Method and system for predicting spark flashover point occurrence position of pulse high voltage power supply

Abstract

The application discloses a kind of spark flashover point generation position prediction method and system of pulse high voltage power supply, obtain spark flashover characteristic database from initial time to the total number of spark flashover stored during current time, determine the spark flashover number of each partition in total number of spark flashover, based on total number of spark flashover and the spark flashover number corresponding to each partition, obtain the current occurrence probability of spark flashover of each partition, determine the instantaneous impedance variation law of each partition when flue gas working condition parameter changes, based on the current occurrence probability corresponding to each partition spark flashover and instantaneous impedance variation law of spark flashover, using random optimization algorithm, obtain the predicted occurrence position and predicted occurrence probability of spark flashover point next time.The application realizes the predicted occurrence position and predicted occurrence probability of spark flashover point next time, to improve the intelligent control level of pulse high voltage power supply.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of high-voltage power supply, more particularly, to a method and system for predicting the occurrence position of spark flashover point of a pulsed high-voltage power supply. BACKGROUND

[0002] The pulsed high-voltage power supply is an important power supply device for electric dust collectors and plasma reactors. The pulsed high-voltage power supply outputs a relatively narrow high-voltage pulse during operation, and the pulse width is generally tens of microseconds to hundreds of microseconds, and the pulse repetition frequency is generally tens to hundreds. Under the working condition, the load (electric dust collector and plasma reactor) of the pulsed high-voltage power supply is a capacitive load, and the pulse voltage waveform in the load is similar to a cosine waveform, and the pulse current waveform is similar to a sine waveform. Generally, the higher the voltage peak value in the electric field of the electric dust collector and the plasma reactor, the higher the operating efficiency of the device. However, an excessively high operating voltage will cause a breakdown discharge in the electric field, resulting in a sharp drop in the voltage peak value in the electric field and a sudden change in the current, at which time a spark flashover occurs in the electric field, and the operating efficiency of the device also sharply decreases. Therefore, the best working state of the electric dust collector and the plasma reactor is to maintain a state close to the maximum high-voltage peak value, while the number of spark flashovers in the electric field is close to zero. However, in reality, the pulsed high-voltage power supply will more or less have spark flashovers during operation.

[0003] At present, when a spark flashover occurs, the existing high-voltage power supply control technology defaults that the occurrence position of the spark flashover point remains unchanged, and controls the high-voltage output in a fixed manner. However, in actual application, the occurrence position of the spark flashover point is not fixed when the pulsed high-voltage power supply is working. Therefore, how to predict the occurrence position of the next spark flashover point to improve the control level of the pulsed high-voltage power supply has become a technical problem that needs to be solved by those skilled in the art. SUMMARY

[0004] Therefore, the present application discloses a method and system for predicting the occurrence position of a spark flashover point of a pulsed high-voltage power supply, so as to predict the occurrence position of the next spark flashover point and improve the control level of the pulsed high-voltage power supply.

[0005] A method for predicting the occurrence position of a spark flashover point of a pulsed high-voltage power supply, comprising:

[0006] acquiring the total number of spark flashovers stored in a spark flashover characteristic database from an initial time to a current time;

[0007] determining the number of spark flashovers in each partition in the total number of spark flashovers, wherein the partition is a waveform region obtained on a time axis according to a preset division standard for a complete pulse waveform output by the pulsed high-voltage power supply during operation;

[0008] obtain a current occurrence probability of spark flashover of each of the partitions based on the total number of spark flashovers and the number of spark flashovers corresponding to each of the partitions;

[0009] determine a variation law of instantaneous impedance of each of the partitions when the flue gas working condition parameter changes;

[0010] based on the current occurrence probability corresponding to the spark flashover of each of the partitions and the variation law of instantaneous impedance, obtain a predicted occurrence position and a predicted occurrence probability of a spark flashover point at a next moment by using a random optimization algorithm.

[0011] Optionally, the construction process of the spark flashover characteristic database comprises:

[0012] obtain a pulse waveform of one pulse cycle output by the pulse high-voltage power supply when the pulse high-voltage power supply is running, wherein the pulse waveform comprises a pulse voltage waveform and a pulse current waveform;

[0013] divide the pulse waveform on a time axis according to the preset division standard to obtain a plurality of the partitions;

[0014] determine position information of each spark flashover point in the partitions;

[0015] determine instantaneous impedance of each of the spark flashover points based on instantaneous voltage and instantaneous current of each of the spark flashover points;

[0016] construct the spark flashover characteristic database based on the position information and the instantaneous impedance of each of the spark flashover points according to the occurrence time sequence of each of the spark flashover points.

[0017] Optionally, the determination of the position information of each spark flashover point in the partitions comprises:

[0018] determine a target partition identifier corresponding to each of the spark flashover points in the pulse waveform, wherein each of the partitions in the pulse waveform has a unique partition identifier.

[0019] Optionally, the preset division standard comprises a waveform feature of the pulse waveform.

[0020] Optionally, the flue gas working condition parameter comprises a flue gas amount, a flue gas temperature, a dust concentration, a dust specific resistance and a moisture content.

[0021] Optionally, the method further comprises:

[0022] when the spark flashover point at the next moment occurs, determine an actual occurrence position and instantaneous impedance of the spark flashover point at the next moment;

[0023] The actual occurrence position of the spark flashover point of the next moment and the instantaneous impedance are stored in the spark flashover characteristic database.

[0024] A prediction system of an occurrence position of a spark flashover point of a pulse high-voltage power supply, comprising:

[0025] A total number of spark flashovers obtaining unit is configured to obtain a total number of spark flashovers stored in the spark flashover characteristic database during an initial moment to a current moment;

[0026] A partition flashover number determining unit is configured to determine a number of spark flashovers in each partition of the total number of spark flashovers, wherein the partition is a waveform region obtained by dividing a complete pulse waveform output by the pulse high-voltage power supply in a pulse period on a time axis according to a preset division standard;

[0027] A current occurrence probability determining unit is configured to obtain a current occurrence probability of spark flashover in each partition based on the total number of spark flashovers and the number of spark flashovers corresponding to each partition;

[0028] An impedance change rule determining unit is configured to determine an instantaneous impedance change rule of each partition when a flue gas working condition parameter changes;

[0029] An occurrence position prediction unit is configured to obtain a predicted occurrence position and a predicted occurrence probability of a spark flashover point of a next moment by using a random optimization algorithm based on the current occurrence probability corresponding to spark flashover in each partition and the instantaneous impedance change rule.

[0030] Optionally, the system further comprises:

[0031] A database construction unit is configured to construct the spark flashover characteristic database;

[0032] The database construction unit comprises:

[0033] A pulse waveform obtaining subunit is configured to obtain a complete pulse waveform output by the pulse high-voltage power supply in a pulse period, wherein the pulse waveform comprises a pulse voltage waveform and a pulse current waveform;

[0034] A region division subunit is configured to divide the pulse waveform on a time axis according to the preset division standard to obtain a plurality of partitions;

[0035] A position information determining subunit is configured to determine position information of each spark flashover point in the partition;

[0036] An instantaneous impedance determining subunit is configured to determine an instantaneous impedance of each spark flashover point based on an instantaneous voltage and an instantaneous current of each spark flashover point;

[0037] The database construction subunit is configured to construct, according to the occurrence time sequence of each spark flashover point, the spark flashover characteristic database based on the position information and the instantaneous impedance of each spark flashover point.

[0038] Optionally, the position information determination subunit is specifically configured to:

[0039] The determination subunit is configured to determine the target partition identifier corresponding to each spark flashover point in the pulse waveform, wherein each partition in the pulse waveform has a unique partition identifier.

[0040] Optionally, the system further comprises:

[0041] The spark flashover characteristic determination unit is configured to determine the actual occurrence position and the instantaneous impedance of the next-time spark flashover point when the next-time spark flashover point occurs.

[0042] The storage unit is configured to store the actual occurrence position and the instantaneous impedance of the next-time spark flashover point in the spark flashover characteristic database.

[0043] As can be seen from the above technical solution, the present application discloses a method and system for predicting the occurrence position of a spark flashover point of a pulse high-voltage power supply, obtains the total number of spark flashovers stored in a spark flashover characteristic database from an initial time to a current time, determines the number of spark flashovers in each partition of the total number of spark flashovers, the partition is a waveform region obtained on a time axis according to a preset division standard for a complete pulse waveform output by the pulse high-voltage power supply during operation of the pulse high-voltage power supply, obtains the current occurrence probability of spark flashover in each partition based on the total number of spark flashovers and the number of spark flashovers corresponding to each partition, determines the variation law of the instantaneous impedance of each partition when the flue gas working condition parameters change, and obtains the predicted occurrence position and the predicted occurrence probability of a next-time spark flashover point by using a random optimization algorithm based on the current occurrence probability corresponding to the occurrence of spark flashover in each partition and the variation law of the instantaneous impedance. The present application takes the current occurrence probability of spark flashover in each partition stored in the spark flashover characteristic database as a basic value, combines the variation law of the instantaneous impedance of each partition when the flue gas working condition parameters change, and uses the random optimization algorithm to iteratively solve, so as to obtain the predicted occurrence position and the predicted occurrence probability of the next-time spark flashover point, thereby improving the intelligent control level of the pulse high-voltage power supply. BRIEF DESCRIPTION OF DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description are only embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative effort.

[0045] Figure 1 Figure 1 is a flow chart of a method for predicting the location of a spark flashover point of a pulse high-voltage power supply according to an embodiment of the present application;

[0046] Figure 2(a) is a pulse voltage waveform and pulse partition identification diagram according to an embodiment of the present application;

[0047] Figure 2(b) is a pulse current waveform and pulse partition identification diagram according to an embodiment of the present application;

[0048] Figure 3 Figure 3 is a flow chart of a method for constructing a spark flashover characteristic database according to an embodiment of the present application;

[0049] Figure 4(a) is a pulse voltage waveform diagram when a spark flashover point Sn in a partition Sc flashes over according to an embodiment of the present application;

[0050] Figure 4(b) is a pulse current waveform diagram when a spark flashover point Sn in a partition Sc flashes over according to an embodiment of the present application;

[0051] Figure 5 Figure 5 is a structure diagram of a prediction system for predicting the location of a spark flashover point of a pulse high-voltage power supply according to an embodiment of the present application. DETAILED DESCRIPTION

[0052] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of the present application.

[0053] The embodiment of the application discloses a prediction method and system for the occurrence position of a spark flashover point of a pulse high-voltage power supply, obtains the total number of spark flashovers stored in a spark flashover characteristic database from an initial time to a current time, determines the number of spark flashovers in each partition of the total number of spark flashovers, the partition is a waveform region obtained on a time axis according to a preset division standard for a complete pulse waveform of one pulse period output by the pulse high-voltage power supply during operation, based on the total number of spark flashovers and the number of spark flashovers corresponding to each partition, the current occurrence probability of spark flashover of each partition is obtained, the instantaneous impedance variation law of each partition when the flue gas working condition parameter changes is determined, based on the current occurrence probability of spark flashover corresponding to each partition and the instantaneous impedance variation law, a random optimization algorithm is used to obtain the predicted occurrence position and predicted occurrence probability of the spark flashover point at the next time. The current occurrence probability of spark flashover of each partition stored in the spark flashover characteristic database is taken as a basic value, the instantaneous impedance variation law of each partition when the flue gas working condition parameter changes is combined, and a random optimization algorithm is used for continuous iterative solution to obtain the predicted occurrence position and predicted occurrence probability of the spark flashover point at the next time, so that the intelligent control level of the pulse high-voltage power supply is improved.

[0054] Reference Figure 1 The embodiment of the application discloses a prediction method for the occurrence position of a spark flashover point of a pulse high-voltage power supply, and a flowchart of the method, the method comprises:

[0055] Step S101, obtaining the total number of spark flashovers stored in a spark flashover characteristic database from an initial time to a current time.

[0056] In the embodiment, the initial time refers to the time when the spark flashover characteristic database initially stores the spark flashover characteristics.

[0057] In actual application, when a spark flashover occurs, the position information and instantaneous impedance of each spark flashover point and other spark flashover characteristics are recorded in the spark flashover characteristic database in the order of occurrence time of the spark flashover point.

[0058] When the pulse high-voltage power supply operates for a long enough time, the position information and instantaneous impedance of many spark flashover points and other spark flashover characteristic data will be stored in the spark flashover characteristic database. Before predicting the occurrence position of the spark flashover point, the total number of spark flashovers stored in the spark flashover characteristic database from the initial time to the current time is obtained.

[0059] Step S102, determining the number of spark flashovers in each partition of the total number of spark flashovers.

[0060] The partition is a waveform region obtained on a time axis according to a preset division standard for a complete pulse waveform of one pulse period output by the pulse high-voltage power supply during operation.

[0061] The preset division criterion includes, but is not limited to, a waveform feature of the pulse waveform.

[0062] The pulse high-voltage power supply is an important power supply equipment of an electric dust collector and a plasma reactor, which continuously and periodically outputs a narrow pulse high voltage, the pulse width of which is generally tens of microseconds to hundreds of microseconds, and the pulse repetition frequency of which is generally tens to hundreds; under the conventional working condition of the electric dust collector, when the pulse high-voltage power supply is running, the pulse voltage waveform is similar to a cosine waveform, the pulse current waveform is similar to a sine waveform, the pulse width is 100 microseconds, and the pulse repetition frequency is 100 pps.

[0063] It should be noted that the pulse waveform in the embodiment includes a pulse voltage waveform and a pulse current waveform. When the pulse waveform is divided, the pulse voltage waveform and the pulse current waveform have the same division interval on the time axis.

[0064] The spark flashover characteristic database records the position information of each spark flashover point, and the position information is actually the specific division position of the spark flashover point in the pulse waveform. Based on this, the number of spark flashovers in each division can be counted.

[0065] In step S103, based on the total number of spark flashovers and the number of spark flashovers corresponding to each division, the current occurrence probability of spark flashover in each division is obtained.

[0066] Suppose the total number of spark flashovers is S, and refer to the pulse voltage waveform, the pulse current waveform and the pulse division identification diagram shown in FIGS. 2(a) and 2(b). The pulse waveform (including the pulse voltage waveform and the pulse current waveform) is divided into five divisions a, b, c, d and e, and the number of spark flashovers corresponding to each division is Sa, Sb, Sc, Sd and Se respectively. Therefore, the current occurrence probability of spark flashover in each division is (Sa / S)*100%, (Sb / S)*100%, (Sc / S)*100%, (Sd / S)*100% and (Se / S)*100% respectively.

[0067] In step S104, the instantaneous impedance variation law of each division when the flue gas working condition parameter changes is determined.

[0068] The flue gas working condition parameters include flue gas volume, flue gas temperature, dust concentration, dust specific resistance, moisture content and the like.

[0069] Through calculation, the characteristics of the instantaneous impedance of each partition are: the instantaneous impedance Zsa of the a zone is a value fluctuating in a certain range; the instantaneous impedance Zsb of the b zone sharply increases with the movement of the time axis; the instantaneous impedance Zsc of the c zone is the largest, and when Isc=0, the Zsc value is infinite; the instantaneous impedance Zsd of the d zone sharply decreases with the movement of the time axis; and the instantaneous impedance Zse of the e zone is a value fluctuating in a certain range.

[0070] The change of the flue gas working condition parameters will cause the change of the spark flashover point, and the corresponding instantaneous impedance Zs value also changes. For example, assuming that an existing spark flashover point is in the c zone, when the water content in the flue gas in the flue gas working condition parameters increases, the spark flashover point will move to the b zone, and the instantaneous impedance Zs value will decrease, at this time, it can be predicted that the probability of the future occurrence of the spark flashover point in the b zone increases; when the dust specific resistance in the electric field increases or the internal electrode is seriously fouled, the spark flashover point will move to the d zone, and the instantaneous impedance Zs value will decrease, at this time, it can be predicted that the probability of the future occurrence of the spark flashover point in the d zone increases.

[0071] In step S105, based on the current occurrence probability corresponding to the spark flashover of each partition and the change rule of the instantaneous impedance, a random optimization algorithm is used to obtain the predicted occurrence position and the predicted occurrence probability of the spark flashover point at the next moment.

[0072] The present application takes the current occurrence probability corresponding to the spark flashover of each partition as a basic value, combines the determined change rule of the instantaneous impedance, and uses a random optimization algorithm to obtain the predicted occurrence position and the predicted occurrence probability of the spark flashover point at the next moment.

[0073] For example, it is predicted that the probability of the occurrence of the spark flashover point in the b zone and the d zone at the next moment increases, and at the same time, it is predicted that the probability of the occurrence of the spark flashover point in the c zone decreases, so that the predicted occurrence position and the predicted occurrence probability of the spark flashover point in the a, b, c, d and e zones at the next moment after the change of the flue gas working condition parameters are obtained.

[0074] The present application uses a random optimization algorithm to continuously and repeatedly iteratively solve the predicted occurrence position and the predicted occurrence probability of the spark flashover point with higher accuracy.

[0075] In summary, the present application discloses a kind of spark flashover point of pulse high voltage power supply to occur position prediction method, obtain spark flashover characteristic database from initial time to the total number of spark flashovers stored during current time, determine the spark flashover times of each partition in total number of spark flashovers, partition is to the pulse waveform of one pulse period complete that pulse high voltage power supply runs output on time axis according to the waveform region obtained according to preset division standard, based on total number of spark flashovers and the spark flashover times corresponding to each partition, obtain the current occurrence probability of each partition spark flashover, determine the instantaneous impedance variation law of each partition when flue gas working condition parameter changes, based on the current occurrence probability corresponding to each partition spark flashover and instantaneous impedance variation law, using random optimization algorithm, the predicted occurrence position and predicted occurrence probability of spark flashover point in next time are obtained.The present application is by the current occurrence probability of each partition spark flashover stored in spark flashover characteristic database as base value, in combination with the instantaneous impedance variation law of each partition when flue gas working condition parameter changes, using random optimization algorithm iteratively solving, to obtain the predicted occurrence position and predicted occurrence probability of spark flashover point in next time, to improve the intelligent control level of pulse high voltage power supply.

[0076] Reference Figure 3 The present application embodiment discloses a kind of spark flashover characteristic database construction method flow chart, the method includes:

[0077] Step S201, obtain the pulse waveform of one pulse period complete that pulse high voltage power supply runs output.

[0078] Wherein, pulse waveform includes: pulse voltage waveform and pulse current waveform.

[0079] Step S202, according to the preset division standard, the pulse waveform is divided on time axis, and multiple partitions are obtained.

[0080] As shown in FIG. 2(a) and FIG. 2(b), it is assumed that the pulse waveform (including pulse voltage waveform and pulse current waveform) is divided into five partitions a, b, c, d and e, a is the voltage rising and current rising area, b is the voltage rising and current falling area, c is the voltage peak area (here, the interval between 95% before and after the peak value), d is the voltage falling and current reverse rising area, and e is the voltage falling and current reverse falling area.

[0081] The preset division standard includes but is not limited to the waveform characteristics of pulse waveform.

[0082] Step S203, determine the position information of each spark flashover point in the partition.

[0083] Specifically, a target partition identifier corresponding to each spark flashover point in the pulse waveform is determined, wherein each partition in the pulse waveform has a unique corresponding partition identifier.

[0084] When a spark flashover occurs, assuming that the spark flashover point is identified as S, the pulse waveform is divided into five zones as shown in Figure 2. In actual applications, the spark flashover point is always located in the five zones a, b, c, d, and e. For ease of distinction, the spark flashover points in each zone can be marked as Sa, Sb, Sc, Sd, and Se. For example, Figures 4(a) and 4(b) are respectively a pulse voltage waveform graph and a pulse current waveform graph when a spark flashover point Sn in zone Sc occurs.

[0085] In step S204, the instantaneous impedance of each spark flashover point is determined based on the instantaneous voltage and the instantaneous current of each spark flashover point.

[0086] This step mainly digitizes the voltage and current characteristics of the spark flashover point. The voltage of the spark flashover point is denoted as Vs, and the current is denoted as Is. The instantaneous impedance of the spark flashover point is calculated as Zs = Vs / Is.

[0087] In actual applications, the instantaneous impedance of the spark flashover points in zones a, b, c, d, and e can be denoted as Zsa, Zsb, Zsc, Zsd, and Zse, respectively. For example, for a spark flashover point in zone c, the voltage when the spark flashover point flashes is denoted as Vsc, the current is denoted as Isc, and the instantaneous impedance is Zsc = Vsc / Isc. The pulse high-voltage power supply continuously generates spark flashovers during operation. Each spark flashover point is sequentially numbered, and the nth spark flashover point can be denoted as Sn, as shown in Figures 4(a) and 4(b). Therefore, the instantaneous impedance of the nth spark flashover point in zone c is Zscn = Vscn / Iscn.

[0088] Through analysis, it can be known that the instantaneous impedance Zsa in zone a is within a certain range of values, the instantaneous impedance Zsb in zone b sharply increases with the movement of the time axis, the instantaneous impedance Zsc in peak zone c is the largest, and when Isc = 0, the value of Zsc is infinite; the instantaneous impedance Zsd in zone d sharply decreases with the movement of the time axis, and the instantaneous impedance Zse in zone e is stable within a certain range of values.

[0089] In step S205, a spark flashover characteristic database is constructed based on the position information and the instantaneous impedance of each spark flashover point in the order of occurrence of the spark flashover points.

[0090] When the pulse high-voltage power supply operates for a period of time, the position information and the instantaneous impedance of many spark flashover points can be obtained.

[0091] The present application takes the current occurrence probability of spark flashover of each partition stored in the spark flashover characteristic database as a basis value, combines the instantaneous impedance variation law of each partition when the flue gas working condition parameter changes, and uses a random optimization algorithm to continuously iteratively solve to obtain the predicted occurrence position and predicted occurrence probability of the spark flashover point at the next moment, thereby improving the intelligent control level of the pulse high-voltage power supply.

[0092] To further optimize the above embodiment, after step S105, the following can also be included:

[0093] When the spark flashover point occurs at the next moment, the actual occurrence position and instantaneous impedance of the spark flashover point at the next moment are determined.

[0094] The actual occurrence position and instantaneous impedance of the spark flashover point at the next moment are stored in the spark flashover characteristic database.

[0095] The present application stores the actual occurrence position and instantaneous impedance of the latest spark flashover point in the spark flashover characteristic database after each occurrence of the spark flashover point, so as to predict the occurrence position and occurrence probability of the next spark flashover point.

[0096] Corresponding to the above method embodiment, the present application also discloses a spark flashover point occurrence position prediction system.

[0097] Referring to Figure 5 The present application embodiment discloses a structure schematic diagram of a spark flashover point occurrence position prediction system of a pulse high-voltage power supply, and the system comprises:

[0098] A total number of spark flashovers acquisition unit 301 is configured to acquire the total number of spark flashovers stored in the spark flashover characteristic database from an initial moment to a current moment.

[0099] When the pulse high-voltage power supply runs for a long enough time, the spark flashover characteristic database will store a lot of spark flashover point position information and instantaneous impedance and other spark flashover characteristic data. Before predicting the spark flashover point occurrence position, the present application acquires the total number of spark flashovers stored in the spark flashover characteristic database from an initial moment to a current moment.

[0100] A partition flashover number determination unit 302 is configured to determine the number of spark flashovers of each partition in the total number of spark flashovers.

[0101] The partition is a waveform region obtained on a time axis according to a preset division standard for a pulse waveform of one pulse period output during operation of the pulse high-voltage power supply.

[0102] The preset division standard includes but is not limited to waveform characteristics of the pulse waveform.

[0103] It should be noted that the pulse waveform in the embodiment includes a pulse voltage waveform and a pulse current waveform.

[0104] The spark flashover characteristic database records position information of each spark flashover point, and the position information is actually a specific partition position of the spark flashover point in the pulse waveform.

[0105] The current occurrence probability determination unit 303 is configured to obtain a current occurrence probability of spark flashover of each partition based on the total number of spark flashovers and the number of spark flashovers corresponding to each partition.

[0106] The impedance change rule determination unit 304 is configured to determine an instantaneous impedance change rule of each partition when the flue gas working condition parameter changes.

[0107] The flue gas working condition parameter includes flue gas volume, flue gas temperature, dust concentration, dust specific resistance, moisture content and the like.

[0108] The occurrence position prediction unit 305 is configured to obtain a predicted occurrence position and a predicted occurrence probability of a spark flashover point at the next moment by using a random optimization algorithm based on the current occurrence probability corresponding to the spark flashover of each partition and the instantaneous impedance change rule.

[0109] The present application takes the current occurrence probability corresponding to the spark flashover of each partition as a basic value, combines the determined instantaneous impedance change rule, and uses a random optimization algorithm to obtain a predicted occurrence position and a predicted occurrence probability of a spark flashover point at the next moment.

[0110] The present application uses a random optimization algorithm to continuously cycle and iterate to solve the predicted occurrence position and the predicted occurrence probability of the spark flashover point with higher accuracy.

[0111] In summary, the present application discloses a kind of spark flashover point of pulse high voltage power supply to predict the system of occurrence position, obtain spark flashover characteristic database from initial time to the total number of spark flashovers stored during current time, determine the spark flashover times of each partition in total number of spark flashovers, partition is to the pulse waveform of one pulse period complete that pulse high voltage power supply runs output in time axis according to preset division standard The waveform region obtained, based on total number of spark flashovers and the spark flashover times corresponding to each partition, the current occurrence probability of each partition spark flashover is obtained, the instantaneous impedance variation law of each partition is determined when flue gas working condition parameter changes, based on the current occurrence probability corresponding to each partition spark flashover and instantaneous impedance variation law, using random optimization algorithm, the predicted occurrence position and predicted occurrence probability of spark flashover point in next time are obtained.The present application is by the current occurrence probability of each partition spark flashover stored in spark flashover characteristic database as base value, in combination with the instantaneous impedance variation law of each partition when flue gas working condition parameter changes, using random optimization algorithm iteratively solving, to obtain the predicted occurrence position and predicted occurrence probability of spark flashover point in next time, to improve the intelligent control level of pulse high voltage power supply.

[0112] To further optimize the above embodiment, the prediction system can further include:

[0113] The database construction unit is configured to construct the spark flashover characteristic database.

[0114] Specifically, the database construction unit includes:

[0115] The pulse waveform acquisition subunit is configured to acquire a complete pulse waveform of one pulse period output when the pulse high voltage power supply runs, wherein the pulse waveform includes a pulse voltage waveform and a pulse current waveform.

[0116] The region division subunit is configured to divide the pulse waveform in time axis according to the preset division standard to obtain a plurality of partitions.

[0117] The position information determination subunit is configured to determine the position information of each spark flashover point in the partition.

[0118] The instantaneous impedance determination subunit is configured to determine the instantaneous impedance of each spark flashover point based on the instantaneous voltage and instantaneous current of each spark flashover point.

[0119] The database construction subunit is configured to construct the spark flashover characteristic database based on the position information and the instantaneous impedance of each spark flashover point according to the occurrence time sequence of each spark flashover point.

[0120] The present application takes the current occurrence probability of each partition spark flashover stored in the spark flashover characteristic database as a basis value, combines the instantaneous impedance variation law of each partition when the flue gas working condition parameter changes, and uses a random optimization algorithm to continuously iteratively solve to obtain the predicted occurrence position and predicted occurrence probability of the next moment spark flashover point, thereby improving the intelligent control level of the pulse high-voltage power supply.

[0121] To further optimize the above embodiment, the position information determination subunit can be specifically used for:

[0122] Determining the corresponding target partition identifier of each spark flashover point in the pulse waveform, wherein each partition in the pulse waveform has a unique corresponding partition identifier.

[0123] To further optimize the above embodiment, the prediction system can further comprise:

[0124] A spark flashover characteristic determination unit is configured to determine the actual occurrence position and instantaneous impedance of the next moment spark flashover point after the occurrence of the next moment spark flashover point.

[0125] A storage unit is configured to store the actual occurrence position and instantaneous impedance of the next moment spark flashover point in the spark flashover characteristic database.

[0126] The present application stores the actual occurrence position and instantaneous impedance of the latest spark flashover point in the spark flashover characteristic database after each occurrence of the spark flashover point, so as to predict the occurrence position and occurrence probability of the next spark flashover point.

[0127] It should be noted that the specific working principles of the components in the system embodiment are described in the corresponding part of the method embodiment, and will not be repeated here.

[0128] Finally, it should be noted that in this document, relationship terms such as first and second are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. Moreover, the terms "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or device. Without more limitations, the element defined by the statement "including a" does not exclude the presence of another identical element in the process, method, article or device including the element.

[0129] The various embodiments described in this specification are intended to be illustrative only and in no way limit the scope of the application. Changes and modifications can be made by those skilled in the art, which employ the principles of the application, without departing from the scope of the application. Accordingly, the application is not limited to the embodiments described herein, but instead has scope to encompass any choice whatsoever that is dependent on, or can be substituted in, the principal, new and inventive features that are described and claimed herein.

[0130] The above description of disclosed embodiments is intended to be illustrative only and not limiting of the application. Numerous modifications to these embodiments can be made by those skilled in the art without departing from the spirit or scope of the application. The scope of the application is not limited to the embodiments described herein, but rather extends to any that are dependent on, or can be substituted in, the principal, new and inventive features that are described and claimed herein.

Claims

1. A method for predicting the location of a spark flashover point in a pulsed high-voltage power supply, characterized in that, include: Obtain the total number of spark flashovers stored in the spark flashover characteristic database from the initial time to the current time; The number of spark flashovers in each partition of the total number of spark flashovers is determined, wherein the partition is: a waveform region obtained on the time axis according to a preset division standard for a complete pulse waveform of one pulse cycle output by the pulse high voltage power supply during operation; Based on the total number of spark flashovers and the number of spark flashovers corresponding to each partition, the current occurrence probability of spark flashovers in each partition is obtained; Determine the instantaneous impedance change pattern of each zone when the flue gas operating parameters change; Based on the current occurrence probability and the instantaneous impedance change law corresponding to the spark flashover in each of the partitions, a random optimization algorithm is used to obtain the predicted occurrence location and predicted occurrence probability of the spark flashover point at the next moment. The process of constructing the spark flashover characteristic database includes: Obtain the complete pulse waveform of one pulse cycle output by the pulse high voltage power supply during operation, wherein the pulse waveform includes: pulse voltage waveform and pulse current waveform; The pulse waveform is divided along the time axis according to the preset division criteria to obtain multiple partitions; Determine the location information of each spark flashover point in the partition; Based on the instantaneous voltage and instantaneous current of each spark flashover point, determine the instantaneous impedance of each spark flashover point; According to the occurrence time sequence of each spark flashover point, and based on the location information and instantaneous impedance of each spark flashover point, the spark flashover characteristic database is constructed.

2. The prediction method according to claim 1, characterized in that, Determining the location information of each spark flashover point in the partition includes: Determine the target partition identifier corresponding to each spark flash point in the pulse waveform, wherein each partition in the pulse waveform has a unique corresponding partition identifier.

3. The prediction method according to claim 1, characterized in that, The preset division criteria include: the waveform characteristics of the pulse waveform.

4. The prediction method according to claim 1, characterized in that, The flue gas operating parameters include: flue gas volume, flue gas temperature, dust concentration, dust resistivity, and moisture content.

5. The prediction method according to claim 1, characterized in that, Also includes: Once the next spark flashover point occurs, determine the actual location and instantaneous impedance of the next spark flashover point. The actual location of the spark flashover point at the next moment and the instantaneous impedance are stored in the spark flashover characteristic database.

6. A system for predicting the location of a spark flashover point in a pulsed high-voltage power supply, characterized in that, include: The total number of flashovers acquisition unit is used to acquire the total number of flashovers stored in the spark flashover characteristic database from the initial time to the current time; The partition flashover count determination unit is used to determine the number of spark flashovers in each partition of the total number of spark flashovers, wherein the partition is: a waveform region obtained on the time axis according to a preset division standard for a complete pulse waveform of one pulse cycle output by the pulse high voltage power supply during operation; The current occurrence probability determination unit is used to obtain the current occurrence probability of spark flashover in each partition based on the total number of spark flashovers and the number of spark flashovers corresponding to each partition. The impedance change law determination unit is used to determine the instantaneous impedance change law of each zone when the flue gas operating parameters change; The occurrence location prediction unit is used to obtain the predicted occurrence location and predicted occurrence probability of the spark flashover point at the next moment by using a random optimization algorithm based on the current occurrence probability and the instantaneous impedance change law corresponding to the spark flashover in each of the partitions. Also includes: Database construction unit, used to construct the spark flashover characteristic database; The database construction unit includes: The pulse waveform acquisition subunit is used to acquire a complete pulse waveform of one pulse cycle output by the pulse high voltage power supply during operation, wherein the pulse waveform includes: pulse voltage waveform and pulse current waveform; A region division subunit is used to divide the pulse waveform on the time axis according to the preset division criteria to obtain multiple partitions; The location information determination subunit is used to determine the location information of each spark flashover point in the partition; The instantaneous impedance determination subunit is used to determine the instantaneous impedance of each spark flashover point based on the instantaneous voltage and instantaneous current of each spark flashover point; The database construction subunit is used to construct the spark flashover characteristic database according to the occurrence time sequence of each spark flashover point, based on the location information and instantaneous impedance of each spark flashover point.

7. The prediction system according to claim 6, characterized in that, The location information determination subunit is specifically used for: Determine the target partition identifier corresponding to each spark flash point in the pulse waveform, wherein each partition in the pulse waveform has a unique corresponding partition identifier.

8. The prediction system according to claim 6, characterized in that, Also includes: The spark flashover characteristic determination unit is used to determine the actual location and instantaneous impedance of the spark flashover point at the next moment after the spark flashover point occurs. A storage unit is used to store the actual occurrence location and instantaneous impedance of the spark flashover point at the next moment in the spark flashover characteristic database.

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