Multi-parameter analysis and fault diagnosis method based on resolver output signal

Abstract

The application relates to the field of resolver fault detection, in particular to a multi-parameter analysis and fault diagnosis method based on a resolver output signal, which comprises the following steps: obtaining a target output signal of a diagnosis analysis target; determining whether to perform harmonic information processing or electric energy information processing according to a fluctuation amplitude index; when the harmonic information processing is performed, determining whether to perform harmonic component analysis or harmonic energy analysis according to a fluctuation characteristic recurrence index, determining recommended fault positioning information according to a dominant frequency state, and determining a fault radiation index according to the amplitudes of the frequency components corresponding to the target identification spectrum; when the electric energy information processing is performed, determining whether to send the recommended fault positioning information to a user based on a direct current resistance parameter and an insulation resistance parameter. The application realizes effective monitoring of a resolver and application equipment thereof based on the output signal of the resolver, reduces the demand for external monitoring, and improves the data analysis efficiency of the fault monitoring process.

Description

Technical Field

[0001] This invention relates to the field of rotary transformer fault detection, and in particular to a multi-parameter analysis and fault diagnosis method based on the output signal of a rotary transformer. Background Technology

[0002] Rotary transformers are widely used as precision angle sensors in servo systems and position detection. The reliability of fault monitoring and diagnosis for rotary transformers is crucial for the quality of actual detection. Current technologies for fault diagnosis of equipment using rotary transformers often rely on external sensors, increasing the complexity of the overall system. Furthermore, fault diagnosis for rotary transformers only assesses the amplitude of the output signal, failing to accurately locate or predict faults. Therefore, how to fully utilize the physical information contained in the output signal of a rotary transformer to effectively detect the fault status of rotary transformers and their application equipment, thereby reducing the need for external monitoring equipment in actual fault monitoring, is a problem that urgently needs to be solved by those skilled in the art.

[0003] Chinese Patent Application Publication No. CN118671469A discloses a signal fault diagnosis method, apparatus, computer equipment, and storage medium. The method includes: when a zero-crossing square wave corresponding to a zero-crossing detection circuit is detected to be within a preset period, controlling the zero-crossing detection circuit corresponding to a resolver to output a trigger signal; connecting the resolver to the zero-crossing detection circuit; acquiring the peak value and valley value of the resolver wave corresponding to the corresponding signal type based on the signal type of the resolver signal corresponding to the resolver and the transition type of the trigger signal; and determining the signal fault type of the resolver signal corresponding to the resolver based on the peak value, valley value, and preset voltage conditions. Chinese Patent Publication No. CN118795388A discloses a method and system for diagnosing eccentricity in a reluctance rotary transformer. The method includes acquiring the output voltage of two-phase signal windings at a fixed rotational speed of the rotary transformer under test; performing a Hilbert transform on the output voltage to obtain its envelope; performing a Fast Fourier Transform on the envelope of the output voltage to obtain the frequency domain characteristics of the output voltage envelope of the rotary transformer under test; and determining whether the rotary transformer has eccentricity and the type of eccentricity based on the frequency domain characteristics and preset parameters of the rotary transformer. However, the above solution has the following drawbacks: it fails to fully utilize the physical information contained in the output signal of the rotary transformer to effectively detect the fault status of the rotary transformer and its application equipment, resulting in a high demand for external monitoring data during actual fault monitoring. Summary of the Invention

[0004] To address this, the present invention provides a multi-parameter analysis and fault diagnosis method based on the output signal of a rotary transformer, which overcomes the problem that the existing technology fails to fully utilize the physical information contained in the output signal of the rotary transformer to effectively detect the fault status of the rotary transformer and its application equipment, resulting in a high demand for external monitoring data in the actual fault monitoring process.

[0005] To achieve the above objectives, the present invention provides a multi-parameter analysis and fault diagnosis method based on the output signal of a rotary transformer, comprising:

[0006] Initialize the acquisition parameters of the target output signal and continuously acquire the target output signal for diagnostic analysis;

[0007] The fluctuation amplitude index of the target output signal is periodically determined based on the determined synthetic voltage coefficient for each period, and the fluctuation amplitude index is used to determine whether to perform harmonic information processing or power information processing for the diagnostic analysis target.

[0008] When processing harmonic information, the recurrence index of wave characteristics is used to determine whether to perform harmonic component analysis or harmonic energy analysis on the target output signal.

[0009] The dominant frequency state is determined based on the dominant frequency component of the target identification spectrum, and the recommended fault location information of the diagnostic analysis equipment is determined based on the dominant frequency state. In addition, the fault radiation index of the diagnostic analysis equipment or the diagnostic analysis target is determined based on the amplitude of each frequency component corresponding to the target identification spectrum.

[0010] When processing electrical energy information, the DC resistance parameters and insulation resistance parameters of the diagnostic analysis target are used to determine whether to send recommended fault location information to the user.

[0011] Output a fault diagnosis report.

[0012] Furthermore, the fluctuation amplitude index of the diagnostic analysis target is periodically detected, and the fluctuation amplitude index is determined based on the synthetic voltage coefficient determined in each monitoring execution cycle.

[0013] The synthesized voltage coefficient is determined based on the sine voltage, cosine voltage, and excitation voltage corresponding to the target output signal in the diagnostic analysis.

[0014] Furthermore, when the fluctuation amplitude index of the diagnostic analysis target is greater than a preset fluctuation amplitude index, harmonic information processing is performed on the diagnostic analysis target, wherein...

[0015] The fluctuation feature reproduction index of the target output signal obtained for diagnostic analysis within the target analysis period is detected, and Fourier transform is performed to obtain the target recognition spectrum corresponding to the target analysis period.

[0016] The fluctuation characteristic reproduction index is determined based on the synthesized voltage coefficient and its timestamp for each determination.

[0017] Furthermore, when the fluctuation characteristic reproduction index is greater than the preset fluctuation characteristic reproduction index, harmonic component analysis is performed on the target output signal, wherein...

[0018] Based on the fundamental frequency, determine the multiple parameters corresponding to the frequency components present in the target identification spectrum, so as to determine the dominant frequency component corresponding to the target analysis period;

[0019] Recommended fault location information is determined by identifying the dominant frequency state corresponding to the target identification spectrum.

[0020] Furthermore, when the dominant frequency state corresponding to the target identification spectrum is a single frequency state, the recommended fault location information sent to the user is rotor radial eccentricity and rotor imbalance.

[0021] The dominant frequency state corresponding to the target recognition spectrum is the double frequency state, and the recommended fault location information sent to the user is that the coupling is misaligned.

[0022] The dominant frequency state corresponding to the target recognition spectrum is a high-order frequency state, and the recommended fault location information sent to the user is mechanical loosening;

[0023] The dominant frequency state corresponding to the target identification spectrum is a high-frequency dominant state, and the recommended fault location information sent to the user is bearing abnormality.

[0024] Furthermore, when the fluctuation characteristic reproduction index is less than or equal to the preset fluctuation characteristic reproduction index or when harmonic component analysis is completed, harmonic energy analysis is performed on the target output signal, wherein...

[0025] The harmonic cumulative energy parameter is determined based on the amplitude of each frequency component present in the target identification spectrum.

[0026] Furthermore, the fault radiation index is determined based on the cumulative energy assessment parameters and the cumulative energy rise parameters;

[0027] The fault radiation index is positively correlated with both the cumulative energy assessment parameter and the cumulative energy rise parameter.

[0028] Furthermore, when the stage evaluation anomaly index corresponding to the target analysis cycle is greater than the preset stage evaluation anomaly index, a reference setting anomaly prompt for the excitation voltage is sent to the user.

[0029] The stage assessment anomaly index is determined based on the cumulative energy assessment parameters and fluctuation amplitude assessment parameters corresponding to the target analysis period.

[0030] Furthermore, when the fluctuation amplitude index of the diagnostic analysis target is less than or equal to a preset fluctuation amplitude index, power information processing is performed on the diagnostic analysis target, wherein...

[0031] High voltage testing and DC resistance detection are performed on the target of diagnostic analysis to obtain the DC resistance parameters and insulation resistance parameters of the target.

[0032] If the DC resistance change parameter or insulation resistance parameter obtained for the diagnostic analysis target is not within the corresponding preset threshold range, the recommended fault location information sent to the user indicates that the diagnostic analysis target has an electrical performance abnormality.

[0033] Furthermore, the fault diagnosis report includes: recommended fault location information, fault radiation index, and fault determination time.

[0034] Compared with the prior art, the beneficial effects of the present invention are that the technical solution of the present invention effectively assesses the fault status of the rotary transformer itself and its application equipment by performing in-depth analysis of the output signal of the rotary transformer. Furthermore, the harmonic components present in the output signal are effectively combined during the fault assessment process, making full use of the information value present in the output signal, reducing the need for external fault monitoring data of the rotary transformer itself and its application equipment, thereby improving the data analysis efficiency in the actual fault monitoring process. The present invention improves the data analysis efficiency while ensuring the quality of fault monitoring of the rotary transformer itself and its application equipment.

[0035] Furthermore, this invention performs targeted calculations on the output signal of the rotary transformer to obtain the corresponding synthetic voltage coefficient, and determines whether there is a fault or anomaly by analyzing the fluctuation of the synthetic voltage coefficient. The fluctuation of the synthetic voltage coefficient characterizes the air gap change between the rotor and stator. By evaluating the fluctuation of the synthetic voltage coefficient corresponding to the output signal of the rotary transformer, it is possible to effectively respond to the current fault situation. This avoids the problem of traditional methods that only monitor the amplitude of the output signal of the rotary transformer or perform single harmonic analysis, resulting in a single information dimension and inability to effectively utilize the physical information in the output signal. This invention achieves effective utilization of the output signal of the rotary transformer itself, thereby reducing the need for external monitoring.

[0036] Furthermore, this invention determines whether to perform harmonic component analysis or harmonic energy analysis on the target output signal based on the fluctuation feature reproducibility index. The fluctuation feature reproducibility index characterizes whether the fluctuation features of the synthetic voltage coefficient of the target output signal within the target analysis period have a strong degree of reproducibility. Since the fluctuation features of the synthetic voltage coefficient corresponding to faults in the rotary transformer and its application equipment are different, the fault location is initially classified by the reproducibility of the fluctuation of the synthetic voltage coefficient, and targeted analysis is performed accordingly. This enables effective differentiation and parallel monitoring of mechanical and electrical faults in the rotary transformer and its application equipment. The fault monitoring process performs targeted analysis under different conditions, further improving data analysis efficiency. This invention improves the coverage and effectiveness of fault diagnosis, ensuring that the health status of the rotary transformer and its connected equipment can be assessed simultaneously.

[0037] Furthermore, in this invention, when the fluctuation feature recurrence index is greater than the preset fluctuation feature recurrence index, harmonic component analysis is performed. Since the fluctuation feature of the synthesized voltage coefficient of the target output signal has a strong recurrence degree, that is, it has a certain periodic recurrence, the fault factors causing the fluctuation of the synthesized voltage coefficient are more likely to be concentrated in the equipment used by the rotary transformer. This causes the output signal to produce periodic fluctuations that are synchronized with the mechanical fault frequency of the equipment. Further fault feature matching is performed based on the frequency components present in the target identification spectrum to locate the fault in the equipment used by the rotary transformer. This invention achieves effective utilization of the output signal of the rotary transformer itself.

[0038] Furthermore, in this invention, when the fluctuation characteristic reproduction index is less than or equal to the preset fluctuation characteristic reproduction index or when harmonic component analysis is completed, harmonic energy analysis is performed to quantify the degree of impact on the faults existing in the diagnostic analysis equipment or diagnostic analysis target. In addition, the rationality of the setting of the reference value of the excitation voltage on which the synthesis voltage coefficient is based is evaluated by combining the obtained cumulative energy assessment parameters with the fluctuation amplitude assessment parameters. This further improves the utilization of the output signal of the rotary transformer and reduces the need for external monitoring data in the fault monitoring process of the rotary transformer itself and its application equipment. Attached Figure Description

[0039] Figure 1 This is a schematic diagram of the multi-parameter analysis and fault diagnosis method based on the output signal of a rotary transformer according to the present invention;

[0040] Figure 2 This is a flowchart illustrating the present invention's method for determining whether to perform harmonic information processing or power information processing on a diagnostic analysis target based on a fluctuation amplitude index.

[0041] Figure 3 This is a flowchart illustrating the present invention for determining whether to perform harmonic component analysis or harmonic energy analysis on the target output signal based on the wave characteristic reproducibility index.

[0042] Figure 4 This is a flowchart illustrating the process of determining whether to send a reference setting anomaly alert to the user based on a stage-based assessment anomaly index. Detailed Implementation

[0043] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0044] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0045] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0046] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0047] Please see Figures 1 to 4 As shown, this invention provides a multi-parameter analysis and fault diagnosis method based on the output signal of a rotary transformer, including:

[0048] Initialize the acquisition parameters of the target output signal and continuously acquire the target output signal for diagnostic analysis;

[0049] The fluctuation amplitude index of the target output signal is periodically determined based on the determined synthetic voltage coefficient for each period, and the fluctuation amplitude index is used to determine whether to perform harmonic information processing or power information processing for the diagnostic analysis target.

[0050] When processing harmonic information, the recurrence index of wave characteristics is used to determine whether to perform harmonic component analysis or harmonic energy analysis on the target output signal.

[0051] The dominant frequency state is determined based on the dominant frequency component of the target identification spectrum, and the recommended fault location information of the diagnostic analysis equipment is determined based on the dominant frequency state. In addition, the fault radiation index of the diagnostic analysis equipment or the diagnostic analysis target is determined based on the amplitude of each frequency component corresponding to the target identification spectrum.

[0052] When processing electrical energy information, the DC resistance parameters and insulation resistance parameters of the diagnostic analysis target are used to determine whether to send recommended fault location information to the user.

[0053] Output a fault diagnosis report.

[0054] This invention is used for continuous fault monitoring of rotary transformers and the equipment used in them, and outputs a fault diagnosis report. The rotary transformer being monitored is designated as the diagnostic analysis target, and the equipment used in the diagnostic analysis target is designated as the diagnostic analysis equipment. In this invention, fault monitoring is completed by analyzing the output signal of the diagnostic analysis target. The output signal of the diagnostic analysis target is designated as the target output signal. The acquisition parameters of the target output signal are initialized and configured, and the sampling frequency and sampling precision of the target output signal are set. This is content that is easy for those skilled in the art to understand and will not be elaborated here. A value for the sampling frequency and sampling precision of the target output signal is provided, with the sampling frequency set to 100kHz and the sampling precision set to 16 bits.

[0055] This invention utilizes several fault monitoring records. Each fault monitoring record records at least one instance of fault monitoring for the diagnostic analysis target and its corresponding diagnostic analysis equipment, including fluctuation amplitude index, fluctuation characteristic recurrence index, amplitude difference index, harmonic cumulative energy parameter, stage evaluation anomaly index, and DC resistance change parameter. Each fault monitoring record also has a corresponding qualification mark. The qualification mark indicates whether the quality and efficiency of fault monitoring for the diagnostic analysis target and its corresponding diagnostic analysis equipment meet the user's requirements. It is understood that the user can determine whether the quality and efficiency of fault monitoring for the diagnostic analysis target and its corresponding diagnostic analysis equipment meet the user's requirements based on self-defined indicators.

[0056] Specifically, the fluctuation amplitude index of the diagnostic analysis target is periodically detected, and the fluctuation amplitude index is determined based on the synthetic voltage coefficient determined in each monitoring execution cycle.

[0057] The synthesized voltage coefficient is determined based on the sine voltage, cosine voltage, and excitation voltage corresponding to the target output signal in the diagnostic analysis.

[0058] In this invention, a monitoring execution cycle is applied. The duration of the monitoring execution cycle can be determined by the user. The higher the user's requirements for the fault monitoring quality and analysis efficiency of the diagnostic analysis target and its corresponding diagnostic analysis equipment, the shorter the duration of the monitoring execution cycle. A monitoring execution cycle duration of 5 seconds is provided. At the end of each monitoring execution cycle, the fluctuation amplitude index of the diagnostic analysis target is detected.

[0059] During the process of acquiring and analyzing the target output signal, the output voltage and phase signals of the rotary transformer are acquired through a high-speed sampling decoder. The acquired signals are filtered to remove interference signals, and a Fourier transform is performed on the filtered signals to obtain the corresponding frequency domain signal characteristics. If the current time is the end time of a monitoring execution cycle, this monitoring execution cycle is recorded as the target analysis cycle. The fluctuation amplitude index corresponding to the target being analyzed within this monitoring execution cycle is detected. , This represents the average value of the synthesized voltage coefficients determined for each diagnostic analysis target within the target analysis cycle. This refers to the maximum value of the synthesized voltage coefficient determined for each diagnostic analysis target within the target analysis cycle. The minimum value of the synthesized voltage coefficient determined for each diagnostic analysis target within the target analysis cycle, and the synthesized voltage coefficient for a single acquisition of the output voltage of the diagnostic analysis target. This refers to the value of the sinusoidal voltage obtained for the diagnostic analysis target. This refers to the value of the cosine voltage obtained for the diagnostic analysis target. This is the current reference value for the excitation voltage. When the reference value for the excitation voltage is initially set, the reference value for the excitation voltage is the rated excitation voltage of the diagnostic analysis target. Each determined composite voltage coefficient has its own timestamp, and the time corresponding to the timestamp is the time when the corresponding sine and cosine voltage values ​​are obtained.

[0060] This invention determines the potential for faults in the diagnostic analysis target and its equipment based on fluctuations in the synthesized voltage coefficient determined for the diagnostic analysis target. In the absence of mechanical faults, the calculated synthesized voltage coefficient remains constant regardless of the rotor's rotation angle. However, when the rotor experiences radial static or dynamic eccentricity, the air gap between the rotor and stator becomes non-uniform. The size of this air gap directly affects the magnetic permeability of the magnetic circuit; smaller gaps result in larger permeability, and vice versa. This change in permeability directly impacts the electromagnetic coupling coefficient between the excitation winding and the sine and cosine windings, causing the transformer ratio to change from a constant to a function of the motor's mechanical angle. The determination of the synthesized voltage coefficient eliminates variables related to angle decoding through mathematical calculations, extracting a physical quantity that should be constant under normal conditions. Fluctuations in this quantity directly reveal changes in electromagnetic parameters caused by mechanical faults, thus enabling electrical monitoring of the mechanical state.

[0061] Specifically, when the fluctuation amplitude index of the diagnostic analysis target is greater than a preset fluctuation amplitude index, harmonic information processing is performed on the diagnostic analysis target, wherein...

[0062] The fluctuation feature reproduction index of the target output signal obtained for diagnostic analysis within the target analysis period is detected, and Fourier transform is performed to obtain the target recognition spectrum corresponding to the target analysis period.

[0063] The fluctuation characteristic reproduction index is determined based on the synthesized voltage coefficient and its timestamp for each determination.

[0064] If the fluctuation amplitude index of the diagnostic analysis target for the target analysis period is greater than the preset fluctuation amplitude index, it indicates that the target output signal obtained within the target analysis period can characterize the fault problems existing in the diagnostic analysis target and its diagnostic analysis equipment. Therefore, by performing harmonic information processing on the target output signal obtained within the target analysis period, the fault factors existing in the diagnostic analysis target and its diagnostic analysis equipment can be further determined. The fluctuation characteristic recurrence index characterizes whether the fluctuation of the synthetic voltage coefficient determined within the target analysis period has periodic recurrence, thereby distinguishing whether the existing fault problems are caused by the diagnostic analysis target or by the fault of the diagnostic analysis equipment.

[0065] When processing harmonic information, a Fourier transform is performed on the acquired target output signal. How to perform the Fourier transform (FFT) is a topic well understood by those skilled in the art and will not be elaborated upon here. When performing fluctuation characteristic reproduction index detection on the target output signal acquired for diagnostic analysis within the target analysis period, the synthesized voltage coefficients determined for each diagnostic analysis within the target analysis period are arranged based on their corresponding timestamps to form a numerical curve of the synthesized voltage coefficients for the target analysis period. The fluctuation characteristic reproduction index is defined based on the maximum and minimum points of the numerical curve of the synthesized voltage coefficients corresponding to the target analysis period. , The recurrence interval difference index corresponding to the maximum point. The index representing the recurrence interval difference at the minimum point is given by the following formula: If the value is 0, the volatility characteristic recurrence index is recorded as 1, where the recurrence interval difference index corresponding to the maximum point is... , The average time interval between the timestamps corresponding to any two adjacent maximum points of the numerical curve of the synthesized voltage coefficient corresponding to the target analysis period is given. The standard deviation between the time intervals between two adjacent maxima and minima is analyzed for the numerical curve of the synthesized voltage coefficient corresponding to the target analysis period. , The average time interval between the timestamps corresponding to any two adjacent minimum points on the numerical curve of the synthesized voltage coefficient corresponding to the target analysis period. The standard deviation between the time intervals between two adjacent minimum points of the numerical curve of the synthetic voltage coefficient corresponding to the target analysis period, and how to determine the maximum and minimum points of the numerical curve, are contents that are known to those skilled in the art and will not be elaborated here.

[0066] The value of the preset fluctuation amplitude index can be determined by the user according to the actual working scenario. For example, the user can set it according to the fault monitoring record. The higher the user's requirements for the fault monitoring quality and analysis efficiency of the diagnostic analysis target and its corresponding diagnostic analysis equipment, the smaller the value of the preset fluctuation amplitude index. A method for determining the value of the preset fluctuation amplitude index is provided, in which the fault monitoring record for harmonic information processing of the target output signal of the diagnostic analysis target is recorded as the harmonic analysis record, and the minimum value of the fluctuation amplitude index in the harmonic analysis record that meets the user's requirements for the fault monitoring quality and analysis efficiency of the diagnostic analysis target and its corresponding diagnostic analysis equipment is recorded as the preset fluctuation amplitude index.

[0067] Specifically, when the fluctuation characteristic reproduction index is greater than the preset fluctuation characteristic reproduction index, harmonic component analysis is performed on the target output signal, wherein...

[0068] Based on the fundamental frequency, determine the multiple parameters corresponding to the frequency components present in the target identification spectrum, in order to determine the dominant frequency component corresponding to the target analysis period, and in order to determine the dominant frequency state corresponding to the target identification spectrum.

[0069] Recommended fault location information is determined by identifying the dominant frequency state corresponding to the target identification spectrum.

[0070] Specifically, when the dominant frequency state corresponding to the target identification spectrum is a single frequency state, the recommended fault location information sent to the user is rotor radial eccentricity and rotor imbalance.

[0071] The dominant frequency state corresponding to the target recognition spectrum is the double frequency state, and the recommended fault location information sent to the user is that the coupling is misaligned.

[0072] The dominant frequency state corresponding to the target recognition spectrum is a high-order frequency state, and the recommended fault location information sent to the user is mechanical loosening;

[0073] The dominant frequency state corresponding to the target identification spectrum is a high-frequency dominant state, and the recommended fault location information sent to the user is bearing abnormality.

[0074] If the fluctuation feature recurrence index is greater than the preset fluctuation feature recurrence index, it indicates that the fluctuation feature of the synthesized voltage coefficient of the target output signal within the target analysis period has a strong degree of recurrence, that is, it has a certain periodic recurrence. At this time, the fault factors causing the fluctuation of the synthesized voltage coefficient are more likely concentrated in the diagnostic analysis equipment. The diagnostic analysis target is sensed as a high-precision measurement probe, causing the output signal to produce periodic fluctuations that are synchronized with the mechanical fault frequency corresponding to the diagnostic analysis equipment. Therefore, harmonic component analysis is performed on the target output signal obtained within the target analysis period. During the harmonic component analysis, the dominant frequency component is determined according to the amplitude corresponding to each frequency component in the target identification spectrum, and the multiple parameters corresponding to the frequency component are determined based on the fundamental frequency. The rotation speed of the rotor corresponding to the diagnostic analysis equipment and the diagnostic analysis target is consistent, and the rotation speed of the rotor corresponding to the diagnostic analysis equipment and the diagnostic analysis target is recorded as the reference analysis parameter. The fundamental frequency... , As the baseline analysis parameter, for a single frequency component, the multiple parameter... The harmonic frequency corresponding to this frequency component is: the first harmonic component is the frequency component with a harmonic parameter of 1, the second harmonic component is the frequency component with a harmonic parameter of 2, and the third harmonic component is the frequency component with a harmonic parameter of 3.

[0075] The dominant frequency state includes a single-frequency state, a double-frequency state, a high-frequency state, and a high-frequency dominant state. If only one frequency component is the dominant frequency component in the target identification spectrum, then the dominant frequency state corresponding to the target identification spectrum is determined to be a single-frequency state. If the amplitude of the one-frequency component is greater than the amplitudes of all other frequency components, and the amplitude difference index of the one-frequency component relative to all other frequency components is greater than a preset amplitude difference index, then the one-frequency component is determined to be the dominant frequency component. For any two frequency components, the amplitude difference index... , It is the absolute value of the difference between the amplitudes corresponding to the two frequency components mentioned above. The value is the average of the amplitudes corresponding to the two frequency components mentioned above. If only the second-order frequency component is the dominant frequency component in the target recognition spectrum, then the dominant frequency state of the target recognition spectrum is determined to be the second-order frequency state. If the amplitude of the second-order frequency component is greater than the amplitudes of all other frequency components, and the amplitude difference index of the second-order frequency component relative to all other frequency components is greater than the preset amplitude difference index, then the second-order frequency component is determined to be the dominant frequency component. If the third-order frequency component or a frequency component with a larger corresponding multiple parameter is the dominant frequency component in the target recognition spectrum, then the dominant frequency state of the target recognition spectrum is determined to be the high-order frequency state. If the amplitude difference index between the other frequency components and the third-order frequency component or a frequency component with a larger corresponding multiple parameter is greater than the preset amplitude, then the dominant frequency state of the target recognition spectrum is determined to be the high-order frequency state. If the frequency component of the difference index is determined, then the frequency component with a frequency three times greater or the corresponding multiple parameter with a larger value is determined to be the dominant frequency component. If there is a high-frequency component as the dominant frequency component in the target identification spectrum, then the dominant frequency state corresponding to the target identification spectrum is determined to be a high-frequency dominant state. If the amplitude of the high-frequency component is greater than the amplitude of all other frequency components and there is a frequency component among the other frequency components whose amplitude difference index with the high-frequency component is greater than the preset amplitude difference index, then the high-frequency component is determined to be the dominant frequency component. The high-frequency component is the frequency component whose corresponding frequency is greater than the preset high-frequency parameter. The value of the preset high-frequency parameter can be set by the user according to the actual situation. A value of the preset high-frequency parameter is provided when the fundamental frequency is 50Hz, and the value of the preset high-frequency parameter is 500Hz.

[0076] If the dominant frequency state corresponding to the target identification spectrum is a single frequency state, the recommended fault location information sent to the user is rotor radial eccentricity and rotor imbalance. When the rotor is unbalanced, due to uneven mass distribution, the rotor's center of gravity does not coincide with the geometric center. Every time the rotor rotates, the unbalanced mass generates a centrifugal force excitation, and the frequency corresponds exactly to a single frequency separation. When the rotor is radially eccentric, the rotor's geometric center does not coincide with the stator center, resulting in uneven air gap. Every time the rotor rotates, the air gap undergoes a periodic change from minimum to maximum, and the modulation frequency of the electromagnetic field corresponds exactly to a single frequency separation.

[0077] If the dominant frequency state corresponding to the target identification spectrum is the double frequency state, the recommended fault location information sent to the user is that the coupling is misaligned. When there is parallel misalignment or angular misalignment between two connecting shafts (such as motor shaft and load shaft), the coupling will generate periodic bending moment during rotation. For each revolution of the rotor, the coupling will experience two "tension-compression" cycles. Therefore, the double frequency component will be prominent in the spectrum.

[0078] If the dominant frequency state corresponding to the target identification spectrum is a high-harmonic frequency state, the recommended fault location information sent to the user is mechanical loosening. When mechanical loosening exists, gaps will be generated between components. When rotating, the parts will have tiny collisions, separations and re-contacts within the gaps. The above process is a non-linear vibration that will generate rich harmonics, i.e. integer multiples of the rotation frequency. Therefore, when it is in a high-harmonic frequency state, the user is prompted that mechanical loosening has occurred.

[0079] If the dominant frequency state corresponding to the target identification spectrum is high frequency dominant state, the recommended fault location information sent to the user is bearing abnormality. Bearings (inner ring, outer ring, balls, cage) have inherent fault frequencies determined by their geometry. These frequencies are usually much higher than the rotation frequency. When the bearing suffers damage such as pitting or spalling, the rolling elements will generate periodic high-frequency impact pulses when they roll over the damage point. Therefore, when it is in high frequency dominant state, the user is prompted that a bearing abnormality has occurred.

[0080] The values ​​of the preset fluctuation feature reproduction index and the preset amplitude difference index can be determined by the user according to the actual working scenario. For example, the user can set them based on fault monitoring records. The higher the user's requirements for the quality and efficiency of fault monitoring and analysis of the diagnostic analysis target and its corresponding diagnostic analysis equipment, the larger the value of the preset amplitude difference index. A method for determining the value of the preset fluctuation feature reproduction index is provided, in which fault monitoring records that perform harmonic component analysis on the target output signal are recorded as component analysis records, and the minimum value of the fluctuation feature reproduction index in the component analysis records that meet the user's requirements for the quality and efficiency of fault monitoring and analysis of the diagnostic analysis target and its corresponding diagnostic analysis equipment is recorded as the preset fluctuation feature reproduction index. A method for determining the value of the preset amplitude difference index is provided, in which the average value of the amplitude difference index of the dominant frequency component relative to other frequency components in the component analysis records that meet the user's requirements for the quality and efficiency of fault monitoring and analysis of the diagnostic analysis target and its corresponding diagnostic analysis equipment is recorded as the preset amplitude difference index.

[0081] Specifically, when the fluctuation characteristic reproduction index is less than or equal to the preset fluctuation characteristic reproduction index or when harmonic component analysis is completed, harmonic energy analysis is performed on the target output signal, wherein...

[0082] The harmonic cumulative energy parameter is determined based on the amplitude of each frequency component present in the target identification spectrum.

[0083] Specifically, the fault radiation index is determined based on the cumulative energy assessment parameters and the cumulative energy rise parameters;

[0084] The fault radiation index is positively correlated with both the cumulative energy assessment parameter and the cumulative energy rise parameter.

[0085] If the fluctuation feature reproduction index is less than or equal to the preset fluctuation feature reproduction index, it indicates that the reproduction degree of the fluctuation feature of the synthetic voltage coefficient of the target output signal within the target analysis period is weak. Since the rotary transformer itself has a fault, what is affected is the electrical characteristics of the rotary transformer as a sensor. At this time, the fluctuation of the synthetic voltage coefficient of the target output signal is holistic and non-periodic. The recommended fault location information sent to the user at this time is that the target itself has a fault. By performing harmonic energy analysis on the target output signal when the fluctuation feature reproduction index is less than or equal to the preset fluctuation feature reproduction index or when harmonic component analysis is completed, the influence of the fault on the diagnostic analysis equipment or the diagnostic analysis target is quantified. The cumulative harmonic energy parameter corresponding to the target analysis period is the sum of the squares of the amplitudes of all frequency components other than the fundamental frequency in the target identification spectrum corresponding to the target analysis period.

[0086] The fault radiation index corresponding to the target analysis cycle is the sum of the products of the cumulative energy assessment parameter and the cumulative energy rise parameter, respectively, and their corresponding radiation assessment coefficients. The cumulative energy assessment parameter... The harmonic cumulative energy parameters are determined for the target analysis period. The cumulative energy rise parameter is a preset harmonic cumulative energy parameter. The harmonic cumulative energy parameters are determined for the target analysis period. The preset harmonic cumulative energy parameter is determined for the previous monitoring execution cycle of the target analysis cycle. The value of this preset harmonic cumulative energy parameter can be determined by the user based on the actual working scenario. For example, the user can set it based on fault monitoring records. The higher the user's requirements for the quality and efficiency of fault monitoring and analysis of the diagnostic analysis target and its corresponding diagnostic analysis equipment, the smaller the value of the preset harmonic cumulative energy parameter. A method for determining the preset harmonic cumulative energy parameter is provided, where the minimum value of the harmonic cumulative energy parameter in the component analysis records that meets the user's requirements for the quality and efficiency of fault monitoring and analysis of the diagnostic analysis target and its corresponding diagnostic analysis equipment is recorded as the preset harmonic cumulative energy parameter. The values ​​of the cumulative energy evaluation parameter and the radiation evaluation coefficient corresponding to the cumulative energy rise parameter can be determined by the user based on the actual working scenario. For example, the user can set it based on fault monitoring records. A value of 0.5 is provided for the cumulative energy evaluation parameter and the radiation evaluation coefficient corresponding to the cumulative energy rise parameter.

[0087] Specifically, when the stage evaluation anomaly index corresponding to the target analysis cycle is greater than the preset stage evaluation anomaly index, a reference setting anomaly prompt for the excitation voltage is sent to the user.

[0088] The stage assessment anomaly index is determined based on the cumulative energy assessment parameters and fluctuation amplitude assessment parameters corresponding to the target analysis period.

[0089] In the process of harmonic information processing of the target output signal for diagnostic analysis, the actual value of the excitation voltage of the target itself may vary due to external influences, which may lead to deviations in the determination of the synthetic voltage coefficient. Abnormal fluctuations in the synthetic voltage coefficient may originate from mechanical faults or electrical reference value setting problems. Meanwhile, the cumulative harmonic energy mainly reflects signal distortion caused by mechanical vibration. When these two indicators contradict each other, it is necessary to evaluate the rationality of the reference value setting of the excitation voltage. The stage evaluation anomaly index is used to characterize the degree of fluctuation of the synthetic voltage coefficient and the degree of contradiction of the cumulative harmonic energy parameters. When completing the harmonic energy analysis, the stage evaluation anomaly index is detected. If the stage evaluation anomaly index is large, an abnormal reference setting prompt for the excitation voltage is sent to the user, and the actual value of the excitation voltage needs to be detected.

[0090] The abnormal index of the stage assessment corresponding to the target analysis cycle , The parameters for evaluating the fluctuation range corresponding to the target analysis period are: The cumulative energy assessment parameters and fluctuation amplitude assessment parameters are for the target analysis period. , The volatility index determined for the target analysis period. For the preset volatility index, if it is If the stage evaluation anomaly index is 1, then the value of the preset stage evaluation anomaly index can be determined by the user according to the actual working scenario. For example, the user can set it according to the fault monitoring record. The higher the user's requirements for the fault monitoring quality and analysis efficiency of the diagnostic analysis target and its corresponding diagnostic analysis equipment, the smaller the value of the preset stage evaluation anomaly index. A method for determining the value of the preset stage evaluation anomaly index is provided, in which the fault monitoring record that sends the reference setting anomaly prompt to the user for the excitation voltage is recorded as the excitation anomaly record, and the minimum value of the stage evaluation anomaly index among the excitation anomaly records that meets the user's requirements for the fault monitoring quality and analysis efficiency of the diagnostic analysis target and its corresponding diagnostic analysis equipment is recorded as the preset stage evaluation anomaly index.

[0091] Specifically, when the fluctuation amplitude index of the diagnostic analysis target is less than or equal to a preset fluctuation amplitude index, power information processing is performed on the diagnostic analysis target, wherein...

[0092] High voltage testing and DC resistance detection are performed on the target of diagnostic analysis to obtain the DC resistance parameters and insulation resistance parameters of the target.

[0093] If the DC resistance change parameter or insulation resistance parameter obtained for the diagnostic analysis target is not within the corresponding preset threshold range, the recommended fault location information sent to the user indicates that the diagnostic analysis target has an electrical performance abnormality.

[0094] If the fluctuation amplitude index of the diagnostic analysis target is less than or equal to the preset fluctuation amplitude index, it indicates that the target output signal obtained within the target analysis period fails to characterize the fault problems of the diagnostic analysis target and its diagnostic analysis equipment. Therefore, it is necessary to perform power information processing on the diagnostic analysis target. By detecting the power-related parameters of the diagnostic analysis target, the fault anomaly can be further judged. How to perform high voltage testing and DC resistance testing on the diagnostic analysis target is a topic already mastered by those skilled in the art and will not be elaborated here.

[0095] The DC resistance change parameter , The DC resistance value determined for the diagnostic analysis target is the target analysis cycle. For the DC resistance value determined for the diagnostic analysis target in the previous monitoring execution cycle of the target analysis cycle, if the DC resistance change parameter is greater than the preset DC resistance change parameter, it is determined that the DC resistance change parameter is not within the corresponding preset threshold range. If the insulation resistance parameter is less than or equal to the preset insulation resistance parameter, it is determined that the insulation resistance parameter is not within the corresponding preset threshold range. The values ​​of the preset DC resistance change parameter and the preset insulation resistance parameter can be determined by the user according to the actual working scenario. For example, the user can set them according to the fault monitoring records. The higher the user's requirements for the fault monitoring quality and analysis efficiency of the diagnostic analysis target and its corresponding diagnostic analysis equipment, the smaller the value of the preset DC resistance change parameter. This provides a preset DC resistance change parameter... The parameter value selection method is as follows: the fault monitoring record of the electrical performance abnormality of the diagnostic analysis target, which is the recommended fault location information sent to the user, is recorded as the electrical reference record. The minimum value of the DC resistance change parameter in the electrical reference record that meets the user's requirements for the fault monitoring quality and analysis efficiency of the diagnostic analysis target and its corresponding diagnostic analysis equipment is recorded as the preset DC resistance change parameter. A preset DC resistance change parameter value of 0.05 is provided. The preset insulation resistance parameter value needs to be set according to the actual working scenario, which is easy for those skilled in the art to understand. A preset insulation resistance parameter value of 100MΩ is provided when the DC voltage used for testing is 500V.

[0096] Specifically, the fault diagnosis report includes: recommended fault location information, fault radiation index, and fault determination time.

[0097] When recommended fault location information is determined, a fault diagnosis report is output to the user, which includes the determined recommended fault location information, fault radiation index, and fault determination time. When outputting recommended fault location information, the fault radiation index can be output simultaneously, and the fault determination time is the time when the recommended fault location information is determined.

[0098] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. A method for multi-parameter analysis and fault diagnosis based on resolver output signals, characterized in that The method comprises the following steps: initializing the acquisition parameters of the target output signal, and continuously acquiring the target output signal of the diagnostic analysis target; periodically determining the fluctuation amplitude index of the target output signal according to the determined synthetic voltage coefficients each time, and determining whether to perform harmonic information processing or electric energy information processing on the diagnostic analysis target according to the fluctuation amplitude index; when performing harmonic information processing, determining whether to perform harmonic component analysis or harmonic energy analysis on the target output signal according to the fluctuation characteristic recurrence index, wherein, determining the dominant frequency state according to the dominant frequency component of the target identification spectrum, and determining the recommended fault positioning information of the diagnostic analysis device according to the dominant frequency state, and determining the fault radiation index of the diagnostic analysis device or the diagnostic analysis target according to the amplitude corresponding to each frequency component corresponding to the target identification spectrum; when performing electric energy information processing, determining whether to send the recommended fault positioning information to the user based on the direct current resistance parameter and the insulation resistance parameter of the diagnostic analysis target; outputting a fault diagnosis report; a synthetic voltage coefficient for a single acquisition of an output voltage for a diagnostic analysis target a value of a sine voltage acquired for the single acquisition of the diagnostic analysis target, a value of a cosine voltage acquired for the single acquisition of the diagnostic analysis target, a reference value set for the field voltage, the reference value set for the field voltage being a rated field voltage of the diagnostic analysis target when the reference value set for the field voltage is initially set the fluctuation amplitude index an average value of the determined composite voltage coefficients for the diagnostic analysis target in the target analysis period, a maximum value of the determined composite voltage coefficients for the diagnostic analysis target in the target analysis period, a minimum value of the determined composite voltage coefficients for the diagnostic analysis target in the target analysis period, the maximum value point and the minimum value point of the numerical curve of the synthetic voltage coefficient corresponding to the target analysis period, the fluctuation characteristic recurrence index , the recurrence interval difference index corresponding to the maximum value point, the recurrence interval difference index corresponding to the minimum value point, if is 0, the fluctuation characteristic recurrence index is recorded as 1, wherein the recurrence interval difference index corresponding to the maximum value point , is the average value of the interval duration between the time stamps corresponding to each adjacent two maximum value points of the numerical curve of the synthetic voltage coefficient corresponding to the target analysis period, is the standard deviation between the interval durations between the time stamps corresponding to each adjacent two minimum value points of the numerical curve of the synthetic voltage coefficient corresponding to the target analysis period, the recurrence interval difference index corresponding to the minimum value point , is the average value of the interval duration between the time stamps corresponding to each adjacent two minimum value points of the numerical curve of the synthetic voltage coefficient corresponding to the target analysis period, is the standard deviation between the interval durations between the time stamps corresponding to each adjacent two minimum value points of the numerical curve of the synthetic voltage coefficient corresponding to the target analysis period.

2. The method for multi-parameter analysis and fault diagnosis based on resolver output signals according to claim 1, characterized in that, periodically detecting the fluctuation amplitude index of the diagnostic analysis target, which is determined according to the synthetic voltage coefficients determined each time within each monitoring execution period; the synthetic voltage coefficient is determined according to the sine voltage, cosine voltage and excitation voltage corresponding to the diagnostic analysis target output signal.

3. The method for multi-parameter analysis and fault diagnosis based on resolver output signals according to claim 2, characterized in that, When the fluctuation amplitude index of the diagnostic analysis target is greater than a preset fluctuation amplitude index, perform harmonic information processing on the diagnostic analysis target, wherein, detect the fluctuation characteristic recurrence index of the target output signal obtained for the diagnostic analysis target within a target analysis period, and perform Fourier transform to obtain a target identification spectrum corresponding to the target analysis period; the fluctuation characteristic recurrence index is determined according to the synthetic voltage coefficients determined each time and their time stamps.

4. The method for multi-parameter analysis and fault diagnosis based on resolver output signals according to claim 3, characterized in that, When the fluctuation characteristic recurrence index is greater than a preset fluctuation characteristic recurrence index, perform harmonic component analysis on the target output signal, wherein, determine the multiple parameters corresponding to the frequency components existing in the target identification spectrum based on the fundamental frequency to determine the dominant frequency component corresponding to the target analysis period; determine the recommended fault positioning information through the dominant frequency state corresponding to the target identification spectrum.

5. The method for multi-parameter analysis and fault diagnosis based on resolver output signals according to claim 4, characterized in that, When the dominant frequency state corresponding to the target identification spectrum is a single frequency state, the recommended fault positioning information sent to the user is rotor radial eccentricity and rotor imbalance; When the dominant frequency state corresponding to the target identification spectrum is a two frequency state, the recommended fault positioning information sent to the user is shaft coupling misalignment; When the dominant frequency state corresponding to the target identification spectrum is a high multiple frequency state, the recommended fault positioning information sent to the user is mechanical looseness; When the dominant frequency state corresponding to the target identification spectrum is a high frequency dominant state, the recommended fault positioning information sent to the user is bearing abnormality.

6. The method for multi-parameter analysis and fault diagnosis based on resolver output signals according to claim 5, characterized in that, When the fluctuation characteristic recurrence index is less than or equal to a preset fluctuation characteristic recurrence index or the harmonic component analysis is completed, perform harmonic energy analysis on the target output signal, wherein, the harmonic cumulative energy parameter is determined according to the amplitudes corresponding to each frequency component existing in the target identification spectrum.

7. The method for multi-parameter analysis and fault diagnosis based on resolver output signals according to claim 6, characterized in that, determine the fault radiation index according to the cumulative energy evaluation parameter and the cumulative energy rising parameter; The fault radiation index is in positive correlation with the cumulative energy evaluation parameter and the cumulative energy rise parameter respectively.

8. The method for multi-parameter analysis and fault diagnosis based on resolver output signals according to claim 7, characterized in that, Determine whether to send a reference setting abnormality prompt of the excitation voltage to the user according to the stage evaluation abnormality index; When the stage evaluation abnormality index corresponding to the target analysis period is greater than a preset stage evaluation abnormality index, send a reference setting abnormality prompt of the excitation voltage to the user; The stage evaluation abnormality index is determined according to the cumulative energy evaluation parameter and the fluctuation amplitude evaluation parameter corresponding to the target analysis period.

9. The method for multi-parameter analysis and fault diagnosis based on resolver output signals according to claim 2, characterized in that, When the fluctuation amplitude index of the diagnostic analysis target is less than or equal to a preset fluctuation amplitude index, perform electric energy information processing on the diagnostic analysis target, wherein, Perform high-voltage testing and direct-current resistance detection on the diagnostic analysis target to obtain a direct-current resistance parameter and an insulation resistance parameter of the diagnostic analysis target; If the obtained direct-current resistance change parameter or insulation resistance parameter of the diagnostic analysis target is not within the corresponding preset threshold range, the recommended fault positioning information sent to the user is that the diagnostic analysis target has an electrical performance abnormality.

10. The method for multi-parameter analysis and fault diagnosis based on resolver output signals according to claim 1, characterized in that, The fault diagnosis report includes recommended fault positioning information, a fault radiation index, and a fault determination time.

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