Non-intrusive three-phase motor operation state identification method

Abstract

The invention provides a non-intrusive three-phase motor operation state identification method. Comprising a signal sampling step, a preprocessing step, a high-frequency characteristic calculation step, a low-frequency event detection step, an operation state detection step and a real-time recording step, and is characterized in that data acquired by a high-precision current and voltage sensor is processed based on an annular buffer area data structure to obtain differentiated current cyclic waves; the method comprises the following steps: extracting specific harmonic waves of current cyclic waves based on a fast Fourier transform algorithm, constructing a high-frequency feature set in combination with other statistical features, calculating active power and reactive power of the cyclic waves in an annular buffer area and performing extreme point judgment on detected events, and respectively processing data sources of a three-phase motor by the events to obtain a three-phase motor data source; and the state of the three-phase motor is judged and recorded, so that comprehensive monitoring of the running state of the three-phase motor is realized. The method has the advantage that the problem that the monitoring of the three-phase motor is not comprehensive and accurate enough by the existing three-phase motor operation state identification method is solved.

Description

Technical Field

[0001] The present application relates to the field of electricity technology, and in particular to a non-invasive three-phase motor operating status identification method. Background Art

[0002] Three-phase motors occupy a pivotal position in the modern industrial system and are the core power source for efficient production in many fields. In the manufacturing industry, from stamping, welding, painting and other links in automobile manufacturing to the operation of lathes, milling machines, grinders and other equipment in mechanical processing, three-phase motors provide stable and strong power support for various precision machinery to ensure the continuity and accuracy of the production process. In the energy mining industry, whether it is a large oil pumping unit on an oil drilling platform or ventilation and drainage equipment underground in a coal mine, the reliable operation of three-phase motors is related to the safety and efficiency of the entire mining operation. In construction scenes, tower cranes, concrete mixers, construction elevators and other equipment rely on three-phase motors to drive.

[0003] Traditional monitoring methods for three-phase motors mainly use invasive detection solutions. This method requires professional maintenance personnel to open the motor casing in the shutdown state and use various professional detection instruments, such as oscilloscopes and multimeters, to access the key parts of the motor, such as the stator winding, rotor winding, brushes, commutator (for DC motors or some wound asynchronous motors) and terminal blocks. The operation process is not only complicated and cumbersome, but also consumes a lot of manpower and time costs, and there are many disadvantages. For example, frequent disassembly of the motor casing and terminal blocks can easily cause mechanical damage to the connection parts, loosen the bolts, wear the threads, and increase the contact resistance during subsequent operation, which in turn causes safety hazards such as heating and sparking; in the process of connecting the detection instrument, if the operation is not careful, it is easy to scratch the insulation layer inside the motor, exposing key components such as windings and cores, greatly increasing the risk of leakage and endangering the personal safety of operators. Moreover, since intrusive detection is mostly regular inspection, it is impossible to obtain the motor operating status data in real time and continuously, and it is difficult to capture some instantaneous or short-lived fault signals in time, causing the motor to be in a "monitoring blind spot" during the interval between two inspections, posing a hidden danger to long-term stable operation.

[0004] Nowadays, with the development of industrial automation, intelligent manufacturing and Internet of Things technology, enterprises are in urgent need of non-invasive, high-precision and real-time monitoring of three-phase motors. The present invention came into being to build a new monitoring system, including modules such as data acquisition, preprocessing, high-frequency and low-frequency feature analysis, operation status inspection and event reporting. The coordinated operation of each module can not only ensure the safety and stability of the motor itself, but also provide data support for the intelligent operation and maintenance of industrial production systems, and help industrial upgrading and sustainable development. Among them, the data acquisition module uses high-precision sensors to sample current and voltage signals at a safe position outside the motor; the data preprocessing module processes data with the help of a circular buffer; the high-frequency feature calculation module extracts features such as harmonics; the low-frequency event detection module calculates power and judges events; the motor operation status inspection module comprehensively judges the motor's on, off, and phase loss status; the motor event reporting module promptly cooperates with other devices to report motor events, prompting the system to adjust and respond in a timely manner. Summary of the invention

[0005] The present application provides a non-intrusive three-phase motor operating status identification method to solve the problem that the existing three-phase motor operating status identification method is not comprehensive and accurate enough in monitoring the three-phase motor.

[0006] The present application provides a non-intrusive three-phase motor operating status identification method, which specifically includes a signal sampling step, a preprocessing step, a high-frequency feature calculation step, a low-frequency event detection step and an operating status inspection step.

[0007] The signal sampling step is to synchronously sample the current change and voltage change of different phase lines of the three-phase motor through a high-precision current and voltage sensor, and convert the collected voltage change and the current change into a voltage signal and a current signal; the preprocessing step is to preprocess the current signal and the voltage signal based on the ring buffer data structure to obtain the first frequency after differentiation; the high-frequency feature calculation step is to extract the first harmonic amplitude, the second harmonic amplitude and the third harmonic amplitude of the three-phase motor, calculate the characteristic zero rate, UI trajectory envelope area and margin of the first frequency, construct the characteristic zero rate, the UI trajectory envelope area, the margin, the first harmonic amplitude, the second harmonic amplitude and the third harmonic amplitude into a high-frequency feature set, mark the first frequency that satisfies the high-frequency feature of the three-phase motor in the high-frequency feature set, and obtain the second frequency; the low The low-frequency event detection step is to create a buffer, calculate the active power and reactive power of each cycle in the circular buffer, if there is a second cycle in the cycle, mark the specific data points of the second cycle with high-frequency features, each position in the buffer is used to store the active power, the reactive power and the high-frequency feature mark, if there is a position where the active power and reactive power stored meet the preset conditions, it is determined that there is a low-frequency event; the operating status inspection step is to perform a high-frequency feature inspection on the low-frequency events detected in each phase of the three-phase motor, if there is a high-frequency feature, then perform a low-frequency feature inspection on the low-frequency events detected in each phase of the three-phase motor, judge the operating status of each phase according to the result of the low-frequency feature inspection, and then determine the operating status of the three-phase motor according to the operating status of each phase and the time error of the operating status being turned on.

[0008] Furthermore, the preprocessing step specifically includes a buffer establishment step, a maximum value alignment step, a Manhattan distance calculation step, a cycle correction step and a differential operation step.

[0009] The buffer establishment step is to set up a voltage ring buffer and a current ring buffer, and each buffer position stores one cycle of data; the maximum value alignment step is to find the maximum value index of the head pointer and the tail pointer through traversal, so as to align the tail pointer voltage with the head pointer voltage, and the calculation formula is:

[0010]

[0011] in, Represents the voltage at the head pointer of the voltage ring buffer after alignment, k = 0, 1, ..., M-1, k represents the data point of the cycle, V h Indicates the voltage at the voltage ring buffer head pointer position, Indicates the maximum value index of the tail pointer of the voltage ring buffer. Indicates the maximum value index of the voltage ring buffer head pointer, M=32.

[0012] The Manhattan distance calculation step is performed by fixing the frequency at the tail pointer of the voltage ring buffer, setting an offset, traversing all offsets to calculate the Manhattan distance between the frequency at the head pointer of the voltage ring buffer and the frequency at the tail pointer of the voltage ring buffer, and recording the minimum distance d min And the corresponding offset s min , and its calculation formula is

[0013]

[0014] Where d(s) represents the Manhattan distance, s represents the offset, s = -5, -4, ..., 4, 5, V t Indicates the voltage at the tail pointer position of the voltage ring buffer.

[0015] The frequency correction step is based on the offset S calculated in the voltage ring buffer. min , to correct the frequency of the head pointer in the current ring buffer, the formula is:

[0016]

[0017] in, Represents the corrected cyclic current at the head pointer of the current ring buffer, I h Indicates the current at the head pointer in the current ring buffer.

[0018] The differential operation step is to perform differential operation on the corrected current cycle at the head pointer of the current ring buffer and the current cycle at the tail pointer of the current ring buffer to obtain the differential current cycle, which is the first cycle, and its formula is:

[0019]

[0020] Among them, I diff Represents the current cycle after differentiation, I t Indicates the current at the tail pointer of the current ring buffer.

[0021] Furthermore, the high-frequency feature calculation step specifically includes a harmonic amplitude extraction step, a zero-rate customization step, an envelope area calculation step, and a margin calculation step.

[0022] The harmonic amplitude extraction step is to extract the first harmonic amplitude, the second harmonic amplitude and the third harmonic amplitude of the three-phase motor through a discrete Fourier transform formula, and the discrete Fourier transform formula is:

[0023]

[0024] Among them, f=0,1,2.....N-1, f represents the specific frequency generated when the motor is running, N represents the length of the cycle, W represents the complex matrix, and n represents the index of the cycle length, representing the position in the cycle.

[0025] The zero rate customization step is to describe the proportion of the value near the zero point in the cyclic current by customizing the zero rate, and the formula is:

[0026]

[0027] Among them, count low Indicates the number of values ​​near zero, n indicates the number of cycles, n = 32, I i Represents cyclic current, lowbound represents the upper limit of the threshold defined as "value near zero point", and minorrate represents zero rate.

[0028] The envelope area calculation step is used to calculate the envelope area of ​​the relationship curve between the voltage and current of each phase of the three-phase motor, and its formula is:

[0029]

[0030] Among them, S U-I represents the envelope area, n represents the number of cycles, n=32, I i Indicates the frequency current, U i Indicates frequency voltage.

[0031] The margin calculation step is used to calculate the sharpness of the current peak in the waveform, and its formula is:

[0032]

[0033] Among them, x r Indicates the square root amplitude of the current, n indicates the number of cycles, n = 32, I i Represents the frequency current, x peak Indicates the current amplitude, C e Represents the calculated margin.

[0034] Furthermore, the judgment criteria for whether the high-frequency feature set meets the high-frequency characteristics of the three-phase motor are: the first harmonic amplitude is greater than a first amplitude threshold, the second harmonic amplitude is greater than a second amplitude threshold, and the third harmonic amplitude is greater than a third amplitude threshold; the zero rate is less than a zero rate threshold; the UI trajectory envelope area is within a preset area threshold range; and the margin is within a preset margin threshold range.

[0035] Furthermore, the low-frequency event detection step specifically includes an active power calculation step, a reactive power calculation step, an active power accumulation and calculation step, and a reactive power accumulation and calculation step.

[0036] The active power calculation step is used to calculate the active power of each cycle in the ring buffer, and its formula is:

[0037] P=UI cosφ

[0038] Among them, P represents active power, U represents frequency voltage, and I represents frequency current.

[0039] The reactive power calculation step is used to calculate the reactive power of each cycle in the ring buffer, and its formula is:

[0040] Q=UIsinφ

[0041] Among them, Q represents reactive power.

[0042] The active power accumulation and calculation step is used to calculate the accumulated active power of each cycle in the ring buffer, and its formula is:

[0043]

[0044] Among them, i represents the time, P k represents the active power at time k, P0 represents the initial value of the active power, S p (i) represents the accumulated active power.

[0045] The reactive power accumulation and calculation step is used to calculate the accumulated sum of reactive power of each cycle in the ring buffer, and its formula is:

[0046]

[0047] Among them, Q k represents the reactive power at time k, Q0 represents the initial value of the reactive power, S Q (i) represents the cumulative sum of reactive power.

[0048] Furthermore, the preset condition is that if there is a position m that satisfies the following two preset conditions, it is determined that the mth position and the 0th position constitute a low-frequency event:

[0049]

[0050] Among them, 1≤m≤n, abs(S P (m)) represents the accumulated and data point active power, abs(S Q (m)) represents the accumulated and data point reactive power.

[0051] Furthermore, the operation status inspection step specifically includes a high-frequency feature inspection step, a low-frequency feature inspection step and a comprehensive determination step.

[0052] The high-frequency feature inspection step is to detect whether the low-frequency event has high-frequency features for each phase-detected low-frequency event. The data point set included in the low-frequency event is E={e1, e2, ..., e n}, where n represents the number of data points contained in the event, e i represents the i-th data point, i = 1, 2, ..., n; define the labeling function M(e i ), used to determine the data point e i Is it marked? When the data point e i When marked, M(e i )=1, and execute the next step; when the data point e i When not marked, M(e i )=0, and detect the next low-frequency event; the low-frequency feature inspection step is to define the low-frequency event that passes the high-frequency feature inspection step as a marked low-frequency event, and determine whether the marked low-frequency event has a transient low-frequency feature of motor startup. If so, and the reactive power of the marked low-frequency event is within the power threshold range, it is determined that a motor event is detected in each phase; the comprehensive determination step is based on the motor event detected in each phase, and determines whether the three-phase motor is in one of the three states of three-phase motor on, three-phase motor missing phase and three-phase motor off.

[0053] Furthermore, the low-frequency feature inspection step specifically includes a peak detection step, a peak ratio detection step and a power jump detection step.

[0054] The peak detection step is to detect the first marker low frequency event E1 = {e 11 ,e 12 ,...,e 1n}The next second marked low frequency event E2 adjacent to it = {e 21 ,e 22 ,...,e 2n}Whether the following detection conditions are met, if so, execute the next step, if not, detect the next marked low-frequency event pair, the detection conditions are

[0055]

[0056] Among them, P represents active power and Q represents reactive power.

[0057] The peak ratio detection step is used to determine whether the peak ratio meets the determination condition. If it meets, the next step is executed. If it does not meet, the next peak ratio is detected. The determination condition is

[0058]

[0059] 1.2 < g < 2.1

[0060] where g represents the peak ratio.

[0061] The power jump detection step is to judge whether the reactive power of the low-frequency event is within the power threshold range by combining the reactive power changes of the first marked low-frequency event E1 = {e 11 , e 12 ,..., e1n} and the second marked low-frequency event E2 = {e 21 , e 22 ,..., e2n}. The reactive power calculation formula of the low-frequency event is

[0062] qdiff = Q[e 2n - Q[e 11

[0063] where qdiff represents the reactive power of the low-frequency event. When 50 < qdiff < 300, it is determined that the reactive power of the low-frequency event is within the power threshold range, and there is a motor start event.

[0064] Further, the comprehensive determination step specifically includes a three-phase motor start determination step, a three-phase motor phase loss determination step, and a three-phase motor shutdown determination step.

[0065] The three-phase motor start determination step is that when a motor start event is detected in each phase, the maximum time deviation of the occurrence times of the motor start events in the three phases needs to be obtained. The formula is

[0066] Δt max (t1, t2, t3) = max(|t1 - t2|, |t2 - t3|, |t1 - t3|)

[0067] where Δt max represents the maximum time deviation, and t1, t2, and t3 respectively represent the occurrence times of a motor start event in a phase. When Δt max < 1, it is determined that the three-phase motor is in the start state.

[0068] The three-phase motor phase loss determination step is that on the premise of detecting a three-phase motor start event, when a phase detects a motor shutdown event within a preset time period while there are still motors running in other phases, it is determined that the three-phase motor is in a phase loss state. ​

[0069] The three-phase motor shutdown determination step is to determine that the three-phase motor is in a shutdown state when no motor startup event is detected in each phase.

[0070] Furthermore, after the running status checking step, a real-time recording step is also included, in which the detected three-phase motors are matched by unique numbers, and the running status of the three-phase motors corresponding to the numbers are recorded in real time.

[0071] The present application provides a non-invasive three-phase motor operating status identification method, which adopts a high-precision current and voltage sensor to synchronously sample the current and voltage signals of different phase lines of the three-phase motor at a sampling frequency of not less than 1600 Hz, processes the data collected by the high-precision current and voltage sensor based on the ring buffer data structure to obtain the differential current cycle, extracts the specific harmonics of the current cycle based on the fast Fourier transform algorithm, and constructs a high-frequency feature set in combination with other statistical features, calculates the active power and reactive power of the cycle in the ring buffer and performs extreme point judgment to detect the event, and the event processes the three-phase motor data source separately, judges the state of the three-phase motor and records it, so as to realize comprehensive monitoring of the operating status of the three-phase motor, and solves the problem that the existing three-phase motor operating status identification method is not comprehensive and accurate enough in monitoring the three-phase motor. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0073] Figure 1 is a flow chart of a non-intrusive three-phase motor operating state identification method according to an embodiment of the present application;

[0074] Figure 2 is a flow chart of the preprocessing steps described in the embodiments of the present application;

[0075] Figure 3 is a flow chart of the high frequency feature calculation steps described in the embodiment of the present application;

[0076] Figure 4 is a flow chart of the low-frequency event detection steps described in an embodiment of the present application;

[0077] Figure 5 is a flow chart of the operation status inspection steps described in the embodiment of the present application;

[0078] Figure 6 is a flow chart of the low-frequency feature inspection steps described in the embodiment of the present application;

[0079] Figure 7 It is a flow chart of the comprehensive determination steps described in the embodiment of the present application. DETAILED DESCRIPTION

[0080] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this application.

[0081] like Figure 1 As shown, the present application provides a non-invasive three-phase motor operating status identification method, which specifically includes step S1) signal sampling step, step S2) preprocessing step, step S3) high-frequency feature calculation step, step S4) low-frequency event detection step, step S5) operating status inspection step and step S6) real-time recording step.

[0082] Step S1) signal sampling step, synchronously sampling the current changes and voltage changes of different phase lines of the three-phase motor through high-precision current and voltage sensors, and converting the collected voltage changes and the current changes into voltage signals and current signals.

[0083] In this embodiment, a high-precision current and voltage sensor is used to synchronously sample the current and voltage signals of different phase lines of the three-phase motor at a sampling frequency of 1600 Hz. The selection of the sampling frequency is based on an in-depth study of the operating characteristics of the three-phase motor and the frequency range of the fault signal. The current and voltage signals of the three-phase motor will show changes in different frequency components under normal operation and fault conditions. 1600 Hz can ensure that sufficiently fine signal details are captured, covering both the fundamental frequency information of the three-phase motor during steady-state operation and the high-frequency harmonic components caused by the fault. The sensor is installed in a safe position outside the three-phase motor near the terminal, cleverly using the principle of electromagnetic induction to non-invasively sense the current and voltage changes, avoiding any interference to the internal structure of the three-phase motor, and converting these time-varying physical quantities into electrical signals through the sensor, and transmitting them to the subsequent processing unit to execute subsequent steps.

[0084] Step S2) a preprocessing step, preprocessing the current signal and the voltage signal based on the ring buffer data structure to obtain a first frequency after differentiation.

[0085] In this embodiment, taking into account the continuity and real-time processing requirements of the motor operation data, a current ring buffer and a voltage ring buffer are defined based on the ring buffer data structure. First, the frequencies at the head and tail pointers of the voltage buffer are aligned to the maximum value, and then one frequency is fixed. The Manhattan distance is calculated with another frequency through continuous offset with the fixed frequency, and the minimum distance and offset are recorded. The frequencies of the head and tail pointers in the current buffer are corrected according to the voltage offset, and the current frequency at the tail pointer and the frequency at the head pointer are differentially processed to obtain the differential frequency.

[0086] like Figure 2 As shown, step S2) the preprocessing step specifically includes step S21) a buffer establishment step, step S22) a maximum value alignment step, step S23) a Manhattan distance calculation step, step S24) a cycle correction step and step S25) a differential operation step.

[0087] Step S21) Buffer establishment step, setting a voltage ring buffer and a current ring buffer, the length of the voltage ring buffer and the current ring buffer is N=10, each buffer position stores one cycle of data, and each cycle of data includes 32 data points.

[0088] Step S22) Maximum value alignment step, by traversing to find the maximum value index of the head pointer and the tail pointer, to align the tail pointer voltage with the head pointer voltage, the calculation formula is:

[0089]

[0090] in, Represents the voltage at the head pointer of the voltage ring buffer after alignment, k = 0, 1, ..., M-1, k represents the data point of the cycle, V h Indicates the voltage at the voltage ring buffer head pointer position, Indicates the maximum value index of the tail pointer of the voltage ring buffer. Indicates the maximum value index of the voltage ring buffer head pointer, M=32.

[0091] Step S23) Manhattan distance calculation step, fix the frequency at the tail pointer of the voltage ring buffer, set the offset, traverse all offsets to calculate the Manhattan distance between the frequency at the head pointer of the voltage ring buffer and the frequency at the tail pointer of the voltage ring buffer, and record the minimum distance d min And the corresponding offset s min , and its calculation formula is

[0092]

[0093] Where d(s) represents the Manhattan distance, s represents the offset, s = -5, -4, ..., 4, 5, V t Indicates the voltage at the tail pointer position of the voltage ring buffer.

[0094] Step S24) a frequency correction step, based on the offset S calculated in the voltage ring buffer min , to correct the frequency of the head pointer in the current ring buffer, the formula is:

[0095]

[0096] in, Represents the corrected cyclic current at the head pointer of the current ring buffer, I h Indicates the current at the head pointer in the current ring buffer.

[0097] Step S25) a differential operation step, performing a differential operation on the current cycle after correction at the head pointer of the current ring buffer and the current cycle at the tail pointer of the current ring buffer to obtain a differential current cycle, which is the first cycle, and its formula is:

[0098]

[0099] Among them, I diff Represents the current cycle after differentiation, I t Indicates the current at the tail pointer of the current ring buffer.

[0100] Step S3) a high-frequency feature calculation step, extracting the first harmonic amplitude, the second harmonic amplitude and the third harmonic amplitude of the three-phase motor, calculating the characteristic zero rate, UI trajectory envelope area and margin of the first frequency, constructing the characteristic zero rate, the UI trajectory envelope area, the margin, the first harmonic amplitude, the second harmonic amplitude and the third harmonic amplitude into a high-frequency feature set, marking the first frequency that satisfies the high-frequency characteristics of the three-phase motor in the high-frequency feature set, and obtaining the second frequency.

[0101] In this embodiment, the first harmonic amplitude is the 5th harmonic amplitude, the second harmonic amplitude is the 7th harmonic amplitude, and the third harmonic amplitude is the 23rd harmonic amplitude.

[0102] like Figure 3 As shown, step S3) high frequency feature calculation step specifically includes step S31) harmonic amplitude extraction step, step S32) zero rate customization step, step S33) envelope area calculation step and step S34) margin calculation step.

[0103] Step S31) Harmonic amplitude extraction step, extracting the first harmonic amplitude, the second harmonic amplitude and the third harmonic amplitude of the three-phase motor by discrete Fourier transform formula, the discrete Fourier transform formula is:

[0104]

[0105] Among them, f=0,1,2.....N-1, f represents the specific frequency generated when the motor is running; N represents the length of the cycle; W represents the complex matrix; n represents the index of the cycle length, representing the position in the cycle.

[0106] Step S32) Zero rate customization step, by customizing the zero rate to describe the proportion of the value near the zero point in the cyclic current, the formula is:

[0107]

[0108] Among them, count low It represents the number of values ​​near the zero point, n represents the number of cycles, n=32, Ii represents the cycle current, lowbound represents the upper limit of the threshold that satisfies the definition of "values ​​near the zero point", and minorrate represents the zero rate.

[0109] Step S33) Envelope area calculation step, calculating the envelope area of ​​the relationship curve between the voltage and current of each phase of the three-phase motor, the formula is:

[0110]

[0111] Among them, S U-I represents the envelope area, n represents the number of cycles, n=32, I i Indicates the frequency current, U i Indicates frequency voltage.

[0112] Step S34) Margin calculation step, calculating the sharpness of the current peak in the waveform, the formula is:

[0113]

[0114] Among them, x r Indicates the square root amplitude of the current, n indicates the number of cycles, n = 32, I i Indicates the frequency current, x peak Indicates the current amplitude, C e Represents the calculated margin.

[0115] Furthermore, the judgment criteria for whether the high-frequency feature set meets the high-frequency characteristics of the three-phase motor are: the first harmonic amplitude is greater than a first amplitude threshold, the second harmonic amplitude is greater than a second amplitude threshold, and the third harmonic amplitude is greater than a third amplitude threshold; the zero rate is less than a zero rate threshold; the UI trajectory envelope area is within a preset area threshold range; and the margin is within a preset margin threshold range.

[0116] In this embodiment, the first amplitude threshold is 1.5, the second amplitude threshold is 0.7, the third amplitude threshold is 0.3, the zero rate threshold is 0.2, and the preset area threshold range is 500. U-I <1200, margin threshold range is 1 <C e <3.5.

[0117] Step S4) Low-frequency event detection step, by creating a buffer, the size of the buffer is 1s, the buffer has a total of 10 positions for storing active power, reactive power and high-frequency feature marks, the active power and reactive power of each cycle in the circular buffer are calculated, if there is a second cycle in the cycle, the specific data point of the second cycle is marked with high-frequency features, the specific data point is a 50Hz data point, this mark can help the subsequent processing process to more easily identify and process this specific data point, each position in the buffer is used to store the active power, the reactive power and the high-frequency feature mark, if there is a position where the active power and reactive power stored meet the preset conditions, it is determined that a low-frequency event exists.

[0118] In this embodiment, in the monitoring of the motor operating status, the detection of low-frequency events is crucial for timely discovering the abnormal operation of the motor. By analyzing the motor operation data, the changes in active power and reactive power in the motor operation, as well as the extreme points of reactive power, are accurately detected, so as to determine whether a specific event has occurred, and the event is recorded and stored.

[0119] like Figure 4 As shown, step S4) the low frequency event detection step specifically includes step S41) an active power calculation step, step S42) a reactive power calculation step, step S43) an active power accumulation and calculation step, and step S44) a reactive power accumulation and calculation step.

[0120] Step S41) Active power calculation step, calculating the active power of each cycle in the ring buffer, the formula is:

[0121] P=UI cosφ

[0122] Among them, P represents active power, U represents frequency voltage, and I represents frequency current. ​

[0123] Step S42) Reactive power calculation step, calculating the reactive power of each cycle in the ring buffer, the formula is:

[0124] Q=UIsinφ

[0125] Among them, Q represents reactive power.

[0126] Step S43) Active power accumulation and calculation step, calculating the accumulated active power of each cycle in the ring buffer, the formula is:

[0127]

[0128] Among them, i represents the time, P k represents the active power at time k, P0 represents the initial value of the active power, S p (i) represents the accumulated active power.

[0129] Step S44) Reactive power accumulation and calculation step, calculating the accumulated sum of reactive power of each cycle in the ring buffer, the formula is:

[0130]

[0131] Among them, Q k represents the reactive power at time k, Q0 represents the initial value of the reactive power, S Q (i) represents the cumulative sum of reactive power.

[0132] Furthermore, the preset condition is that if there is a position m that satisfies the following two preset conditions, it is determined that the mth position and the 0th position constitute a low-frequency event:

[0133]

[0134] Among them, 1≤m≤n, abs(S P (m)) represents the accumulated and data point active power, abs(S Q (m)) represents the accumulated and data point reactive power.

[0135] In this embodiment, when the motor starts, its electromagnetic conversion process will cause significant reactive power changes. At the moment of motor startup, the stator winding needs to establish a rotating magnetic field, which requires a large amount of reactive current to support, causing the reactive power to rise sharply. When the motor is turned off, the reactive power drops sharply. Based on these significant characteristics of reactive power when the motor starts, the key events in the operation of the motor can be analyzed by comprehensive determination of reactive power and active power.

[0136] Step S5) is an operation status inspection step, performing a high-frequency feature inspection on the low-frequency events detected in each phase of the three-phase motor. If a high-frequency feature exists, a low-frequency feature inspection is performed on the low-frequency events detected in each phase of the three-phase motor. The operation status of each phase is determined according to the result of the low-frequency feature inspection. The operation status of the three-phase motor is then determined by the operation status of each phase and the time error of starting the operation status.

[0137] like Figure 5 As shown, step S5) the running status inspection step specifically includes step S51) a high-frequency feature inspection step, step S52) a low-frequency feature inspection step and step S53) a comprehensive determination step.

[0138] Step S51) high-frequency feature inspection step, for each low-frequency event detected by phase separation, detect whether the low-frequency event has high-frequency features, and the data point set included in the low-frequency event is E = {e1, e2, ..., e n}, where n represents the number of data points contained in the event, e i represents the i-th data point, i = 1, 2, ..., n; define the labeling function M(e i ), used to determine the data point e i Is it marked? When the data point e i When marked, M(e i )=1, and execute the next step; when the data point e i When not marked, M(e i )=0, and detect the next low frequency event.

[0139] Step S52) A low-frequency feature inspection step is performed, wherein a low-frequency event that passes the high-frequency feature inspection step is defined as a marked low-frequency event, and it is determined whether the marked low-frequency event has a transient low-frequency feature of motor startup. If so, and the reactive power of the marked low-frequency event is within a power threshold range, it is determined that a motor event is detected in the phase splitting.

[0140] Step S53) A comprehensive determination step is performed to determine whether the three-phase motor is in one of the three states of three-phase motor on, three-phase motor missing phase and three-phase motor off based on the motor events detected in each phase.

[0141] like Figure 6 As shown, step S52) the low frequency feature inspection step specifically includes step S54) a peak detection step, step S55) a peak ratio detection step and step S56) a power jump detection step.

[0142] Step S54) Peak detection step, by detecting the first marked low frequency event E1 = {e 11 ,e 12,..., e1n} and its adjacent next second marked low-frequency event E2 = {e 21 , e 22 ,..., e2n} satisfy the following detection conditions. If satisfied, perform the next step. If not satisfied, detect the next pair of marked low-frequency events. The detection conditions are

[0143]

[0144] e 21 -e1n == 1

[0145] where P represents active power and Q represents reactive power.

[0146] Step S55) Peak ratio detection step. Determine whether the peak ratio satisfies the determination condition. If satisfied, perform the next step. If not satisfied, detect the next peak ratio. The determination condition is

[0147]

[0148] 1.2 < g < 2.1

[0149] where g represents the peak ratio.

[0150] Step S56) Power jump detection step. By combining the first marked low-frequency event E1 = {e 11 , e 12 ,..., e1n} and the second marked low-frequency event E2 = {e 21 , e 22 ,..., e2n}, judge whether the reactive power of the low-frequency event is within the power threshold range. The reactive power calculation formula of the low-frequency event is

[0151] qdiff = Q[e2n] - Q[e 11

[0152] where qdiff represents the reactive power of the low-frequency event. When 50 < qdiff < 300, it is determined that the reactive power of the low-frequency event is within the power threshold range, and there is a motor startup event.

[0153] ​In this embodiment, for each event detected by phase splitting, the event data point is further tested for high-frequency characteristics, that is, whether the motor high-frequency characteristics are detected during the time period of the event. If the high-frequency characteristics exist, it is further determined whether the transient low-frequency characteristics of the motor start-up exist. The transient state of the motor start-up will produce a large current change, and then the current will drop sharply. Reflected in the power level, active and reactive power spikes will be generated. The low-frequency characteristic segment first performs a peak detection on the marked low-frequency event. If the peak detection passes, it is further checked for active and reactive peak peak ratio. If the ratio is greater than 1.2 and less than 2.1, it is determined that the motor low-frequency power segment characteristics are met. If the above conditions are met and the event reactive power is greater than 50 var and less than 300 var, it is determined that the phase splitting detects a motor start event.

[0154] like Figure 7 As shown, step S53) the comprehensive determination step specifically includes step S57) a three-phase motor on determination step, step S58) a three-phase motor missing phase determination step and step S59) a three-phase motor off determination step.

[0155] Step S57) Three-phase motor start determination step: when each phase detects a motor start event, the maximum time deviation of the three phase motor start event occurrence times needs to be calculated, and the formula is:

[0156] Δt max (t1,t2,t3)=max(|t1-t2|,|t2-t3|,|t1-t3|)

[0157] Among them, Δt max Indicates the maximum time deviation, t1, t2, t3 respectively represent the time when a split-phase motor starts. max <1, it is determined that the three-phase motor is in the on state.

[0158] In this embodiment, if the three phases each detect a motor start event according to the above steps, it is not possible to simply determine that the three-phase motor is turned on as a whole, because the synchronization of the three-phase motor is crucial; for this reason, it is necessary to obtain the maximum time deviation of the occurrence time of the three motor events, the purpose of which is to consider the coordination when the three-phase power supply drives the motor to start.

[0159] Step S58) A three-phase motor phase loss determination step, under the premise of detecting a three-phase motor start event, when a motor shutdown event is detected in a split phase within a preset time period, and at the same time other split phases still have motors running, the three-phase motor is determined to be in a phase loss state.

[0160] In this embodiment, under the premise that the "three-phase motor is turned on" event has been clearly detected, the system maintains continuous monitoring of the motor's operating status. Once a motor shutdown event is detected in a certain phase within 1s, and motors are still running in other phases, this inconsistent operating state points to the fault condition of "three-phase motor phase loss". The 1s time limit is set based on the characteristics of rapid changes in electrical parameters and mechanical properties after the motor phase loss, which can capture the hidden danger of phase loss at an early stage and avoid further deterioration of the fault. On the other hand, it prevents the three-phase motor from being strictly aligned in time when it is actually turned off. For example, the A-phase motor shutdown event is 0.2s earlier than the B-phase, resulting in the "three-phase motor shutdown" being mistakenly determined as "three-phase motor phase loss", causing unnecessary impact.

[0161] Step S59) A three-phase motor shutdown determination step, when no motor startup event is detected in each phase, the three-phase motor is determined to be in a shutdown state.

[0162] In this embodiment, when no motor start event is detected in each phase, it means that there is no running motor in the three phases, and the three-phase current, voltage and other data sources show that the motor is in a stationary state. At this time, it can be determined that the "three-phase motor is turned off"; this judgment is relatively intuitive, but it also relies on the precise processing of data by each module in the early stage to ensure that there will be no misjudgment due to data errors or interference.

[0163] Step S6) is a real-time recording step, in which the detected three-phase motors are matched by unique numbers, and the operating status of the three-phase motors corresponding to the numbers are recorded in real time.

[0164] The present application provides a non-invasive three-phase motor operating status identification method, which adopts a high-precision current and voltage sensor to synchronously sample the current and voltage signals of different phase lines of the three-phase motor at a sampling frequency of not less than 1600 Hz, processes the data collected by the high-precision current and voltage sensor based on the ring buffer data structure to obtain the differential current cycle, extracts the specific harmonics of the current cycle based on the fast Fourier transform algorithm, and constructs a high-frequency feature set in combination with other statistical features, calculates the active power and reactive power of the cycle in the ring buffer and performs extreme point judgment to detect the event, and the event processes the three-phase motor data source separately, judges the state of the three-phase motor and records it, so as to realize comprehensive monitoring of the operating status of the three-phase motor, and solves the problem that the existing three-phase motor operating status identification method is not comprehensive and accurate enough in monitoring the three-phase motor.

[0165] The above is a detailed introduction to the non-invasive three-phase motor operating status identification method provided by the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A non-intrusive three-phase motor operating state identification method, characterized in that: The specific steps include: A signal sampling step, synchronously sampling the current changes and voltage changes of different phase lines of the three-phase motor through a high-precision current and voltage sensor, and converting the collected voltage changes and the current changes into voltage signals and current signals; A preprocessing step of preprocessing the current signal and the voltage signal based on a ring buffer data structure to obtain a first cycle after differentiation; A high-frequency feature calculation step, extracting the first harmonic amplitude, the second harmonic amplitude and the third harmonic amplitude of the three-phase motor, calculating the characteristic zero rate, UI trajectory envelope area and margin of the first cycle, constructing the characteristic zero rate, the UI trajectory envelope area, the margin, the first harmonic amplitude, the second harmonic amplitude and the third harmonic amplitude into a high-frequency feature set, marking the first cycle of the high-frequency feature set that meets the high-frequency characteristics of the three-phase motor, and obtaining the second cycle; A low-frequency event detection step, creating a buffer, calculating the active power and reactive power of each cycle in the circular buffer, if there is a second cycle in the cycle, marking the specific data points of the second cycle with high-frequency features, each position in the buffer is used to store the active power, the reactive power and the high-frequency feature mark, if there is a position where the active power and reactive power stored meet the preset conditions, it is determined that a low-frequency event exists; as well as The step of checking the operating status is to perform a high-frequency feature check on the low-frequency events detected in each phase of the three-phase motor. If a high-frequency feature exists, a low-frequency feature check is performed on the low-frequency events detected in each phase of the three-phase motor. The operating status of each phase is determined according to the result of the low-frequency feature check. The operating status of the three-phase motor is determined by the operating status of each phase and the time error when the operating status is turned on.

2. The non-intrusive three-phase motor operating state identification method according to claim 1, characterized in that: The pre-processing step specifically comprises the following steps: The buffer establishment step includes setting a voltage ring buffer and a current ring buffer, and each buffer location stores data of one cycle; The maximum value alignment step traverses to find the maximum value index of the head pointer and the tail pointer, and realizes the alignment of the tail pointer voltage with the head pointer voltage. The calculation formula is: in, Indicates the voltage of the cycle at the head pointer of the voltage ring buffer after alignment, k = 0, 1, ..., M-1, k represents the data point of the cycle, Vh represents the voltage at the position of the head pointer of the voltage ring buffer, Indicates the maximum value index of the tail pointer of the voltage ring buffer. Indicates the maximum value index of the voltage ring buffer head pointer, M = 32; The Manhattan distance calculation step is to fix the frequency at the tail pointer of the voltage ring buffer, set the offset, traverse all offsets to calculate the Manhattan distance between the frequency at the head pointer of the voltage ring buffer and the frequency at the tail pointer of the voltage ring buffer, and record the minimum distance dmin and the corresponding offset smin. The calculation formula is: Wherein, d(s) represents the Manhattan distance, s represents the offset, s=-5,-4,...,4,5, and Vt represents the voltage at the tail pointer position of the voltage ring buffer; The frequency correction step is to correct the frequency of the head pointer in the current ring buffer according to the offset Smin calculated in the voltage ring buffer. The formula is: in, Ih represents the corrected cyclic current at the head pointer of the current ring buffer, and Ih represents the current at the head pointer in the current ring buffer; and The differential operation step is to perform a differential operation on the current cycle after correction at the head pointer of the current ring buffer and the current cycle at the tail pointer of the current ring buffer to obtain the differential current cycle, which is the first cycle, and its formula is: Wherein, Idiff represents the current cycle after differentiation, and It represents the current at the tail pointer of the current ring buffer.

3. The non-intrusive three-phase motor operating state identification method according to claim 1, characterized in that: The high-frequency feature calculation step specifically includes the following steps: The harmonic amplitude extraction step is to extract the first harmonic amplitude, the second harmonic amplitude and the third harmonic amplitude of the three-phase motor by using a discrete Fourier transform formula. The discrete Fourier transform formula is: Where, f=0,1,2.....N-1, f represents the specific frequency generated when the motor is running, N represents the length of the cycle, W represents the complex matrix, and n represents the index of the cycle length, representing the position in the cycle; Zero rate customization step, customize the zero rate to describe the proportion of the value near the zero point in the cyclic current. The formula is: Where count is the number of values ​​near zero, n is the number of cycles, n=32, Ii is the cycle current, lowbound is the upper limit of the threshold that satisfies the definition of "values ​​near zero", minorrate is indicates zero rate; The envelope area calculation step is to calculate the envelope area of ​​the relationship curve between the voltage and current of each phase of the three-phase motor, and the formula is: Among them, S U-I represents the envelope area, n represents the number of cycles, n=32, Ii represents the cycle current, Ui represents the cycle voltage; and Margin calculation steps: calculate the sharpness of the current peak in the waveform. The formula is: Wherein, xr represents the root square amplitude of the current, n represents the number of cycles, n=32, Ii represents the cycle current, xpeak represents the current amplitude, and Ce represents the calculated margin.

4. The non-intrusive three-phase motor operating state identification method according to claim 3, characterized in that: The judgment criteria of whether the high-frequency feature set meets the high-frequency feature of the three-phase motor are: The first harmonic amplitude is greater than a first amplitude threshold, the second harmonic amplitude is greater than a second amplitude threshold, and the third harmonic amplitude is greater than a third amplitude threshold; The zero rate is less than a zero rate threshold; The UI trajectory envelope area is within a preset area threshold range; The margin is within a preset margin threshold range.

5. The non-intrusive three-phase motor operating state identification method according to claim 1, characterized in that: The low-frequency event detection step specifically includes the following steps: The active power calculation step calculates the active power of each cycle in the ring buffer, and the formula is: P=UIcosφ Among them, P represents active power, U represents cycle voltage, and I represents cycle current; The reactive power calculation step calculates the reactive power of each cycle in the ring buffer, and the formula is: Q=UIsinφ Where Q represents reactive power; The active power accumulation and calculation step calculates the accumulated active power of each cycle in the ring buffer, and the formula is: Wherein, i represents the time, Pk represents the active power at time k, P0 represents the initial value of the active power, and Sp(i) represents the accumulated active power; and The reactive power accumulation and calculation step calculates the accumulated reactive power of each cycle in the ring buffer, and the formula is: Among them, Qk represents the reactive power at time k, Q0 represents the initial value of reactive power, S Q (i) represents the cumulative sum of reactive power.

6. The non-intrusive three-phase motor operating state identification method according to claim 1, characterized in that: The preset condition is: If there is a position m that satisfies the following two preset conditions, then the mth position and the 0th position are determined to constitute a low-frequency event: Among them, 1≤m≤n, abs(S P (m)) represents the accumulated and data point active power, abs(S Q (m)) represents the accumulated and data point reactive power.

7. The non-intrusive three-phase motor operating state identification method according to claim 1, characterized in that: The running state inspection step specifically includes the following steps: High-frequency feature inspection step: For each low-frequency event detected in each phase, it is detected whether the low-frequency event has high-frequency features. The set of data points included in the low-frequency event is E = {e1, e2,..., en}, where n represents the number of data points included in the event, and ei represents the i-th data point, i = 1, 2,..., n; a marking function M(ei) is defined to determine whether the data point ei is marked; when the data point ei is marked, M(ei) = 1, and the next step is executed; when the data point ei is not marked, M(ei) = 0, and the next low-frequency event is detected; Low-frequency feature inspection step: Define the low-frequency event that passes through the high-frequency feature inspection step as a marked low-frequency event, and determine whether the marked low-frequency event has the low-frequency features of motor starting transient. If it exists and the reactive power of the marked low-frequency event is within the power threshold range, it is determined that a motor event is detected in the phase; and Comprehensive determination step: Based on the motor events detected in each phase, it is determined whether the three-phase motor is in one of the three states: three-phase motor starting, three-phase motor phase loss, and three-phase motor shutdown.

8. The non-intrusive three-phase motor operating state identification method according to claim 7, characterized in that: The low-frequency feature inspection step specifically includes the following steps: Peak detection step, detecting the first marked low frequency event E1 = {e 11 ,e 12 ,...,e1n} and the next second marked low frequency event E2={e 21 ,e 22 ,...,e2n} satisfies the following detection conditions. If so, the next step is executed. If not, the next marked low-frequency event pair is detected. The detection conditions are: yes 21 -e1n==1 Where P represents active power and Q represents reactive power; Peak ratio detection step: Determine whether the peak ratio meets the determination condition. If it meets, the next step is executed; if it does not meet, the next peak ratio is detected. The determination condition is 1.2<g<2.1 Where g represents the peak ratio; and The power jump detection step combines the first marked low frequency event E1 = {e 11 ,e 12 ,...,e1n} and the second marker low frequency event E2=e 21 ,e 22 ,...,e2n} reactive power changes, judging whether the reactive power of the low-frequency event is within the power threshold range. The reactive power calculation formula of the low-frequency event is: qdiff=Q[e2n]-Q[e 11 ] Where qdiff represents the reactive power of the low-frequency event. When 50 < qdiff < 300, it is determined that the reactive power of the low-frequency event is within the power threshold range and there is a motor starting event.

9. The non-intrusive three-phase motor operating state identification method according to claim 7, characterized in that: The comprehensive determination step specifically includes the following steps: Three-phase motor starting determination step: When motor starting events are detected in each phase, the maximum time deviation of the occurrence times of the three-phase motor starting events in the three phases needs to be calculated. The formula is Δtmax(t1, t2, t3) = max(|t1 - t2|, |t2 - t3|, |t1 - t3|) Where Δtmax represents the maximum time deviation, and t1, t2, and t3 respectively represent the occurrence times of a three-phase motor starting event in a phase. When Δtmax < 1, it is determined that the three-phase motor is in the starting state; Three-phase motor phase loss determination step: On the premise that a three-phase motor starting event is detected, when it is detected that a phase has a motor shutdown event within a preset time period while there are still motors running in other phases, it is determined that the three-phase motor is in the phase loss state; and Three-phase motor shutdown determination step: When no motor starting event is detected in each phase, it is determined that the three-phase motor is in the shutdown state.

10. The non-intrusive three-phase motor operating state identification method according to claim 1, characterized in that: After the running state inspection step, there is also Real-time recording step: For the detected three-phase motors, they are all matched by a unique number, and the running states of the three-phase motors corresponding to the numbers are recorded in real time.

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