Non-intrusive detection method and system for dynamic eccentricity fault of brushless doubly-fed motor

Abstract

The application provides a non-invasive detection method and system for dynamic eccentricity fault of a brushless doubly-fed motor, and the method comprises the following steps: according to the basic electromagnetic relationship of the brushless doubly-fed motor, when the rotor dynamic eccentricity occurs, the fault characteristic frequency of the control winding connected with the frequency converter of the motor is calculated; the motor current is detected by using the FFT decomposition method, if the fault characteristic frequency signal appears, the current signal X(t) changing with time in the current transformer directly connected with the control winding in a certain time period of motor operation is recorded; the dynamic signal decomposition is performed on the current signal X(t), and the natural mode function of the current signal is obtained; the natural mode function of the current signal is fitted, and compared with the curve in the non-eccentric working state, if the fitted curve is offset compared with the curve in the non-eccentric working state, it is judged that the dynamic eccentricity fault occurs. The application detects the fault without adding additional sensors, and greatly improves the system reliability.

Description

Technical Field

[0001] The present invention relates to the technical field of electric power equipment, and in particular to a non-invasive detection method and system for a dynamic eccentricity fault of a brushless doubly-fed motor. Background Art

[0002] The brushless doubly-fed motor inherits the advantages of the traditional AC excitation motor's dual electrical ports while eliminating brushes and slip rings. It has the advantages of simple structure and durability, and has broad application prospects in high-voltage explosion-proof drives, offshore wind power, pumped storage and other fields.

[0003] The wound rotor structure has excellent harmonic suppression capabilities and design flexibility, ensuring efficient and stable operation of brushless doubly-fed motors. It has become the most widely used brushless doubly-fed motor technology to date. However, because the wound rotor structure requires the use of unequal turns and unequal pitches to adjust the rotor winding arrangement, it will lead to empty slots or uneven distribution of conductors within the slots, resulting in asymmetric internal mass of the motor. In actual operation, it is easy to cause dynamic eccentricity of the motor, which in turn can cause serious damage to the motor. In order to effectively avoid dynamic eccentricity failures in brushless doubly-fed motors without increasing system costs, a non-invasive diagnostic method for detecting dynamic eccentricity failures in brushless doubly-fed motors during operation is urgently needed.

[0004] Most existing technical documents only use finite element analysis to analyze the harmonic content of the motor air gap magnetic flux density, and need to rely on invasive means such as magnetic field detection coils to diagnose eccentricity faults. Even non-invasive detection methods are only applicable to static eccentricity faults of brushless doubly fed motors and cannot be used to detect dynamic eccentricity faults of brushless doubly fed motors. Summary of the Invention

[0005] To solve the above problems, the present invention provides a non-invasive detection method for the dynamic eccentricity fault of a brushless doubly-fed motor. By utilizing the special electromagnetic coupling principle of the brushless doubly-fed motor, the dynamic eccentricity fault of the brushless doubly-fed motor is diagnosed using the converter signal without adding additional sensors, effectively addressing the potential fault hazards of this type of motor due to the complex rotor topology.

[0006] To achieve the above object, the first aspect of the present invention discloses a method for diagnosing a short-circuit fault in a power winding of a brushless doubly-fed motor, comprising the following steps:

[0007] Based on the basic electromagnetic relationship of the brushless doubly-fed motor, when dynamic rotor eccentricity occurs, the fault characteristic frequency of the control winding of the motor connected to the inverter is calculated;

[0008] The motor current is detected using the FFT decomposition method. If a fault characteristic frequency signal appears, the current signal X(t) that changes with time in the converter directly connected to the control winding during a certain period of motor operation is recorded.

[0009] Perform dynamic signal decomposition on the current signal X(t) to obtain the natural mode function of the current signal;

[0010] The natural mode function of the current signal is fitted and compared with the curve under the non-eccentric working state. If the fitted curve is offset compared with the curve under the non-eccentric working state, it is determined that a dynamic eccentricity fault has occurred.

[0011] Preferably, the calculation of the control winding fault characteristic frequency is specifically as follows:

[0012] Calculate the air gap permeance when the brushless doubly-fed motor has dynamic eccentricity;

[0013] Multiply the air gap permeability by the magnetomotive force of the brushless doubly fed motor to obtain the harmonic magnetic field and calculate the magnetic induction intensity of the magnetic field;

[0014] The magnetic field harmonics caused by the dynamic eccentricity fault can be induced into the current frequency of the stator winding, and then the frequency of the dynamic eccentricity fault reaction to the time harmonics can be calculated.

[0015] Preferably, the air gap permeability can be expressed by the following formula:

[0016]

[0017] Where, is the air gap permeability, Λ a0 is the constant term when the motor is eccentric, a is the coefficient of the non-constant term, a is the harmonic order, ω r is the rotor rotation angular frequency.

[0018] Preferably, the magnetic induction intensity of the magnetic field can be expressed by the following formula:

[0019]

[0020] Where B p is the magnetic induction intensity of the power winding; B c To control the magnetic induction intensity of the winding; B 1p 、B 1c B p and B c The amplitude of p p is the number of power winding pole pairs; p c is the number of control winding pole pairs; ω p is the angular frequency of the rotating magnetic field of the power winding; ω c To control the angular frequency of the winding rotating magnetic field; The initial phase angle of the synthetic magnetomotive force of the main wave of the power winding; To control the initial phase angle of the winding main wave synthetic magnetomotive force, θ is the angle of the air gap circumferential space position, ω ε is the angular velocity of the eccentric air gap when the rotor rotates, and ε is the rotor eccentricity.

[0021] Preferably, the frequency of the time harmonics resulting from the dynamic eccentricity fault reaction can be expressed by the following formula:

[0022]

[0023] Where, f pε is the distortion frequency of the power winding frequency after the eccentricity fault, f cε To control the distortion frequency of the winding frequency after the eccentricity fault, f p is the power winding current frequency, f c To control the winding current frequency, p p is the number of power winding pole pairs, p c To control the number of winding pole pairs, s p and s c are the power winding and control winding slip rates respectively.

[0024] Preferably, the power winding slip rate s p and control winding slip s c It can be expressed by the following formula:

[0025]

[0026] Where, f p is the power winding current frequency, f c To control the winding current frequency, p p is the number of power winding pole pairs, p c To control the number of winding pole pairs, take a negative sign when the phase sequence of the power winding and the control winding is the same, otherwise take a positive sign.

[0027] Preferably, the dynamic signal decomposition of the current signal X(t) is specifically performed as follows:

[0028] Identify all the maximum and minimum points of the original signal, fit the extreme points, and form the upper bound X of the signal max (t) and the lower bound X min (t), calculate the average value m1(t) of the upper and lower bounds;

[0029] Subtract the original current signal X(t) from the average value of the upper and lower bounds m1(t) to obtain the remaining signal d1(t);

[0030] The remaining signal d1(t) is regarded as the new original signal X(t) to be processed, and the above steps are processed repeatedly until the first-order mode component NF1(t) is obtained;

[0031] Subtract the original signal X(t) from the first-order mode component NF1(t) to obtain the first-order residual y1(t). Replace X(t) with y1(t) and iterate m times until the standard deviation meets the set stop criterion and the m-th NF component is obtained. The m-th order mode function NF m (t) and the final residual amount y that meets the requirements m (t);

[0032] The original signal X(t) is decomposed and represented by a natural mode function and a residual.

[0033] Preferably, the standard deviation can be expressed as follows:

[0034]

[0035] Where SD is the standard deviation, d k-1 (t) and d k (t) are the time series of two continuous signals, and T represents the time span.

[0036] Preferably, the decomposed original signal X(t) can be expressed by the following formula:

[0037]

[0038] Where NF m is the mth natural mode function, y M is the original signal X(t) minus NF m The remaining amount after.

[0039] A second aspect of the present invention discloses a non-intrusive detection system for a dynamic eccentricity fault of a brushless doubly-fed motor, and the non-intrusive detection method for a dynamic eccentricity fault of a brushless doubly-fed motor described above is executed, comprising:

[0040] Frequency calculation module, used to calculate the fault characteristic frequency of the control winding of the motor connected to the inverter;

[0041] Current detection module, used to detect motor current through FFT decomposition method;

[0042] A signal decomposition module is used to dynamically decompose the motor's current signal;

[0043] The fault judgment module is used to detect the eccentricity fault and judge the severity of the eccentricity fault.

[0044] Beneficial effects of the present invention:

[0045] The application provides a non-invasive detection method for dynamic eccentricity fault of a brushless doubly-fed motor. BRIEF DESCRIPTION OF DRAWINGS

[0046] Figure 1 FIG. 1 is a flow chart of a non-invasive detection method for dynamic eccentricity fault of a brushless doubly-fed motor according to an embodiment of the application;

[0047] Figure 2 FIG. 2 is a structural block diagram of a brushless doubly-fed motor system according to an embodiment of the application; DETAILED DESCRIPTION

[0048] In order to make the objectives, technical solutions and advantages of the application clearer, the technical solutions of the application will be described clearly and completely below with reference to the drawings in the embodiments of the application. The embodiments described in the application are only a part of the embodiments of the application, but not all the embodiments. Based on the spirit of the application, other embodiments obtained by those skilled in the art without creative work fall within the protection scope of the application.

[0049] The application provides a non-invasive detection method for dynamic eccentricity fault of a brushless doubly-fed motor, which diagnoses the dynamic eccentricity fault of the brushless doubly-fed motor rotor by using the converter signal at the control winding side without adding additional sensors.

[0050] Figure 2 The structural block diagram of the brushless doubly-fed motor and the control system thereof provided in the embodiments of the application includes a brushless doubly-fed motor, a converter and a transformer. The brushless doubly-fed motor includes a stator and a rotor. The stator of the brushless doubly-fed motor includes a power winding and a control winding. The power winding is directly connected to a power grid, and the control winding is connected to the power grid in series through the converter.

[0051] The first embodiment of the application provides a non-invasive detection method for dynamic eccentricity fault of a brushless doubly-fed motor, as shown in FIG. 1, which specifically includes the following steps. Figure 1

[0052] Step 1: According to the basic electromagnetic relationship of the brushless doubly-fed motor, when the rotor dynamic eccentricity occurs, the fault characteristic frequency of the control winding connected to the converter of the motor is calculated. The specific calculation steps are as follows:

[0053] ​Step 1.1: When the motor has dynamic eccentricity, calculate the air gap permeance. The air gap permeance is a function of time and space and can be expressed by formula (1), as follows:

[0054]

[0055] Where, is the air gap permeability, Λ a0 is the constant term when the motor is eccentric, a is the coefficient of the non-constant term, a is the harmonic order, ω r is the rotor rotation angular frequency.

[0056] Step 1.2: The synthetic air gap magnetomotive force of the brushless doubly fed motor is formed by the superposition of multiple magnetomotive forces. The air gap permeability expression obtained in step 1.1 is multiplied by the magnetomotive force to obtain the harmonic magnetic field. The magnetic induction intensity of the magnetic field can be expressed by equations (2) and (3), as follows:

[0057]

[0058] Where B p is the magnetic induction intensity of the power winding; B c To control the magnetic induction intensity of the winding; B 1c B p and B c The amplitude of p p is the number of power winding pole pairs; p c is the number of control winding pole pairs; ω p is the angular frequency of the rotating magnetic field of the power winding; ω c To control the angular frequency of the winding rotating magnetic field; The initial phase angle of the synthetic magnetomotive force of the main wave of the power winding; To control the initial phase angle of the winding main wave synthetic magnetomotive force, θ is the angle of the air gap circumferential space position, ω ε is the angular velocity of the eccentric air gap when the rotor rotates, and ε is the rotor eccentricity.

[0059] In step 1.3, the magnetic field harmonics caused by the dynamic eccentricity fault can be induced into the current frequency of the stator winding, and then the expression of the dynamic eccentricity fault response to the time harmonic frequency is obtained, that is, the coefficient of the time term of the magnetic induction intensity in step 1.2. This expression can be expressed by equations (4) and (5), as follows:

[0060]

[0061] Where, f pε is the distortion frequency of the power winding frequency after the eccentricity fault; f cε To control the distortion frequency of the winding frequency after the eccentricity fault, p pis the number of power winding pole pairs, p c To control the number of winding pole pairs, s p and s c are the power winding and control winding slip rates, s p and s c It can be expressed by formula (6) and formula (7), as follows:

[0062]

[0063] Where, f p is the power winding current frequency, f c To control the winding current frequency, p p is the number of power winding pole pairs, p c To control the number of winding pole pairs, take a negative sign when the phase sequence of the power winding and the control winding is the same, otherwise take a positive sign.

[0064] For a brushless doubly-fed motor with 4 power winding poles and 8 control winding poles, when the motor speed is 700 r / min, the distortion frequencies caused by dynamic eccentricity can be calculated to be 50 Hz and 60 Hz.

[0065] As a prominent substantive feature of the present invention and one of the significant advances it brings to the prior art, the present invention proposes a non-invasive diagnostic method for the dynamic eccentricity fault of a brushless doubly-fed motor. Without the need for additional sensors, the present invention utilizes a current transformer connected to the motor control winding to extract the control winding current signal, performs data processing, establishes a mathematical model of the dynamic eccentricity fault of the brushless doubly-fed motor, and analyzes the changing patterns of the magnetic field and current.

[0066] Step 2: Use FFT decomposition method to detect the motor current. If the fault characteristic frequency signal f calculated in step 1 appears pε or f cε , then record the current signal X(t) that changes with time in the converter directly connected to the control winding during a certain period of motor operation;

[0067] Step 3: Perform dynamic signal decomposition on the current signal X(t) calculated in step 2 to obtain a natural mode function of the current signal.

[0068] In a preferred but non-limiting embodiment of the present invention,

[0069] Step 3.1: Identify all the maximum and minimum points of the original signal, fit these extreme points by curve interpolation method, and form the upper bound X of the signal. max (t) and the lower bound X min (t), its average value m1(t) can be expressed by formula (7), as follows:

[0070]

[0071] In step 3.2, the original signal X(t) is subtracted from the mean of the upper and lower bounds, m1(t), to obtain the remaining signal d1(t). Generally, for a stationary signal, this is the first mode function NF of the original signal X(t). However, for nonstationary signals, this function is not monotonic within a certain region and instead exhibits inflection points. If these inflection points, which reflect the specific characteristics of the original signal, are not included, then the first mode function is inaccurate. In other words, the remaining signal does not meet the conditions for a natural mode function, so further screening is required.

[0072] Step 3.3, treat the remaining signal d1(t) as the new original signal X(t) to be processed, and perform the above steps repeatedly until the first-order mode component NF1(t) that meets the conditions is obtained. Subtract the signal X(t) from the first-order mode component NF1(t) to obtain the first-order residual y1(t), and use y1(t) to replace X(t) and iterate m times until the standard deviation SD meets the set stopping standard and the m-th NF component is obtained. The m-th order mode function NF m (t) and the final residual amount y that meets the requirements m (t).

[0073] The stopping criterion can also be called the screening threshold, which is generally set between 0.2 and 0.3.

[0074] The standard deviation SD can be expressed by formula (8), as follows:

[0075]

[0076] Where SD is the standard deviation, d k-1 (t) and d k (t) are the time series of two continuous signals, and T represents the time span.

[0077] In step 3.4, the input signal is decomposed into several natural mode functions and a residual component, which can be expressed by formula (9):

[0078]

[0079] Where X(t) is the original signal, NF m is the mth natural mode function, y M is the original signal minus NF m The remaining amount after.

[0080] In step 4, after iterative dynamic signal decomposition, the time domain characteristics can be reflected in the current amplitude. The natural mode function NF of the current signal obtained in step 3 is fitted and compared with the current curve under the normal non-eccentric working state. If the fitting curve is offset compared with the current curve under the normal non-eccentric working state, and there are large changes at most peaks, it is judged that a dynamic eccentricity fault has occurred. At the same time, the degree of offset can be used as a criterion for judging the severity of the dynamic eccentricity fault.

[0081] As a prominent substantive feature of the present invention and one of the significant advances it brings to the prior art, the present invention extracts the fault characteristics of dynamic eccentricity from the control winding current signal, and through multiple iterations of dynamic signal decomposition, fits and compares it with the curve under the normal non-eccentric working state, and uses the degree of offset as the basis for judging the severity of the eccentricity fault.

[0082] A second embodiment of the present invention provides a non-intrusive detection system for a dynamic eccentricity fault of a brushless doubly-fed motor, which executes the non-intrusive detection method for a dynamic eccentricity fault of a brushless doubly-fed motor according to claim 1, comprising:

[0083] Frequency calculation module, used to calculate the fault characteristic frequency of the control winding of the motor connected to the inverter;

[0084] Current detection module, used to detect motor current through FFT decomposition method;

[0085] A signal decomposition module is used to dynamically decompose the motor's current signal;

[0086] The fault judgment module is used to detect the eccentricity fault and judge the severity of the eccentricity fault.

[0087] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

[0088] The present disclosure may be a system, method and / or computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present disclosure.

[0089] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. A non-intrusive detection method for dynamic eccentricity fault of a brushless doubly-fed motor, characterized in that: include: Based on the basic electromagnetic relationship of the brushless doubly-fed motor, when dynamic rotor eccentricity occurs, the fault characteristic frequency of the control winding of the motor connected to the inverter is calculated; The calculation of the control winding fault characteristic frequency is as follows: When the brushless doubly-fed motor has dynamic eccentricity, the air gap permeance is calculated; the air gap permeance can be expressed by the following formula: Where, is the air gap permeability, Λ a0 is the constant term when the motor is eccentric, a is the coefficient of the non-constant term, a is the harmonic order, ω r is the rotor rotation angular frequency; Multiply the air gap permeability by the magnetomotive force of the brushless doubly fed motor to obtain the harmonic magnetic field and calculate the magnetic induction intensity of the magnetic field; The magnetic induction intensity of the magnetic field can be expressed by the following formula: Where B p is the magnetic induction intensity of the power winding; B c To control the magnetic induction intensity of the winding; B 1p 、B 1c B p and B c The amplitude of p p is the number of power winding pole pairs; p c is the number of control winding pole pairs; ω p is the angular frequency of the rotating magnetic field of the power winding; ω c To control the angular frequency of the winding rotating magnetic field; The initial phase angle of the synthetic magnetomotive force of the main wave of the power winding; To control the initial phase angle of the winding main wave synthetic magnetomotive force, θ is the angle of the air gap circumferential space position, ω ε is the angular velocity of the eccentric air gap when the rotor rotates, and ε is the rotor eccentricity; The magnetic field harmonics caused by the dynamic eccentricity fault can be induced into the current frequency of the stator winding, and then the frequency of the dynamic eccentricity fault reaction to the time harmonics can be calculated; The motor current is detected using FFT decomposition. If a fault characteristic frequency signal appears, the current signal X(t) that changes with time in the converter directly connected to the control winding during a certain period of motor operation is recorded. Perform dynamic signal decomposition on the current signal X(t) to obtain the natural mode function of the current signal; The dynamic signal decomposition of the current signal X(t) is specifically as follows: Identify all the maximum and minimum points of the original signal, fit the extreme points, and form the upper bound X of the signal max (t) and the lower bound X min (t), calculate the average value m1(t) of the upper and lower bounds; Subtract the original current signal X(t) from the average value of the upper and lower bounds m1(t) to obtain the remaining signal d1(t); The remaining signal d1(t) is regarded as the new original signal X(t) to be processed, and the above steps are processed repeatedly until the first-order mode component NF1(t) is obtained; Subtract the original signal X(t) from the first-order mode component NF1(t) to obtain the first-order residual y1(t). Replace X(t) with y1(t) and iterate m times until the standard deviation meets the set stop criterion and the m-th NF component is obtained. The m-th order mode function NF m (t) and the final residual amount y that meets the requirements m (t); The standard deviation can be expressed as follows: Where SD is the standard deviation, d k-1 (t) and d k (t) are the time series of two continuous signals, T represents the time span; Decompose the original signal X(t) into a natural mode function and a residual; The decomposed original signal X(t) can be expressed by the following formula: Where NF m is the mth natural mode function, y M is the original signal X(t) minus NF m The remaining amount after The natural mode function of the current signal is fitted and compared with the curve under the non-eccentric working state. If the fitted curve is offset compared with the curve under the non-eccentric working state, it is determined that a dynamic eccentricity fault has occurred.

2. The non-intrusive detection method for a dynamic eccentricity fault of a brushless doubly-fed motor according to claim 1, wherein: The frequency of the time harmonics resulting from the dynamic eccentricity fault reaction can be expressed by the following formula: Where, f pε is the distortion frequency of the power winding frequency after the eccentricity fault, f cε To control the distortion frequency of the winding frequency after the eccentricity fault, f p is the power winding current frequency, f c To control the winding current frequency, p p is the number of power winding pole pairs, p c To control the number of winding pole pairs, s p and s c are the power winding and control winding slip rates respectively.

3. The non-intrusive detection method for a dynamic eccentricity fault of a brushless doubly-fed motor according to claim 2, wherein: Power winding slip s p and control winding slip s c It can be expressed by the following formula: Where, f p is the power winding current frequency, f c To control the winding current frequency, p p is the number of power winding pole pairs, p c To control the number of winding pole pairs, a negative sign is used when the phase sequence of the power winding and the control winding is the same, and a positive sign is used otherwise.

4. A non-intrusive detection system for a dynamic eccentricity fault of a brushless doubly-fed motor, which runs a non-intrusive detection method for a dynamic eccentricity fault of a brushless doubly-fed motor as claimed in claims 1 to 3, characterized in that: include: Frequency calculation module, used to calculate the fault characteristic frequency of the control winding of the motor connected to the inverter; Current detection module, used to detect motor current through FFT decomposition method; A signal decomposition module is used to dynamically decompose the motor's current signal; The fault judgment module is used to detect the eccentricity fault and judge the severity of the eccentricity fault.

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