CN111637924B - Detection method and detection device for abnormality of excavator and readable storage medium - Google Patents
Detection method and detection device for abnormality of excavator and readable storage medium Download PDFInfo
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- CN111637924B CN111637924B CN202010461573.XA CN202010461573A CN111637924B CN 111637924 B CN111637924 B CN 111637924B CN 202010461573 A CN202010461573 A CN 202010461573A CN 111637924 B CN111637924 B CN 111637924B
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Abstract
The application provides a detection method, a detection device and a readable storage medium for excavator abnormity, which are characterized in that the hydraulic oil temperature and the pump power of an excavator to be detected at each detection moment in a detection time period are obtained; determining a hydraulic oil temperature standard deviation and a pump power standard deviation of the excavator to be detected in a detection time period based on the obtained multiple hydraulic oil temperatures and the obtained multiple pump powers respectively; determining thermal characteristic parameters of the excavator to be detected based on the standard deviation of the hydraulic oil temperature and the standard deviation of the pump power; when the thermal characteristic parameters are detected not to be in the range of the corresponding thermal characteristic parameters of the excavator to be detected, determining that the excavator to be detected is abnormal, determining the working state of the excavator to be detected according to the thermal characteristic parameters determined by the standard difference of the hydraulic oil temperature and the standard difference of the pump power, avoiding the condition that whether the excavator to be detected is abnormal or not is misjudged due to the fact that the hydraulic oil temperature is influenced by environmental factors, and improving the accuracy of detecting the abnormality of the excavator.
Description
Technical Field
The present disclosure relates to the field of mechanical equipment monitoring technologies, and in particular, to a method and a device for detecting abnormality of an excavator, and a readable storage medium.
Background
With the development of industrial technology, construction machines are increasingly used in construction sites, and an excavator is one of the representatives of the construction machines used in the construction sites. In the working process of the excavator, the judgment of the working state of the excavator is a necessary step for ensuring the normal work of the excavator, wherein the hydraulic oil temperature of the excavator is an important reference index for judging the working state of the excavator, and when the hydraulic temperature is abnormally increased, the energy loss of a hydraulic system is large, and the working state of the excavator is abnormal.
At the present stage, the hydraulic oil temperature is influenced by a plurality of factors such as environmental factors, and under the influence of the factors, a large amount of interference oil temperature data exist during the early warning of the hydraulic oil temperature, so that the early warning opportunity and the early warning data have deviation, and further the judgment error of the working state of the excavator is caused.
Disclosure of Invention
In view of this, an object of the present application is to provide a method, a device and a readable storage medium for detecting an abnormality of an excavator, wherein a working state of the excavator to be detected is determined according to a thermal characteristic parameter determined by a standard deviation of hydraulic oil temperature and a standard deviation of pump power, so as to avoid a situation of misjudgment on whether the excavator to be detected is abnormal or not due to an influence of an environmental factor on the hydraulic oil temperature, and improve accuracy of detecting the abnormality of the excavator.
The embodiment of the application provides a method for detecting abnormality of an excavator, which comprises the following steps:
acquiring the hydraulic oil temperature and the pump power of the excavator to be detected at each detection moment in a detection time period;
determining a hydraulic oil temperature standard deviation and a pump power standard deviation of the excavator to be detected in the detection time period based on the obtained multiple hydraulic oil temperatures and the obtained multiple pump powers respectively;
determining thermal characteristic parameters of the excavator to be detected based on the hydraulic oil temperature standard deviation and the pump power standard deviation;
and when the thermal characteristic parameters are detected not to belong to the thermal characteristic parameter range corresponding to the excavator to be detected, determining that the excavator to be detected is abnormal.
Further, before the obtaining of the hydraulic oil temperature and the pump power at each detection time in the detection time period of the excavator to be detected, the detection method further includes:
determining a plurality of hydraulic oil temperature sample sets based on a plurality of historical hydraulic oil temperatures of the excavator to be detected in a historical working time period;
for each hydraulic oil temperature sample set, based on the calculated sample hydraulic oil temperature standard deviation of the hydraulic oil temperature sample set, eliminating abnormal hydraulic oil temperature in the hydraulic oil temperature sample set, and determining a target sample set and target thermal characteristic parameters of the target sample set;
and determining the thermal characteristic parameter range corresponding to the excavator to be detected based on the historical hydraulic oil temperature in each target sample set and the corresponding target thermal characteristic parameters.
Further, the determining a plurality of hydraulic oil temperature sample sets based on a plurality of historical hydraulic oil temperatures of the excavator to be detected in a historical working time period includes:
dividing the historical working time period into a plurality of sub-time periods based on a preset time interval;
based on the acquisition time of each historical hydraulic oil temperature, dividing at least one historical hydraulic oil temperature with the acquisition time in the same sub-time period into the same sample set to generate a hydraulic oil temperature sample set.
Further, the target sample set is determined by:
determining the dispersion of each historical hydraulic oil temperature based on the sample hydraulic oil temperature standard deviation, and determining the historical hydraulic oil temperature with the dispersion larger than a preset dispersion threshold value as a first abnormal hydraulic oil temperature;
determining a starting time period of the excavator to be detected and acquisition time of each historical hydraulic oil temperature, and determining the historical hydraulic oil temperature of the acquisition time in the starting time period as a second abnormal hydraulic oil temperature;
and filtering the determined at least one first abnormal hydraulic oil temperature and at least one second abnormal hydraulic oil temperature from the hydraulic oil temperature sample set to determine a target sample set.
Further, a target thermal property parameter of the target sample set is determined by:
determining a target pump power standard deviation of the target sample set based on a plurality of historical pump powers in a sub-time period corresponding to the determined target sample set;
determining a target hydraulic oil temperature standard deviation of the target sample set based on a plurality of historical hydraulic oil temperatures from which abnormal hydraulic oil temperatures are filtered;
determining the target thermal property parameter based on the target hydraulic oil temperature standard deviation and the target hydraulic oil temperature standard deviation.
Further, the thermal property parameter range is determined by:
determining a thermal characteristic parameter standard deviation of the target thermal characteristic parameter based on the target thermal characteristic parameter of each target sample set;
based on the standard deviation of the thermal characteristic parameters, filtering abnormal thermal characteristic parameters from the determined multiple target thermal characteristic parameters, and determining multiple residual thermal characteristic parameters;
determining the highest historical hydraulic oil temperature and the lowest historical hydraulic oil temperature from the target sample set corresponding to each residual characteristic parameter;
determining a target high hydraulic oil temperature and a target low hydraulic oil temperature based on the determined multiple highest historical hydraulic oil temperatures, multiple lowest historical hydraulic oil temperatures and a preset normal hydraulic oil temperature range;
and determining a thermal characteristic parameter range determined by the target thermal characteristic parameter of the target sample set in which the target low hydraulic oil temperature is located and the target thermal characteristic parameter of the target sample set in which the target high hydraulic oil temperature is located as the thermal characteristic parameter range.
The embodiment of the present application further provides an abnormal detection device for an excavator, where the detection device includes:
the acquisition module is used for acquiring the hydraulic oil temperature and the pump power of the excavator to be detected at each detection moment in the detection time period;
the first determining module is used for determining a hydraulic oil temperature standard deviation and a pump power standard deviation of the excavator to be detected in the detection time period respectively based on the obtained multiple hydraulic oil temperatures and the obtained multiple pump powers;
the second determination module is used for determining the thermal characteristic parameters of the excavator to be detected based on the hydraulic oil temperature standard deviation and the pump power standard deviation;
and the third determining module is used for determining that the excavator to be detected is abnormal when the thermal characteristic parameter is detected not to belong to the thermal characteristic parameter range corresponding to the excavator to be detected.
Further, the detection apparatus further includes a fourth determining module, where the fourth determining module is configured to:
determining a plurality of hydraulic oil temperature sample sets based on a plurality of historical hydraulic oil temperatures of the excavator to be detected in a historical working time period;
for each hydraulic oil temperature sample set, based on the calculated sample hydraulic oil temperature standard deviation of the hydraulic oil temperature sample set, eliminating abnormal hydraulic oil temperature in the hydraulic oil temperature sample set, and determining a target sample set and target thermal characteristic parameters of the target sample set;
and determining the thermal characteristic parameter range corresponding to the excavator to be detected based on the historical hydraulic oil temperature in each target sample set and the corresponding target thermal characteristic parameters.
Further, when the fourth determining module is configured to determine a plurality of hydraulic oil temperature sample sets based on a plurality of historical hydraulic oil temperatures of the excavator to be detected in a historical working time period, the fourth determining module is configured to:
dividing the historical working time period into a plurality of sub-time periods based on a preset time interval;
based on the acquisition time of each historical hydraulic oil temperature, dividing at least one historical hydraulic oil temperature with the acquisition time in the same sub-time period into the same sample set to generate a hydraulic oil temperature sample set.
Further, the fourth determination module is configured to determine the target sample set by:
determining the dispersion of each historical hydraulic oil temperature based on the sample hydraulic oil temperature standard deviation, and determining the historical hydraulic oil temperature with the dispersion larger than a preset dispersion threshold value as a first abnormal hydraulic oil temperature;
determining a starting time period of the excavator to be detected and acquisition time of each historical hydraulic oil temperature, and determining the historical hydraulic oil temperature of the acquisition time in the starting time period as a second abnormal hydraulic oil temperature;
and filtering the determined at least one first abnormal hydraulic oil temperature and at least one second abnormal hydraulic oil temperature from the hydraulic oil temperature sample set to determine a target sample set.
Further, the fourth determination module is configured to determine the target thermal property parameter of the target sample set by:
determining a target pump power standard deviation of the target sample set based on a plurality of historical pump powers in a sub-time period corresponding to the determined target sample set;
determining a target hydraulic oil temperature standard deviation of the target sample set based on a plurality of historical hydraulic oil temperatures from which abnormal hydraulic oil temperatures are filtered;
determining the target thermal property parameter based on the target hydraulic oil temperature standard deviation and the target hydraulic oil temperature standard deviation.
Further, the fourth determination module is configured to determine the thermal property parameter range by:
determining a thermal characteristic parameter standard deviation of the target thermal characteristic parameter based on the target thermal characteristic parameter of each target sample set;
based on the standard deviation of the thermal characteristic parameters, filtering abnormal thermal characteristic parameters from the determined multiple target thermal characteristic parameters, and determining multiple residual thermal characteristic parameters;
determining the highest historical hydraulic oil temperature and the lowest historical hydraulic oil temperature from the target sample set corresponding to each residual characteristic parameter;
determining a target high hydraulic oil temperature and a target low hydraulic oil temperature based on the determined multiple highest historical hydraulic oil temperatures, multiple lowest historical hydraulic oil temperatures and a preset normal hydraulic oil temperature range;
and determining a thermal characteristic parameter range determined by the target thermal characteristic parameter of the target sample set in which the target low hydraulic oil temperature is located and the target thermal characteristic parameter of the target sample set in which the target high hydraulic oil temperature is located as the thermal characteristic parameter range.
An embodiment of the present application further provides an electronic device, including: the detection method comprises a processor, a memory and a bus, wherein the memory stores machine readable instructions executable by the processor, the processor and the memory are communicated through the bus when the electronic device runs, and the machine readable instructions are executed by the processor to execute the steps of the detection method for the abnormality of the excavator.
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 excavator anomaly as described above are performed.
According to the detection method, the detection device and the readable storage medium for the abnormality of the excavator, the hydraulic oil temperature and the pump power of the excavator to be detected at each detection moment in the detection time period are obtained; determining a hydraulic oil temperature standard deviation and a pump power standard deviation of the excavator to be detected in the detection time period based on the obtained multiple hydraulic oil temperatures and the obtained multiple pump powers respectively; determining thermal characteristic parameters of the excavator to be detected based on the hydraulic oil temperature standard deviation and the pump power standard deviation; and when the thermal characteristic parameters are detected not to belong to the thermal characteristic parameter range corresponding to the excavator to be detected, determining that the excavator to be detected is abnormal.
In this way, the hydraulic oil temperature and the pump power of the excavator to be detected at each detection time in the detection time period are obtained, the hydraulic oil temperature standard deviation and the pump power standard deviation are determined according to the obtained hydraulic oil temperatures and the obtained pump powers, and when the thermal characteristic parameters of the excavator to be detected determined according to the hydraulic oil temperature standard deviation and the pump power standard deviation are detected and do not belong to the corresponding thermal characteristic parameter range of the excavator to be detected, the excavator to be detected is determined to be in an abnormal state. The working state of the excavator to be detected is determined according to the thermal characteristic parameters determined by the standard deviation of the hydraulic oil temperature and the standard deviation of the pump power, the condition that whether the excavator to be detected is abnormal or not is judged mistakenly due to the fact that the hydraulic oil temperature is influenced by environmental factors can be avoided, and the accuracy of detecting the abnormality of the excavator can be 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 anomaly of an excavator according to an embodiment of the present disclosure;
fig. 3 is a flowchart of a method for detecting an anomaly of an excavator according to another embodiment of the present application;
fig. 4 is a schematic structural diagram of an abnormal detection device for an excavator according to an embodiment of the present disclosure;
fig. 5 is a second schematic structural diagram of an abnormal detection device for an excavator according to an embodiment of the present application;
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 method can be applied to the technical field of mechanical equipment monitoring, the hydraulic oil temperature and the pump power of the excavator to be detected at each detection moment in the detection time period are obtained, the hydraulic oil temperature standard deviation and the pump power standard deviation are determined according to the obtained hydraulic oil temperatures and the obtained pump powers, and when the thermal characteristic parameters of the excavator to be detected determined by the hydraulic oil temperature standard deviation and the pump power standard deviation are detected to be not in the thermal characteristic parameter range corresponding to the excavator to be detected, the abnormality of the excavator to be detected is determined. Therefore, the working state of the excavator to be detected is determined through the thermal characteristic parameters determined by the standard deviation of the hydraulic oil temperature and the standard deviation of the pump power, the condition that whether the excavator to be detected is abnormal or not is judged mistakenly due to the fact that the hydraulic oil temperature is influenced by environmental factors can be avoided, and the accuracy of detecting the abnormality of the excavator can be improved. 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 data acquisition device and a detection device, the data acquisition device acquires a plurality of hydraulic oil temperatures and a plurality of pump powers within a detection time period, the detection device acquires the plurality of hydraulic oil temperatures and the plurality of pump powers acquired by the data acquisition device, and determines a hydraulic oil temperature standard deviation and a pump power standard deviation based on the plurality of hydraulic oil temperatures and the plurality of pump powers, thereby determining a thermal characteristic parameter, and based on the thermal characteristic parameter, detects whether the excavator to be detected is abnormal.
Research shows that in the present stage, the hydraulic oil temperature is influenced by a plurality of factors such as environmental factors, and under the influence of the factors, a large amount of interference oil temperature data exist during early warning of the hydraulic oil temperature, so that deviation exists between early warning opportunity and early warning data, and further judgment errors of the working state of the excavator are caused.
Based on this, the embodiment of the application provides a method for detecting abnormality of an excavator, which determines the working state of the excavator to be detected through the thermal characteristic parameters determined by the standard deviation of the hydraulic oil temperature and the standard deviation of the pump power, so that the condition that whether the excavator to be detected is abnormal or not is misjudged due to the fact that the hydraulic oil temperature is affected by environmental factors can be avoided, and the accuracy of detecting the abnormality of the excavator can be improved.
Referring to fig. 2, fig. 2 is a flowchart illustrating a method for detecting an anomaly of an excavator according to an embodiment of the present disclosure. As shown in fig. 2, a method for detecting an abnormality of an excavator according to an embodiment of the present application includes:
In the step, the hydraulic oil temperature and the pump power at each detection moment when the excavator to be detected can acquire the working data of the excavator to be detected in the detection time period are acquired.
The detection time period is a preset detection time period, and may be a working time period from the start of the excavator to be detected to work to the end of the excavator to be detected to work, or a preset time period, such as one day, one week, one month, and the like.
Here, each detection time is a predetermined data collection time interval of a sensor provided on the excavator to be detected, and the time interval between every two detection times is equal.
The hydraulic oil temperature refers to the temperature of hydraulic oil when the excavator to be detected works, and is an important reference index for detecting the state of the excavator; the pump power refers to the hydraulic pump power, and is the ratio of the working pressure of the excavator to the output flow of the pump.
In the step, the standard deviation of the hydraulic oil temperature of the excavator to be detected in the detection time period is determined according to the plurality of hydraulic oil temperatures acquired in the detection time period, and meanwhile, the standard deviation of the pump power of the excavator to be detected in the detection time period is determined according to the plurality of pump powers acquired in the detection time period.
And 203, determining the thermal characteristic parameters of the excavator to be detected based on the standard deviation of the hydraulic oil temperature and the standard deviation of the pump power.
In the step, the quotient of the determined hydraulic oil temperature standard deviation and the pump power standard deviation is determined as the thermal characteristic parameter of the excavator to be detected in the detection time period.
The thermal characteristic parameter may be a quotient between a hydraulic oil temperature standard deviation and a pump power standard deviation, or a quotient between a pump power standard deviation and a hydraulic oil temperature standard deviation, and the specific setting is determined according to a calculation manner of the thermal characteristic parameter included in a thermal characteristic parameter range corresponding to the excavator to be detected.
And 204, determining that the excavator to be detected is abnormal when the thermal characteristic parameters are detected not to belong to the thermal characteristic parameter range corresponding to the excavator to be detected.
In this step, when the thermal characteristic parameter determined in step 203 does not belong to the thermal characteristic parameter range corresponding to the excavator to be detected, it is determined that the thermal characteristic parameter of the excavator to be detected is abnormal, and according to the abnormality of the thermal characteristic parameter, it is determined that the hydraulic oil temperature of the excavator to be detected is abnormal, so that according to the abnormality of the hydraulic oil temperature, it is determined that the excavator to be detected is abnormal.
Here, the thermal characteristic parameter range is determined according to the historical hydraulic oil temperature and the historical pump power acquired when the excavator works in the past, so that for each excavator, a certain difference may exist in the corresponding thermal characteristic parameter range, and when abnormality detection is performed on the excavator to be detected, the corresponding thermal characteristic parameter range needs to be acquired so as to more accurately judge the abnormality of the excavator to be detected.
Here, the determination that the thermal property parameter is not within the thermal property parameter range means: the thermal property parameter is less than a smallest thermal property parameter of a range of thermal property parameters or greater than a largest thermal property parameter of the range of thermal property parameters.
According to the method for detecting the abnormality of the excavator, the hydraulic oil temperature and the pump power of the excavator to be detected at each detection moment in the detection time period are obtained; determining a hydraulic oil temperature standard deviation and a pump power standard deviation of the excavator to be detected in the detection time period based on the obtained multiple hydraulic oil temperatures and the obtained multiple pump powers respectively; determining thermal characteristic parameters of the excavator to be detected based on the hydraulic oil temperature standard deviation and the pump power standard deviation; and when the thermal characteristic parameters are detected not to belong to the thermal characteristic parameter range corresponding to the excavator to be detected, determining that the excavator to be detected is abnormal.
In this way, the hydraulic oil temperature and the pump power of the excavator to be detected at each detection time in the detection time period are obtained, the hydraulic oil temperature standard deviation and the pump power standard deviation are determined according to the obtained hydraulic oil temperatures and the obtained pump powers, and when the thermal characteristic parameters of the excavator to be detected determined according to the hydraulic oil temperature standard deviation and the pump power standard deviation are detected and do not belong to the corresponding thermal characteristic parameter range of the excavator to be detected, the excavator to be detected is determined to be in an abnormal state. The working state of the excavator to be detected is determined according to the thermal characteristic parameters determined by the standard deviation of the hydraulic oil temperature and the standard deviation of the pump power, the condition that whether the excavator to be detected is abnormal or not is judged mistakenly due to the fact that the hydraulic oil temperature is influenced by environmental factors can be avoided, and the accuracy of detecting the abnormality of the excavator can be improved.
Referring to fig. 3, fig. 3 is a flowchart illustrating a method for detecting an anomaly of an excavator according to another embodiment of the present application. As shown in fig. 3, a method for detecting an abnormality of an excavator according to an embodiment of the present application includes:
In the step, a plurality of historical hydraulic oil temperatures of the excavator to be detected in a certain historical working time period are obtained from a background memory, the historical hydraulic oil temperatures are divided according to the acquisition time, and a plurality of hydraulic oil temperature sample sets are determined.
Here, when dividing according to the acquisition time of each historical hydraulic oil temperature, it is necessary to set a plurality of sub-periods for the division, and when dividing the sub-periods, the divided time intervals are uniform.
In the step, for each historical hydraulic oil temperature data in each hydraulic oil temperature sample set determined in the step 301, a sample hydraulic oil temperature standard deviation of the sample hydraulic oil temperature sample set is calculated, and a dispersion degree of each historical hydraulic oil temperature data is determined according to the calculated sample hydraulic oil temperature standard deviation, so that an abnormal hydraulic oil temperature is determined according to the dispersion degree, the abnormal hydraulic oil temperature is filtered, a target sample set is determined, and meanwhile, a target thermal characteristic parameter of the target sample set is determined according to the historical hydraulic oil temperature and the historical pump power in the target sample set in which the abnormal hydraulic oil temperature is filtered.
Here, the standard deviation of the sample hydraulic oil temperature may be calculated according to a plurality of historical hydraulic oil temperatures included in the hydraulic oil temperature sample set to determine and filter the abnormal hydraulic oil temperature, or a range of the normal hydraulic oil temperature may be roughly defined according to historical experience, and the obviously abnormal hydraulic oil temperature may be directly removed before calculating the labeling deviation.
The abnormal hydraulic oil temperature determined according to the standard deviation of the sample hydraulic oil temperature may be caused by factors such as a fault sent by a data acquisition sensor or an error in recording, and the abnormal hydraulic oil temperature affects the calculation process of the subsequent thermal characteristic parameter range, so that the abnormal hydraulic oil temperature needs to be filtered.
In this way, after the sample hydraulic oil temperature standard deviation is calculated and the abnormal hydraulic oil temperature is filtered, the determined historical hydraulic oil temperatures remaining in the target sample set are all historical hydraulic oil temperatures which can be used for subsequent calculation, and are within an acceptable range even if certain errors exist.
In this step, a thermal characteristic parameter range of the excavator to be detected is determined according to the historical hydraulic oil temperature included in each target sample set determined in step 302 and the target thermal characteristic parameter corresponding to each target sample set.
Here, can regard as the standard that detects the excavator hydraulic oil temperature to detect with the thermal characteristic parameter range that determines, when the thermal characteristic parameter that detects the excavator is in the thermal characteristic parameter range that determines, then can confirm on this detection dimension of hydraulic oil temperature that it is normal to detect the excavator, otherwise, then confirm to detect that detects the excavator is unusual, can generate the early warning information of hydraulic oil temperature simultaneously, inform and detect the operating personnel or the detection personnel on waiting to detect the excavator, detect the hydraulic oil temperature that detects the excavator and the concrete trouble of hydraulic cylinder.
Here, since the thermal characteristic parameter range is determined according to the historical operating data of the excavator to be detected, as the service time of the excavator to be detected increases, the thermal characteristic parameter range defined by the normal thermal characteristic parameters may change, and a plurality of historical hydraulic oil temperatures may be collected within the preset historical operating time period to redefine the thermal characteristic parameter range.
And step 304, acquiring the hydraulic oil temperature and the pump power of the excavator to be detected at each detection moment in the detection time period.
And 305, determining a hydraulic oil temperature standard deviation and a pump power standard deviation of the excavator to be detected in the detection time period respectively based on the obtained multiple hydraulic oil temperatures and the obtained multiple pump powers.
And step 306, determining thermal characteristic parameters of the excavator to be detected based on the hydraulic oil temperature standard deviation and the pump power standard deviation.
And 307, determining that the excavator to be detected is abnormal when the thermal characteristic parameter is detected not to belong to the range of the thermal characteristic parameter corresponding to the excavator to be detected.
The descriptions of step 304 to step 307 may refer to the descriptions of step 201 to step 204, and the same technical effects can be achieved, which is not described in detail herein.
Further, step 301 includes: dividing the historical working time period into a plurality of sub-time periods based on a preset time interval; based on the acquisition time of each historical hydraulic oil temperature, dividing at least one historical hydraulic oil temperature with the acquisition time in the same sub-time period into the same sample set to generate a hydraulic oil temperature sample set.
In the step, after the determined historical working time period, the historical working time period is divided into a plurality of sub-time periods according to a preset time interval, at least one historical hydraulic oil temperature with the acquisition time in the same sub-time period is divided into the same sample set according to the acquisition time of each historical hydraulic oil temperature, and after the historical hydraulic oil temperatures in the historical working time period are divided, a plurality of hydraulic oil temperature sample sets are determined.
Here, in the historical working process of the excavator to be detected, a plurality of working hours exist, one working hour refers to a time period from the start of the excavator to be detected to the flameout stop of the excavator to be detected, and when the equal time interval is divided, the working time period is divided into sub-time periods according to the start time and the stop time.
For example, if the starting time period of one working time in the historical working time period is 9:00-13:00, and the preset time interval is 1 hour when the sub-time periods are divided, the working time periods can be divided into four sub-time periods of 9:00-10:00, 10:00-11:00, 11:00-12:00 and 12:00-13:00, and all the historical hydraulic oil temperatures in the working time periods belong to four different hydraulic oil temperature sample sets.
Further, the target sample set is determined by: determining the dispersion of each historical hydraulic oil temperature based on the sample hydraulic oil temperature standard deviation, and determining the historical hydraulic oil temperature with the dispersion larger than a preset dispersion threshold value as a first abnormal hydraulic oil temperature; determining a starting time period of the excavator to be detected and acquisition time of each historical hydraulic oil temperature, and determining the historical hydraulic oil temperature of the acquisition time in the starting time period as a second abnormal hydraulic oil temperature; and filtering the determined at least one first abnormal hydraulic oil temperature and at least one second abnormal hydraulic oil temperature from the hydraulic oil temperature sample set to determine a target sample set.
The method comprises the steps of calculating a sample hydraulic oil temperature standard difference of each hydraulic oil temperature sample set aiming at a plurality of historical hydraulic oil temperatures in each hydraulic oil temperature sample set, determining the dispersion of each historical hydraulic oil temperature in each hydraulic oil temperature sample set based on the sample hydraulic oil temperature standard difference, determining the hydraulic oil temperature with the dispersion larger than a preset dispersion threshold value as a first abnormal hydraulic oil temperature, determining a plurality of starting time periods of an excavator to be detected in the historical working time periods after the first abnormal hydraulic oil temperature is determined, determining a second abnormal hydraulic oil temperature according to the acquisition time of each historical hydraulic oil temperature from the historical hydraulic oil temperature in the starting time periods, removing the determined at least one first abnormal hydraulic oil temperature and the determined at least one second abnormal hydraulic oil temperature from the hydraulic oil temperature sample sets, and removing the at least one first abnormal hydraulic oil temperature and the at least one second abnormal hydraulic oil temperature from the hydraulic oil temperature sample sets And determining the target sample set.
Here, the dispersion degree indicates the dispersion degree of the historical hydraulic oil temperature, and the larger the dispersion degree of one historical hydraulic oil temperature is, the larger the difference between the historical hydraulic oil temperature and other historical hydraulic oil temperatures is, the larger the probability that the historical hydraulic oil temperature is an abnormal hydraulic oil temperature is (generally, in a normal case, the difference between the historical hydraulic oil temperatures of the same excavator to be detected is not large), so that the abnormal hydraulic oil temperature needs to be filtered, and the accuracy of defining a thermal characteristic parameter range in a subsequent calculation process is prevented from being influenced.
Here, in the starting process of the excavator to be detected, the historical hydraulic oil temperature is quickly increased from the temperature close to the environment to the normal working temperature, the historical hydraulic oil temperature belongs to the normal temperature change process, the change range of the historical hydraulic oil temperature is large in the period, the starting process needs to be identified, the historical hydraulic oil temperature in the starting process needs to be filtered, and the accuracy of subsequent calculation is guaranteed.
Further, a target thermal property parameter of the target sample set is determined by: determining a target pump power standard deviation of the target sample set based on a plurality of historical pump powers in a sub-time period corresponding to the determined target sample set; determining a target hydraulic oil temperature standard deviation of the target sample set based on a plurality of historical hydraulic oil temperatures from which abnormal hydraulic oil temperatures are filtered; determining the target thermal property parameter based on the target hydraulic oil temperature standard deviation and the target hydraulic oil temperature standard deviation.
In the step, a plurality of historical pump powers in a sub-time period corresponding to a target sample set are determined, and the obtaining time of general pump power is consistent with the obtaining time of historical hydraulic oil temperature, so that the number of the historical pump powers in the same sub-time period is corresponding to the number of the historical hydraulic oil temperature, a target pump power standard deviation of the target sample set is determined according to the plurality of historical pump powers, a target hydraulic oil temperature standard deviation of the target sample set is determined according to a plurality of historical hydraulic oil temperatures left after abnormal hydraulic oil temperature is filtered, and a quotient of the target pump power standard deviation and the target hydraulic oil temperature standard deviation is determined as a target thermal characteristic parameter.
Here, the target thermal characteristic parameter may be a ratio between the target pump power standard deviation and the target hydraulic oil temperature standard deviation, or may be a standard deviation between the target hydraulic oil temperature standard deviation and the target pump power standard deviation.
Here, for each target sample set, there may be an abnormality in the historical hydraulic oil temperature due to the influence of factors such as the operating environment temperature, and although the operating environment temperature has little influence on the historical pump power, the machine of the excavator to be detected may influence the collection of the historical pump power, which may cause the historical pump power to be abnormal, and the abnormal pump power may also be filtered according to the filtering step of the abnormal hydraulic oil temperature in the historical hydraulic oil temperature, so that the calculation process of subsequently determining the thermal characteristic parameter range is performed more accurately.
Further, the thermal property parameter range is determined by:
(1) determining a thermal characteristic parameter standard deviation of the target thermal characteristic parameter based on the target thermal characteristic parameter of each target sample set;
in this step, based on the determined multiple target sample sets and the target thermal characteristic parameters of each target sample set, the thermal characteristic parameter standard deviation is determined according to the multiple target thermal characteristic parameters.
(2) Based on the standard deviation of the thermal characteristic parameters, filtering abnormal thermal characteristic parameters from the determined multiple target thermal characteristic parameters, and determining multiple residual thermal characteristic parameters;
in the step, based on the determined standard deviation of the thermal characteristic parameters, the dispersion of each target thermal characteristic parameter is determined, the target thermal characteristic parameters with the dispersion larger than a preset threshold are determined as abnormal thermal characteristic parameters, the determined plurality of abnormal thermal characteristic parameters are filtered from the plurality of target thermal characteristic parameters, and a plurality of residual thermal characteristic parameters are determined.
The filtering frequency can be more than or equal to one time, so that the accuracy of filtering the abnormal thermal characteristic parameters is ensured.
(3) Determining the highest historical hydraulic oil temperature and the lowest historical hydraulic oil temperature from the target sample set corresponding to each residual characteristic parameter;
in this step, the highest historical hydraulic oil temperature and the lowest historical hydraulic oil temperature in the target sample set corresponding to each remaining characteristic parameter are determined.
(4) Determining a target high hydraulic oil temperature and a target low hydraulic oil temperature based on the determined multiple historical highest hydraulic oil temperatures, multiple historical lowest hydraulic oil temperatures and a preset normal hydraulic oil temperature range;
in the step, a plurality of historical maximum hydraulic oil temperatures in a set of all target samples are compared, the highest historical hydraulic oil temperature in a preset normal hydraulic oil temperature range is determined, the historical hydraulic oil temperature is determined as the target high hydraulic oil temperature, a plurality of historical minimum hydraulic oil temperatures in a set of all target samples are compared, the lowest historical hydraulic oil temperature in the preset normal hydraulic oil temperature range is determined, and the historical hydraulic oil temperature is determined as the target low hydraulic oil temperature.
(5) And determining a thermal characteristic parameter range determined by the target thermal characteristic parameter of the target sample set in which the target low hydraulic oil temperature is located and the target thermal characteristic parameter of the target sample set in which the target high hydraulic oil temperature is located as the thermal characteristic parameter range.
In the step, a target thermal characteristic parameter of a target sample set where the target low hydraulic oil temperature is located and a target thermal characteristic parameter of a target sample set where the target high hydraulic oil temperature is located are determined, and a parameter range determined by the two target thermal characteristic parameters is determined as a thermal characteristic parameter range.
Here, the determining process of the thermal characteristic parameter range may further include constructing a training set and a testing set according to a plurality of historical hydraulic oil temperatures and a plurality of historical pump powers in the target sample set of the excavator to be detected, obtaining a thermal characteristic parameter threshold range determination model by the training model, and then determining the thermal characteristic parameter range by using the thermal characteristic parameter threshold range determination model.
According to the method for detecting the abnormality of the excavator, a plurality of hydraulic oil temperature sample sets are determined based on a plurality of historical hydraulic oil temperatures of the excavator to be detected in a historical working time period; for each hydraulic oil temperature sample set, based on the calculated sample hydraulic oil temperature standard deviation of the hydraulic oil temperature sample set, eliminating abnormal hydraulic oil temperature in the hydraulic oil temperature sample set, and determining a target sample set and target thermal characteristic parameters of the target sample set; determining a thermal characteristic parameter range corresponding to the excavator to be detected based on the historical hydraulic oil temperature in each target sample set and the corresponding target thermal characteristic parameters; acquiring the hydraulic oil temperature and the pump power of the excavator to be detected at each detection moment in a detection time period; determining a hydraulic oil temperature standard deviation and a pump power standard deviation of the excavator to be detected in the detection time period based on the obtained multiple hydraulic oil temperatures and the obtained multiple pump powers respectively; determining thermal characteristic parameters of the excavator to be detected based on the hydraulic oil temperature standard deviation and the pump power standard deviation; and when the thermal characteristic parameters are detected not to belong to the thermal characteristic parameter range corresponding to the excavator to be detected, determining that the excavator to be detected is abnormal.
In this way, the hydraulic oil temperature and the pump power of the excavator to be detected at each detection time in the detection time period are obtained, the hydraulic oil temperature standard deviation and the pump power standard deviation are determined according to the obtained hydraulic oil temperatures and the obtained pump powers, and when the thermal characteristic parameters of the excavator to be detected determined according to the hydraulic oil temperature standard deviation and the pump power standard deviation are detected and do not belong to the corresponding thermal characteristic parameter range of the excavator to be detected, the excavator to be detected is determined to be in an abnormal state. The working state of the excavator to be detected is determined according to the thermal characteristic parameters determined by the standard deviation of the hydraulic oil temperature and the standard deviation of the pump power, the condition that whether the excavator to be detected is abnormal or not is judged mistakenly due to the fact that the hydraulic oil temperature is influenced by environmental factors can be avoided, and the accuracy of detecting the abnormality of the excavator can be improved.
Referring to fig. 4 and 5, fig. 4 is a schematic structural diagram of an excavator abnormality detection device according to an embodiment of the present application, and fig. 5 is a second schematic structural diagram of an excavator abnormality detection device according to an embodiment of the present application. As shown in fig. 4, the detection apparatus 400 includes:
the obtaining module 410 is configured to obtain the hydraulic oil temperature and the pump power of the excavator to be detected at each detection time in the detection time period.
The first determining module 420 is configured to determine a standard deviation of the hydraulic oil temperature and a standard deviation of the pump power of the excavator to be detected in the detection time period based on the obtained multiple hydraulic oil temperatures and multiple pump powers, respectively.
The second determining module 430 is configured to determine a thermal characteristic parameter of the excavator to be detected based on the standard deviation of the hydraulic oil temperature and the standard deviation of the pump power.
A third determining module 440, configured to determine that the excavator to be detected is abnormal when it is detected that the thermal characteristic parameter does not belong to the thermal characteristic parameter range corresponding to the excavator to be detected.
Further, as shown in fig. 5, the detecting apparatus 400 further includes a fourth determining module 450, where the fourth determining module 450 is configured to:
determining a plurality of hydraulic oil temperature sample sets based on a plurality of historical hydraulic oil temperatures of the excavator to be detected in a historical working time period;
for each hydraulic oil temperature sample set, based on the calculated sample hydraulic oil temperature standard deviation of the hydraulic oil temperature sample set, eliminating abnormal hydraulic oil temperature in the hydraulic oil temperature sample set, and determining a target sample set and target thermal characteristic parameters of the target sample set;
and determining the thermal characteristic parameter range corresponding to the excavator to be detected based on the historical hydraulic oil temperature in each target sample set and the corresponding target thermal characteristic parameters.
Further, when the fourth determining module 450 is configured to determine a plurality of hydraulic oil temperature sample sets based on a plurality of historical hydraulic oil temperatures of the excavator to be detected in the historical working time period, the fourth determining module 450 is configured to:
dividing the historical working time period into a plurality of sub-time periods based on a preset time interval;
based on the acquisition time of each historical hydraulic oil temperature, dividing at least one historical hydraulic oil temperature with the acquisition time in the same sub-time period into the same sample set to generate a hydraulic oil temperature sample set.
Further, the fourth determining module 450 is configured to determine the target sample set by:
determining the dispersion of each historical hydraulic oil temperature based on the sample hydraulic oil temperature standard deviation, and determining the historical hydraulic oil temperature with the dispersion larger than a preset dispersion threshold value as a first abnormal hydraulic oil temperature;
determining a starting time period of the excavator to be detected and acquisition time of each historical hydraulic oil temperature, and determining the historical hydraulic oil temperature of the acquisition time in the starting time period as a second abnormal hydraulic oil temperature;
and filtering the determined at least one first abnormal hydraulic oil temperature and at least one second abnormal hydraulic oil temperature from the hydraulic oil temperature sample set to determine a target sample set.
Further, the fourth determination module 450 is configured to determine the target thermal property parameter of the target sample set by:
determining a target pump power standard deviation of the target sample set based on a plurality of historical pump powers in a sub-time period corresponding to the determined target sample set;
determining a target hydraulic oil temperature standard deviation of the target sample set based on a plurality of historical hydraulic oil temperatures from which abnormal hydraulic oil temperatures are filtered;
determining the target thermal property parameter based on the target hydraulic oil temperature standard deviation and the target hydraulic oil temperature standard deviation.
Further, the fourth determining module 450 is configured to determine the thermal property parameter range by:
determining a thermal characteristic parameter standard deviation of the target thermal characteristic parameter based on the target thermal characteristic parameter of each target sample set;
based on the standard deviation of the thermal characteristic parameters, filtering abnormal thermal characteristic parameters from the determined multiple target thermal characteristic parameters, and determining multiple residual thermal characteristic parameters;
determining the highest historical hydraulic oil temperature and the lowest historical hydraulic oil temperature from the target sample set corresponding to each residual characteristic parameter;
determining a target high hydraulic oil temperature and a target low hydraulic oil temperature based on the determined multiple highest historical hydraulic oil temperatures, multiple lowest historical hydraulic oil temperatures and a preset normal hydraulic oil temperature range;
and determining a thermal characteristic parameter range determined by the target thermal characteristic parameter of the target sample set in which the target low hydraulic oil temperature is located and the target thermal characteristic parameter of the target sample set in which the target high hydraulic oil temperature is located as the thermal characteristic parameter range.
The detection device for the abnormality of the excavator, provided by the embodiment of the application, is used for acquiring the hydraulic oil temperature and the pump power of the excavator to be detected at each detection moment in a detection time period; determining a hydraulic oil temperature standard deviation and a pump power standard deviation of the excavator to be detected in the detection time period based on the obtained multiple hydraulic oil temperatures and the obtained multiple pump powers respectively; determining thermal characteristic parameters of the excavator to be detected based on the hydraulic oil temperature standard deviation and the pump power standard deviation; and when the thermal characteristic parameters are detected not to belong to the thermal characteristic parameter range corresponding to the excavator to be detected, determining that the excavator to be detected is abnormal.
In this way, the hydraulic oil temperature and the pump power of the excavator to be detected at each detection time in the detection time period are obtained, the hydraulic oil temperature standard deviation and the pump power standard deviation are determined according to the obtained hydraulic oil temperatures and the obtained pump powers, and when the thermal characteristic parameters of the excavator to be detected determined according to the hydraulic oil temperature standard deviation and the pump power standard deviation are detected and do not belong to the corresponding thermal characteristic parameter range of the excavator to be detected, the excavator to be detected is determined to be in an abnormal state. The working state of the excavator to be detected is determined according to the thermal characteristic parameters determined by the standard deviation of the hydraulic oil temperature and the standard deviation of the pump power, the condition that whether the excavator to be detected is abnormal or not is judged mistakenly due to the fact that the hydraulic oil temperature is influenced by environmental factors can be avoided, and the accuracy of detecting the abnormality of the excavator can be 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 an excavator exception 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 excavator anomaly 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 for detecting abnormality of an excavator, the method comprising:
acquiring the hydraulic oil temperature and the pump power of the excavator to be detected at each detection moment in a detection time period;
determining a hydraulic oil temperature standard deviation and a pump power standard deviation of the excavator to be detected in the detection time period based on the obtained multiple hydraulic oil temperatures and the obtained multiple pump powers respectively;
determining thermal characteristic parameters of the excavator to be detected based on the hydraulic oil temperature standard deviation and the pump power standard deviation;
and when the thermal characteristic parameters are detected not to belong to the thermal characteristic parameter range corresponding to the excavator to be detected, determining that the excavator to be detected is abnormal.
2. The detection method according to claim 1, wherein before the obtaining of the hydraulic oil temperature and the pump power at each detection time within the detection time period of the excavator to be detected, the detection method further comprises:
determining a plurality of hydraulic oil temperature sample sets based on a plurality of historical hydraulic oil temperatures of the excavator to be detected in a historical working time period;
for each hydraulic oil temperature sample set, based on the calculated sample hydraulic oil temperature standard deviation of the hydraulic oil temperature sample set, eliminating abnormal hydraulic oil temperature in the hydraulic oil temperature sample set, and determining a target sample set and target thermal characteristic parameters of the target sample set;
and determining the thermal characteristic parameter range corresponding to the excavator to be detected based on the historical hydraulic oil temperature in each target sample set and the corresponding target thermal characteristic parameters.
3. The detection method according to claim 2, wherein the determining a plurality of hydraulic oil temperature sample sets based on a plurality of historical hydraulic oil temperatures of the excavator to be detected in a historical working time period comprises:
dividing the historical working time period into a plurality of sub-time periods based on a preset time interval;
based on the acquisition time of each historical hydraulic oil temperature, dividing at least one historical hydraulic oil temperature with the acquisition time in the same sub-time period into the same sample set to generate a hydraulic oil temperature sample set.
4. The detection method according to claim 2, wherein the set of target samples is determined by:
determining the dispersion of each historical hydraulic oil temperature based on the sample hydraulic oil temperature standard deviation, and determining the historical hydraulic oil temperature with the dispersion larger than a preset dispersion threshold value as a first abnormal hydraulic oil temperature;
determining a starting time period of the excavator to be detected and acquisition time of each historical hydraulic oil temperature, and determining the historical hydraulic oil temperature of the acquisition time in the starting time period as a second abnormal hydraulic oil temperature;
and filtering the determined at least one first abnormal hydraulic oil temperature and at least one second abnormal hydraulic oil temperature from the hydraulic oil temperature sample set to determine a target sample set.
5. The detection method according to claim 3, wherein the target thermal property parameter of the target sample set is determined by:
determining a target pump power standard deviation of the target sample set based on a plurality of historical pump powers in a sub-time period corresponding to the determined target sample set;
determining a target hydraulic oil temperature standard deviation of the target sample set based on a plurality of historical hydraulic oil temperatures from which abnormal hydraulic oil temperatures are filtered;
determining the target thermal property parameter based on the target hydraulic oil temperature standard deviation and the target hydraulic oil temperature standard deviation.
6. The detection method according to claim 2, wherein the thermal property parameter range is determined by:
determining a thermal characteristic parameter standard deviation of the target thermal characteristic parameter based on the target thermal characteristic parameter of each target sample set;
based on the standard deviation of the thermal characteristic parameters, filtering abnormal thermal characteristic parameters from the determined multiple target thermal characteristic parameters, and determining multiple residual thermal characteristic parameters;
determining the highest historical hydraulic oil temperature and the lowest historical hydraulic oil temperature from the target sample set corresponding to each residual characteristic parameter;
determining a target high hydraulic oil temperature and a target low hydraulic oil temperature based on the determined multiple highest historical hydraulic oil temperatures, multiple lowest historical hydraulic oil temperatures and a preset normal hydraulic oil temperature range;
and determining a thermal characteristic parameter range determined by the target thermal characteristic parameter of the target sample set in which the target low hydraulic oil temperature is located and the target thermal characteristic parameter of the target sample set in which the target high hydraulic oil temperature is located as the thermal characteristic parameter range.
7. An abnormal detection device for an excavator, the abnormal detection device comprising:
the acquisition module is used for acquiring the hydraulic oil temperature and the pump power of the excavator to be detected at each detection moment in the detection time period;
the first determining module is used for determining a hydraulic oil temperature standard deviation and a pump power standard deviation of the excavator to be detected in the detection time period respectively based on the obtained multiple hydraulic oil temperatures and the obtained multiple pump powers;
the second determination module is used for determining the thermal characteristic parameters of the excavator to be detected based on the hydraulic oil temperature standard deviation and the pump power standard deviation;
and the third determining module is used for determining that the excavator to be detected is abnormal when the thermal characteristic parameter is detected not to belong to the thermal characteristic parameter range corresponding to the excavator to be detected.
8. The detection apparatus according to claim 7, further comprising a fourth determination module configured to:
determining a plurality of hydraulic oil temperature sample sets based on a plurality of historical hydraulic oil temperatures of the excavator to be detected in a historical working time period;
for each hydraulic oil temperature sample set, based on the calculated sample hydraulic oil temperature standard deviation of the hydraulic oil temperature sample set, eliminating abnormal hydraulic oil temperature in the hydraulic oil temperature sample set, and determining a target sample set and target thermal characteristic parameters of the target sample set;
and determining the thermal characteristic parameter range corresponding to the excavator to be detected based on the historical hydraulic oil temperature in each target sample set and the corresponding target thermal characteristic parameters.
9. An electronic device, comprising: processor, memory and bus, the memory storing machine-readable instructions executable by the processor, the processor and the memory communicating over the bus when the electronic device is running, the machine-readable instructions when executed by the processor performing the steps of the method of detecting excavator anomalies according to any one of claims 1 to 6.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a computer program which, when being executed by a processor, performs the steps of the method for detecting an abnormality of an excavator according to any one of claims 1 to 6.
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| CN112254972B (en) * | 2020-10-26 | 2023-02-24 | 上海三一重机股份有限公司 | Excavator oil temperature early warning method and device, server and excavator |
| CN113640024B (en) * | 2021-08-09 | 2024-08-20 | 上海华兴数字科技有限公司 | Excavator fault diagnosis method, excavator, electronic device and storage medium |
| CN114440983B (en) * | 2022-04-06 | 2022-10-25 | 常州市瑞德信息科技有限公司 | Equipment and method for measuring and detecting operation state of firework and firecracker gunpowder mechanical |
| CN114646342B (en) * | 2022-05-19 | 2022-08-02 | 蘑菇物联技术（深圳）有限公司 | Method, apparatus, and medium for locating an anomaly sensor |
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| JP3848829B2 (en) * | 2000-11-09 | 2006-11-22 | 三菱重工業株式会社 | Tunnel excavator control device and drive motor abnormality detection device |
| JP4178101B2 (en) * | 2003-12-17 | 2008-11-12 | 日立建機株式会社 | Fault diagnosis device for hydraulic oil cooling system of construction machinery |
| WO2007080835A1 (en) * | 2006-01-12 | 2007-07-19 | Hitachi Construction Machinery Co., Ltd. | Construction machine inspection history information management system |
| CN202090380U (en) * | 2011-04-01 | 2011-12-28 | 长沙中联重工科技发展股份有限公司 | Fault diagnosis system for evacuator |
| CN109898592A (en) * | 2017-12-08 | 2019-06-18 | 江苏曜曜机械科技有限公司 | A kind of excavator method for maintaining |
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| CN110377491A (en) * | 2019-07-10 | 2019-10-25 | 中国银联股份有限公司 | A kind of data exception detection method and device |
| CN110415494A (en) * | 2019-07-25 | 2019-11-05 | 西安因联信息科技有限公司 | A kind of equipment alarm threshold value calculation method based on history data |
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