain a preprocessing parameter set.

[0019] The difference threshold is set to 11.

[0020] The performing of health monitoring processing on the preprocessing parameter set to obtain a motor health monitoring result value for automatically and quickly extending and retracting the tent includes:

[0021] Performing distribution stability calculation on the running value sequence of the motor rotor speed in the preprocessing parameter set to obtain a distribution stability value;

[0022] Calculating a distribution concentration value of an operating value sequence of the inverter voltage in the preprocessing parameter set to obtain a distribution concentration value;

[0023] Determine whether the distribution stability value and the distribution concentration value simultaneously satisfy the requirement that the distribution stability value is greater than a preset first threshold value and the distribution concentration value is less than a preset second threshold value, thereby obtaining a first determination result;

[0024] When the first discrimination result is yes, the preprocessing parameter set is processed using a distribution discrimination model to obtain a motor state monitoring result value for automatically and quickly extending and retracting the tent;

[0025] When the first discrimination result is negative, the preprocessing parameter set is processed using a difference discrimination model to obtain a motor state monitoring result value for automatically and quickly extending and retracting the tent.

[0026] The distribution concentration value calculation includes:

[0027] Assume that the operating value sequence of the inverter voltage obeys the χ with n degrees of freedom. 2 distributed;

[0028] Calculating a quantile boundary value α according to the operating value sequence of the inverter voltage;

[0029] According to the quantile boundary value α, we can obtain the χ value with n degrees of freedom. 2 The 1-α quantile value of the distribution;

[0030] Determine the n degrees of freedom x 2 The 1-α percentile value of the distribution is the distribution concentration value.

[0031] The step of calculating the quantile boundary value α based on the operating value sequence of the inverter voltage includes:

[0032] Calculating the mean and variance of the operating value sequence of the inverter voltage;

[0033] Calculating the mean and variance of the running value sequence to obtain a quantile boundary value α;

[0034] The calculation expression of the quantile boundary value α is:

[0035]

[0036] Wherein, μ and δ are the mean and variance of the running value sequence respectively.

[0037] The distribution stability calculation includes:

[0038] Assume that the running value sequence of the motor rotor speed obeys the standard normal distribution;

[0039] Calculating the second-order central moment and the third-order origin moment of the running value sequence of the motor rotor speed;

[0040] Performing joint calculation processing on the second-order central moment and the third-order origin moment to obtain a distribution stability value;

[0041] The expression for the joint calculation process is:

[0042]

[0043] Among them, p is the distribution stability value, l i is the i-th element of the running value sequence of the motor rotor speed, l0 is the second-order central moment, ε is the third-order origin moment, N is the total number of elements in the running value sequence of the motor rotor speed, and lmax is the maximum element in the running value sequence of the motor rotor speed.

[0044] According to a second aspect of the present invention, a motor status monitoring device for automatically and quickly deploying and retracting a tent is disclosed, the device comprising:

[0045] a memory storing executable program code;

[0046] a processor coupled to the memory;

[0047] The processor calls the executable program code stored in the memory to execute the motor status monitoring method for automatically and quickly deploying and retracting a tent.

[0048] According to a third aspect of the present invention, a computer storable medium is disclosed. The computer storable medium stores computer instructions. When the computer instructions are called by a computer, the computer instructions are used to execute the motor status monitoring method for automatically and quickly deploying and retracting a tent.

[0049] According to a fourth aspect of the present invention, an information data processing terminal is disclosed. The information data processing terminal is used to implement the motor status monitoring method for automatically and quickly deploying and retracting a tent.

[0050] The beneficial effects of the present invention are:

[0051] By collecting discrete value sequences of key operating parameters such as motor rotor speed and inverter voltage, and performing preprocessing operations such as data filtering, category checking, and pattern discrimination, noise and abnormal data are effectively removed, the accuracy and reliability of monitoring data are improved, and a solid foundation is laid for subsequent status health monitoring.

[0052] During the health monitoring phase, the distribution stability and distribution concentration of the operating value sequences of the motor rotor speed and inverter voltage are calculated respectively, and a comprehensive judgment is made by combining the distribution discrimination model and the difference discrimination model. This enables a comprehensive and accurate assessment of the motor status, and can promptly detect potential fault hazards of the motor, ensuring the reliable operation of the automatic and rapid deployment and retraction of the tent.

[0053] The method and device of the present invention have a high degree of automation and can monitor the motor status in real time and dynamically without manual intervention, which greatly improves the monitoring efficiency and reduces labor costs. At the same time, it improves the safety and service life of the automatic and rapid deployment tent, and has broad application prospects and important practical significance. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 4 is an implementation flow chart of the method of the present invention. DETAILED DESCRIPTION

[0055] In order to better understand the content of the present invention, an embodiment is given here.

[0056] Figure 1 4 is an implementation flow chart of the method of the present invention.

[0057] In a first aspect, an embodiment of the present invention discloses a method for monitoring the status of a motor for automatically and quickly deploying and retracting a tent, comprising:

[0058] S1, acquiring a set of operating parameter values ​​of a drive motor for automatically and rapidly deploying and retracting a tent; the set of operating parameter values ​​of the drive motor includes an operating value sequence of each parameter; the parameters include motor rotor speed, inverter voltage, torque, temperature, and power; the operating value sequence is a discrete value acquired at a plurality of moments;

[0059] S2, preprocessing the drive motor operating parameter value set to obtain a preprocessing parameter set;

[0060] S3, performing health monitoring on the preprocessing parameter set to obtain a motor health monitoring result value for automatically and quickly extending and retracting the tent;

[0061] The preprocessing of the drive motor operating parameter value set to obtain a preprocessing parameter set includes:

[0062] S21, performing data filtering processing on the set of operating parameter values ​​of the drive motor to obtain a first data set;

[0063] S22, performing category checking processing on the first data set to obtain a second data set;

[0064] S23, performing pattern discrimination processing on the second data set to obtain a preprocessing parameter set;

[0065] The performing pattern discrimination processing on the second data set to obtain a preprocessing parameter set includes:

[0066] S231, constructing an approximation matrix using each operating value sequence in the second data set as a row vector; constructing an acquisition matrix using data acquisition information of each operating value sequence as a row vector; constructing a matching optimization model using the approximation matrix as a dependent variable and the acquisition matrix as an independent variable;

[0067] S232, solving the matching optimization model to obtain a matching discrimination model; the matching discrimination model is expressed as f(x)=xA, where x is the input acquisition matrix of the matching discrimination model, and the matrix A is obtained by solving the matching optimization model;

[0068] S233, using the matching discriminant model, calculating and processing the data collection information of each type of operating value sequence to obtain a solution matrix;

[0069] S234, subtracting each data in the solution matrix from the data in the approximation matrix that is in the same row and column as the data in the solution matrix, and calculating the absolute value to obtain a difference value of the data;

[0070] S235, deleting the data whose difference value is greater than the set difference threshold from the second data set;

[0071] S236 , executing S234 to S235 for each data in the solution matrix to obtain a preprocessing parameter set.

[0072] The present invention uses the approximation matrix and the acquisition matrix to construct a matching optimization model, and obtains the matching discrimination model by solving it, further optimizing the data acquisition information processing process of the operating value sequence. It can accurately identify and eliminate data with difference values ​​greater than the set threshold, ensuring that the preprocessed parameter set is more representative and improving the accuracy of the monitoring results.

[0073] The performing of health monitoring processing on the preprocessing parameter set to obtain a motor health monitoring result value for automatically and quickly extending and retracting the tent includes:

[0074] Performing distribution stability calculation on the running value sequence of the motor rotor speed in the preprocessing parameter set to obtain a distribution stability value;

[0075] Calculating a distribution concentration value of an operating value sequence of the inverter voltage in the preprocessing parameter set to obtain a distribution concentration value;

[0076] Determine whether the distribution stability value and the distribution concentration value simultaneously satisfy the requirement that the distribution stability value is greater than a preset first threshold value and the distribution concentration value is less than a preset second threshold value, thereby obtaining a first determination result;

[0077] When the first discrimination result is yes, the preprocessing parameter set is processed using a distribution discrimination model to obtain a motor state monitoring result value for automatically and quickly extending and retracting the tent;

[0078] When the first discrimination result is negative, the preprocessing parameter set is processed using a difference discrimination model to obtain a motor state monitoring result value for automatically and quickly extending and retracting the tent;

[0079] The distribution concentration value calculation includes:

[0080] Assume that the operating value sequence of the inverter voltage obeys the χ with n degrees of freedom. 2 distributed;

[0081] Calculating a quantile boundary value α according to the operating value sequence of the inverter voltage;

[0082] According to the quantile boundary value α, we can obtain the χ value with n degrees of freedom. 2 The 1-α quantile value of the distribution;

[0083] Determine the n degrees of freedom x 2 The 1-α percentile value of the distribution is the distribution concentration value.

[0084] The value of the degree of freedom n can be 3; is χ with n degrees of freedom 2 1-α quantile of the distribution

[0085] According to the quantile boundary value α, we can obtain the χ value with n degrees of freedom. 2 The 1-α quantile value of the distribution can be found by finding the χ 2 The probability density function value table of the distribution is obtained;

[0086] The first threshold may be 0.8, and the second threshold may be 0.6.

[0087] The step of calculating the quantile boundary value α based on the operating value sequence of the inverter voltage includes:

[0088] Calculating the mean and variance of the operating value sequence of the inverter voltage;

[0089] Calculating the mean and variance of the running value sequence to obtain a quantile boundary value α;

[0090] The calculation expression of the quantile boundary value α is:

[0091]

[0092] Wherein, μ and ε are the mean and variance of the running value sequence respectively;

[0093] The distribution stability calculation includes:

[0094] Assume that the running value sequence of the motor rotor speed obeys the standard normal distribution;

[0095] Calculating the second-order central moment and the third-order origin moment of the running value sequence of the motor rotor speed;

[0096] Performing joint calculation processing on the second-order central moment and the third-order origin moment to obtain a distribution stability value;

[0097] The expression for the joint calculation process is:

[0098]

[0099] Among them, p is the distribution stability value, l i is the i-th element of the running value sequence of the motor rotor speed, l0 is the second-order central moment, ε is the third-order origin moment, N is the total number of elements in the running value sequence of the motor rotor speed, and lmax is the maximum element in the running value sequence of the motor rotor speed.

[0100] The distribution discrimination model includes:

[0101] Obtaining a standard value of each parameter of a driving motor for the automatic rapid tent deployment;

[0102] Subtracting the running value sequence of each parameter of the preprocessing parameter set from the corresponding standard value to obtain a first difference sequence of each parameter;

[0103] Using all first difference sequences, a first difference matrix is ​​constructed;

[0104] performing a cross-correlation calculation on the first difference matrix to obtain a cross-correlation matrix, wherein the element in the i-th row and the j-th column of the cross-correlation matrix is ​​a cross-correlation value between the i-th row vector and the j-th row vector of the first difference matrix;

[0105] Performing eigenvalue calculation processing on the mutual correlation matrix to obtain an eigenvalue set; sorting all elements of the eigenvalue set from large to small according to their values ​​to obtain an eigenvalue vector;

[0106] Performing fusion calculation processing on the eigenvalue vector to obtain a motor state monitoring result value for automatically and quickly expanding and closing the tent;

[0107] The expression for the first feature calculation process is:

[0108]

[0109] Among them, DJZ is the motor status monitoring result value of the automatic rapid tent expansion and contraction, ri is the i-th element of the eigenvalue vector, ω i represents the mean of the i-th row of the first difference matrix, τ represents the mean of all elements of the first difference sequence, and N0 represents the number of rows of the first difference sequence;

[0110] The difference discrimination model includes:

[0111] Obtaining a standard value of each parameter of a driving motor for the automatic rapid tent deployment;

[0112] Dividing the running value sequence of each parameter of the preprocessing parameter set by the corresponding standard value to obtain a second difference sequence of each parameter;

[0113] Using all the second difference sequences, a second difference matrix is ​​constructed;

[0114] performing singular value solving processing on the second difference matrix to obtain a singular value set;

[0115] Sort all elements of the singular value set from small to large according to their values ​​to obtain a singular value sequence;

[0116] Performing evaluation and calculation processing on the singular value sequence to obtain a motor state monitoring result value for automatically and quickly extending and retracting the tent;

[0117] The expression for the evaluation calculation process is:

[0118]

[0119] Among them, T i () represents the i-th order polynomial of the first kind Chebyshev polynomial, p i represents the i-th element of the singular value sequence, J is the length of the singular value sequence, and DJZ is the motor status monitoring result value of the automatic rapid tent expansion and contraction;

[0120] The dividing of the running value sequence of each parameter of the preprocessing parameter set by the corresponding standard value is to divide each element of the running value sequence by the standard value;

[0121] The data filtering process includes filling missing values, smoothing noisy data, and smoothing or deleting outliers;

[0122] The category checking process includes determining, for each data in the first data set, whether its data attribute is consistent with a preset data attribute, and deleting inconsistent data from the first data set to obtain a second data set;

[0123] The data collection information is collection time information;

[0124] The matching optimization model is expressed as follows:

[0125] minvA-R,

[0126] subject to AA T =I A ,

[0127] Among them, I A represents the identity matrix with the row dimension of matrix A as the dimension, matrix A represents the matrix to be solved, v represents the acquisition matrix, and R represents the approximation matrix;

[0128] The algorithm for solving the matching optimization model can adopt genetic algorithm and particle filter algorithm;

[0129] The smaller the monitoring result value is, the healthier the running state of the motor is.

[0130] The motor of the automatic rapid tent deployment is used to control the deployment or contraction of the automatic rapid tent deployment support.

[0131] According to a second aspect of the present invention, a motor status monitoring device for automatically and quickly deploying and retracting a tent is disclosed, the device comprising:

[0132] a memory storing executable program code;

[0133] a processor coupled to the memory;

[0134] The processor calls the executable program code stored in the memory to execute the motor status monitoring method for automatically and quickly deploying and retracting a tent.

[0135] According to a third aspect of the present invention, a computer storable medium is disclosed. The computer storable medium stores computer instructions. When the computer instructions are called by a computer, the computer instructions are used to execute the motor status monitoring method for automatically and quickly deploying and retracting a tent.

[0136] According to a fourth aspect of the present invention, an information data processing terminal is disclosed. The information data processing terminal is used to implement the motor status monitoring method for automatically and quickly deploying and retracting a tent.

[0137] The foregoing is merely an embodiment of the present invention and is not intended to limit the present invention. It will be apparent to those skilled in the art that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention are intended to be included within the scope of the claims of the present invention.

Claims

1. A method for monitoring the motor status of a tent that can be automatically and quickly deployed, characterized in that: include: S1, acquiring a set of operating parameter values ​​of a drive motor for automatically and rapidly deploying and retracting a tent; the set of operating parameter values ​​of the drive motor includes an operating value sequence of each parameter; the parameters include motor rotor speed, inverter voltage, torque, temperature, and power; the operating value sequence is a discrete value of the parameter acquired at a plurality of moments; S2, preprocessing the drive motor operating parameter value set to obtain a preprocessing parameter set; S3, performing health monitoring on the preprocessing parameter set to obtain a motor health monitoring result value for automatically and quickly extending and retracting the tent; The performing of health monitoring processing on the preprocessing parameter set to obtain a motor health monitoring result value for automatically and quickly extending and retracting the tent includes: Performing distribution stability calculation on the running value sequence of the motor rotor speed in the preprocessing parameter set to obtain a distribution stability value; Calculating a distribution concentration value of an operating value sequence of the inverter voltage in the preprocessing parameter set to obtain a distribution concentration value; Determine whether the distribution stability value and the distribution concentration value simultaneously satisfy the requirement that the distribution stability value is greater than a preset first threshold value and the distribution concentration value is less than a preset second threshold value, thereby obtaining a first determination result; When the first discrimination result is yes, the preprocessing parameter set is processed using a distribution discrimination model to obtain a motor state monitoring result value for automatically and quickly extending and retracting the tent; When the first discrimination result is negative, the preprocessing parameter set is processed using a difference discrimination model to obtain a motor state monitoring result value for automatically and quickly extending and retracting the tent.

2. The method for monitoring the motor status of an automatic and rapid tent deployment and folding according to claim 1, wherein: The preprocessing of the drive motor operating parameter value set to obtain a preprocessing parameter set includes: S21, performing data filtering processing on the set of operating parameter values ​​of the drive motor to obtain a first data set; S22, performing category checking processing on the first data set to obtain a second data set; S23: Perform pattern discrimination processing on the second data set to obtain a preprocessing parameter set.

3. The method for monitoring the motor status of an automatic and rapid tent deployment and folding according to claim 2, wherein: The performing pattern discrimination processing on the second data set to obtain a preprocessing parameter set includes: S231, constructing an approximation matrix using each operating value sequence in the second data set as a row vector; constructing an acquisition matrix using data acquisition information of each operating value sequence as a row vector; constructing a matching optimization model using the approximation matrix as a dependent variable and the acquisition matrix as an independent variable; S232, solving the matching optimization model to obtain a matching discrimination model; the matching discrimination model is expressed as f(x)=xA, where x is the input acquisition matrix of the matching discrimination model, and the matrix A is obtained by solving the matching optimization model; S233, using the matching discriminant model, calculating and processing the data collection information of each type of operating value sequence to obtain a solution matrix; S234, subtracting each data in the solution matrix from the data in the approximation matrix that is in the same row and column as the data in the solution matrix, and calculating the absolute value to obtain a difference value of the data; S235, deleting the data whose difference value is greater than the set difference threshold from the second data set; S236 , executing S234 to S235 for each data in the solution matrix to obtain a preprocessing parameter set.

4. The method for monitoring the motor status of an automatic and rapid tent deployment and folding according to claim 1, wherein: The distribution concentration value calculation includes: Assume that the operating value sequence of the inverter voltage obeys the χ with n degrees of freedom. 2 distributed; Calculating a quantile boundary value α according to the operating value sequence of the inverter voltage; According to the quantile boundary value α, we can obtain the χ value with n degrees of freedom. 2 The 1-α quantile value of the distribution; Determine the n degrees of freedom x 2 The 1-α percentile value of the distribution is the distribution concentration value.

5. The method for monitoring the motor status of an automatic and rapid tent deployment and folding according to claim 4, wherein: The step of calculating the quantile boundary value α based on the operating value sequence of the inverter voltage includes: Calculating the mean and variance of the operating value sequence of the inverter voltage; Calculating the mean and variance of the running value sequence to obtain a quantile boundary value α; The calculation expression of the quantile boundary value α is: Wherein, μ and δ are the mean and variance of the running value sequence respectively.

6. The method for monitoring the motor status of an automatic and rapid tent deployment and folding system according to claim 1, wherein: The distribution stability calculation includes: Assume that the running value sequence of the motor rotor speed obeys the standard normal distribution; Calculating the second-order central moment and the third-order origin moment of the running value sequence of the motor rotor speed; Performing joint calculation processing on the second-order central moment and the third-order origin moment to obtain a distribution stability value; The expression for the joint calculation process is: Among them, p is the distribution stability value, l i is the i-th element of the running value sequence of the motor rotor speed, l0 is the second-order central moment, ε is the third-order origin moment, N is the total number of elements in the running value sequence of the motor rotor speed, and lmax is the maximum element in the running value sequence of the motor rotor speed.

7. A motor status monitoring device for automatically and quickly deploying and retracting a tent, characterized in that: The device comprises: a memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the motor status monitoring method for automatically and quickly deploying and retracting a tent according to any one of claims 1 to 6.

8. A computer storable medium, characterized in that The computer storable medium stores computer instructions, and when the computer instructions are called by a computer, they are used to execute the motor status monitoring method for automatically and quickly deploying and retracting a tent according to any one of claims 1 to 6.

9. An information data processing terminal, characterized in that: The information data processing terminal is used to implement the motor status monitoring method for automatically and quickly deploying and retracting a tent as claimed in any one of claims 1 to 6.

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