CN111272256A - Data processing method and device for oil level abnormity monitoring - Google Patents
Data processing method and device for oil level abnormity monitoring Download PDFInfo
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Abstract
The application discloses a data processing method and device for oil level abnormity monitoring, electronic equipment and a readable storage medium. The method comprises the following steps: collecting mechanical state information and an oil level data group, wherein the oil level data group comprises an oil level value and sampling time; determining an oil level change slope according to the oil level data set to obtain an oil level change sequence; extracting oil level variation characteristics according to the oil level variation sequence; and monitoring whether the oil level is abnormal or not according to the oil level change characteristic and the mechanical state information. The method solves the technical problems that the oil level abnormity monitoring method in the related art is greatly influenced by environmental conditions, so that the accuracy of the monitoring result is not high, and the oil level abnormity condition is easily reported in a false mode or is not reported. By the aid of the method and the device, the purpose of timely and accurately detecting the abnormal conditions of the oil levels of various mechanical vehicles under different working conditions is achieved, and therefore the technical effect of avoiding the abnormal conditions of false alarm or missing alarm of the oil levels is achieved.
Description
Technical Field
The application relates to the technical field of engineering machinery oil level monitoring, in particular to a data processing method and device for oil level abnormity monitoring, electronic equipment and a readable storage medium.
Background
Oil level measurement and monitoring is one of the important areas in the field of detection and control. Because the price of fuel oil in the current market is higher, the phenomenon of oil stealing of individual personnel for privately discharging oil from the oil tank due to greediness sometimes happens, and particularly the phenomenon of oil stealing is more frequent in the current engineering field.
The inventors have found that the oil level abnormality monitoring method in the related art has at least the following problems: 1) the oil level abnormality detection method is generally used for detecting the abnormal fluctuation of the oil level of a stationary fixed container, and is not accurate in detecting the abnormal fluctuation of the oil level of a movable vehicle and other machines, because the oil in the container can fluctuate violently when the vehicle and other machines move, and false alarm are easily caused. 2) The real-time effect is poor, and sometimes more data need to be sampled to judge that the oil level is abnormal, so that the monitoring delay is caused. 3) Generally, only the data of the oil quantity is collected, only the monotonous rapid reduction of the oil level is detected, and the accuracy of the detection result is not high.
Aiming at the technical problems that the accuracy of a monitoring result is not high and false alarm or abnormal oil level condition is easily reported in a large way due to the influence of environmental conditions in an oil level abnormal monitoring method in the related art, an effective solution is not provided at present.
Disclosure of Invention
The application mainly aims to provide a data processing method and device for oil level abnormity monitoring, electronic equipment and a readable storage medium, so as to solve the technical problems that in the related art, due to the fact that an oil level abnormity monitoring method is greatly influenced by environmental conditions, the accuracy of a monitoring result is not high, and false alarm or oil level abnormity is easily reported in a missing mode.
In order to achieve the above object, according to a first aspect of the present application, there is provided a data processing method for oil level abnormality monitoring.
The data processing method for oil level abnormality monitoring according to the application comprises the following steps: collecting mechanical state information and an oil level data group, wherein the oil level data group comprises an oil level value and sampling time; determining an oil level change slope according to the oil level data set to obtain an oil level change sequence; extracting oil level variation characteristics according to the oil level variation sequence; and monitoring whether the oil level is abnormal or not according to the oil level change characteristic and the mechanical state information.
Further, the determining an oil level change slope from the oil level data set to obtain an oil level change sequence includes: determining the sampling number N of the oil level change slopes and a preset oil level change threshold according to the mechanical state information, and sequencing the N oil level change slopes according to time, wherein N is not less than 1; comparing the N oil level change slopes with the preset oil level change threshold respectively to obtain the oil level abrupt change sequence and the oil level slowly-changing sequence; and determining the oil level change characteristic according to the oil level abrupt change sequence, the oil level gradual change sequence and the sampling number N of the oil level change slope.
Further, the oil level change sequence comprises an oil level abrupt change sequence and an oil level gradual change sequence, and the extracting of the oil level change characteristics according to the oil level change sequence comprises: determining an oil level ascending characteristic and/or an oil level slowly descending characteristic judgment sequence according to the oil level abrupt change sequence, the oil level slowly changing sequence and the sampling number of the oil level change slope; according to the mechanical state information, carrying out weighted summation processing on the oil level rising characteristic and/or oil level slow-falling characteristic judgment sequence; and judging whether the first oil level change characteristic value obtained after the summation processing meets a first preset condition or not, so as to determine an oil level rising characteristic and/or an oil level slow-falling characteristic according to the judgment result.
Further, the oil level change sequence includes an oil level abrupt change sequence, and the extracting of the oil level change characteristic according to the oil level change sequence includes: determining an oil level sudden drop characteristic judgment sequence according to the oil level sudden change sequence and the sampling number of the oil level change slope; according to the mechanical state information, carrying out weighted summation processing on the oil level sudden drop characteristic judgment sequence; and judging whether the second oil level change characteristic value obtained after the summation processing meets a second preset condition or not so as to determine the oil level sudden-drop characteristic according to the judgment result.
Further, the collecting the oil level data set previously comprises: judging whether an oil level abnormity monitoring instruction is received or not; and if so, entering the step of collecting the mechanical state information and the oil level data set.
Further, the mechanical state information includes any one or more of a normal operating state, a refueling state, an uncovering state, an abnormal state, a defense deploying state, an oil stealing state and a suspected oil stealing state, and the monitoring whether the oil level abnormality occurs according to the oil level change characteristic and the mechanical state information includes: determining a first mechanical state; and determining whether to switch the first mechanical state or not according to the monitoring result so as to obtain a second mechanical state.
In order to achieve the above object, according to a second aspect of the present application, there is provided a data processing device for oil level abnormality monitoring.
The data processing device for oil level abnormality monitoring according to the present application includes: the oil level data set comprises an oil level value and sampling time; the first determination module is used for determining an oil level change slope according to the oil level data group so as to obtain an oil level change sequence; the extraction module is used for extracting oil level change characteristics according to the oil level change sequence; and the monitoring module is used for monitoring whether the oil level is abnormal or not according to the oil level change characteristics and the mechanical state information.
Further, the oil level change slope includes a plurality of slopes, and the first determination module includes: the first determining unit is used for determining the sampling number N of the oil level change slopes and a preset oil level change threshold according to the mechanical state information, and sequencing the N oil level change slopes according to time, wherein N is not less than 1; the comparison unit is used for comparing the N oil level change slopes with the preset oil level change threshold respectively to obtain the oil level abrupt change sequence and the oil level gradual change sequence; and the second determination unit is used for determining the oil level change characteristic according to the oil level abrupt change sequence, the oil level gradual change sequence and the sampling number N of the oil level change slope.
In order to achieve the above object, according to a third aspect of the present application, there is provided an electronic apparatus comprising: one or more processors; storage means for storing one or more programs; the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method as previously described.
In order to achieve the above object, according to a fourth aspect of the present application, there is provided a non-transitory readable storage medium having stored thereon computer instructions which, when executed by a processor, implement the steps of the method as described above.
In the embodiment of the application, mechanical state information and an oil level data group are collected, wherein the oil level data group comprises an oil level value and sampling time; determining an oil level change slope according to the oil level data set to obtain an oil level change sequence; according to the mode of extracting the oil level change characteristics according to the oil level change sequence, whether the oil level is abnormal or not is monitored according to the oil level change characteristics and the mechanical state information, the purpose of accurately monitoring the abnormal condition of the oil level under different working conditions is achieved, the technical effect of avoiding the abnormal condition of the oil level from being misreported or being misreported is achieved, and the technical problems that the accuracy of a monitoring result is low and the abnormal condition of the oil level is easily misreported or being misreported due to the fact that the oil level abnormal monitoring method in the related technology is greatly influenced by the environmental working conditions are solved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, serve to provide a further understanding of the application and to enable other features, objects, and advantages of the application to be more apparent. The drawings and their description illustrate the embodiments of the invention and do not limit it. In the drawings:
FIG. 1 is a schematic flow diagram of a data processing method for oil level anomaly monitoring according to a first embodiment of the present application;
FIG. 2 is a schematic flow chart diagram of a data processing method for oil level anomaly monitoring according to a second embodiment of the present application;
FIG. 3 is a schematic flow chart diagram of a data processing method for oil level anomaly monitoring according to a third embodiment of the present application;
FIG. 4 is a schematic flow chart diagram of a data processing method for oil level anomaly monitoring according to a fourth embodiment of the present application;
FIG. 5 is a schematic flow chart diagram of a data processing method for oil level anomaly monitoring according to a fifth embodiment of the present application;
FIG. 6 is a schematic flow chart diagram of a data processing method for oil level anomaly monitoring according to a sixth embodiment of the present application;
FIG. 7 is a schematic illustration of mechanical oil level state switching according to an embodiment of the present application;
FIG. 8 is a schematic diagram of the component structure of a data processing device for oil level abnormality monitoring according to an embodiment of the present application; and
fig. 9 is a schematic diagram of a composition structure of an electronic device according to an embodiment of the present application.
Detailed Description
In order to make the technical solutions better understood by those skilled in the art, 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 partial embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It should be understood that the data so used may be interchanged under appropriate circumstances such that embodiments of the application described herein may be used. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
According to an embodiment of the present invention, there is provided a data processing method for oil level abnormality monitoring, as shown in fig. 1, the method including steps S101 to S104 as follows:
step S101, collecting mechanical state information and an oil level data set, wherein the oil level data set comprises an oil level value and sampling time.
In specific implementation, the mechanical state information may be collected through an acceleration sensor, the oil level data may be collected through a pressure sensor in the oil tank, the above-mentioned collection process may be performed according to a certain time interval, the time interval may be an equal time interval or an unequal time interval, and a person skilled in the art can flexibly set the specific sampling interval according to actual conditions, and is not specifically limited herein. The plurality of oil level data sampled at regular time intervals form an oil level data set, which includes specific oil level values and corresponding sampling times.
And step S102, determining an oil level change slope according to the oil level data group to obtain an oil level change sequence.
In specific implementation, the oil level change slope k may be determined according to the oil level value X2 obtained by the current sampling and the corresponding sampling time T2, and the oil level value X1 obtained by the last sampling and the corresponding sampling time T1, and specifically calculated according to the following formula:
because a plurality of oil level data are obtained by continuous sampling and the like at certain time intervals, a plurality of oil level change slopes can be correspondingly obtained, and an oil level change sequence can be obtained by comparing each of the plurality of oil level change slopes with a preset oil level characteristic change threshold value.
And step S103, extracting oil level change characteristics according to the oil level change sequence.
In specific implementation, the oil level change sequence reflects the relationship between the oil level change slope and a preset threshold value in a period of time, if the oil level change slope exceeds the preset threshold value, it indicates that the oil level may be abnormal, and if the oil level decrease slope does not exceed the preset threshold value, it indicates that the oil level may not be abnormal, so that the oil level change characteristics can be extracted according to the oil level change sequence as one of the conditions for monitoring and determining whether the oil level is abnormal.
And step S104, monitoring whether oil level abnormity occurs according to the oil level change characteristics and the mechanical state information.
In particular, the abnormality determination conditions of the machine in different states should be different, so after the oil level variation characteristic is obtained, it is necessary to combine the oil level variation characteristic with the current state information of the machine to determine whether the oil level is abnormal. For example, the oil level variation threshold for a machine in motion is clearly different from the oil level variation threshold for a machine in rest. Through the process, the accuracy and the timeliness of oil level monitoring are realized, and especially when the oil level monitoring system is applied to oil tank oil quantity management of mechanical vehicles under different working conditions, the occurrence of oil level abnormal conditions such as oil stealing and oil leakage can be effectively monitored.
As a preferred implementation of the embodiment of the present application, as shown in fig. 2, the determining the oil level change slope according to the oil level data set to obtain the oil level change sequence includes steps S201 to S203 as follows:
step S201, determining the sampling number N of the oil level change slopes and a preset oil level change threshold according to the mechanical state information, and sorting the N oil level change slopes according to time, where N is not less than 1.
In specific implementation, the sampling number N of the oil level change slopes and the corresponding oil level change threshold required in different mechanical states are different, for example, when the machine is in a arming or disarming state, N may take different values, N1 and N2, that is, different sampling numbers or sampling frequencies may be set according to different states of the machine, so as to obtain different numbers of oil level change slopes, and meet the oil level abnormal data monitoring requirements in different states. Therefore, the embodiment of the application firstly needs to determine the sampling number of the oil level change slope and the oil level change threshold according to the current state information of the machine. When an oil level change sequence is determined, N oil level change slopes stored within a period of time need to be sorted according to the generation time of the slopes, an oil level change slope queue formed by the N oil level change slopes is dynamically changed in real time, and when a new k value is generated, the earliest k value is deleted and shifted.
Step S202, comparing the N oil level change slopes with the preset oil level change threshold respectively, so as to obtain the oil level abrupt change sequence and the oil level gradual change sequence.
In specific implementation, the preset oil level variation threshold according to the embodiment of the present application may include a preset oil level abrupt change threshold H1 and a preset oil level gradual change threshold H2, and the oil level variation sequence may include an oil level abrupt change sequence and an oil level gradual change sequence, and the N oil level variation slopes k obtained by applying the above-mentioned method are used to determine the oil level variation slope1～KNRespectively, with a preset oil level mutation threshold value H1, and then an oil level mutation sequence F can be obtained1～FNBy changing the above-obtained N oil level change slopes k1～KNAre respectively compared with preset oil level slowly-changing threshold value H2, so that oil level slowly-changing sequence D can be obtained1～DN. The sizes of the preset oil level abrupt change threshold H1 and the preset oil level gradual change threshold H2 can be flexibly set by those skilled in the art according to actual situations, and are not particularly limited herein. Specifically, the oil level mutation sequence F1～FNCan be determined according to the following formula:
a) if k isi>H1, then Fi＝1
b) If k isi>H1/2, then Fi＝0.5
c) If k isi<-H1, then Fi＝-1
d) If k isi<H1/2, then Fi＝-0.5，
Wherein k isiRepresents k1～KN(ii) any one of oil level change slopes, FiRepresents and kiMutation of sequence F at oil level1～FNThe value of (1).
Oil level slowly-varying sequence D1～DNCan be determined according to the following formula:
a) if k isi>H2, then Di＝1
b) If k isi>H2/2, then Di＝0.5
c) If k isi<-H2, then Di＝-1
d) If k isi<H2/2, then Di＝-0.5，
Wherein k isiRepresents k1～KNAny one of the oil level change slopes, DiRepresents and kiIn the oil level slowly changing sequence D1～DNThe value of (1).
Step S203, determining the oil level change characteristic according to the oil level abrupt change sequence, the oil level gradual change sequence and the sampling number N of the oil level change slope.
In specific implementation, after the oil level abrupt change sequence and the oil level gradual change sequence are obtained, the final oil level change characteristic is determined according to the oil level abrupt change sequence, the oil level gradual change sequence and the sampling number N of the oil level descending slope.
As a preferred implementation of the embodiment of the present application, as shown in fig. 3, the oil level change sequence includes an oil level abrupt change sequence and an oil level gradual change sequence, and the extracting of the oil level change characteristic according to the oil level change sequence includes steps S301 to S303 as follows:
step S301, determining an oil level ascending characteristic and/or an oil level slowly descending characteristic judgment sequence according to the oil level abrupt change sequence, the oil level slowly changing sequence and the sampling number of the oil level change slope.
In specific implementation, the oil level change sequence comprises an oil level mutation sequence FiAnd oil level slowly-varying sequence DiMutation of sequence F according to oil leveliAnd oil level slowly-varying sequence DiAnd the sampling number N of the change slope of the oil level can be determinedSequence G for determining rising or falling characteristics of oil leveliSpecifically, the following formula can be used to determine:
Gi＝Di+Fix N, wherein i is more than or equal to 1 and less than or equal to N.
Step S302, according to the mechanical state information, carrying out weighted summation processing on the oil level rising characteristic and/or oil level slow-falling characteristic judgment sequence.
In specific implementation, different weighting is performed on different mechanical states, specifically, weighting and summing processing is performed on the oil level rising characteristic and/or the oil level slow-falling characteristic judgment sequence according to the following rules:
a) will sequence GiIs added to obtain SGall；
b) Will sequence GiRemoving the first and last elements, adding the rest N-2 elements to obtain SGmid。
Step S303, determining whether the first oil level change characteristic value obtained after the summation process meets a first preset condition, so as to determine an oil level rising characteristic and/or an oil level slow-falling characteristic according to the determination result.
In specific implementation, when the following two conditions are simultaneously satisfied, the oil level rise characteristic is determined as follows:
a)SGmid≥N-1
b)SGall≥N；
when the following two conditions are simultaneously met, the oil level slow-falling characteristic is judged:
a)SGmid≤-(N-1)
b)SGall≤-N。
as a preferred implementation of the embodiment of the present application, as shown in fig. 4, the oil level variation sequence includes an oil level abrupt change sequence, and the extracting of the oil level variation characteristic according to the oil level variation sequence includes steps S401 to S403 as follows:
step S401, determining an oil level sudden drop characteristic judgment sequence according to the oil level sudden change sequence and the sampling number of the oil level change slope.
In particular embodiments, the oil level variation sequence comprises an oil level bump sequenceColumn FiMutation of sequence F according to oil leveliAnd the sampling number N of the oil level change slope can determine the oil level dip characteristic judgment sequence.
Step S402, according to the mechanical state information, carrying out weighted summation processing on the oil level sudden drop characteristic judgment sequence.
In specific implementation, different weighting is performed on different mechanical states, specifically, the oil level sudden drop characteristic determination sequence is subjected to weighted summation processing according to the following rule:
a) will sequence FiIs added to obtain SFall；
b) Will sequence FiRemoving the first and last ones, and adding the rest N-2 elements to obtain SFmid。
In step S403, it is determined whether the second oil level variation characteristic value obtained after the summation process satisfies a second preset condition, so as to determine an oil level dip characteristic according to the determination result.
In specific implementation, when the following two conditions are simultaneously satisfied, the characteristic of sudden drop of the oil level is judged:
a)SFmid≤-1
b)SFall≤-1。
alternatively, when the oil level variation characteristic does not belong to any one of the oil level raising characteristic, the oil level slow-falling characteristic, and the oil level sudden-falling characteristic, it is determined that there is no variation characteristic in the oil level.
As a preferred implementation manner of the embodiment of the present application, as shown in fig. 5, the acquiring oil level data set includes the following steps S501 to S502:
in step S501, it is determined whether an oil level abnormality monitoring instruction is received.
In specific implementation, before collecting oil level data, the method further comprises a step of acquiring a motion state of the machine, specifically, a continuous time domain signal of triaxial acceleration data of the machine can be collected through a triaxial sensor, the collected continuous time domain signal is divided according to time periods, and then one or more time domain signal segments are obtained, so that the current state of the machine, including a working state or a static state, is judged according to at least one time domain signal segment. When the machine is in a static state, the machine state monitoring end sends the monitoring indication of the abnormal oil level state to continuously monitor the oil level, so that whether the abnormal oil level monitoring indication can be received or not needs to be judged firstly.
And step S502, if the oil level data is received, the step of collecting the mechanical state information and the oil level data set is carried out.
In specific implementation, if the oil level abnormity monitoring indication sent by the mechanical state monitoring end can be received within a certain time period, the oil level data is collected.
As a preferred implementation manner of the embodiment of the present application, as shown in fig. 6, the mechanical state information includes any one or more of a normal operating state, a refueling state, an uncapping state, an abnormal state, a defense state, an oil stealing state, and a suspected oil stealing state, and the monitoring whether an oil level abnormality occurs according to the oil level variation characteristic and the mechanical state information includes steps S601 to S602 as follows:
in step S601, a first mechanical state is determined.
In a specific implementation, the oil level change characteristic may include an oil level rising characteristic, an oil level slow-falling characteristic, and an oil level sudden-falling characteristic, and after the current oil level change characteristic is determined, it is necessary to determine a mechanical state before the current oil level change characteristic is obtained, where the mechanical state includes any one or more of a normal operating state, a refueling state, a uncovering state, an abnormal state, a defense state, an oil stealing state, and a suspected oil stealing state.
Step S602, determining whether to switch the first mechanical state according to the monitoring result, so as to obtain a second mechanical state.
In particular, if the oil level change characteristic is determined to be the oil level rise characteristic, the machine is in the oiling state. If the oil level change characteristic is determined to be that the oil level drop characteristic comprises sudden drop and slow drop, the machine is in an oil stealing state or suspected oil stealing state, and therefore whether the current machine state is switched or not can be determined according to the oil level change characteristic, and a new machine state is obtained.
Fig. 7 provides a schematic diagram of state switching of a mechanical oil level, where the state switching process specifically includes:
[ normal operating state ]: in this state, the rise and fall of the oil level are not detected;
switching to [ armed state ]: simultaneously satisfying 1) arming and disarming control state machine is in [ arming request state ]; 2) the oil level abnormity detection state machine leaves the oiling state for T6 time, and under the two conditions, the state is switched to the defense state;
switching to [ uncap state ]: and when the fuel tank cover is opened, switching to the opening state.
[ refueling state ]: in this state, pushing a refueling event alarm;
switching to [ normal operating state ]: the fuel tank cap closing event occurs under the condition of 1); 2) the oil level is unchanged for a time T5 and is switched to [ normal operation ] in the case of one of these two conditions.
[ deployment state ]: in the state, the abnormal events are continuously monitored, the three-axis sensor of the machine is set to be in a movable contact state in the state, and once obvious movement or vibration occurs, the abnormal vibration events are pushed to give an alarm;
switch to [ abnormal state ]: after the triaxial trigger occurs, switching to [ abnormal state ];
switching to [ uncap state ]: switching to the opening state under the condition that the opening event of the oil tank cover occurs;
switch to [ refuel state ]: when the oil level rising characteristic is met, switching to the oil adding state;
switch to [ oil stealing state ]: and when the oil level drop characteristic is met, switching to the oil stealing state.
[ abnormal state ]: under this state, can improve the frequency of data acquisition, collect more effective data and improve the judgement accuracy, the unusual characteristic of continuous monitoring oil level informs the networking state machine of mechanical state monitoring end to network simultaneously.
Switching to [ armed state ]: after the oil level is free from abnormality for a time T7, switching to [ armed state ];
switch to [ oil stealing state ]: when the oil level slow-falling characteristic is met, switching to an oil stealing state;
switch to [ suspected oil theft 1 state ]: when the oil level sudden drop characteristic is met, switching to a suspected oil stealing 1 state;
switching to [ uncap state ]: switching to the opening state under the condition that the opening event of the oil tank cover occurs;
switch to [ refuel state ]: when the oil level rising characteristic is met, switching to the oil adding state;
switching to [ normal operating state ]: when the arming and disarming control state machine is in a disarming request state, switching to a normal working state.
[ oil stealing state ]: in the state, an oil stealing event is pushed to alarm, and the descending characteristic of the oil level is continuously concerned;
switch to [ abnormal state ]: after the oil level is not abnormal for a time T8, switching is made to [ abnormal state ].
[ uncapped state ]: under this state, can improve the frequency of data acquisition, collect more effective data and improve the judgement accuracy, the unusual characteristic of continuous monitoring oil level informs the networking state machine of mechanical state monitoring end to network simultaneously.
Switch to [ abnormal state ]: the fuel tank cap closing event occurs under the condition of 1); 2) the oil level does not change for a time T5 continuously, and in the case of one of these two conditions, it switches to [ abnormal state ];
switch to [ refuel state ]: when the oil level rising characteristic is met, switching to the oil adding state;
switch to [ oil stealing state ]: and when the oil level slow-falling characteristic is met, switching to the oil stealing state.
[ suspected oil theft 1 state ]: in the state, suspected disarming and disarming instructions generated by a mechanical state monitoring end are waited to eliminate false alarm generated by the motion of the mechanical vehicle;
switch to [ suspected oil theft 2 state ]: when the arming and disarming control state machine is in a suspected disarming state, switching to a suspected oil stealing 2 state;
switching to [ normal operating state ]: when the arming and disarming control state machine is in a disarming request state, switching to a normal working state;
switch to [ oil stealing state ]: during this state, which lasts for time T9, the state switches to the oil stealing state.
[ suspected oil theft 2 state ]: in this state, a disarming instruction generated by a mechanical state monitoring end is waited to eliminate false alarm generated by the motion of the mechanical vehicle;
switching to [ normal operating state ]: when the arming and disarming control state machine is in a disarming request state, switching to a normal working state;
switch to [ oil stealing state ]: during this state, which lasts for time T10, the state switches to the oil stealing state.
From the above description, it can be seen that the present invention achieves the following technical effects: collecting mechanical state information and an oil level data group, wherein the oil level data group comprises an oil level value and sampling time; determining an oil level change slope according to the oil level data set to obtain an oil level change sequence; according to the mode of extracting the oil level change characteristics according to the oil level change sequence, whether the oil level is abnormal or not is monitored according to the oil level change characteristics and the mechanical state information, the purpose of accurately monitoring the abnormal condition of the oil level under different working conditions is achieved, and therefore the technical effect of avoiding the abnormal condition of the oil level from being misreported or being misreported is achieved.
It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer-executable instructions and that, although a logical order is illustrated in the flowcharts, in some cases, the steps illustrated or described may be performed in an order different than presented herein.
According to an embodiment of the present invention, there is also provided an apparatus for implementing the above-described data processing method for oil level abnormality monitoring, as shown in fig. 8, the apparatus including: the oil level data set comprises an oil level value and sampling time; the first determination module is used for determining an oil level change slope according to the oil level data group so as to obtain an oil level change sequence; the extraction module is used for extracting oil level change characteristics according to the oil level change sequence; and the monitoring module is used for monitoring whether the oil level is abnormal or not according to the oil level change characteristics and the mechanical state information.
As a preferred implementation of the embodiment of the present application, the oil level change slope includes a plurality of slopes, and the first determining module includes: the first determining unit is used for determining the sampling number N of the oil level change slopes and a preset oil level change threshold according to the mechanical state information, and sequencing the N oil level change slopes according to time, wherein N is not less than 1; the comparison unit is used for comparing the N oil level change slopes with the preset oil level change threshold respectively to obtain the oil level abrupt change sequence and the oil level gradual change sequence; and the second determination unit is used for determining the oil level change characteristic according to the oil level abrupt change sequence, the oil level gradual change sequence and the sampling number N of the oil level change slope.
As a preferred implementation manner of the embodiment of the present application, the oil level variation sequence includes an oil level abrupt change sequence and an oil level gradual change sequence, and the extraction module includes: the first determining unit is used for determining an oil level ascending characteristic and/or an oil level slowly descending characteristic judging sequence according to the oil level abrupt change sequence, the oil level slowly changing sequence and the sampling number of the oil level change slope; the first summing unit is used for carrying out weighted summing processing on the oil level rising characteristic and/or the oil level slow-falling characteristic judgment sequence according to the mechanical state information; and the first judgment unit is used for judging whether the first oil level change characteristic value obtained after the summation processing meets a first preset condition or not so as to determine the oil level rising characteristic and/or the oil level slowly falling characteristic according to the judgment result.
As a preferred implementation manner of the embodiment of the present application, the oil level change sequence includes an oil level mutation sequence, and the extraction module includes: the second determining unit is used for determining an oil level sudden drop characteristic judging sequence according to the oil level sudden change sequence and the sampling number of the oil level change slope; the second summation unit is used for carrying out weighted summation processing on the oil level sudden drop characteristic judgment sequence according to the mechanical state information; and the second judging unit is used for judging whether the second oil level change characteristic value obtained after the summation processing meets a second preset condition or not so as to determine the oil level sudden-drop characteristic according to the judgment result.
As a preferred implementation of the embodiment of the present application, the apparatus further includes: the judging module is used for judging whether an oil level abnormity monitoring instruction is received or not; and the entering module is used for entering the step of collecting the mechanical state information and the oil level data set if the mechanical state information and the oil level data set are received.
As a preferred implementation manner of the embodiment of the present application, the mechanical state information includes any one or more of a normal operating state, an oil filling state, an uncovering state, an abnormal state, a defense deploying state, an oil stealing state, and a suspected oil stealing state, and the monitoring module includes: a third determination unit for determining the first mechanical state; and the fourth determining unit is used for determining whether to switch the first mechanical state or not according to the monitoring result so as to obtain a second mechanical state.
For the specific connection relationship between the modules and the units and the functions performed, please refer to the detailed description of the method, which is not repeated herein.
According to an embodiment of the present invention, there is also provided a computer apparatus including: one or more processors; storage means for storing one or more programs; the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method as previously described.
There is also provided, in accordance with an embodiment of the present invention, a computer-readable storage medium having stored thereon computer instructions, which when executed by a processor, implement the steps of the method as previously described.
As shown in fig. 9, the electronic device includes one or more processors 31 and a memory 32, and one processor 31 is taken as an example in fig. 9.
The control unit may further include: an input device 33 and an output device 34.
The processor 31, the memory 32, the input device 33 and the output device 34 may be connected by a bus or other means, and the bus connection is exemplified in fig. 9.
The processor 31 may be a Central Processing Unit (CPU). The Processor 31 may also be other general purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, or combinations thereof. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 32, which is a non-transitory computer readable storage medium, may be used to store non-transitory software programs, non-transitory computer executable programs, and modules. The processor 31 executes various functional applications of the server and data processing, i.e., implements the data processing method for oil level abnormality monitoring of the above-described method embodiment, by running non-transitory software programs, instructions, and modules stored in the memory 32.
The memory 32 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to use of a processing device operated by the server, and the like. Further, the memory 32 may include high speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory 32 may optionally include memory located remotely from the processor 31, which may be connected to a network connection device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input device 33 may receive input numeric or character information and generate key signal inputs related to user settings and function control of the processing device of the server. The output device 34 may include a display device such as a display screen.
One or more modules are stored in the memory 32, which when executed by the one or more processors 31 perform the methods as previously described.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein. Computer instructions for causing the computer to perform a data processing method for oil level anomaly monitoring.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, the principle and the implementation of the present invention are explained by applying the specific embodiments in the present invention, and the above description of the embodiments is only used to help understanding the method and the core idea of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (10)
1. A data processing method for oil level anomaly monitoring, comprising:
collecting mechanical state information and an oil level data group, wherein the oil level data group comprises an oil level value and sampling time;
determining an oil level change slope according to the oil level data set to obtain an oil level change sequence;
extracting oil level variation characteristics according to the oil level variation sequence;
and monitoring whether the oil level is abnormal or not according to the oil level change characteristic and the mechanical state information.
2. The data processing method for oil level abnormality monitoring according to claim 1, wherein said determining an oil level change slope from said oil level data set to obtain an oil level change sequence includes:
determining the sampling number N of the oil level change slopes and a preset oil level change threshold according to the mechanical state information, and sequencing the N oil level change slopes according to time, wherein N is not less than 1;
comparing the N oil level change slopes with the preset oil level change threshold respectively to obtain the oil level abrupt change sequence and the oil level slowly-changing sequence;
and determining the oil level change characteristic according to the oil level abrupt change sequence, the oil level gradual change sequence and the sampling number N of the oil level change slope.
3. The data processing method for oil level abnormality monitoring according to claim 1, wherein the oil level variation sequence includes an oil level abrupt change sequence and an oil level gradual change sequence, and the extracting of the oil level variation characteristics from the oil level variation sequence includes:
determining an oil level ascending characteristic and/or an oil level slowly descending characteristic judgment sequence according to the oil level abrupt change sequence, the oil level slowly changing sequence and the sampling number of the oil level change slope;
according to the mechanical state information, carrying out weighted summation processing on the oil level rising characteristic and/or oil level slow-falling characteristic judgment sequence;
and judging whether the first oil level change characteristic value obtained after the summation processing meets a first preset condition or not, so as to determine an oil level rising characteristic and/or an oil level slow-falling characteristic according to the judgment result.
4. The data processing method for oil level abnormality monitoring according to claim 1, wherein the oil level change sequence includes an oil level abrupt change sequence, and the extracting of the oil level change characteristic from the oil level change sequence includes:
determining an oil level sudden drop characteristic judgment sequence according to the oil level sudden change sequence and the sampling number of the oil level change slope;
according to the mechanical state information, carrying out weighted summation processing on the oil level sudden drop characteristic judgment sequence;
and judging whether the second oil level change characteristic value obtained after the summation processing meets a second preset condition or not so as to determine the oil level sudden-drop characteristic according to the judgment result.
5. The data processing method for oil level anomaly monitoring according to claim 1, wherein said collecting an oil level data set previously comprises:
judging whether an oil level abnormity monitoring instruction is received or not;
and if so, entering the step of collecting the mechanical state information and the oil level data set.
6. The data processing method for monitoring the oil level abnormality according to claim 1, wherein the mechanical state information includes any one or more of a normal operation state, a refueling state, an uncovering state, an abnormal state, a defense state, an oil stealing state and a suspected oil stealing state, and the monitoring whether the oil level abnormality occurs according to the oil level variation characteristics and the mechanical state information includes:
determining a first mechanical state;
and determining whether to switch the first mechanical state or not according to the monitoring result so as to obtain a second mechanical state.
7. A data processing apparatus for oil level anomaly monitoring, comprising:
the oil level data set comprises an oil level value and sampling time;
the first determination module is used for determining an oil level change slope according to the oil level data group so as to obtain an oil level change sequence;
the extraction module is used for extracting oil level change characteristics according to the oil level change sequence;
and the monitoring module is used for monitoring whether the oil level is abnormal or not according to the oil level change characteristics and the mechanical state information.
8. The data processing device for oil level abnormality monitoring according to claim 7, wherein said oil level change slope includes a plurality, said first determination module includes:
the first determining unit is used for determining the sampling number N of the oil level change slopes and a preset oil level change threshold according to the mechanical state information, and sequencing the N oil level change slopes according to time, wherein N is not less than 1;
the comparison unit is used for comparing the N oil level change slopes with the preset oil level change threshold respectively to obtain the oil level abrupt change sequence and the oil level gradual change sequence;
and the second determination unit is used for determining the oil level change characteristic according to the oil level abrupt change sequence, the oil level gradual change sequence and the sampling number N of the oil level change slope.
9. An electronic device, comprising:
one or more processors;
storage means for storing one or more programs;
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method of any of claims 1-6.
10. A non-transitory readable storage medium having stored thereon computer instructions which, when executed by a processor, implement the steps of the method of any one of claims 1 to 6.
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