CN113177337B - Reed harvester safety assessment method based on association factor characteristic value fluctuation interval - Google Patents
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Abstract
The invention discloses a reed harvester operation safety assessment method based on a correlation factor characteristic value fluctuation interval, which comprises the following steps: s1, monitoring local vibration of a reed harvester structure in real time; s2, determining a correlation factor of a vibration area; s3, determining a relevance factor intermediate density value based on Weibull probability; s4, determining a safety early warning value based on the damage intermediate probability density value; s5, determining the damage degree based on the association factors. The method has high monitoring precision and has important practical significance for determining the health state of the large reed harvester.
Description
Technical Field
The invention relates to a mechanical safety assessment method, in particular to a reed harvester safety assessment method based on a fluctuation range of characteristic values of association factors.
Background
The status of large reed harvesters in modern agricultural production is increasingly prominent, and the safety problem in the reed harvesting process is increasingly emphasized. Therefore, real-time health monitoring of reed harvesters is necessary during their operation. The current state monitoring method of reed harvesters generally collects vibration signals and the like of the reed harvesters on site and performs diagnosis according to the spectrum analysis and extraction characteristics of the vibration signals, but the method is cumbersome and inconvenient to collect on site and has low precision.
Disclosure of Invention
The invention aims to: the invention aims to provide a reed harvester operation safety assessment method based on a fluctuation range of characteristic values of association factors, which has high monitoring precision. The safety early warning mode of the association factor and the characteristic value fluctuation interval is considered, so that the self-detection function of the reed harvester is realized, and the health state of the reed harvester is better monitored.
The technical scheme is as follows: the invention provides a reed harvester operation safety assessment method based on a fluctuation range of a characteristic value of a correlation factor, which comprises the following steps:
s1, monitoring local vibration of a reed harvester structure in real time;
s2, determining a correlation factor of a vibration area;
s3, determining a relevance factor intermediate density value based on Weibull probability;
s4, determining a safety early warning value based on the damage intermediate probability density value;
s5, determining the damage degree based on the association factors.
Further, a three-dimensional model of the operation structure of the reed harvester is imported into finite element analysis software ANSYS, the three-dimensional model of the structure of the reed harvester is subjected to gridding division in an automatic grid mode, working condition loads are applied to a pretreatment module, then post-treatment results are solved, and the area where damage is most likely to occur to the structure under the conditions of maximum stress, strain value and Vonmase stress of the structure of the reed harvester is determined.
The method comprises the steps of structurally monitoring vibration quantity of a reed harvester determined to be a damaged area under actual working conditions, arranging 3 vibration sensors in the damaged area according to an equilateral triangle arrangement method, and collecting vibration quantity of an ith damaged area in real time to obtain vibration quantity A corresponding to each sensor ij (i is the number of the damaged area, j is the j-th sensor corresponding to the i-th area, j=1, 2, 3)
Further, the vibration quantity A corresponding to the time range from 0 to t is calculated in the MATLAB program ij Fitting the parameter function to obtain a 5-order limited vibration quantity A ij (t) the corresponding best defined function.
A ij (t)＝α 1 t 5 +α 2 t 4 +α 3 t 3 +α 4 t 2 +α 5 t+α 6
Wherein A is ij (t) is an optimal limiting function of the vibration quantity under 5-order limiting; t is time; alpha 1 ，α 2 ，α 3 ，α 4 ，α 5 ，α 6 The best fit coefficients for the 5 th order defined function.
Then, the vibration region correlation factor β for each region with respect to all damaged regions is substituted into the following formula i And (5) performing calculation.
Wherein A is ij (t) is an optimal limiting function of the vibration quantity under 5-order limiting; t is time; j is a j sensor corresponding to the i-th area; i is the number of the damaged area; n is the maximum value of the number of the damaged area; a is that i1 The interference interception coefficient corresponding to the sensor 1 in the ith area is obtained; a is that i2 The interference interception coefficient corresponding to a No. 2 sensor in the i-th area; a is that i3 The interference interception coefficient corresponding to a No. 3 sensor in the i-th area; c (A) i1 ，A i2 ，A i3 ) max Is A i1 ，A i2 ，A i3 The maximum of the three parameters.
Wherein A is i1 The interference interception coefficient corresponding to the sensor 1 in the ith area is obtained; t is time; j is a j sensor corresponding to the i-th area; a is that i1 (t) the optimal limiting function under 5-order limitation corresponding to the 1 st sensor of the i-th damaged area is obtained through MATLAB software fitting; a is that ij (t) is an optimal limiting function of the vibration quantity under 5 th order limitation.
Wherein A is i2 The interference interception coefficient corresponding to a No. 2 sensor in the i-th area; a is that i3 The interference interception coefficient corresponding to a No. 3 sensor in the i-th area; t is time; j is a j sensor corresponding to the i-th area; a is that i2 (t) the optimal limiting function under 5-order limitation corresponding to the 2 nd sensor of the i-th damaged area is obtained through MATLAB software fitting; a is that i3 (t) the optimal limiting function under 5-order limitation corresponding to the 3 rd sensor of the i-th damaged area is obtained through MATLAB software fitting; a is that ij (t) is an optimal limiting function of the vibration quantity under 5 th order limitation.
Further, the determination of the relevance factor intermediate density value based on Weibull probability:
the calculated vibration area correlation factor beta of each area relative to all damaged areas i Leading the obtained product into a MATLAB program to automatically fit an equation f (i) under the condition of a Weibull equation to obtain a Weibull equation mode of
Wherein f (i) is a correlation factor beta i Weibull equation model of (C); b 1 Shape parameters of Weibull equation; b 2 Size parameters of Weibull equation; b 3 Position parameters of Weibull equations; e is the number of fingers; i is the number of the damaged area.
Then f (i) is substituted into the intermediate density value Z of the relevance factor of the following formula to the ith damaged area i And (5) performing calculation.
Wherein f (i) is a relevance factor beta i Weibu of (A)A ll equation pattern; n is the maximum value of the number of the damaged area; i is the number of the damaged area; c [ f (i)] max For all relevance factors beta i Probability maxima in equation mode; c [ f (i)] min For all relevance factors beta i Probability minima in the equation mode; z is Z i Is the median density value of the relevance factor of the ith lesion area.
Further, determining a safety precaution value based on the damage intermediate probability density value:
determining a safety early warning value G of each sensor corresponding to the time t ij (t)。
Wherein G is ij (t) is a safety precaution value of each sensor corresponding to the time t; a is that ij (t) is an optimal limiting function of the vibration quantity under 5-order limiting; beta i A vibration region correlation factor for each region relative to all damaged regions; z is Z i Is the median density value of the relevance factor of the ith lesion area.
Further, based on the determination of the degree of damage of the correlation factor:
substituting the calculated data into the damage degree value D based on the correlation factor t And solving.
Wherein D is t Is a damage degree value based on the association factor; g ij (t) is a safety precaution value of each sensor corresponding to the time t; a is that ij (t) is an optimal limiting function of the vibration quantity under 5-order limiting; i is the number of the damaged area; j is a j sensor corresponding to the i-th area; n is the maximum value of the lesion field number.
The beneficial effects are that: vibration data of the reed harvester are collected by arranging the vibration sensors according to an equilateral triangle, real-time determination of the health state of the large reed harvester in the operation process can be achieved, related factors of the large reed harvester are determined in real time through monitored data signals, the middle probability density is determined through Weibull distribution, accordingly damage pre-warning threshold values are determined based on characteristic value fluctuation intervals, damage values under different relevance degrees are determined, and further the health state of the reed harvester is determined in real time.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
Detailed Description
As shown in fig. 1, the embodiment is based on a reed harvester operation safety evaluation method based on a fluctuation range of characteristic values of association factors, and the method comprises the following steps:
s1, monitoring local vibration of a reed harvester structure in real time:
the method comprises the steps of importing a three-dimensional model of a reed harvester operation structure into finite element analysis software ANSYS, meshing the three-dimensional model of the reed harvester structure by adopting an automatic grid mode, applying working condition load in a pretreatment module, then solving a post-treatment result, and determining the area of the reed harvester structure which is most easily damaged under the conditions of maximum stress and strain values and Vonmase stress.
The method comprises the steps of structurally monitoring vibration quantity of a reed harvester determined to be a damaged area under actual working conditions, arranging 3 vibration sensors in the damaged area according to an equilateral triangle arrangement method, and collecting vibration quantity of an ith damaged area in real time to obtain vibration quantity A corresponding to each sensor ij (i is the number of the damaged area, j is the j-th sensor corresponding to the i-th area, j=1, 2, 3)
S2, determining a vibration area relevance factor:
on the basis of S1, the vibration quantity A corresponding to the time range from 0 to t in the MATLAB program ij Fitting the parameter function to obtain a 5-order limited vibration quantity A ij (t) the corresponding best defined function.
A ij (t)＝α 1 t 5 +α 2 t 4 +α 3 t 3 +α 4 t 2 +α 5 t+α 6
Wherein A is ij (t) is an optimal limiting function of the vibration quantity under 5-order limiting; t is time; alpha 1 ，α 2 ，α 3 ，α 4 ，α 5 ，α 6 The best fit coefficients for the 5 th order defined function.
Then, the vibration region correlation factor β for each region with respect to all damaged regions is substituted into the following formula i And (5) performing calculation.
Wherein A is ij (t) is an optimal limiting function of the vibration quantity under 5-order limiting; t is time; j is a j sensor corresponding to the i-th area; i is the number of the damaged area; n is the maximum value of the number of the damaged area; a is that i1 The interference interception coefficient corresponding to the sensor 1 in the ith area is obtained; a is that i2 The interference interception coefficient corresponding to a No. 2 sensor in the i-th area; a is that i3 The interference interception coefficient corresponding to a No. 3 sensor in the i-th area; c (A) i1 ，A i2 ，A i3 ) max Is A i1 ，A i2 ，A i3 The maximum of the three parameters.
Wherein A is i1 The interference interception coefficient corresponding to the sensor 1 in the ith area is obtained; t is time; j is a j sensor corresponding to the i-th area; a is that i1 (t) the optimal limiting function under 5-order limitation corresponding to the 1 st sensor of the i-th damaged area is obtained through MATLAB software fitting; a is that ij (t) is an optimal limiting function of the vibration quantity under 5 th order limitation.
Wherein A is i2 The interference interception coefficient corresponding to a No. 2 sensor in the i-th area; a is that i3 The interference interception coefficient corresponding to a No. 3 sensor in the i-th area; t is time; j is a j sensor corresponding to the i-th area; a is that i2 (t) the optimal limiting function under 5-order limitation corresponding to the 2 nd sensor of the i-th damaged area is obtained through MATLAB software fitting; a is that i3 (t) the optimal limiting function under 5-order limitation corresponding to the 3 rd sensor of the i-th damaged area is obtained through MATLAB software fitting; a is that ij (t) is an optimal limiting function of the vibration quantity under 5 th order limitation.
S3, determining a relevance factor intermediate density value based on Weibull probability:
the vibration region correlation factor beta of each region calculated in the step S2 relative to all damaged regions i Leading the obtained product into a MATLAB program to automatically fit an equation f (i) under the condition of a Weibull equation to obtain a Weibull equation mode of
Wherein f (i) is a correlation factor beta i Weibull equation model of (C); b 1 Shape parameters of Weibull equation; b 2 Size parameters of Weibull equation; b 3 Position parameters of Weibull equations; e is the number of fingers; i is the number of the damaged area.
Then f (i) is substituted into the intermediate density value Z of the relevance factor of the following formula to the ith damaged area i And (5) performing calculation.
Wherein f (i) is the associationFactor beta i Weibull equation model of (C); n is the maximum value of the number of the damaged area; i is the number of the damaged area; c [ f (i)] max For all relevance factors beta i Probability maxima in equation mode; c [ f (i)] min For all relevance factors beta i Probability minima in the equation mode; z is Z i Is the median density value of the relevance factor of the ith lesion area.
S4, determining a safety early warning value based on the damage intermediate probability density value:
on the basis of S2-S3, determining a safety early warning value G of each sensor corresponding to the moment t ij (t)。
Wherein G is ij (t) is a safety precaution value of each sensor corresponding to the time t; a is that ij (t) is an optimal limiting function of the vibration quantity under 5-order limiting; beta i A vibration region correlation factor for each region relative to all damaged regions; z is Z i Is the median density value of the relevance factor of the ith lesion area.
S5, determining the damage degree based on the association factors:
substituting the data calculated in S1-S5 into the damage degree value D based on the correlation factor of the following formula t And solving.
Wherein D is t Is a damage degree value based on the association factor; g ij (t) is a safety precaution value of each sensor corresponding to the time t; a is that ij (t) is an optimal limiting function of the vibration quantity under 5-order limiting; i is the number of the damaged area; j is a j sensor corresponding to the i-th area; n is the maximum value of the lesion field number.
Claims (2)
1. A reed harvester safety evaluation method based on a correlation factor characteristic value fluctuation interval is characterized by comprising the following steps of: the method comprises the following steps:
s1, monitoring local vibration of a reed harvester structure in real time;
s2, determining a correlation factor of a vibration area;
s3, determining a relevance factor intermediate density value based on Weibull probability;
s4, determining a safety early warning value based on the damage intermediate probability density value;
s5, determining the damage degree based on the association factors,
the method for determining the correlation factor of the S2 vibration area is as follows:
on the basis of S1, the vibration quantity A corresponding to the time range from 0 to t in the MATLAB program ij Fitting the parameter function to obtain a 5-order limited vibration quantity A ij (t) the corresponding best defined function,
A ij (t)＝α 1 t 5 +α 2 t 4 +α 3 t 3 +α 4 t 2 +α 5 t+α 6
wherein A is ij (t) is an optimal limiting function of the vibration quantity under 5-order limiting; t is time; alpha 1 ，α 2 ，α 3 ，α 4 ，α 5 ，α 6 The best fit coefficients for the 5 th order defined function,
then, the vibration region correlation factor β for each region with respect to all damaged regions is substituted into the following formula i The calculation is performed such that,
wherein A is ij (t) is an optimal limiting function of the vibration quantity under 5-order limiting; t is time; j is a j sensor corresponding to the i-th area; i is the number of the damaged area; n is the maximum value of the number of the damaged area; a is that i1 The interference interception coefficient corresponding to the sensor 1 in the ith area is obtained; a is that i2 Is the ith numberThe interference interception coefficient corresponding to the No. 2 sensor of the area; a is that i3 The interference interception coefficient corresponding to a No. 3 sensor in the i-th area; c (A) i1 ，A i2 ，A i3 ) max Is A i1 ，A i2 ，A i3 The maximum value of the three parameters is,
wherein A is i1 The interference interception coefficient corresponding to the sensor 1 in the ith area is obtained; t is time; j is a j sensor corresponding to the i-th area; a is that i1 (t) the optimal limiting function under 5-order limitation corresponding to the 1 st sensor of the i-th damaged area is obtained through MATLAB software fitting; a is that ij (t) is an optimal limiting function of the vibration quantity under 5 th order limitation,
wherein A is i2 The interference interception coefficient corresponding to a No. 2 sensor in the i-th area; a is that i3 The interference interception coefficient corresponding to a No. 3 sensor in the i-th area; t is time; j is a j sensor corresponding to the i-th area; a is that i2 (t) the optimal limiting function under 5-order limitation corresponding to the 2 nd sensor of the i-th damaged area is obtained through MATLAB software fitting; a is that i3 (t) the optimal limiting function under 5-order limitation corresponding to the 3 rd sensor of the i-th damaged area is obtained through MATLAB software fitting; a is that ij (t) is an optimal limiting function of the vibration quantity under 5 th order limitation,
the method for determining the relevance factor intermediate density value based on Weibull probability in S3 is as follows:
calculated in S2Vibration region correlation factor beta for each region relative to all damaged regions i The equation f (i) under the condition of the Weibull equation is automatically fitted after being imported into a MATLAB program, so that the Weibull equation mode is obtained,
wherein f (i) is a correlation factor beta i Weibull equation model of (C); b 1 Shape parameters of Weibull equation; b 2 Size parameters of Weibull equation; b 3 Position parameters of Weibull equations; e is the number of fingers; i is the number of the damaged area,
then f (i) is substituted into the intermediate density value Z of the relevance factor of the following formula to the ith damaged area i The calculation is performed such that,
wherein f (i) is a relevance factor beta i Weibull equation model of (C); n is the maximum value of the number of the damaged area; i is the number of the damaged area; c [ f (i)] max For all relevance factors beta i Probability maxima in equation mode; c [ f (i)] min For all relevance factors beta i Probability minima in the equation mode; z is Z i An intermediate density value of the relevance factor for the ith lesion field,
and S4, a method for determining the safety early warning value based on the damage intermediate probability density value comprises the following steps:
on the basis of S2-S3, determining a safety early warning value G of each sensor corresponding to the moment t ij (t)，
Wherein G is ij (t) safety precaution for each sensor corresponding to time tA value; a is that ij (t) is an optimal limiting function of the vibration quantity under 5-order limiting; beta i A vibration region correlation factor for each region relative to all damaged regions; z is Z i An intermediate density value of the relevance factor for the ith lesion field,
the method for determining the damage degree based on the association factor in the S5 is as follows:
substituting the data calculated in S1-S5 into the damage degree value D based on the correlation factor of the following formula t The solution is carried out so that,
wherein D is t Is a damage degree value based on the association factor; g ij (t) is a safety precaution value of each sensor corresponding to the time t; a is that ij (t) is an optimal limiting function of the vibration quantity under 5-order limiting; i is the number of the damaged area; j is a j sensor corresponding to the i-th area; n is the maximum value of the lesion field number.
2. The reed harvester safety evaluation method based on the association factor characteristic value fluctuation interval as set forth in claim 1, wherein: the real-time monitoring method for the local vibration of the reed harvester structure in the S1 is as follows:
introducing a three-dimensional model of a reed harvester operation structure into finite element analysis software ANSYS, meshing the three-dimensional model of the reed harvester structure by adopting an automatic mesh mode, applying working condition load in a pretreatment module, then solving a post-treatment result, determining the area of the reed harvester structure which is most easily damaged under the conditions of maximum stress and strain values and Vonmase stress,
the method comprises the steps of structurally monitoring vibration quantity of a reed harvester determined to be a damaged area under actual working conditions, arranging 3 vibration sensors in each damaged area according to an equilateral triangle arrangement method in the area, and collecting vibration quantity of an ith damaged area in real time to obtain corresponding vibration quantity of each sensorVibration quantity A ij (i is the number of the damaged area, j is the j-th sensor corresponding to the i-th area, j=1, 2, 3).
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