Method and device for diagnosing open-circuit fault of driver of electric excavator

Abstract

The invention discloses an open-circuit fault diagnosis method and device for a driver of an electric excavator, and the method comprises the following steps: firstly, obtaining a three-phase current signal of an inverter; filtering and smoothing the current signal; performing positive and negative half-wave separation on the current signal to obtain an odd symmetric component and an even symmetric component; calculating an integral mean value, constructing a phase current characteristic vector, and comparing the maximum value of the integral mean value with a detection threshold value to judge whether an open-circuit fault occurs or not; calculating a positioning threshold value in real time, comparing the phase current characteristic vector with the positioning threshold value, and separating an abnormal value; and finally, obtaining a fault positioning result according to the index relation between the abnormal value and the inverter switching tube. According to the method, information containing fault characteristic essence can be extracted only by using three-phase current data, a phase current vector is constructed through odd-even symmetric components, and a distributed adaptive threshold algorithm is constructed, so that open-circuit fault detection and identification of the inverter module under a complex working condition can be realized without complex calculation.

Description

Technical Field

[0001] This invention relates to the field of inverter monitoring technology for electric construction machinery, and in particular to a method and device for diagnosing open-circuit faults in the drive of an electric excavator. Background Technology

[0002] Permanent magnet synchronous motors (PMSMs) are the core drive system of electric construction machinery, possessing advantages such as high power density and high efficiency, and occupying a crucial position in various electric drive solutions. The inverter, as a key power conversion unit in the electric drive system, directly determines the reliability of the motor and the overall performance of the machine. Therefore, conducting research on efficient and accurate fault diagnosis for inverters in PMSM drive systems is a critical step in ensuring the stable and safe operation of electric construction machinery.

[0003] Existing diagnostic methods fall into three categories: model-based, data-based, and signal-based methods. Model-based methods construct a model similar to the actual system, obtain reference values, and compare them with the actual system output for consistency. The comparison results serve as the carrier of fault information. The biggest advantages of model-based methods are their strong interpretability and fast diagnostic speed; however, their accuracy is limited by whether the model accurately reflects the actual system.

[0004] Data-driven methods can diagnose faults without building precise models. They identify faults by utilizing machine learning techniques to extract essential features from fault data. While data-driven methods are highly adaptable, their high reliance on historical data and computational burden mean they require further optimization to better meet the needs of industrial applications requiring rapid diagnostics.

[0005] Compared to model-based methods, signal-based methods have lower requirements for models. Compared to data-based methods, signal-based methods have a significant advantage in diagnostic speed. Therefore, at present, signal-based methods are more suitable for industrial applications. Since they do not require additional hardware circuits or sensors, signal-based methods are currently attracting more attention. Signal-based methods directly start from signal characteristics, analyzing the largest differences between normal and faulty conditions and optimizing thresholds to achieve fault detection and location. However, for electric engineering machinery, frequent load changes are a typical characteristic. For signal-based methods that rely on time-domain waveforms, this is undoubtedly an uncertain disturbance. The uncertainty of threshold optimization has become an obstacle to the development of signal-based methods.

[0006] Based on this, the present invention proposes a dynamic adaptive open-circuit fault diagnosis method. Summary of the Invention

[0007] The purpose of this invention is to provide a method and device for diagnosing open-circuit faults in electric excavator drives, which addresses the aforementioned problems. This method can extract information containing the essential characteristics of the fault using only three-phase current data. It constructs phase current vectors through odd-even symmetrical components and builds a distributed adaptive threshold algorithm, enabling the detection and identification of open-circuit faults in inverter modules under complex operating conditions without the need for complex calculations.

[0008] To achieve the above-mentioned objectives, the technical solution adopted by this invention is as follows: According to one aspect of the present invention, a method and apparatus for diagnosing open-circuit faults in the drive of an electric excavator are provided, comprising the following steps: S1. Obtain the three-phase current signal at the drive end of the permanent magnet synchronous motor drive system; S2. Filter and smooth the acquired three-phase current signal; S3. Perform positive and negative half-wave separation on the processed three-phase current signal to obtain the odd symmetric component and even symmetric component corresponding to the positive and negative half-waves. S4. Calculate the integral mean of the odd symmetric component and the even symmetric component, construct the phase current characteristic vector with the integral mean as the characteristic quantity, and compare the maximum value of the integral mean with the detection threshold to determine whether an open circuit fault has occurred. S5. Calculate the positioning threshold in real time based on the phase current characteristic vector, compare the phase current characteristic vector with the positioning threshold, and separate abnormal values ​​from the phase current characteristic vector; S6. Obtain the fault location result based on the index relationship between the abnormal value and the inverter switching transistor.

[0009] Preferably, in step S2, the three-phase current signal is filtered using the following formula: in, It is the length of the filtering window; This is the location of the data point to be calculated. It is a summation index; It is the maximum current amplitude.

[0010] Preferably, in step S3, the odd-symmetric component and the even-symmetric component are calculated by the following formula: in, It is an odd symmetric component; It is an even-symmetric component.

[0011] Preferably, in step S4, the mean integral of the odd-symmetric component and the even-symmetric component is calculated by the following formula: in, The mean of the integrals corresponding to the odd symmetric components; The mean of the integrals corresponding to the even-symmetric components; This is one fundamental frequency period.

[0012] Preferably, in step S4, the phase current characteristic vector is represented by the following formula: in, The characteristic vector of phase current; They are respectively Odd-symmetric and even-symmetric components of the phase; They are respectively Odd-symmetric and even-symmetric components of the phase; They are respectively The odd-symmetric and even-symmetric components of the phase.

[0013] Preferably, in step S4, the determination of whether an open-circuit fault has occurred is determined by a detection index, which is expressed by the following formula: in, and This represents the maximum value of the integral mean.

[0014] Preferably, in step S5, the positioning threshold is calculated by the following formula: in, The center point of the characteristic vector; Standard deviation; This is the detection threshold.

[0015] Preferably, in step S6, the fault location method includes the following steps: S71. The fault feature value is obtained by combining the indicator vector with the detection indicator. The fault feature value is represented by the following formula: in, These are fault characteristic values; For detection indicators; This is the index vector.

[0016] S72. Based on the index relationship between the characteristic value and the fault characteristic value, the fault location result is obtained.

[0017] Preferably, the index vector is represented by the following formula: in, and This is the identification vector.

[0018] Preferably, an open-circuit fault diagnosis device for an electric excavator drive includes a data acquisition module, a fault detection module, and a fault identification module; The data acquisition module is used to acquire the three-phase current signal of the drive motor; The fault detection module is used to determine whether a system fault has occurred. The fault identification module identifies the fault location information.

[0019] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: This invention acquires three-phase current signals during inverter operation, smooths the current waveform using a mean filtering algorithm, and periodically extracts data. The current data is then separated into positive and negative half-waves, and the symmetrical components of each half-wave are calculated. These three sets of symmetrical components form a phase current vector. By analyzing the relative change trend of this vector, a diagnostic threshold is calculated in real time. Symmetrical components exceeding the threshold are identified as abnormal, and a fault location feature calculation formula is constructed based on this, thereby achieving accurate fault location. This method requires only three-phase current measurements and constructs phase current vectors using odd and even symmetrical components, enabling efficient multi-type fault detection without complex calculations. Attached Figure Description

[0020] Figure 1 This is a flowchart of the method steps of the present invention.

[0021] Figure 2 This is a schematic diagram of the experimental platform for the permanent magnet synchronous motor drive system of the present invention.

[0022] Figure 3 This is a schematic diagram of the current loop under the T1 open-circuit fault of the present invention.

[0023] Figure 4 This is a graph showing the positive and negative half-wave curves before and after a phase A fault according to the present invention.

[0024] Figure 5 This is a flowchart of the open-circuit fault diagnosis method of the present invention.

[0025] Figure 6 This is a diagnostic flowchart of the inverter fault diagnosis device of the present invention.

[0026] Figure 7 This is a schematic diagram of different fault location function values ​​of the present invention. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and preferred embodiments. However, it should be noted that many details listed in the specification are merely to provide the reader with a thorough understanding of one or more aspects of the invention, and these aspects of the invention can be achieved even without these specific details.

[0028] Please see Figures 1 to 7 This invention provides a method and device for diagnosing open-circuit faults in the drive system of an electric excavator. The technical solution is as follows: A method for diagnosing open-circuit faults in an electric excavator drive includes the following steps: S1. Build an experimental platform for a permanent magnet synchronous motor drive system based on magnetic field orientation control to collect experimental data under different working conditions.

[0029] Specifically, the experimental platform for the permanent magnet synchronous motor drive system consists of a permanent magnet synchronous motor, drive board, control board, brake, DC regulated power supply, Hall current sensor, etc. It is used to simulate the sudden load changes of an electric excavator during operation and the corresponding inverter open-circuit fault types. The structure is as follows... Figure 2As shown, there are 21 types of inverter open-circuit faults, including 6 single-side open-circuit faults (T1, T2, T3, T4, T5, T6), 6 same-side double-side open-circuit faults (T1&T3, T1&T5, T3&T5, T2&T4, T2&T6, T4&T6), and 9 opposite-side double-side open-circuit faults (T1&T2, T1&T4, T1&T6, T2&T3, T2&T5, T3&T4, T3&T6, T4&T5, T5&T6). Inverter open-circuit faults are addressed through manual injection. That is, the corresponding component is opened by setting the gate of the Insulated Gate Bipolar Transistor (IGBT) to a low level. In this embodiment, the controller is a TMS320F28335 chip. The permanent magnet synchronous motor is a low-voltage motor with a specification of 3000RPM / 100W, 8 pole pairs, rated current of 5.5A, and rated torque of 0.32Nm. It has a built-in Hall position sensor. A Hall current sensor is used to collect current signals. The brake is a manual hysteresis brake with a rated torque of 0.2Nm. The motor control method adopts a field-oriented control algorithm based on Id=0. The data acquisition card model is HK_USB6202-S. The signal acquisition circuit used in this embodiment has a sampling frequency of 100kHz. This embodiment includes six steady-state operating conditions and a speed-varying operating condition of 500RPM-3000RPM. The steady-state operating conditions are 1500 RPM & 0.05 N·m, 1500 RPM & 0.1 N·m, 2000 RPM & 0.05 N·m, 2000 RPM & 0.1 N·m, 2500 RPM & 0.05 N·m, and 2500 RPM & 0.1 N·m. Data is collected for 6 seconds under each condition. Fault injection occurs during the data acquisition time. The current loop under fault conditions is as follows... Figure 3 As shown.

[0030] S2. Place Hall sensors at key locations on the experimental platform, such as the motor power supply terminals and rotor, and obtain the three-phase current signal of the drive end through the data acquisition card.

[0031] S3. The signal is filtered and smoothed using the mean filtering algorithm and the two-stage normalization strategy.

[0032] Specifically, the mean filtering algorithm and two-stage normalization strategy are used to smooth the acquired three-phase current signal and eliminate the influence of load fluctuations on the signal characteristics. This is achieved through the following formula: in, It is the length of the filtering window; This is the location of the data point to be calculated. It is a summation index; It is the maximum current amplitude.

[0033] S4. Perform positive and negative half-wave separation on the data processed in step S3 to construct phase current characteristic components containing odd-symmetric and even-symmetric components.

[0034] Specifically, the periodic components calculated in step S3 are separated into positive and negative half-waves. The positive half-wave is considered an odd-symmetric component, and the negative half-wave is considered an even-symmetric component. The separation diagram is shown below. Figure 4 As shown, the calculation is as follows: in, For odd-symmetric components, only the positive value of the current is retained, and the negative value is set to zero; For even-symmetric components, only the negative part of the current is retained, and the positive value is cleared to zero.

[0035] S5. Calculate the integral mean value corresponding to the phase current characteristic components, use it as a signal feature to construct the phase current characteristic vector, and compare the maximum value with the detection threshold to determine whether a fault has occurred.

[0036] Specifically, calculate the mean of the integrals corresponding to the symmetric components: in, The mean of the integrals corresponding to the odd symmetric components; The mean of the integrals corresponding to the even-symmetric components; This is one fundamental frequency period.

[0037] The methods for determining whether a fault has occurred include the following steps: S51. Construct the phase current characteristic vector and determine the detection threshold based on the motor power. .

[0038] in, The characteristic vector of phase current; They are respectively Odd-symmetric and even-symmetric components of the phase; They are respectively Odd-symmetric and even-symmetric components of the phase; They are respectively The odd-symmetric and even-symmetric components of the phase.

[0039] S52. The maximum value of the phase current characteristic vector is compared with the detection threshold to determine whether a system fault has occurred. If a fault has occurred, the detection index G is 1; otherwise, it is 0. As shown in the following formula: in, and This represents the maximum value of the integral mean.

[0040] S6. Determine the positioning threshold based on the dynamic change trend of the phase current characteristic vector over time, and compare the vector with the positioning threshold to separate outliers.

[0041] Specifically, the location threshold is calculated based on the distribution trend of the phase current characteristic vector. The location threshold consists of the center point and standard deviation of the characteristic quantity. in, The center point of the characteristic vector; Standard deviation; This is the detection threshold.

[0042] The fault identification process requires obtaining indicator vectors, which can be obtained in two ways: the extreme value method and the distributed threshold method.

[0043] When the system exhibits only one outlier, the extreme value method is used to obtain the index vector. This involves statistically analyzing the index value corresponding to the maximum value in the phase current characteristic vector to construct an identification vector. in, for The index value corresponding to the maximum value in the index vector is set to only be found at the index. The index value is 1 for all others and 0 for the rest. For example, if the index value is 2, then the index vector is... .

[0044] The extreme value method can only filter out one outlier. However, when a double switch fault occurs in the system, two outliers will appear, and the extreme value method is not applicable. Therefore, the distributed threshold method is introduced.

[0045] The distributed threshold is: Among them, the recognition vector Combined with recognition vector and recognition vector This yields the index vector: S7. Obtain the fault location result based on the index relationship between the abnormal value and the inverter switching transistor.

[0046] Specifically, the fault location method includes the following steps: S71. Combine the index vector with the detection index G to obtain the fault feature value: in, These are fault characteristic values.

[0047] S72, see as follows Figure 7 The algorithm correlates the feature values ​​with the fault index to obtain the fault location result. The overall flowchart of the algorithm is shown below. Figure 5 As shown.

[0048] like Figure 6 As shown, the present invention also provides a fault diagnosis device for an electric excavator drive, the fault diagnosis device including a data acquisition module, a fault detection module and a fault identification module; The data acquisition module uses a data acquisition card to collect three-phase current information of the drive motor; The fault detection module uses a mean filtering algorithm to denoise and smooth the signal. A two-stage normalization strategy is used to reduce the impact of characteristic instability caused by load changes. The positive and negative half-waves are separated to obtain the corresponding odd symmetric components and even symmetric components. The phase current characteristic vector is constructed, and the maximum value of the vector is compared with the detection threshold to determine whether the system has a fault. The fault identification module calculates the identification threshold based on the changing trend of the phase current characteristic vector, compares the characteristic vector with the identification threshold, returns the index vector, and combines the index vector with the detection index to obtain the fault characteristic value. The specific fault location information is then output using a lookup table method.

[0049] This embodiment uses a self-powered drive system test bench as an example, and sets 21 fault types. For open circuit faults, the IGBT gate is set to a low level.

[0050] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for diagnosing open-circuit faults in the drive unit of an electric excavator, characterized in that, Includes the following steps: S1. Obtain the three-phase current signal at the drive end of the permanent magnet synchronous motor drive system; S2. Filter and smooth the acquired three-phase current signal; S3. Perform positive and negative half-wave separation on the processed three-phase current signal to obtain the odd symmetric component and even symmetric component corresponding to the positive and negative half-waves. S4. Calculate the integral mean of the odd symmetric component and the even symmetric component, construct the phase current characteristic vector with the integral mean as the characteristic quantity, and compare the maximum value of the integral mean with the detection threshold to determine whether an open circuit fault has occurred. S5. Calculate the positioning threshold in real time based on the phase current characteristic vector, compare the phase current characteristic vector with the positioning threshold, and separate abnormal values ​​from the phase current characteristic vector; S6. Obtain the fault location result based on the index relationship between the abnormal value and the inverter switching transistor.

2. The method for diagnosing open-circuit faults in an electric excavator drive according to claim 1, characterized in that: In step S2, the three-phase current signal is filtered using the following formula: in, It is the length of the filtering window; This is the location of the data point to be calculated. It is a summation index; It is the maximum current amplitude.

3. The method for diagnosing open-circuit faults in an electric excavator drive according to claim 1, characterized in that: In step S3, the odd-symmetric component and the even-symmetric component are calculated by the following formula: in, It is an odd symmetric component; It is an even-symmetric component.

4. The method for diagnosing open-circuit faults in an electric excavator drive according to claim 1, characterized in that: In step S4, the integral mean of the odd-symmetric component and the even-symmetric component is calculated by the following formula: in, The mean of the integrals corresponding to the odd symmetric components; The mean of the integrals corresponding to the even-symmetric components; This is one fundamental frequency period.

5. The method for diagnosing open-circuit faults in an electric excavator drive according to claim 1, characterized in that: In step S4, the phase current characteristic vector is represented by the following equation: in, The characteristic vector of phase current; They are respectively Odd-symmetric and even-symmetric components of the phase; They are respectively Odd-symmetric and even-symmetric components of the phase; They are respectively The odd-symmetric and even-symmetric components of the phase.

6. The method for diagnosing open-circuit faults in an electric excavator drive according to claim 1, characterized in that: In step S4, the determination of whether an open-circuit fault has occurred is determined by a detection index, which is expressed by the following formula: in, and This represents the maximum value of the integral mean.

7. The method for diagnosing open-circuit faults in an electric excavator drive according to claim 1, characterized in that: In step S5, the positioning threshold is calculated by the following formula: in, The center point of the characteristic vector; Standard deviation; This is the detection threshold.

8. The method for diagnosing open-circuit faults in an electric excavator drive according to claim 1, characterized in that: In step S6, the fault location method includes the following steps: S71. The fault feature value is obtained by combining the indicator vector with the detection indicator. The fault feature value is represented by the following formula: in, These are fault characteristic values; For detection indicators; This is the index vector. S72. Based on the index relationship between the characteristic value and the fault characteristic value, the fault location result is obtained.

9. A method for diagnosing open-circuit faults in an electric excavator drive according to claim 8, characterized in that: The index vector is represented by the following formula: in, and This is the identification vector.

10. A diagnostic device for open-circuit faults in an electric excavator drive, applied to the diagnostic method for open-circuit faults in an electric excavator drive as described in any one of claims 1-9, characterized in that: It includes a data acquisition module, a fault detection module, and a fault identification module; The data acquisition module is used to acquire the three-phase current signal of the drive motor; The fault detection module is used to determine whether a system fault has occurred. The fault identification module identifies the fault location information.

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