CN111637115B - Method and device for detecting abnormality of hydraulic system and readable storage medium - Google Patents
Method and device for detecting abnormality of hydraulic system and readable storage medium Download PDFInfo
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Abstract
The application provides a hydraulic system abnormity detection method, a detection device and a readable storage medium, wherein a plurality of pressure data of a hydraulic system to be detected, which are acquired within the same preset time interval during the working period, are divided into the same data group; for each data group, determining the standard deviation of the pressure of the data group based on a plurality of pressure data of the data group after abnormal pressure data are filtered; determining a plurality of target data based on the plurality of determined pressure standard deviations and a preset standard deviation range; determining a change curve of the pressure data along with the change of time according to the plurality of target data; and when the variation curve is detected to be inconsistent with the variation trend of the historical variation curve of the hydraulic system to be detected, determining that the hydraulic system to be detected is abnormal. Therefore, the influence of interference data on the judgment result can be eliminated, and the detection accuracy of the hydraulic system is improved.
Description
Technical Field
The present disclosure relates to the field of mechanical equipment monitoring technologies, and in particular, to a method and an apparatus for detecting an abnormality of a hydraulic system, and a readable storage medium.
Background
Engineering machinery is very important equipment in the field of machinery, the engineering machinery penetrates into various working environments, and in the process of working of the engineering machinery, in order to ensure the working safety, the working condition of each system in the working process of the engineering machinery is very necessary to be analyzed according to the working data of each system in the engineering machinery.
At the present stage, taking a hydraulic system of an engineering machine as an example, in the process of collecting and analyzing working data of the hydraulic system, due to the fact that a collecting sensor is abnormal or the data transmission process is abnormal, the working data participating in analysis may be messy, the data continuity and the recognizable performance are poor, accurate system analysis cannot be performed, the judgment of the working condition of the engineering machine is made to be wrong, and further the engineering machine has potential safety hazards.
Disclosure of Invention
In view of the above, an object of the present application is to provide a method, a device and a readable storage medium for detecting an abnormality of a hydraulic system, which are capable of directly determining a working condition of the hydraulic system according to a pressure data change trend determined by a plurality of target data without interference data, eliminating an influence of the interference data on a determination result, and facilitating improvement of accuracy of detection of the hydraulic system.
The embodiment of the application provides a method for detecting the abnormality of a hydraulic system, which comprises the following steps:
determining pressure data of each acquisition time of the hydraulic system to be detected in the working time period, and dividing a plurality of pressure data of which the acquisition time is in the same preset time interval into the same data group;
for each data group, determining the standard deviation of the pressure of the data group based on a plurality of pressure data of the data group after abnormal pressure data are filtered;
determining a plurality of target data based on the plurality of determined pressure standard deviations and a preset standard deviation range;
determining a change curve of the pressure data along with the change of time according to the plurality of target data;
and when the variation curve is detected to be inconsistent with the variation trend of the historical variation curve of the hydraulic system to be detected, determining that the hydraulic system to be detected is abnormal.
Further, before determining, for each data set, a standard deviation of pressure of the data set based on the plurality of pressure data of the data set from which abnormal pressure data is filtered, the detection method further includes:
for each data group, arranging a plurality of pressure data in the data group according to a sequence from small to large, and determining minimum pressure data and maximum pressure data in the plurality of pressure data;
determining a first data difference between the minimum pressure data and a first pressure data of a neighboring rank, and a second data difference between the maximum pressure data and a second pressure data of a neighboring rank;
when the first data difference and/or the second data difference are/is detected to be larger than a preset difference threshold value, determining the minimum pressure data and/or the maximum pressure data as abnormal pressure data;
the determined at least one abnormal pressure data is filtered from the data set.
Further, the determining a plurality of target data based on the determined plurality of pressure standard deviations and the preset standard deviation range includes:
determining the pressure standard deviation as a target data set, wherein the pressure standard deviation belongs to at least one data set within the preset standard deviation range;
determining pressure data included in each target data group as candidate data;
and filtering abnormal candidate data in the plurality of determined candidate data to determine a plurality of target data.
Further, the target data is determined by:
acquiring a preset pressure threshold;
determining candidate data which is larger than the preset pressure threshold value in the plurality of candidate data as abnormal candidate data;
and determining the plurality of candidate data left after the determined at least one abnormal candidate data is filtered from the plurality of candidate data as target data.
Further, the variation trend of the variation curve is determined to be inconsistent with the variation trend of the historical variation curve of the hydraulic system to be detected through the following steps:
determining the slope of the curve corresponding to the change curve at a target time and the slope of the historical curve corresponding to the historical change curve at the target time;
detecting whether the slope of the curve is equal to the slope of the historical curve;
and if the slope of the curve is not equal to that of the historical curve, determining that the change trend of the change curve is inconsistent with that of the historical change curve of the hydraulic system to be detected.
The embodiment of the present application further provides a detection device for detecting an abnormality of a hydraulic system, where the detection device includes:
the first determining module is used for determining pressure data of each acquisition time of the hydraulic system to be detected in the working time period and dividing a plurality of pressure data of which the acquisition time is in the same preset time interval into the same data group;
the second determining module is used for determining the standard deviation of the pressure of each data group based on the plurality of pressure data of the data group after abnormal pressure data are filtered out;
the third determining module is used for determining a plurality of target data based on the plurality of determined pressure standard deviations and the preset standard deviation range;
the fourth determining module is used for determining a change curve of the pressure data along with the change of time according to the plurality of target data;
and the fifth determining module is used for determining that the hydraulic system to be detected is abnormal when the variation curve is detected to be inconsistent with the variation trend of the historical variation curve of the hydraulic system to be detected.
Further, the detection apparatus further includes a data filtering module, and the data filtering module is configured to:
for each data group, arranging a plurality of pressure data in the data group according to a sequence from small to large, and determining minimum pressure data and maximum pressure data in the plurality of pressure data;
determining a first data difference between the minimum pressure data and a first pressure data of a neighboring rank, and a second data difference between the maximum pressure data and a second pressure data of a neighboring rank;
when the first data difference and/or the second data difference are/is detected to be larger than a preset difference threshold value, determining the minimum pressure data and/or the maximum pressure data as abnormal pressure data;
the determined at least one abnormal pressure data is filtered from the data set.
Further, when the third determining module is configured to determine a plurality of target data based on the plurality of determined pressure standard deviations and the preset standard deviation range, the third determining module is configured to:
determining the pressure standard deviation as a target data set, wherein the pressure standard deviation belongs to at least one data set within the preset standard deviation range;
determining pressure data included in each target data group as candidate data;
and filtering abnormal candidate data in the plurality of determined candidate data to determine a plurality of target data.
Further, the third determining module is configured to determine the target data by:
acquiring a preset pressure threshold;
determining candidate data which is larger than the preset pressure threshold value in the plurality of candidate data as abnormal candidate data;
and determining the plurality of candidate data left after the determined at least one abnormal candidate data is filtered from the plurality of candidate data as target data.
Further, the fifth determining module is configured to determine that the variation curve is inconsistent with the variation trend of the historical variation curve of the hydraulic system to be detected through the following steps:
determining the slope of the curve corresponding to the change curve at a target time and the slope of the historical curve corresponding to the historical change curve at the target time;
detecting whether the slope of the curve is equal to the slope of the historical curve;
and if the slope of the curve is not equal to that of the historical curve, determining that the change trend of the change curve is inconsistent with that of the historical change curve of the hydraulic system to be detected.
An embodiment of the present application further provides an electronic device, including: a processor, a memory and a bus, the memory storing machine readable instructions executable by the processor, the processor and the memory communicating via the bus when the electronic device is operating, the machine readable instructions when executed by the processor performing the steps of the method of detecting hydraulic system anomalies as described above.
The embodiment of the present application further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method for detecting an abnormality in a hydraulic system as described above are performed.
The detection method, the detection device and the readable storage medium for the hydraulic system abnormity, provided by the embodiment of the application, are used for determining the pressure data of the hydraulic system to be detected in each acquisition time in the working time period and dividing a plurality of pressure data of which the acquisition time is in the same preset time interval into the same data group; for each data group, determining the standard deviation of the pressure of the data group based on a plurality of pressure data of the data group after abnormal pressure data are filtered; determining a plurality of target data based on the plurality of determined pressure standard deviations and a preset standard deviation range; determining a change curve of the pressure data along with the change of time according to the plurality of target data; and when the variation curve is detected to be inconsistent with the variation trend of the historical variation curve of the hydraulic system to be detected, determining that the hydraulic system to be detected is abnormal.
Therefore, by determining the pressure data of each acquisition time of the hydraulic system to be detected in the working time period and according to the acquisition time of each pressure data, a plurality of data groups are determined, the pressure standard deviation of each data group is calculated, target data are determined from the plurality of pressure data according to the plurality of pressure standard deviations and the preset standard deviation range, the change curve of the pressure data along with the change of time is determined according to the plurality of target data without interference data, and when the change trend of the change curve is inconsistent with the change trend of the historical change curve, the abnormality of the hydraulic system to be detected is determined, the influence of the interference data on the judgment result can be eliminated, and the detection accuracy of the hydraulic system is improved.
In order to make the aforementioned objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.
FIG. 1 is a block diagram of a possible application scenario;
fig. 2 is a flowchart of a method for detecting an abnormality of a hydraulic system according to an embodiment of the present disclosure;
fig. 3 is a flowchart of a method for detecting an abnormality of a hydraulic system according to another embodiment of the present application;
fig. 4 is a schematic structural diagram of a detection apparatus for detecting an abnormality of a hydraulic system according to an embodiment of the present disclosure;
fig. 5 is a second schematic structural diagram of a hydraulic system abnormality detection apparatus according to an embodiment of the present disclosure;
fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all the embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. Every other embodiment that can be obtained by a person skilled in the art without making creative efforts based on the embodiments of the present application falls within the protection scope of the present application.
First, an application scenario to which the present application is applicable will be described. The application can be applied to the technical field of mechanical equipment monitoring, confirm that to detect hydraulic system and each pressure data on the acquisition time during the operating period, and according to the acquisition time of each pressure data, determine a plurality of data sets, and calculate the pressure standard deviation of each data set, according to a plurality of pressure standard deviations and preset standard deviation scope, determine the target data from a plurality of pressure data, according to a plurality of target data that do not contain interference data determine the change curve of pressure data along with the time variation, when detecting that the change curve is inconsistent with the change trend of historical change curve, confirm to detect hydraulic system and unusual, can get rid of the influence of interference data to the judged result, help improving the accuracy that detects hydraulic system. Referring to fig. 1, fig. 1 is a system structure diagram in a possible application scenario, as shown in fig. 1, the system includes a collecting device and a detecting device, the collecting device collects pressure data of a hydraulic system to be detected at regular time intervals during a working period, the detecting device obtains a plurality of pressure data collected by the collecting device, determines a variation curve of the pressure data along with time according to a plurality of target data after interference data is filtered, and detects whether the hydraulic system to be detected is abnormal according to a comparison result of the variation curve and a variation trend of a history variation curve.
Research shows that, in the present stage, taking a hydraulic system of an engineering machine as an example, in the process of acquiring and analyzing the working data of the hydraulic system, due to the conditions of abnormality of an acquisition sensor or abnormality in the data transmission process, the working data participating in analysis may be messy, the data continuity and the recognizable performance are poor, accurate system analysis cannot be performed, the judgment on the working condition of the engineering machine is made to be wrong, and further the engineering machine has potential safety hazards.
Based on this, the embodiment of the application provides a method for detecting the abnormality of a hydraulic system, which directly judges the working condition of the hydraulic system according to the pressure data change trend determined by a plurality of target data without interference data, can eliminate the influence of the interference data on the judgment result, and is beneficial to improving the accuracy of detection on the hydraulic system.
Referring to fig. 2, fig. 2 is a flowchart illustrating a method for detecting an abnormality of a hydraulic system according to an embodiment of the present disclosure. As shown in fig. 2, the method for detecting an abnormality of a hydraulic system according to the embodiment of the present application includes:
In the step, in the working time period of the hydraulic system, the data acquisition sensor acquires pressure data of the hydraulic system at each acquisition time, and for the acquired pressure data, the pressure data with the acquisition time within the same preset time interval are divided into the same data group to determine the data groups.
Here, the hydraulic system is a system applied to the construction machine to increase an acting force by changing a pressure, and an operation time period of the hydraulic system is an operation time of the construction machine, which refers to a time period from start to stop of the construction machine.
The engineering machine may be a crane, a fracturing machine, a bulldozer, an excavator, or other mechanical equipment that can be used in a construction site.
The pressure data can refer to pressure data of a hydraulic main pump on the engineering machinery and is acquired by a sensor.
The design of the preset time interval can be determined according to the quantity of pressure data generated in the historical working process of the hydraulic system and the acquisition time of the pressure data, when segmentation is carried out, the quantity of the pressure data in each preset time interval is ensured to be approximately equal, and after the preset time interval is determined, the pressure data are divided according to the acquisition time.
For example, five valid pressure data are collected during a certain working period: data A-8:05, data B-10:05, data C-12:30, data D-13:45 and data F-14: 03; the preset time interval is [8:00-11:00], [11:00-14:00], [14:00-17:00], and can be known according to the dividing principle: the data A and the data B are in the same data group; the data C and the data D are in the same data group; data F in the other groups.
Therefore, the collected pressure data are divided into different data groups for processing, the quantity of the pressure data processed in each data group is greatly reduced compared with the quantity of the pressure data which are simultaneously processed, and the processing speed of the pressure data is improved.
In this step, for each data set determined in step 201, the pressure standard deviation of the data set needs to be determined according to a plurality of pressure data obtained by filtering abnormal pressure data in the data set.
Here, the abnormal pressure data in each data group may be an abnormality due to a transmission failure of the data collection sensor, or a recording error.
In this way, the degree of dispersion of the pressure data in the data set is determined based on the standard deviation of the data set for subsequent data filtering operations.
In this step, a plurality of target data in the data group having a pressure standard deviation within the preset standard deviation range are determined from the plurality of pressure data according to the pressure standard deviation and the preset standard deviation range of each data group determined in step 202.
The preset standard deviation range indicates that the fluctuation of the pressure data in the preset standard deviation range can be received as normal fluctuation, and the fluctuation of the pressure data in the range does not influence the subsequent data processing process. For the setting of the preset standard deviation range, the fluctuation condition and the dispersion of the historical pressure data in the historical pressure data of the hydraulic system to be detected can be comprehensively considered for setting.
And 204, determining a change curve of the pressure data along with the change of time according to the plurality of target data.
In the step, a change curve of the pressure data along with the change of the time is determined according to the pressure value indicated by each target data and the acquisition time of each target data, so that the change trend of the pressure data along with the time is determined according to the change curve.
Here, for the determination of the variation curve, a binary coordinate system may be constructed with the collection time as an abscissa and the pressure value as an ordinate, the position point of each target data in the binary coordinate system may be determined based on the pressure value of each target data and the collection time, and the position points corresponding to each target data may be connected to generate the variation curve of the pressure data varying with time.
And step 205, when the variation curve is detected to be inconsistent with the variation trend of the historical variation curve of the hydraulic system to be detected, determining that the hydraulic system to be detected is abnormal.
In this step, after the change curve of the pressure data changing with time is determined in step 204, the historical change curve of the historical hydraulic data of the hydraulic system to be detected changing with time is obtained, the change curves are compared with the change trends of the historical change curve, and when the change trends of the change curves are inconsistent, it is determined that the hydraulic system to be detected is currently in an abnormal working state.
Here, the trend of the curve indicates whether the hydraulic pressure data is gradually increased (decreased) or increased in which time interval and decreased in which time interval, as time goes by, and also reflects the current operating state of the hydraulic system to be detected.
Here, the historical variation curve indicates a variation tendency of the pressure data with time in a case where the hydraulic system is normally operated, the variation tendency of the historical variation curve indicates a variation tendency of the pressure data in a normal state, and the detection hydraulic system is highly likely to be in an abnormal operation state in a case where the variation curve is not in agreement with the historical variation curve.
Here, for the change curve and the historical change curve, it is not necessarily required that the pressure data at each time point are completely consistent, and the change trends indicated by both are considered to be consistent as long as the overall change trend is consistent.
The method for detecting the abnormality of the hydraulic system comprises the steps of determining pressure data of the hydraulic system to be detected in each acquisition time in the working time period, and dividing a plurality of pressure data of which the acquisition times are in the same preset time interval into the same data group; for each data group, determining the standard deviation of the pressure of the data group based on a plurality of pressure data of the data group after abnormal pressure data are filtered; determining a plurality of target data based on the plurality of determined pressure standard deviations and a preset standard deviation range; determining a change curve of the pressure data along with the change of time according to the plurality of target data; and when the variation curve is detected to be inconsistent with the variation trend of the historical variation curve of the hydraulic system to be detected, determining that the hydraulic system to be detected is abnormal.
Therefore, by determining the pressure data of each acquisition time of the hydraulic system to be detected in the working time period and according to the acquisition time of each pressure data, a plurality of data groups are determined, the pressure standard deviation of each data group is calculated, target data are determined from the plurality of pressure data according to the plurality of pressure standard deviations and the preset standard deviation range, the change curve of the pressure data along with the change of time is determined according to the plurality of target data without interference data, and when the change trend of the change curve is inconsistent with the change trend of the historical change curve, the abnormality of the hydraulic system to be detected is determined, the influence of the interference data on the judgment result can be eliminated, and the detection accuracy of the hydraulic system is improved.
Referring to fig. 3, fig. 3 is a flowchart illustrating a method for detecting an abnormality of a hydraulic system according to another embodiment of the present disclosure. As shown in fig. 3, the method for detecting an abnormality of a hydraulic system according to the embodiment of the present application includes:
And step 303, determining at least one data group with the pressure standard deviation within the preset standard deviation range as a target data group.
In the step, at least one data set with the pressure standard deviation within a preset standard deviation range is determined as a target data set according to the pressure standard deviation of each data set.
Here, the pressure standard deviation is not data in the data group within the preset standard deviation range, is interference data that does not meet the subsequent calculation standard, and needs to be filtered, and these pressure data will not be considered in the subsequent calculation process of the pressure data.
In this step, the pressure data included in each of the plurality of target data sets determined in step 303 is determined as candidate data.
Here, when determining the candidate data, the pressure data of each target data group is directly collected together for subsequent data screening and calculation, and the calculation is not distinguished according to the data group.
In this step, after the plurality of candidate data determined in step 304, further interference filtering needs to be performed on the data, and after abnormal candidate data in the plurality of candidate data is filtered, the remaining candidate data will be used as target data of the candidate determination change curve.
Here, when filtering the abnormal candidate data, the zero phase shift filtering may be performed by using a butterworth filter to obtain target data without distortion.
And step 306, determining a change curve of the pressure data along with the change of time according to the plurality of target data.
And 307, determining that the hydraulic system to be detected is abnormal when the variation curve is detected to be inconsistent with the variation trend of the historical variation curve of the hydraulic system to be detected.
The descriptions of step 301, step 302, step 306, and step 307 may refer to the descriptions of step 201, step 202, step 204, and step 205, and the same technical effect can be achieved, which is not described in detail herein.
Further, before step 302, the method further includes: for each data group, arranging a plurality of pressure data in the data group according to a sequence from small to large, and determining minimum pressure data and maximum pressure data in the plurality of pressure data; determining a first data difference between the minimum pressure data and a first pressure data of a neighboring rank, and a second data difference between the maximum pressure data and a second pressure data of a neighboring rank; when the first data difference and/or the second data difference are/is detected to be larger than a preset difference threshold value, determining the minimum pressure data and/or the maximum pressure data as abnormal pressure data; the determined at least one abnormal pressure data is filtered from the data set.
In the step, aiming at each data group, arranging all pressure data in the data group according to a sequence from small to large, determining minimum pressure data and maximum pressure data in a plurality of pressure data, determining a first data difference between the minimum pressure data and first pressure data adjacent to the minimum pressure data, and simultaneously determining a second data difference between the maximum pressure data and second pressure data adjacent to the maximum pressure data; when the first data difference is detected to be larger than a preset difference threshold value, determining the minimum pressure data as abnormal pressure data, and when the second data difference is detected to be larger than a preset difference threshold value, determining the maximum pressure data as abnormal pressure data; after determining the abnormal pressure data, the abnormal pressure data is filtered from the data set.
The pressure data are divided and then subjected to preliminary data filtering, obvious abnormal pressure data are filtered, the direct sequencing is adopted in an intuitive mode, whether the data difference between the pressure data at the two ends of the sequencing sequence and other pressure data is too large is detected, if the data difference is too large, the pressure data and other pressure data are shown to be too large, the pressure data are abnormal pressure data, and the pressure data need to be directly filtered.
Here, in addition to calculating the numerical values at both ends in the sorted sequence, a data difference between every two adjacent pressure data in the sequence may also be calculated, two data differences corresponding to each pressure data are determined, and when it is detected that both the two data differences corresponding to the same pressure data are greater than a preset difference threshold, the pressure data is determined to be abnormal pressure data, and then the abnormal pressure data is filtered.
Here, when the hydraulic system normally works, the acquired pressure data is changed steadily, the change range is also within the preset fluctuation range, when the pressure data difference corresponding to the pressure data is too large, the pressure data is indicated to be suddenly changed, when the pressure data is acquired, deviation is likely to occur in the data acquisition, transmission and processing processes, and the pressure data is inaccurate and needs to be filtered.
Further, the target data is determined by: acquiring a preset pressure threshold; determining candidate data which is larger than the preset pressure threshold value in the plurality of candidate data as abnormal candidate data; and determining the plurality of candidate data left after the determined at least one abnormal candidate data is filtered from the plurality of candidate data as target data.
In the step, a preset pressure threshold is obtained, candidate data which are larger than the preset pressure threshold in the plurality of candidate data are determined as abnormal candidate data, at least one abnormal candidate data are determined, and after all abnormal candidate data are removed, the remaining candidate data are required non-interference target data.
The preset pressure threshold is determined according to historical working data of the hydraulic system to be detected, abnormal pressure data in the historical working process are counted, the minimum abnormal pressure data are determined, and when the pressure data larger than the abnormal pressure data, the pressure data can be regarded as abnormal pressure data.
The definition of the preset pressure threshold value is different due to the difference of the working environment and the working parameters of each mechanical device.
Further, the variation trend of the variation curve is determined to be inconsistent with the variation trend of the historical variation curve of the hydraulic system to be detected through the following steps: determining the slope of the curve corresponding to the change curve at a target time and the slope of the historical curve corresponding to the historical change curve at the target time; detecting whether the slope of the curve is equal to the slope of the historical curve; and if the slope of the curve is not equal to that of the historical curve, determining that the change trend of the change curve is inconsistent with that of the historical change curve of the hydraulic system to be detected.
In the step, the slope of the curve, also called the era and the derivative, may be determined by the slope of a tangent at a certain point on the curve, determining the slope of a tangent at a curve point corresponding to the target time, and determining the slope of a historical tangent at a curve point corresponding to the target time, and when the slope of a tangent is not consistent with the slope of a historical tangent, determining that the change curves and the historical change curves show different pressure data change trends with the passage of time.
Here, the target time may be one or a plurality of target times, and when the change curve is not a monotone change trend of monotone increase or monotone decrease, it is necessary to determine whether the slope of the change curve in each monotone self-interval is consistent with the slope of the history change curve through the plurality of target times, so that the change trend of the curve can be determined more accurately.
The method for detecting the abnormality of the hydraulic system comprises the steps of determining pressure data of the hydraulic system to be detected in each acquisition time in the working time period, and dividing a plurality of pressure data of which the acquisition times are in the same preset time interval into the same data group; for each data group, determining the standard deviation of the pressure of the data group based on a plurality of pressure data of the data group after abnormal pressure data are filtered; determining the pressure standard deviation as a target data set, wherein the pressure standard deviation belongs to at least one data set within the preset standard deviation range; determining pressure data included in each target data group as candidate data; filtering abnormal candidate data in the determined plurality of candidate data to determine a plurality of target data; determining a change curve of the pressure data along with the change of time according to the plurality of target data; and when the variation curve is detected to be inconsistent with the variation trend of the historical variation curve of the hydraulic system to be detected, determining that the hydraulic system to be detected is abnormal.
Therefore, by determining the pressure data of each acquisition time of the hydraulic system to be detected in the working time period and according to the acquisition time of each pressure data, a plurality of data groups are determined, the pressure standard deviation of each data group is calculated, target data are determined from the plurality of pressure data according to the plurality of pressure standard deviations and the preset standard deviation range, the change curve of the pressure data along with the change of time is determined according to the plurality of target data without interference data, and when the change trend of the change curve is inconsistent with the change trend of the historical change curve, the abnormality of the hydraulic system to be detected is determined, the influence of the interference data on the judgment result can be eliminated, and the detection accuracy of the hydraulic system is improved.
Referring to fig. 4 and 5, fig. 4 is a first schematic structural diagram of a hydraulic system abnormality detection device according to an embodiment of the present disclosure, and fig. 5 is a second schematic structural diagram of a hydraulic system abnormality detection device according to an embodiment of the present disclosure. As shown in fig. 4, the detection apparatus 400 includes:
the first determining module 410 is configured to determine pressure data of the hydraulic system to be detected at each acquisition time in the working time period, and divide a plurality of pressure data of which the acquisition times are within the same preset time interval into the same data group.
The second determining module 420 is configured to determine, for each data set, a standard deviation of pressure of the data set based on the plurality of pressure data of the data set from which the abnormal pressure data is filtered.
A third determining module 430, configured to determine a plurality of target data based on the determined plurality of pressure standard deviations and the preset standard deviation range.
A fourth determining module 440, configured to determine a variation curve of the pressure data over time according to the plurality of target data.
A fifth determining module 450, configured to determine that the hydraulic system to be detected is abnormal when it is detected that the variation curve is inconsistent with the variation trend of the historical variation curve of the hydraulic system to be detected.
Further, as shown in fig. 5, the detection apparatus 400 further includes a data filtering module 460, where the data filtering module 460 is configured to:
for each data group, arranging a plurality of pressure data in the data group according to a sequence from small to large, and determining minimum pressure data and maximum pressure data in the plurality of pressure data;
determining a first data difference between the minimum pressure data and a first pressure data of a neighboring rank, and a second data difference between the maximum pressure data and a second pressure data of a neighboring rank;
when the first data difference and/or the second data difference are/is detected to be larger than a preset difference threshold value, determining the minimum pressure data and/or the maximum pressure data as abnormal pressure data;
the determined at least one abnormal pressure data is filtered from the data set.
Further, when the third determining module 430 is configured to determine a plurality of target data based on the determined plurality of pressure standard deviations and the preset standard deviation range, the third determining module 430 is configured to:
determining the pressure standard deviation as a target data set, wherein the pressure standard deviation belongs to at least one data set within the preset standard deviation range;
determining pressure data included in each target data group as candidate data;
and filtering abnormal candidate data in the plurality of determined candidate data to determine a plurality of target data.
Further, the third determining module 430 is configured to determine the target data by:
acquiring a preset pressure threshold;
determining candidate data which is larger than the preset pressure threshold value in the plurality of candidate data as abnormal candidate data;
and determining the plurality of candidate data left after the determined at least one abnormal candidate data is filtered from the plurality of candidate data as target data.
Further, the fifth determining module 450 is configured to determine that the variation curve is inconsistent with the variation trend of the historical variation curve of the hydraulic system to be detected by:
determining the slope of the curve corresponding to the change curve at a target time and the slope of the historical curve corresponding to the historical change curve at the target time;
detecting whether the slope of the curve is equal to the slope of the historical curve;
and if the slope of the curve is not equal to that of the historical curve, determining that the change trend of the change curve is inconsistent with that of the historical change curve of the hydraulic system to be detected.
The detection device provided by the embodiment of the application determines pressure data of each acquisition time of the hydraulic system to be detected in the working time period, and divides a plurality of pressure data of which the acquisition times are in the same preset time interval into the same data group; for each data group, determining the standard deviation of the pressure of the data group based on a plurality of pressure data of the data group after abnormal pressure data are filtered; determining a plurality of target data based on the plurality of determined pressure standard deviations and a preset standard deviation range; determining a change curve of the pressure data along with the change of time according to the plurality of target data; and when the variation curve is detected to be inconsistent with the variation trend of the historical variation curve of the hydraulic system to be detected, determining that the hydraulic system to be detected is abnormal.
Therefore, by determining the pressure data of each acquisition time of the hydraulic system to be detected in the working time period and according to the acquisition time of each pressure data, a plurality of data groups are determined, the pressure standard deviation of each data group is calculated, target data are determined from the plurality of pressure data according to the plurality of pressure standard deviations and the preset standard deviation range, the change curve of the pressure data along with the change of time is determined according to the plurality of target data without interference data, and when the change trend of the change curve is inconsistent with the change trend of the historical change curve, the abnormality of the hydraulic system to be detected is determined, the influence of the interference data on the judgment result can be eliminated, and the detection accuracy of the hydraulic system is improved.
Referring to fig. 6, fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure. As shown in fig. 6, the electronic device 600 includes a processor 610, a memory 620, and a bus 630.
The memory 620 stores machine-readable instructions executable by the processor 610, when the electronic device 600 runs, the processor 610 communicates with the memory 620 through the bus 630, and when the machine-readable instructions are executed by the processor 610, the steps of the method for detecting the hydraulic system abnormality in the method embodiment shown in fig. 2 and fig. 3 may be executed.
An embodiment of the present application further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method for detecting an abnormality of a hydraulic system in the method embodiments shown in fig. 2 and fig. 3 may be executed.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer-readable storage medium executable by a processor. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present application, and are used for illustrating the technical solutions of the present application, but not limiting the same, and the scope of the present application is not limited thereto, and although the present application is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope disclosed in the present application; such modifications, changes or substitutions do not depart from the spirit and scope of the exemplary embodiments of the present application, and are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. A method of detecting an abnormality in a hydraulic system, the method comprising:
determining pressure data of each acquisition time of the hydraulic system to be detected in the working time period, and dividing a plurality of pressure data of which the acquisition time is in the same preset time interval into the same data group;
for each data group, determining the standard deviation of the pressure of the data group based on a plurality of pressure data of the data group after abnormal pressure data are filtered;
determining a plurality of target data based on the plurality of determined pressure standard deviations and a preset standard deviation range;
determining a change curve of the pressure data along with the change of time according to the plurality of target data;
and when the variation curve is detected to be inconsistent with the variation trend of the historical variation curve of the hydraulic system to be detected, determining that the hydraulic system to be detected is abnormal.
2. The method of claim 1, wherein before determining, for each data set, a standard deviation of pressure for the data set based on the plurality of pressure data of the data set from which abnormal pressure data has been filtered, the method further comprises:
for each data group, arranging a plurality of pressure data in the data group according to a sequence from small to large, and determining minimum pressure data and maximum pressure data in the plurality of pressure data;
determining a first data difference between the minimum pressure data and a first pressure data of a neighboring rank, and a second data difference between the maximum pressure data and a second pressure data of a neighboring rank;
when the first data difference is detected to be larger than a preset difference threshold value, determining the minimum pressure data as abnormal pressure data, or when the second data difference is detected to be larger than a preset difference threshold value, determining the maximum pressure data as abnormal pressure data, or when the first data difference and the second data difference are detected to be larger than a preset difference threshold value, determining the minimum pressure data and the maximum pressure data as abnormal pressure data;
the determined at least one abnormal pressure data is filtered from the data set.
3. The method according to claim 1, wherein the determining a plurality of target data based on the determined plurality of pressure standard deviations and a preset standard deviation range comprises:
determining the pressure standard deviation as a target data set, wherein the pressure standard deviation belongs to at least one data set within the preset standard deviation range;
determining pressure data included in each target data group as candidate data;
and filtering abnormal candidate data in the plurality of determined candidate data to determine a plurality of target data.
4. The detection method according to claim 3, wherein the target data is determined by:
acquiring a preset pressure threshold;
determining candidate data which is larger than the preset pressure threshold value in the plurality of candidate data as abnormal candidate data;
and determining the plurality of candidate data left after the determined at least one abnormal candidate data is filtered from the plurality of candidate data as target data.
5. The detection method according to claim 1, characterized in that the variation curve is determined to be inconsistent with the variation trend of the historical variation curve of the hydraulic system to be detected by the following steps:
determining the slope of the curve corresponding to the change curve at a target time and the slope of the historical curve corresponding to the historical change curve at the target time;
detecting whether the slope of the curve is equal to the slope of the historical curve;
and if the slope of the curve is not equal to that of the historical curve, determining that the change trend of the change curve is inconsistent with that of the historical change curve of the hydraulic system to be detected.
6. A hydraulic system abnormality detection apparatus, characterized by comprising:
the first determining module is used for determining pressure data of each acquisition time of the hydraulic system to be detected in the working time period and dividing a plurality of pressure data of which the acquisition time is in the same preset time interval into the same data group;
the second determining module is used for determining the standard deviation of the pressure of each data group based on the plurality of pressure data of the data group after abnormal pressure data are filtered out;
the third determining module is used for determining a plurality of target data based on the plurality of determined pressure standard deviations and the preset standard deviation range;
the fourth determining module is used for determining a change curve of the pressure data along with the change of time according to the plurality of target data;
and the fifth determining module is used for determining that the hydraulic system to be detected is abnormal when the variation curve is detected to be inconsistent with the variation trend of the historical variation curve of the hydraulic system to be detected.
7. The detection apparatus according to claim 6, further comprising a data filtering module, wherein the data filtering module is configured to:
for each data group, arranging a plurality of pressure data in the data group according to a sequence from small to large, and determining minimum pressure data and maximum pressure data in the plurality of pressure data;
determining a first data difference between the minimum pressure data and a first pressure data of a neighboring rank, and a second data difference between the maximum pressure data and a second pressure data of a neighboring rank;
when the first data difference is detected to be larger than a preset difference threshold value, determining the minimum pressure data as abnormal pressure data, or when the second data difference is detected to be larger than a preset difference threshold value, determining the maximum pressure data as abnormal pressure data, or when the first data difference and the second data difference are detected to be larger than a preset difference threshold value, determining the minimum pressure data and the maximum pressure data as abnormal pressure data;
the determined at least one abnormal pressure data is filtered from the data set.
8. The detecting device according to claim 6, wherein the third determining module, when configured to determine a plurality of target data based on the plurality of determined pressure standard deviations and a preset standard deviation range, is configured to:
determining the pressure standard deviation as a target data set, wherein the pressure standard deviation belongs to at least one data set within the preset standard deviation range;
determining pressure data included in each target data group as candidate data;
and filtering abnormal candidate data in the plurality of determined candidate data to determine a plurality of target data.
9. An electronic device, comprising: a processor, a memory and a bus, the memory storing machine-readable instructions executable by the processor, the processor and the memory communicating over the bus when an electronic device is running, the machine-readable instructions when executed by the processor performing the steps of the method of detecting hydraulic system anomalies according to any one of claims 1 to 5.
10. A computer-readable storage medium, characterized in that a computer program is stored thereon, which, when being executed by a processor, carries out the steps of the method of detection of an abnormality of a hydraulic system according to any one of claims 1 to 5.
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| CN112507151B (en) * | 2020-11-23 | 2023-02-03 | 首钢京唐钢铁联合有限责任公司 | Pressure data processing method, device, equipment and medium |
| CN112963406B (en) * | 2021-03-31 | 2023-06-02 | 上海电气集团股份有限公司 | Monitoring method, device and system of hydraulic system and storage medium |
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| CN115144113B (en) * | 2022-06-28 | 2024-06-14 | 中国第一汽车股份有限公司 | Clutch pressure fluctuation detection method and device and electronic equipment |
| CN117464997A (en) * | 2022-07-21 | 2024-01-30 | 深圳市创想三维科技股份有限公司 | Height data determining method, apparatus, computer device and storage medium |
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