A non-invasive identification method and identification system based on power phase characteristics

Abstract

The application provides a non-invasive identification method and system based on power stage characteristics. The non-invasive identification method comprises collecting the voltage and current of a total power supply and calculating an average active power sequence; setting a first screening condition to extract effective pulses and original events from the average active power sequence; selecting an inflection point pair in which the change amount of active power in the original event is greater than a first preset threshold value, and one inflection point pair forms a feature set; one inflection point pair comprises adjacent inflection points; setting a second screening condition to obtain a first event from the feature set; defining the feature set as an instance; the second screening condition comprises that the increment of active power in the instance is less than or equal to the first threshold value; the maximum active power difference of adjacent instances is greater than a second threshold value; and determining whether the number of first events is greater than or equal to a first preset number value. If yes, it is confirmed that the washing machine is running, so as to solve the technical problem that the existing identification method has a high time complexity and cannot run efficiently.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of smart grid, in particular to a non-invasive identification method and system based on power phase characteristics. BACKGROUND

[0002] Smart power consumption is an important part of connecting the grid side and the user side to realize the smart grid, which has a great influence on the efficient and economic operation of the entire power grid and future power grid construction and planning. Power user load detail monitoring is the first step to realize smart power consumption. Load monitoring technology monitors the running and closing state of each electric appliance in the user by sampling and analyzing the total load data of the user to obtain the power consumption and power consumption behavior of each electric appliance of the power user.

[0003] The currently widely used non-invasive load identification technology relies on algorithm research on load characteristics during operation of different electric appliances. Load characteristics include electric appliance characteristics unique to electric appliances during power consumption, including current, active and reactive power, instantaneous power, V-I curve, P-t curve, switching transient, running steady state, etc. of the electric appliance. The research on load characteristics of household appliances is an important basis for power demand side management. Currently known household appliances can be divided into electric appliances composed of motor elements and electric appliances composed of heating resistors, i.e. two categories of motor and heater. Among them, the running state of the motor is more complex than that of the heater, the current and power fluctuation is large, the starting process has an impact current, and it is accompanied by a large amount of harmonics, and its P-t curve reaction is strong fluctuation and unclear rule.

[0004] Washing machines are one of the typical electric appliances of the motor class (although the heating resistor works when the washing machine's heating mode is running). The existing research has analyzed the model and operating characteristics of washing machine load in detail. Its speed is usually 1200r / min, its washing power is generally between 100w and 300w, and its dehydration power is generally between 300w and 400w. The heating resistor works when the washing machine's heating mode is running, and it is basically the same as other typical heaters (such as water heaters, electric kettles, electric heaters) except for the difference in power amplitude, so only the heating characteristics cannot achieve the purpose of identifying the washing machine. Its motor operating characteristics are different from other motors and have obvious characteristics, which are still the main basis for identification.

[0005] The limitation of the current washing machine identification method is that the time complexity is too high to run efficiently. SUMMARY

[0006] The application provides a non-invasive identification method and system based on power phase characteristics to solve the technical problem that the existing washing machine identification method has high time complexity and cannot operate efficiently.

[0007] The application provides a non-invasive identification method based on power phase characteristics, comprising:

[0008] Real-time collection of voltage signals and current signals of the total power supply, and calculation of average active power sequences and average reactive power sequences;

[0009] Setting a first screening condition to extract effective pulses from the average active power sequences and original events formed by the effective pulses;

[0010] Selecting at least two inflection point pairs in which the change amount of active power in the original events is greater than a first preset threshold value, each inflection point pair forming a feature set; each inflection point pair includes two adjacent active power inflection points;

[0011] Setting a second screening condition to obtain at least one first event from at least two feature sets; the feature set is defined as an instance within the active power sequence; the second screening condition includes:

[0012] The increment of active power in the instance is less than or equal to a first threshold value, and the range of the first threshold value is 400-1200; the difference between the maximum active power of adjacent instances is greater than a second threshold value, and the range of the second threshold value is 100-600;

[0013] Judging whether the number of first events is greater than or equal to a first preset number value, and if yes, confirming that there is a washing machine operation within the active power sequence.

[0014] Optionally, the elements of the feature set include the start time, the end time, the time span, the power at the start time, the power at the end time, the change amount of power, the ratio of the change amount of power to the time span, the difference, and the derivative.

[0015] Optionally, a third screening condition is set to screen a second event from the first event; the third screening condition includes that the active power difference between adjacent two instances is less than a second preset number value, and the range of the second preset number value is 50-60; the active power increment of the instance is positive, if yes, the value of the active power increment is greater than a third preset number value, and the range of the third preset number value is 250-300; if not, the value of the active power increment is less than a fourth preset number value, and the range of the fourth preset number value is -300--250.

[0016] Optionally, when it is confirmed that there is a washing machine operation within the active power sequence, the following steps are performed:

[0017] setting a fourth screening condition to screen a first part of the third event from the first event; the fourth screening condition comprises: the value range of the active power increment of the first two instances in the first event is -200-200, the absolute value of the previous active power increment is greater than the absolute value of the subsequent active power increment; and the active power increments of the two instances are opposite in direction; and the sum of the time span of the instances in one first event is less than a fifth preset value, and the range of the fifth preset value is 90-100;

[0018] setting a fifth screening condition to screen a second part of the third event from the first event; the fifth screening condition comprises: the ratio of the power change amount to the time span of any instance includes a first slope and a second slope, when the span of time is 2-10S, the range of the first slope is -4--0.5; when the span of the event is 10-120S, the range of the second slope is -0.5-0.5; the sum of the time span of the instances in one first event is less than a sixth preset value, and the range of the sixth preset value is 180-220.

[0019] Optionally, the first screening condition comprises the following steps:

[0020] obtaining all inflection points in the active power sequence;

[0021] obtaining at least one initial inflection point pair based on the active power difference between adjacent inflection points being greater than the minimum pulse rise height limit;

[0022] screening at least one valid inflection point pair from the initial inflection point pair based on the time span of two inflection points being greater than the minimum pulse span, and the difference between the active power of the subsequent inflection point and the active power of the previous inflection point being less than the maximum pulse difference threshold; any valid inflection point pair determines one valid pulse.

[0023] Optionally, in the step of setting the first screening condition to extract valid pulses from the average active power sequence and the original event composed of the valid pulses, the following steps are included:

[0024] setting a sixth screening condition to screen a primary screening event from the original event; the sixth screening condition comprises:

[0025] selecting, based on the average active power sequence, a valid pulse with an active power range from the start time to the end time being greater than a second preset threshold, a time span being greater than or equal to a third preset threshold, and a power difference between the start time and the end time being less than or equal to a fourth preset threshold.

[0026] Optionally, the first preset threshold ranges from 90 to 150; the second preset threshold ranges from 60 to 120; and the third preset threshold ranges from 10 to 50.

[0027] Optionally, after the step of confirming the existence of the washing machine operation in the active power sequence, the method further comprises the following steps: adding all events by using a summation function, and calculating the total power consumption of the washing machine.

[0028] Correspondingly, the application further provides a non-invasive identification system based on power phase characteristics, which comprises a memory and a processor, the memory is used for storing executable program codes; the processor is connected to the memory, and runs a computer program corresponding to the executable program codes by reading the executable program codes, so as to execute the steps in any one of the above non-invasive identification methods based on power phase characteristics.

[0029] Optionally, the non-invasive identification system based on power phase characteristics further comprises a power calculator, which is electrically connected to the processor; the power calculator adds events in each phase by using a summation function, and calculates the total power consumption of the washing machine.

[0030] The application provides a non-invasive identification method and system based on power phase characteristics. During the washing process of the washing machine, the motor rotates periodically, so that the running power of the washing machine is relatively large. Therefore, the first running phase is selected from the running process of the washing machine based on the form of the active power and the reactive power changing with time in the washing phase, the corresponding screening condition is set according to the event characteristics of the running phase, the first event in the phase is identified and extracted respectively, and whether the washing machine runs is judged based on the number of the first events, so that the washing machine can be identified simply, efficiently and accurately.

[0031] The running process of the washing machine is sequentially divided into a first running phase, a second running phase and a third running phase, the corresponding screening condition is set according to the event characteristics of each running phase, and the events in the phase are identified and extracted respectively, so as to improve the accuracy of washing machine identification.

[0032] The total power consumption of the washing machine is calculated based on the first event, the second event and the third event screened in each running phase, so that the user and the designer can know the power consumption of the washing machine in each running process, and the scheme is further designed to reduce the power consumption of the washing machine. BRIEF DESCRIPTION OF DRAWINGS

[0033] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments description will be briefly introduced. Obviously, the drawings in the following description only constitute some embodiments of the present application, and all other drawings obtained by those skilled in the art without creative effort based on these drawings also belong to the protection scope of the present application. In addition, it should be understood that the specific embodiments described herein are only used to illustrate and explain the present application, and are not used to limit the present application. In the present application, the orientation words such as "upper", "lower", "left", "right" generally refer to the upper, lower, left and right of the device in the actual use or working state, and specifically refer to the drawing direction in the drawings.

[0034] Figure 1 is a flowchart of the non-invasive identification method based on power phase characteristics provided by the present application;

[0035] Figure 2 is a process diagram of extracting the preliminary screening event in step S200 in the non-invasive identification method based on power phase characteristics provided by the present application;

[0036] Figure 3 is the division of washing machine running phases in the non-invasive identification method based on power phase characteristics provided by the present application;

[0037] Figure 4 is the event feature map of the first phase of the washing machine in the non-invasive identification method based on power phase characteristics provided by the present application;

[0038] Figure 5 is the event feature map of the second phase of the washing machine in the non-invasive identification method based on power phase characteristics provided by the present application;

[0039] Figure 6 is the event feature map of the third phase of the washing machine in the non-invasive identification method based on power phase characteristics provided by the present application. DETAILED DESCRIPTION

[0040] The technical solutions in the embodiments of the present application will be described clearly and completely in the following with reference to the drawings of the embodiments of the present application. Obviously, the described embodiments only constitute some embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative effort also belong to the protection scope of the present application. In addition, it should be understood that the specific embodiments described herein are only used to illustrate and explain the present application, and are not used to limit the present application. In the present application, the orientation words such as "upper", "lower", "left", "right" generally refer to the upper, lower, left and right of the device in the actual use or working state, and specifically refer to the drawing direction in the drawings.

[0041] The application provides a non-invasive identification method and system based on power phase characteristics, which are described in detail below. It should be noted that the order of the following embodiments is not limited as the preferred order of the embodiments of the application. In the following embodiments, each embodiment is described with emphasis, and the parts not described in detail in a certain embodiment can be referred to the related description of other embodiments.

[0042] Please refer to Figure 1 The application provides a non-invasive identification method based on power phase characteristics, which is based on the motor operating characteristics of a washing machine as the basis for identification. The operation of the washing machine is divided into four processes: washing, draining, dewatering and water filling. In the washing and dewatering processes, the motor rotates periodically in the direction, so that the operating power of the washing machine is relatively large, about 200w to 800w, and the mode is relatively fixed and the form is relatively stable. Therefore, the active power and the reactive power can be extracted according to the rules of the change over time. The non-invasive identification method based on power phase characteristics in the application is mainly applicable to the pulsator washing machine, of course, it can also be applicable to the drum washing machine. The identification steps of the two types of washing machines are basically the same, except that the specific screening values may be different based on different types. In this embodiment, the identification method applicable to the pulsator washing machine is taken as an example for description, but the scheme applicable to the drum washing machine also belongs to the protection scope of the application.

[0043] A non-invasive identification method based on power phase characteristics, specifically comprising the following steps:

[0044] S100, in a preset sampling range, real-time acquisition of voltage signal and current signal of total power supply, so as to obtain voltage signal sampling sequence u and current signal sampling sequence i; and calculation of average active power sequence and average reactive power sequence;

[0045] The voltage signal and the current signal of the total power supply are collected in real time by the monitoring device installed at the total power supply. By a series of processing on the obtained voltage signal sampling sequence u and current signal sampling sequence i, the type and operation of a single load in the load cluster can be obtained. The voltage signal, current signal, active power and reactive power and other characteristics in each electrical appliance are different, so different electrical equipment can be identified based on the differences between the characteristic parameters of each electrical appliance.

[0046] The value of the above-mentioned preset sampling range is mainly selected considering the performance of the equipment and other factors. In the application, the voltage signal and the current signal of the total power supply are collected at the power inlet with a sampling frequency of 10HZ.

[0047] The average active power P is calculated according to the following formula:

[0048]

[0049] Wherein, T is the period of the periodic AC signal, U is the voltage effective value, and I is the current effective value.

[0050] The average reactive power sequence Q is calculated according to the following formula:

[0051]

[0052] Wherein, T is the period of the periodic AC signal, U is the voltage effective value, and I is the current effective value.

[0053] S200, set the first screening condition, extract the effective pulse and the original event composed of the effective pulse from the average active power sequence;

[0054] Wherein, the first screening condition includes the following steps:

[0055] S210, obtain all the inflection points in the active power sequence;

[0056] Based on the active power sequence P obtained in step S100, all the inflection points are screened out according to formula (1) and formula (2), which are respectively:

[0057] P i ≥P i-1 And P i >P i+1 (1)

[0058] P i ≤P i+1 And P i <P i+1 (2)

[0059] Wherein, P is the active power, and i is the time.

[0060] S220, based on the condition that the active power difference between adjacent inflection points is greater than the minimum pulse rise height, obtain at least one initial inflection point pair;

[0061] Based on all the inflection points obtained in the foregoing steps, adjacent inflection points with an active power difference greater than the minimum pulse rise height are screened out and recorded as initial inflection point pairs.

[0062] S230, based on the condition that the time span of two inflection points is greater than the minimum pulse span, and the difference between the active power of the latter inflection point and the active power of the former inflection point is less than the maximum pulse difference threshold, at least one effective inflection point pair is screened out from the initial inflection point pairs, and any effective inflection point pair determines an effective pulse;

[0063] Based on all the initial inflection points obtained in the foregoing, valid inflection point pairs are sequentially selected from the plurality of initial inflection point pairs according to a screening condition that a time span is greater than a minimum pulse span and an active power difference between a latter inflection point and a former inflection point is less than a maximum pulse difference threshold, so as to extract valid pulses.

[0064] S300, a sixth screening condition is set to screen out pre-screening events from the original events; the sixth screening condition comprises:

[0065] Based on the average active power sequence, an effective pulse is selected, in which a range of active power from a start time to an end time is greater than a second preset threshold, a time span is greater than or equal to a third preset threshold, and a power difference between the start time and the end time is less than or equal to a fourth preset threshold;

[0066] Please refer to Figure 2 Based on the intercepted average active power sequence, all original events are selected, in which a range of active power from a start time to an end time is greater than a first preset threshold, a distance difference between the start time and the end time is greater than or equal to a second preset threshold, and an active power difference between the start time and the end time is less than or equal to a third preset threshold, so as to screen out pre-screening events.

[0067] The first preset threshold is a minimum pulse rising height, the range of the minimum pulse rising height can be 90-150; the second preset threshold is a minimum pulse span, the range of the minimum pulse span can be 60-120; and the third preset threshold is a maximum pulse difference, the range of the maximum pulse difference can be 10-50. The amplitudes of active power of events at different gears such as washing, draining, dehydration and water filling of the pulsator washing machine are between 100W and 400W, so that by limiting the appropriate ranges of the minimum pulse rising height, the minimum pulse span and the maximum pulse difference, the accuracy of the recognition result of the washing machine can be improved.

[0068] S400, at least two inflection point pairs in which a variation of active power is greater than a first preset threshold are selected from the pre-screening events, each of the inflection point pairs forms a feature set; each of the inflection point pairs comprises two adjacent inflection points of active power.

[0069] The elements of the feature set comprise a start time, a stop time, a time span, a power at the start time, a power at the stop time, a variation of power, a ratio of the variation of power to the time span, a difference and a derivative.

[0070] All the inflection point pairs in which the variation of active power is greater than the first preset threshold are selected from the pre-screening events in the foregoing, each of the inflection point pairs can form a feature set, and the feature set is a rising or falling line.

[0071] S500, setting a second screening condition to obtain at least one first event from at least two of the feature sets; the feature sets are defined as instances in the active power sequence; the second screening condition includes that the increment of the active power in the instance is less than or equal to a first threshold value, and the first threshold value can range from 400 to 1200; the difference between the maximum active power of adjacent instances is greater than a second threshold value, and the second threshold value can range from 100 to 600;

[0072] In each operating phase (the first operating phase, the second operating phase, and the third operating phase) of the drum washing machine, the feature sets are defined as instances, and the instances are rising or falling lines.

[0073] Based on all the feature sets screened out in the foregoing steps, a part of the instances are screened out from the multiple instances according to the second screening condition, and at least one first event is obtained from the part of the instances, so as to ensure that the obtained first event meets the characteristics of the event in the first operating phase of the drum washing machine. Each first event in the present application can be composed of 2 or 3 instances.

[0074] Referring to Figure 3 and Figure 4 , the first operating phase characteristics of the drum washing machine include that the increment of the active power in the instance is less than or equal to the first threshold value, and the difference between the maximum active power of adjacent instances is greater than the second threshold value, so the second screening condition in step S500 corresponds to the characteristics of the first operating phase. The first operating phase characteristics correspond to the washing process in the drum washing machine, so the first event screened out based on the second screening condition meets the event characteristics in the first operating phase, and thus can be used to assist in identifying whether the drum washing machine is running in the first operating phase.

[0075] S600, obtaining the number of the first events, and determining whether the number of the first events is greater than or equal to a first preset number value; if yes, it is determined that the drum washing machine is running in the active power sequence; if no, it is determined that the drum washing machine is not running in the active power sequence.

[0076] The first event is selected based on the second screening condition and meets the characteristics of the first operating phase of the drum washing machine, and when the number of the first events is greater than or equal to the first preset number value, it is determined that the drum washing machine is running in the first operating phase. The first preset number value is the minimum number of the drum washing machine running in an active power sequence, and the first preset number in the present application can be 10.

[0077] S700, setting a third screening condition to screen out a second event from the first event; the third screening condition includes that the difference between the active power of adjacent two instances is less than a second preset number value, and the second preset number value ranges from 50 to 60;

[0078] determining whether the active power increment of the instance is positive, if yes, the value of the active power increment is greater than a third preset value, the third preset value ranges from 250 to 300; if no, the value of the active power increment is less than a fourth preset value, the fourth preset value ranges from -300 to -250;

[0079] When the non-intrusive recognition method based on the power stage characteristics determines that the first running stage of the pulsator washing machine exists, step S700 can be continued to recognize the second running stage of the pulsator washing machine, so as to improve the accuracy of the washing machine recognition.

[0080] Please refer to Figure 3 and Figure 5 , the second running stage characteristics of the pulsator washing machine include that the active power difference between two adjacent instances in the instance is less than a second preset value; when the active power increment of the instance is positive, the value of the active power increment should be greater than a third preset value, and when the active power increment of the instance is negative, the value of the active power increment should be less than a fourth preset value; therefore, the third screening condition in step S700 corresponds to the characteristics of the second running stage.

[0081] The second running stage characteristics correspond to the washing process in the pulsator washing machine, the second event screened based on the third screening condition meets the event characteristics in the second running stage, and therefore can be used to assist in recognizing the second running stage of the pulsator washing machine. When the non-intrusive recognition method screens the second event, it can be confirmed that the second running stage of the washing machine exists in the active power sequence, so as to improve the accuracy of the washing machine recognition.

[0082] S810, a fourth screening condition is set to screen a first part of the third event from the first event; the fourth screening condition includes that the values of the active power increments of the first two instances in the first event are similar, the values range from -200 to 200, the absolute value of the previous active power increment is greater than the absolute value of the latter active power increment, and the active power increments of the two instances are opposite in direction; and the time span sum of the instances in the first event is less than a fifth preset value, the fifth preset value ranges from 90 to 100;

[0083] S820, set a fifth screening condition to screen a second part of the third event from the first event; the fifth screening condition comprises: a ratio of a power change amount of any one of the instances to a time span comprises a first slope and a second slope, when the time span is 2-10s, the first slope ranges from -4 to -0.5; when the event span is 10-120s, the second slope ranges from -0.5 to 0.5; a sum of the time spans of the instances in the first event is less than a sixth preset number value, and the sixth preset number value ranges from 180 to 220;

[0084] Referring to Figure 3 and Figure 6 , the third running phase of the impeller washing machine can be divided into an earlier short event and a later long event, and the characteristics of the earlier short event meet the fourth screening condition, and the characteristics of the later long event meet the fifth screening condition. The characteristics of the earlier short event in the running of the impeller washing machine are not obvious, and therefore the identification of the third running phase of the impeller washing machine depends on the characteristics of the later long event.

[0085] The characteristics of the short event in the third running phase of the impeller washing machine include that the active power increments of the first two instances in a first event are similar in value, the absolute value of the active power increment in the former instance is greater than that in the latter instance, and the active power increments of the two instances are opposite in direction, that is, one is an upward line and the other is a downward line. Based on Figure 6 The fourth screening condition in step S810 corresponds to the characteristics of the first half of the third phase in

[0086] The characteristics of the first half of the third running phase correspond to the dehydration process in the impeller washing machine, and therefore the first part of the third event screened based on the fourth screening condition meets the event characteristics in the first half of the third running phase, and therefore can be used to assist in identifying the third running phase of the impeller washing machine.

[0087] According to the characteristics of the long event in the third running phase of the impeller washing machine, when the time span is 2-10s, the first slope ranges from -4 to -0.5, as shown by the highlighted first part in the schematic diagram of the second half of Figure 6 According to the characteristics of the long event in the third running phase of the impeller washing machine, when the event span is 10-120s, the second slope ranges from -0.5 to 0.5, as shown by the relatively smooth second part in the schematic diagram of the second half of Figure 6 According to the characteristics of the long event in the third running phase of the impeller washing machine, when the event span is 10-120s, the second slope ranges from -0.5 to 0.5, as shown by the relatively smooth second part in the schematic diagram of the second half of Figure 6 The fifth screening condition in step S820 corresponds to the characteristics of the second half of the third phase in

[0088] The latter half of the third operation phase corresponds to the dehydration process in the pulsator washing machine, and thus the second part of the third event screened based on the fifth screening condition meets the event feature in the latter half of the third operation phase, and thus can be used to assist in identifying the third operation phase of the pulsator washing machine. When the non-intrusive identification method screens the first part and the second part of the third event, it can be confirmed that the third operation phase of the washing machine exists in the active power sequence, thereby improving the accuracy of washing machine identification.

[0089] S900, adding all events by using a summation function and calculating the total power consumption of the washing machine.

[0090] The total power consumption of the pulsator washing machine is calculated according to the following formula:

[0091]

[0092] wherein E P is the active power, P is the active power, i is the time, and j is the operation phase of the washing machine.

[0093] The foregoing non-intrusive identification method based on power phase features in the present application includes all identification steps of the first operation phase, the second operation phase and the third operation phase of the washing machine. In other schemes, the non-intrusive identification method only includes identification of the first operation phase of the washing machine, or only includes identification of the first operation phase and the second operation phase, or only includes identification of the first operation phase and the third operation phase; the above schemes all belong to the protection scope of the present application.

[0094] During the washing and dehydration processes of the washing machine, the motor rotates periodically, so that the operation power of the washing machine is relatively large. Therefore, the operation process of the washing machine is divided into three phases based on the form of change of the active power and the reactive power with time during the washing and dehydration phases, events in each phase are identified and extracted respectively based on different screening conditions, so that different operation phases of the washing machine are identified, and thus the washing machine can be identified simply, efficiently and accurately.

[0095] Meanwhile, the total power consumption of the washing machine can be calculated based on the first event, the second event and the third event screened in each operation phase, so as to facilitate the user and the designer to understand the power consumption of the washing machine in each operation process, thereby further designing a scheme to reduce the power consumption of the washing machine.

[0096] The present application also provides a non-intrusive identification system based on power phase features, which includes a memory and a processor, the memory is used to store executable program code; the processor is connected to the memory, and runs the computer program corresponding to the executable program code by reading the executable program code, so as to execute the steps in the foregoing non-intrusive identification method based on power phase features.

[0097] In addition, the non-invasive identification system based on power phase characteristics further comprises an electricity calculator, which is electrically connected to the processor and can add the events (the first event, the second event and the third event) of each operation phase by using a summation function and calculate the total electricity consumption of the washing machine.

[0098] The above describes in detail the non-invasive identification method and identification system based on power phase characteristics provided by the present application. The principles and implementation manners of the present application are described by using specific examples. The above description of the examples is only used to help understand the method of the present application and its core idea. Meanwhile, for those skilled in the art, the specific implementation manners and application ranges will be changed according to the idea of the present application. In summary, the content of the specification should not be understood as a limitation of the present application.

Claims

1. A non-invasive identification method based on power phasic features, characterized in that, The method comprises: real-time acquisition of voltage signals and current signals of a total power supply, and calculation of average active power sequences and average reactive power sequences; setting a first screening condition to extract effective pulses from the average active power sequences and original events formed by the effective pulses; selecting at least two inflection point pairs in which the change of active power in the original events is greater than a first preset threshold value, each of the inflection point pairs forming a feature set; each of the inflection point pairs including two adjacent active power inflection points; setting a second screening condition to obtain at least one first event from the at least two feature sets; the feature set in the segment of active power sequences is defined as an instance; the second screening condition includes: the increment of active power in the instance is less than or equal to a first threshold value, the range of the first threshold value being 400-1200; the difference between the maximum active power of adjacent instances is greater than a second threshold value, the range of the second threshold value being 100-600; judging whether the number of the first events is greater than or equal to a first preset number value, if yes, it is confirmed that the segment of active power sequences has a washing machine running.

2. The non-invasive identification method based on power phase characteristics according to claim 1, characterized in that, the elements of the feature set include the start time, the end time, the time span, the power at the start time, the power at the end time, the change of power, the ratio of the change of power to the time span, the difference and the derivative.

3. The method of claim 1, wherein the power phase-based feature is a power phase-based feature of a user. after it is confirmed that the segment of active power sequences has a washing machine running, the following steps are performed: setting a third screening condition to screen a second event from the first events; the third screening condition includes: the difference between the active power of adjacent two instances is less than a second preset number value, the range of the second preset number value being 50-60; judging whether the increment of active power of the instance is positive, if yes, the value of the increment of active power is greater than a third preset number value, the range of the third preset number value being 250-300; if not, the value of the increment of active power is less than a fourth preset number value, the range of the fourth preset number value being -300--250.

4. The non-invasive identification method based on power phase characteristics according to claim 1 or 3, characterized in that, after it is confirmed that the segment of active power sequences has a washing machine running, the following steps are performed: setting a fourth screening condition to screen a first part of a third event from the first events; the fourth screening condition includes: the value range of the increment of active power of the first two instances in the first event is -200-200, the absolute value of the previous increment of active power is greater than the absolute value of the subsequent increment of active power; and the increments of active power of the two instances are opposite in direction; meanwhile, the sum of the time spans of the instances in a first event is less than a fifth preset number value, the range of the fifth preset number value being 90-100; setting a fifth screening condition to screen a second part of the third event from the first events; the fifth screening condition includes: The ratio of the power change amount of any of the instances to the time span includes a first slope and a second slope, the first slope ranges from -4 to -0.5 when the time span is 2-10 seconds, the second slope ranges from -0.5 to 0.5 when the time span is 10-120 seconds, and the sum of the time spans of the instances in the first event is less than a sixth preset number, which ranges from 180 to 220.

5. The method of claim 1, wherein the power phase-based feature is a power phase-based feature of a user. The first screening condition includes the following steps: Obtaining all inflection points in the active power sequence; Based on the active power difference between adjacent inflection points being greater than the minimum pulse rise height limit, obtaining at least one initial inflection point pair; Based on the time span of two inflection points being greater than the minimum pulse span, and the difference between the active power of the latter inflection point and the active power of the former inflection point being less than the maximum pulse difference threshold, screening at least one valid inflection point pair from the initial inflection point pair, any of the valid inflection point pairs determines a valid pulse.

6. The method of claim 1, wherein the power phase-based feature is a power phase-based feature of a user. In the step of setting the first screening condition, extracting valid pulses from the average active power sequence, and the original event composed of the valid pulses, the following steps are included: Setting a sixth screening condition to screen out a primary screening event from the original event; the sixth screening condition includes: Based on the average active power sequence, selecting the valid pulse with an active power range from the start time to the end time being greater than a second preset threshold, the time span being greater than or equal to a third preset threshold, and the power difference between the start time and the end time being less than or equal to a fourth preset threshold.

7. The non-intrusive identification method based on power phase characteristics according to claim 6, characterized in that, The first preset threshold ranges from 90 to 150, the second preset threshold ranges from 60 to 120, and the third preset threshold ranges from 10 to 50.

8. The non-invasive identification method based on power phase characteristics according to claim 1, characterized in that: After the step of confirming that the washing machine is running in the active power sequence, the following steps are included: Using a summation function to add all events and calculating the total power consumption of the washing machine.

9. A non-invasive identification system based on power phasic features, characterized by, Including: a memory for storing executable program code; and a processor connected to the memory, running the computer program corresponding to the executable program code by reading the executable program code, to perform the steps in the non-intrusive identification method based on power phase characteristics according to any of claims 1-8.

10. The non-invasive identification system based on power phasic features of claim 9, wherein, Further including: a power calculator electrically connected to the processor; the power calculator uses a summation function to add events in each phase and calculates the total power consumption of the washing machine.

Images