A multi-hardware compatible aviation power supply characteristic test analysis system

Abstract

The present application relates to the technical field of power supply test, and more particularly to a multi-hardware compatible aviation power supply characteristic test analysis system. The present application collects signal data based on a data acquisition module, determines representative waveform segments of each range interval according to signal stagnation degree by a representative feature construction module, calibrates each different variation peak time according to the change difference between real-time waveform and representative waveform segments by a peak calibration module, judges whether there is a switching blind area tendency according to forward aggregation characteristics and center migration characteristics by a tendency analysis module, determines a sampling period according to the change trend of forward aggregation characteristics for the existence of switching blind area tendency by a sampling execution module, and collects signal waveforms in the sampling period by a sampling analysis module to test and analyze the signal waveforms. The present application identifies the risk of transient peak falling into the switching blind area before the execution of range switching, and carries out targeted sampling analysis, thereby improving the authenticity and reliability of aviation power supply characteristic test data.

Description

Technical Field

[0001] This invention relates to the field of power supply testing technology, and in particular to a multi-hardware compatible aviation power supply characteristic testing and analysis system. Background Technology

[0002] With the rapid development of aviation power supply testing technology, aviation power supply systems are evolving rapidly from traditional low-voltage systems to high-voltage DC systems. The testing and verification of power supply characteristics are not only closely related to the power quality, transient characteristics and stability verification of the high-voltage DC bus, but also closely linked to the airworthiness compliance, safety and reliability assessment of airborne electrical equipment. A high-precision, compatible aviation power supply characteristic testing and analysis system with multi-hardware adaptation capabilities has become an indispensable part of modern aviation power supply systems.

[0003] Chinese Patent Publication No. CN119689317A discloses a load testing method and system for an aviation power supply system. The load testing method includes: testing the target aviation power supply system under test with an initial load, and obtaining test data values ​​for the target aviation power supply system; obtaining the load increase gradient value based on the test data values ​​corresponding to the initial load of the target aviation power supply system; gradually increasing the load according to the load increase gradient value, and obtaining the test data values ​​of the target aviation power supply system corresponding to each increase in load; and determining whether the operation of the target aviation power supply system meets the load test performance requirements based on the test data values ​​corresponding to each increase in load. The system includes modules corresponding to the steps of the method.

[0004] However, the following problems still exist in the existing technology. Because there is an inherent delay in the switching response when the range switching action is performed in the aviation power supply system, and the transient spikes caused by random events such as load shedding and power conversion last only on the order of microseconds, they are very likely to fall into the switching blind zone and be silently masked, thereby reducing the authenticity and reliability of aviation power supply characteristic test data. Summary of the Invention

[0005] To address this issue, the present invention provides a multi-hardware compatible aviation power supply characteristic testing and analysis system to overcome the problem in the prior art where transient spikes caused by random events during range switching in the aviation power supply system are easily trapped in the switching blind zone and silently masked, thereby reducing the authenticity and reliability of aviation power supply characteristic test data.

[0006] To achieve the above objectives, the present invention provides a multi-hardware compatible aviation power supply characteristic testing and analysis system, which includes, The data acquisition module is used to acquire hardware attribute data and signal data of the target acquisition channel; the signal data includes voltage data and current data. The representative feature construction module is used to divide the range of the target acquisition channel into several range intervals and determine the representative waveform segment of each range interval based on the signal stagnation degree. The range is determined based on hardware attribute data, and the signal stagnation degree is determined based on the ratio of the cumulative duration of the signal data in the corresponding range interval within the reference time domain segment to the reference time domain segment. The peak calibration module is used to calibrate the timing of each variation peak based on the difference between the real-time waveform and the representative waveform segment of the corresponding range. The tendency analysis module is used to determine whether there is a switching blind zone tendency in the target acquisition channel based on the forward aggregation characteristics and the center migration characteristics. The forward aggregation characteristics are determined based on the concentration of the adjacent time difference corresponding to each mutation peak moment, and the center migration characteristics are determined based on the change of the center of the range interval corresponding to each mutation peak moment. The sampling execution module is used to determine the sampling period based on the changing trend of forward aggregation characteristics, in response to the tendency of switching blind spots. The sampling analysis module is used to collect signal waveforms during the sampling period and to test and analyze the signal waveforms.

[0007] Furthermore, the representative feature construction module includes, The range division subunit is used to determine the range based on the hardware attribute data of the target acquisition channel and divide the range into several range intervals. The representative waveform segment determination subunit is used to determine the signal waveform segment corresponding to the reference time domain segment with the highest signal stagnation in each range interval as the representative waveform segment of the range interval.

[0008] Furthermore, the representative feature building module also includes, The reference time domain segment division subunit is used to divide the reference historical monitoring period into several reference time domain segments; The stall degree determination subunit is used to determine the signal stall degree by the ratio of the cumulative duration of signal data in the corresponding range interval to the reference time domain segment for a single reference time domain segment.

[0009] Furthermore, the peak calibration module includes, The peak moment determination sub-unit is used to identify the moment when the variation difference exceeds the baseline variation difference as the variation peak moment.

[0010] Furthermore, the peak calibration module also includes, The rate of change determination subunit is used to determine the first rate of change at each sampling moment in the real-time waveform, and the second rate of change at each sampling moment in the representative waveform segment of the corresponding range interval of the real-time waveform. The variation difference determination subunit is used to determine the variation difference by the absolute value of the difference between the first rate of change and the second rate of change at each sampling time.

[0011] Furthermore, the tendency analysis module includes, The tendency determination sub-unit is used to determine the presence of a switching blind zone tendency in target acquisition channels where the forward aggregation characteristics exceed the baseline aggregation value or the center migration characteristics exceed the baseline migration value.

[0012] Furthermore, the tendency analysis module also includes, The up-switching start time determination subunit is used to determine the start time of the up-switching when the target acquisition channel is switched from a low range to a high range. The adjacency time difference determination subunit is used to determine the absolute value of the time difference between each mutation peak moment and the starting moment of the upward switch with the smallest time interval as the adjacency time difference corresponding to the mutation peak moment. The forward clustering feature determines the sub-unit, which is used to determine the forward clustering feature by the reciprocal of the variance of the time difference of each adjacent unit.

[0013] Furthermore, the tendency analysis module also includes, The center-determining sub-unit is used to determine the average of the upper and lower limits of each range interval as the center of the range interval. The center sequence determination subunit is used to arrange the centers of the range intervals corresponding to each anomaly peak time in chronological order to obtain the center sequence; The migration feature value determination subunit is used to determine the difference between the previous center and the subsequent center in the center sequence, and the average of the positive differences is determined as the center migration feature.

[0014] Furthermore, the sampling execution module includes, The sampling time determination sub-unit is used to determine the end time of the reference window as the sampling time when the mean rate of change of the forward aggregation feature within the reference window exceeds the reference aggregation change value.

[0015] Furthermore, the sampling execution module also includes, The up-switching end time determination sub-unit is used to determine the completion time of the action of switching the target acquisition channel from a low range to a high range as the end time of the up-switching. The sampling period determination sub-unit is used to determine the time interval from the sampling time to the end time of the next upward switch as the sampling period.

[0016] Compared with existing technologies, this invention acquires signal data using a data acquisition module. A representative feature construction module determines representative waveform segments for each measurement range based on signal stagnation. A peak calibration module calibrates the timing of each aberration peak based on the difference between the real-time waveform and the representative waveform segments. A trend analysis module determines the presence of a switching blind zone tendency based on forward aggregation and center migration characteristics. For modules with a switching blind zone tendency, a sampling execution module determines the sampling period based on the changing trend of the forward aggregation characteristics. The sampling analysis module acquires signal waveforms within the sampling period for testing and analysis. This invention identifies the risk of transient peaks falling into switching blind zones before range switching and performs targeted sampling analysis, thereby improving the authenticity and reliability of aviation power supply characteristic test data.

[0017] In particular, this invention divides the target acquisition channel's measurement range into several range intervals and determines the representative waveform segment of each range interval based on the signal stagnation. During aviation power supply testing, the signal from the target acquisition channel is not uniformly distributed across the entire range, but rather remains stationary in certain range intervals due to the operating state of the power supply system under test. For example, during steady-state DC testing, the voltage remains within a narrow range for an extended period, with a stable waveform and slow changes. However, when a sudden load unloading or power conversion occurs, the signal may surge into a higher range interval or drop into a lower range interval within a very short time, before quickly returning to the original steady-state range. The waveforms corresponding to these brief jumps are significantly affected by transient disturbances and cannot reflect the typical fluctuation patterns of the corresponding range interval under normal testing conditions. If a unified judgment criterion is used in subsequent analysis, it becomes difficult to distinguish between stable fluctuations in the stationary range and brief jumps in the transient range, easily leading to misjudgments or missed judgments in anomaly identification. Therefore, this invention uses the ratio of the cumulative dwell time of signal data in each range interval to the total duration of the corresponding reference time domain segment as the signal stagnation degree, and selects the signal waveform segment corresponding to the reference time domain segment with the highest signal stagnation degree in each range interval as the representative waveform segment of that range interval. The representative waveform segment directly originates from the signal data acquired by the target acquisition channel under actual test conditions, reflecting the typical and stable fluctuation state of the signal within the corresponding range interval. This eliminates the influence of using occasional jumps as subsequent comparison benchmarks, reduces misjudgments caused by differences in fluctuation characteristics between different range intervals, provides a reliable basis for determining the tendency of switching blind zones, and thus improves the accuracy of peak calibration and the authenticity and reliability of aviation power supply characteristic test data.

[0018] In particular, this invention calibrates the timing of each transient spike based on the difference in variation between the real-time waveform and the representative waveform segment of the corresponding range interval. During aviation power supply testing, the essential characteristic of transient spikes lies not in their absolute amplitude, but in the sudden and significant increase in their rate of change. Different range intervals inherently exhibit different levels of signal fluctuation. Using a uniform reference value to determine the timing of transient spikes could lead to misjudging normal fluctuations, which are already relatively strong in higher range intervals, as spikes, and missing spikes in lower range intervals with small amplitudes but significantly abnormal rates of change. Therefore, this invention establishes representative waveform segments for each range interval and compares the rate of change of the real-time waveform with that of the representative waveform segment within its range interval to obtain the difference in variation. When the difference in variation exceeds the baseline difference, that moment is calibrated as the timing of the transient spike. This invention, based on the degree to which the signal deviates from the typical fluctuation state of its range interval, can more accurately detect transient anomalies, reduce misjudgments and omissions, provide a reliable basis for subsequent determination of switching blind zone tendencies, and thus improve the accuracy of spike calibration and the authenticity and reliability of aviation power supply characteristic test data.

[0019] In particular, this invention determines whether the target acquisition channel has a tendency to switch blind zones based on forward aggregation characteristics and center migration characteristics. In aviation power supply testing, the real danger is not the spike itself, but the overlap between the timing of the spike and the range switching action, causing the signal to be undetected in a timely manner within the switching blind zone. The timing of the range switching is controlled by the system itself and is known, but when a spike occurs is random, and a single spike cannot be predicted. However, although a single spike is unpredictable, there are precursors to the system entering a high-risk state. For example, when load switching operations become more frequent, and when continuous disturbances occur on the power supply bus before and after the switching of high-power equipment, the frequency of spike occurrence will increase, the time correlation between the spike and the range switching action will become more obvious, and the range range where the spike is located will gradually shift towards higher ranges. These changes are not single events, but a gradually accumulating trend over a period of time.

[0020] Therefore, this invention determines whether a target acquisition channel has a tendency to switch blind zones based on forward aggregation characteristics and center migration characteristics. The forward aggregation characteristic reflects the temporal collision trend by the concentration of the time difference between each anomaly peak moment and the upward switching start moment with the smallest time interval. When peaks appear more densely before and after the switching action, the time difference variance decreases, its reciprocal increases, and the forward aggregation characteristic strengthens, indicating that the peak and the switching window are converging in time, increasing the risk of falling into the blind zone. The center migration characteristic reflects the range migration trend by arranging the center values ​​of the range intervals corresponding to each anomaly peak moment in chronological order, and then averaging the positive differences between adjacent center values. The larger the center migration characteristic, the more the range where the peak is located continues to move towards higher ranges, the signal as a whole approaches the upper limit of the range, the more urgent the need for the system to switch ranges, and the greater the risk of blind zones. If any feature exceeds the benchmark value, it is determined that there is a tendency for switching blind spots. This invention combines the timing relationship between peaks and switching actions with the changing trend of the range in which the peaks are located, thereby identifying the risk accumulation trend shown by the peak groups that have already occurred. This can more reliably determine whether there is a tendency for switching blind spots in the target acquisition channel, thereby improving the accuracy of peak calibration and the authenticity and reliability of aviation power supply characteristic test data.

[0021] In particular, this invention addresses the issue of handover blind zone tendencies by determining the sampling period based on the changing trend of forward aggregation characteristics. In actual aviation power supply testing, merely identifying a handover blind zone tendency is insufficient to initiate targeted sampling. This is because the tendency may be caused by occasional spikes or fluctuations, or it may be an early manifestation of accumulating risk. Immediately using the entire subsequent time period as the sampling period would create unnecessary sampling burden and could also lead to missing truly dangerous time windows due to improper time selection. Therefore, after determining the presence of a handover blind zone tendency, this invention further observes the average rate of change of the forward aggregation characteristics within a baseline window. This average rate of change reflects whether the speed at which spikes and handover actions converge in time is accelerating. Only when the average rate of change exceeds the baseline aggregation change value is the risk considered to be substantially escalating, and the end time of the baseline window is determined as the sampling time. After the sampling time, the system enters a risk-increasing phase, and this invention uses the time interval between the sampling time and the end time of the next upward handover as the sampling period. The sampling period is triggered by the actual changing trend of the forward aggregation characteristics, and can be dynamically adjusted according to the temporal behavior of the peak group, eliminating the influence of oversampling of random fluctuations. Simultaneously, targeted and accurate sampling is completed before the peak and switching window overlap, ensuring that the signal waveform acquired during the sampling period is complete and unaffected by range switching blind spots, providing a reliable basis for subsequent testing and analysis. This improves the accuracy of peak calibration and the authenticity and reliability of aviation power supply characteristic test data. Attached Figure Description

[0022] Figure 1 A system block diagram of a multi-hardware compatible aviation power supply characteristic test and analysis system according to an embodiment of the invention; Figure 2 This is a logic decision diagram for calibrating the timing of each variation spike in an embodiment of the invention; Figure 3 This is a logic diagram for determining whether a target acquisition channel has a tendency to switch blind spots, as shown in an embodiment of the invention. Figure 4 This is a logic diagram for determining the sampling time in an embodiment of the invention. Detailed Implementation

[0023] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0024] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0025] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the term "connection" should be interpreted broadly. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium; it can be a connection within two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0026] Please see Figure 1 The diagram shown is a system block diagram of a multi-hardware compatible aviation power supply characteristic test and analysis system according to an embodiment of the invention. The system of the present invention includes: The data acquisition module is used to acquire hardware attribute data and signal data of the target acquisition channel; The representative feature construction module is used to divide the range of the target acquisition channel into several range intervals and determine the representative waveform segment of each range interval based on the signal stagnation. The peak calibration module is used to calibrate the timing of each variation peak based on the difference between the real-time waveform and the representative waveform segment of the corresponding range. The tendency analysis module is used to determine whether there is a switching blind zone tendency in the target acquisition channel based on forward aggregation characteristics and center migration characteristics. The sampling execution module is used to determine the sampling period based on the changing trend of forward aggregation characteristics, in response to the tendency of switching blind spots. The sampling analysis module is used to collect signal waveforms during the sampling period and to test and analyze the signal waveforms.

[0027] It is understandable that the target acquisition channel is a hardware channel used in a multi-hardware compatibility test system to acquire the power supply signal of the aircraft under test. The hardware channel can correspond to acquisition hardware from different manufacturers and has a range determined by hardware attribute data.

[0028] It is understandable that the hardware attribute data of the target acquisition channel can be obtained by reading the device description information of the acquisition hardware itself, or by obtaining it from the channel configuration information during system initialization. It is sufficient to obtain the hardware attribute data such as the range of the channel, which will not be elaborated further.

[0029] It is understandable that the signal data of the target acquisition channel can be acquired in real time by acquisition hardware or by reading the acquisition records stored in the test system. It is sufficient to obtain the voltage and current data of the target acquisition channel, which will not be elaborated further.

[0030] It is understandable that when the target acquisition channel is a voltage channel, this scheme is executed based on the voltage data; when the target acquisition channel is a current channel, this scheme is executed based on the current data.

[0031] Specifically, the representative feature construction module includes, The range division subunit is used to determine the range based on the hardware attribute data of the target acquisition channel and divide the range into several range intervals. The representative waveform segment determination subunit is used to determine the signal waveform segment corresponding to the reference time domain segment with the highest signal stagnation in each range interval as the representative waveform segment of the range interval.

[0032] In this embodiment, there is no limitation on the way the measurement range is divided into several range intervals. The measurement range can be divided at equal intervals, or it can be divided according to the main distribution range of the signal amplitude of the target acquisition channel under test conditions. As long as the measurement range can be divided into several range intervals for analyzing the stagnation of the signal, it will not be elaborated further.

[0033] In this embodiment, when a signal spans multiple measurement ranges within a reference time domain segment, when determining the representative waveform segment for a certain measurement range, only the signal waveform corresponding to the period during which the signal within that reference time domain segment actually falls within that measurement range is extracted.

[0034] Specifically, the representative feature construction module also includes, The reference time domain segment division subunit is used to divide the reference historical monitoring period into several reference time domain segments; The stall degree determination subunit is used to determine the signal stall degree by the ratio of the cumulative duration of signal data in the corresponding range interval to the reference time domain segment for a single reference time domain segment.

[0035] In this embodiment, the baseline historical monitoring period is predetermined. Those skilled in the art can determine the baseline historical monitoring period based on the complete test period of the same working condition in the existing test data, or based on the period of pre-collection before the start of the current test. As long as sample data for signal analysis can be obtained, the specific value does not constitute a limitation on the present invention, and will not be elaborated here.

[0036] In this embodiment, the method of dividing the benchmark historical monitoring period is not limited. As an example, those skilled in the art can divide the benchmark historical monitoring period into several benchmark time domain segments, as long as each benchmark time domain segment is sufficient to analyze the signal stagnation. The specific values ​​do not constitute a limitation on the present invention, and will not be elaborated here.

[0037] It is understandable that the cumulative duration of signal data within the corresponding range is the sum of the duration for which the signal amplitude acquired by the target acquisition channel falls within that range within a single reference time domain segment.

[0038] In this embodiment, the signal stagnation degree is the ratio of the cumulative duration of signal data within the corresponding range interval in a single reference time domain segment to the total duration of that reference time domain segment. A larger signal stagnation degree indicates a longer time the signal remains within the corresponding range interval in the reference time domain segment, a more stable signal state within that range interval, and a signal waveform corresponding to the reference time domain segment that better represents the fluctuation state of that range interval. Conversely, a smaller signal stagnation degree indicates a shorter time the signal remains within the corresponding range interval in the reference time domain segment, with the signal exhibiting mostly brief jumps or transient fluctuations within that range interval, and a signal waveform corresponding to the reference time domain segment that is less suitable as a representative waveform segment of that range interval.

[0039] Please see Figure 2 As shown, it is a logic decision diagram for calibrating the timing of each variation spike in an embodiment of the invention. The spike calibration module described in this embodiment includes, The peak moment determination sub-unit is used to identify the moment when the variation difference exceeds the baseline variation difference as the variation peak moment.

[0040] In this embodiment, the baseline variation difference is the normal level of the difference in the rate of change between the real-time waveform and the representative waveform segment. The baseline variation difference is predetermined. As an example, those skilled in the art can determine the baseline variation difference based on the average value of the difference in the rate of change between the real-time waveform and the representative waveform segment under the same test conditions in historical test data. It is only necessary to be able to distinguish between normal fluctuations and transient spikes. The specific value does not constitute a limitation on the present invention, and will not be elaborated here.

[0041] Specifically, the peak calibration module also includes, The rate of change determination subunit is used to determine the first rate of change at each sampling moment in the real-time waveform, and the second rate of change at each sampling moment in the representative waveform segment of the corresponding range interval of the real-time waveform. The variation difference determination subunit is used to determine the variation difference by the absolute value of the difference between the first rate of change and the second rate of change at each sampling time.

[0042] In this embodiment, both the real-time waveform and the representative waveform segment are arranged in sampling order. When calculating the variation difference, each sampling moment of the real-time waveform is aligned with the corresponding sampling points in the representative waveform segment in chronological order. When the length of the real-time waveform and the length of the representative waveform segment are inconsistent, they can be aligned by interpolation before comparison. It is only necessary to ensure that each sampling moment has a corresponding second rate of change, which will not be elaborated further.

[0043] In this embodiment, the first rate of change is the signal change rate at each sampling moment in the real-time waveform; the second rate of change is the signal change rate at the sampling point corresponding to each sampling moment of the real-time waveform in the representative waveform segment corresponding to the range interval of the real-time waveform in chronological order; the difference in change is the absolute value of the difference between the first rate of change and the second rate of change.

[0044] Please see Figure 3 As shown, this is a logic diagram for determining whether a target acquisition channel has a switching blind spot tendency according to an embodiment of the invention. The tendency analysis module described in this embodiment includes, The tendency determination sub-unit is used to determine the presence of a switching blind zone tendency in target acquisition channels where the forward aggregation characteristics exceed the baseline aggregation value or the center migration characteristics exceed the baseline migration value.

[0045] In this embodiment, the baseline aggregation value is the normal level reached by the forward aggregation feature of the target acquisition channel under normal test conditions. The baseline aggregation value is predetermined. As an example, those skilled in the art can determine the baseline aggregation value based on the average value of the forward aggregation feature under the same test conditions in historical test data. It is only necessary to be able to distinguish the state with a tendency to switch blind spots. The specific value does not constitute a limitation on the present invention, and will not be elaborated here.

[0046] In this embodiment, the baseline migration value is the normal level corresponding to the center migration feature of the target acquisition channel under normal test conditions. The baseline migration value is predetermined. As an example, those skilled in the art can determine the average value of the center migration feature under the same test conditions in historical test data as the baseline migration value. It is only necessary to be able to distinguish the state with a tendency to switch blind spots. The specific value does not constitute a limitation on the present invention, and will not be elaborated here.

[0047] Specifically, the tendency analysis module also includes, The up-switching start time determination subunit is used to determine the start time of the up-switching when the target acquisition channel is switched from a low range to a high range. The adjacency time difference determination subunit is used to determine the absolute value of the time difference between each mutation peak moment and the starting moment of the upward switch with the smallest time interval as the adjacency time difference corresponding to the mutation peak moment. The forward clustering feature determines the sub-unit, which is used to determine the forward clustering feature by the reciprocal of the variance of the time difference of each adjacent unit.

[0048] In this embodiment, the starting time of the upward switching is the actual start time of the switching action when the target acquisition channel switches from a low range to a high range. This time can be determined by the range switching event recorded by the system.

[0049] In this embodiment, the adjacency time difference is the absolute value of the time difference between each mutation peak moment and the time difference between the start moment of the nearest upward switch, which is used to reflect the temporal proximity of the peak and the switching action.

[0050] In this embodiment, the forward clustering feature is the reciprocal of the variance of each adjacent time difference. The larger the forward clustering feature, the more concentrated the time difference between each mutation peak moment and the most recent upward handover start moment, the more densely the peaks appear near the handover action, and the higher the risk of the peaks falling into the handover blind zone; the smaller the forward clustering feature, the more dispersed the time difference between each mutation peak moment and the upward handover start moment, the weaker the temporal correlation between the peaks and the handover action, and the lower the risk of the peaks falling into the handover blind zone.

[0051] It is understandable that this embodiment uses the start time of upward switching as the analysis object because the signal change direction is the same as the transient spike direction during upward switching, and the risk of the switching blind zone coinciding with the spike is significantly higher than that of downward switching. For downward switching, the direction is opposite to that of the transient spike, and the probability of the spike falling into the switching blind zone is low. The existing range switching processing method can meet the test requirements.

[0052] It should be noted that if the number of upward switching times within the corresponding monitoring period is too small, making the variance calculation based on adjacency time difference unreliable, the starting time of upward switching can be accumulated until enough adjacency time difference samples can be obtained to calculate the forward aggregation feature.

[0053] It should be noted that when the time differences of all adjacent connections are equal, resulting in a variance of zero, it indicates that the peak time is completely concentrated near the handover action. In this case, those skilled in the art can directly determine that there is a tendency for a handover blind zone. This indicates the highest risk of a handover blind zone.

[0054] Specifically, the tendency analysis module also includes, The center-determining sub-unit is used to determine the average of the upper and lower limits of each range interval as the center of the range interval. The center sequence determination subunit is used to arrange the centers of the range intervals corresponding to each anomaly peak time in chronological order to obtain the center sequence; The migration feature value determination subunit is used to determine the difference between the previous center and the subsequent center in the center sequence, and the average of the positive differences is determined as the center migration feature.

[0055] In this embodiment, the center migration feature is the average of the positive differences obtained by subtracting the previous center from the subsequent center in the center sequence. The larger the center migration feature, the more obvious the trend of the center of the range interval corresponding to each mutation peak moment migrating towards the higher range in chronological order, the closer the overall signal is to the upper limit of the range, the more urgent the need for range switching, and the higher the risk of switching blind zone; the smaller the center migration feature, the weaker the upward shift trend of the center of the range interval where the peak is located, the lower the degree to which the overall signal approaches the higher range, and the relatively lower the risk of switching blind zone.

[0056] It should be noted that when there is no positive difference in the center sequence, that is, when all subsequent centers are less than or equal to the previous center, the center migration feature is set to zero, indicating that the range of the peak does not show a trend of migration towards a higher range.

[0057] Please see Figure 4 As shown, it is a logic decision diagram for determining the sampling time in an embodiment of the invention. The sampling execution module described in this embodiment includes, The sampling time determination sub-unit is used to determine the end time of the reference window as the sampling time when the mean rate of change of the forward aggregation feature within the reference window exceeds the reference aggregation change value.

[0058] In this embodiment, the reference window is the time period for calculating the average rate of change of the forward aggregation feature. Those skilled in the art can determine the reference window based on the sampling rate of the target acquisition channel in a way that covers a sufficient number of sampling points, as long as the rate of change of the forward aggregation feature within the window is statistically significant; further details are omitted here.

[0059] In this embodiment, the baseline aggregation change value is the normal level of the forward aggregation feature change within the baseline window. The baseline aggregation change value is predetermined. As an example, those skilled in the art can determine the baseline aggregation change value based on the average rate of change of the forward aggregation feature under the same test conditions in historical test data. It is only necessary to be able to determine whether the forward aggregation feature shows a significant upward trend. The specific value does not constitute a limitation on the present invention, and will not be elaborated further.

[0060] Specifically, the sampling execution module also includes, The up-switching end time determination sub-unit is used to determine the completion time of the action of switching the target acquisition channel from a low range to a high range as the end time of the up-switching. The sampling period determination sub-unit is used to determine the time interval from the sampling time to the end time of the next upward switch as the sampling period.

[0061] It is understood that in this embodiment, the end time of the next upward switch is triggered by the test system according to the control command, and the start and end times of the switch can be obtained in advance by the system test plan. Therefore, the end time of the next upward switch after the sampling time is a planned event known to the system.

[0062] In this embodiment, signal waveforms are acquired during the sampling period and then tested and analyzed. The specific methods of testing and analysis are not limited. Those skilled in the art can compare the signal waveforms acquired during the sampling period with a reference waveform, or perform steady-state characteristic analysis, ripple characteristic analysis, or transient characteristic analysis on the signal waveforms, based on the characteristics of the aviation power supply under test. As long as the testing and analysis can be completed based on the signal waveforms during the sampling period, the specific testing and analysis methods will not be elaborated here.

[0063] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. A multi-hardware compatible aviation power supply characteristic testing and analysis system, characterized in that, include, The data acquisition module is used to acquire hardware attribute data and signal data of the target acquisition channel; the signal data includes voltage data and current data. The representative feature construction module is used to divide the range of the target acquisition channel into several range intervals and determine the representative waveform segment of each range interval based on the signal stagnation degree. The range is determined based on hardware attribute data, and the signal stagnation degree is determined based on the ratio of the cumulative duration of the signal data in the corresponding range interval within the reference time domain segment to the reference time domain segment. The peak calibration module is used to calibrate the timing of each variation peak based on the difference between the real-time waveform and the representative waveform segment of the corresponding range. The tendency analysis module is used to determine whether there is a switching blind zone tendency in the target acquisition channel based on the forward aggregation characteristics and the center migration characteristics. The forward aggregation characteristics are determined based on the concentration of the adjacent time difference corresponding to each mutation peak moment, and the center migration characteristics are determined based on the change of the center of the range interval corresponding to each mutation peak moment. The sampling execution module is used to determine the sampling period based on the changing trend of forward aggregation characteristics, in response to the tendency of switching blind spots. The sampling analysis module is used to collect signal waveforms during the sampling period and to test and analyze the signal waveforms.

2. The multi-hardware compatible aviation power supply characteristic testing and analysis system according to claim 1, characterized in that, The representative feature construction module includes, The range division subunit is used to determine the range based on the hardware attribute data of the target acquisition channel and divide the range into several range intervals. The representative waveform segment determination subunit is used to determine the signal waveform segment corresponding to the reference time domain segment with the highest signal stagnation in each range interval as the representative waveform segment of the range interval.

3. The multi-hardware compatible aviation power supply characteristic testing and analysis system according to claim 2, characterized in that, The representative feature construction module also includes, The reference time domain segment division subunit is used to divide the reference historical monitoring period into several reference time domain segments; The stall degree determination subunit is used to determine the signal stall degree by the ratio of the cumulative duration of signal data in the corresponding range interval to the reference time domain segment for a single reference time domain segment.

4. The multi-hardware compatible aviation power supply characteristic testing and analysis system according to claim 1, characterized in that, The peak calibration module includes: The peak moment determination sub-unit is used to identify the moment when the variation difference exceeds the baseline variation difference as the variation peak moment.

5. The multi-hardware compatible aviation power supply characteristic testing and analysis system according to claim 4, characterized in that, The peak calibration module also includes, The rate of change determination subunit is used to determine the first rate of change at each sampling moment in the real-time waveform, and the second rate of change at each sampling moment in the representative waveform segment of the corresponding range interval of the real-time waveform. The variation difference determination subunit is used to determine the variation difference by the absolute value of the difference between the first rate of change and the second rate of change at each sampling time.

6. The multi-hardware compatible aviation power supply characteristic testing and analysis system according to claim 1, characterized in that, The tendency analysis module includes, The tendency determination sub-unit is used to determine the presence of a switching blind zone tendency in target acquisition channels where the forward aggregation characteristics exceed the baseline aggregation value or the center migration characteristics exceed the baseline migration value.

7. The multi-hardware compatible aviation power supply characteristic testing and analysis system according to claim 6, characterized in that, The tendency analysis module also includes, The up-switching start time determination subunit is used to determine the start time of the up-switching when the target acquisition channel is switched from a low range to a high range. The adjacency time difference determination subunit is used to determine the absolute value of the time difference between each mutation peak moment and the starting moment of the upward switch with the smallest time interval as the adjacency time difference corresponding to the mutation peak moment. The forward clustering feature determines the sub-unit, which is used to determine the forward clustering feature by the reciprocal of the variance of the time difference of each adjacent unit.

8. The multi-hardware compatible aviation power supply characteristic testing and analysis system according to claim 6, characterized in that, The tendency analysis module also includes, The center-determining sub-unit is used to determine the average of the upper and lower limits of each range interval as the center of the range interval. The center sequence determination subunit is used to arrange the centers of the range intervals corresponding to each anomaly peak time in chronological order to obtain the center sequence; The migration feature value determination subunit is used to determine the difference between the previous center and the subsequent center in the center sequence, and the average of the positive differences is determined as the center migration feature.

9. The multi-hardware compatible aviation power supply characteristic testing and analysis system according to claim 1, characterized in that, The sampling execution module includes, The sampling time determination sub-unit is used to determine the end time of the reference window as the sampling time when the mean rate of change of the forward aggregation feature within the reference window exceeds the reference aggregation change value.

10. The multi-hardware compatible aviation power supply characteristic testing and analysis system according to claim 9, characterized in that, The sampling execution module also includes, The up-switching end time determination sub-unit is used to determine the completion time of the action of switching the target acquisition channel from a low range to a high range as the end time of the up-switching. The sampling period determination sub-unit is used to determine the time interval from the sampling time to the end time of the next upward switch as the sampling period.

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