Monitoring method and device for high-altitude operation machine and high-altitude operation machine

Abstract

The embodiment of the invention provides a monitoring method and device for a high-altitude operation machine and the high-altitude operation machine. The monitoring method comprises the following steps: acquiring first electrical data and first hydraulic data of the high-altitude operation machine in real time in the operation process of the high-altitude operation machine; based on the first electrical data, the first hydraulic data and historical electrical data and historical hydraulic data of the high-altitude operation machine in a historical time period, updating a digital twinborn model of the high-altitude operation machine; second electrical data and second hydraulic data obtained by simulation of the digital twin model based on the first electrical data and the first hydraulic data are obtained; according to the first electrical data, the second electrical data, the first hydraulic data and the second hydraulic data, the current operation state of the aerial work machine is determined; and determining the fault type of the high-altitude operation machine according to the first electrical data and the first hydraulic data under the condition that the high-altitude operation machine is determined to have a fault according to the operation state of the high-altitude operation machine.

Description

Technical Field

[0001] The present application relates to the technical field of engineering machinery, and in particular to a monitoring method and device for aerial work machinery, aerial work machinery and a storage medium. Background Art

[0002] Aerial work machinery is an important branch of the field of engineering machinery. It is a general term for mechanical equipment used to transport workers and equipment to a designated height for work. Aerial work machinery is a complex mechanical equipment with interrelated and simultaneous structural, electrical and hydraulic systems. The fatigue life of any structure or the state of the system is an important factor affecting the safety of the entire machine.

[0003] In the prior art, the operating status of a certain structure of the equipment is usually determined by collecting the working data of the structure. However, aerial work machinery is a complex mechanical equipment composed of multiple structures, electrical and hydraulic systems that are interconnected and act simultaneously. It is obviously impossible to accurately monitor the status of the entire aerial work machinery by only collecting the working data of a certain structure. Therefore, there is an urgent need for a technical means to accurately monitor the operating status of aerial work machinery in order to achieve safe control of aerial work machinery. Summary of the invention

[0004] The purpose of the embodiments of the present application is to provide a monitoring method, device, aerial work machinery and storage medium for aerial work machinery, so as to solve the technical defect in the prior art that the operating status of the aerial work machinery cannot be accurately monitored in real time.

[0005] In order to achieve the above-mentioned purpose, the first aspect of the present application provides a monitoring method for aerial work machinery, which is applied to aerial work machinery. The monitoring method comprises:

[0006] During the operation of the aerial work machine, first electrical data and first hydraulic data of the aerial work machine are acquired in real time;

[0007] Updating the digital twin model of the aerial work machine based on the first electrical data, the first hydraulic data, and the historical electrical data and the historical hydraulic data of the aerial work machine within a historical time period;

[0008] Acquire second electrical data and second hydraulic data obtained by simulating the digital twin model based on the first electrical data and the first hydraulic data;

[0009] Determine the current operating state of the aerial work machine according to the first electrical data, the second electrical data, the first hydraulic data and the second hydraulic data;

[0010] When it is determined that the aerial work machine has a fault according to the operating state of the aerial work machine, the fault type of the aerial work machine is determined according to the first electrical data and the first hydraulic data.

[0011] In an embodiment of the present application, the monitoring method also includes: obtaining the operating data of the aerial work machinery in real time during the operation of the aerial work machinery, wherein the aerial work machinery includes at least a chassis, a boom and multiple legs, and the operating data includes at least the operating angle of the boom and the torque of the multiple legs; determining a real-time damage value corresponding to the operating data based on a fatigue damage library, wherein the fatigue damage library includes a correspondence between multiple operating angles and torques and damage values ​​of the operating mechanism, and the correspondence is obtained after fatigue test training based on multiple historical operating angles and historical torques that meet preset conditions; determining the historical cumulative damage value of the boom based on the model information of the aerial work machinery; determining the remaining life of the boom based on the real-time damage value and the historical cumulative damage value.

[0012] In an embodiment of the present application, the monitoring method further includes: generating a corresponding alarm signal when the remaining life of the boom is lower than a preset threshold or a failure occurs in the aerial work machinery.

[0013] In an embodiment of the present application, the method also includes a step of constructing a fatigue damage library, the construction step including: obtaining multiple historical operating data of the aerial work machinery within a historical time period, the multiple historical operating data including multiple historical operating angles of the boom and multiple historical torques of multiple legs; for multiple historical operating angles, determining the cumulative number of occurrences of each historical operating angle within the historical time period; eliminating historical operating angles whose cumulative number of occurrences is lower than a preset number threshold, and determining the remaining historical operating angles as target operating angles that meet preset conditions; analyzing multiple historical torques, and screening out target torques that meet the preset conditions; generating fatigue test conditions based on the target operating angles and target torques; for any fatigue test condition, repeatedly performing fatigue test training on the fatigue test condition until fatigue cracks exist in the boom under the fatigue test condition, and determining the number of training times for the fatigue test condition as the fatigue life of the boom under the fatigue test condition; determining the damage value corresponding to each fatigue test condition based on the fatigue life of the boom under each fatigue test condition, and constructing a fatigue damage library based on the correspondence between each fatigue test condition and the damage value.

[0014] In an embodiment of the present application, analyzing multiple historical moments and screening out target moments that meet preset conditions includes: performing normal distribution analysis on multiple historical moments to obtain a normal distribution graph for multiple historical moments; based on the normal distribution graph, eliminating historical moments outside a preset interval, and determining the remaining historical moments as target moments that meet the preset conditions.

[0015] In an embodiment of the present application, generating fatigue test conditions based on target operating angles and target torques includes: for each target operating angle, combining the target operating angle with all other target operating angles except the target operating angle in turn to obtain multiple angle groups; sorting all target torques in ascending order to obtain torque intervals for all target torques; dividing the torque interval into multiple continuous sub-torque intervals based on a preset division ratio; combining each sub-torque interval with each angle group in turn to generate corresponding multiple fatigue test conditions.

[0016] In an embodiment of the present application, determining the fault type of the aerial work machinery based on the first electrical data and the first hydraulic data includes: inputting the first electrical data and the first hydraulic data into a fault detection model to output a corresponding data label through the fault detection model; determining the fault type corresponding to the data label based on a data label library, wherein the data label library includes a plurality of labels and a fault type corresponding to each label, and the fault type includes at least one of a broken rotor bar fault, a stator fault, a bearing fault, a cylinder wear, an oil leakage, and a bearing wear.

[0017] The second aspect of the present application provides a monitoring device for aerial work machinery, comprising:

[0018] a memory configured to store instructions; and

[0019] The processor is configured to call the instructions from the memory and implement the above-mentioned monitoring method for aerial work machinery when executing the instructions.

[0020] The third aspect of the present application provides an aerial work machine, comprising:

[0021] The above-mentioned monitoring device for aerial work machinery;

[0022] Multiple outriggers;

[0023] a chassis, fixed on a plurality of legs;

[0024] Boom, one end of the boom is fixed on the chassis.

[0025] A fourth aspect of the present application provides a machine-readable storage medium having instructions stored thereon, which, when executed by a processor, configures the processor to execute the above-mentioned monitoring method for aerial work machinery.

[0026] The above technical scheme obtains the first electrical data and the first hydraulic data of the aerial work machinery in real time during the operation of the aerial work machinery, updates the digital twin model of the aerial work machinery based on the first electrical data, the first hydraulic data and the historical electrical data and the historical hydraulic data of the aerial work machinery in a historical time period, and obtains the second electrical data and the second hydraulic data simulated by the digital twin model based on the first electrical data and the first hydraulic data, so as to determine the current operating status of the aerial work machinery according to the first electrical data, the second electrical data, the first hydraulic data and the second hydraulic data. When it is determined that the aerial work machinery has a fault according to the operating status of the aerial work machinery, the fault type of the aerial work machinery is determined according to the first electrical data and the first hydraulic data, so as to realize accurate detection of the operating status of the aerial work machinery, and effectively improve the safety of the aerial work machinery.

[0027] Other features and advantages of the embodiments of the present application will be described in detail in the subsequent specific implementation section. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The accompanying drawings are used to provide a further understanding of the embodiments of the present application and constitute a part of the specification. Together with the following specific implementations, they are used to explain the embodiments of the present application, but do not constitute a limitation on the embodiments of the present application. In the accompanying drawings:

[0029] Figure 1 A schematic diagram of an application environment of a monitoring method for aerial work machinery according to an embodiment of the present application is schematically shown;

[0030] Figure 2 A schematic diagram of a process flow of a monitoring method for aerial work machinery according to an embodiment of the present application is schematically shown;

[0031] Figure 3 A schematic diagram of a process for building a digital twin model according to an embodiment of the present application is schematically shown;

[0032] Figure 4 A schematic diagram of a normal distribution diagram according to an embodiment of the present application is schematically shown;

[0033] Figure 5 A schematic diagram of a torque interval according to an embodiment of the present application is schematically shown;

[0034] Figure 6 The internal structure diagram of a computer device according to an embodiment of the present application is schematically shown.

[0035] Description of Reference Numerals

[0036] 101 chassis 102 arm

[0037] 103 Leg 104 Angle sensor

[0038] 105 torque sensor 106 motor

[0039] 107 Hydraulic pump 108 Subframe

[0040] 109 Turntable 110 Working Platform DETAILED DESCRIPTION

[0041] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. It should be understood that the specific implementation methods described herein are only used to illustrate and explain the embodiments of the present application, and are not used to limit the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0042] It should be noted that if the embodiments of the present application involve directional indications (such as up, down, left, right, front, back...), the directional indications are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0043] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present application, the descriptions of "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or suggesting their relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of such features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in the field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such combination of technical solutions does not exist and is not within the scope of protection required by this application.

[0044] The monitoring method for aerial work machinery provided in this application can be applied to Figure 1 In the application environment shown in the figure. Figure 1 As shown, a schematic diagram of the structure of an aerial work machine is provided, and the aerial work machine includes:

[0045] Chassis 101 , boom 102 , multiple legs 103 , angle sensor 104 , torque sensor 105 , motor 106 , hydraulic pump 107 , subframe 108 , turntable 109 , and work platform 110 .

[0046] In this embodiment, it should be noted that the aerial work machine may refer to a telescopic boom aerial work vehicle. Specifically, the main structure of the telescopic boom aerial work vehicle includes, from bottom to top, a plurality of legs 103, a chassis 101, a subframe 108, a turntable 109, a boom 102, and a work platform 110. The boom 102 is a telescopic segmented boom, a first end of the boom 102 is fixed to the chassis through a state 109, and the other end is fixed to the work platform 110.

[0047] An angle sensor 104 is installed on the bottom plate of the turntable 109 to collect the operating angle of the boom 102 in real time. The turntable 109 has a built-in motor 106, wherein the motor 106 is arranged with multiple sensors, which may include a current sensor, a temperature sensor, and a speed sensor to collect the electrical data of the motor 106 in real time. A hydraulic pump 107 is installed in the chassis 101, wherein the hydraulic pump 107 is arranged with multiple sensors, which may include a pressure sensor and a flow sensor to collect the hydraulic data of the hydraulic pump 107 in real time.

[0048] The sub-frame 108 is connected to a plurality of legs 103 , and a torque sensor 105 is installed at the support position of the leg 103 to collect the torque of the leg 103 in real time, wherein the torque of the leg 103 may refer to the leg reaction force of the leg 103 .

[0049] The aerial work platform 110 can be used to carry a target object, and the boom 102 can drive the aerial work platform 110 to rise through a lifting action, so as to transport the target object to a target height.

[0050] Figure 2 The following schematically shows a flow chart of a monitoring method for aerial work machinery according to an embodiment of the present application. Figure 2 As shown, an embodiment of the present application provides a monitoring method for aerial work machinery. The method is applied to the aerial work machinery. The aerial work machinery at least includes a chassis, a boom, and a plurality of legs. The method may include the following steps.

[0051] Step 201, during the operation of the aerial work machine, first electrical data and first hydraulic data of the aerial work machine are acquired in real time.

[0052] In the embodiment of the present application, during the operation of the aerial work machine, the first electrical data of the aerial work machine can be obtained in real time through the current sensor, speed sensor and temperature sensor installed on the motor. Specifically, the first electrical data may include the motor current data I, motor speed data V and motor temperature data T. At the same time, the first hydraulic data of the aerial work machine can be obtained in real time through the pressure sensor and flow sensor installed on the hydraulic pump. Specifically, the hydraulic data may include the hydraulic pump pressure P and the hydraulic pump flow Q.

[0053] Step 202 : updating the digital twin model of the aerial work machinery based on the first electrical data, the first hydraulic data, and the historical electrical data and the historical hydraulic data of the aerial work machinery within a historical time period.

[0054] In the embodiment of the present application, it should be noted that the data information of any model of aerial work machinery will be stored in the remote server, so the historical electrical data and historical hydraulic data of the aerial work machinery in any historical time period can be obtained from the remote server through the model information of the aerial work machinery. The required historical time period can be selected according to actual needs.

[0055] After acquiring the historical electrical data and historical hydraulic data, the digital twin model of the aerial work machinery is updated based on the first electrical data, the first hydraulic data, the historical electrical data, and the historical hydraulic data. It should be noted that digital twin refers to making full use of physical models, sensors, operation history and other data, integrating multi-disciplinary, multi-physical quantity, multi-scale, and multi-probability simulation processes, and completing mapping in virtual space, thereby reflecting the entire life cycle of the corresponding physical equipment. In this technical solution, a digital twin model for any model of aerial work machinery can be constructed based on a large amount of historical electrical data and historical hydraulic data of the aerial work machinery. Figure 3 As shown in the figure, a flowchart for building a digital twin model is provided. Specifically, based on the geometric structure of the physical entity of the aerial work machinery and the constraints between the components, a multi-domain visualization model of electromechanical and hydraulic control is built according to the internal actual operation mechanism of the electrical and hydraulic systems. Then, based on the intelligent optimization algorithm, the dynamic adaptive update and correction of the digital twin model is realized by acquiring data from the physical entity. At the same time, the artificial neural network is used to learn the rule model obtained with a large amount of historical electrical data and historical hydraulic data to predict the evolution of the twin model. Finally, the predicted evolution results of the twin model are compared with the detection parameters of the real physical model to determine whether the parameter error between the two models is less than a given threshold. If not, the digital twin model needs to be further adaptively updated and corrected. If so, it is considered that the modeling accuracy of the digital twin model meets the requirements and the modeling is accurate.

[0056] Step 203: Acquire second electrical data and second hydraulic data obtained by simulating the digital twin model based on the first electrical data and the first hydraulic data.

[0057] In an embodiment of the present application, after updating the digital twin model, the acquired first electrical data (U1, V1, T1) and the first hydraulic data (P1, Q1) are input into the digital twin model, so as to obtain the second electrical data (U2, V2, T2) and the second hydraulic data (U2, V2, T2) through simulation based on the first electrical data (U1, V1, T1) and the first hydraulic data (P1, Q1) through the digital twin model.

[0058] Step 204, determining the current operating state of the aerial work machine according to the first electrical data, the second electrical data, the first hydraulic data and the second hydraulic data.

[0059] In an embodiment of the present application, the current operating state of the aerial work machinery is determined based on the first electrical data (U1, V1, T1), the second electrical data (U2, V2, T2), the first hydraulic data (P1, Q1) and the second hydraulic data (P2, Q2). Specifically, the first electrical data, the first hydraulic data and the second electrical data, the second hydraulic data can be subtracted from each other, and the current state of the aerial work machinery can be judged by comparing the error obtained by the subtraction with the preset threshold. Specifically, if the error is greater than the preset threshold, the aerial work machinery can be regarded as being in a discontinuous state, that is, a sudden failure may occur at present. If the error is less than or equal to the preset threshold, the aerial work machinery can be regarded as being in a continuous state, that is, it is currently operating normally.

[0060] Step 205, when it is determined that the aerial work machine has a fault according to the operating state of the aerial work machine, determine the fault type of the aerial work machine according to the first electrical data and the first hydraulic data.

[0061] In an embodiment of the present application, when it is determined that the aerial work machinery has a fault according to the operating state of the aerial work machinery, the fault type of the aerial work machinery can be determined according to the first electrical data and the first hydraulic data. In this technical solution, features can be extracted from the physical entity of the aerial work machinery and the historical data of the digital twin model, and then a fault detection model can be trained to determine the fault type of the aerial work machinery according to the acquired real-time electrical data, hydraulic data, digital twin model state and the fault detection model.

[0062] In an embodiment of the present application, determining the fault type of the aerial work machinery based on the first electrical data and the first hydraulic data includes: inputting the first electrical data and the first hydraulic data into a fault detection model to output a corresponding data label through the fault detection model; determining the fault type corresponding to the data label based on a data label library, wherein the data label library includes a plurality of labels and a fault type corresponding to each label, and the fault type includes at least one of a broken rotor bar fault, a stator fault, a bearing fault, a cylinder wear, an oil leakage, and a bearing wear.

[0063] In this embodiment, it should be noted that features can be extracted from the historical data of the physical entity and the digital twin model of the aerial work machinery to train the fault detection model. Specifically, the historical data of the digital twin model and the physical entity of the aerial work machinery are collected to form feature parameters K = (UE, VE, TE, PP, QP), and a normal working condition sample data set and various fault working condition sample data sets are established. Then, the maximum and minimum normalization method is used to preprocess all data sample sets, and a data label library is established. The normal working condition data label in the data label library is set to ("0"), and the data labels of the classic fault types including rotor broken bar fault, stator fault, bearing fault, cylinder wear, oil leakage and bearing wear are set to ("1", "2", "3", "4", "5", "6"), and the training sample library and the test sample library are obtained respectively. The support vector machine algorithm model is trained using the training sample library, the accuracy of the fault detection model is tested with the test sample, and the fault detection model is parameter optimized to obtain a trained fault detection model. Therefore, when it is determined that the aerial work machine has a fault, the first electrical data and the first hydraulic data can be input into the fault detection model to output the corresponding data label through the fault detection model, and the fault type corresponding to the data label is determined based on the data label library. For example, if the data label output by the fault detection model is "1", at this time, it can be known from the data label library that the fault type corresponding to the data label "1" is a broken rotor bar fault.

[0064] The above technical scheme obtains the first electrical data and the first hydraulic data of the aerial work machinery in real time during the operation of the aerial work machinery, updates the digital twin model of the aerial work machinery based on the first electrical data, the first hydraulic data and the historical electrical data and the historical hydraulic data of the aerial work machinery in a historical time period, and obtains the second electrical data and the second hydraulic data simulated by the digital twin model based on the first electrical data and the first hydraulic data, so as to determine the current operating status of the aerial work machinery according to the first electrical data, the second electrical data, the first hydraulic data and the second hydraulic data. When it is determined that the aerial work machinery has a fault according to the operating status of the aerial work machinery, the fault type of the aerial work machinery is determined according to the first electrical data and the first hydraulic data, so as to realize accurate detection of the operating status of the aerial work machinery and effectively improve the safety of the aerial work machinery.

[0065] In one embodiment, the monitoring method also includes: obtaining the operating data of the aerial work machinery in real time during the operation of the aerial work machinery, wherein the aerial work machinery includes at least a chassis, a boom and multiple legs, and the operating data includes at least the operating angle of the boom and the torque of the multiple legs; determining a real-time damage value corresponding to the operating data based on a fatigue damage library, wherein the fatigue damage library includes a correspondence between multiple operating angles and torques and damage values ​​of the operating mechanism, and the correspondence is obtained after fatigue test training based on multiple historical operating angles and historical torques that meet preset conditions; determining the historical cumulative damage value of the boom based on the model information of the aerial work machinery; and determining the remaining life of the boom based on the real-time damage value and the historical cumulative damage value.

[0066] In this embodiment, it should be noted that during the operation of the aerial work machinery, the operating angle θ of the boom and the torque F (f1, f2, f3, f4) of multiple legs and other operating data can be obtained in real time by collecting signal data from angle sensors and torque sensors.

[0067] The fatigue damage library includes a plurality of correspondences between operating angles and moments and the damage values ​​of the boom, and each set of correspondences has a corresponding damage value, wherein the correspondences are obtained after fatigue test training based on a plurality of historical operating angles and historical moments that meet preset conditions, and the preset conditions can be set according to actual needs. Therefore, after obtaining the operating data of the boom, the operating data can be matched with the fatigue damage library to determine which set of correspondences in the fatigue damage library the operating angle θ and moment F (f1, f2, f3, f4) included in the operating data meet, and the damage value of the set of correspondences is determined as the real-time damage value corresponding to the operating data. Specifically, as shown in Table 1, a fatigue damage library is provided, which includes a plurality of sets of correspondences between operating angles and moments, and each set of correspondences has a corresponding damage value. For example, the damage value corresponding to (F1(f1,f2,f3,f4), θ1θ2), (F1(f1,f2,f3,f4), θ1θ3), (F1(f1,f2,f3,f4), θ1θ2) is D1, and the damage value corresponding to (F1(f1,f2,f3,f4), θ1θ3) is D2. Therefore, taking the acquired operation data T of the boom as an example, the operation data T includes the torque F1(f1,f2,f3,f4) and the operation angle θ1θ3. Through the fatigue damage library, the corresponding relationship of the operation data T can be matched to (F1(f1,f2,f3,f4), θ1θ3), and then the damage value D2 corresponding to (F1(f1,f2,f3,f4), θ1θ3) can be determined as the real-time damage value Dnow corresponding to the operation data T.

[0068] Table 1 Fatigue damage library

[0069]

[0070]

[0071] It should be noted that the data information of any model of aerial work machinery will be stored in the remote server. Therefore, the historical cumulative damage value Dtot-last of the boom of the aerial work machinery can be obtained from the remote server through the model information of the aerial work machinery. At the same time, the total life Ttot of the boom of the aerial work machinery can also be obtained. After determining the real-time damage value of the boom under the current operating data based on the fatigue damage library, and obtaining the current historical cumulative damage value of the boom based on the remote server, the real-time cumulative damage value Dtot=Dtot-last+Dnow can be determined based on the sum of the historical cumulative damage value Dtot-last and the real-time damage value Dnow, and the inverse of the real-time cumulative damage value 1 / Dtot is taken as the current cumulative consumed life TD=1 / Dtot. Therefore, the remaining life Tr=Ttot.-TD=Ttot-1 / Dtot of the boom can be further calculated based on the total life Ttot of the boom and the cumulative consumed life TD.

[0072] In an embodiment of the present application, the method also includes a step of constructing a fatigue damage library, the construction step including: obtaining multiple historical operating data of the aerial work machinery within a historical time period, the multiple historical operating data including multiple historical operating angles of the boom and multiple historical torques of multiple legs; for multiple historical operating angles, determining the cumulative number of occurrences of each historical operating angle within the historical time period; eliminating historical operating angles whose cumulative number of occurrences is lower than a preset number threshold, and determining the remaining historical operating angles as target operating angles that meet preset conditions; analyzing multiple historical torques, and screening out target torques that meet the preset conditions; generating fatigue test conditions based on the target operating angles and target torques; for any fatigue test condition, repeatedly performing fatigue test training on the fatigue test condition until fatigue cracks exist in the boom under the fatigue test condition, and determining the number of training times for the fatigue test condition as the fatigue life of the boom under the fatigue test condition; determining the damage value corresponding to each fatigue test condition based on the fatigue life of the boom under each fatigue test condition, and constructing a fatigue damage library based on the correspondence between each fatigue test condition and the damage value.

[0073] In this embodiment, the fatigue damage library is obtained after fatigue test training based on multiple historical operating angles and historical torques that meet the preset conditions. Therefore, when constructing the fatigue damage library, a historical time period can be selected first, and multiple historical operating data of the boom of the aerial work machinery in the historical time period can be obtained. It should be noted that the selected historical time period should be a time period with a long time span to ensure that the number of historical operating data of the boom in the historical time period is sufficient, for example, the number of historical operating angles and historical torques should be more than 1000 groups. After obtaining multiple historical operating data, the cumulative number of occurrences of each historical operating angle is counted respectively, and the historical operating angles with a cumulative number of occurrences lower than the preset number threshold are eliminated, and the remaining historical operating angles are determined as target operating angles that meet the preset conditions. For example, the preset number threshold can be set to 10 times, that is, for any historical operating angle, if the cumulative number of occurrences of the historical operating angle is less than 10 times, it is an operating angle that does not meet the preset conditions and needs to be eliminated. If the cumulative number of occurrences is greater than or equal to 10 times, it is an operating angle that meets the preset conditions and needs to be retained. Specifically, as shown in Table 2, a cumulative number of occurrences of each historical operating angle in a historical time period is provided, for example, the cumulative number of occurrences of θ1 is k1, and the cumulative number of occurrences of θ2 is k2. After obtaining the cumulative number of occurrences of each historical operating angle, the operating angles with a cumulative number of occurrences less than 10 times are eliminated to obtain an angle real operating condition library composed of target operating angles that meet the preset conditions as shown in Table 3.

[0074] Table 2 Cumulative number of occurrences of each historical operation angle in the historical time period

[0075] Serial number θ[°] Cumulative number of occurrences 1 <![CDATA[θ1]]> k1 2 <![CDATA[θ2]]> k2 3 <![CDATA[θ3]]> k3 …… …… …… …… …… …… n <![CDATA[θ n ]]> k

[0076] Table 3 Angle real working condition library

[0077] Serial number θ[°] 1 <![CDATA[θ1]]> 2 <![CDATA[θ2]]> 3 <![CDATA[θ3]]> …… …… …… …… m <![CDATA[θ m ]]>

[0078] At the same time, the obtained multiple historical moments are analyzed, and the target moments that meet the preset conditions are screened out. Specifically, normal distribution analysis can be performed on the multiple historical moments to screen out the target moments that meet the preset conditions.

[0079] In the present technical solution, after obtaining the target operating angle and target torque that meet the preset conditions, a fatigue test condition is generated based on the target operating angle and the target torque. For any fatigue test condition, fatigue test training is repeated for the fatigue test condition until fatigue cracks exist in the boom under the fatigue test condition. The number of training times for the fatigue test condition is determined as the fatigue life of the boom under the fatigue test condition, and then the damage value corresponding to each fatigue test condition is further determined based on the fatigue life of the boom under each fatigue test condition. Specifically, taking the fatigue life as Ti as an example, the inverse of the fatigue life Ti 1 / Ti is taken to determine the damage value Di corresponding to the fatigue test condition. After determining the damage value corresponding to each fatigue test condition, a fatigue damage library is constructed based on the correspondence between each fatigue test condition and the damage value.

[0080] In an embodiment of the present application, analyzing multiple historical moments and screening out target moments that meet preset conditions includes: performing normal distribution analysis on multiple historical moments to obtain a normal distribution graph for multiple historical moments; based on the normal distribution graph, eliminating historical moments outside a preset interval, and determining the remaining historical moments as target moments that meet the preset conditions.

[0081] In this embodiment, it should be noted that a normal distribution analysis can be performed on the multiple historical moments obtained to screen out the target moments that meet the preset conditions. Specifically, a normal distribution analysis is performed on the multiple historical moments to obtain a normal distribution diagram for the multiple historical moments. For example, as shown in Table 4, multiple historical moments are provided, and a normal distribution analysis is performed on the multiple historical data in Table 4 to obtain the following: Figure 4 A schematic diagram of a normal distribution diagram is shown in Figure . Figure 4 As shown in Figure 5, the expected value is 3σ. Therefore, the preset interval can be set to [-3σ, +3σ], the historical moments outside the interval [-3σ, +3σ] are eliminated, and the historical moments within the interval [-3σ, +3σ] are determined as the target moments that meet the preset conditions, and the torque real working condition library shown in Table 5 is obtained.

[0082] Table 4 Multiple historical moments

[0083] Serial number F[N] 1 F1(f1,f2,f3,f4) 2 F2(f1,f2,f3,f4) 3 F3(f1,f2,f3,f4) …… …… …… …… n Fn(f1,f2,f3,f4)

[0084] Table 5 Torque real working condition library

[0085] Serial number F[N] 1 F1(f1,f2,f3,f4) 2 F2(f1,f2,f3,f4) 3 F3(f1,f2,f3,f4) …… …… …… …… m Fm(f1,f2,f3,f4)

[0086] In an embodiment of the present application, generating fatigue test conditions based on target operating angles and target torques includes: for each target operating angle, combining the target operating angle with all other target operating angles except the target operating angle in turn to obtain multiple angle groups; sorting all target torques in ascending order to obtain torque intervals for all target torques; dividing the torque interval into multiple continuous sub-torque intervals based on a preset division ratio; and combining each sub-torque interval with each angle group in turn to generate corresponding multiple fatigue test conditions.

[0087] In this embodiment, after obtaining the target operating angle and target torque that meet the preset conditions, for each target operating angle, the target operating angle is sequentially combined with all other target operating angles except the target operating angle to obtain multiple angle groups. For example, as shown in Table 3, taking θ1 as an example, θ1 is combined with θ2…θ m By combining them in sequence, multiple lifting starting angle groups as shown in Table 6 can be obtained, such as θ1θ2, θ1θ3, etc.

[0088] Table 6 Lifting start angle group

[0089] Lifting start angle group <![CDATA[θ1θ2]]> <![CDATA[θ1θ3]]> <![CDATA[θ2θ3]]> …… …… <![CDATA[θ m-1 i m ]]>

[0090] At the same time, the obtained target torques are sorted in ascending order to obtain the maximum target torque and the minimum target torque, and are respectively determined as the maximum value Fmax and the minimum value Fmin of all target torques. Based on the maximum value Fmax and the minimum value Fmin, the following is obtained: Figure 5 The torque interval schematic diagram for all target torques is shown, and the value of the torque interval is [Fmin, Fmax]. It should be noted that the preset ratio can be set to 100N, so the torque interval can be divided into equal proportions with 100N as the division interval to obtain a plurality of consecutive sub-torque intervals. For example, as shown in Table 7, a load F table including a plurality of consecutive sub-torque intervals is provided.

[0091] Table 7 Load F table

[0092] Serial number F[N] 1 F1(f1,f2,f3,f4) 2 F2(f1,f2,f3,f4) 3 F3(f1,f2,f3,f4) …… …… …… …… j Fj(f1,f2,f3,f4)

[0093] Each sub-torque interval obtained by division is sequentially combined with each angle group obtained by combination to generate a corresponding plurality of fatigue test conditions. Specifically, each angle group in the lifting start angle group shown in Table 6 can be sequentially combined with each sub-torque interval in the load F table shown in Table 7 to obtain the fatigue test condition table shown in Table 8.

[0094] Table 8 Fatigue test conditions

[0095] Load\Start Angle <![CDATA[θ1θ2]]> <![CDATA[θ1θ3]]> …… <![CDATA[θ m-1 i m ]]> F1(f1,f2,f3,f4) Condition 1 Condition 2 …… …… F2(f1,f2,f3,f4) …… …… …… …… …… …… …… …… …… Fj(f1,f2,f3,f4) …… …… …… Working condition K

[0096] Specifically, for any fatigue test condition in Table 8, fatigue test training is repeated for the fatigue test condition, that is, each condition is repeatedly executed according to the load and starting angle in the fatigue test condition table until the boom stops after fatigue cracks exist under the fatigue test condition. The number of repeated training Ti of the fatigue test condition at this time is recorded, and Ti is determined as the fatigue life of the boom under the fatigue test condition. At the same time, the reciprocal of the fatigue life Ti 1 / Ti is taken as the damage value Di corresponding to the fatigue test condition. After determining the damage value corresponding to each fatigue test condition, a fatigue damage library as shown in Table 1 is constructed based on the correspondence between each fatigue test condition and the damage value.

[0097] In an embodiment of the present application, the monitoring method further includes: generating a corresponding alarm signal when the remaining life of the boom is lower than a preset threshold or a failure occurs in the aerial work machinery.

[0098] In this embodiment, it should be noted that the preset threshold can be set according to actual needs, for example, it can include but is not limited to being set to half a year. Specifically, when the remaining life of the boom is less than half a year or a failure occurs in the aerial work machinery, an alarm reminder mechanism is initiated. The configured alarm system will send an alarm signal to the service equipment via GPRS, triggering the alarm of the service equipment to alert the user to perform maintenance in time. At the same time, the alarm system will send text messages to the pre-bound mobile phone number and email address, and push alarm information. The alarm information contains the diagnosis results to remind the user to perform maintenance in time.

[0099] The present technical scheme provides a method for determining the remaining life of a boom, by acquiring the operating data of the aerial work machinery, such as the operating angle of the boom and the torque of multiple legs in real time during the operation of the aerial work machinery, and determining the real-time damage value corresponding to the operating data based on a fatigue damage library, wherein the fatigue damage library includes the correspondence between multiple operating angles and torques and the damage values ​​of the boom, and then further determining the historical cumulative damage value of the boom based on the model information of the aerial work machinery, thereby determining the remaining life of the boom based on the real-time damage value and the historical cumulative damage value, so as to achieve real-time and accurate prediction of the fatigue life of the boom, while effectively improving the safety of the aerial work machinery.

[0100] The present application provides a monitoring device for aerial work machinery, including:

[0101] a memory configured to store instructions; and

[0102] The processor is configured to call the instructions from the memory and implement a monitoring method for aerial work machinery when executing the instructions.

[0103] An embodiment of the present application provides a machine-readable storage medium on which a program is stored. When the program is executed by a processor, the above-mentioned monitoring method for aerial work machinery is implemented.

[0104] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 6 As shown. The computer device includes a processor A01, a network interface A02, a memory (not shown in the figure) and a database (not shown in the figure) connected through a system bus. Among them, the processor A01 of the computer device is used to provide computing and control capabilities. The memory of the computer device includes an internal memory A03 and a non-volatile storage medium A04. The non-volatile storage medium A04 stores an operating system B01, a computer program B02 and a database (not shown in the figure). The internal memory A03 provides an environment for the operation of the operating system B01 and the computer program B02 in the non-volatile storage medium A04. The database of the computer device is used to store monitoring method data for aerial work machinery. The network interface A02 of the computer device is used to communicate with an external terminal through a network connection. When the computer program B02 is executed by the processor A01, a monitoring method for aerial work machinery is implemented.

[0105] Those skilled in the art will understand that Figure 6 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0106] The present application also provides an aerial work machine, including:

[0107] Multiple outriggers;

[0108] a chassis, fixed on a plurality of legs;

[0109] A boom, one end of which is fixed to the chassis; and

[0110] The above-mentioned monitoring device for aerial work machinery.

[0111] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing a program for initializing the steps of a monitoring method for aerial work machinery.

[0112] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0113] The present application is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0114] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0115] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0116] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0117] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0118] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules 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 technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0119] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0120] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A monitoring method for aerial work machinery, characterized in that: The monitoring method comprises: During the operation of the aerial work machine, first electrical data and first hydraulic data of the aerial work machine are acquired in real time; Updating the digital twin model of the aerial work machine based on the first electrical data, the first hydraulic data, and historical electrical data and historical hydraulic data of the aerial work machine within a historical time period; Acquire second electrical data and second hydraulic data obtained by simulating the digital twin model based on the first electrical data and the first hydraulic data; Determine the current operating state of the aerial work machine according to the first electrical data, the second electrical data, the first hydraulic data, and the second hydraulic data; When it is determined that the aerial work machine has a fault according to the operating state of the aerial work machine, the fault type of the aerial work machine is determined according to the first electrical data and the first hydraulic data.

2. The monitoring method for aerial work machinery according to claim 1, characterized in that: The monitoring method further comprises: During the operation of the aerial work machine, real-time acquisition of operating data of the aerial work machine, wherein the aerial work machine comprises at least a chassis, a boom and a plurality of legs, and the operating data comprises at least an operating angle of the boom and a torque of the plurality of legs; Determine a real-time damage value corresponding to the operation data based on a fatigue damage library, wherein the fatigue damage library includes a correspondence between a plurality of operation angles and moments and a damage value of the operating mechanism, and the correspondence is obtained after fatigue test training based on a plurality of historical operation angles and historical moments that meet preset conditions; Determining a historical cumulative damage value of the boom based on the model information of the aerial work machinery; The remaining life of the boom is determined based on the real-time damage value and the historical accumulated damage value.

3. The monitoring method for aerial work machinery according to claim 2, characterized in that: The monitoring method further comprises: When the remaining life of the boom is lower than a preset threshold or the aerial work machine fails, a corresponding alarm signal is generated.

4. The monitoring method for aerial work machinery according to claim 2, characterized in that: The method further comprises a step of constructing a fatigue damage library, wherein the step of constructing the fatigue damage library comprises: Acquire a plurality of historical operation data of the aerial work machine in a historical time period, wherein the plurality of historical operation data include a plurality of historical operation angles of the boom and a plurality of historical moments of the plurality of legs; For a plurality of historical operation angles, determining the cumulative number of occurrences of each historical operation angle within the historical time period; Eliminate historical operating angles whose cumulative occurrence times are lower than a preset number threshold, and determine the remaining historical operating angles as target operating angles that meet the preset conditions; Analyze the multiple historical moments and select target moments that meet preset conditions; Generate fatigue test conditions based on target operating angle and target torque; For any fatigue test condition, fatigue test training is repeatedly performed on the fatigue test condition until fatigue cracks occur in the boom under the fatigue test condition, and the number of training times for the fatigue test condition is determined as the fatigue life of the boom under the fatigue test condition; Based on the fatigue life of the boom under each fatigue test condition, a damage value corresponding to each fatigue test condition is determined, and a fatigue damage library is constructed based on the corresponding relationship between each fatigue test condition and the damage value.

5. The monitoring method for aerial work machinery according to claim 4, characterized in that: The analyzing the multiple historical moments and selecting the target moments meeting the preset conditions comprises: Performing normal distribution analysis on the multiple historical moments to obtain normal distribution graphs for the multiple historical moments; Based on the normal distribution diagram, historical moments outside a preset interval are eliminated, and the remaining historical moments are determined as target moments that meet preset conditions.

6. The monitoring method for aerial work machinery according to claim 4, characterized in that: The fatigue test condition generated based on the target operating angle and the target torque includes: For each target operating angle, sequentially combine the target operating angle with all other target operating angles except the target operating angle to obtain a plurality of angle groups; Sort all target moments in ascending order to obtain moment intervals for all target moments; Dividing the torque interval into a plurality of continuous sub-torque intervals in sequence based on a preset division ratio; Each sub-torque interval is combined with each angle group in sequence to generate corresponding multiple fatigue test conditions.

7. The monitoring method for aerial work machinery according to claim 1, characterized in that: Determining the fault type of the aerial work machine according to the first electrical data and the first hydraulic data includes: Inputting the first electrical data and the first hydraulic data into a fault detection model so as to output corresponding data labels through the fault detection model; The fault type corresponding to the data label is determined based on a data label library, wherein the data label library includes multiple labels and a fault type corresponding to each label, and the fault type includes at least one of a broken rotor bar fault, a stator fault, a bearing fault, a cylinder wear, an oil leakage, and a bearing wear.

8. A monitoring device for aerial work machinery, characterized in that: include: a memory configured to store instructions; as well as A processor is configured to call the instructions from the memory and implement the monitoring method for aerial work machinery according to any one of claims 1 to 7 when executing the instructions.

9. A high-altitude working machine, characterized in that: include: The monitoring device for aerial work machinery according to claim 8; Multiple outriggers; A chassis, fixed on the plurality of legs; An arm frame, one end of which is fixed on the chassis.

10. A machine-readable storage medium having instructions stored thereon, characterized in that: When the instruction is executed by a processor, the processor is configured to execute the monitoring method for aerial work machinery according to any one of claims 1 to 7.

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