A power monitoring method and system for a highly efficient and energy-saving five-phase permanent magnet electric drum

Abstract

The present application relates to the technical field of power monitoring, and specifically to a power monitoring method and system for an efficient and energy-saving five-phase permanent magnet electric roller, the method comprising: obtaining the current data of each current phase in the five-phase permanent magnet electric roller within its preset time period, and forming a current sequence of each current phase; obtaining the multi-phase amplitude difference of each current data in the current sequence of any current phase based on the difference between the current data of the same position in the current sequence between any current phase and the remaining current phases; obtaining the multi-phase distortion degree of each current data in the current sequence of any current phase; obtaining the abnormal identification coefficient of any current phase; judging whether the power of the five-phase permanent magnet electric roller is abnormal based on the distribution of the abnormal identification coefficients of all current phases. The present application aims to improve the accuracy and efficiency of monitoring the power of the five-phase permanent magnet electric roller.

Description

Technical Field

[0001] The present application relates to the technical field of power monitoring, and in particular to a power monitoring method and system for a high-efficiency and energy-saving five-phase permanent magnet electric drum. Background Art

[0002] The five-phase permanent magnet electric drum is a high-performance five-phase permanent magnet synchronous motor with a star winding structure. It occupies an important position in industrial applications with its unique design and excellent performance, and is widely used in conveyor belt systems, transportation equipment and other fields.

[0003] For power monitoring of five-phase permanent magnet electric drums, traditional technology generally determines whether the current data of the five-phase permanent magnet electric drum exceeds the preset threshold. If exceeded, the abnormal data segment is extracted, and then the neural network model is trained through the abnormal data segment. The trained neural network model is used to monitor the power status of the five-phase permanent magnet electric drum in real time. Although traditional technology can monitor the power of permanent magnet motors, the training of neural networks requires a lot of time and energy, and is not energy-efficient. Summary of the invention

[0004] In view of the above, it is necessary to provide a high-efficiency and energy-saving five-phase permanent magnet electric drum power monitoring method and system, which improves the accuracy and efficiency of monitoring the power of the five-phase permanent magnet electric drum compared with the traditional five-phase permanent magnet electric drum power monitoring method:

[0005] In a first aspect, an embodiment of the present application provides a power monitoring method for a five-phase permanent magnet electric drum with high efficiency and energy saving, the method comprising the following steps:

[0006] Acquire current data of each current phase in the five-phase permanent magnet electric drum within a preset time period and form a current sequence of each current phase;

[0007] Based on the difference between the current data at the same position in the current sequence between any current phase and the remaining current phases, obtaining the multi-phase amplitude difference of each current data in the current sequence of any current phase;

[0008] For the current sequence of any current phase, based on the multi-phase amplitude difference of multiple current data within the local range where each current data is located, compared with the degree of deviation of the multi-phase amplitude difference of all current data in the entire current sequence, obtain the multi-phase distortion degree of each current data in the current sequence of any current phase;

[0009] Based on the distance between the current sequences of any current phase and the other current phases, and comparing the multi-phase distortion of current data at the same position in the current sequences of any current phase and the other current phases, an abnormality identification coefficient of any current phase is obtained;

[0010] Based on the distribution of the abnormality identification coefficients of all current phases, it is determined whether the power of the five-phase permanent magnet motor drum is abnormal.

[0011] In one embodiment, the current data in the current sequence is arranged in time sequence.

[0012] In one embodiment, the multi-phase amplitude difference is the sum of all the differences corresponding to each current data in the current sequence of any current phase.

[0013] In one embodiment, the process of acquiring the multi-phase distortion is as follows:

[0014] Calculating the mean of multi-phase amplitude differences of each current data in the current sequence of any current phase and the current data at multiple adjacent moments;

[0015] Calculating the average value of multi-phase amplitude differences of all current data in the current sequence of any current phase;

[0016] The multi-phase distortion degree is the difference between the mean and the average value.

[0017] In one embodiment, the process of obtaining the abnormality identification coefficient is as follows:

[0018] The multi-phase distortion degrees of all current data in the current sequence of any current phase are combined into a multi-phase distortion sequence;

[0019] The distance of the current sequence between any current phase and the remaining current phases is recorded as the current distance;

[0020] The distance of the multi-phase distortion sequence between any current phase and the remaining current phases is recorded as the distortion distance;

[0021] The abnormality identification coefficient is positively correlated with the current distance and the distortion distance respectively.

[0022] In one embodiment, the further acquisition process of the abnormality identification coefficient is:

[0023] For the current distance and the distortion distance between any one current phase and any other current phase, calculating a fusion result of the current distance and the distortion distance;

[0024] The abnormality identification coefficient is the sum of all the fusion results corresponding to any current.

[0025] In one embodiment, the process of determining whether the power of the five-phase permanent magnet electric drum is abnormal is as follows:

[0026] Arrange the normalized values ​​of the abnormality identification coefficients of all current phases according to their numerical values, and calculate the difference between any two adjacent normalized values;

[0027] By comparing the maximum value of all the difference amounts with the remaining difference amounts, it is determined whether the power of the five-phase permanent magnet motor drum is abnormal.

[0028] In one embodiment, the method for determining whether the power of the five-phase permanent magnet electric drum is abnormal is:

[0029] Calculating a cumulative value of all the difference amounts except the maximum value among all the difference amounts;

[0030] If the maximum value is greater than the accumulated value, it is determined that the power of the five-phase permanent magnet electric drum is abnormal; otherwise, there is no abnormality.

[0031] In one of the embodiments, after determining that the power of the five-phase permanent magnet electric drum is abnormal, the maximum value of the two normalized values ​​corresponding to the maximum value is recorded as the maximum normalized value, all the normalized values ​​greater than or equal to the maximum normalized value are extracted, and the current phases corresponding to all the extracted normalized values ​​are taken as abnormal current phases.

[0032] In the second aspect, an embodiment of the present application also provides a power monitoring system for an efficient and energy-saving five-phase permanent magnet electric drum, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein when the processor executes the computer program, the steps of a power monitoring method for an efficient and energy-saving five-phase permanent magnet electric drum as described above are implemented.

[0033] This application has at least the following beneficial effects:

[0034] The present application collects and preprocesses the current data of the five-phase permanent magnet electric drum, extracts the staggered current data of different current phases, and obtains the multi-phase amplitude difference by analyzing the difference between the current data of different current phases. This can accurately capture the difference between different current phases, which is helpful for the subsequent identification of the power state of the five-phase permanent magnet electric drum.

[0035] Furthermore, by analyzing the similar characteristics of the current waveforms of different current phases under the normal operation of the five-phase permanent magnet electric drum, and combining the deviation of the multi-phase amplitude difference in the local time range and the multi-phase amplitude difference in the long time range, the multi-phase distortion degree is obtained to reflect the abnormal change degree of the current waveform in the local time range, which can effectively evaluate the power state of the five-phase permanent magnet electric drum;

[0036] Furthermore, the differences between the current data of different current phases and the differences between the multi-phase distortion degrees of different current phases are combined to obtain the abnormality identification coefficient, and then the distribution of the abnormality identification coefficient is used to accurately determine whether the power of the five-phase permanent magnet electric drum is abnormal. This can significantly improve the accuracy and efficiency of monitoring the power of the five-phase permanent magnet electric drum, simplify the monitoring process, effectively shorten the monitoring cycle, and detect power abnormalities in a timely manner, thereby avoiding unnecessary maintenance of the normally working five-phase permanent magnet electric drum and reducing maintenance costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0038] Figure 1 A flowchart of a method for monitoring power of a five-phase permanent magnet electric drum with high efficiency and energy saving provided in one embodiment of the present application;

[0039] Figure 2 It is the schematic diagram of current data extraction;

[0040] Figure 3 It is a five-phase current schematic diagram;

[0041] Figure 4 Schematic diagram of five-phase current extraction data. DETAILED DESCRIPTION

[0042] In the description of the embodiments of the present application, words such as "exemplary", "or", "for example" and the like are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary", "or", "for example" and the like is intended to present related concepts in a concrete manner.

[0043] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art in the present application. The terms used in the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. It should be understood that, unless otherwise specified, " / " means or.

[0044] It should also be noted that the terms "first" and "second" in the present application are used to distinguish similar objects rather than to describe a specific order or sequence.

[0045] The specific scheme of a power monitoring method and system for a high-efficiency and energy-saving five-phase permanent magnet electric drum provided by the present application is described in detail below with reference to the accompanying drawings.

[0046] See also Figure 1 , which shows a flowchart of a power monitoring method for a high-efficiency and energy-saving five-phase permanent magnet electric drum provided by an embodiment of the present application, the method comprising the following steps:

[0047] Step S1, obtaining current data of each current phase in a five-phase permanent magnet electric drum within a preset time period, and forming a current sequence of each current phase.

[0048] Step S101, collecting current data of each current phase in a five-phase permanent magnet electric drum through an AC mutual inductor.

[0049] There are five stator windings in the five-phase permanent magnet electric drum. Since the spatial form of the stator winding is star-connected, different stator windings are connected to different currents. Therefore, there are five current phases in the five-phase permanent magnet electric drum, namely phase A, phase B, phase C, phase D, and phase E. Under normal circumstances, the stator winding is a symmetrical structure. In order to obtain a constant electromagnetic torque, when applying current to the stator winding, it is necessary to maintain a current phase difference of 0.4π between the applied currents of adjacent stator windings. In terms of timing, there is a phase difference between adjacent phases. The time difference is 100 seconds. Wherein, n represents the value of the AC frequency of the current. In this embodiment, the AC frequency is 50 Hz, so n is 50. Further, the current data of each current phase in the five-phase permanent magnet electric drum are collected respectively through the AC mutual inductor.

[0050] In this embodiment, the current data collection frequency is 1kHz, and the collection time is 0.1 seconds. The values ​​of the collection frequency and the collection time are preset manually, and the implementer can set them according to the actual situation. This application does not impose any special restrictions.

[0051] In this embodiment, the model of the AC transformer is DL-CT1010A micro current transformer, and the implementer may select other feasible AC transformers.

[0052] Step S102: Processing the collected current data.

[0053] Since there is a time gap between adjacent phases in the five-phase permanent magnet electric drum, the collected current data is extracted to facilitate subsequent calculations. The extraction method is to collect the time length of A phase, B phase, C phase, D phase and E phase for The current data in the time period of seconds, where the time period corresponding to A is recorded as the basic time period, and the time period corresponding to B is different from the start time of the basic time period. seconds, the time period corresponding to C differs from the start time of the basic time period seconds, the time period corresponding to D differs from the start time of the basic time period seconds, the time period corresponding to E differs from the start time of the basic time period Seconds. The schematic diagram of current data extraction is as follows Figure 2 As shown, Figure 2 Each small cell represents The length of time in seconds, N represents the data extraction area.

[0054] All the extracted current data of each current phase are arranged in time sequence to form a current sequence of each current phase, and the current data in each current sequence are denoised.

[0055] In this embodiment, a mean filtering method is used to denoise the current data in each current sequence. As other implementation methods, on the basis of being able to denoise the current data in each current sequence, the implementer may adopt other existing technologies, such as a Gaussian filtering algorithm, a median filtering algorithm, etc., and this application does not impose any special restrictions.

[0056] The five-phase current diagram is as follows Figure 3 The five-phase current extraction data diagram is shown in Figure 4 As shown, from Figure 4 It can be seen that under the most ideal operating state of the five-phase permanent magnet electric drum, the extracted current data of phase A, phase B, phase C, phase D and phase E are overlapping.

[0057] Step S2, based on the difference of current data at the same position in the current sequence between any current phase and the remaining current phases, obtain the multi-phase amplitude difference of each current data in the current sequence of any current phase.

[0058] During the operation of the five-phase permanent magnet electric roller, if the current of any current phase is abnormal, it will cause the operating power of the five-phase permanent magnet electric roller to be abnormal, so that the five-phase permanent magnet electric roller will no longer operate efficiently and energy-saving. Therefore, it is necessary to monitor the state of each phase current in the five-phase permanent magnet electric roller in order to promptly detect and handle current abnormalities. After the different current phases of the five-phase permanent magnet electric roller extract data through the offset time, the current amplitude difference of different current phases is small. Therefore, based on the difference between the current data of the same position in the current sequence between any current phase and the remaining current phases, the multi-phase amplitude difference of each current data in the current sequence of any current phase is obtained, and the expression is:

[0059] ; In the formula, represents the multi-phase amplitude difference of the zth current data in the current sequence of the xth current phase; m represents the number of current phases of the five-phase permanent magnet electric drum, and in this application, the value is 5; , They respectively represent the zth current data in the current sequence of the xth current phase and the yth current phase.

[0060] It should be noted that: during the operation of the five-phase permanent magnet electric drum, when the current of the xth current phase is abnormal, there is a certain amplitude difference between the current of the xth current phase and the current of other current phases. When the multi-phase amplitude difference of the current data of the xth current phase increases significantly, and the larger the value of the multi-phase amplitude difference, the higher the possibility that the current of the xth current phase is abnormal. The size of the multi-phase amplitude difference of the current data helps to identify the power state of the five-phase permanent magnet electric drum.

[0061] Step S3, for the current sequence of any current phase, based on the multi-phase amplitude difference of multiple current data within the local range where each current data is located, compared with the degree of deviation of the multi-phase amplitude difference of all current data in the entire current sequence, obtain the multi-phase distortion degree of each current data in the current sequence of any current phase.

[0062] Since in normal operation, for the current sequences of the five current phases in the five-phase permanent magnet electric drum, the shapes of the fitting curves of the current data in the five current sequences should be similar, therefore, the multi-phase amplitude differences of different current data in a single current sequence are the same or similar. When the current of the current phase is abnormal, the multi-phase amplitude differences of different current data in a single current sequence have obvious differences in value.

[0063] Based on the above analysis, for the current sequence of any current phase, the mean of the multi-phase amplitude differences of each current data in the current sequence and the current data at multiple adjacent moments is calculated, and the average of the multi-phase amplitude differences of all current data in the current sequence is calculated; the difference between the mean and the average value is used as the multi-phase distortion degree of each current data in the current sequence of any current phase.

[0064] In this embodiment, the number of neighboring moments is 4. The number of neighboring moments is preset manually and can be set by the implementer. This application does not impose any special restrictions.

[0065] In this embodiment, the difference between the mean and the average value is the absolute value of the difference. As other implementations, on the basis of being able to measure the difference between the mean and the average value, the implementer may adopt other calculation methods, such as ratio, square of difference, etc., and this application does not impose any special restrictions. In this embodiment, the expression of the multi-phase distortion degree of each current data in the current sequence of any current phase is:

[0066] ; In the formula, Indicates the multi-phase distortion degree of the zth current data in the current sequence of the xth current phase; The mean value of the zth current data in the current sequence representing the xth current phase; Represents the average value of the multi-phase amplitude differences of all current data in the current sequence of the x-th current phase.

[0067] It should be noted that: during the operation of the five-phase permanent magnet electric drum, if the current of the current phase is abnormal, the current data of the abnormal current phase will deviate significantly from the normal value, resulting in a significant difference in the multi-phase amplitude difference between the abnormal current data and other current data, making the multi-phase amplitude difference of the current data within the local time range have a large difference compared to the multi-phase amplitude difference of the current data within the long time range. The larger the value of the multi-phase distortion, the higher the possibility that the current of the x-th current phase is abnormal. By monitoring and analyzing the multi-phase distortion, the health status of the five-phase permanent magnet electric drum can be effectively evaluated, potential operating abnormalities can be discovered and prevented in a timely manner, and the stable and efficient operation of the five-phase permanent magnet electric drum can be ensured.

[0068] Step S4, based on the distance between the current sequences of the any current phase and the other current phases, and comparing the multi-phase distortion degree of the current data at the same position in the current sequences of the any current phase and the other current phases, obtaining the abnormality recognition coefficient of the any current phase.

[0069] Furthermore, the multi-phase distortion degrees of all current data in the current sequence of any current phase are arranged according to the positions of the current data in the current sequence to form the multi-phase distortion sequence of any current phase.

[0070] When the current of the current phase in the five-phase permanent magnet electric drum is abnormal, the multi-phase distortion of the current data of the abnormal current phase is greatly different from that of the current data of the normal current phase. When there is no abnormality, the current data in the current sequence of different current phases are less different.

[0071] Based on the above analysis, based on the distance of the current sequence between any current phase and the other current phases, and the distance of the multi-phase distortion sequence between any current phase and the other current phases, the abnormal identification coefficient of any current phase is obtained. The specific process is:

[0072] The distance of the current sequence between any current phase and the other current phases is recorded as the current distance; the distance of the multi-phase distortion sequence between any current phase and the other current phases is recorded as the distortion distance;

[0073] For the current distance and the distortion distance between any one current phase and any other current phase, calculating a fusion result of the current distance and the distortion distance;

[0074] The sum of all the fusion results corresponding to any current is used as the abnormality identification coefficient of any current phase.

[0075] It should be understood that fusion refers to combining multiple independent variables in a way that enhances the overall effect, such as an additive relationship, a multiplicative relationship, etc. The implementer may limit it according to the actual situation, and this application does not impose any special restrictions.

[0076] In this embodiment, the fusion result of the current distance and the distortion distance is the sum of the current distance and the distortion distance.

[0077] In another embodiment, the fusion result of the current distance and the distortion distance is the product of the current distance and the distortion distance.

[0078] In this embodiment, in the process of calculating the abnormality identification coefficient, the distances involved are all Euclidean distances. As other implementation methods, on the basis of being able to measure the distance between two current sequences and the distance between two multi-phase distortion sequences, the implementer may adopt other existing technologies for measurement, such as Manhattan distance, Chebyshev distance, etc., and this application does not impose any special restrictions.

[0079] It should be noted that: during the operation of the five-phase permanent magnet electric drum, if the current of a current phase is abnormal, the current data of the abnormal current phase will show a significant difference from the current data of other current phases, and the distance between the current sequences will increase. At the same time, the distance between the multi-phase distortion sequences will also increase, which directly reflects the degree of deviation of the abnormal current phase from other current phases in current characteristics. Therefore, the size of the abnormal identification coefficient is crucial to judging the health status and power status of the five-phase permanent magnet electric drum. By monitoring the abnormal identification coefficient, the abnormal current phase can be identified and located in time, so that necessary maintenance measures can be taken to ensure the efficient and safe operation of the five-phase permanent magnet electric drum.

[0080] Step S5, judging whether the power of the five-phase permanent magnet motor drum is abnormal based on the distribution of the abnormality identification coefficients of all current phases.

[0081] When the five-phase permanent magnet electric drum has an abnormality during operation, the abnormal identification coefficient of the abnormal current phase is larger than the abnormal identification coefficient of the normal current phase. Due to the abnormal current phase, the abnormal identification coefficient of the normal current phase is not 0. Since the value range of the abnormal identification coefficient of the normal current phase cannot be directly determined when the abnormal current phase occurs, the normalized values ​​of the abnormal identification coefficients of all current phases are obtained.

[0082] In the most ideal operating state of the five-phase permanent magnet electric drum, the abnormal identification coefficient of each current phase is 0, so the normalized value is also 0. However, in the actual operation process, even if the five-phase permanent magnet electric drum operates normally, the current data of different current phases will have slight differences, resulting in the abnormal identification coefficient of the current phase not being 0, and the normalized value of the abnormal identification coefficient is evenly distributed in [0,1]. When the current of the current phase is abnormal, the normalized value of the abnormal identification coefficient of the abnormal current phase is close to 1, and the normalized value of the abnormal identification coefficient of the normal current phase is close to 0. The normalized value of the abnormal identification coefficient of the abnormal current phase is significantly different from the normalized value of the abnormal identification coefficient of the normal current phase.

[0083] In this embodiment, the Min-Max normalization method is used to obtain the normalized values ​​of the abnormal identification coefficients of all current phases, wherein the Min-Max normalization method is a well-known technology and will not be described in detail in this application.

[0084] Based on the above analysis, the normalized values ​​of the abnormal identification coefficients of all current phases are arranged according to the numerical values, and the difference between any two adjacent normalized values ​​is calculated. The maximum value of all the difference values ​​is counted, and the cumulative value of all the difference values ​​except the maximum value is calculated. If the maximum value is greater than the cumulative value, it is determined that there is an abnormality in the current phase of the five-phase permanent magnet electric roller, and the power of the five-phase permanent magnet electric roller is abnormal. Otherwise, it is determined that there is no abnormality in the current phase of the five-phase permanent magnet electric roller, and the power of the five-phase permanent magnet electric roller is not abnormal.

[0085] In this embodiment, the difference between the normalized values ​​is the absolute value of the difference.

[0086] In this embodiment, the normalized values ​​of the abnormality identification coefficients of all current phases are arranged from small to large. As another implementation method, on the basis of satisfying the arrangement of the normalized values ​​of the abnormality identification coefficients of all current phases according to the numerical values, the implementer may also arrange the normalized values ​​of the abnormality identification coefficients of all current phases from large to small.

[0087] Furthermore, after determining that the power of the five-phase permanent magnet electric drum is abnormal, the abnormal current phase is located. The specific process is as follows:

[0088] The maximum value of the two normalized values ​​corresponding to the maximum value is recorded as the maximum normalized value, all the normalized values ​​greater than or equal to the maximum normalized value are extracted, and the current phases corresponding to all the extracted normalized values ​​are taken as abnormal current phases.

[0089] Based on the same inventive concept as the above method, an embodiment of the present application also provides a power monitoring system for a high-efficiency and energy-saving five-phase permanent magnet electric drum, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein when the processor executes the computer program, the steps of any one of the above-mentioned methods for power monitoring a high-efficiency and energy-saving five-phase permanent magnet electric drum are implemented.

[0090] In summary, the present application collects and preprocesses the current data of the five-phase permanent magnet electric drum, extracts the staggered current data of different current phases, and obtains the multi-phase amplitude difference by analyzing the difference between the current data of different current phases. This can accurately capture the difference between different current phases, which is helpful for the subsequent identification of the power state of the five-phase permanent magnet electric drum.

[0091] Furthermore, by analyzing the similar characteristics of the current waveforms of different current phases under the normal operation of the five-phase permanent magnet electric drum, and combining the deviation of the multi-phase amplitude difference in the local time range and the multi-phase amplitude difference in the long time range, the multi-phase distortion degree is obtained to reflect the abnormal change degree of the current waveform in the local time range, which can effectively evaluate the power state of the five-phase permanent magnet electric drum;

[0092] Furthermore, the differences between the current data of different current phases and the differences between the multi-phase distortion degrees of different current phases are combined to obtain the abnormality identification coefficient, and then the distribution of the abnormality identification coefficient is used to accurately determine whether the power of the five-phase permanent magnet electric drum is abnormal. This can significantly improve the accuracy and efficiency of monitoring the power of the five-phase permanent magnet electric drum, simplify the monitoring process, effectively shorten the monitoring cycle, and detect power abnormalities in a timely manner, thereby avoiding unnecessary maintenance of the normally working five-phase permanent magnet electric drum and reducing maintenance costs.

[0093] The flowchart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system, method and computer program product according to the embodiment of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of the code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. In some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which can depend on the functions involved. In the description corresponding to the flowchart and the block diagram in the accompanying drawings, the operations or steps corresponding to different boxes can also occur in a different order from the order disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which can depend on the functions involved. Each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented by a dedicated hardware-based system that performs the specified functions or actions, or may be implemented by a combination of dedicated hardware and computer instructions.

[0094] It is obvious to those skilled in the art that the present application is not limited to the details of the above exemplary embodiments, and that the present application can be implemented in other specific forms without departing from the basic features of the present application. Therefore, no matter from which point of view, the above embodiments of the present application should be regarded as exemplary and non-restrictive.

Claims

1. A power monitoring method for a five-phase permanent magnet electric drum with high efficiency and energy saving, characterized in that: The method comprises the following steps: Acquire current data of each current phase in the five-phase permanent magnet electric drum within a preset time period and form a current sequence of each current phase; The sum of the differences between each current data in the current sequence of any current phase and the current data at the same position in the current sequences of the other current phases is taken as the multi-phase amplitude difference of each current data; For the current sequence of any current phase, the difference between the mean of the multi-phase amplitude differences of each current data in the current sequence of any current phase and the current data at multiple adjacent moments and the average of the multi-phase amplitude differences of all current data in the current sequence of any current phase is taken as the multi-phase distortion degree of each current data in the current sequence of any current phase; Based on the distance between the current sequences of any current phase and the other current phases, and comparing the multi-phase distortion of current data at the same position in the current sequences of any current phase and the other current phases, an abnormality identification coefficient of any current phase is obtained; Based on the distribution of abnormal identification coefficients of all current phases, determine whether the power of the five-phase permanent magnet electric drum is abnormal; The process of obtaining the abnormal identification coefficient is as follows: The multi-phase distortion degrees of all current data in the current sequence of any current phase are combined into a multi-phase distortion sequence; The distance of the current sequence between any current phase and the remaining current phases is recorded as the current distance; The distance of the multi-phase distortion sequence between any current phase and the remaining current phases is recorded as the distortion distance; The abnormality identification coefficient is positively correlated with the current distance and the distortion distance respectively.

2. A power monitoring method for a high-efficiency and energy-saving five-phase permanent magnet electric drum as claimed in claim 1, characterized in that: The current data in the current sequence are arranged in time sequence.

3. The power monitoring method of a high-efficiency and energy-saving five-phase permanent magnet electric drum according to claim 1 is characterized in that: The further acquisition process of the abnormal identification coefficient is as follows: For the current distance and the distortion distance between any one current phase and any other current phase, calculating a fusion result of the current distance and the distortion distance; The abnormality identification coefficient is the sum of all the fusion results corresponding to any current.

4. The power monitoring method of a high-efficiency and energy-saving five-phase permanent magnet electric drum according to claim 1 is characterized in that: The process of judging whether the power of the five-phase permanent magnet electric drum is abnormal is as follows: Arrange the normalized values ​​of the abnormality identification coefficients of all current phases according to their numerical values, and calculate the difference between any two adjacent normalized values; By comparing the maximum value of all the difference amounts with the remaining difference amounts, it is determined whether the power of the five-phase permanent magnet motor drum is abnormal.

5. A power monitoring method for a high-efficiency and energy-saving five-phase permanent magnet electric drum as claimed in claim 4, characterized in that: The method for judging whether the power of the five-phase permanent magnet electric drum is abnormal is: Calculating the cumulative value of all the difference amounts except the maximum value among all the difference amounts; If the maximum value is greater than the accumulated value, it is determined that the power of the five-phase permanent magnet electric drum is abnormal; otherwise, there is no abnormality.

6. A power monitoring method for a high-efficiency and energy-saving five-phase permanent magnet electric drum as claimed in claim 5, characterized in that: After determining that the power of the five-phase permanent magnet electric drum is abnormal, the maximum value of the two normalized values ​​corresponding to the maximum value is recorded as the maximum normalized value, all the normalized values ​​greater than or equal to the maximum normalized value are extracted, and the current phases corresponding to all the extracted normalized values ​​are taken as abnormal current phases.

7. A power monitoring system for a five-phase permanent magnet electric drum with high efficiency and energy saving, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the power monitoring method of a high-efficiency and energy-saving five-phase permanent magnet electric drum as described in any one of claims 1 to 6 are implemented.

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