CN111142496A - Temperature rise calculation method for transition process of double-frequency quenching machining - Google Patents

Temperature rise calculation method for transition process of double-frequency quenching machining Download PDF

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CN111142496A
CN111142496A CN201811298294.5A CN201811298294A CN111142496A CN 111142496 A CN111142496 A CN 111142496A CN 201811298294 A CN201811298294 A CN 201811298294A CN 111142496 A CN111142496 A CN 111142496A
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immersed pump
working condition
pressure
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matrix
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吴雨川
周国鹏
钮雨欢
段建民
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Wuhan Textile University
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0259—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
    • G05B23/0262—Confirmation of fault detection, e.g. extra checks to confirm that a failure has indeed occurred
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
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Abstract

A temperature rise calculation method for a transition process of double-frequency quenching machining comprises the following steps: data acquisition and storage, data processing and analysis and data diagnosis and alarm. The design adopts a multi-metadata analysis method to accurately reflect the fault information in the system, and analyzes the coupling of a plurality of variables in the system to form a new comprehensive index, and the new index can comprehensively reflect the faults of the original system. The design can accurately reflect the fault type of the immersed pump, effectively improve the reliability of the immersed pump system, and has wide application range and low manufacturing and operating cost.

Description

Temperature rise calculation method for transition process of double-frequency quenching machining
Technical Field
The invention relates to a temperature rise calculation method in a transition process of double-frequency quenching machining, which is particularly suitable for calculating quenching temperature.
Background
The FPSO platform or the oil tanker immersed cargo oil loading and unloading system equipment is still blank at home nowadays, the power source of the immersed pump is hydraulic drive, and the importance of the hydraulic drive system is self-evident, so that the reliability and the safety of the hydraulic system are key factors for the safety and the reliability of the system. In order to ensure the reliability and the safety of the immersed pump, the adoption of a fault detection technology suitable for the working condition of the immersed pump system has great significance.
Some important faults of the immersed pump system cannot be detected through the sensors or the detection cost and the construction cost of the immersed pump system are too high through the sensors, the faults can be indirectly reflected through the information of a plurality of sensor sampling points through the collection and analysis of the faults and the sensors, and thus the analysis of the sensor sampling data is the key point of fault detection.
In order to accurately reflect the fault information in the system, a multivariate data analysis method is adopted, the coupling of a plurality of variables in the system is analyzed, a new comprehensive index is formed, and the new index can comprehensively reflect the faults of the original system.
Disclosure of Invention
The invention aims to solve the problem that the fault cannot be detected through a sensor or the detection cost is high through the sensor in the prior art, and provides a temperature rise calculation method for a double-frequency quenching machining transition process, which utilizes a low-cost sensor to detect.
In order to achieve the above purpose, the technical solution of the invention is as follows:
a temperature rise calculation method for a transition process of double-frequency quenching machining comprises the following steps: data acquisition and storage, data processing and analysis, and data diagnosis and alarm:
step one, data acquisition and storage: the method comprises the following steps of collecting state parameters of running current of a main pump motor, pressure of a hydraulic system, outlet pressure of the immersed pump, outlet flow of the immersed pump, temperature of the hydraulic system and STC valve pressure by using a sensor on the immersed pump, then transmitting the six state parameters to a quantification device in real time for quantification, finally transmitting the quantified parameters to a storage device and a diagnosis device respectively, and storing collected data by the storage device for later calling;
and step two, data processing and analysis: the diagnostic device establishes a sample matrix for n pieces of collected observation data of the main pump motor running current, the hydraulic system pressure, the immersed pump outlet flow, the hydraulic system temperature and the STC valve pressure, and obtains a time change curve of a square prediction error SPE by using a multivariate data analysis method;
thirdly, data diagnosis and alarm: and step jumping occurs on the SPE curve in the operation process of the immersed pump system, and the SPE value exceeds a threshold value 118 in normal operation of the system, so that the operation of the immersed pump system has a fault: when the SPE curve jumps within the range of 200 +/-30, diagnosing the leakage fault of the hydraulic pipeline; when the SPE curve jumps within the range of 220 +/-20, the fault of the condensing system is diagnosed to occur; when an SPE curve jumps within a range of 150 +/-25, cargo oil pipeline leakage or concentric pipeline failure is possible to occur, historical data in a storage device is called, STC valve pressure, immersed pump outlet pressure and immersed pump outlet flow under a failure working condition are compared with STC valve pressure, immersed pump outlet pressure and immersed pump outlet flow under a normal working condition, and when the STC valve pressure under the failure working condition is the same as that under the normal working condition, if the difference value between the immersed pump outlet flow under the normal working condition and the immersed pump outlet flow under the failure working condition is greater than 25 cubic meters, concentric pipeline leakage of the system is diagnosed; when the outlet pressure of the immersed pump under the fault working condition is the same as that under the normal working condition, if the difference value between the outlet flow of the immersed pump under the normal working condition and the outlet flow of the immersed pump under the fault working condition is more than 30 cubic meters, the occurrence of the cargo oil pipeline leakage is diagnosed; when the SPE curve jumps within the range of 180 +/-35, STC valve failure or cavitation of the immersed pump is possible, historical data in the storage device is called, the hydraulic system pressure, the STC valve pressure and the main pump motor running current under the failure working condition are compared with the hydraulic system pressure, the STC valve pressure and the main pump motor running current under the normal working condition, and when the hydraulic system pressure under the failure working condition is the same as that under the normal working condition, if the difference value between the STC valve pressure under the normal working condition and the STC valve pressure under the failure working condition is greater than 0.5MPa, the system STC valve failure is diagnosed; when the pressure of the hydraulic system under the fault working condition is the same as that of the hydraulic system under the normal working condition, if the difference value between the running current of the main pump motor under the normal working condition and the running current of the main pump motor under the fault working condition is larger than 15A, the immersed pump is diagnosed to generate cavitation; when the change condition of the SPE curve or the collected parameter change conditions of the main pump motor running current, the hydraulic system pressure, the immersed pump outlet flow, the hydraulic system temperature and the STC valve pressure cannot meet the judgment conditions of the six fault types, judging the fault as a comprehensive fault;
and finally, outputting the analysis result to an external execution device, and after receiving the instruction, the execution device gives an alarm and displays an alarm state on a monitoring interface of the upper computer.
And in the second step, data processing and analysis:
establishing a 6 x n matrix as a sample matrix according to n observation data of the collected main pump motor running current, the pressure of a hydraulic system, the outlet pressure of an immersed pump, the outlet flow of the immersed pump, the temperature of the hydraulic system and the STC valve pressure, namely:
Figure BDA0001851666320000031
the processing procedure of the multivariate data analysis method comprises the following steps:
first, the matrix X can be decomposed as the sum of the outer products of 6 vectors, i.e.:
Figure BDA0001851666320000032
score vector t in the above equationi∈RnLoad vector pi∈R6Thus, matrix X can be modeled as: x is TPT(ii) a Wherein the score matrix T ═ T1t2t3t4t5t6]The load matrix P ═ P1p2p3p4p5p6]The vectors of the matrix T and the matrix P are orthogonal pairwise, and the length of each vector of the load matrix P is 1, that is:
Figure BDA0001851666320000033
Figure BDA0001851666320000034
the compound represented by the formula (1.1) can be obtained: t is ti＝Xpi
Then extracting a covariance matrix S of the sample matrix X
Figure BDA0001851666320000035
Wherein X is a matrix after the sample matrix is normalized; corresponding to formula (1.2) are obtained
P＝V (1.4)
Figure BDA0001851666320000036
From this, it follows thatiIs the sample variance of the ith principal element;
then, eigenvalue decomposition of the covariance matrix S
S＝VΛVT(1.6)
Where Λ is a diagonal matrix of the covariance matrix S, containing non-negative real eigenvalues of decreasing amplitude (λ)1＞λ2＞λ3＞λ4＞λ5＞λ6) V is an orthogonal array (V)TV ═ I, where I is the unit matrix), is the unitized eigenvector corresponding to eigenvalue λ;
substituting formulae (1.4) and (1.5) into (1.6) can yield:
Figure BDA0001851666320000041
finally, a score matrix T is solved:
T＝XP
for a new sample capacity x ∈ R6×1Then the score, estimate and residual vectors for this new vector are:
and (3) scoring vector: t ═ PTx, estimated vector:
Figure BDA0001851666320000042
residual vector: e ═ I (I-PP)T)x
The squared prediction error SPE is:
SPE＝eTe＝xT(I-PPT)x
the upper limit control of SPE is:
Figure BDA0001851666320000043
wherein c isαIs a standard normal deviation, h, corresponding to an upper limit of (1- α). times.100%0＝1-2θ1θ3/(3θ2 2)，
Figure BDA0001851666320000044
And lambdajIs the eigenvalue associated with the jth load vector of the data covariance;
and in the system operation process, the main pump motor operation current, the hydraulic system pressure, the immersed pump outlet flow, the hydraulic system temperature and the STC valve pressure data collected at the same time can all obtain an SPE value, and the SPE value is used for drawing a time change curve of the square prediction error SPE according to the time sequence.
Compared with the prior art, the invention has the beneficial effects that:
1. in the method for calculating the temperature rise in the transition process of the double-frequency quenching machining, the basic sensor on the hydraulic immersed pump is adopted to measure the parameters of the main pump motor running current, the hydraulic system pressure, the immersed pump outlet flow, the hydraulic system temperature and the STC valve pressure, and then the immersed pump fault is detected by using a multivariate data analysis method. Therefore, the invention has the advantages of accurate fault diagnosis, wide application range and low manufacturing and operating cost.
2. According to the multi-element data analysis method in the double-frequency quenching machining transition process temperature rise calculation method, a mathematical model is established by using each parameter of the hydraulic immersed pump, a time change curve of a square prediction error SPE is obtained, and whether the immersed pump has a fault or not and the fault type of the immersed pump are judged according to the change of the square prediction error SPE curve, so that detection personnel can find the fault of the immersed pump more quickly, and the operation safety and reliability of the immersed pump are improved. Therefore, the invention can accurately detect the fault and improve the safety and reliability of the operation of the immersed pump.
Drawings
Fig. 1 is a diagram of a fault diagnosis structure of the present invention.
FIG. 2 is a SPE time plot of a hydraulic line leak fault.
FIG. 3 is a SPE time graph of a condensing system failure.
FIG. 4 is a SPE time plot of a concentric pipe leak fault.
FIG. 5 is a SPE time plot of a cargo line leak fault.
Figure 6 is a SPE time plot of system STC valve failure.
FIG. 7 is a SPE time graph of cavitation failure of the submersible pump.
Fig. 8 is a schematic structural view of a hydraulic submersible pump.
Detailed Description
The present invention will be described in further detail with reference to the following description and embodiments in conjunction with the accompanying drawings.
Referring to fig. 1 to 8, a temperature rise calculation method in a transition process of double-frequency quenching machining includes: data acquisition and storage, data processing and analysis, and data diagnosis and alarm:
step one, data acquisition and storage: the method comprises the following steps of collecting state parameters of running current of a main pump motor, pressure of a hydraulic system, outlet pressure of the immersed pump, outlet flow of the immersed pump, temperature of the hydraulic system and STC valve pressure by using a sensor on the immersed pump, then transmitting the six state parameters to a quantification device in real time for quantification, finally transmitting the quantified parameters to a storage device and a diagnosis device respectively, and storing collected data by the storage device for later calling;
and step two, data processing and analysis: the diagnostic device establishes a sample matrix for n pieces of collected observation data of the main pump motor running current, the hydraulic system pressure, the immersed pump outlet flow, the hydraulic system temperature and the STC valve pressure, and obtains a time change curve of a square prediction error SPE by using a multivariate data analysis method;
thirdly, data diagnosis and alarm: and step jumping occurs on the SPE curve in the operation process of the immersed pump system, and the SPE value exceeds a threshold value 118 in normal operation of the system, so that the operation of the immersed pump system has a fault: when the SPE curve jumps within the range of 200 +/-30, diagnosing the leakage fault of the hydraulic pipeline; when the SPE curve jumps within the range of 220 +/-20, the fault of the condensing system is diagnosed to occur; when an SPE curve jumps within a range of 150 +/-25, cargo oil pipeline leakage or concentric pipeline failure is possible to occur, historical data in a storage device is called, STC valve pressure, immersed pump outlet pressure and immersed pump outlet flow under a failure working condition are compared with STC valve pressure, immersed pump outlet pressure and immersed pump outlet flow under a normal working condition, and when the STC valve pressure under the failure working condition is the same as that under the normal working condition, if the difference value between the immersed pump outlet flow under the normal working condition and the immersed pump outlet flow under the failure working condition is greater than 25 cubic meters, concentric pipeline leakage of the system is diagnosed; when the outlet pressure of the immersed pump under the fault working condition is the same as that under the normal working condition, if the difference value between the outlet flow of the immersed pump under the normal working condition and the outlet flow of the immersed pump under the fault working condition is more than 30 cubic meters, the occurrence of the cargo oil pipeline leakage is diagnosed; when the SPE curve jumps within the range of 180 +/-35, STC valve failure or cavitation of the immersed pump is possible, historical data in the storage device is called, the hydraulic system pressure, the STC valve pressure and the main pump motor running current under the failure working condition are compared with the hydraulic system pressure, the STC valve pressure and the main pump motor running current under the normal working condition, and when the hydraulic system pressure under the failure working condition is the same as that under the normal working condition, if the difference value between the STC valve pressure under the normal working condition and the STC valve pressure under the failure working condition is greater than 0.5MPa, the system STC valve failure is diagnosed; when the pressure of the hydraulic system under the fault working condition is the same as that of the hydraulic system under the normal working condition, if the difference value between the running current of the main pump motor under the normal working condition and the running current of the main pump motor under the fault working condition is larger than 15A, the immersed pump is diagnosed to generate cavitation; when the change condition of the SPE curve or the collected parameter change conditions of the main pump motor running current, the hydraulic system pressure, the immersed pump outlet flow, the hydraulic system temperature and the STC valve pressure cannot meet the judgment conditions of the six fault types, judging the fault as a comprehensive fault;
and finally, outputting the analysis result to an external execution device, and after receiving the instruction, the execution device gives an alarm and displays an alarm state on a monitoring interface of the upper computer.
And in the second step, data processing and analysis:
establishing a 6 x n matrix as a sample matrix according to n observation data of the collected main pump motor running current, the pressure of a hydraulic system, the outlet pressure of an immersed pump, the outlet flow of the immersed pump, the temperature of the hydraulic system and the STC valve pressure, namely:
Figure BDA0001851666320000061
the processing procedure of the multivariate data analysis method comprises the following steps:
first, the matrix X can be decomposed as the sum of the outer products of 6 vectors, i.e.:
Figure BDA0001851666320000062
score vector t in the above equationi∈RnLoad vector pi∈R6Thus, matrix X can be modeled as: x is TPT(ii) a Wherein the score matrix T ═ T1t2t3t4t5t6]The load matrix P ═ P1p2p3p4p5p6]The vectors of the matrix T and the matrix P are orthogonal pairwise, and the length of each vector of the load matrix P is 1, that is:
Figure BDA0001851666320000071
Figure BDA0001851666320000072
the compound represented by the formula (1.1) can be obtained: t is ti＝Xpi
Then extracting a covariance matrix S of the sample matrix X
Figure BDA0001851666320000073
Wherein X is a matrix after the sample matrix is normalized; corresponding to formula (1.2) are obtained
P＝V (1.4)
Figure BDA0001851666320000074
From this, it follows thatiIs the sample variance of the ith principal element;
then, eigenvalue decomposition of the covariance matrix S
S＝VΛVT(1.6)
Where Λ is a diagonal matrix of the covariance matrix S, containing non-negative real eigenvalues of decreasing amplitude (λ)1＞λ2＞λ3＞λ4＞λ5＞λ6) V is an orthogonal array (V)TV ═ I, where I is the unit matrix), is the unitized eigenvector corresponding to eigenvalue λ;
substituting formulae (1.4) and (1.5) into (1.6) can yield:
Figure BDA0001851666320000075
finally, a score matrix T is solved:
T＝XP
for a new sample capacity x ∈ R6×1Then the score, estimate and residual vectors for this new vector are:
and (3) scoring vector: t ═ PTx, estimated vector:
Figure BDA0001851666320000076
residual vector: e ═ I (I-PP)T)x
The squared prediction error SPE is:
SPE＝eTe＝xT(I-PPT)x
upper bound control of SPEComprises the following steps:
Figure BDA0001851666320000077
wherein c isαIs a standard normal deviation, h, corresponding to an upper limit of (1- α). times.100%0＝1-2θ1θ3/(3θ2 2)，
Figure BDA0001851666320000081
And lambdajIs the eigenvalue associated with the jth load vector of the data covariance;
and in the system operation process, the main pump motor operation current, the hydraulic system pressure, the immersed pump outlet flow, the hydraulic system temperature and the STC valve pressure data collected at the same time can all obtain an SPE value, and the SPE value is used for drawing a time change curve of the square prediction error SPE according to the time sequence.
The principle of the invention is illustrated as follows:
in the design, the six parameters of the running current of the main pump motor, the pressure of the hydraulic system, the outlet pressure of the immersed pump, the outlet flow of the immersed pump, the temperature of the hydraulic system and the STC valve pressure are conventional measurement parameters of the hydraulic immersed pump system, and the parameters are obtained without additionally arranging a sensor for measurement.
The running current of a main pump motor is as follows: the operation current of the main pump motor changes along with the load change of the hydraulic system, and under the normal working condition of the system, the load is increased, and the current of the motor is increased.
Pressure of a hydraulic system: the pressure of the hydraulic system reflects the pressure of an oil pipe of the STC valve, and under the normal working condition of the system, the larger the system pressure is, the larger the pressure of the oil pipe of the STC valve is, the larger the valve opening is, and the rotating speed of the immersed pump is increased.
Outlet pressure of the immersed pump: the outlet pressure of the immersed pump influences the lift of the immersed pump, the lift of the immersed pump is reflected, and under the normal working condition of the system, the outlet pressure of the immersed pump is increased, the lift of the immersed pump is increased, and the efficiency of the immersed pump is increased.
Outlet flow of the immersed pump: the output flow of the immersed pump reflects the output power of the immersed pump, and under the normal working condition of the system, the output flow of the immersed pump is increased, and the output power of the immersed pump is increased.
Temperature of the hydraulic system: the temperature of the hydraulic system influences the viscosity of hydraulic oil, the oil temperature of the hydraulic oil rises, the viscosity is reduced, the flow of the hydraulic system is increased, and when the oil temperature rises to 65 ℃, the hydraulic system is a shutdown alarm limit value.
STC valve pressure: the pressure of the STC valve reflects the load of the hydraulic system, the rotating speed of the immersed pump is influenced, under the normal working condition of the system, the pressure of the STC valve is increased, the rotating speed of the immersed pump is increased, the system load is increased, and the current of a motor of a main pump is increased.
For the double pump immersed pump system aimed at by the invention, the faults occurring in the system operation process can be mainly divided into 6 types: a hydraulic line leak failure; a cargo oil pipeline leakage fault; a condensing system failure; STC valve failure; a concentric pipeline fault of the immersed pump; cavitation failure of the immersed pump.
Hydraulic line leakage failure: the hydraulic pressure pipeline takes place the oil leak and can exert an influence to hydraulic tank's liquid level, and when the oil leak volume was more, the oil tank liquid level can take place to show the decline, and nevertheless when revealing the volume less, general oil tank liquid level can not in time change, wants to detect the small change of oil tank liquid level, then needs to increase the higher level sensor of sensitivity, has increased hydraulic system's cost.
Leakage fault of the cargo oil pipeline: the freight oil pipeline has leakage points, and when leakage occurs, the inlet flow and the outlet flow of the freight oil pipeline are different. In order to detect the fault, a flowmeter is respectively arranged at the inlet and the outlet of the cargo pipeline, and the fault is judged by monitoring the difference of the flowmeters. Firstly this method increases costs and secondly the installation of the flow meter is inconvenient because the cargo oil inlet of the immersed pump is flooded with oil.
Failure of the condensing system: the possible reasons for the failure of the condensing system are that the electromagnetic valve fails and is not opened after being electrified, or condensed water is not supplied. After the condensing system is in fault, the temperature of the oil temperature of the hydraulic system is increased rapidly. The temperature sensor for monitoring the oil temperature of the hydraulic system cannot detect the change of the temperature rise rate and cannot find faults in time.
STC valve failure: the STC valve controls the load of the hydraulic system and influences the rotation of the immersed pump. When the STC valve fails, the pressure of the hydraulic system reaches the opening value of the STC valve, but the valve is not opened, the load pressure of the STC valve is 0MPa, namely no hydraulic oil acts on the immersed pump, and the rotating speed of the immersed pump is 0 RPM. Monitoring for such failures can be accomplished by installing a valve position sensor on the STC valve, but this will increase the failure rate and cost of the system. Because the oil pressure at the STC valve is high, one more sensor is installed, and one more leakage point is possible. When the system runs for a long time, an oil leakage accident may occur from the sensor installation position.
The concentric pipeline of the immersed pump has faults: the immersed pump concentric pipeline fault means that an inlet oil pipe and an outlet oil pipe of a concentric pipe of the immersed pump are communicated, so that hydraulic oil can flow from the inlet oil pipe to the outlet oil pipeline without passing through a hydraulic motor, and the immersed pump cannot rotate; or part of oil directly returns to the outlet oil pipeline without passing through the hydraulic motor, and the rotating speed of the immersed pump has larger deviation from the designed value. The detection of such a fault is not directly measurable by the sensor.
Cavitation failure of immersed pump: when the immersed pump has cavitation failure, the rotating speed of the immersed pump cannot be changed, the outlet flow of the immersed pump can be changed, however, the factors influencing the outlet flow of the immersed pump are more, and whether the immersed pump has cavitation or not can not be judged through the outlet flow change. In addition, no sensor can directly detect the cavitation fault of the immersed pump, and once the cavitation duration is long, the immersed pump can be damaged greatly.
Through the analysis of the reasons, the influences and the solutions for the faults of the immersed pump system, the faults of the immersed pump system can be timely and accurately monitored, if a common monitoring means of adding a measuring sensor is adopted, the cost of the immersed pump system is increased, the fault rate can be increased, and even some faults can not be directly measured through the sensor. According to the design, collected data of the immersed pump system are processed through a multivariate data analysis method to obtain the Square Prediction Error (SPE) of the system, and whether the system breaks down or not can be judged, so that the safety and reliability of the system are guaranteed.
In addition, if the change condition of the SPE curve or the collected parameter change conditions of the main pump motor running current, the hydraulic system pressure, the immersed pump outlet flow, the hydraulic system temperature and the STC valve pressure cannot meet the determination conditions of the six fault types, it is determined that a comprehensive fault occurs in the hydraulic immersed pump system, that is, a fault caused by simultaneous occurrence of two or more of the six faults.
Example 1:
referring to fig. 1 to 8, a temperature rise calculation method in a transition process of double-frequency quenching processing includes: data acquisition and storage, data processing and analysis, and data diagnosis and alarm:
step one, data acquisition and storage: the method comprises the following steps of collecting state parameters of running current of a main pump motor, pressure of a hydraulic system, outlet pressure of the immersed pump, outlet flow of the immersed pump, temperature of the hydraulic system and STC valve pressure by using a sensor on the immersed pump, then transmitting the six state parameters to a quantification device in real time for quantification, finally transmitting the quantified parameters to a storage device and a diagnosis device respectively, and storing collected data by the storage device for later calling;
and step two, data processing and analysis: the diagnostic device establishes a sample matrix for n observation data of the collected main pump motor running current, the pressure of a hydraulic system, the outlet pressure of an immersed pump, the outlet flow of the immersed pump, the temperature of the hydraulic system and the STC valve pressure, and obtains a time change curve of a square prediction error SPE by using a multivariate data analysis method:
establishing a 6 x n matrix as a sample matrix according to n observation data of the collected main pump motor running current, the pressure of a hydraulic system, the outlet pressure of an immersed pump, the outlet flow of the immersed pump, the temperature of the hydraulic system and the STC valve pressure, namely:
Figure BDA0001851666320000101
the processing procedure of the multivariate data analysis method comprises the following steps:
first, the matrix X can be decomposed as the sum of the outer products of 6 vectors, i.e.:
Figure BDA0001851666320000102
score vector t in the above equationi∈RnLoad vector pi∈R6Thus, matrix X can be modeled as: x is TPT(ii) a Wherein the score matrix T ═ T1t2t3t4t5t6]The load matrix P ═ P1p2p3p4p5p6]The vectors of the matrix T and the matrix P are orthogonal pairwise, and the length of each vector of the load matrix P is 1, that is:
Figure BDA0001851666320000103
Figure BDA0001851666320000104
the compound represented by the formula (1.1) can be obtained: t is ti＝Xpi
Then extracting a covariance matrix S of the sample matrix X
Figure BDA0001851666320000111
Wherein X is a matrix after the sample matrix is normalized; corresponding to formula (1.2) are obtained
P＝V (1.4)
Figure BDA0001851666320000112
From this, it follows thatiIs the sample variance of the ith principal element;
then, eigenvalue decomposition of the covariance matrix S
S＝VΛVT(1.6)
Where Λ is the diagonal matrix of the covariance matrix SIncluding non-negative real eigenvalues (λ) of decreasing amplitude1＞λ2＞λ3＞λ4＞λ5＞λ6) V is an orthogonal array (V)TV ═ I, where I is the unit matrix), is the unitized eigenvector corresponding to eigenvalue λ;
substituting formulae (1.4) and (1.5) into (1.6) can yield:
Figure BDA0001851666320000113
finally, a score matrix T is solved:
T＝XP
for a new sample capacity x ∈ R6×1Then the score, estimate and residual vectors for this new vector are:
and (3) scoring vector: t ═ PTx, estimated vector:
Figure BDA0001851666320000114
residual vector: e ═ I (I-PP)T)x
The squared prediction error SPE is:
SPE＝eTe＝xT(I-PPT)x
the upper limit control of SPE is:
Figure BDA0001851666320000115
wherein c isαIs a standard normal deviation, h, corresponding to an upper limit of (1- α). times.100%0＝1-2θ1θ3/(3θ2 2)，
Figure BDA0001851666320000116
And lambdajIs the eigenvalue associated with the jth load vector of the data covariance;
and in the system operation process, the main pump motor operation current, the hydraulic system pressure, the immersed pump outlet flow, the hydraulic system temperature and the STC valve pressure data collected at the same time can all obtain an SPE value, and the SPE value is used for drawing a time change curve of the square prediction error SPE according to the time sequence.
Thirdly, data diagnosis and alarm: and step jumping occurs on the SPE curve in the operation process of the immersed pump system, and the SPE value exceeds a threshold value 118 in normal operation of the system, so that the operation of the immersed pump system has a fault: when the SPE curve jumps within the range of 200 +/-30, diagnosing the leakage fault of the hydraulic pipeline; when the SPE curve jumps within the range of 220 +/-20, the fault of the condensing system is diagnosed to occur; when an SPE curve jumps within a range of 150 +/-25, cargo oil pipeline leakage or concentric pipeline failure is possible to occur, historical data in a storage device is called, STC valve pressure, immersed pump outlet pressure and immersed pump outlet flow under a failure working condition are compared with STC valve pressure, immersed pump outlet pressure and immersed pump outlet flow under a normal working condition, and when the STC valve pressure under the failure working condition is the same as that under the normal working condition, if the difference value between the immersed pump outlet flow under the normal working condition and the immersed pump outlet flow under the failure working condition is greater than 25 cubic meters, concentric pipeline leakage of the system is diagnosed; when the outlet pressure of the immersed pump under the fault working condition is the same as that under the normal working condition, if the difference value between the outlet flow of the immersed pump under the normal working condition and the outlet flow of the immersed pump under the fault working condition is more than 30 cubic meters, the occurrence of the cargo oil pipeline leakage is diagnosed; when the SPE curve jumps within the range of 180 +/-35, STC valve failure or cavitation of the immersed pump is possible, historical data in the storage device is called, the hydraulic system pressure, the STC valve pressure and the main pump motor running current under the failure working condition are compared with the hydraulic system pressure, the STC valve pressure and the main pump motor running current under the normal working condition, and when the hydraulic system pressure under the failure working condition is the same as that under the normal working condition, if the difference value between the STC valve pressure under the normal working condition and the STC valve pressure under the failure working condition is greater than 0.5MPa, the system STC valve failure is diagnosed; when the pressure of the hydraulic system under the fault working condition is the same as that of the hydraulic system under the normal working condition, if the difference value between the running current of the main pump motor under the normal working condition and the running current of the main pump motor under the fault working condition is larger than 15A, the immersed pump is diagnosed to generate cavitation; when the change condition of the SPE curve or the collected parameter change conditions of the main pump motor running current, the hydraulic system pressure, the immersed pump outlet flow, the hydraulic system temperature and the STC valve pressure cannot meet the judgment conditions of the six fault types, judging the fault as a comprehensive fault; and finally, outputting the analysis result to an external execution device, and after receiving the instruction, the execution device gives an alarm and displays an alarm state on a monitoring interface of the upper computer.

Claims (2)

1. A temperature rise calculation method in a transition process of double-frequency quenching machining is characterized by comprising the following steps: the method comprises the following steps: data acquisition and storage, data processing and analysis, and data diagnosis and alarm:
step one, data acquisition and storage: the method comprises the following steps of collecting state parameters of running current of a main pump motor, pressure of a hydraulic system, outlet pressure of the immersed pump, outlet flow of the immersed pump, temperature of the hydraulic system and STC valve pressure by using a sensor on the immersed pump, then transmitting the six state parameters to a quantification device in real time for quantification, finally transmitting the quantified parameters to a storage device and a diagnosis device respectively, and storing collected data by the storage device for later calling;
and step two, data processing and analysis: the diagnostic device establishes a sample matrix for n pieces of collected observation data of the main pump motor running current, the hydraulic system pressure, the immersed pump outlet flow, the hydraulic system temperature and the STC valve pressure, and obtains a time change curve of a square prediction error SPE by using a multivariate data analysis method;
thirdly, data diagnosis and alarm: and step jumping occurs on the SPE curve in the operation process of the immersed pump system, and the SPE value exceeds a threshold value 118 in normal operation of the system, so that the operation of the immersed pump system has a fault: when the SPE curve jumps within the range of 200 +/-30, diagnosing the leakage fault of the hydraulic pipeline; when the SPE curve jumps within the range of 220 +/-20, the fault of the condensing system is diagnosed to occur; when an SPE curve jumps within a range of 150 +/-25, cargo oil pipeline leakage or concentric pipeline failure is possible to occur, historical data in a storage device is called, STC valve pressure, immersed pump outlet pressure and immersed pump outlet flow under a failure working condition are compared with STC valve pressure, immersed pump outlet pressure and immersed pump outlet flow under a normal working condition, and when the STC valve pressure under the failure working condition is the same as that under the normal working condition, if the difference value between the immersed pump outlet flow under the normal working condition and the immersed pump outlet flow under the failure working condition is greater than 25 cubic meters, concentric pipeline leakage of the system is diagnosed; when the outlet pressure of the immersed pump under the fault working condition is the same as that under the normal working condition, if the difference value between the outlet flow of the immersed pump under the normal working condition and the outlet flow of the immersed pump under the fault working condition is more than 30 cubic meters, the occurrence of the cargo oil pipeline leakage is diagnosed; when the SPE curve jumps within the range of 180 +/-35, STC valve failure or cavitation of the immersed pump is possible, historical data in the storage device is called, the hydraulic system pressure, the STC valve pressure and the main pump motor running current under the failure working condition are compared with the hydraulic system pressure, the STC valve pressure and the main pump motor running current under the normal working condition, and when the hydraulic system pressure under the failure working condition is the same as that under the normal working condition, if the difference value between the STC valve pressure under the normal working condition and the STC valve pressure under the failure working condition is greater than 0.5MPa, the system STC valve failure is diagnosed; when the pressure of the hydraulic system under the fault working condition is the same as that of the hydraulic system under the normal working condition, if the difference value between the running current of the main pump motor under the normal working condition and the running current of the main pump motor under the fault working condition is larger than 15A, the immersed pump is diagnosed to generate cavitation; when the change condition of the SPE curve or the collected parameter change conditions of the main pump motor running current, the hydraulic system pressure, the immersed pump outlet flow, the hydraulic system temperature and the STC valve pressure cannot meet the judgment conditions of the six fault types, judging the fault as a comprehensive fault;
and finally, outputting the analysis result to an external execution device, and after receiving the instruction, the execution device gives an alarm and displays an alarm state on a monitoring interface of the upper computer.
2. The temperature rise calculation method for the transition process of the double-frequency quenching machining, according to claim 1, is characterized in that:
and in the second step, data processing and analysis:
establishing a 6 x n matrix as a sample matrix according to n observation data of the collected main pump motor running current, the pressure of a hydraulic system, the outlet pressure of an immersed pump, the outlet flow of the immersed pump, the temperature of the hydraulic system and the STC valve pressure, namely:
Figure FDA0001851666310000021
the processing procedure of the multivariate data analysis method comprises the following steps:
first, the matrix X can be decomposed as the sum of the outer products of 6 vectors, i.e.:
Figure FDA0001851666310000022
score vector t in the above equationi∈RnLoad vector pi∈R6Thus, matrix X can be modeled as: x is TPT(ii) a Wherein the score matrix T ═ T1t2t3t4t5t6]The load matrix P ═ P1p2p3p4p5p6]The vectors of the matrix T and the matrix P are orthogonal pairwise, and the length of each vector of the load matrix P is 1, that is:
Figure FDA0001851666310000023
Figure FDA0001851666310000024
the compound represented by the formula (1.1) can be obtained: t is ti＝Xpi
Then extracting a covariance matrix S of the sample matrix X
Figure FDA0001851666310000025
Wherein X is a matrix after the sample matrix is normalized; corresponding to formula (1.2) are obtained
P＝V (1.4)
Figure FDA0001851666310000026
From this, it follows thatiIs the sample variance of the ith principal element;
then, eigenvalue decomposition of the covariance matrix S
S＝VΛVT(1.6)
Where Λ is a diagonal matrix of the covariance matrix S, containing non-negative real eigenvalues of decreasing amplitude (λ)1＞λ2＞λ3＞λ4＞λ5＞λ6) V is an orthogonal array (V)TV ═ I, where I is the unit matrix), is the unitized eigenvector corresponding to eigenvalue λ;
substituting formulae (1.4) and (1.5) into (1.6) can yield:
Figure FDA0001851666310000031
finally, a score matrix T is solved:
T＝XP
for a new sample capacity x ∈ R6×1Then the score, estimate and residual vectors for this new vector are:
and (3) scoring vector: t ═ PTx, estimated vector:
Figure FDA0001851666310000032
residual vector: e ═ I (I-PP)T)x
The squared prediction error SPE is:
SPE＝eTe＝xT(I-PPT)x
the upper limit control of SPE is:
Figure FDA0001851666310000033
wherein c isαIs a standard normal deviation, h, corresponding to an upper limit of (1- α). times.100%0＝1-2θ1θ3/(3θ2 2)，
Figure FDA0001851666310000034
And lambdajIs the eigenvalue associated with the jth load vector of the data covariance;
and in the system operation process, the main pump motor operation current, the hydraulic system pressure, the immersed pump outlet flow, the hydraulic system temperature and the STC valve pressure data collected at the same time can all obtain an SPE value, and the SPE value is used for drawing a time change curve of the square prediction error SPE according to the time sequence.
CN201811298294.5A 2018-11-02 2018-11-02 Temperature rise calculation method for transition process of double-frequency quenching machining Pending CN111142496A (en)

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