A high-voltage solid-state soft-start device fault intelligent detection system

Abstract

The application relates to the technical field of fault detection, in particular to a high-voltage solid-state soft start device fault intelligent detection system, which comprises a data acquisition module, a first early warning module used for determining whether the high-voltage solid-state soft start device has a fault according to a fault coefficient, a fault analysis module used for performing primary determination based on three-phase current balance degree, and performing secondary determination according to maximum data correlation coefficient or thyristor abnormality comparison degree to determine whether the thyristor has an abnormality under the condition of primary abnormality according to the correlation degree of thyristor fault data, an abnormality identification module used for determining an abnormal thyristor group according to current difference degree and temperature abnormal value, and a second early warning module used for determining the abnormality degree of the thyristor according to sudden damage degree or thyristor aging degree, and determining whether to perform fault early warning based on the maximum thyristor abnormality degree. The application can improve the timeliness of fault early warning.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of fault detection, and in particular to a high-voltage solid-state soft starter fault intelligent detection system. BACKGROUND

[0002] Since the high-voltage solid-state soft starter works in a complex environment of high voltage, large current and strong electromagnetic interference for a long time, its core components are prone to failure due to aging, excessive temperature rise, overvoltage and overcurrent impact, etc. The traditional fault detection method relies on manual inspection or simple sensor alarm, which has the problems of poor real-time performance, insufficient accuracy and low intelligence, etc. Therefore, how to perform fault detection to improve the timeliness of fault warning is a problem to be solved by those skilled in the art.

[0003] Chinese patent publication No. CN117741519A discloses a motor soft starter detection method, processor and motor soft starter, comprising: obtaining the connection detection result of the voltage detection cable between the line between the power input terminal and the silicon controlled assembly and the voltage detection circuit, the connection detection result of the trigger cable between the silicon controlled assembly and the trigger circuit, and the connection detection result of the current sampling cable between the current sensor and the current sampling circuit. Without relying on manual investigation, the position of the cable connection anomaly can be quickly located. However, the above-mentioned scheme has the following problems: it cannot capture subtle abnormalities and trend changes during device operation, resulting in poor timeliness of fault warning. SUMMARY

[0004] Therefore, the present application provides a high-voltage solid-state soft starter fault intelligent detection system to overcome the problem that the prior art cannot capture subtle abnormalities and trend changes during device operation, resulting in poor timeliness of fault warning.

[0005] To achieve the above-mentioned purpose, the present application provides a high-voltage solid-state soft starter fault intelligent detection system, comprising:

[0006] A data acquisition module is used to acquire marker data and monitoring data of the high-voltage solid-state soft starter;

[0007] A first warning module is connected to the data acquisition module and is used to determine a fault coefficient according to an abnormal reference value and a fluctuation ratio value of the monitoring data, and to determine whether the high-voltage solid-state soft starter has a fault according to the fault coefficient;

[0008] a fault analysis module connected with the data acquisition module and the first early warning module, configured to determine whether the thyristor exists abnormality according to the maximum data correlation coefficient or the thyristor abnormality comparison degree based on the thyristor fault data correlation degree under a preset fault condition and a primary abnormal condition;

[0009] an abnormality identification module connected with the fault analysis module, configured to determine the abnormal thyristor group according to the current difference degree and the temperature abnormal value when the thyristor exists abnormality;

[0010] a second early warning module connected with the abnormality identification module, configured to determine that the reason that the abnormal thyristor group exists abnormality includes sudden damage and aging according to the temperature difference degree, determine the thyristor abnormality degree according to the sudden damage degree or the thyristor aging degree, and determine whether to perform fault early warning based on the maximum thyristor abnormality degree.

[0011] Further, the first early warning module determines the fault coefficient according to the abnormal reference value and the fluctuation comparison value of the monitoring data.

[0012] The fault coefficient has a positive correlation with the abnormal reference value and the fluctuation comparison value.

[0013] Further, the first early warning module determines that the high-voltage solid-state soft starter exists fault when the fault coefficient is greater than or equal to a first preset fault coefficient.

[0014] Further, the fault analysis module determines whether the thyristor exists abnormality according to the maximum data correlation coefficient or the thyristor abnormality comparison degree based on the thyristor fault data correlation degree under a preset fault condition, including:

[0015] If the three-phase current balance degree is less than a preset three-phase current balance degree, it is determined that the thyristor exists abnormality.

[0016] If the three-phase current balance degree is greater than or equal to the preset three-phase current balance degree, it is determined that the thyristor does not exist abnormality.

[0017] The preset fault condition is that the fault coefficient is greater than or equal to a first preset fault coefficient and less than a second preset fault coefficient.

[0018] Further, the fault analysis module determines whether the thyristor exists abnormality according to the maximum data correlation coefficient or the thyristor abnormality comparison degree based on the thyristor fault data correlation degree under a primary abnormal condition, including:

[0019] If the thyristor fault data correlation degree is less than a preset thyristor fault data correlation degree, it is determined whether the thyristor exists abnormality according to the maximum data correlation coefficient.

[0020] If the correlation degree of the thyristor fault data is greater than or equal to the preset correlation degree of the thyristor fault data, whether the thyristor exists an abnormality is determined according to the abnormality comparison degree of the thyristor.

[0021] The primary abnormal condition is that the thyristor exists an abnormality when the primary determination is made.

[0022] Further, the confirmation manner of the abnormality comparison degree of the thyristor includes:

[0023] If the current rate change degree is greater than or equal to the preset current rate change degree, the abnormality comparison degree of the thyristor is determined according to the rate change comparison degree.

[0024] If the current rate change degree is less than the preset current rate change degree, the abnormality comparison degree of the thyristor is determined according to the current attenuation degree.

[0025] Further, the abnormality identification module determines the abnormal thyristor group according to the current difference degree and the temperature abnormal value.

[0026] The abnormal thyristor group is a thyristor group with a current difference degree greater than a preset current difference degree or a temperature abnormal value greater than a preset temperature abnormal value.

[0027] The thyristor group is each thyristor in a single phase of a three-phase bridge circuit of a high-voltage solid-state soft starter.

[0028] Further, the second warning module determines that the abnormal thyristor group exists an abnormality due to sudden damage when the temperature difference degree is greater than or equal to the preset temperature difference degree, and determines the abnormality degree of the thyristor according to the sudden damage degree.

[0029] The sudden damage degree is determined according to the pressure drop change degree.

[0030] Further, the second warning module determines that the abnormal thyristor group exists an abnormality due to aging when the temperature difference degree is less than the preset temperature difference degree, and determines the abnormality degree of the thyristor according to the thyristor aging degree.

[0031] The thyristor aging degree is determined based on the current-temperature correlation degree.

[0032] Further, the second warning module determines whether to perform fault warning according to the abnormality degree change degree when the maximum abnormality degree of the thyristor is greater than or equal to the preset maximum abnormality degree of the thyristor.

[0033] When it is determined whether to perform fault warning according to the abnormality degree change degree, if the abnormality degree change degree is greater than or equal to the preset abnormality degree change degree, fault warning is performed; if the abnormality degree change degree is less than the preset abnormality degree change degree, fault warning is not needed.

[0034] Compared with the prior art, the beneficial effects of the present application are that, in the technical scheme of the present application, by monitoring the abnormal reference value and fluctuation comparison value of the data, the degree of deviation of each monitoring parameter in the high-voltage solid-state soft starter from the normal operating state and the stability of the parameter change can be effectively reflected, and then the fault coefficient is determined according to the abnormal reference value and fluctuation comparison value of the monitoring data, the abnormality severity of the high-voltage solid-state soft starter as a whole is effectively reflected through the fault coefficient, and then whether the high-voltage solid-state soft starter has a fault is determined according to the fault coefficient, so that accurate evaluation of the operating state of the device can be realized, misjudgment or missed judgment caused by single parameter abnormality can be avoided, and at the same time, the gradient management of the fault is realized through the hierarchical threshold, which not only ensures timely identification of early hidden dangers, but also triggers emergency warning when the fault risk is high, thereby finally improving the reliability of device operation and the pertinence of maintenance.

[0035] Further, in the present application, the balance state of the current of each phase in the three-phase bridge circuit is effectively reflected through the three-phase current balance degree, and then a primary determination is made according to the three-phase current balance degree, so that whether the thyristor has an abnormality can be preliminarily and quickly identified, and then under the condition of primary abnormality, a secondary determination is adaptively made according to the data association coefficient or the thyristor abnormality comparison degree through the thyristor fault data association degree, so that the determination basis can be flexibly selected according to the association strength of the fault data and the non-fault data, and the accuracy of the thyristor abnormality determination is improved.

[0036] Further, in the present application, the temperature distribution uniformity of each thyristor in the same thyristor group is effectively reflected through the temperature difference degree, and then the thyristor abnormality degree is adaptively determined according to the sudden damage degree or the thyristor aging degree according to the temperature difference degree, which is conducive to accurately distinguishing the abnormal reasons of the abnormal thyristor group and evaluating the abnormal severity through the corresponding quantitative indicators sudden damage degree or thyristor aging degree.

[0037] Further, in the present application, the most serious abnormality degree in each abnormal thyristor group is effectively reflected through the maximum thyristor abnormality degree, and then it is determined whether to perform fault warning based on the maximum thyristor abnormality degree, so that the most dangerous abnormal state can be focused on preferentially, which is conducive to avoiding the lag of early warning caused by the overall average abnormal level covering up the local serious fault, and improving the pertinence and timeliness of the fault warning. BRIEF DESCRIPTION OF DRAWINGS

[0038] Fig. 1 It is a module connection diagram of the high-voltage solid-state soft starter fault intelligent detection system of the present application;

[0039] Fig. 2 It is a flowchart for determining whether the high-voltage solid-state soft starter has a fault according to the fault coefficient of the present application;

[0040] Fig. 3 It is a flowchart for making a primary determination based on the three-phase current balance degree of the present application;

[0041] Fig. 4 Flow chart for determining whether to give a fault warning based on maximum thyristor abnormality according to the present application. DETAILED DESCRIPTION

[0042] In order to make the objects and advantages of the present application clearer, the following further describes the present application with reference to examples; it should be understood that the specific examples described herein are merely used to explain the present application and do not limit the present application.

[0043] The preferred embodiments of the present application are described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely used to explain the technical principles of the present application and are not intended to limit the protection scope of the present application.

[0044] It should be noted that, in the description of the present application, the terms "upper", "lower", "left", "right", "inner", "outer" and the like indicate the direction or positional relationship terms based on the direction or positional relationship shown in the drawings, which are merely for the convenience of description and do not indicate or imply that the device or element must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation on the present application.

[0045] Please refer to Figs. 1 to 4 As shown in the drawings, the present application provides a high-voltage solid-state soft starter fault intelligent detection system, comprising:

[0046] A data acquisition module is used to acquire marker data and monitoring data of the high-voltage solid-state soft starter;

[0047] A first warning module is connected to the data acquisition module and is used to determine a fault coefficient according to an abnormal reference value and a fluctuation ratio value of the monitoring data, and to determine whether the high-voltage solid-state soft starter has a fault according to the fault coefficient;

[0048] A fault analysis module is connected to the data acquisition module and the first warning module, and is used to make a first determination based on three-phase current balance under a preset fault condition, and to make a second determination according to a maximum data correlation coefficient or a thyristor abnormality comparison degree to determine whether there is an abnormality in the thyristor under a first abnormality condition;

[0049] An abnormality recognition module is connected to the fault analysis module and is used to determine an abnormal thyristor group according to a current difference degree and a temperature abnormality value when the thyristor has an abnormality;

[0050] A second early warning module is connected to the anomaly identification module, and is used to determine the cause of the abnormal thyristor group according to the temperature difference degree, including sudden damage and aging, to determine the thyristor abnormality degree according to the sudden damage degree or the thyristor aging degree, and to determine whether to perform fault early warning based on the maximum thyristor abnormality degree.

[0051] The application scenario of the present application is fault detection of a high-voltage solid-state soft starter.

[0052] In the present application, a plurality of historical records are correspondingly provided, each of which records the fluctuation reference value, the abnormal reference value, the fluctuation comparison value and the three-phase current balance degree in the historical process of at least one fault detection of the high-voltage solid-state soft starter, and each of the historical records corresponds to a qualified mark, which records whether the process of the fault detection of the high-voltage solid-state soft starter meets the user's demand, and the qualified mark can be recorded manually.

[0053] In the present application, a continuous monitoring cycle is provided, and the length of the monitoring cycle can be set according to the user's demand.

[0054] The monitoring data includes monitoring parameters corresponding to each time point in the current monitoring cycle, and a setting method of the time point is provided, taking the starting time of the current monitoring cycle as the starting point, setting an interval point every 10s, and recording the starting point and each interval point as a time point.

[0055] The application comprises several marked data, and each marked data is the monitoring data of a single monitoring period of the high-voltage solid-state soft starter in the historical operation process, each marked data corresponds to a data label, the data label is "0" or "1", when the data label is "0", it indicates that the thyristor of the high-voltage solid-state soft starter is abnormal, and when the data label is "1", it indicates that the thyristor of the high-voltage solid-state soft starter is normal, the marked data with the data label "0" is recorded as the thyristor fault data, and the marked data with the data label "1" is recorded as the non-thyristor fault data.

[0056] Specifically, the first early warning module determines the fault coefficient according to the abnormal reference value and the fluctuation ratio value of the monitoring data.

[0057] The fault coefficient, the abnormal reference value and the fluctuation ratio value are all positively correlated.

[0058] The abnormal reference value is the maximum value in the sub-abnormal degree corresponding to each monitoring parameter, the historical record that does not need to be faulted and can meet the user's demand is recorded as a reference historical record, for any monitoring parameter, the monitoring parameter is recorded as a target monitoring parameter, the sub-abnormal degree corresponding to the target monitoring parameter = (the abnormal value of the target monitoring parameter corresponding to the current monitoring period - the average value of the abnormal value of the target monitoring parameter in the monitoring period corresponding to each reference historical record) / the average value of the abnormal value of the target monitoring parameter corresponding to each reference historical record, and the abnormal value of the target monitoring parameter is the maximum value in the target monitoring parameter corresponding to each time point in a single monitoring period.

[0059] The fluctuation ratio value is the maximum value in the sub-fluctuation ratio value corresponding to each monitoring parameter, and the sub-fluctuation ratio value corresponding to the target monitoring parameter = (the fluctuation reference value of the target monitoring parameter corresponding to the current monitoring period - the average value of the fluctuation reference value of the target monitoring parameter in the monitoring period corresponding to each reference historical record) / the average value of the fluctuation reference value of the target monitoring parameter in the monitoring period corresponding to each reference historical record.

[0060] The fluctuation reference value of the target monitoring parameter in a single monitoring period is the standard deviation of the value of the target monitoring parameter corresponding to each time point in the monitoring period.

[0061] The fault coefficient = (the abnormal reference value / the average value of the abnormal reference value corresponding to each reference historical record) x the first weight coefficient + (the fluctuation ratio value / the average value of the fluctuation ratio value corresponding to each reference historical record) x the second weight coefficient, the first weight coefficient is 0.6, and the second weight coefficient is 0.4.

[0062] Specifically, the first early warning module determines that the high-voltage solid-state soft starter has a fault when the fault coefficient is greater than or equal to a first preset fault coefficient.

[0063] If the fault coefficient is greater than or equal to the first preset fault coefficient and less than the second preset fault coefficient, it is determined whether the thyristor is abnormal;

[0064] If the fault coefficient is greater than or equal to the second preset fault coefficient, a fault warning is performed.

[0065] If the fault coefficient is less than the first preset fault coefficient, it is determined that the high-voltage solid-state soft starter does not have a fault.

[0066] The first preset fault coefficient is less than the second preset fault coefficient. The values of the first preset fault coefficient and the second preset fault coefficient can be determined by the user according to the actual application scenario. The greater the user's demand for warning accuracy, the smaller the values of the first preset fault coefficient and the second preset fault coefficient. A value of the first preset fault coefficient and the second preset fault coefficient is provided, the first preset fault coefficient is 0.2, and the second preset fault coefficient is 0.4.

[0067] It can be understood that when the fault coefficient is greater than or equal to the first preset fault coefficient and less than the second preset fault coefficient, it indicates that the operating parameters of the high-voltage solid-state soft starter have deviated from the normal range, but the overall abnormality degree is at a medium level and has not reached the emergency risk level. However, since the thyristor is the core power element of the high-voltage solid-state soft starter, its performance degradation or abnormality is often the main cause of early failure, and the abnormality at this stage may be caused by slight aging or poor contact of the thyristor. Therefore, it is determined whether the thyristor is abnormal to accurately locate potential hazards.

[0068] When the fault coefficient is greater than or equal to the second preset fault coefficient, it indicates that the abnormality degree of the operating parameters of the device is relatively significant, and the fault risk is greatly increased. Therefore, a fault warning needs to be performed immediately to prompt the user to urgently investigate and handle to avoid the expansion of the fault.

[0069] Specifically, the fault analysis module performs a determination based on the three-phase current balance degree under a preset fault condition, including:

[0070] If the three-phase current balance degree is less than a preset three-phase current balance degree, it is determined that the thyristor is abnormal.

[0071] If the three-phase current balance degree is greater than or equal to the preset three-phase current balance degree, it is determined that the thyristor is not abnormal.

[0072] The preset fault condition is that the fault coefficient is greater than or equal to the first preset fault coefficient and less than the second preset fault coefficient.

[0073] The three-phase current balance degree = 1 - (maximum phase current - minimum phase current) / three-phase average current.

[0074] In the high-voltage solid-state soft starter, a three-phase bridge circuit is used in the high-voltage solid-state soft starter, the three-phase current refers to the current passing through three phases in the three-phase bridge circuit, the maximum phase current and the minimum phase current correspond to the maximum value and the minimum value of the current passing through the three phases respectively, the current passing through each phase is monitored by a current sensor, and the three-phase average current is the average value of the current passing through the three phases in the main circuit of the high-voltage solid-state soft starter.

[0075] The preset three-phase current balance degree value can be determined by the user according to the actual application scene. The greater the user's demand for improving the fault detection accuracy, the smaller the preset three-phase current balance degree value. A method for determining the value of the preset three-phase current balance degree is provided. The average value of the three-phase current balance degree corresponding to the historical record that meets the user's demand is recorded as the preset three-phase current balance degree.

[0076] Specifically, the fault analysis module determines whether the thyristor exists abnormity according to the maximum data correlation coefficient or the thyristor abnormality comparison degree according to the thyristor fault data correlation degree under a primary abnormal condition, comprising:

[0077] If the thyristor fault data correlation degree is less than the preset thyristor fault data correlation degree, it is determined whether the thyristor exists abnormity according to the maximum data correlation coefficient;

[0078] If the thyristor fault data correlation degree is greater than or equal to the preset thyristor fault data correlation degree, it is determined whether the thyristor exists abnormity according to the thyristor abnormality comparison degree;

[0079] The primary abnormal condition is that the thyristor exists abnormity in the primary determination.

[0080] The thyristor fault data correlation degree is the average value of the correlation reference values corresponding to each thyristor fault data, and the correlation reference value corresponding to a single thyristor fault data is the maximum value in the correlation coefficients corresponding to each non-thyristor fault data.

[0081] The correlation coefficient corresponding to a single thyristor fault data and a single non-thyristor fault data is the average value of the matching coefficients corresponding to each monitoring parameter.

[0082] The calculation formula of the matching coefficient r corresponding to a single monitoring parameter is:

[0083]

[0084] Wherein, m is the number of time points in a single monitoring period; are the values of the monitoring parameter corresponding to the kth time point in a single thyristor fault data and a single non-thyristor fault data, respectively, an average value of the values of the monitoring parameter corresponding to each time point in the single thyristor fault data, an average value of the values of the monitoring parameter corresponding to each time point in the single non-thyristor fault data, k = 1, 2, 3, …, m;

[0085] a preset value of the thyristor fault data correlation degree, which can be determined by the user according to the actual application scenario. It can be understood that the smaller the preset value of the thyristor fault data correlation degree, the greater the user's requirement for the accuracy of identifying potential faults caused by non-strongly associated factors. A method for determining the preset value of the thyristor fault data correlation degree is provided. The user determines whether there is an abnormal history record of the thyristor according to the abnormal comparison degree of the thyristor. The average value of the thyristor fault data correlation degree corresponding to the history record that meets the user's requirement is recorded as the preset value of the thyristor fault data correlation degree.

[0086] determining whether there is an abnormal thyristor according to the maximum data correlation coefficient, comprising:

[0087] if the maximum data correlation coefficient is greater than or equal to the preset maximum data correlation coefficient, it is determined that there is an abnormal thyristor;

[0088] if the maximum data correlation coefficient is less than the preset maximum data correlation coefficient, it is determined that there is no abnormal thyristor.

[0089] determining whether there is an abnormal thyristor according to the abnormal comparison degree of the thyristor, comprising:

[0090] if the abnormal comparison degree of the thyristor is greater than or equal to the preset abnormal comparison degree of the thyristor, it is determined that there is an abnormal thyristor;

[0091] if the abnormal comparison degree of the thyristor is less than the preset abnormal comparison degree of the thyristor, it is determined that there is no abnormal thyristor.

[0092] the maximum data correlation coefficient is the maximum value in the correlation coefficients corresponding to the monitoring data and each thyristor fault data. It should be noted that the calculation method of the correlation coefficient corresponding to the monitoring data and the single thyristor fault data is the same as that of the single thyristor fault data and the single non-thyristor fault data, which is not described in detail;

[0093] The preset maximum data correlation coefficient and the preset thyristor abnormality comparison degree can be determined by the user according to the actual application scene. The greater the user's demand for improving the accuracy of fault early warning and timeliness, the smaller the value of the preset maximum data correlation coefficient and the preset thyristor abnormality comparison degree. A method for determining the value of the preset maximum data correlation coefficient and the preset thyristor abnormality comparison degree is provided. The average value of the maximum data correlation coefficient corresponding to the historical record in which the user determines that the thyristor is abnormal and can meet the user's demand according to the maximum data correlation coefficient is recorded as the preset maximum data correlation coefficient. The average value of the thyristor abnormality comparison degree corresponding to the historical record in which the user determines that the thyristor is abnormal and can meet the user's demand according to the thyristor abnormality comparison degree is recorded as the preset thyristor abnormality comparison degree.

[0094] It can be understood that the thyristor fault data correlation degree effectively reflects the overall correlation strength between the thyristor fault data and the non-thyristor fault data. When the thyristor fault data correlation degree is less than the preset thyristor fault data correlation degree, it indicates that the overall correlation between the thyristor fault data and the non-thyristor fault data is weak, and the monitoring parameter characteristics of the two types of data are significantly different. At this time, by comparing the direct correlation of the current monitoring data and the thyristor fault data, the existence of the thyristor abnormality can be more clearly identified. Therefore, whether the thyristor is abnormal is determined according to the maximum data correlation coefficient.

[0095] When the thyristor fault data correlation degree is greater than or equal to the preset thyristor fault data correlation degree, it indicates that the overall correlation between the thyristor fault data and the non-thyristor fault data is strong. When the data feature correlation degree is large, the direct correlation degree comparison effect is limited. Focusing on the abnormality degree of the thyristor core operating parameter can more accurately locate whether the thyristor is abnormal.

[0096] Specifically, the confirmation method of the thyristor abnormality comparison degree comprises:

[0097] If the current rate change degree is greater than or equal to the preset current rate change degree, the thyristor abnormality comparison degree is determined according to the rate change comparison degree;

[0098] If the current rate change degree is less than the preset current rate change degree, the thyristor abnormality comparison degree is determined according to the current decay degree.

[0099] The current rate change degree is the maximum value in the rate reference values corresponding to each time point. For a single time point, the time point is recorded as a target time point, the rate reference value corresponding to the target time point is equal to the absolute value of the difference between the output current corresponding to the target time point and the output current corresponding to the time point adjacent to the target time point and earlier than the target time point, and the time length between the two adjacent time points, and the unit of the rate reference value is A / s.

[0100] The user can determine the preset current rate change degree value according to the actual application scene. The smaller the preset current rate change degree value is, the greater the user's demand for determining the thyristor abnormal comparison degree according to the rate change comparison degree is. A preset current rate change degree value determination method is provided. The average value of the current rate change degree corresponding to the historical record that can meet the user's demand is recorded as the preset current rate change degree.

[0101] When the rate change comparison degree is used to determine the thyristor abnormal comparison degree, the thyristor abnormal comparison degree = rate change comparison degree / (average value of the rate change comparison degree corresponding to each reference historical record + 1), and the rate change comparison degree = current rate change degree - preset current rate change degree.

[0102] When the current decay degree is used to determine the thyristor abnormal comparison degree, the thyristor abnormal comparison degree = current decay degree / (average value of the current decay degree corresponding to each reference historical record + 1).

[0103] The current decay degree = average value of the output current corresponding to each time point in the current monitoring period - average value of the output current corresponding to each time point in the monitoring period of each reference historical record when the current rate change degree is less than the preset current rate change degree.

[0104] It can be understood that the current rate change degree effectively reflects the instantaneous change degree of the output current of the high-voltage solid-state soft start device in the monitoring period. When the current rate change degree is greater than or equal to the preset current rate change degree, it means that the change rate exceeds the normal threshold, and therefore the abnormality caused by the sudden change of the current needs to be focused on. Therefore, the rate change comparison degree is used to determine the thyristor abnormal comparison degree.

[0105] When the current rate change degree is less than the preset current rate change degree, it means that the output current changes smoothly in the monitoring period, and there is no obvious abnormality. At this time, more attention should be paid to the overall decay trend of the current. The current decay degree can reflect the decay difference between the current average level and the historical normal smooth scene. Therefore, the current decay degree is used to determine the thyristor abnormal comparison degree.

[0106] Specifically, the abnormal identification module determines the abnormal thyristor group according to the current difference degree and the temperature abnormal value.

[0107] The abnormal thyristor group is a thyristor group with a current difference degree greater than a preset current difference degree or a temperature abnormal value greater than a preset temperature abnormal value.

[0108] The thyristor group is each thyristor in a single phase in a three-phase bridge circuit of the high-voltage solid-state soft start device.

[0109] Wherein, in the high-voltage solid-state soft starter, a three-phase bridge circuit is adopted, and a plurality of thyristors are contained in each phase, and each thyristor in a single phase is recorded as a thyristor group;

[0110] The current difference degree corresponding to a single thyristor group is equal to | the current passing through the phase corresponding to the thyristor group - the three-phase average current | / the three-phase average current;

[0111] The temperature abnormal value corresponding to a single thyristor group is the average value of the maximum temperature values of the thyristor group at each time point in the current monitoring period, and the maximum temperature value of the thyristor group at a single time point is the maximum value of the temperatures corresponding to each thyristor in the thyristor group;

[0112] The values of the preset current difference degree and the preset temperature abnormal value can be determined by the user according to the actual application scene, the greater the value of the preset temperature difference degree, the greater the user's demand for determining the thyristor abnormality degree according to the thyristor aging degree, and a value determination method of the preset temperature difference degree is provided, and the average value of the temperature difference degree corresponding to the historical record meeting the user's demand is recorded as the preset temperature difference degree.

[0113] Specifically, the second warning module determines that the abnormal thyristor group has an abnormal reason of sudden damage when the temperature difference degree is greater than or equal to the preset temperature difference degree, and determines the thyristor abnormality degree according to the sudden damage degree;

[0114] The sudden damage degree is determined according to the pressure drop change degree.

[0115] Wherein, the temperature difference degree corresponding to a single thyristor group is the standard deviation of the temperature reference values corresponding to each thyristor in the thyristor group, and the temperature reference value corresponding to a single thyristor is the average value of the temperatures corresponding to each time point in the current monitoring period of the thyristor;

[0116] The value of the preset temperature difference degree can be determined by the user according to the actual application scene, the greater the value of the preset temperature difference degree, the greater the user's demand for determining the thyristor abnormality degree according to the thyristor aging degree, and a value determination method of the preset temperature difference degree is provided, and the average value of the temperature difference degree corresponding to the historical record meeting the user's demand is recorded as the preset temperature difference degree;

[0117] The time point when the anode current > anode current threshold value is recorded as the conduction time point; the anode current threshold value is 5 mA, and the anode current is the current of the thyristor anode, which is detected by a current sensor;

[0118] The average value of the voltage difference corresponding to each conduction time point in the current monitoring period is recorded as a voltage drop reference value; the voltage sensor input end is connected in parallel across the anode and cathode of the thyristor to directly collect the voltage difference across the two ends;

[0119] The voltage drop change degree corresponding to a single abnormal thyristor group is the maximum value among the sub-voltage drop change degrees corresponding to each thyristor in the abnormal thyristor group, and the sub-voltage drop change degree corresponding to a single thyristor is | voltage drop reference value - average value of the voltage drop reference values corresponding to each thyristor in each reference history record | / average value of the voltage drop reference values corresponding to each thyristor in each reference history record;

[0120] The sudden damage degree corresponding to a single thyristor group is the voltage drop change degree / average value of the voltage drop change degrees corresponding to each thyristor group in each reference history record;

[0121] The thyristor abnormality degree corresponding to a single thyristor group is sudden damage degree x damage influence coefficient, and the damage influence coefficient is 1.2;

[0122] It can be understood that the temperature difference degree effectively reflects the temperature distribution uniformity of each thyristor in the same thyristor group, and when the temperature difference degree is greater than or equal to the preset temperature difference degree, it indicates that the temperature distribution difference of each thyristor in the thyristor group is significant. Such uneven temperature distribution is usually caused by abnormal heating of individual thyristors, indicating that individual thyristors have sudden damages such as local breakdown, lead virtual connection, etc., so the reason for the existence of abnormal thyristor group is sudden damage, and the thyristor abnormality degree is determined according to the sudden damage degree;

[0123] When the temperature difference degree is less than the preset temperature difference degree, it indicates that the temperature distribution of each thyristor in the thyristor group is relatively uniform, and at this time, the abnormality is more likely to be caused by the overall performance degradation due to long-term operation. The reason for the existence of abnormal thyristor group is aging, and the thyristor abnormality degree is determined according to the thyristor aging degree.

[0124] Specifically, the second warning module determines that the reason for the existence of abnormal thyristor group is aging when the temperature difference degree is less than the preset temperature difference degree, and determines the thyristor abnormality degree according to the thyristor aging degree;

[0125] The thyristor aging degree is determined based on the current-temperature correlation degree.

[0126] The current-temperature correlation degree corresponding to a single abnormal thyristor group is the minimum value among the sub-current-temperature correlation degrees corresponding to each thyristor in the abnormal thyristor group;

[0127] The calculation formula of the sub-current-temperature correlation degree w is:

[0128]

[0129] wherein m is the number of time points in a single monitoring period; and are the anode current and temperature of a single thyristor at the jth time point in the current monitoring period, respectively, and are the average value of the anode current and the average value of the temperature of a single thyristor at each time point in the current monitoring period, respectively, j = 1, 2, 3, …, m;

[0130] the aging degree of a single thyristor group = the current-temperature correlation degree / the average value of the current-temperature correlation degrees of each thyristor group in each reference historical record;

[0131] the abnormality degree of a single thyristor group = the aging degree of the thyristor × the aging influence coefficient, and the aging influence coefficient is 1.0.

[0132] Specifically, the second early warning module determines whether to perform fault early warning according to the abnormality degree change when the maximum thyristor abnormality degree is greater than or equal to a preset maximum thyristor abnormality degree;

[0133] When determining whether to perform fault early warning according to the abnormality degree change, if the abnormality degree change is greater than or equal to a preset abnormality degree change, fault early warning is performed; if the abnormality degree change is less than the preset abnormality degree change, fault early warning is not needed.

[0134] The second early warning module does not need to perform fault early warning when the maximum thyristor abnormality degree is less than a preset maximum thyristor abnormality degree;

[0135] The maximum thyristor abnormality degree is the maximum value in the thyristor abnormality degrees corresponding to each abnormal thyristor group, and the value of the preset maximum thyristor abnormality degree can be determined by a user according to an actual application scenario. The greater the accuracy requirement of the user for improving the timeliness of fault early warning, the smaller the value of the preset maximum thyristor abnormality degree. A value of the preset maximum thyristor abnormality degree is provided, historical records of the user determining whether to perform fault early warning according to the abnormality degree change are detected, and the average value of the maximum thyristor abnormality degrees corresponding to the historical records that can meet the requirement of the user is recorded as the preset maximum thyristor abnormality degree;

[0136] The abnormality degree change = the maximum thyristor abnormality degree corresponding to the current monitoring period - the maximum thyristor abnormality degree corresponding to the monitoring period adjacent to and earlier than the current monitoring period;

[0137] The preset abnormality degree change value can be determined by the user according to an actual application scene. The smaller the preset abnormality degree change value is, the greater the accuracy requirement of the user for improving fault early warning timeliness is. A preset abnormality degree change value method is provided. A history record of whether the user determines to perform fault early warning according to the abnormality degree change is detected. An average value of the abnormality degree change corresponding to the history record that can meet the user requirement and perform fault early warning is recorded as the preset abnormality degree change.

[0138] So far, the technical solutions of the present application have been described in combination with the preferred embodiments shown in the drawings, but those skilled in the art can easily understand that the protection scope of the present application is obviously not limited to these specific embodiments. Those skilled in the art can make equivalent changes or replacements to the related technical features without departing from the principles of the present application, and the technical solutions after the changes or replacements will all fall within the protection scope of the present application.

Claims

1. A fault intelligent detection system for a high-voltage solid-state soft starter, characterized in that, include: The data acquisition module is used to collect marker data and monitoring data from the high-voltage solid-state soft starter. The first early warning module is connected to the data acquisition module and is used to determine the fault coefficient based on the abnormal reference value and fluctuation comparison value of the monitoring data, and to determine whether the high-voltage solid-state soft starter has a fault based on the fault coefficient. The fault analysis module is connected to the data acquisition module and the first early warning module respectively. It is used to make a first judgment based on the three-phase current balance under preset fault conditions, and under a first abnormal condition, to make a second judgment based on the correlation of thyristor fault data, or the maximum data correlation coefficient or thyristor abnormality comparison degree to determine whether there is an abnormality in the thyristor. The preset fault condition is that the fault coefficient is greater than or equal to the first preset fault coefficient and less than the second preset fault coefficient. An anomaly identification module, which is connected to the fault analysis module, is used to identify the abnormal thyristor group based on the current difference and temperature anomaly value when there is an anomaly in the thyristor. The second early warning module is connected to the anomaly identification module. It is used to determine the cause of the abnormality of the abnormal thyristor group based on the temperature difference, including sudden damage and aging. It also determines the degree of thyristor abnormality based on the degree of sudden damage or thyristor aging, and determines whether to issue a fault warning based on the maximum degree of thyristor abnormality.

2. The intelligent fault detection system for high-voltage solid-state soft starter according to claim 1, characterized in that, The first early warning module determines the fault coefficient based on the abnormal reference value and fluctuation comparison value of the monitoring data; The fault coefficient is positively correlated with both the abnormal reference value and the fluctuation comparison value.

3. The intelligent fault detection system for high-voltage solid-state soft starter according to claim 2, characterized in that, The first early warning module determines that the high-voltage solid-state soft starter has a fault when the fault coefficient is greater than or equal to the first preset fault coefficient.

4. The intelligent fault detection system for high-voltage solid-state soft starter according to claim 3, characterized in that, The fault analysis module performs a judgment based on the three-phase current balance under preset fault conditions, including: If the three-phase current balance is less than the preset three-phase current balance, the thyristor is determined to be abnormal. If the three-phase current balance is greater than or equal to the preset three-phase current balance, then the thyristor is determined to be normal.

5. The intelligent fault detection system for high-voltage solid-state soft starter according to claim 4, characterized in that, The fault analysis module, under a single abnormal condition, determines a secondary judgment based on the correlation degree of thyristor fault data, or the maximum data correlation coefficient or thyristor anomaly comparison degree, including: If the correlation of thyristor fault data is less than the preset correlation of thyristor fault data, then the maximum correlation coefficient is used to determine whether there is an abnormality in the thyristor. If the correlation degree of thyristor fault data is greater than or equal to the preset correlation degree of thyristor fault data, then it is determined whether there is an abnormality in the thyristor based on the thyristor anomaly comparison degree. The aforementioned abnormal condition is that the thyristor is abnormal during a single determination.

6. The intelligent fault detection system for high-voltage solid-state soft starter according to claim 5, characterized in that, The method for confirming the anomaly comparison of the thyristor includes: If the current rate change is greater than or equal to the preset current rate change, the thyristor anomaly comparison degree is determined based on the rate change comparison degree. If the current rate change is less than the preset current rate change, the thyristor anomaly comparison degree is determined based on the current attenuation degree. Current decay rate = average value of output current at each time point in the current monitoring cycle - average value of output current at each time point in the monitoring cycle corresponding to each reference historical record where the current rate change rate is less than the preset current rate change rate; the output current is the current value flowing to the motor through the high-voltage solid-state soft starter.

7. The intelligent fault detection system for high-voltage solid-state soft starter according to claim 5, characterized in that, The anomaly identification module determines the abnormal thyristor group based on the current difference and temperature anomaly value. The abnormal thyristor group is a thyristor group whose current difference is greater than a preset current difference or whose temperature abnormality value is greater than a preset temperature abnormality value. The thyristor group refers to each thyristor in a single phase of a three-phase bridge circuit in a high-voltage solid-state soft starter.

8. The intelligent fault detection system for high-voltage solid-state soft starter according to claim 7, characterized in that, When the temperature difference is greater than or equal to the preset temperature difference, the second early warning module determines that the abnormal thyristor group is due to sudden damage, and determines the degree of thyristor abnormality based on the degree of sudden damage. The degree of sudden damage is determined based on the degree of pressure drop change.

9. The intelligent fault detection system for high-voltage solid-state soft starter according to claim 8, characterized in that, When the temperature difference is less than the preset temperature difference, the second early warning module determines that the abnormal thyristor group is aging, and determines the degree of thyristor abnormality based on the degree of aging. The aging degree of the thyristor is determined based on the correlation between current and temperature.

10. The intelligent fault detection system for high-voltage solid-state soft starter according to claim 9, characterized in that, When the maximum thyristor anomaly degree is greater than or equal to the preset maximum thyristor anomaly degree, the second early warning module determines whether to issue a fault warning based on the degree of change in anomaly degree. When determining whether to issue a fault warning based on the degree of anomaly change, if the degree of anomaly change is greater than or equal to the preset degree of anomaly change, then a fault warning is issued. If the degree of anomaly change is less than the preset degree of anomaly change, then no fault warning is required.

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