Engine post-processing function detection method and device, electronic equipment and engineering machinery

Abstract

The invention relates to the technical field of engines, in particular to an engine aftertreatment function detection method and device, electronic equipment and engineering machinery. Acquiring first current working state data corresponding to the engineering machinery; acquiring second current working state data corresponding to the engine of the engineering machinery; based on the first current working state data and the second current working state data, predicting a current urea consumption predicted value corresponding to the engine; and according to the current urea consumption predicted value, it is determined that post-processing system SCR module data corresponding to the engine is changed. The accuracy of the changed result of the determined data of the SCR module of the aftertreatment system corresponding to the engine can be ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of engines, and in particular to an engine post-processing function detection method, device, electronic equipment and engineering machinery. Background Art

[0002] To meet the National Stage IV emission standards for non-road mobile machinery, modern construction machinery diesel engines are usually equipped with post-treatment modules, among which selective catalytic reduction (SCR) technology is widely used. This technology requires the regular addition of urea to reduce the emission of harmful exhaust gas.

[0003] However, this requirement brings additional maintenance costs. Some users illegally block the engine aftertreatment system SCR (Selective catalytic reduction) module function and change the engine aftertreatment system SCR (Selective catalytic reduction) module data in order to reduce vehicle use costs. Such practices not only increase the risk of complete machine failure, but may also lead to environmental compliance issues.

[0004] Therefore, how to determine whether the SCR module data of the after-treatment system corresponding to the engine has been changed has become an urgent problem to be solved. Summary of the invention

[0005] In view of this, the present invention provides an engine after-treatment function detection method, device, electronic equipment and engineering machinery to solve the problem of how to determine whether the SCR module data of the after-treatment system corresponding to the engine has been changed.

[0006] In a first aspect, the present invention provides a method for detecting an engine post-processing function, the method comprising:

[0007] Acquire first current working state data corresponding to the engineering machinery;

[0008] Acquiring second current working state data corresponding to the engine of the engineering machinery;

[0009] Based on the first current working state data and the second current working state data, predicting a current urea consumption prediction value corresponding to the engine;

[0010] According to the current urea consumption prediction value, it is determined that the after-treatment system SCR module data corresponding to the engine is changed.

[0011] The engine post-processing function detection method provided in the embodiment of the present application obtains the first current working state data corresponding to the engineering machinery; obtains the second current working state data corresponding to the engine of the engineering machinery; based on the first current working state data and the second current working state data, predicts the current urea consumption prediction value corresponding to the engine, thereby ensuring the accuracy of the predicted current urea consumption prediction value corresponding to the engine. According to the current urea consumption prediction value, it is determined that the post-processing system SCR module data corresponding to the engine is changed, thereby ensuring the accuracy of the result that the post-processing system SCR module data corresponding to the engine is changed.

[0012] In an optional implementation, the first current working state data includes the current main pump pressure corresponding to the engineering machinery, the second current working state data includes the current fuel consumption corresponding to the engine and the current upstream nitrogen oxide concentration and the current downstream nitrogen oxide concentration of the SCR module, and based on the first current working state data and the second current working state data, predicting the current urea consumption prediction value corresponding to the engine includes:

[0013] Calculating a current change in nitrogen oxide concentration based on a current upstream nitrogen oxide concentration and a current downstream nitrogen oxide concentration;

[0014] Inputting the current main pump pressure, the current fuel consumption and the current nitrogen oxide concentration change into a preset urea consumption prediction model;

[0015] The preset urea consumption prediction model extracts features of the current main pump pressure, the current fuel consumption and the current change in nitrogen oxide concentration, and outputs the current urea consumption prediction value.

[0016] The engine post-treatment function detection method provided in the embodiment of the present application calculates the current nitrogen oxide concentration change based on the current upstream nitrogen oxide concentration and the current downstream nitrogen oxide concentration, thereby ensuring the accuracy of the calculated current nitrogen oxide concentration change. The current main pump pressure, the current fuel consumption, and the current nitrogen oxide concentration change are input into the preset urea consumption prediction model; the preset urea consumption prediction model extracts features from the current main pump pressure, the current fuel consumption, and the current nitrogen oxide concentration change, and outputs the current urea consumption prediction value, thereby ensuring the accuracy of the output current urea consumption prediction value.

[0017] In an optional implementation, the training process of the preset urea consumption prediction model includes:

[0018] Obtain a training data set; the training data set includes a training main pump pressure, a training fuel consumption, a training nitrogen oxide concentration change, and a corresponding training actual urea consumption; the training actual urea consumption is a label;

[0019] Input the training data set into the initial urea consumption prediction network and output the virtual urea consumption prediction value;

[0020] Calculating a loss function based on the actual urea consumption of the training and the predicted value of the virtual urea consumption;

[0021] The loss function is minimized using a preset method to obtain the target model parameters corresponding to the minimized loss function;

[0022] Based on the target model parameters, the initial model parameters in the initial urea consumption prediction network are updated to generate a preset urea consumption prediction model.

[0023] The engine after-treatment function detection method provided in the embodiment of the present application obtains a training data set; inputs the training data set into the initial urea consumption prediction network, outputs a virtual urea consumption prediction value, and ensures the accuracy of the output virtual urea consumption prediction value. Based on the training actual urea consumption and the virtual urea consumption prediction value, the loss function is calculated to ensure the accuracy of the calculated loss function. The loss function is minimized by a preset method to obtain the target model parameters corresponding to the minimized loss function, and ensure the accuracy of the obtained target model parameters. Based on the target model parameters, the initial model parameters in the initial urea consumption prediction network are updated to generate a preset urea consumption prediction model, and the accuracy of the generated preset urea consumption prediction model is ensured.

[0024] In an optional implementation, a preset method is used to minimize the loss function to obtain target model parameters corresponding to the minimized loss function, including:

[0025] Generate a target matrix according to the training main pump pressure, training fuel consumption and training nitrogen oxide concentration change in the loss function;

[0026] Generate a target vector based on the actual urea consumption trained in the loss function;

[0027] Based on the target matrix and target vector, the target model parameters are calculated.

[0028] The engine post-processing function detection method provided in the embodiment of the present application generates a target matrix according to the training main pump pressure, training fuel consumption and training nitrogen oxide concentration change in the loss function, thereby ensuring the accuracy of the generated target matrix. According to the actual urea consumption trained in the loss function, a target vector is generated, thereby ensuring the accuracy of the generated target matrix equation. Based on the target matrix and the target vector, the target model parameters are calculated, thereby ensuring the accuracy of the obtained target model parameters, thereby ensuring the accuracy of the generated preset urea consumption prediction model.

[0029] In an optional implementation, determining that the post-treatment system SCR module data corresponding to the engine is changed according to the current urea consumption prediction value includes:

[0030] Get the current urea remaining amount corresponding to the engine;

[0031] Based on the current urea remaining amount, determining the actual value of the current urea consumption corresponding to the engine;

[0032] Calculate the difference between the actual urea consumption value and the current urea consumption prediction value;

[0033] According to the difference, it is determined that the SCR module data of the after-treatment system corresponding to the engine is changed.

[0034] The engine post-treatment function detection method provided in the embodiment of the present application obtains the current urea remaining amount corresponding to the engine; based on the current urea remaining amount, the actual value of the current urea consumption corresponding to the engine is determined, thereby ensuring the accuracy of the determined actual value of the current urea consumption corresponding to the engine. The difference between the actual value of urea consumption and the predicted value of current urea consumption is calculated, thereby ensuring the accuracy of the calculated difference. Based on the difference, it is determined that the post-treatment system SCR module data corresponding to the engine has been changed, thereby ensuring the accuracy of the determined post-treatment system SCR module data corresponding to the engine has been changed.

[0035] In an optional implementation, determining, based on the difference, that the post-treatment system SCR module data corresponding to the engine is changed includes:

[0036] If the difference is greater than a first preset difference threshold, it is determined that the data change trend of the post-processing system SCR module corresponding to the engine is abnormal, and a prompt message is output to the user;

[0037] If the difference is greater than a second preset difference threshold, it is determined that the post-processing system SCR module data corresponding to the engine is changed, and an alarm message is output to the user; wherein the second preset difference threshold is greater than the first preset difference threshold.

[0038] The engine post-processing function detection method provided in the embodiment of the present application determines that the data change trend of the post-processing system SCR module corresponding to the engine is abnormal if the difference is greater than the first preset difference threshold, and outputs a prompt message to the user, thereby ensuring the accuracy of the result of the abnormal data change trend of the post-processing system SCR module corresponding to the engine, and outputs a prompt message to the user, so that the user can receive the prompt message. If the difference is greater than the second preset difference threshold, it is determined that the data of the post-processing system SCR module corresponding to the engine is changed, and outputs an alarm message to the user, thereby ensuring the accuracy of the result of the change of the post-processing system SCR module corresponding to the engine, and outputs an alarm message to the user, so that the user can receive the user-output alarm message.

[0039] In an optional implementation, after determining that the post-treatment system SCR module data corresponding to the engine is changed according to the current urea consumption prediction value, the method further includes:

[0040] The engine is controlled using a preset strategy.

[0041] The engine post-processing function detection method provided in the embodiment of the present application adopts a preset strategy to control the engine, thereby preventing further damage to the engineering machinery or non-compliant emissions.

[0042] In a second aspect, the present invention provides an engine post-processing function detection device, the device comprising:

[0043] A first acquisition module, used to acquire first current working state data corresponding to the engineering machinery;

[0044] A second acquisition module, used to acquire second current working state data corresponding to the engine of the engineering machinery;

[0045] A prediction module, used for predicting a current urea consumption prediction value corresponding to the engine based on the first current working state data and the second current working state data;

[0046] The determination module is used to determine whether the SCR module data of the post-treatment system corresponding to the engine is changed according to the current urea consumption prediction value.

[0047] The engine post-processing function detection device provided in the embodiment of the present application obtains the first current working state data corresponding to the engineering machinery; obtains the second current working state data corresponding to the engine of the engineering machinery; based on the first current working state data and the second current working state data, predicts the current urea consumption prediction value corresponding to the engine, thereby ensuring the accuracy of the predicted current urea consumption prediction value corresponding to the engine. According to the current urea consumption prediction value, it is determined that the post-processing system SCR module data corresponding to the engine is changed, thereby ensuring the accuracy of the result that the post-processing system SCR module data corresponding to the engine is changed.

[0048] In a third aspect, the present invention provides an electronic device, comprising: a memory and a processor, the memory and the processor are communicatively connected to each other, computer instructions are stored in the memory, and the processor executes the engine post-processing function detection method of the first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0049] In a fourth aspect, the present invention provides an engineering machinery, comprising: an electronic device, an engine and an engineering machinery body, wherein the electronic device is used to execute the engine post-processing function detection method of the above-mentioned first aspect or any corresponding embodiment thereof.

[0050] In a fifth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the engine post-processing function detection method of the first aspect or any corresponding embodiment thereof.

[0051] In a sixth aspect, the present invention provides a computer program product, comprising computer instructions for causing a computer to execute the engine post-processing function detection method of the first aspect or any corresponding embodiment thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0053] Figure 1 is a flow chart of a first engine post-processing function detection method according to an embodiment of the present invention;

[0054] Figure 2 is a flow chart of a second engine post-processing function detection method according to an embodiment of the present invention;

[0055] Figure 3 is a flow chart of a third engine post-processing function detection method according to an embodiment of the present invention;

[0056] Figure 4 is a structural schematic diagram of an engine post-processing function detection system according to an embodiment of the present invention;

[0057] Figure 5 is a flow chart of a fourth engine post-processing function detection method according to an embodiment of the present invention;

[0058] Figure 6 is a structural block diagram of an engine post-processing function detection device according to an embodiment of the present invention;

[0059] Figure 7 is a structural block diagram of another engine post-processing function detection device according to an embodiment of the present invention;

[0060] Figure 8 It is a schematic diagram of the hardware structure of the electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0061] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0062] To meet the National Stage IV emission standards for non-road mobile machinery, modern construction machinery diesel engines are usually equipped with post-treatment modules, among which selective catalytic reduction (SCR) technology is widely used. This technology requires the regular addition of urea to reduce the emission of harmful exhaust gas.

[0063] However, this requirement brings additional maintenance costs. Some users illegally block the engine aftertreatment system SCR (Selective catalytic reduction) module function and forge the engine aftertreatment system SCR (Selective catalytic reduction) module data to reduce vehicle use costs. Such practices not only increase the risk of whole machine failure, but may also lead to environmental compliance issues.

[0064] To solve these problems, construction machinery manufacturers usually use remote monitoring and local alarm systems to monitor the important parameters of the engine post-processing module. The diesel engine is connected to the whole machine electronic control system through the CAN bus, and the key parameters and fault information of the post-processing module (such as urea residue, SCR (Selective catalytic reduction) module inlet and outlet nitrogen oxide concentration, etc.) are transmitted to the CAN bus in real time, and uploaded to the remote monitoring platform through the on-board TBOX; the key parameters such as urea residue and fault information are displayed in real time through the on-board display, so as to monitor the normal operation and timely maintenance of the post-processing system.

[0065] The whole-machine electronic control CAN bus network of construction machinery manufacturers generally adopts the J1939 public protocol, which makes the data messages in the CAN bus network vulnerable to illegal interference. Some users add additional equipment to the whole-machine CAN bus network, intercept and forge the data messages related to the post-processing module, and send false data to the vehicle terminal device TBOX and display, thereby shielding the remote monitoring and local alarm system. This behavior can deceive the whole-machine electronic control system and remote monitoring platform, making them mistakenly believe that the urea system is operating normally, so that the construction machinery continues to work without adding urea, causing the whole machine to fail and increase the risk of environmental compliance.

[0066] Although the existing remote monitoring solutions and local alarm systems can monitor the key parameters of the after-treatment system of the construction machinery engine in real time, such as the urea residual and the nitrogen oxide concentration at the inlet and outlet of the SCR (Selective catalytic reduction) module.

[0067] However, these solutions are usually unable to effectively detect whether the data has been forged. When the whole machine is working normally, the display and remote monitoring platform may receive forged data. This means that in some cases, the electronic control system of the whole machine of the construction machinery may not be able to detect the data forgery problem in time, and thus cannot take necessary maintenance measures, affecting the normal operation of the engine aftertreatment system and environmental compliance.

[0068] Therefore, how to determine whether the SCR module data of the after-treatment system corresponding to the engine has been changed has become an urgent problem to be solved.

[0069] It should be noted that the execution subject of the method for detecting the engine post-processing function provided in the embodiment of the present application may be a device for detecting the engine post-processing function, and the device for detecting the engine post-processing function may be implemented as part or all of an electronic device through software, hardware, or a combination of software and hardware, wherein the electronic device may be a server or a terminal, wherein the server in the embodiment of the present application may be a single server or a server cluster composed of multiple servers, and the terminal in the embodiment of the present application may be a smart phone, a personal computer, a tablet computer, a wearable device, an intelligent robot, or other intelligent hardware devices. In the following method embodiments, the execution subject is an electronic device as an example for explanation.

[0070] According to an embodiment of the present invention, an embodiment of an engine after-treatment function detection method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0071] In this embodiment, a method for detecting an engine post-processing function is provided, which can be used in the above-mentioned electronic device. Figure 1 : is a flow chart of a method for detecting an engine post-processing function according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps:

[0072] Step S101, obtaining first current working state data corresponding to the construction machinery.

[0073] Specifically, the electronic device can obtain the first current working state data corresponding to the engineering machinery based on the sensor installed in the engineering machinery.

[0074] The first current working state data may include engine speed, oil temperature, oil pressure, water temperature, etc., and may also include the working mode of the engineering machinery, such as excavation, loading, transportation, etc., and may also include load conditions, such as lifting weight, excavation depth, bucket capacity, etc., and may also include the current main pump pressure corresponding to the engineering machinery. The embodiment of the present application does not specifically limit the first current working state data.

[0075] Step S102, obtaining second current working state data corresponding to the engine of the engineering machinery.

[0076] Specifically, the electronic device may be based on installing various sensors on the engine, such as a rotation speed sensor, a temperature sensor, a pressure sensor, etc. These sensors may monitor the second current working state data corresponding to the engine in real time.

[0077] Among them, the second current working status data may include engine speed, oil temperature, oil pressure, current fuel consumption, current upstream nitrogen oxide concentration and current downstream nitrogen oxide concentration of the SCR module, etc. The embodiment of the present application does not specifically limit the second current working status data.

[0078] Step S103: predicting a current urea consumption prediction value corresponding to the engine based on the first current working state data and the second current working state data.

[0079] Specifically, the electronic device can obtain the fitting relationship between the first current working state data, the second current working state data and the current urea consumption prediction value, and then input the first current working state data and the second current working state data into the fitting relationship to determine the current urea consumption prediction value corresponding to the engine.

[0080] This step will be described in detail below.

[0081] Step S104: determining, based on the current urea consumption prediction value, whether the post-treatment system SCR module data corresponding to the engine is modified.

[0082] Specifically, the electronic device may compare the current urea consumption prediction value with the current urea consumption actual value, and then determine, based on the comparison result, that the post-treatment system SCR module data corresponding to the engine is changed.

[0083] This step will be described in detail below.

[0084] The engine post-processing function detection method provided in the embodiment of the present application obtains the first current working state data corresponding to the engineering machinery; obtains the second current working state data corresponding to the engine of the engineering machinery; based on the first current working state data and the second current working state data, predicts the current urea consumption prediction value corresponding to the engine, thereby ensuring the accuracy of the predicted current urea consumption prediction value corresponding to the engine. According to the current urea consumption prediction value, it is determined that the post-processing system SCR module data corresponding to the engine is changed, thereby ensuring the accuracy of the result that the post-processing system SCR module data corresponding to the engine is changed.

[0085] In this embodiment, a method for detecting an engine post-processing function is provided, which can be used in the above-mentioned electronic device. Figure 2 : is a flow chart of a method for detecting an engine post-processing function according to an embodiment of the present invention. Figure 2 As shown, the process includes the following steps:

[0086] Step S201, obtaining first current working state data corresponding to the construction machinery.

[0087] For details about this step, please refer to the above description of step S101, which will not be elaborated here.

[0088] Step S202, obtaining second current working state data corresponding to the engine of the engineering machinery.

[0089] For details about this step, please refer to the above description of step S102, which will not be elaborated here.

[0090] Step S203: predicting a current urea consumption prediction value corresponding to the engine based on the first current working state data and the second current working state data.

[0091] Specifically, the first current working state data includes the current main pump pressure corresponding to the engineering machinery, and the second current working state data includes the current fuel consumption corresponding to the engine and the current upstream nitrogen oxide concentration and the current downstream nitrogen oxide concentration of the SCR module. The above step S203 may include the following steps:

[0092] Step S2031, calculating the current change in nitrogen oxide concentration based on the current upstream nitrogen oxide concentration and the current downstream nitrogen oxide concentration.

[0093] Specifically, the electronic device may calculate the current change in nitrogen oxide concentration by subtracting the current upstream nitrogen oxide concentration from the current downstream nitrogen oxide concentration.

[0094] Step S2032, inputting the current main pump pressure, the current fuel consumption and the current change in nitrogen oxide concentration into a preset urea consumption prediction model.

[0095] Specifically, the electronic device may input the current main pump pressure, the current fuel consumption, and the current nitrogen oxide concentration change into a preset urea consumption prediction model.

[0096] Among them, the preset urea consumption prediction model can be a multivariate regression algorithm, a radial basis function (RBF) network, a feedforward neural network (FFNN), a convolutional neural network (CNN), a deconvolutional neural network (DN), a deep convolutional inverse graphics network (DCIGN), a generative adversarial network (GAN), a recurrent neural network (RNN), a long / short term memory network (LSTM), a deep residual network (DRN) and an extreme learning machine (ELM) Any one of them. The embodiment of the present application does not limit the preset urea consumption prediction model.

[0097] Step S2033: The preset urea consumption prediction model extracts features of the current main pump pressure, the current fuel consumption and the current nitrogen oxide concentration change, and outputs a current urea consumption prediction value.

[0098] Specifically, the preset urea consumption prediction model extracts features of the current main pump pressure, the current fuel consumption and the current change in nitrogen oxide concentration, and then outputs a current urea consumption prediction value based on the extracted features.

[0099] Optionally, the preset urea consumption prediction model can determine the amount of NOx generated per unit fuel consumption based on the operating characteristics of the engine, and then calculate the amount of NOx removal using the upstream and downstream NOx concentration measurements. Finally, the urea consumption is estimated by combining the NOx removal amount and the urea reaction ratio, thereby outputting the current urea consumption prediction value.

[0100] In an optional implementation manner of the present application, the training process of the preset urea consumption prediction model includes:

[0101] Step a1: Obtain a training data set.

[0102] The training data set includes training main pump pressure, training fuel consumption, training nitrogen oxide concentration change and corresponding training actual urea consumption; the training actual urea consumption is the label.

[0103] Specifically, the electronic device can receive a training data set input by a user, or a training data set sent by other devices. The electronic device can also collect training main pump pressure, training fuel consumption, training nitrogen oxide concentration change, and corresponding training actual urea consumption included in the training data set based on various sensors. The embodiment of the present application does not specifically limit the manner in which the electronic device obtains the training data set.

[0104] Optionally, after collecting the training main pump pressure, training fuel consumption, training nitrogen oxide concentration change and corresponding training actual urea consumption in the training data set, the electronic device can store the collected training data set in the data storage system of the host computer. Then, the training data set is cleaned (noise removed) and normalized (normalized or standardized) to ensure the consistency and accuracy of the data. These pre-processed data provide the basis for model training and verification.

[0105] Step a2: input the training data set into the initial urea consumption prediction network and output the virtual urea consumption prediction value.

[0106] Specifically, the electronic device may input the training data set into the initial urea consumption prediction network and output a virtual urea consumption prediction value.

[0107] Exemplarily, it is assumed that the initial urea consumption prediction network is a multivariate regression algorithm, wherein the multivariate regression form is:

[0108] U=αF+βN+δP+γ

[0109] Among them, α, β, δ and γ are the parameters to be learned, P is the training main pump pressure, F is the training fuel consumption, N is the training nitrogen oxide concentration change, and U is the training actual urea consumption.

[0110] Step a3, calculating the loss function based on the training actual urea consumption and the virtual urea consumption prediction value.

[0111] Specifically, the electronic device may calculate the loss function based on the training actual urea consumption and the virtual urea consumption prediction value.

[0112] Exemplarily, the loss function can be the following formula:

[0113]

[0114] Step a4, using a preset method to minimize the loss function, and obtaining the target model parameters corresponding to the minimized loss function.

[0115] Specifically, the electronic device may use a preset method to minimize the loss function to obtain target model parameters corresponding to the minimized loss function.

[0116] Among them, the preset method can be the least squares method, the gradient descent method, or other preset methods. The embodiment of the present application does not specifically limit the preset method.

[0117] Specifically, the above step a4 may include the following steps:

[0118] Step a41, generating a target matrix according to the training main pump pressure, training fuel consumption and training nitrogen oxide concentration change in the loss function.

[0119] Specifically, the electronic device can generate a target matrix based on the training main pump pressure, the training fuel consumption, and the training nitrogen oxide concentration change in the loss function.

[0120] Exemplary. Design matrix X (including training main pump pressure, training fuel consumption and training nitrogen oxide concentration change):

[0121]

[0122] Step a42, generating a target vector according to the actual urea consumption trained in the loss function.

[0123] Specifically, the electronic device can generate a target vector based on the actual urea consumption trained in the loss function.

[0124] Exemplarily, the target vector is:

[0125]

[0126] Step a43, based on the target matrix and the target vector, calculate and obtain the target model parameters.

[0127] Specifically, the electronic device can calculate the target model parameters based on the target matrix and the target vector according to the following formula.

[0128]

[0129] Step a5: based on the target model parameters, updating the initial model parameters in the initial urea consumption prediction network to generate a preset urea consumption prediction model.

[0130] Specifically, the electronic device may update the initial model parameters in the initial urea consumption prediction network based on the target model parameters, and generate a preset urea consumption prediction model.

[0131] In an optional embodiment of the present application, after generating a preset urea consumption prediction model, the electronic device can verify the preset urea consumption prediction model based on a test set to evaluate its ability to detect abnormal data. If the deviation between the predicted urea consumption value and the actual urea consumption value is less than a preset deviation threshold, it is considered that the parameters of the preset urea consumption prediction model training meet expectations. If the deviation between the predicted urea consumption value and the actual urea consumption value is greater than the preset deviation threshold, the preset urea consumption prediction model is trained again. Finally, the preset urea consumption prediction model is further tested in a simulation environment to ensure its reliability and accuracy in practical applications.

[0132] The preset deviation threshold may be 4% or 5%, and the embodiment of the present application does not specifically limit the electronic device.

[0133] Step S204: determining, based on the current urea consumption prediction value, whether the post-treatment system SCR module data corresponding to the engine is modified.

[0134] For details about this step, please refer to the above description of step S104, which will not be elaborated here.

[0135] The engine post-treatment function detection method provided in the embodiment of the present application calculates the current nitrogen oxide concentration change based on the current upstream nitrogen oxide concentration and the current downstream nitrogen oxide concentration, thereby ensuring the accuracy of the calculated current nitrogen oxide concentration change. The current main pump pressure, the current fuel consumption, and the current nitrogen oxide concentration change are input into the preset urea consumption prediction model; the preset urea consumption prediction model extracts features from the current main pump pressure, the current fuel consumption, and the current nitrogen oxide concentration change, and outputs the current urea consumption prediction value, thereby ensuring the accuracy of the output current urea consumption prediction value.

[0136] Among them, the training process of the preset urea consumption prediction model includes: obtaining a training data set; inputting the training data set into the initial urea consumption prediction network, outputting a virtual urea consumption prediction value, and ensuring the accuracy of the output virtual urea consumption prediction value. Based on the training actual urea consumption and the virtual urea consumption prediction value, the loss function is calculated to ensure the accuracy of the calculated loss function. According to the training main pump pressure, training fuel consumption, and training nitrogen oxide concentration change in the loss function, a target matrix is ​​generated to ensure the accuracy of the generated target matrix. According to the training actual urea consumption in the loss function, a target vector is generated to ensure the accuracy of the generated target matrix equation. Based on the target matrix and the target vector, the target model parameters are calculated to ensure the accuracy of the obtained target model parameters, thereby ensuring the accuracy of the generated preset urea consumption prediction model. Based on the target model parameters, the initial model parameters in the initial urea consumption prediction network are updated to generate a preset urea consumption prediction model to ensure the accuracy of the generated preset urea consumption prediction model.

[0137] In this embodiment, a method for detecting an engine post-processing function is provided, which can be used in the above-mentioned electronic device. Figure 3 : is a flow chart of a method for detecting an engine post-processing function according to an embodiment of the present invention. Figure 3 As shown, the process includes the following steps:

[0138] Step S301, obtaining first current working state data corresponding to the construction machinery.

[0139] For details about this step, please refer to the above description of step S201, which will not be elaborated here.

[0140] Step S302, obtaining second current working state data corresponding to the engine of the engineering machinery.

[0141] For details about this step, please refer to the above description of step S202, which will not be elaborated here.

[0142] Step S303: predicting a current urea consumption prediction value corresponding to the engine based on the first current working state data and the second current working state data.

[0143] For details about this step, please refer to the above description of step S203, which will not be elaborated here.

[0144] Step S304: determining, based on the current urea consumption prediction value, whether the post-treatment system SCR module data corresponding to the engine is modified.

[0145] Specifically, the above step S304 may include the following steps:

[0146] Step S3041, obtaining the current urea remaining amount corresponding to the engine.

[0147] Specifically, the electronic device may collect the current urea remaining amount corresponding to the engine based on the data of the urea liquid level sensor.

[0148] Step S3042: determining the actual value of the current urea consumption corresponding to the engine based on the current urea remaining amount.

[0149] Specifically, the electronic device can obtain the amount of urea added, and then use the amount of urea added to subtract the current urea remaining amount to calculate the actual value of the current urea consumption corresponding to the engine.

[0150] Step S3043, calculating the difference between the actual value of urea consumption and the current predicted value of urea consumption.

[0151] Specifically, the electronic device may calculate a difference between the actual value of urea consumption and the current predicted value of urea consumption.

[0152] Step S3044: Determine, based on the difference, whether the post-treatment system SCR module data corresponding to the engine is modified.

[0153] Specifically, the above step S3044 may include the following steps:

[0154] Step b1: if the difference is greater than a first preset difference threshold, it is determined that the data change trend of the post-processing system SCR module corresponding to the engine is abnormal, and a prompt message is output to the user.

[0155] Specifically, the electronic device can receive a first preset difference threshold input by a user, or can receive a first preset difference threshold sent by other devices of the user. The electronic device can also set the first preset difference threshold based on the attribute information of the engine. The embodiment of the present application does not specifically limit the manner in which the electronic device obtains the first preset difference threshold.

[0156] Then, the electronic device may compare the difference with a first preset difference threshold value. If the difference is greater than the first preset difference threshold value, it is determined that the data change trend of the post-processing system SCR module corresponding to the engine is abnormal, and a prompt message is output to the user.

[0157] Step b2: If the difference is greater than a second preset difference threshold, it is determined that the SCR module data of the post-treatment system corresponding to the engine is changed, and an alarm message is output to the user.

[0158] The second preset difference threshold is greater than the first preset difference threshold.

[0159] Specifically, the electronic device can receive a second preset difference threshold input by a user, or can receive a second preset difference threshold sent by other devices of the user. The electronic device can also set the second preset difference threshold based on the attribute information of the engine. The embodiment of the present application does not specifically limit the manner in which the electronic device obtains the second preset difference threshold.

[0160] Then, the electronic device may compare the difference with a second preset difference threshold value. If the difference is greater than the second preset difference threshold value, it is determined that the post-processing system SCR module data corresponding to the engine is changed, and an alarm message is output to the user.

[0161] Step S305: Control the engine using a preset strategy.

[0162] Specifically, after determining that the aftertreatment system SCR module data corresponding to the engine is modified, the electronic device may reduce the engine power and / or limit the engine speed to prevent further damage or emission non-compliance.

[0163] The engine post-processing function detection method provided in the embodiment of the present application determines that the data change trend of the post-processing system SCR module corresponding to the engine is abnormal if the difference is greater than the first preset difference threshold, and outputs a prompt message to the user, thereby ensuring the accuracy of the result of the abnormal data change trend of the post-processing system SCR module corresponding to the engine, and outputs a prompt message to the user, so that the user can receive the prompt message. If the difference is greater than the second preset difference threshold, it is determined that the data of the post-processing system SCR module corresponding to the engine is changed, and outputs an alarm message to the user, thereby ensuring the accuracy of the result of the change of the post-processing system SCR module corresponding to the engine, and outputs an alarm message to the user, so that the user can receive the user-output alarm message.

[0164] In addition, based on the current urea consumption prediction value, after determining that the SCR module data of the after-treatment system corresponding to the engine has been changed, the preset strategy is used to control the engine, thereby preventing further damage to the construction machinery or non-compliance with emissions.

[0165] The present invention provides an engine post-processing function detection system, such as Figure 4 As shown, the engine post-processing function detection system includes 1. host computer; 2. I-ECU display; 3. V-ECU controller; 4. TBOX. 5. Remote monitoring platform. For example, Figure 5 As shown, the engine post-processing function detection method includes the following steps:

[0166] Step 1, S1 data collection phase, data acquisition: During the operation of the construction machinery, the upper computer module obtains the engine post-processing module data (SCR (Selective catalytic reduction) upstream and downstream NOx sensor output values, urea residual, engine fuel consumption, etc.) and the whole machine working status data (construction machinery main pump pressure, etc.) in real time through the whole machine electronic control CAN bus network.

[0167] Step 2, S2 data collection phase, data storage and processing: The collected data is first stored in the data storage system of the host computer, followed by data cleaning (noise removal) and data standardization (normalization or standardization) to ensure data consistency and accuracy. These pre-processed data provide the basis for model training and verification.

[0168] Step 3, S3 model training and optimization phase, training data preparation: the preprocessed data is divided into training set, validation set, and test set.

[0169] Step 4, S4 model training and optimization phase, model training: During the training process, the multivariate regression algorithm fits the data by adjusting the loss function (mean square error) and solving key parameters using the least squares method.

[0170] Step 5, S5 model training and optimization phase, model verification and simulation. After training, the model is verified on the test set to evaluate its ability to detect abnormal data. If the deviation between the predicted value and the actual value is less than 4%, it is considered that the parameters of the model training are in line with expectations. If the deviation between the predicted value and the actual value is greater than 4%, repeat step 4; the model is further tested in a simulation environment to ensure its reliability and accuracy in practical applications.

[0171] Step 6, S6 model training and optimization phase, embedded code generation: The verified model is converted into C++ code suitable for the I-ECU display development platform, ready to be deployed to the display module of the construction machinery.

[0172] Step 7, S7 model deployment and real-time monitoring phase, display loading module: Integrate the model embedded code into the construction machinery display module, compile and test it through the integrated development environment (IDE). The model will be used to analyze the key parameter data of the construction machinery in real time.

[0173] Step 8, S8 model deployment and real-time monitoring phase, real-time data acquisition: the display module continuously obtains data from the engineering machinery electronic control CAN bus network and inputs it into the model for analysis.

[0174] Step 9, S9 model deployment and real-time monitoring phase, trend analysis and anomaly detection: The model performs real-time trend analysis and anomaly detection on the collected message data. Compare the deviation between the predicted urea consumption value and the actual urea consumption value. When the deviation between the two exceeds 15%, it is considered that the data change trend of the engine post-processing module is abnormal, and the display will generate an alarm to prompt the user to check the system status of the engine post-processing SCR (Selective catalytic reduction) module; if the deviation between the two exceeds 30%, it is considered that the post-processing data does not match the working status of the whole machine, and there is data falsification. The display warns the user and sends a command to the V-ECU to limit the whole machine action and lock the engine speed.

[0175] If the monitored data fluctuation exceeds the normal range, the display will generate an alarm. Abnormal data can indicate abnormal data change trend of the engine post-processing module, mismatch between post-processing data and the working status of the whole machine, etc.

[0176] Step 10, S10 abnormality handling and protection mechanism stage, alarm and feedback: the display notifies the operator of abnormal conditions through visual and sound alarms. The triggering of the alarm can prompt the operator to immediately check the system status or stop the operation.

[0177] Step 11, S11 abnormality handling and protection mechanism stage, controller response: the display module transmits the abnormal information to the controller module. The controller executes the preset protection mechanism according to the abnormal data and alarm information, such as reducing the engine power or limiting the engine speed to prevent further damage or emission non-compliance.

[0178] Step 12, S12 abnormality handling and protection mechanism stage, log recording: the controller records the abnormal data and its processing results for subsequent analysis and review.

[0179] Step 13, S13 remote monitoring and updating phase, data upload: TBOX module uploads the results of dynamic monitoring model, abnormal information and system status to the remote monitoring platform in real time. This platform can be managed by the equipment manufacturer or service provider.

[0180] Step 14, S14 remote monitoring and updating phase, remote updating: TBOX module supports updating the model configuration parameters of the display module via OTA. OTA updating can improve the performance and accuracy of the model and ensure the effectiveness of the system under different working conditions.

[0181] The entire process ensures the effectiveness of the construction machinery engine aftertreatment system and the authenticity of the data through real-time data collection, model training, real-time monitoring and protection mechanisms. The dynamic monitoring model can detect and respond to data anomalies in a timely manner, ensure the normal operation of the equipment, and reduce environmental pollution and maintenance costs.

[0182] The present invention collects the excavator main pump pressure, engine fuel consumption, and nitrogen oxide concentrations upstream and downstream of the SCR module, integrates the actual working conditions of the excavator and the engine post-processing SCR module data, and builds a parameter real-time monitoring model to predict urea consumption. Then, the predicted value of the urea consumption is compared with the actual value, and then it is identified whether the actual urea consumption change trend is abnormal, whether the engine post-processing SCR (Selective catalytic reduction) module data matches the whole machine working state, so as to judge whether there is data falsification.

[0183] Compared with the prior art, the dynamic monitoring model of the parameters of the engineering machinery engine after-treatment system constructed by the present invention integrates the working status of the engineering machinery as a whole and the status of the engineering machinery engine after-treatment module, deeply analyzes and identifies the working status of the engine after-treatment module, and can predict the change trend of relevant important data in real time, identify potential data fraud, and then judge whether the engine after-treatment system is operating normally. When abnormal data of the engine after-treatment system is detected, the user is immediately reminded, the engine speed is locked, the whole machine action is restricted, and the engine is prevented from continuing to run without adding urea. It effectively avoids the whole machine failure caused by data falsification and reduces the negative impact on the environment.

[0184] In this embodiment, an engine post-processing function detection device is also provided, which is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0185] This embodiment provides an engine post-processing function detection device, such as Figure 6 As shown, including:

[0186] A first acquisition module 401 is used to acquire first current working state data corresponding to the engineering machinery;

[0187] The second acquisition module 402 is used to acquire second current working state data corresponding to the engine of the engineering machinery;

[0188] A prediction module 403, configured to predict a current urea consumption prediction value corresponding to the engine based on the first current working state data and the second current working state data;

[0189] The determination module 404 is used to determine whether the post-treatment system SCR module data corresponding to the engine is changed according to the current urea consumption prediction value.

[0190] In some optional embodiments, the first current working status data includes the current main pump pressure corresponding to the construction machinery, the second current working status data includes the current fuel consumption corresponding to the engine and the current upstream nitrogen oxide concentration and the current downstream nitrogen oxide concentration of the SCR module, and the prediction module 403 is specifically used to calculate the current change in nitrogen oxide concentration based on the current upstream nitrogen oxide concentration and the current downstream nitrogen oxide concentration; input the current main pump pressure, the current fuel consumption and the current change in nitrogen oxide concentration into a preset urea consumption prediction model; the preset urea consumption prediction model performs feature extraction on the current main pump pressure, the current fuel consumption and the current change in nitrogen oxide concentration, and outputs a current urea consumption prediction value.

[0191] In some optional embodiments, the prediction module 403 is specifically used to obtain a training data set; the training data set includes a training main pump pressure, a training fuel consumption, a training nitrogen oxide concentration change, and a corresponding training actual urea consumption; the training actual urea consumption is used as a label; the training data set is input into an initial urea consumption prediction network, and a virtual urea consumption prediction value is output; based on the training actual urea consumption and the virtual urea consumption prediction value, a loss function is calculated; a preset method is used to minimize the loss function to obtain a target model parameter corresponding to the minimized loss function; based on the target model parameters, the initial model parameters in the initial urea consumption prediction network are updated to generate a preset urea consumption prediction model.

[0192] In some optional embodiments, the prediction module 403 is specifically used to generate a target matrix based on the training main pump pressure, training fuel consumption, and training nitrogen oxide concentration change in the loss function; generate a target vector based on the training actual urea consumption in the loss function; and calculate the target model parameters based on the target matrix and the target vector.

[0193] In some optional embodiments, the determination module 404 is specifically used to obtain the current urea remaining amount corresponding to the engine; based on the current urea remaining amount, determine the actual value of the current urea consumption corresponding to the engine; calculate the difference between the actual value of the urea consumption and the predicted value of the current urea consumption; and determine, based on the difference, that the post-treatment system SCR module data corresponding to the engine is changed.

[0194] In some optional embodiments, the determination module 404 is specifically used to determine that the data change trend of the after-treatment system SCR module corresponding to the engine is abnormal if the difference is greater than a first preset difference threshold, and output a prompt message to the user; if the difference is greater than a second preset difference threshold, it is determined that the data of the after-treatment system SCR module corresponding to the engine is changed, and output an alarm message to the user.

[0195] In some optional embodiments, such as Figure 7 As shown, the above-mentioned engine post-processing function detection device also includes:

[0196] The control module 405 is used to control the engine using a preset strategy.

[0197] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0198] The engine post-processing function detection device in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above-mentioned functions.

[0199] The embodiment of the present invention also provides an electronic device having the above Figure 6 as well as Figure 7 The engine aftertreatment function detection device is shown.

[0200] See also Figure 8 , Figure 8 is a schematic diagram of the structure of an electronic device provided by an optional embodiment of the present invention, such as Figure 8 As shown, the electronic device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. The various components are connected to each other using different buses for communication, and can be installed on a common mainboard or installed in other ways as needed. The processor can process instructions executed in the electronic device, including instructions stored in or on the memory to display graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple electronic devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 8 A processor 10 is taken as an example.

[0201] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0202] The memory 20 stores instructions executable by at least one processor 10, so that at least one processor 10 executes the method shown in the above embodiment.

[0203] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the electronic device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the electronic device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0204] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0205] The electronic device further comprises a communication interface 30 for the electronic device to communicate with other devices or a communication network.

[0206] An embodiment of the present invention further provides an engineering machine, comprising: an electronic device, an engine, and an engineering machine body, wherein the electronic device is used to execute the engine post-processing function detection method described in any one of the above-mentioned embodiments.

[0207] The embodiment of the present invention also provides a computer-readable storage medium. The method according to the embodiment of the present invention can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0208] A part of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the existence of the computer program instruction in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc., and accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium accessible to the computer.

[0209] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A method for detecting engine post-processing function, characterized in that: The method comprises: Acquire first current working state data corresponding to the construction machinery; Acquiring second current working state data corresponding to the engine of the engineering machinery; Based on the first current working state data and the second current working state data, predicting a current urea consumption prediction value corresponding to the engine; According to the current urea consumption prediction value, it is determined that the SCR module data of the post-treatment system corresponding to the engine is changed.

2. The method according to claim 1, characterized in that The first current working state data includes the current main pump pressure corresponding to the engineering machinery, the second current working state data includes the current fuel consumption corresponding to the engine and the current upstream nitrogen oxide concentration and the current downstream nitrogen oxide concentration of the SCR module, and the current urea consumption prediction value corresponding to the engine is predicted based on the first current working state data and the second current working state data, including: Calculating a current change in nitrogen oxide concentration based on the current upstream nitrogen oxide concentration and the current downstream nitrogen oxide concentration; Inputting the current main pump pressure, the current fuel consumption and the current nitrogen oxide concentration change into a preset urea consumption prediction model; The preset urea consumption prediction model performs feature extraction on the current main pump pressure, the current fuel consumption and the current nitrogen oxide concentration change, and outputs the current urea consumption prediction value.

3. The method according to claim 2, characterized in that The training process of the preset urea consumption prediction model includes: Acquire a training data set; the training data set includes a training main pump pressure, a training fuel consumption, a training nitrogen oxide concentration change, and a corresponding training actual urea consumption; the training actual urea consumption is a label; Inputting the training data set into an initial urea consumption prediction network, and outputting a virtual urea consumption prediction value; Calculating a loss function based on the training actual urea consumption and the virtual urea consumption prediction value; Minimize the loss function using a preset method to obtain target model parameters corresponding to the minimized loss function; Based on the target model parameters, the initial model parameters in the initial urea consumption prediction network are updated to generate the preset urea consumption prediction model.

4. The method according to claim 3, characterized in that The method of minimizing the loss function by a preset method to obtain target model parameters corresponding to the minimized loss function includes: Generate a target matrix according to the training main pump pressure, the training fuel consumption and the training nitrogen oxide concentration change in the loss function; Generate a target vector according to the actual urea consumption of the training described in the loss function; The target model parameters are calculated based on the target matrix and the target vector.

5. The method according to claim 1, characterized in that The determining, based on the current urea consumption prediction value, that the post-treatment system SCR module data corresponding to the engine is changed includes: Obtaining a current urea residual amount corresponding to the engine; Based on the current urea remaining amount, determining a current urea consumption real value corresponding to the engine; Calculating a difference between the actual value of urea consumption and the current predicted value of urea consumption; According to the difference, it is determined that the SCR module data of the post-treatment system corresponding to the engine is modified.

6. The method according to claim 5, characterized in that Determining, based on the difference, that the post-processing system SCR module data corresponding to the engine is changed includes: If the difference is greater than a first preset difference threshold, determining that the data change trend of the post-processing system SCR module corresponding to the engine is abnormal, and outputting a prompt message to the user; If the difference is greater than a second preset difference threshold, it is determined that the post-treatment system SCR module data corresponding to the engine is changed, and an alarm message is output to the user; wherein the second preset difference threshold is greater than the first preset difference threshold.

7. The method according to claim 1, characterized in that After determining, based on the current urea consumption prediction value, that the post-treatment system SCR module data corresponding to the engine is changed, the method further includes: The engine is controlled using a preset strategy.

8. An engine post-processing function detection device, characterized in that: The device comprises: A first acquisition module, used to acquire first current working state data corresponding to the engineering machinery; A second acquisition module, used to acquire second current working state data corresponding to the engine of the engineering machinery; A prediction module, configured to predict a current urea consumption prediction value corresponding to the engine based on the first current working state data and the second current working state data; The determination module is used to determine, according to the current urea consumption prediction value, whether the post-treatment system SCR module data corresponding to the engine is changed.

9. An electronic device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the engine post-processing function detection method according to any one of claims 1 to 7 by executing the computer instructions.

10. An engineering machine, characterized in that: include: An electronic device, an engine and an engineering machinery body, wherein the electronic device is used to execute the engine post-processing function detection method according to any one of claims 1 to 7.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the engine post-processing function detection method according to any one of claims 1 to 7.

12. A computer program product, characterized in that The method comprises computer instructions, wherein the computer instructions are used to cause a computer to execute the engine post-processing function detection method according to any one of claims 1 to 7.

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