Method for identifying pump truck with abnormal fuel consumption and method for analyzing abnormal fuel consumption of pump truck

Abstract

The embodiment of the present application provides a kind of method for identifying oil consumption abnormal pump truck and the method for analyzing pump truck oil consumption anomaly, belong to engineering machinery field.The method for identifying oil consumption abnormal pump truck includes: obtaining the working condition data of each pump truck in the same type pump truck machine group in the preset time period, wherein, working condition data includes pumping volume and oil consumption;Determine the volume oil consumption of pump truck according to working condition data;Compare volume oil consumption with volume oil consumption average, wherein, volume oil consumption average is the average of volume oil consumption of pump truck machine group;In the case where the difference between volume oil consumption and volume oil consumption average is greater than the preset value, determine the pump truck as oil consumption abnormal pump truck.The embodiment of the present application can improve identification accuracy.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of engineering machinery, in particular to a method for identifying an oil consumption abnormal pump truck and a method for analyzing oil consumption abnormality of a pump truck. BACKGROUND

[0002] In the field of engineering machinery, the pump truck belongs to high oil consumption engineering machinery, and the oil consumption is an important parameter for measuring the working performance of the pump truck. At present, the important index for measuring the oil consumption of the pump truck is the cubic oil consumption. The existing technology usually compares the cubic oil consumption with the cubic oil consumption range determined according to user experience after obtaining the cubic oil consumption of the pump truck. If the cubic oil consumption is not in the cubic oil consumption range, the pump truck is identified as an oil consumption abnormal pump truck. However, due to the diversity of the construction conditions of the pump truck and the unpredictability of the construction environment, the oil consumption abnormality judgment relying on inherent user experience is prone to misjudgment or omission, and thus there is a problem of low identification accuracy. SUMMARY

[0003] The purpose of the embodiments of the present application is to provide a method for identifying an oil consumption abnormal pump truck, a processor and a device, a method for analyzing oil consumption abnormality of a pump truck, a processor and a device, a pump truck and a storage medium, so as to solve the problem of low identification accuracy existing in the prior art.

[0004] In order to achieve the above-mentioned purpose, the first aspect of the embodiments of the present application provides a method for identifying an oil consumption abnormal pump truck, the method comprising:

[0005] Obtaining working condition data of each pump truck in a pump truck group of the same type within a preset time period, wherein the working condition data comprises a pumping cubic capacity and an oil consumption;

[0006] Determining the cubic oil consumption of the pump truck according to the working condition data;

[0007] Comparing the cubic oil consumption with a cubic oil consumption average value, wherein the cubic oil consumption average value is a mean value of the cubic oil consumption of the pump truck group;

[0008] In the case that the difference between the cubic oil consumption and the cubic oil consumption average value is greater than a preset value, determining that the pump truck is an oil consumption abnormal pump truck.

[0009] In the embodiments of the present application, the preset value is a first preset multiple of the standard deviation of the cubic oil consumption of the pump truck group or a second preset multiple of the quartile distance of the cubic oil consumption of the pump truck group, wherein the first preset multiple is greater than the second preset multiple.

[0010] In the embodiments of the present application, the oil consumption comprises total oil consumption of the pump truck, and the cubic oil consumption comprises total cubic oil consumption; determining the cubic oil consumption of the pump truck according to the working condition data comprises: determining the ratio of the total oil consumption to the pumping cubic capacity to obtain the total cubic oil consumption of the pump truck.

[0011] In the embodiment of the present application, the fuel consumption includes total fuel consumption of the pump truck and driving fuel consumption of the pump truck in a driving state, and the cubic fuel consumption includes driving cubic fuel consumption and working cubic fuel consumption; the cubic fuel consumption of the pump truck is determined according to the working condition data, including: determining a difference between the total fuel consumption and the driving fuel consumption to obtain working fuel consumption of the pump truck in a working state; determining a ratio of the driving fuel consumption to the pumping cubic and a ratio of the working fuel consumption to the pumping cubic to respectively obtain the driving cubic fuel consumption and the working cubic fuel consumption; the cubic fuel consumption average includes driving cubic fuel consumption average and working cubic fuel consumption average; the comparison between the cubic fuel consumption and the cubic fuel consumption average includes: comparing the driving cubic fuel consumption with the driving cubic fuel consumption average; and / or comparing the working cubic fuel consumption with the working cubic fuel consumption average; in the case that a difference between the cubic fuel consumption and the cubic fuel consumption average is greater than a preset value, the pump truck is determined as a fuel consumption abnormal pump truck, including: in the case that a difference between the driving cubic fuel consumption and the driving cubic fuel consumption average is greater than a first preset value, and / or in the case that a difference between the working cubic fuel consumption and the working cubic fuel consumption average is greater than a second preset value, the pump truck is determined as the fuel consumption abnormal pump truck.

[0012] In the embodiment of the present application, the first preset value is a first preset multiple of a standard deviation of the driving cubic fuel consumption of the pump truck group or a second preset multiple of a quartile distance of the driving cubic fuel consumption of the pump truck group; and the second preset value is a first preset multiple of a standard deviation of the working cubic fuel consumption of the pump truck group or a second preset multiple of a quartile distance of the working cubic fuel consumption of the pump truck group, wherein the first preset multiple is greater than the second preset multiple.

[0013] In the embodiment of the present application, the pump truck comprises a pumping system, a boom system and a standby system, the standby system being a system other than the pumping system and the boom system on the pump truck and needing to consume fuel in a working state; the working fuel consumption comprises pumping fuel consumption of the pumping system, boom fuel consumption of the boom system and standby fuel consumption of the standby system; the working volume fuel consumption comprises pumping volume fuel consumption, boom volume fuel consumption and standby volume fuel consumption; the working condition data further comprises engine speed and engine torque in the standby state, total working time, pumping flow corresponding to each oil pump, pumping pressure and working time; the working volume fuel consumption of the pump truck is determined according to the working condition data, comprising: inputting the engine speed and engine torque in the standby state, the total working time, the pumping flow corresponding to each oil pump, the pumping pressure and the working time into a pre-stored fuel consumption distribution model to obtain the pumping fuel consumption, the boom fuel consumption and the standby fuel consumption; determining the ratio of the pumping fuel consumption to the pumping volume, the ratio of the boom fuel consumption to the pumping volume and the ratio of the standby fuel consumption to the pumping volume to obtain the pumping volume fuel consumption, the boom volume fuel consumption and the standby volume fuel consumption respectively; the working volume fuel consumption average comprises pumping volume fuel consumption average, boom volume fuel consumption average and standby volume fuel consumption average; the working volume fuel consumption is compared with the working volume fuel consumption average, comprising: comparing the pumping volume fuel consumption with the pumping volume fuel consumption average; and / or comparing the boom volume fuel consumption with the boom volume fuel consumption average; and / or comparing the standby volume fuel consumption with the standby volume fuel consumption average; in the case that the difference between the working volume fuel consumption and the working volume fuel consumption average is greater than a second preset value, the pump truck is determined to be an abnormal fuel consumption pump truck, comprising: in the case that the difference between the pumping volume fuel consumption and the pumping volume fuel consumption average is greater than a third preset value, and / or in the case that the difference between the boom volume fuel consumption and the boom volume fuel consumption average is greater than a fourth preset value, and / or in the case that the difference between the standby volume fuel consumption and the standby volume fuel consumption average is greater than a fifth preset value, the pump truck is determined to be an abnormal fuel consumption pump truck.

[0014] In the embodiment of the present application, the third preset value is a first preset multiple of the standard deviation of the pumping volume fuel consumption of the pump truck fleet or a second preset multiple of the interquartile distance of the pumping volume fuel consumption of the pump truck fleet; the fourth preset value is a first preset multiple of the standard deviation of the boom volume fuel consumption of the pump truck fleet or a second preset multiple of the interquartile distance of the boom volume fuel consumption of the pump truck fleet; the fifth preset value is a first preset multiple of the standard deviation of the standby volume fuel consumption of the pump truck fleet or a second preset multiple of the interquartile distance of the standby volume fuel consumption of the pump truck fleet, wherein the first preset multiple is greater than the second preset multiple.

[0015] In this embodiment of the invention, the oil pump includes a main oil pump, a distribution pump, and a boom pump. The engine speed and torque during the waiting-for-materials state, the total operating time, the pumping flow rate and pressure corresponding to each oil pump, and the operating time are input into a pre-stored fuel consumption allocation model to obtain pumping fuel consumption, boom fuel consumption, and waiting-for-materials fuel consumption. This includes: determining pumping power consumption based on the pumping flow rate, pumping pressure, and operating time corresponding to the main oil pump and distribution pump; determining boom power consumption based on the pumping flow rate, pumping pressure, and operating time corresponding to the boom pump; determining waiting-for-materials power consumption based on the engine speed and torque during the waiting-for-materials state and the total operating time; and determining pumping fuel consumption, boom fuel consumption, and waiting-for-materials fuel consumption based on the operating fuel consumption, pumping power consumption, boom power consumption, and waiting-for-materials power consumption.

[0016] A second aspect of this invention provides a method for analyzing abnormal fuel consumption of a concrete pump truck, the method comprising:

[0017] Identify pump trucks with abnormal fuel consumption, wherein the pump trucks with abnormal fuel consumption are identified according to the method described above for identifying pump trucks with abnormal fuel consumption;

[0018] Obtain the fuel consumption influencing factor values ​​of each pump truck in the pump truck group of the type to which the pump truck with abnormal fuel consumption belongs within a preset time period;

[0019] The fuel consumption influencing factor index values ​​of pump trucks with abnormal fuel consumption are compared with the average value of the fuel consumption influencing factor index. The average value of the fuel consumption influencing factor index is the average value of the fuel consumption influencing factor index of the pump truck group.

[0020] If the absolute value of the difference between the index value of the fuel consumption influencing factor and the mean value of the fuel consumption influencing factor is greater than a preset threshold, the fuel consumption influencing factor corresponding to the fuel consumption influencing factor index value is determined as the cause of the abnormal fuel consumption of the pump truck.

[0021] In this embodiment of the invention, the preset threshold is a first preset multiple of the standard deviation of the fuel consumption influencing factor index value of the pump truck group or a second preset multiple of the interquartile range of the fuel consumption influencing factor index value of the pump truck group, wherein the first preset multiple is greater than the second preset multiple.

[0022] In this embodiment of the invention, determining the factors influencing fuel consumption includes: acquiring historical operating data of each pump truck in a pump truck group of the same type within a preset time period; performing preliminary screening of the historical operating data to select first operating data related to volume fuel consumption; performing statistical processing on the first operating data to obtain second operating data; training the second operating data based on a machine learning classification algorithm to obtain a fuel consumption model; and determining the input features of the fuel consumption model as the factors influencing fuel consumption.

[0023] In this embodiment of the invention, there are multiple factors affecting fuel consumption, and the method further includes: obtaining the feature coefficients corresponding to each input feature in the fuel consumption model; sorting the values ​​of the feature coefficients to obtain the order of importance of multiple factors affecting fuel consumption.

[0024] In this embodiment of the invention, the factors affecting fuel consumption include at least one of the following: pumping volume per unit engine working time, pumping volume per unit pumping time, fuel consumption per waiting volume, fuel consumption per driving volume, proportion of waiting time, average pumping frequency, average distribution pressure, average pumping pressure, standard deviation of oil temperature, and engine speed fluctuation.

[0025] A third aspect of the present invention provides a processor configured to execute the method described above for identifying pump trucks with abnormal fuel consumption.

[0026] A fourth aspect of the present invention provides a processor configured to execute the method described above for analyzing abnormal fuel consumption of a pump truck.

[0027] A fifth aspect of the present invention provides an apparatus for identifying pump trucks with abnormal fuel consumption, comprising: a working condition data detection device for detecting the working condition data of the pump truck; and a processor according to the above.

[0028] A sixth aspect of the present invention provides an apparatus for analyzing abnormal fuel consumption of a pump truck, comprising: a processor as described above.

[0029] A seventh aspect of the present invention provides a pump truck, comprising: the apparatus for identifying pump trucks with abnormal fuel consumption as described above, or the apparatus for analyzing abnormal fuel consumption of pump trucks as described above.

[0030] An eighth aspect of the present invention provides a machine-readable storage medium storing a program or instructions, which, when executed by a processor, implement the method described above for identifying pump trucks with abnormal fuel consumption or the method described above for analyzing abnormal fuel consumption of pump trucks.

[0031] The above technical solution acquires operating data of each pump truck in a pump truck group of the same type within a preset time period. Based on this data, it determines the pump truck's fuel consumption per cubic meter and compares this consumption with the average fuel consumption per cubic meter. If the difference between the fuel consumption per cubic meter and the average fuel consumption per cubic meter exceeds a preset value, the pump truck is identified as having abnormal fuel consumption. This solution, by acquiring operating data from the pump truck group and comparing the fuel consumption per cubic meter of each pump truck with the average fuel consumption per cubic meter of the group, identifies pump trucks with abnormal fuel consumption based on a large amount of data. This eliminates the need for user experience in judgment, solving the problem of low accuracy in existing technologies that rely on inherent user experience to identify pump trucks with abnormal fuel consumption, and thus improving the accuracy of identifying pump trucks with abnormal fuel consumption.

[0032] Other features and advantages of the embodiments of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0033] The accompanying drawings are provided to further illustrate embodiments of the present invention and form part of the specification. They are used together with the following detailed description to explain the embodiments of the present invention, but do not constitute a limitation thereof. In the drawings:

[0034] Figure 1 The illustration shows a flowchart of a method for identifying pump trucks with abnormal fuel consumption in one embodiment of the present invention.

[0035] Figure 2 The schematic diagram illustrates a process flow chart of a method for identifying pump trucks with abnormal fuel consumption in another embodiment of the present invention;

[0036] Figure 3 The schematic diagram illustrates a process flow chart of a method for analyzing abnormal fuel consumption of a pump truck according to an embodiment of the present invention;

[0037] Figure 4 The schematic diagram illustrates a flowchart of an algorithm for identifying factors influencing fuel consumption in one embodiment of the present invention.

[0038] Figure 5 The schematic diagram illustrates a process flow chart of a method for analyzing abnormal fuel consumption of a pump truck according to another embodiment of the present invention;

[0039] Figure 6 The illustration shows a schematic diagram of data transmission between a pump truck fleet and a cloud platform in one embodiment of the present invention. Detailed Implementation

[0040] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the scope of the present invention.

[0041] Figure 1 The illustration schematically shows a flowchart of a method for identifying pump trucks with abnormal fuel consumption according to an embodiment of the present invention. Figure 1 As shown in the embodiment of the present invention, a method for identifying pump trucks with abnormal fuel consumption is provided, which may include the following steps:

[0042] Step S102: Obtain the operating data of each pump truck in the same type of pump truck group within a preset time period, wherein the operating data includes pumping volume and fuel consumption.

[0043] It is understandable that the preset time period is a pre-set data collection cycle for operating conditions, such as one month. Operating condition data is data that characterizes the actual working status of the pump truck, which may include pumping volume and fuel consumption. Fuel consumption is the amount of fuel consumed, which may include the total fuel consumption of the engine, and the unit may be L. Pumping volume is the volume of concrete pumped by the pump truck, and the unit may be m3. The specific data can be obtained through the chassis control unit or the vehicle control unit.

[0044] Specifically, the processor can obtain the operating data (including pumping volume and fuel consumption) of each pump truck in a group of pump trucks of the same type within a preset time period (e.g., within one month).

[0045] Step S104: Determine the pump truck's fuel consumption based on the operating data.

[0046] It is understandable that the volumetric fuel consumption refers to the amount of fuel consumed by the pump truck for pumping 1 cubic meter of concrete.

[0047] Specifically, the processor can calculate and determine the volumetric fuel consumption of each pump truck based on the fuel consumption and pumping volume in the operating data of each pump truck. That is, the volumetric fuel consumption of each pump truck in the preset time period is obtained by calculating the ratio of fuel consumption in the preset time period to pumping volume in the preset time period.

[0048] Step S106: Compare the volumetric fuel consumption with the average volumetric fuel consumption, where the average volumetric fuel consumption is the average volumetric fuel consumption of the pump truck group.

[0049] It is understandable that the average fuel consumption per cubic meter is the average fuel consumption per cubic meter of all pump trucks in the same type of pump truck group.

[0050] Specifically, after obtaining the volumetric fuel consumption of each pump truck, the processor can calculate the average volumetric fuel consumption of all pump trucks in the pump truck group and compare the volumetric fuel consumption of each pump truck with the average volumetric fuel consumption.

[0051] Step S108: If the difference between the volume fuel consumption and the average volume fuel consumption is greater than a preset value, the pump truck is determined to be a pump truck with abnormal fuel consumption.

[0052] It is understandable that the preset value is a threshold value for the difference between the pre-set volume fuel consumption and the average volume fuel consumption, which can be a value related to the standard deviation of the volume fuel consumption of the pump truck group.

[0053] Specifically, the processor can determine the difference between the volume fuel consumption of each pump truck and the average volume fuel consumption. When the difference is greater than a preset value, that is, when the volume fuel consumption is greater than the average volume fuel consumption and the difference between the two is greater than the preset value, the pump truck corresponding to the volume fuel consumption is determined to be a pump truck with abnormal fuel consumption.

[0054] The aforementioned method for identifying pump trucks with abnormal fuel consumption acquires operating data of each pump truck in a group of pump trucks of the same type over a preset time period. Based on this data, the method determines the pump truck's fuel consumption per cubic meter and compares it to the average fuel consumption per cubic meter. If the difference between the fuel consumption per cubic meter and the average fuel consumption per cubic meter exceeds a preset value, the pump truck is identified as having abnormal fuel consumption. This method, by acquiring operating data from the pump truck group and comparing the fuel consumption per cubic meter of each pump truck with the average fuel consumption per cubic meter of the group, identifies pump trucks with abnormal fuel consumption based on a large amount of data. It eliminates the need for user experience in judgment, thus solving the problem of low accuracy in existing technologies that rely on inherent user experience to identify pump trucks with abnormal fuel consumption, and improving the accuracy of identifying pump trucks with abnormal fuel consumption.

[0055] In one embodiment, the preset value is a first preset multiple of the standard deviation of the pump truck group's volume fuel consumption or a second preset multiple of the interquartile range of the pump truck group's volume fuel consumption, wherein the first preset multiple is greater than the second preset multiple.

[0056] Understandably, when the sample data is large enough, the distribution of volumetric fuel consumption will necessarily conform to a normal distribution. Fuel consumption values ​​within a certain range, either less than or greater than the mean volumetric fuel consumption, will account for a small proportion. Therefore, abnormal volumetric fuel consumption values ​​can be screened out by adding a first preset multiple of the standard deviation of the volumetric fuel consumption to the mean volumetric fuel consumption value, or adding a second preset multiple of the interquartile range of the volumetric fuel consumption value to the mean volumetric fuel consumption value. This allows for the identification of outliers and abnormal fuel consumption values, thereby identifying pump trucks with abnormal fuel consumption. In one embodiment, the range of the first and second preset multiples can include 0 to 6; more specifically, the range of the first preset multiple can include 3 to 6, and the second preset multiple can be 1.5.

[0057] In this embodiment of the invention, the method of selecting preset values ​​can also efficiently filter out abnormal values ​​and outliers in volume fuel consumption, thereby accurately identifying pump trucks with abnormal fuel consumption and further improving the identification accuracy of pump trucks with abnormal fuel consumption.

[0058] In one embodiment, fuel consumption includes the total fuel consumption of the pump truck, and volumetric fuel consumption includes the total volumetric fuel consumption; determining the volumetric fuel consumption of the pump truck based on operating data includes: determining the ratio of total fuel consumption to pumping volume to obtain the total volumetric fuel consumption of the pump truck.

[0059] It is understandable that fuel consumption can include the total fuel consumption of each pump truck, and volumetric fuel consumption can include the total volumetric fuel consumption of each pump truck. The total volumetric fuel consumption is the ratio of the total fuel consumption of the pump truck to the volumetric pumping volume.

[0060] Specifically, the processor can determine the ratio of the total fuel consumption of each pump truck to the pumping volume of each pump truck, thereby obtaining the total fuel consumption of each pump truck.

[0061] In one embodiment, fuel consumption includes the total fuel consumption of the pump truck and the driving fuel consumption of the pump truck in driving mode, and volumetric fuel consumption includes driving volumetric fuel consumption and operating volumetric fuel consumption; determining the volumetric fuel consumption of the pump truck based on operating data includes: determining the difference between total fuel consumption and driving fuel consumption to obtain the operating fuel consumption of the pump truck in operating mode; determining the ratio of driving fuel consumption to pumping volumetric fuel consumption and the ratio of operating fuel consumption to pumping volumetric fuel consumption to obtain driving volumetric fuel consumption and operating volumetric fuel consumption, respectively.

[0062] It is understood that a pump truck can include multiple working states, such as driving state and operation state. The total fuel consumption of a pump truck can be divided into two parts: driving fuel consumption in driving state and operation fuel consumption in operation state. Driving fuel consumption can be determined by calculating the difference between the fuel consumption value at the beginning of the trip and the fuel consumption value at the end of the trip. Driving volume fuel consumption is the amount of fuel consumed by the pump truck to pump 1 cubic meter of concrete during the driving phase, which can be determined by calculating the ratio of driving fuel consumption to pumped volume. Operation volume fuel consumption is the amount of fuel consumed by the pump truck to pump 1 cubic meter of concrete during the operation phase, which can be determined by calculating the ratio of operation fuel consumption to pumped volume.

[0063] Specifically, after knowing the total fuel consumption and the driving fuel consumption, the processor can determine the difference between the total fuel consumption and the driving fuel consumption, thereby obtaining the operating fuel consumption of the pump truck in the working state. Then, it can determine the ratio of driving fuel consumption to pumping volume to obtain the driving volume fuel consumption, and determine the ratio of operating fuel consumption to pumping volume to obtain the operating volume fuel consumption.

[0064] Furthermore, the average volume fuel consumption includes the average volume fuel consumption for driving and the average volume fuel consumption for operation; comparing volume fuel consumption with the average volume fuel consumption includes: comparing driving volume fuel consumption with the average driving volume fuel consumption; and / or comparing operation volume fuel consumption with the average operation volume fuel consumption.

[0065] It is understandable that the average fuel consumption per cubic meter traveled is the average of the fuel consumption per cubic meter traveled by each pump truck in the same type of pump truck group, and the average fuel consumption per cubic meter operating is the average of the fuel consumption per cubic meter operating by each pump truck in the same type of pump truck group.

[0066] Specifically, the processor can compare the fuel consumption per cubic meter of travel of each pump truck with the average fuel consumption per cubic meter of travel, and it can also compare the fuel consumption per cubic meter of operation of each pump truck with the average fuel consumption per cubic meter of operation, or it can simultaneously compare the fuel consumption per cubic meter of travel with the average fuel consumption per cubic meter of travel and the fuel consumption per cubic meter of operation with the average fuel consumption per cubic meter of operation.

[0067] Furthermore, if the difference between the volumetric fuel consumption and the average volumetric fuel consumption is greater than a preset value, the pump truck is determined to be a pump truck with abnormal fuel consumption, including: if the difference between the volumetric fuel consumption during travel and the average volumetric fuel consumption during travel is greater than a first preset value, and / or if the difference between the volumetric fuel consumption during operation and the average volumetric fuel consumption during operation is greater than a second preset value, the pump truck is determined to be a pump truck with abnormal fuel consumption.

[0068] It is understood that the first preset value is a threshold value for the difference between the pre-set fuel consumption per unit volume traveled and the average fuel consumption per unit volume traveled, specifically a value related to the standard deviation of the fuel consumption per unit volume traveled by the pump truck group. The second preset value is a threshold value for the difference between the pre-set fuel consumption per unit volume of operation and the average fuel consumption per unit volume of operation, specifically a value related to the standard deviation of the fuel consumption per unit volume of operation of the pump truck group.

[0069] Specifically, the processor can identify the pump truck corresponding to the travel volume fuel consumption as an abnormal fuel consumption pump truck when the difference between the travel volume fuel consumption and the average travel volume fuel consumption is greater than a first preset value. It can also identify the pump truck corresponding to the operation volume fuel consumption as an abnormal fuel consumption pump truck when the difference between the operation volume fuel consumption and the average operation volume fuel consumption is greater than a second preset value. Furthermore, it can identify the pump truck corresponding to both the travel volume fuel consumption and the operation volume fuel consumption as an abnormal fuel consumption pump truck when both the difference between the travel volume fuel consumption and the average travel volume fuel consumption is greater than the first preset value and the difference between the operation volume fuel consumption and the average operation volume fuel consumption is greater than the second preset value.

[0070] In one embodiment, the first preset value is a first preset multiple of the standard deviation of the pump truck group's travel volume fuel consumption or a second preset multiple of the interquartile range of the pump truck group's travel volume fuel consumption; the second preset value is a first preset multiple of the standard deviation of the pump truck group's operating volume fuel consumption or a second preset multiple of the interquartile range of the pump truck group's operating volume fuel consumption, wherein the first preset multiple is greater than the second preset multiple.

[0071] Understandably, the range of values ​​for the first preset multiple and the second preset multiple can be found in the above embodiments.

[0072] In this embodiment of the invention, by breaking down the total volume fuel consumption into driving volume fuel consumption and operating volume fuel consumption, the identification of pump trucks with abnormal fuel consumption can be achieved more accurately. This allows for a more detailed understanding of the pump truck's abnormal fuel consumption, facilitating a subsequent detailed analysis of the causes of the abnormal fuel consumption.

[0073] In one embodiment, the pump truck includes a pumping system, a boom system, and a material waiting system. When the material waiting system is in operation, it includes other fuel-consuming systems on the pump truck besides the pumping system and boom system. Operating fuel consumption includes pumping fuel consumption of the pumping system, boom fuel consumption of the boom system, and material waiting system fuel consumption. Operating volume fuel consumption includes pumping volume fuel consumption, boom volume fuel consumption, and material waiting volume fuel consumption. Operating data also includes engine speed and torque, total operating time, pumping flow rate of each pump, and pump... The pump truck's fuel consumption is determined based on operating data, including: inputting the engine speed and torque, total operating time, pumping flow rate, pumping pressure, and operating time of each pump into a pre-stored fuel consumption allocation model to obtain pumping fuel consumption, boom fuel consumption, and waiting-for-material fuel consumption; determining the ratio of pumping fuel consumption to pumping volume, the ratio of boom fuel consumption to pumping volume, and the ratio of waiting-for-material fuel consumption to pumping volume, to obtain pumping volume fuel consumption, boom volume fuel consumption, and waiting-for-material volume fuel consumption, respectively.

[0074] It is understood that the operating state of a concrete pump truck can include at least one of the following: pumping system operation, boom system operation, and material waiting system operation. The boom system can include the outrigger system; that is, the boom system can be used to realize boom operation and / or outrigger operation. Specifically, the boom system can realize boom operation, outrigger operation, or both boom and outrigger operation simultaneously. The material waiting system can be any other fuel-consuming system on the pump truck besides the pumping system and boom system (including outriggers) during operation. For example, the material waiting system can include the chassis itself, cooling system, and mixing system. The fuel consumption of the pumping system is the pumping fuel consumption; the fuel consumption of the boom system is the boom fuel consumption; and the fuel consumption of the material waiting system is the material waiting fuel consumption. Pumping volume fuel consumption is the amount of fuel consumed by the pump truck per cubic meter of concrete pumped when the pumping system is operating. This can be determined by calculating the ratio of pumping fuel consumption to pumping volume. Boom volume fuel consumption refers to the amount of fuel consumed by the pump truck to pump 1 cubic meter of concrete when the boom system is in operation. This can be determined by calculating the ratio of boom fuel consumption to pumped volume. Material waiting volume fuel consumption refers to the amount of fuel consumed by the pump truck to pump 1 cubic meter of concrete when the material waiting system is in operation. This can also be determined by calculating the ratio of material waiting fuel consumption to pumped volume. Operating data such as engine speed and torque, total operating time (i.e., the total time the pump truck is in operation), pumping flow rate, pumping pressure, and operating time for each pump can be obtained by reading data from the chassis controller and vehicle control unit. The pre-stored fuel consumption distribution model is a pre-trained model of the pump truck's fuel consumption distribution. By inputting the actual operating data of the pump truck, this model can output predicted fuel consumption values ​​for each subsystem of the pump truck.

[0075] Specifically, after acquiring operating condition data such as engine speed and torque, total operating time, pumping flow rate, pumping pressure, and operating time of each oil pump under the waiting-for-materials state, the processor can input these data into a pre-stored fuel consumption allocation model to obtain the output results of the fuel consumption allocation model, namely pumping fuel consumption, boom fuel consumption, and waiting-for-materials fuel consumption. This allows the processor to determine the ratio of pumping fuel consumption to pumping volume to obtain pumping volume fuel consumption, the ratio of boom fuel consumption to pumping volume to obtain boom volume fuel consumption, and the ratio of waiting-for-materials fuel consumption to pumping volume to obtain waiting-for-materials volume fuel consumption.

[0076] Furthermore, the average operating volume fuel consumption includes the average pumping volume fuel consumption, the average boom volume fuel consumption, and the average waiting volume fuel consumption; comparing the operating volume fuel consumption with the average operating volume fuel consumption includes: comparing the pumping volume fuel consumption with the average pumping volume fuel consumption; and / or comparing the boom volume fuel consumption with the average boom volume fuel consumption; and / or comparing the waiting volume fuel consumption with the average waiting volume fuel consumption.

[0077] It is understandable that the average pumping volume fuel consumption is the average of the pumping volume fuel consumption of each pump truck in the same type of pump truck group, the average boom volume fuel consumption is the average boom volume fuel consumption of each pump truck in the same type of pump truck group, and the average waiting volume fuel consumption is the average waiting volume fuel consumption of each pump truck in the same type of pump truck group.

[0078] Specifically, the processor can compare only the pumping volume fuel consumption of each pump truck with the average pumping volume fuel consumption, or only the boom volume fuel consumption of each pump truck with the average boom volume fuel consumption, or only the waiting volume fuel consumption of each pump truck with the average waiting volume fuel consumption, or it can compare any two of the following: pumping volume fuel consumption with the average pumping volume fuel consumption, boom volume fuel consumption with the average boom volume fuel consumption, and waiting volume fuel consumption with the average waiting volume fuel consumption, or it can compare all three, in order to improve the accuracy of identifying pump trucks with abnormal fuel consumption.

[0079] Furthermore, if the difference between the working volume fuel consumption and the average working volume fuel consumption is greater than a second preset value, the pump truck is determined to be a pump truck with abnormal fuel consumption, including: if the difference between the pumping volume fuel consumption and the average pumping volume fuel consumption is greater than a third preset value, and / or if the difference between the boom volume fuel consumption and the average boom volume fuel consumption is greater than a fourth preset value, and / or if the difference between the waiting volume fuel consumption and the average waiting volume fuel consumption is greater than a fifth preset value, the pump truck is determined to be a pump truck with abnormal fuel consumption.

[0080] It is understandable that the third preset value is a threshold value for the difference between the pre-set pumping volume fuel consumption and the average pumping volume fuel consumption, specifically a value related to the standard deviation of the pumping volume fuel consumption of the pump truck group. The fourth preset value is a threshold value for the difference between the pre-set boom volume fuel consumption and the average boom volume fuel consumption, specifically a value related to the standard deviation of the boom volume fuel consumption of the pump truck group. The fifth preset value is a threshold value for the difference between the pre-set material waiting volume fuel consumption and the average material waiting volume fuel consumption, specifically a value related to the standard deviation of the material waiting volume fuel consumption of the pump truck group.

[0081] Specifically, the processor can identify the pump truck with abnormal pumping volume oil consumption as an abnormal pump truck when the difference between the pumping volume oil consumption and the average pumping volume oil consumption is greater than a third preset value; it can also identify the pump truck with abnormal boom volume oil consumption as an abnormal pump truck when the difference between the boom volume oil consumption and the average boom volume oil consumption is greater than a fourth preset value; it can also identify the pump truck with abnormal waiting volume oil consumption as an abnormal pump truck when the difference between the waiting volume oil consumption and the average waiting volume oil consumption is greater than a fifth preset value; and it can also identify the pump truck with abnormal oil consumption when at least two of the following three conditions are met: the difference between the pumping volume oil consumption and the average pumping volume oil consumption is greater than the third preset value, the difference between the boom volume oil consumption and the average boom volume oil consumption is greater than the fourth preset value, and the difference between the waiting volume oil consumption and the average waiting volume oil consumption is greater than the fifth preset value.

[0082] In one embodiment, the third preset value is a first preset multiple of the standard deviation of the pumping volume fuel consumption of the pump truck group or a second preset multiple of the interquartile range of the pumping volume fuel consumption of the pump truck group; the fourth preset value is a first preset multiple of the standard deviation of the boom volume fuel consumption of the pump truck group or a second preset multiple of the interquartile range of the boom volume fuel consumption of the pump truck group; the fifth preset value is a first preset multiple of the standard deviation of the waiting volume fuel consumption of the pump truck group or a second preset multiple of the interquartile range of the waiting volume fuel consumption of the pump truck group, wherein the first preset multiple is greater than the second preset multiple.

[0083] Understandably, the range of values ​​for the first preset multiple and the second preset multiple can be found in the above embodiments.

[0084] In this embodiment of the invention, by further decomposing the operating fuel consumption into pumping fuel consumption, boom fuel consumption, and waiting fuel consumption, the abnormal fuel consumption of the pump truck can be accurately identified based on the fuel consumption and volume fuel consumption of each subsystem of the pump truck. This allows for a more comprehensive understanding of the abnormal fuel consumption of the pump truck, facilitating a more accurate analysis of the causes of the abnormal fuel consumption in subsequent pump truck operations.

[0085] In one embodiment, the oil pumps include a main oil pump, a distributor pump, and a boom pump. The engine speed and torque during the waiting-for-materials state, the total operating time, the pumping flow rate and pressure corresponding to each oil pump, and the operating time are input into a pre-stored fuel consumption allocation model to obtain pumping fuel consumption, boom fuel consumption, and waiting-for-materials fuel consumption. This includes: determining pumping power consumption based on the pumping flow rate, pumping pressure, and operating time corresponding to the main oil pump and distributor pump; determining boom power consumption based on the pumping flow rate, pumping pressure, and operating time corresponding to the boom pump; determining waiting-for-materials power consumption based on the engine speed and torque during the waiting-for-materials state and the total operating time; and determining pumping fuel consumption, boom fuel consumption, and waiting-for-materials fuel consumption based on the operating fuel consumption, pumping power consumption, boom power consumption, and waiting-for-materials power consumption.

[0086] Specifically, the processor can determine the main oil pump power consumption based on the pumping flow rate, pumping pressure, and operating time of the main oil pump, and determine the distribution pump power consumption based on the pumping flow rate, pumping pressure, and operating time of the distribution pump. The sum of the main oil pump power consumption and the distribution pump power consumption is determined as the pumping power consumption. Then, the boom power consumption is determined based on the pumping flow rate, pumping pressure, and operating time of the boom pump. Taking the main oil pump power consumption as an example, the specific calculation formulas can be the following formulas (1) and (2):

[0087] W mo =P mo ·T mo Formula (1)

[0088] P mo =Q mo ·Δρ mo / (60·η) Formula (2)

[0089] Among them, W mo Main oil pump power consumption, P mo Main oil pump power, T mo The operating time of the main oil pump, Q mo The pumping flow rate of the main oil pump, Δρ mo The pumping pressure of the main oil pump is η, and the preset efficiency is η (for example, an empirical value of 0.95 can be taken).

[0090] Similarly, the calculation methods for the power consumption of the distribution pump and the boom are similar to those for the main oil pump, and will not be repeated here.

[0091] The calculation of power consumption while waiting for material can be done by first determining the power consumption while waiting for material based on the engine speed and engine torque under the waiting state, and then determining the power consumption while waiting for material based on the power consumption while waiting for material and the total operating time of the pump truck. Specifically, the power consumption while waiting for material can be calculated by the following formula (3) based on the engine speed and engine torque under the waiting state:

[0092] Pi =n i ·M i / 9550 formula(3)

[0093] Among them, P i n represents the power required to supply materials. i M represents engine speed. i This refers to engine torque.

[0094] Understandably, by determining the power of the accessories corresponding to the material receiving system in advance based on the engine speed and torque of the pump truck in the material receiving state, unnecessary calculations can be reduced and the calculation process can be accelerated.

[0095] Determining pumping fuel consumption, boom power consumption, and waiting-for-material fuel consumption based on operating fuel consumption, pumping power consumption, boom power consumption, and waiting-for-material fuel consumption can include: determining the sum of pumping power consumption, boom power consumption, and waiting-for-material fuel consumption to obtain the operating power consumption of the pump truck in operation; determining a first ratio of pumping power consumption to operating power consumption, a second ratio of boom power consumption to operating power consumption, and a third ratio of waiting-for-material fuel consumption to operating power consumption; determining the product of the first ratio and operating fuel consumption as pumping fuel consumption; determining the product of the second ratio and operating fuel consumption as boom fuel consumption; and determining the product of the third ratio and operating fuel consumption as waiting-for-material fuel consumption.

[0096] It is understandable that by calculating the pump truck's operating power consumption in the working state based on the pumping power consumption, boom power consumption, and waiting power consumption, the proportion of each subsystem's power consumption to the total operating power consumption can be calculated. This proportion is the fuel consumption proportion of each subsystem, and thus the corresponding fuel consumption of each subsystem can be determined.

[0097] In a specific embodiment, such as Figure 2 As shown, the method for identifying pump trucks with abnormal fuel consumption may include the following steps:

[0098] Step S201: Based on the raw data from the cloud platform, extract data such as volume and fuel consumption of all devices of the same model within the time period T.

[0099] Step S202: Clean the acquired data and, after data preprocessing, calculate the comprehensive volume fuel consumption F (and / or the volume fuel consumption of subsystems (pumping volume fuel consumption, boom volume fuel consumption, waiting volume fuel consumption, and driving volume fuel consumption) for each equipment of the same model within the time period T.

[0100] Step S203: Calculate the mean μ (hereinafter referred to as vehicle volume fuel consumption), variance σ (hereinafter referred to as vehicle volume fuel consumption variance), and interquartile range IQR of the comprehensive volume fuel consumption of all equipment under the same vehicle model.

[0101] Step S204: For a single device, identify its vehicle model, then calculate its comprehensive fuel consumption f within the time period T, and calculate the difference Δf between it and the average fuel consumption of the vehicle model.

[0102] Step S205: Compare the size of Δf with n1*σ (or n2*IQR) (n1 and n2 can be any real number between 0 and 6, and n1 > n2).

[0103] Step S206: If Δf>n1*σ (or Δf>n2*IQR), then the equipment is determined to have high fuel consumption, and proceed to the next step of diagnosing the cause of abnormally high fuel consumption; otherwise, continue to diagnose the next piece of equipment.

[0104] In existing technologies, the methods for analyzing the causes of abnormal fuel consumption in concrete pump trucks typically involve: when high fuel consumption is found in the total volume of a certain piece of equipment, experts usually check the average values ​​of real-time operating data such as pumping pressure and engine speed, and then combine this with on-site construction material conditions and experience to determine the approximate cause of the abnormal fuel consumption. Therefore, existing technologies for diagnosing and analyzing abnormal fuel consumption rely too heavily on user experience and have low accuracy.

[0105] To solve the above problems, Figure 3 This schematic diagram illustrates a flowchart of a method for analyzing abnormal fuel consumption of a pump truck according to an embodiment of the present invention, as shown below. Figure 3 As shown in this embodiment of the invention, a method for analyzing abnormal fuel consumption of a pump truck is provided, which may include the following steps:

[0106] Step S302: Identify pump trucks with abnormal fuel consumption.

[0107] Specifically, pump trucks with abnormal fuel consumption can be identified using the method described in the above embodiments.

[0108] Step S304: Obtain the fuel consumption influencing factor index values ​​of each pump truck in the pump truck group of the type to which the pump truck with abnormal fuel consumption belongs within a preset time period.

[0109] It is understandable that the fuel consumption influencing factor index value is the corresponding index value of the main factors affecting the fuel consumption of pump trucks, such as the proportion of waiting time, the volume pumped per unit engine working time, and the volume pumped per unit pumping time.

[0110] Specifically, the processor can obtain the operating data of each pump truck in the pump truck group of the type of pump truck with abnormal fuel consumption within a preset time period. By preprocessing the operating data, the value of the fuel consumption influencing factor index can be obtained. Specifically, the operating data can be cleaned first to remove erroneous data, and then the value of the fuel consumption influencing factor index can be calculated based on the cleaned operating data.

[0111] Step S306: Compare the fuel consumption influencing factor index values ​​of the pump truck with the average value of the fuel consumption influencing factor index, wherein the average value of the fuel consumption influencing factor index is the average value of the fuel consumption influencing factor index of the pump truck group.

[0112] It is understandable that the average value of the fuel consumption influencing factor index is the average value of each fuel consumption influencing factor index of all pump trucks in the same type of pump truck group.

[0113] Specifically, after obtaining the fuel consumption influencing factor index values ​​of each pump truck, the processor can calculate the average value of the fuel consumption influencing factor index values ​​of all pump trucks in the pump truck group, and compare the fuel consumption influencing factor index values ​​of each pump truck with the average value of the fuel consumption influencing factor index.

[0114] Step S308: If the absolute value of the difference between the value of the fuel consumption influencing factor index and the average value of the fuel consumption influencing factor index is greater than a preset threshold, the fuel consumption influencing factor corresponding to the value of the fuel consumption influencing factor index is determined as the cause of the abnormal fuel consumption of the pump truck.

[0115] It is understandable that the preset threshold is the threshold of the difference between the pre-set value of the fuel consumption influencing factor index and the mean value of the fuel consumption influencing factor index. Specifically, it can be a value related to the standard deviation of the fuel consumption influencing factor index value of the pump truck group.

[0116] Specifically, the processor can determine the difference between the value of the fuel consumption influencing factor index of each pump truck and the average value of the fuel consumption influencing factor index. When the absolute value of the difference is greater than a preset threshold, the fuel consumption influencing factor corresponding to the fuel consumption influencing factor index value is determined as the cause of the abnormal fuel consumption of the pump truck.

[0117] The method described above for analyzing abnormal fuel consumption of pump trucks involves identifying pump trucks with abnormal fuel consumption, obtaining the fuel consumption influencing factor index values ​​of each pump truck in the pump truck group of the type to which the pump truck with abnormal fuel consumption belongs within a preset time period, and comparing the fuel consumption influencing factor index values ​​of the pump trucks with abnormal fuel consumption with the average value of the fuel consumption influencing factor index. If the absolute value of the difference between the fuel consumption influencing factor index value and the average value of the fuel consumption influencing factor index is greater than a preset threshold, the fuel consumption influencing factor corresponding to the fuel consumption influencing factor index value is determined as the cause of the abnormal fuel consumption of the pump truck. The above method obtains the index values ​​of fuel consumption influencing factors of the pump truck fleet and compares the index values ​​of fuel consumption influencing factors of pump trucks with abnormal fuel consumption with the average index values ​​of fuel consumption influencing factors of the pump truck fleet. Based on a large amount of data, it identifies and analyzes the causes of abnormal fuel consumption. It does not rely on user experience for judgment, which solves the problem of low accuracy in the analysis of abnormal fuel consumption of pump trucks caused by relying on inherent user experience in the existing technology. It reduces the dependence on user experience and improves the accuracy of the diagnosis and analysis of abnormal fuel consumption of pump trucks, so as to make improvements based on the causes of abnormality and reduce equipment fuel consumption.

[0118] In one embodiment, the preset threshold is a first preset multiple of the standard deviation of the fuel consumption influencing factor index value of the pump truck group or a second preset multiple of the interquartile range of the fuel consumption influencing factor index value of the pump truck group, wherein the first preset multiple is greater than the second preset multiple.

[0119] Understandably, when the sample data is large enough, the distribution of fuel consumption influencing factor values ​​will inevitably follow a normal distribution. Values ​​within a certain range that are less than or greater than the mean of the fuel consumption influencing factor values ​​will account for a small proportion. Therefore, abnormal values ​​of the fuel consumption influencing factor values ​​can be screened out by using either a first preset multiple of the standard deviation of the fuel consumption influencing factor values ​​plus the mean of the fuel consumption influencing factor values, or a second preset multiple of the interquartile range of the fuel consumption influencing factor values ​​plus the mean of the fuel consumption influencing factor values. This allows for the identification of outliers and abnormal values, thereby analyzing the causes of abnormal fuel consumption in the pump truck. In one embodiment, the range of the first and second preset multiples can include 0 to 6; more specifically, the range of the first preset multiple can include 3 to 6, and the second preset multiple can be 1.5.

[0120] In this embodiment of the invention, the method of selecting the preset threshold can also efficiently screen out the abnormal values ​​and outliers of the fuel consumption influencing factor index, thereby accurately diagnosing and analyzing the abnormal causes of the pump truck with abnormal fuel consumption.

[0121] In one embodiment, determining the factors influencing fuel consumption includes: acquiring historical operating data of each pump truck in a group of pump trucks of the same type within a preset time period; performing preliminary screening of the historical operating data to identify first operating data related to volume fuel consumption; performing statistical processing on the first operating data to obtain second operating data; training the second operating data based on a machine learning classification algorithm to obtain a fuel consumption model; and determining the input features of the fuel consumption model as the factors influencing fuel consumption.

[0122] It is understandable that fuel consumption factors are the main factors affecting abnormal fuel consumption of pump trucks. Historical operating data refers to the operating data of the pump truck over a certain period of time in the past, which may include, but is not limited to, cumulative data such as pumping volume, total engine fuel consumption, pumping fuel consumption, waiting fuel consumption, boom fuel consumption, driving fuel consumption, working time, and pumping time, as well as real-time data such as pumping status, pumping pressure, engine speed, pumping gear, pressure distribution, and speed fluctuations. The first operating data is the data related to volume and fuel consumption from the historical operating data. The second operating data is the data obtained after statistical processing of the first operating data. Statistical processing may include, but is not limited to, the calculation of statistical values ​​such as mean, median, skewness coefficient, extreme values, standard deviation, and upper and lower quartiles.

[0123] Specifically, the processor can acquire historical operating data of each pump truck in the same type of pump truck group within a preset time period (e.g., within 3 months), and perform preliminary screening on this historical operating data to filter out the first operating data related to volume fuel consumption. Then, the first operating data is subjected to statistical processing, such as calculating the average value or standard deviation, to obtain the second operating data. Based on a machine learning classification algorithm, the second operating data is input into a preset preliminary model for training. When the accuracy of the trained model reaches the preset accuracy, the trained model is the fuel consumption model, and the input features of the fuel consumption model are the fuel consumption influencing factors.

[0124] In one embodiment, there are multiple factors affecting fuel consumption. The method for analyzing abnormal fuel consumption of pump trucks may further include: obtaining the feature coefficients corresponding to each input feature in the fuel consumption model; and sorting the values ​​of the feature coefficients to obtain the order of importance of multiple factors affecting fuel consumption.

[0125] Understandably, the input features of the fuel consumption model are the factors affecting fuel consumption, and the feature coefficients are the model parameters corresponding to the input features in the fuel consumption model. Therefore, if we want to rank the importance of the factors affecting fuel consumption, we can obtain the feature coefficients corresponding to each input feature in the fuel consumption model and sort the feature coefficients from largest to smallest to obtain the order of importance of multiple factors affecting fuel consumption.

[0126] Furthermore, in some embodiments, the fuel consumption influencing factor index value of the pump truck with abnormal fuel consumption is compared with the average value of the fuel consumption influencing factor index, including: comparing the fuel consumption influencing factor index value of the pump truck with the average value of the fuel consumption influencing factor index in order of importance of multiple fuel consumption influencing factors.

[0127] Understandably, the causes of abnormal indicators are sorted according to the importance of factors affecting fuel consumption, so that the causes of abnormalities can be addressed sequentially based on their importance.

[0128] In one embodiment, the factors affecting fuel consumption include at least one of the following: pumping volume per unit engine working time, pumping volume per unit pumping time, fuel consumption per waiting volume, fuel consumption per driving volume, percentage of waiting time, average pumping frequency, average distribution pressure, average pumping pressure, standard deviation of oil temperature, and engine speed fluctuation.

[0129] In a specific embodiment, such as Figure 4 As shown, the algorithm for identifying factors influencing fuel consumption is as follows:

[0130] Step S401: Based on the raw data uploaded by the equipment to the cloud platform, extract the cumulative data such as pumping volume, total engine fuel consumption, pumping fuel consumption, waiting fuel consumption, boom fuel consumption, driving fuel consumption, working time, and pumping time of the same model equipment, as well as real-time data such as pumping status, pumping pressure, engine speed, pumping gear, distribution pressure, and speed fluctuation.

[0131] Step S402: Clean the acquired data. After completing the data preprocessing, take the statistical values ​​of the real-time data within the time period T, such as the mean, median, skewness coefficient, extreme values, standard deviation, and upper and lower quartiles. Segment and summarize the cumulative data according to the time period T.

[0132] Step S403: Extract the cumulative data of the pumping volume, total engine fuel consumption, pumping fuel consumption, waiting fuel consumption, boom fuel consumption, driving fuel consumption, working time, pumping time, etc. of the same model equipment, as well as the real-time data of pumping status, pumping pressure, distribution pressure, pumping gear, engine speed, engine speed fluctuation, etc., and calculate the total volume fuel consumption, pumping volume fuel consumption, waiting fuel consumption, boom volume fuel consumption, driving fuel consumption, waiting time percentage, pumping speed, etc.

[0133] Step S404: Use correlation analysis, independence hypothesis testing and other methods to conduct preliminary correlation analysis on the relevant data in Step 3, and select the working condition data related to total volume fuel consumption as input features of the fuel consumption model.

[0134] Step S405: Divide the total fuel consumption into different intervals and name the values ​​falling into different intervals (e.g., high, medium, low fuel consumption) as labels for the classification model.

[0135] Step S406: Train the fuel consumption model using the input features and label data based on the machine learning classification algorithm, identify the most important influencing factors on total fuel consumption, and rank the influencing factors from largest to smallest according to their importance.

[0136] Step S407: Output the top 10 importance rankings of factors affecting total fuel consumption: volume pumped per unit engine working time, volume pumped per unit pumping time, fuel consumption per unit waiting volume, fuel consumption per unit driving volume, percentage of waiting time, average pumping frequency, average distribution pressure, average pumping pressure, standard deviation of oil temperature, and engine speed fluctuation. For example, total volume fuel consumption = fuel consumption over a period of time / volume pumped over a period of time, i.e., fuel consumption required per cubic meter of concrete pumped; average pumping pressure = the average pumping pressure under pumping conditions over a period of time, and the calculation methods for other operating conditions are similar.

[0137] In one specific embodiment, after determining that the fuel consumption is abnormally high, a fuel consumption anomaly diagnostic model is established based on the main influencing factors of fuel consumption identified by the fuel consumption anomaly influencing factor mining model to diagnose the cause of the fuel consumption anomaly, such as... Figure 5 As shown, the method for analyzing abnormal fuel consumption of pump trucks may include the following steps:

[0138] Step S501: Based on the original data from the cloud platform, extract the fuel consumption influencing factor data for all devices of the same model within the time period T.

[0139] Step S502: Clean the acquired data, and after completing the data preprocessing, calculate the fuel consumption influencing factor data for each device of the same model within the time period T.

[0140] Step S503: Calculate the mean X, standard deviation σ, and interquartile range (IQR) of all fuel consumption influencing factors for all equipment under the same vehicle model.

[0141] Step S504: For devices with abnormal fuel consumption, identify the vehicle model to which they belong, then calculate the fuel consumption influencing factor index x within the time period T, and compare it with the vehicle model index average X in turn to diagnose the cause.

[0142] Step S505: Rank the influencing factors by importance, and calculate the absolute value of the difference |Δxi| between each influencing factor xi of the device with abnormal fuel consumption and the average value Xi of the vehicle model index.

[0143] Step S506: Compare the size of |Δxi| with n1*σ (or n2*IQR) (n1 and n2 can be any real number between 0 and 6, and n1>n2).

[0144] Step S507: If |Δxi|>n1*σ (or |Δxi|>n2*IQR), then the influencing factor is determined to be one of the factors affecting the high fuel consumption of the equipment, and the process continues to determine the next influencing factor until all influencing factors have been determined.

[0145] Step S508: After comparing all abnormal influencing factors, output the indicators and causes of the high fuel consumption anomaly of the equipment within time period T.

[0146] Step S509: Rank the causes of abnormal indicators according to the importance of factors affecting fuel consumption, automatically output suggested measures and solutions, guide technical improvements, and ultimately reduce equipment fuel consumption.

[0147] In one specific embodiment, taking a concrete pump truck as an example, Figure 6 This illustration schematically shows a data transmission diagram between a pump truck fleet and a cloud platform in one embodiment of the present invention. For example... Figure 6As shown, each pump truck may include a communication unit, a computing unit, and a transmission unit. The communication unit reads data from the chassis ECU and vehicle control unit via a fieldbus. The chassis ECU data includes: total engine fuel consumption F, engine speed W, and mileage S. The vehicle control unit data includes: pumping status, boom status, pumping pressure, pumping gear, distribution pressure, pumping volume, pumping time, waiting time, boom time, operating time, and oil pump flow rate. Based on the data received by the communication unit, the computing unit calculates and breaks down the total engine fuel consumption of the pump truck, dividing it into four subsystems: pumping fuel consumption, waiting fuel consumption, mileage fuel consumption, and boom fuel consumption. The volume fuel consumption of each subsystem can be obtained by calculating the power consumption of each subsystem. Specifically, the calculation process for pumping fuel consumption, boom fuel consumption, and waiting fuel consumption is as follows;

[0148] 1) Pumping power consumption calculation

[0149] The pumping system is driven by a main oil pump and a distribution pump, so the power of the two oil pumps needs to be calculated.

[0150] Main oil pump power (KW): P mo =Q mo ·Δρ mo / (60·η); where Q mo Flow rate L / min, Δρ mo The main pump pressure is MPa, and η is the efficiency, which is taken as 0.95 based on industry experience.

[0151] Main oil pump power consumption: W mo =P mo ·T mo Among them, T mo Main oil pump operating time (in seconds).

[0152] Distribution pump power (KW): P ao =Q ao ·Δρ ao / (60·η); where Q ao Flow rate L / min, Δρ ao The distribution pressure is MPa, and η is the efficiency, with an industry experience value of 0.95.

[0153] Distribution pump power consumption: W ao =P ao ·T ao Among them, T ao To allocate pump operating time (in seconds), both pump flow rate and pressure can be detected by sensors.

[0154] 2) Boom power consumption calculation

[0155] The formulas for power and power consumption are similar:

[0156] Boom pump power (KW): P bo =Q bo ·Δρ bo / (60·η); where Q bo Flow rate L / min, Δρ bo The main pump pressure is MPa, and η is the efficiency, which is taken as 0.95 based on industry experience.

[0157] Boom pump power consumption: W bo =P bo ·T bo Among them, T bo The operating time of the boom pump is measured in seconds (s). Both the pump flow rate and pressure can be detected by sensors.

[0158] 3) Calculation of power consumption while waiting for materials

[0159] The power consumption during the waiting period involves multiple systems, including the chassis itself, cooling, and agitation, and is a long-term power consumption. However, its calculation is complex, so a common method is to measure it by reading the engine speed and torque under the waiting state (not in boom or pumping state). The waiting power P is then calculated. i =n i ·M i / 9550,n i Engine speed (RPM, M) under waiting conditions i Engine torque (N·m) under the condition of waiting for fuel.

[0160] Therefore, the power consumption is: W i =P i ·T i T i The time taken for the operation is measured in seconds (S).

[0161] Since the pumping system, boom system, and waiting system often operate simultaneously and consume fuel synchronously, this invention provides a calculation method based on power consumption decomposition to decompose the total fuel consumption into different operating states.

[0162] Assume the total fuel consumption of the engine is L all (Unit: L, which can be read directly from the engine ECU), the fuel consumption under different operating conditions is calculated as follows:

[0163] 1) Fuel consumption (L) d This refers to the fuel consumption of the pumping equipment during operation, which can be directly read from the engine ECU (controller). (Calculation method: Let the fuel consumption at the beginning of operation be L.) all-1 The fuel consumption value at the end of the driving phase is L. all-2 Then the fuel consumption is L d =L all-2 -L all-1 )

[0164] 2) Operating fuel consumption: This is the total engine fuel consumption minus the driving fuel consumption, in liters (L). W =L all -L d

[0165] 3) Pumping oil consumption: L p =(W mo +W ao )·L w / (W mo +W ao +W bo +W i ),

[0166] 4) Boom fuel consumption: L b =W bo ·L w / (W mo +W ao +W bo +W i ),

[0167] 5) Fuel consumption while waiting for materials: L i =(W i )·L w / (W mo +W ao +W bo +W i )

[0168] The calculation unit also calculates the engine speed fluctuation within each pumping cycle based on the engine speed. Then, the vehicle control unit transmits the fuel consumption data, speed fluctuation values, and existing data such as engine speed, pumping status, pumping pressure, pumping gear, distribution pressure, and pumping volume to the transmission unit. The transmission unit then transmits the received data and vehicle location information to the cloud platform for storage.

[0169] In some embodiments, the algorithm for mining fuel consumption influencing factors can employ other regression algorithms, classification algorithms, and tree models, etc.

[0170] In some embodiments, in addition to using the method of detecting and identifying abnormally high fuel consumption by subtracting the average fuel consumption of the same model from the fuel consumption of a single device to a value greater than n1 times the standard deviation or n2 times the interquartile range (IQR) (Δf = fF > n1 * σ (or Δf > n2 * IQR)), other thresholds can also be used to make the judgment.

[0171] In some embodiments, in addition to using the difference between the fuel consumption of a single device and the average fuel consumption of the same model being greater than n1 times the standard deviation or n2 times the interquartile range (IQR) (|Δxi|>n1*σ (or |Δxi|>n2*IQR)), other threshold judgments can also be used to diagnose the relevant influencing factors.

[0172] The technical solution provided in this invention obtains relevant operating condition data such as fuel consumption, volume, and engine speed of the equipment over a certain period of time. Then, based on machine learning algorithms such as classification, regression, and correlation analysis, it identifies the main influencing factors affecting the fuel consumption of concrete pump trucks. Based on relevant fuel consumption influencing factors and related data such as single-equipment fuel consumption and average fuel consumption of a group of equipment, a single-equipment fuel consumption anomaly monitoring and diagnosis model is established. Based on this model, when the difference between the volume fuel consumption of the equipment and / or the volume fuel consumption of its subsystems (pumping volume fuel consumption, boom volume fuel consumption, waiting volume fuel consumption, driving volume fuel consumption) over a certain period of time and the average volume fuel consumption (and / or the volume fuel consumption of each subsystem) of all equipment of the same model during the same period of time is greater than a threshold ΔF, it is determined that the fuel consumption of the equipment during this period is abnormally high. If the fuel consumption is abnormally high, it is further checked whether the absolute value of the difference between the values ​​of each relevant influencing factor and the values ​​of the influencing factors of the same model during this period is greater than a threshold ΔXi. If it is higher, the corresponding influencing factor can be determined as the main reason for the high fuel consumption of the equipment during this period. In turn, relevant solutions and suggestions can be provided for the underlying causes and pushed to equipment management personnel (service engineers or customer equipment managers, operators, owners, etc.) to promote normal equipment use and reduce fuel consumption.

[0173] Therefore, compared with the prior art, the technical solution provided by the embodiments of the present invention has the following advantages:

[0174] 1. By employing machine learning, correlation analysis, and hypothesis testing, the top influencing factors affecting abnormally high fuel consumption are identified as the causes for fuel consumption diagnostic analysis. Besides equipment-related anomalies, some of these causes are due to improper operation by personnel or operating faulty equipment, factors not yet identified by current technology.

[0175] 2. Based on big data and cloud computing platforms and technologies, and combined with threshold conditions for the difference between individual equipment and vehicle models, a monitoring and early warning system for abnormally high fuel consumption is established. Furthermore, by integrating relevant fuel consumption influencing factors, a diagnostic system for abnormally high fuel consumption is developed. This system monitors equipment fuel consumption in real time and can issue warnings and provide diagnostic reasons for fuel consumption anomalies when they deviate from the overall equipment group's levels. This guides technical improvements to reduce equipment fuel consumption. Simultaneously, it indirectly reduces the probability of equipment operating with defects and minimizes equipment downtime.

[0176] 3. Fuel consumption distribution model: The total fuel consumption of the engine is broken down into the fuel consumption of each subsystem (pumping fuel consumption, waiting fuel consumption, boom fuel consumption, driving fuel consumption) and uploaded to assist in fuel consumption diagnosis and analysis.

[0177] This invention provides a processor configured to execute the method for identifying pump trucks with abnormal fuel consumption according to the above embodiments.

[0178] This invention provides a processor configured to execute a method for analyzing abnormal fuel consumption of a pump truck according to the above embodiments.

[0179] This invention provides an apparatus for identifying pump trucks with abnormal fuel consumption, comprising: a working condition data detection device for detecting the working condition data of the pump truck; and a processor according to the above embodiments.

[0180] This invention provides an apparatus for analyzing abnormal fuel consumption of pump trucks, comprising: a processor according to the above embodiments.

[0181] This invention provides a pump truck, including: a device for identifying pump trucks with abnormal fuel consumption according to the above embodiments, or a device for analyzing abnormal fuel consumption of pump trucks according to the above embodiments.

[0182] This invention provides a machine-readable storage medium storing a program or instructions. When the program or instructions are executed by a processor, they implement the method for identifying pump trucks with abnormal fuel consumption according to the above embodiments, or the method for analyzing abnormal fuel consumption of pump trucks according to the above embodiments.

[0183] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can 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, etc.) containing computer-usable program code.

[0184] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can 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, generate instructions for implementing the flowchart...Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0185] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0186] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0187] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0188] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0189] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0190] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0191] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method for identifying pump trucks with abnormal fuel consumption, characterized in that, The pump truck includes a pumping system, a boom system, and a material waiting system. The material waiting system refers to other fuel-consuming systems on the pump truck besides the pumping system and boom system during operation. The method includes: The system acquires the operating data of each pump truck in a group of pump trucks of the same type within a preset time period. The operating data includes pumping volume, fuel consumption, engine speed and engine torque in the waiting state, total operating time, pumping flow rate, pumping pressure and operating time of each oil pump. The fuel consumption includes the total fuel consumption of the pump truck and the driving fuel consumption of the pump truck in the driving state. The oil pumps include the main oil pump, the distribution pump and the boom pump. The volumetric fuel consumption of the pump truck is determined based on the operating data, wherein the volumetric fuel consumption includes the operating volumetric fuel consumption, which includes the pumping volumetric fuel consumption of the pumping system, the boom volumetric fuel consumption of the boom system, and the waiting volumetric fuel consumption of the waiting system. The volumetric fuel consumption is compared with the average volumetric fuel consumption, wherein the average volumetric fuel consumption is the average volumetric fuel consumption of the pump truck group, and the average volumetric fuel consumption includes the average operating volumetric fuel consumption, which includes the average pumping volumetric fuel consumption, the average boom volumetric fuel consumption, and the average waiting volumetric fuel consumption. If the difference between the volume fuel consumption and the average volume fuel consumption is greater than a preset value, the pump truck is determined to be a pump truck with abnormal fuel consumption. The step of determining the pump truck's fuel consumption based on the operating data includes: The pumping power consumption is determined based on the pumping flow rate, pumping pressure, and operating time corresponding to the main oil pump and the distribution pump. The boom power consumption is determined based on the pumping flow rate, pumping pressure, and operating time corresponding to the boom pump. The power consumption for waiting for materials is determined based on the engine speed and torque under the waiting state and the total operating time. The pumping fuel consumption of the pumping system, the boom fuel consumption of the boom system, and the waiting fuel consumption of the waiting system are determined based on the operating fuel consumption, the pumping power consumption, the boom power consumption, and the waiting fuel consumption. The operating fuel consumption is the difference between the total fuel consumption and the driving fuel consumption. The operating fuel consumption includes the pumping fuel consumption, the boom fuel consumption, and the waiting fuel consumption. Determine the ratio of pumping oil consumption to pumping volume, the ratio of boom oil consumption to pumping volume, and the ratio of waiting-for-material oil consumption to pumping volume, so as to obtain the pumping volume oil consumption, boom volume oil consumption, and waiting-for-material volume oil consumption, respectively. The step of comparing the volumetric oil consumption with the average volumetric oil consumption includes: comparing the pumping volumetric oil consumption with the average pumping volumetric oil consumption; and / or comparing the boom volumetric oil consumption with the average boom volumetric oil consumption; and / or comparing the waiting volumetric oil consumption with the average waiting volumetric oil consumption. The step of determining the pump truck as an abnormal fuel consumption pump truck when the difference between the pumping volume fuel consumption and the average pumping volume fuel consumption is greater than a preset value includes: determining the pump truck as an abnormal fuel consumption pump truck when the difference between the pumping volume fuel consumption and the average pumping volume fuel consumption is greater than a third preset value, and / or when the difference between the boom volume fuel consumption and the average boom volume fuel consumption is greater than a fourth preset value, and / or when the difference between the waiting volume fuel consumption and the average waiting volume fuel consumption is greater than a fifth preset value.

2. The method according to claim 1, characterized in that, The preset value is a first preset multiple of the standard deviation of the pump truck group's volume fuel consumption or a second preset multiple of the interquartile range of the pump truck group's volume fuel consumption, wherein the first preset multiple is greater than the second preset multiple.

3. The method according to claim 1, characterized in that, The fuel consumption includes the total fuel consumption of the pump truck, and the volumetric fuel consumption includes the total volumetric fuel consumption; determining the volumetric fuel consumption of the pump truck based on the operating data includes: The ratio of the total fuel consumption to the pumping volume is determined to obtain the total fuel consumption of the pump truck.

4. The method according to claim 1, characterized in that, The volumetric fuel consumption also includes the driving volumetric fuel consumption; determining the volumetric fuel consumption of the pump truck based on the operating condition data includes: Determine the ratio of driving fuel consumption to pumping volume and the ratio of operating fuel consumption to pumping volume, so as to obtain the driving volume fuel consumption and the operating volume fuel consumption, respectively. The average fuel consumption per cubic meter also includes the average fuel consumption per cubic meter of driving; comparing the average fuel consumption per cubic meter with the average fuel consumption per cubic meter further includes: Compare the fuel consumption per unit volume with the average fuel consumption per unit volume; and / or Compare the fuel consumption per unit volume of work with the average fuel consumption per unit volume of work. The method of determining the pump truck as having abnormal fuel consumption when the difference between the volumetric fuel consumption and the average volumetric fuel consumption is greater than a preset value further includes: If the difference between the fuel consumption per unit volume traveled and the average fuel consumption per unit volume traveled is greater than a first preset value, and / or if the difference between the fuel consumption per unit volume of work performed and the average fuel consumption per unit volume of work performed is greater than a second preset value, the pump truck is determined to be a pump truck with abnormal fuel consumption.

5. The method according to claim 4, characterized in that, The first preset value is a first preset multiple of the standard deviation of the pump truck group's fuel consumption per unit volume or a second preset multiple of the interquartile range of the pump truck group's fuel consumption per unit volume. The second preset value is a first preset multiple of the standard deviation of the working volume fuel consumption of the pump truck group or a second preset multiple of the interquartile range of the working volume fuel consumption of the pump truck group, wherein the first preset multiple is greater than the second preset multiple.

6. The method according to claim 1, characterized in that, The third preset value is a first preset multiple of the standard deviation of the pumping volume fuel consumption of the pump truck group or a second preset multiple of the interquartile range of the pumping volume fuel consumption of the pump truck group. The fourth preset value is the first preset multiple of the standard deviation of the boom volume fuel consumption of the pump truck group or the second preset multiple of the interquartile range of the boom volume fuel consumption of the pump truck group. The fifth preset value is a first preset multiple of the standard deviation of the fuel consumption of the pump truck group's waiting volume or a second preset multiple of the interquartile range of the fuel consumption of the pump truck group's waiting volume, wherein the first preset multiple is greater than the second preset multiple.

7. A method for analyzing abnormal fuel consumption of pump trucks, characterized in that, The method includes: Identifying pump trucks with abnormal fuel consumption, wherein the pump trucks with abnormal fuel consumption are identified by the method for identifying pump trucks with abnormal fuel consumption according to any one of claims 1 to 6; Obtain the fuel consumption influencing factor values ​​of each pump truck in the pump truck group of the type to which the pump truck with abnormal fuel consumption belongs within a preset time period; The fuel consumption influencing factor index value of the pump truck with abnormal fuel consumption is compared with the average value of the fuel consumption influencing factor index, wherein the average value of the fuel consumption influencing factor index is the average value of the fuel consumption influencing factor index of the pump truck group. If the absolute value of the difference between the value of the fuel consumption influencing factor index and the mean value of the fuel consumption influencing factor index is greater than a preset threshold, the fuel consumption influencing factor corresponding to the value of the fuel consumption influencing factor index is determined as the cause of the abnormal fuel consumption of the pump truck.

8. The method according to claim 7, characterized in that, The preset threshold is a first preset multiple of the standard deviation of the fuel consumption influencing factor index value of the pump truck group or a second preset multiple of the interquartile range of the fuel consumption influencing factor index value of the pump truck group, wherein the first preset multiple is greater than the second preset multiple.

9. The method according to claim 7, characterized in that, The determination of the factors affecting fuel consumption includes: Obtain historical operating data of each pump truck in a group of pump trucks of the same type within a preset time period; The historical operating data is initially screened to identify the first operating data related to fuel consumption per cubic meter. The data under the first working condition are statistically processed to obtain the data under the second working condition. The second working condition data is trained based on a machine learning classification algorithm to obtain a fuel consumption model; The input features of the fuel consumption model are determined as the fuel consumption influencing factors.

10. The method according to claim 9, characterized in that, The number of factors affecting fuel consumption is multiple, and the method further includes: Obtain the feature coefficients corresponding to each input feature in the fuel consumption model; The values ​​of the characteristic coefficients are sorted to obtain the order of importance of the various fuel consumption influencing factors.

11. The method according to claim 7, characterized in that, The factors affecting fuel consumption include at least one of the following: pumping volume per unit engine working time, pumping volume per unit pumping time, fuel consumption per waiting volume, fuel consumption per driving volume, percentage of waiting time, average pumping frequency, average distribution pressure, average pumping pressure, standard deviation of oil temperature, and engine speed fluctuation.

12. A processor, characterized in that, Configured to perform the method for identifying pump trucks with abnormal fuel consumption as described in any one of claims 1 to 6.

13. A processor, characterized in that, It is configured to perform the method for analyzing abnormal fuel consumption of pump trucks as described in any one of claims 7 to 11.

14. A device for identifying pump trucks with abnormal fuel consumption, characterized in that, include: Operating condition data detection equipment is used to detect the operating condition data of pump trucks; as well as The processor according to claim 12.

15. A device for analyzing abnormal fuel consumption of pump trucks, characterized in that, include: The processor according to claim 13.

16. A pump truck, characterized in that, include: The device for identifying pump trucks with abnormal fuel consumption according to claim 14 or the device for analyzing abnormal fuel consumption of pump trucks according to claim 15.

17. A machine-readable storage medium on which a program or instructions are stored, characterized in that, When the program or instructions are executed by the processor, they implement the method for identifying pump trucks with abnormal fuel consumption according to any one of claims 1 to 6, or the method for analyzing abnormal fuel consumption of pump trucks according to any one of claims 7 to 11.

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