Traction asynchronous motor control method

Abstract

The invention discloses a traction asynchronous motor control method, which comprises the steps of monitoring signal data and operation data of a traction asynchronous motor, performing data preprocessing, comprehensively analyzing and evaluating the operation performance of the traction asynchronous motor, constructing a target function of the optimal performance of the motor, outputting a motor regulation and control scheme and implementing the motor regulation and control scheme. According to the invention, the traction asynchronous motor is monitored and the data is preprocessed and comprehensively analyzed, the electric quality and the operation risk state of the motor are preliminarily assessed, and then the operation performance of the traction asynchronous motor is deeply assessed, so that comprehensive and timely diagnosis and early warning are carried out on the actual application operation performance state of the motor from local to overall. Data processing comprehensiveness and early warning prompt accuracy are guaranteed, so that the operation safety of the motor is guaranteed, a motor regulation and control scheme is output, the optimal operation performance of the traction asynchronous motor is adaptively tended according to the actual application state and performance attenuation characteristics of the motor, and efficient, green and reliable operation of a motor system is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of motor control, and in particular to a traction asynchronous motor control method. Background Art

[0002] Asynchronous motors are one of the most widely used types of motors in industrial production. They have a simple structure and low maintenance cost. However, due to the various faults that may occur during their operation, they pose a threat to the stability and continuity of industrial production. When traction motors are the main components of locomotive traction and braking, their safe and reliable operation is also crucial. Existing traction asynchronous motors may have abnormal fault problems in actual application scenarios. Due to the lack of comprehensiveness of motor operation monitoring and processing and the lack of accuracy of early warning prompts, it is difficult to conduct timely fault risk control management, which will lead to a decrease in motor operation safety. In addition, the performance of the motor will continue to decay in the long-term use state, further leading to poor motor operation state, and unable to achieve the optimal operation performance of the traction asynchronous motor, resulting in increased motor operation resource consumption and use costs, and unable to meet the energy saving and reliability requirements of actual production applications; In view of the above technical defects, a solution is now proposed. Summary of the invention

[0003] The purpose of the present invention is to solve the technical defects in the prior art of insufficient comprehensiveness of traction asynchronous motor faults and insufficient accuracy of diagnostic prompts, which leads to reduced motor operation safety and poor operating status, increased motor operation resource consumption and usage costs, and inability to meet actual production needs. The present invention realizes comprehensive and timely diagnosis and early warning of the actual application operating performance status of the motor from local to overall, ensures the comprehensiveness of data processing and the accuracy of early warning prompts, thereby ensuring the safety of motor operation, and then adaptively tends to the optimal operating performance of the traction asynchronous motor, ensuring efficient, green and reliable operation of the motor system.

[0004] In order to achieve the above object, the present invention adopts the following technical solutions: A traction asynchronous motor control method comprises the following steps: Step 1: monitor the signal data and operation data of the traction asynchronous motor: the signal data includes power signal parameters, stator signal parameters and rotor signal parameters; the operation data includes temperature parameters, vibration parameters and torque parameters; Step 2: preprocessing the signal data and operation data of the traction asynchronous motor: by preprocessing the signal data, the electrical quality of the traction asynchronous motor is evaluated; by preprocessing the operation data, the vibration risk degree, temperature risk degree and traction load performance of the traction asynchronous motor are analyzed, so as to monitor the operation status of the traction asynchronous motor; Step 3: Comprehensively analyze and evaluate the operating performance of the traction asynchronous motor: comprehensively evaluate the operating performance of the traction asynchronous motor by combining the electrical quality of the traction asynchronous motor and the traction load performance; and then evaluate the comprehensive impact of the motor performance by combining the vibration risk level and temperature risk level of the traction asynchronous motor; Step 4: construct the objective function of the motor's optimal performance and output the motor control plan: by establishing a correlation curve between the motor's operating performance index and the motor's performance impact index, and generating the objective function of the motor's optimal performance, the corresponding traction asynchronous motor control plan is generated and output; Step 5: Receive the traction asynchronous motor control plan and perform corresponding processing.

[0005] Furthermore, the specific process of preprocessing the signal data and operation data of the traction asynchronous motor is as follows: A1, by preprocessing the signal data, the electrical quality of the traction asynchronous motor is evaluated; The signal data includes power signal parameters, stator signal parameters and rotor signal parameters. Signal processing is performed through the power signal parameters, stator signal parameters and rotor signal parameters to obtain the power electrical coefficient, stator electrical coefficient and rotor electrical coefficient, analyze the module structural electrical characteristics of the power module, stator module and rotor module of the traction asynchronous motor, and then integrate and generate the electrical quality index through the power electrical coefficient, stator electrical coefficient and rotor electrical coefficient to comprehensively evaluate the electrical quality of the traction asynchronous motor; A2, by pre-processing the operating data, analyzing the vibration risk level, temperature risk level and traction load performance of the traction asynchronous motor, so as to monitor the operating status of the traction asynchronous motor; The operating data includes temperature parameters, vibration parameters and torque parameters. The temperature risk coefficient, vibration risk coefficient and traction load coefficient are obtained through data processing of the temperature parameters, vibration parameters and torque parameters. The temperature risk degree, vibration risk degree and traction load performance of the traction asynchronous motor are analyzed, so as to comprehensively evaluate the operating status of the traction asynchronous motor.

[0006] Furthermore, the specific process of comprehensively evaluating the operating performance of the traction asynchronous motor is as follows: B1, through the electrical quality and traction load performance of the traction asynchronous motor and combined with timing analysis, the electrical quality index and traction load factor are combined to obtain the motor operation performance index, and the operation performance of the traction asynchronous motor is comprehensively evaluated; B2, by analyzing the vibration risk level and temperature risk level of the traction asynchronous motor, the vibration risk coefficient and the temperature risk coefficient are combined to generate a motor performance impact index to evaluate the comprehensive impact level of the motor performance.

[0007] Furthermore, the specific process of preprocessing the signal data is as follows: The signal data includes power signal parameters, stator signal parameters and rotor signal parameters; A1-1, power signal parameters include power supply voltage Uem and power supply current Iem; stator signal parameters include stator voltage Ust and stator current Ist; rotor signal parameters include rotor electrical angular velocity ωrt and rotor current Irt; A1-2, construct a parameter processing model to analyze and process the power signal parameters, stator signal parameters and rotor signal parameters. The specific process of the parameter processing model is as follows: Input signal parameter G to the parameter processing model, the signal parameter includes n0 data indicators, any data indicator is marked as g, and the data value of data indicator g is marked as Mg; The standard interval of the data indicator g is set to [Qg1, Qg2]. When the data value Mg of the data indicator g is within the standard interval, it means that the data indicator g is normal; otherwise, it means that the data indicator g is abnormal. Deviation coefficient δg of output data index g: ; When the deviation coefficient δg is greater than 0, the data index g is judged to be abnormal; otherwise, the data index g is judged to be normal; Deviation coefficients corresponding to n0 data indicators of the output signal parameter G of the parameter processing model; A1-3, set the standard range of the power signal parameter, substitute the power signal parameter and its standard range into the parameter processing model, obtain the deviation coefficients of the power voltage Uem and the power current Iem, and mark them as the power voltage deviation coefficient δuem and the power current deviation coefficient δiem respectively; The power supply electrical coefficient EMe is obtained by combining the power supply voltage deviation coefficient δuem, the power supply current deviation coefficient δiem, the power supply voltage Uem and the power supply current Iem (t); A1-4, set the standard interval of the stator signal parameters, substitute the stator signal parameters and their standard intervals into the parameter processing model, obtain the deviation coefficients of the stator voltage Ust and the stator current Ist, and mark them as the stator voltage deviation coefficient δust and the stator current deviation coefficient δist respectively; The stator electrical coefficient STe is obtained by combining the stator voltage deviation coefficient δust, the stator current deviation coefficient δist, the stator voltage Ust and the stator current Ist (t); A1-5, set the standard interval of the rotor signal parameter, substitute the rotor signal parameter and its standard interval into the parameter processing model, obtain the deviation coefficient of the rotor electrical angular velocity ωrt and the rotor current Irt, and mark them as the rotor speed deviation coefficient δωrt and the rotor current deviation coefficient δirt respectively; The rotor electrical coefficient RTe is obtained by combining the rotor speed deviation coefficient δωrt, the rotor current deviation coefficient δirt, the rotor electrical angular velocity ωrt and the rotor current Irt; A1-6, and then generate the electrical quality index EQ by combining the power supply electrical coefficient EMe, the stator electrical coefficient STe and the rotor electrical coefficient RTe.

[0008] Furthermore, the specific process of preprocessing the running data is as follows: A2-1, temperature parameters include power module temperature Wem, stator module temperature Wst and rotor module temperature Wrt; vibration parameters include vibration speed value Vzd, vibration amplitude value Azd and vibration frequency value Fzd; torque parameters include starting torque Τstart, maximum torque Τmax and slip torque Tslip; A2-2, through the data processing of the power module temperature Wem, the stator module temperature Wst and the rotor module temperature Wrt, the temperature risk coefficient Ψw is obtained, the temperature risk degree of the traction asynchronous motor is evaluated, and the corresponding temperature risk warning signal is generated; A2-3, perform data processing through vibration parameters, set the standard intervals of vibration velocity value Vzd, vibration amplitude value Azd and vibration frequency value Fzd respectively, substitute them into the parameter processing model, output the deviation coefficient of the corresponding data index, and mark them as vibration velocity deviation value respectively , vibration amplitude deviation value , vibration frequency deviation value , and then comprehensively obtain the vibration risk coefficient Ψzd, evaluate the vibration risk degree of the traction asynchronous motor, and generate a corresponding vibration risk warning signal; A2-4, obtain the traction load coefficient Ψτ by processing the starting torque Τstart, the maximum torque Τmax and the slip torque Tslip, evaluate the traction load performance of the traction asynchronous motor, and generate a corresponding load performance prompt signal; A2-5, integrates the temperature risk warning signal, vibration risk warning signal and load performance warning signal into an operation warning signal group, so as to monitor the operating status of the traction asynchronous motor.

[0009] Furthermore, the specific process of comprehensively evaluating the operating performance of the traction asynchronous motor is as follows: B1-1, through the electrical quality and traction load performance of the traction asynchronous motor and combined with timing analysis, the electrical quality index EQ and the traction load coefficient Ψτ are combined, and the data calculation period Ts is set to perform regular calculations on the electrical quality index EQ and the traction load coefficient Ψτ, and the electrical quality index EQ and the traction load coefficient Ψτ corresponding to n1 data calculation periods Ts are extracted to construct the history matrix H; B1-101, establish a matrix analysis model, calculate the variance of the longitudinal quantity of the historical matrix H, and obtain the longitudinal quantity fluctuation coefficient σx; and calculate the average value of the adjacent longitudinal quantity difference to obtain the longitudinal quantity growth average coefficient Kx; then calculate the standard deviation of the adjacent longitudinal quantity difference to obtain the longitudinal quantity growth change coefficient σk; and then obtain the evaluation index φx of the xth group of longitudinal quantities by combining the longitudinal quantity fluctuation coefficient σx, the longitudinal quantity growth average coefficient Kx and the longitudinal quantity growth change coefficient σk; B1-102, mark any electrical quality index EQ as , and substitute it into the matrix analysis model, output the corresponding evaluation index and mark it as the electrical quality evaluation index φ1; B1-103, mark any traction load factor Ψτ as , and substitute it into the matrix analysis model, output the corresponding evaluation index and mark it as the traction load evaluation index φ2; By combining the electrical quality evaluation index φ1 and the traction load evaluation index φ2, the motor operation performance index RUNem is obtained to evaluate the operation performance of the traction asynchronous motor and generate a corresponding motor performance prompt signal.

[0010] Furthermore, the specific process of evaluating the comprehensive impact of motor performance is as follows: B2, by analyzing the vibration risk level and temperature risk level of the traction asynchronous motor, the vibration risk coefficient Ψzd and the temperature risk coefficient Ψw are combined to generate the motor performance impact index INFem, evaluate the comprehensive impact level of the motor performance risk, and generate the corresponding motor performance risk signal.

[0011] Furthermore, the specific process of generating the objective function of the motor's optimal performance and obtaining the traction asynchronous motor control scheme is as follows: By establishing a correlation curve S0 between the motor running performance index RUNem and the motor performance influence index INFem, and fitting the correlation curve S0, an objective function Fopt for the optimal performance of the motor is generated; A dynamic curve is constructed through the objective function Fopt and the maximum value Fmax of the objective function Fopt is extracted. The signal data corresponding to the maximum value Fmax of the objective function Fopt is used as the optimal performance state parameter of the traction asynchronous motor, thereby generating and outputting the corresponding traction asynchronous motor control scheme.

[0012] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: The present invention monitors the signal data and operation data of the traction asynchronous motor, and pre-processes and comprehensively analyzes the data. It first preliminarily evaluates the electrical quality and operation risk status of the motor, and then deeply evaluates the operation performance of the traction asynchronous motor. From the local to the overall, the present invention conducts a comprehensive and timely diagnosis and early warning of the actual application operation performance status of the motor, ensuring the comprehensiveness of data processing and the accuracy of early warning prompts, thereby ensuring the safety of motor operation, and then constructing an objective function for the optimal performance of the motor, and outputting a motor control scheme for processing, so as to dynamically respond according to the actual application status of the motor and its performance attenuation characteristics, adaptively tend to the optimal operation performance of the traction asynchronous motor, and ensure the efficient, green and reliable operation of the motor system. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 A schematic diagram showing the steps of the overall solution process of the present invention is shown; Figure 2 A schematic diagram of the data processing flow of the present invention is shown. DETAILED DESCRIPTION

[0014] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0015] Embodiment 1: like Figure 1-Figure 2 As shown, a traction asynchronous motor control method comprises the following steps: S1, monitoring the signal data and operation data of the traction asynchronous motor: the signal data includes power signal parameters, stator signal parameters and rotor signal parameters; the operation data includes temperature parameters, vibration parameters and torque parameters; S2, preprocessing the signal data and operation data of the traction asynchronous motor: by preprocessing the signal data, the electrical quality of the traction asynchronous motor is evaluated; by preprocessing the operation data, the vibration risk degree, temperature risk degree and traction load performance of the traction asynchronous motor are analyzed, so as to monitor the operation status of the traction asynchronous motor. The specific process is as follows: A1, by preprocessing the signal data, the electrical quality of the traction asynchronous motor is evaluated; The signal data includes power signal parameters, stator signal parameters and rotor signal parameters. Signal processing is performed through the power signal parameters, stator signal parameters and rotor signal parameters to obtain the power electrical coefficient, stator electrical coefficient and rotor electrical coefficient, analyze the module structural electrical characteristics of the power module, stator module and rotor module of the traction asynchronous motor, and then integrate and generate the electrical quality index through the power electrical coefficient, stator electrical coefficient and rotor electrical coefficient to comprehensively evaluate the electrical quality of the traction asynchronous motor; A1-1, power signal parameters include power supply voltage Uem and power supply current Iem; stator signal parameters include stator voltage Ust and stator current Ist; rotor signal parameters include rotor electrical angular velocity ωrt and rotor current Irt; signal data is collected through existing Hall sensors and power meters; A1-2, construct a parameter processing model to analyze and process the power signal parameters, stator signal parameters and rotor signal parameters. The specific process of the parameter processing model is as follows: Input signal parameter G to the parameter processing model, the signal parameter includes n0 data indicators, any data indicator is marked as g, and the data value of data indicator g is marked as Mg; The standard interval of the data indicator g is set to [Qg1, Qg2]. When the data value Mg of the data indicator g is within the standard interval, it means that the data indicator g is normal; otherwise, it means that the data indicator g is abnormal. Deviation coefficient δg of output data index g: ; When the deviation coefficient δg is greater than 0, the data index g is judged to be abnormal; otherwise, the data index g is judged to be normal; Deviation coefficients corresponding to n0 data indicators of the output signal parameter G of the parameter processing model; A1-3, set the standard range of the power signal parameter, substitute the power signal parameter and its standard range into the parameter processing model, obtain the deviation coefficients of the power voltage Uem and the power current Iem, and mark them as the power voltage deviation coefficient δuem and the power current deviation coefficient δiem respectively; The power supply electrical coefficient EMe is obtained by combining the power supply voltage deviation coefficient δuem, the power supply current deviation coefficient δiem, the power supply voltage Uem and the power supply current Iem (t): ; Among them, t is the current time node, It refers to the rate of change of the power supply current Iem. is the power module inductance evaluation coefficient, α0, α1 and α2 are the weight coefficients of the power supply voltage Uem, the power supply voltage deviation coefficient δuem and the power supply current deviation coefficient δiem respectively, and α0, α1 and α2 are all greater than 0. The weight coefficients are preset and obtained after calculating a large amount of experimental data. The specific preset value is combined with the actual parameters of the traction asynchronous motor, and it only needs to meet the corresponding associated influence proportional relationship; when The higher it is, and the lower the power supply voltage deviation coefficient δuem and the power supply current deviation coefficient δiem, the higher the power supply electrical coefficient EMe, indicating that the structural inductance of the power module is lower, indicating that the current delay time constant is lower, indicating that the power module responds faster, and the lower the deviation degree of the power supply voltage Uem and the power supply current Iem, indicating that the abnormality of the power supply signal parameters is lower, and thus the comprehensive evaluation of the electrical characteristics of the power module is better; A1-4, set the standard interval of the stator signal parameters, substitute the stator signal parameters and their standard intervals into the parameter processing model, obtain the deviation coefficients of the stator voltage Ust and the stator current Ist, and mark them as the stator voltage deviation coefficient δust and the stator current deviation coefficient δist respectively; The stator electrical coefficient STe is obtained by combining the stator voltage deviation coefficient δust, the stator current deviation coefficient δist, the stator voltage Ust and the stator current Ist (t): ; in, is the rate of change of the sub-current Ist, is the stator module inductance evaluation formula, β0, β1 and β2 are the weight coefficients of stator voltage Ust, stator voltage deviation coefficient δust and stator current deviation coefficient δist, respectively, and β0, β1 and β2 are all greater than 0; when The higher the value is and the lower the stator voltage deviation coefficient δust and the stator current deviation coefficient δist are, the higher the stator electrical coefficient STe is, and the better the comprehensive evaluation of the electrical characteristics of the stator module is. A1-5, set the standard interval of the rotor signal parameter, substitute the rotor signal parameter and its standard interval into the parameter processing model, obtain the deviation coefficient of the rotor electrical angular velocity ωrt and the rotor current Irt, and mark them as the rotor speed deviation coefficient δωrt and the rotor current deviation coefficient δirt respectively; The rotor electrical coefficient RTe is obtained by combining the rotor speed deviation coefficient δωrt, the rotor current deviation coefficient δirt, the rotor electrical angular velocity ωrt and the rotor current Irt: ; in, It refers to the rate of change of the rotor current Irt. The higher it is, the lower the delay time of the rotor current Irt is within a certain time length, indicating that the rotor module structure responds faster and has better performance. γ0, γ1 and γ2 are the weight coefficients of the rotor electrical angular velocity ωrt, the rotor speed deviation coefficient δωrt and the rotor current deviation coefficient δirt, respectively, and γ0, γ1 and γ2 are all greater than 0. When the rotor electrical angular velocity ωrt is higher and the rotor speed deviation coefficient δωrt and the rotor current deviation coefficient δirt are lower, the rotor electrical coefficient RTe is higher, and the comprehensive evaluation of the electrical characteristics of the rotor module is better. A1-6, and then generate the electrical quality index EQ by combining the power supply electrical coefficient EMe, stator electrical coefficient STe and rotor electrical coefficient RTe: ; Among them, ω1, ω2 and ω3 are conversion coefficients of the power supply electrical coefficient EMe, the stator electrical coefficient STe and the rotor electrical coefficient RTe respectively. The conversion coefficients are preset and obtained after a large amount of data calculation, and the preset ω1, ω2 and ω3 are all greater than 1; the higher the power supply electrical coefficient EMe, the stator electrical coefficient STe and the rotor electrical coefficient RTe, the higher the electrical quality index EQ, indicating that the module structure electrical characteristics of the power module, stator module and rotor module of the traction asynchronous motor are better, and then the comprehensive evaluation of the electrical quality of the traction asynchronous motor is better; A2, by pre-processing the operating data, analyzing the vibration risk level, temperature risk level and traction load performance of the traction asynchronous motor, so as to monitor the operating status of the traction asynchronous motor; The operating data includes temperature parameters, vibration parameters and torque parameters. The temperature risk coefficient, vibration risk coefficient and traction load coefficient are obtained by data processing through the temperature parameters, vibration parameters and torque parameters. The temperature risk degree, vibration risk degree and traction load performance of the traction asynchronous motor are analyzed, so as to comprehensively evaluate the operating status of the traction asynchronous motor. A2-1, temperature parameters include power module temperature Wem, stator module temperature Wst and rotor module temperature Wrt; The vibration parameters include the vibration velocity value Vzd, the vibration amplitude value Azd and the vibration frequency value Fzd; Torque parameters include starting torque Τstart, maximum torque Tmax and slip torque Tslip; Among them, the vibration parameters are evaluated as a whole by collecting the vibration conditions of any point in the internal structure of the motor. The starting torque is the torque generated by the motor during the starting process, which is usually greater than the rated torque of the motor and helps the motor start smoothly. The maximum torque is the maximum torque that the motor can reach when the slip is zero. The slip torque is the torque generated by the motor when it is running. A2-2, through the power module temperature Wem, stator module temperature Wst and rotor module temperature Wrt data processing, obtain the temperature risk coefficient Ψw: ; in, It refers to the average value of the power module temperature Wem, the stator module temperature Wst and the rotor module temperature Wrt. The higher the value is, and the higher the standard deviation between the power module temperature Wem, the stator module temperature Wst, and the rotor module temperature Wrt, it means that the overall temperature of the motor is high and the temperature difference between the structures is large. High temperature and unbalanced temperature distribution will cause the motor to lose its life quickly during use, resulting in poor motor performance. Set the evaluation interval of the temperature risk coefficient Ψw, evaluate the temperature risk level of the traction asynchronous motor by comparing the intervals, and generate a corresponding temperature risk warning signal; A2-3, perform data processing through vibration parameters, set the standard intervals of vibration velocity value Vzd, vibration amplitude value Azd and vibration frequency value Fzd respectively, substitute them into the parameter processing model, output the deviation coefficient of the corresponding data index, and mark them as vibration velocity deviation value respectively , vibration amplitude deviation value , vibration frequency deviation value , and then comprehensively obtain the vibration risk coefficient Ψzd: ; Among them, η1, η2 and η3 are vibration velocity deviation values ​​respectively. , vibration amplitude deviation value And vibration frequency deviation The proportional coefficient, and η1, η2 and η3 are all greater than 0, when the vibration velocity deviation value , vibration amplitude deviation value And vibration frequency deviation When it is higher, the vibration risk coefficient Ψzd is higher, indicating that the degree to which each data index of the vibration parameter deviates from the preset standard range is higher, and the vibration risk degree of the traction asynchronous motor is higher; Set the evaluation interval of the vibration risk coefficient Ψzd, evaluate the vibration risk level of the traction asynchronous motor by comparing the intervals, and generate a corresponding vibration risk warning signal; A2-4, through the starting torque Τstart, maximum torque Τmax and slip torque Tslip data processing, obtain the traction load coefficient Ψτ: ; Wherein, ε1, ε2 and ε3 are the logarithmic bases of the starting torque Τstart, the maximum torque Tmax and the slip torque Tslip, respectively, and ε1, ε2 and ε3 are all preset to be greater than 1. When the starting torque Tstart, the maximum torque Tmax and the slip torque Tslip are higher, the traction load coefficient Ψτ is higher, indicating that the comprehensive traction capacity of the motor is better, and the traction load performance of the traction asynchronous motor is evaluated and analyzed better; An evaluation interval of the traction load coefficient Ψτ is set, and the traction load performance of the traction asynchronous motor is analyzed by comparing and evaluating the intervals, and a corresponding load performance prompt signal is generated; A2-5, integrates the temperature risk warning signal, vibration risk warning signal and load performance warning signal into an operation warning signal group, so as to monitor the operation status of the traction asynchronous motor; S3, comprehensive analysis and evaluation of the operating performance of the traction asynchronous motor: by combining the electrical quality of the traction asynchronous motor and the traction load performance, the operating performance of the traction asynchronous motor is comprehensively evaluated; then by combining the vibration risk level and temperature risk level of the traction asynchronous motor, the comprehensive impact of the motor performance is evaluated. The specific process is as follows: B1, through the electrical quality and traction load performance of the traction asynchronous motor and combined with timing analysis, the electrical quality index and traction load coefficient are combined to obtain the motor operation performance index, and the operation performance of the traction asynchronous motor is comprehensively evaluated. The specific process is as follows: B1-1, through the electrical quality and traction load performance of the traction asynchronous motor and combined with timing analysis, the electrical quality index EQ and the traction load coefficient Ψτ are combined, and the data calculation period Ts is set to perform regular calculations on the electrical quality index EQ and the traction load coefficient Ψτ. The electrical quality index EQ and the traction load coefficient Ψτ corresponding to n1 data calculation periods Ts are extracted to construct the historical matrix H: ; Among them, the two columns of the history matrix H represent the electrical quality index EQ and the traction load coefficient Ψτ, respectively, and the n1 groups of row vectors of the history matrix H represent n1 data measurement cycles Ts, respectively; B1-101, establish a matrix analysis model, calculate the variance of the longitudinal quantity of the historical matrix H, and obtain the longitudinal quantity fluctuation coefficient σx: ,in, is any value of the x-th group of longitudinal quantities, is the average value of n1 data of the xth group of longitudinal quantities; Then calculate the average value of the adjacent longitudinal quantity difference and obtain the average longitudinal quantity growth coefficient Kx: ,in, is the longitudinal quantity of the xth group The adjacent value of ; Then calculate the standard deviation of the adjacent longitudinal quantity difference to obtain the longitudinal quantity growth coefficient σk: ; Then, by combining the longitudinal quantity fluctuation coefficient σx, the longitudinal quantity growth average coefficient Kx and the longitudinal quantity growth variation coefficient σk, the evaluation index φx of the x-th group of longitudinal quantities is obtained: ,in, It refers to the data value corresponding to the last data measurement period Ts of the x-th group of longitudinal quantities. p1 and p2 are the weight indexes of the longitudinal quantity fluctuation coefficient σx and the longitudinal quantity growth change coefficient σk, respectively. It is preset that p1 and p2 are both greater than 0 and p1+p2=1. The lower the longitudinal quantity fluctuation coefficient σx and the longitudinal quantity growth change coefficient σk, the better the stability of the historical data of the x-th group of longitudinal quantities. The higher the average coefficient Kx of the longitudinal quantity growth, the more obvious the growth trend of the longitudinal quantity of the xth group is, which means that the higher the evaluation index φx of the longitudinal quantity of the xth group is, the better the evaluation status of the longitudinal quantity of the xth group is; The matrix analysis model outputs the evaluation index φx of the xth group of longitudinal quantities; B1-102: Mark any electrical quality index EQ as , and substitute the first group of longitudinal quantities into the matrix analysis model, output the corresponding evaluation index and mark it as the electrical quality evaluation index φ1; B1-103: Mark any traction load factor Ψτ as , and substitute the second group of longitudinal quantities into the matrix analysis model, output the corresponding evaluation index and mark it as the traction load evaluation index φ2; B1-2, by combining the electrical quality evaluation index φ1 and the traction load evaluation index φ2, the motor running performance index RUNem is obtained: ; When the electrical quality evaluation index φ1 and the traction load evaluation index φ2 are higher, the motor operation performance index RUNem is higher, and the comprehensive evaluation of the operation performance of the traction asynchronous motor is better; Set the evaluation interval of the motor running performance index RUNem, evaluate the running performance of the traction asynchronous motor through interval comparison, and generate corresponding motor performance prompt signals; B2, by analyzing the vibration risk level and temperature risk level of the traction asynchronous motor, combining the vibration risk coefficient and the temperature risk coefficient to generate the motor performance impact index, and evaluate the comprehensive impact level of the motor performance. The specific process is as follows: By analyzing the vibration risk level and temperature risk level of the traction asynchronous motor, the vibration risk coefficient Ψzd and the temperature risk coefficient Ψw are combined to generate the motor performance impact index INFem: ; Among them, q1 and q2 are weight indexes of the vibration risk coefficient Ψzd and the temperature risk coefficient Ψw, respectively. It is preset that q1 and q2 are both greater than 0 and q1+q2=1. When the vibration risk coefficient Ψzd and the temperature risk coefficient Ψw are higher, the motor performance impact index INFem is higher, and the comprehensive impact degree of the motor performance risk is higher. Set the evaluation interval of the motor performance impact index INFem, evaluate the comprehensive impact of the motor performance risk through interval comparison, and generate the corresponding motor performance risk signal; There are Y evaluation intervals of the preset motor performance impact index INFem, and any evaluation interval is marked as Qy. When the motor performance impact index INFem is in the evaluation interval Qy, the comprehensive impact degree of the motor performance risk is evaluated to be Ny level, and an Ny level motor performance risk signal is generated; S4, constructing the objective function of the motor's optimal performance and outputting the motor control scheme: by establishing the correlation curve between the motor's operating performance index and the motor's performance impact index, and generating the objective function of the motor's optimal performance, the corresponding traction asynchronous motor control scheme is generated and outputted. The specific process is as follows: By establishing the correlation curve S0 between the motor running performance index RUNem and the motor performance influence index INFem, and fitting the mathematical model of the correlation curve S0, the objective function Fopt of the motor optimal performance is generated: , when the motor operation performance index RUNem is higher and the motor performance impact index INFem is lower, the objective function Fopt is higher; A dynamic curve is constructed through the objective function Fopt and the maximum value Fmax of the objective function Fopt is extracted. The signal data corresponding to the maximum value Fmax of the objective function Fopt is used as the optimal performance state parameter of the traction asynchronous motor. The optimal performance state parameter is integrated into the traction asynchronous motor control target, thereby generating and outputting the corresponding traction asynchronous motor control scheme; S5, receiving the traction asynchronous motor control plan and performing corresponding processing: By receiving the traction asynchronous motor control plan and performing corresponding processing, the power signal parameters, stator signal parameters and rotor signal parameters of the dynamic control signal data are continuously approached to the traction asynchronous motor control target. The performance of the traction asynchronous motor in the load application scenario will continue to decay over time, and the objective function Fopt is in a dynamic development of regular measurement, so the maximum value Fmax will be continuously refreshed to adapt to the actual application status of the traction asynchronous motor and its performance attenuation characteristics, and adaptively seek the optimal operating performance under the current state of the motor, reduce the energy consumption cost of the motor, and ensure the efficient, green and reliable operation of the motor system.

[0016] To summarize, the present invention monitors the signal data and operation data of the traction asynchronous motor, and pre-processes and comprehensively analyzes the data. It first preliminarily evaluates the electrical quality and operation risk status of the motor, and then deeply evaluates the operation performance of the traction asynchronous motor, so as to achieve comprehensive and timely diagnosis and early warning of the actual application operation performance status of the motor from local to overall, ensure the comprehensiveness of data processing and the accuracy of early warning prompts, thereby ensuring the safety of motor operation, and then constructing the objective function of the optimal performance of the motor, and outputting the motor control scheme for processing, so as to adaptively tend to the optimal operation performance of the traction asynchronous motor according to the actual application status of the motor and its performance attenuation characteristics, so as to ensure the efficient, green and reliable operation of the motor system.

[0017] The size of the interval and threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by technical personnel in this field for each group of sample data; as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0018] The above formulas are all dimensionless and numerical calculations. The formula is a formula obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formula are set by technicians in this field according to actual conditions. The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A traction asynchronous motor control method, characterized in that: The following steps are involved: Step 1: monitor the signal data and operation data of the traction asynchronous motor: the signal data includes power signal parameters, stator signal parameters and rotor signal parameters; the operation data includes temperature parameters, vibration parameters and torque parameters; Step 2: preprocessing the signal data and operation data of the traction asynchronous motor: by preprocessing the signal data, the electrical quality of the traction asynchronous motor is evaluated; by preprocessing the operation data, the vibration risk degree, temperature risk degree and traction load performance of the traction asynchronous motor are analyzed, so as to monitor the operation status of the traction asynchronous motor; Step 3: Comprehensively analyze and evaluate the operating performance of the traction asynchronous motor: comprehensively evaluate the operating performance of the traction asynchronous motor by combining the electrical quality of the traction asynchronous motor and the traction load performance; and then evaluate the comprehensive impact of the motor performance by combining the vibration risk level and temperature risk level of the traction asynchronous motor; Step 4: construct the objective function of the motor's optimal performance and output the motor control plan: by establishing a correlation curve between the motor's operating performance index and the motor's performance impact index, and generating the objective function of the motor's optimal performance, the corresponding traction asynchronous motor control plan is generated and output; Step 5: Receive the traction asynchronous motor control plan and perform corresponding processing.

2. A traction asynchronous motor control method according to claim 1, characterized in that: The specific process of preprocessing the signal data and operation data of the traction asynchronous motor is as follows: A1, by preprocessing the signal data, the electrical quality of the traction asynchronous motor is evaluated; The signal data includes power signal parameters, stator signal parameters and rotor signal parameters. Signal processing is performed through the power signal parameters, stator signal parameters and rotor signal parameters to obtain the power electrical coefficient, stator electrical coefficient and rotor electrical coefficient, analyze the module structural electrical characteristics of the power module, stator module and rotor module of the traction asynchronous motor, and then integrate and generate the electrical quality index through the power electrical coefficient, stator electrical coefficient and rotor electrical coefficient to comprehensively evaluate the electrical quality of the traction asynchronous motor; A2, by pre-processing the operating data, analyzing the vibration risk level, temperature risk level and traction load performance of the traction asynchronous motor, so as to monitor the operating status of the traction asynchronous motor; The operating data includes temperature parameters, vibration parameters and torque parameters. The temperature risk coefficient, vibration risk coefficient and traction load coefficient are obtained through data processing of the temperature parameters, vibration parameters and torque parameters. The temperature risk degree, vibration risk degree and traction load performance of the traction asynchronous motor are analyzed, so as to comprehensively evaluate the operating status of the traction asynchronous motor.

3. A traction asynchronous motor control method according to claim 2, characterized in that: The specific process of comprehensively evaluating the operating performance of traction asynchronous motors is as follows: B1, through the electrical quality and traction load performance of the traction asynchronous motor and combined with timing analysis, the electrical quality index and traction load factor are combined to obtain the motor operation performance index, and the operation performance of the traction asynchronous motor is comprehensively evaluated; B2, by analyzing the vibration risk level and temperature risk level of the traction asynchronous motor, the vibration risk coefficient and the temperature risk coefficient are combined to generate a motor performance impact index to evaluate the comprehensive impact level of the motor performance.

4. A traction asynchronous motor control method according to claim 3, characterized in that: The specific process of preprocessing signal data is as follows: The signal data includes power signal parameters, stator signal parameters and rotor signal parameters; A1-1, power signal parameters include power voltage Uem and power current Iem; stator signal parameters include stator voltage Ust and stator current Ist; The rotor signal parameters include the rotor electrical angular velocity ωrt and the rotor current Irt; A1-2, construct a parameter processing model to analyze and process the power signal parameters, stator signal parameters and rotor signal parameters. The specific process of the parameter processing model is as follows: Input signal parameter G to the parameter processing model, the signal parameter includes n0 data indicators, any data indicator is marked as g, and the data value of data indicator g is marked as Mg; The standard interval of the data indicator g is set to [Qg1, Qg2]. When the data value Mg of the data indicator g is within the standard interval, it means that the data indicator g is normal; otherwise, it means that the data indicator g is abnormal. Deviation coefficient δg of output data index g: ; When the deviation coefficient δg is greater than 0, the data index g is judged to be abnormal; Otherwise, the data index g is judged to be normal; Deviation coefficients corresponding to n0 data indicators of the output signal parameter G of the parameter processing model; A1-3, set the standard range of the power signal parameter, substitute the power signal parameter and its standard range into the parameter processing model, obtain the deviation coefficients of the power voltage Uem and the power current Iem, and mark them as the power voltage deviation coefficient δuem and the power current deviation coefficient δiem respectively; The power supply electrical coefficient EMe is obtained by combining the power supply voltage deviation coefficient δuem, the power supply current deviation coefficient δiem, the power supply voltage Uem and the power supply current Iem (t); A1-4, set the standard interval of the stator signal parameters, substitute the stator signal parameters and their standard intervals into the parameter processing model, obtain the deviation coefficients of the stator voltage Ust and the stator current Ist, and mark them as the stator voltage deviation coefficient δust and the stator current deviation coefficient δist respectively; The stator electrical coefficient STe is obtained by combining the stator voltage deviation coefficient δust, the stator current deviation coefficient δist, the stator voltage Ust and the stator current Ist (t); A1-5, set the standard interval of the rotor signal parameter, substitute the rotor signal parameter and its standard interval into the parameter processing model, obtain the deviation coefficient of the rotor electrical angular velocity ωrt and the rotor current Irt, and mark them as the rotor speed deviation coefficient δωrt and the rotor current deviation coefficient δirt respectively; The rotor electrical coefficient RTe is obtained by combining the rotor speed deviation coefficient δωrt, the rotor current deviation coefficient δirt, the rotor electrical angular velocity ωrt and the rotor current Irt; A1-6, and then generate the electrical quality index EQ by combining the power supply electrical coefficient EMe, the stator electrical coefficient STe and the rotor electrical coefficient RTe.

5. A traction asynchronous motor control method according to claim 4, characterized in that: The specific process of preprocessing the running data is as follows: A2-1, temperature parameters include power module temperature Wem, stator module temperature Wst and rotor module temperature Wrt; vibration parameters include vibration speed value Vzd, vibration amplitude value Azd and vibration frequency value Fzd; torque parameters include starting torque Τstart, maximum torque Τmax and slip torque Tslip; A2-2, through the data processing of the power module temperature Wem, the stator module temperature Wst and the rotor module temperature Wrt, the temperature risk coefficient Ψw is obtained, the temperature risk degree of the traction asynchronous motor is evaluated, and the corresponding temperature risk warning signal is generated; A2-3, perform data processing through vibration parameters, set the standard intervals of vibration velocity value Vzd, vibration amplitude value Azd and vibration frequency value Fzd respectively, substitute them into the parameter processing model, output the deviation coefficient of the corresponding data index, and mark them as vibration velocity deviation value respectively , vibration amplitude deviation value , vibration frequency deviation value , and then comprehensively obtain the vibration risk coefficient Ψzd, evaluate the vibration risk degree of the traction asynchronous motor, and generate a corresponding vibration risk warning signal; A2-4, obtain the traction load coefficient Ψτ by processing the starting torque Τstart, the maximum torque Τmax and the slip torque Tslip, evaluate the traction load performance of the traction asynchronous motor, and generate a corresponding load performance prompt signal; A2-5, integrates the temperature risk warning signal, vibration risk warning signal and load performance warning signal into an operation warning signal group, so as to monitor the operating status of the traction asynchronous motor.

6. A traction asynchronous motor control method according to claim 5, characterized in that: The specific process of comprehensively evaluating the operating performance of traction asynchronous motors is as follows: B1-1, through the electrical quality and traction load performance of the traction asynchronous motor and combined with timing analysis, the electrical quality index EQ and the traction load coefficient Ψτ are combined, and the data calculation period Ts is set to perform regular calculations on the electrical quality index EQ and the traction load coefficient Ψτ, and the electrical quality index EQ and the traction load coefficient Ψτ corresponding to n1 data calculation periods Ts are extracted to construct the history matrix H; B1-101, establish a matrix analysis model, calculate the variance of the longitudinal quantity of the historical matrix H, and obtain the longitudinal quantity fluctuation coefficient σx; and calculate the average value of the adjacent longitudinal quantity difference to obtain the longitudinal quantity growth average coefficient Kx; then calculate the standard deviation of the adjacent longitudinal quantity difference to obtain the longitudinal quantity growth change coefficient σk; and then obtain the evaluation index φx of the xth group of longitudinal quantities by combining the longitudinal quantity fluctuation coefficient σx, the longitudinal quantity growth average coefficient Kx and the longitudinal quantity growth change coefficient σk; B1-102, mark any electrical quality index EQ as , and substitute it into the matrix analysis model, output the corresponding evaluation index and mark it as the electrical quality evaluation index φ1; B1-103, mark any traction load factor Ψτ as , and substitute it into the matrix analysis model, output the corresponding evaluation index and mark it as the traction load evaluation index φ2; By combining the electrical quality evaluation index φ1 and the traction load evaluation index φ2, the motor operation performance index RUNem is obtained to evaluate the operation performance of the traction asynchronous motor and generate a corresponding motor performance prompt signal.

7. A traction asynchronous motor control method according to claim 6, characterized in that: The specific process of evaluating the comprehensive impact of motor performance is: B2, by analyzing the vibration risk level and temperature risk level of the traction asynchronous motor, the vibration risk coefficient Ψzd and the temperature risk coefficient Ψw are combined to generate the motor performance impact index INFem, evaluate the comprehensive impact level of the motor performance risk, and generate the corresponding motor performance risk signal.

8. A traction asynchronous motor control method according to claim 7, characterized in that: The specific process of generating the objective function of the motor's optimal performance and obtaining the traction asynchronous motor control scheme is as follows: By establishing a correlation curve S0 between the motor running performance index RUNem and the motor performance influence index INFem, and fitting the correlation curve S0, the objective function Fopt of the motor optimal performance is generated; A dynamic curve is constructed through the objective function Fopt and the maximum value Fmax of the objective function Fopt is extracted. The signal data corresponding to the maximum value Fmax of the objective function Fopt is used as the optimal performance state parameter of the traction asynchronous motor, thereby generating and outputting the corresponding traction asynchronous motor control scheme.

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