A work recognition method, device, equipment and crane

Abstract

The application provides a work recognition method, device and equipment and a crane. The work recognition method comprises the following steps: acquiring work data of a mechanical device; extracting work features in the work data, wherein the work features are determined according to actions performed in a work process of the mechanical device; and in the case that the work features match a work flow of a target working condition, counting the work data as target work data matching the target working condition. According to the technical scheme of the application, the target working condition can be recognized according to the work data of the mechanical device, so that the work data of the mechanical device related to the target working condition is effectively developed and utilized, and the data value of the work data of the mechanical device is fully tapped.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of data processing, in particular to a work recognition method and device, and a crane. BACKGROUND

[0002] With the development of industry, mechanical equipment is widely used in industrial construction and plays an important role in China's modernization.

[0003] The mechanical equipment in the prior art can collect work data during work. However, after collecting the work data, the work data is not effectively developed and utilized, especially the work data related to the working condition is not analyzed, the specific working condition cannot be identified, and the data value is difficult to mine. For example, in the process of hoisting a fan, the prior art does not analyze the work data related to the hoisting of the fan collected by the hoisting equipment, and the specific hoisting work process cannot be identified, and the data value of the work data related to the hoisting of the fan is difficult to mine.

[0004] Therefore, how to identify a specific working condition according to the work data of the mechanical equipment, so that the work data of the mechanical equipment related to the specific working condition can be effectively developed and utilized, is a technical problem to be solved by those skilled in the art. SUMMARY

[0005] Therefore, the present application provides a work recognition method, device, equipment and crane, which can identify a specific working condition according to the work data of the mechanical equipment.

[0006] According to a first aspect of an embodiment of the present application, a work recognition method is provided, comprising:

[0007] obtaining work data of a mechanical equipment;

[0008] extracting work features in the work data, wherein the work features are determined according to actions performed in the work process of the mechanical equipment;

[0009] in a case where the work features match a work flow of a target working condition, the work data is counted as target work data matching the target working condition.

[0010] Optionally, after the work data is counted as the target work data matching the target working condition, the method further comprises:

[0011] collecting a plurality of groups of target work data matching the target working condition;

[0012] analyzing the plurality of groups of target work data to generate an optimization result of a work parameter of the target working condition.

[0013] Optionally, the work data comprises work location information, and after the work data is counted as target work data matching the target working condition, the method further comprises:

[0014] counting work location information of multiple sets of target work data matching the target working condition;

[0015] generating work region distribution data corresponding to the target working condition according to the counted work location information.

[0016] Optionally, the work data comprises work location information, and after the work data of the mechanical equipment is obtained, the method further comprises:

[0017] dividing the work data into at least one working condition data block according to work location information of the work data, wherein each working condition data block comprises work data of the mechanical equipment at one work site;

[0018] the extracting of the work feature in the work data comprises:

[0019] extracting the work feature of each working condition data block respectively.

[0020] Optionally, before the work data is counted as target work data matching the target working condition, the method further comprises:

[0021] obtaining historical work data of the mechanical equipment performing the target working condition;

[0022] generating historical work features of the target working condition according to the historical work data;

[0023] determining a work flow of the target working condition according to an arrangement order of the historical work features.

[0024] Optionally, the work flow of the target working condition comprises work flows of various work stages of the target working condition;

[0025] the counting of the work data as target work data matching the target working condition in the case that the work feature matches the work flow of the target working condition comprises:

[0026] comparing the work feature with work flows of various work stages of the target working condition to determine whether the work feature matches the work flows of various work stages of the target working condition;

[0027] determining whether the job feature matches the job flow of the target working condition according to an order of each target data segment in the job data and an order of each working stage of the target working condition, the each target data segment being a job data segment matched with each working stage of the target working condition;

[0028] in a case where the job feature matches the job flow of the target working condition, counting the job data as target job data matched with the target working condition.

[0029] Optionally, the comparing the job feature with the job flow of each working stage of the target working condition and determining whether the job feature matches the job flow of each working stage of the target working condition comprises:

[0030] comparing the job feature with the job flow of a first working stage of the target working condition and determining whether the job feature matches the job flow of the first working stage of the target working condition;

[0031] in a case where the job feature matches the job flow of the first working stage of the target working condition, comparing the job feature with the job flow of a second working stage of the target working condition and determining whether the job feature matches the job flow of the second working stage of the target working condition;

[0032] repeating the above processing until it is determined whether the job feature matches the job flow of each working stage of the target working condition.

[0033] Optionally, the mechanical equipment is a hoisting equipment, and the job data comprises one or more of hoisting weight, hoisting height, hoisting posture and hoisting time.

[0034] According to a second aspect of the embodiment of the present application, a job recognition device is provided, comprising:

[0035] a data acquisition unit configured to acquire job data of a mechanical equipment;

[0036] a feature extraction unit configured to extract a job feature in the job data, wherein the job feature is determined according to an action performed in a working process of the mechanical equipment;

[0037] a recognition unit configured to, in a case where the job feature matches a job flow of a target working condition, count the job data as target job data matched with the target working condition.

[0038] According to a third aspect of the embodiment of the present application, a job recognition device is provided, comprising:

[0039] a processor, and a memory connected with the processor;

[0040] the memory is configured to store a computer program;

[0041] the processor is configured to invoke and execute the computer program in the memory to perform the job identification method according to the first aspect of the present application.

[0042] According to a fourth aspect of the present application, a crane is provided, comprising the job identification device according to the third aspect of the present application.

[0043] The technical solution provided by the present application can include the following beneficial effects:

[0044] In the technical solution provided by the present application, first, job data of a mechanical device is acquired; then, job features in the job data are extracted, wherein the job features are determined according to actions performed in a job process of the mechanical device; finally, in a case where the job features match a job flow of a target working condition, the job data is counted as target job data matching the target working condition. By using the technical solution of the present application, the target working condition can be identified according to the job data of the mechanical device, so that the job data of the mechanical device related to the target working condition is effectively developed and utilized, and the data value of the job data of the mechanical device is fully tapped. BRIEF DESCRIPTION OF DRAWINGS

[0045] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced as follows. Obviously, the drawings in the following description are only embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor on the basis of the provided drawings.

[0046] Figure 1 An application scenario diagram of a job identification method provided by an embodiment of the present application.

[0047] Figure 2 A flowchart of a first job identification method provided by an embodiment of the present application.

[0048] Figure 3 A flowchart of a second job identification method provided by an embodiment of the present application.

[0049] Figure 4 A flowchart of a third job identification method provided by an embodiment of the present application.

[0050] Figure 5 A flowchart of a fourth job identification method provided by an embodiment of the present application.

[0051] Figure 6 A flowchart of a fifth work identification method provided by an embodiment of the present application is shown.

[0052] Figure 7 A structural diagram of a work identification device provided by an embodiment of the present application is shown.

[0053] Figure 8 A structural diagram of a work identification device provided by an embodiment of the present application is shown. DETAILED DESCRIPTION

[0054] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0055] With the development of industry, mechanical equipment is widely used in industrial construction and plays an important role in modernization construction in China.

[0056] The mechanical equipment in the prior art can collect work data during work. However, after collecting the work data, the work data is not effectively developed and utilized, especially the work data related to the working condition is not analyzed specifically, the specific working condition cannot be identified, and the data value of the work data is difficult to mine. For example, during the hoisting work of the fan, the work data related to the hoisting of the fan collected by the hoisting equipment is not analyzed specifically in the prior art, the specific hoisting work process cannot be identified, and the data value of the work data related to the hoisting of the fan is difficult to mine.

[0057] Therefore, how to identify the specific working condition according to the work data of the mechanical equipment so that the work data of the mechanical equipment related to the specific working condition can be effectively developed and utilized is a technical problem to be solved by those skilled in the art.

[0058] Therefore, how to identify the specific working condition according to the work data of the mechanical equipment so that the work data of the mechanical equipment related to the specific working condition can be effectively developed and utilized is a technical problem to be solved by those skilled in the art.

[0059] The embodiments of the present application provide a work identification method, which can be applied, for example, to the application scenario as shown in Figure 1 Figure 1 Figure 1 ​​An application scenario of a work recognition method provided in an embodiment of the present application is shown in FIG. 1. A vehicle terminal 110 installed on a hoisting device is connected to a server 120 through a communication network to transmit data. The vehicle terminal 110 can acquire work data of the hoisting device and transmit the acquired work data of the hoisting device to the server 120 through the communication network. After receiving the work data of the hoisting device transmitted by the vehicle terminal 110, the server 120 can execute the work recognition method provided in the embodiment of the present application.

[0060] The vehicle terminal 110 can be a vehicle terminal device installed on or carried by the hoisting device, for example, a vehicle computer inside the hoisting device or a smart phone, a tablet computer, a notebook computer or other terminal device connected to the vehicle computer, which is not limited in the present application.

[0061] The server 120 can be a stand-alone physical server, a server group composed of multiple physical servers, or a cloud server providing cloud computing services, which is not limited in the present application.

[0062] The communication network can be any form of wireless communication network or wired communication network, or any combination thereof, which is not limited in the present application.

[0063] In some optional embodiments, the vehicle terminal 110 can control the sensor device on the hoisting device, for example, the work data of the hoisting device can be collected by the sensor carried by the hoisting device, and the vehicle terminal acquires the above work data.

[0064] Please refer to Figure 2 , Figure 2 A flowchart of a work recognition method provided in an embodiment of the present application is shown in FIG. 2. As shown in FIG. 2, the work recognition method of the present embodiment includes the following steps S201-S203: Figure 2

[0065] S201, acquiring work data of a mechanical device.

[0066] The mechanical device can be understood as a mechanical equipment necessary for mechanized construction engineering, which can be the hoisting device shown in FIG. 1, or a mechanical equipment such as an excavator, a shovel transporter, a road roller, etc. not shown in FIG. 1, which is not limited in the present application. Figure 1 Figure 1 The work data can be understood as data related to work generated by the mechanical device when performing work. For example, the mechanical device can be a hoisting device, which performs hoisting work, and the work data is data related to hoisting work, including one or more of hoisting weight, hoisting height, hoisting posture and hoisting time.

[0067] The work data can be understood as data related to work generated by the mechanical device when performing work. For example, the mechanical device can be a hoisting device, which performs hoisting work, and the work data is data related to hoisting work, including one or more of hoisting weight, hoisting height, hoisting posture and hoisting time. ​​

[0068] The operation data can be collected by a sensor arranged on the mechanical equipment, the vehicle terminal acquires the operation data, and sends the operation data to the server through a communication network, and the server acquires the operation data of the mechanical equipment.

[0069] S202, extracting operation features in the operation data, wherein the operation features are determined according to actions performed in the operation process of the mechanical equipment.

[0070] The operation features can be understood as data features extracted from the operation data of the mechanical equipment, which can represent the working content, working process and working state of the mechanical equipment, and are determined by the actions performed by the mechanical equipment in the operation process.

[0071] Specifically, after the server acquires the operation data of the mechanical equipment, the operation features of the operation data are extracted from the acquired operation data.

[0072] S203, in the case that the operation features match the operation process of the target working condition, the operation data is counted as target operation data matching the target working condition.

[0073] The target working condition can be understood as the standard working state of the mechanical equipment when performing target operation, and the operation process can be understood as the action process of the mechanical equipment in the standard working state when performing target operation.

[0074] The operation features matching the operation process of the target working condition can be understood as the operation features extracted by the server from the operation data of the mechanical equipment matching the first operation features of the operation data generated when the mechanical equipment (or the same model mechanical equipment as the mechanical equipment) performs target operation in the target working condition.

[0075] The first operation features of the operation data generated when the mechanical equipment performs target operation in the target working condition can be pre-determined and stored, and when step S203 is performed, the first operation features can be directly read from the data storage position storing the first operation features of the operation data generated when the mechanical equipment performs target operation in the target working condition.

[0076] The first operation features of the operation data generated when the mechanical equipment performs target operation in the target working condition can be determined by feature extraction on the operation data generated when the mechanical equipment performs target operation in the target working condition. In addition, the first operation features can also be determined by processing the historical operation data of the mechanical equipment performing the target working condition.

[0077] Specifically, after obtaining the work data of the mechanical equipment and extracting the work feature from the work data, the server compares the work feature with a first work feature of work data generated when the mechanical equipment performs a target work under a target working condition. If the comparison result meets a preset requirement, for example, a data feature segment matching the first work feature can be matched from the work feature, or a matching degree between the work feature and the first work feature reaches a preset threshold, it is determined that the work feature matches the first work feature, that is, the work feature matches a work flow of the target working condition. In the case that the work feature matches the work flow of the target working condition, the work data is counted as target work data matching the target working condition.

[0078] Optionally, the first work feature of work data generated when the mechanical equipment performs a target work under a target working condition can be a model of the target working condition, and the server obtains the model of the target working condition from a cloud or a server internal storage space. After obtaining the work data of the mechanical equipment and extracting the work feature from the work data, the server compares the work feature with the model of the target working condition to determine whether the work feature matches the work flow of the target working condition.

[0079] Optionally, the first work feature of work data generated when the mechanical equipment performs a target work under a target working condition can be a fixed feature value, and the work feature is also represented in the form of a feature value. The step S203 can include steps S1-S2:

[0080] S1, calculating a difference between the work feature and the first work feature of work data generated when the mechanical equipment performs a target work under a target working condition.

[0081] S2, comparing the difference with a preset threshold to determine whether the difference meets the preset threshold. If the preset threshold is met, it is determined that the work feature matches the first work feature of work data generated when the mechanical equipment performs a target work under a target working condition, that is, the work feature matches a work flow of the target working condition. The work data is counted as target work data matching the target working condition.

[0082] It should be noted that the preset threshold is obtained after multiple tests according to historical work data, which is not limited in the present application.

[0083] Optionally, the first work feature of work data generated when the mechanical equipment performs a target work under a target working condition can be a feature value interval, and the work feature is represented in the form of a feature value. The step S203 can include the following steps:

[0084] determining whether the work feature meets a value interval of a first work feature of work data generated when the mechanical equipment performs the target work in the target working condition, and if so, determining that the work feature matches the first work feature of the work data generated when the mechanical equipment performs the target work in the target working condition, that is, the work feature matches the work flow of the target working condition.

[0085] As can be seen from the above, the work recognition method provided by the embodiments of the present application first acquires work data of a mechanical equipment, then extracts a work feature in the work data, wherein the work feature is determined according to actions performed in a working process of the mechanical equipment, and finally, in the case that the work feature matches a work flow of a target working condition, the work data is counted as target work data matching the target working condition. By using the technical solution of the present application, the target working condition can be recognized according to the work data of the mechanical equipment, so that the work data of the mechanical equipment related to the target working condition is effectively developed and utilized, and the data value of the work data of the mechanical equipment is fully tapped.

[0086] Optionally, before step S203 is performed, the method further includes steps A1-A3:

[0087] A1, acquiring historical work data of the mechanical equipment performing the target working condition.

[0088] The historical work data refers to work data generated in a process of the mechanical equipment performing a historical working condition multiple times.

[0089] The historical work data can be acquired by the server from the cloud, or directly acquired by the server from an internal storage space of the server.

[0090] A2, generating a historical work feature of the target working condition according to the historical work data.

[0091] After the server acquires the work data generated in the process of the mechanical equipment performing the historical working condition multiple times, the server extracts effective features related to target work in the work data generated in the process of the mechanical equipment performing the historical working condition each time, and determines the historical work feature of the target working condition according to the effective features related to target work in the work data generated in the process of the mechanical equipment performing the historical working condition each time.

[0092] A3, determining a work flow of the target working condition according to an arrangement order of the historical work feature.

[0093] From the above, the operation feature is determined by the action performed by the mechanical equipment in the working process of performing the target operation, and can represent the data feature of the working content, working process and working state of the mechanical equipment. According to the historical operation feature, the action performed by the mechanical equipment in the historical working process can be determined, and according to the arrangement order of the action, the operation flow of the target working condition can be determined.

[0094] Further, the target operation can include multiple working stages, such as the wind turbine hoisting operation which can include hoisting the tower, hoisting the nacelle and hoisting the blade. In this case, in order to further improve the identification effect of the target operation, the application provides an optional implementation. In the optional implementation, step S203 can specifically include steps B1-B3:

[0095] B1, compare the operation feature with the operation flow of each working stage of the target working condition to determine whether the operation feature matches the operation flow of each working stage of the target working condition.

[0096] The operation feature matches the operation flow of one working stage of the target working condition, which can be understood as that the operation feature matches the first operation feature of the operation data generated by the mechanical equipment when performing the working stage of the target operation under the target working condition.

[0097] Specifically, after the server obtains the operation data of the mechanical equipment and extracts the operation feature in the operation data, the server compares the operation feature with each first operation feature of the operation data generated by the mechanical equipment when performing each working stage of the target operation under the target working condition. If each comparison result meets the preset requirement, for example, from the operation feature, each first operation feature of the operation data generated by the mechanical equipment when performing each working stage of the target operation under the target working condition can be matched, or the matching degree between the operation feature and each first operation feature reaches the preset threshold, it is determined that the operation feature matches the operation flow of each working stage of the target working condition. At this time, step B2 can be continued; otherwise, it is determined that the operation data does not match the operation flow of each working stage of the target working condition, and the process is ended.

[0098] For example, the target work includes three work stages a, b and c. In this case, the work feature of the work data A is compared with the first work feature of the work data generated when the machine equipment executes the work stage a in the standard work state with the standard action flow. If the comparison result meets the preset requirement, for example, the comparison result indicates that the work feature contains a feature segment matching the first work feature, it is indicated that the work data A matches the work flow of the work stage a of the target work condition, otherwise, it is indicated that the work data A does not match the work flow of the work stage a of the target work condition. According to the above comparison scheme, it can be judged whether the work data A matches the work flow of the work stage a, the work stage b and the work stage c of the target work condition. If yes, step B2 is executed, and if no, the process is ended.

[0099] B2, in the case that the work feature matches the work flow of each work stage of the target work condition, whether the work feature matches the work flow of the target work condition is determined according to the order of each target data segment in the work data and the order of each work stage of the target work condition; the each target data segment is respectively a work data segment matching each work stage of the target work condition.

[0100] In the case that the work feature of the work data matches the work flow of one work stage of the target work condition, it can be determined that the work data contains a target data segment matching the work stage of the target work condition. Similarly, in the case that the work feature of the work data matches the work flow of each work stage of the target work condition, it can be determined that the work data contains each target data segment respectively matching each work stage of the target work condition.

[0101] The order of each target data segment contained in the work data and respectively matching each work stage of the target work condition is compared with the order of each work stage of the target work condition, and whether the above two orders are the same is judged. If yes, it is determined that the work feature of the work data matches the work flow of the target work condition, and step B3 is continued to be executed; if no, it is determined that the work feature of the work data does not match the work flow of the target work condition, and the process is ended.

[0102] B3, in the case that the work feature matches the work flow of the target work condition, the work data is counted as the target work data matching the target work condition.

[0103] The specific content of step B3 can be referred to the content of step S203 in the embodiment shown in Figure 2 The content of step S203 in the embodiment shown in

[0104] Further, to improve the operation recognition speed and reduce the calculation amount, an optional implementation manner is provided in the embodiments of the present application, in which step B1 can specifically include steps C1-C3.

[0105] C1, compare the operation feature with the operation flow of the first working stage of the target working condition, and determine whether the operation feature matches the operation flow of the first working stage of the target working condition.

[0106] The operation feature is compared with the operation flow of the first working stage of the target working condition. If the comparison result meets the preset requirement, for example, a feature segment that matches the first operation feature of the operation data generated when the mechanical equipment performs the first working stage of the target operation under the target working condition can be matched from the operation feature, it is determined that the operation feature matches the operation flow of the first working stage of the target working condition, and step C2 is continued to be executed. Otherwise, it is determined that the operation feature does not match the operation flow of the first working stage of the target working condition, i.e., the operation feature does not match the operation flow of the target working condition, and the process is ended.

[0107] C2, when the operation feature matches the operation flow of the first working stage of the target working condition, the operation feature is compared with the operation flow of the second working stage of the target working condition, and it is determined whether the operation feature matches the operation flow of the first working stage of the target working condition and the operation flow of the second working stage of the target working condition.

[0108] When it is determined that the operation feature matches the operation flow of the first working stage of the target working condition, the operation feature is compared with the operation flow of the second working stage of the target working condition. If the comparison result meets the preset requirement, for example, a feature segment that matches the first operation feature of the operation data generated when the mechanical equipment performs the second working stage of the target operation under the target working condition can be matched from the operation feature, it is determined that the operation feature matches the operation flow of the second working stage of the target working condition, and step C3 is continued to be executed. Otherwise, it is determined that the operation feature does not match the operation flow of the second working stage of the target working condition, i.e., the operation feature does not match the operation flow of the target working condition, and the process is ended.

[0109] C3, the above process is repeatedly executed until it is determined whether the operation feature matches the operation flow of each working stage of the target working condition.

[0110] It should be noted that the work stages of the target operation can be determined in order as the first work stage, the second work stage, and the nth work stage according to the order of performing the work stages of the target operation according to the standard requirements, or can be determined in order as the first work stage, the second work stage, and the nth work stage according to the difficulty of identifying the first work feature of the work data generated when the mechanical equipment performs each work stage of the target operation, from simple to difficult, or can be determined as the first work stage, the second work stage, and the nth work stage according to other rules, and the application does not make specific limitations.

[0111] Preferably, the first work stage, the second work stage, and the nth work stage are determined in order according to the difficulty of identifying the first work feature of the work data generated when the mechanical equipment performs each work stage of the target operation, from simple to difficult, which can further improve the work recognition efficiency and reduce the amount of calculation.

[0112] Further, the target operation can be a wind turbine hoisting operation, and the wind turbine hoisting operation includes a tower hoisting operation, a nacelle hoisting operation, and three work stages including a blade hoisting operation or a blade assembly hoisting operation. The blade hoisting operation refers to hoisting the wind turbine blade in the form of a single blade to a designated position, and the blade assembly hoisting operation refers to mounting the wind turbine blade on the hub and hoisting the blade assembly to a designated position. In actual application, the wind turbine hoisting operation can be selected to include the blade hoisting operation or the blade assembly hoisting operation according to the actual working condition, i.e., the wind turbine hoisting operation can be selected to include the blade hoisting operation or the blade assembly hoisting operation according to the actual working condition.

[0113] Figure 3 The second work recognition method provided by the embodiment of the application is suitable for the case that the target operation is a wind turbine hoisting operation, and the wind turbine hoisting operation includes a tower hoisting operation, a nacelle hoisting operation, and three work stages including a blade hoisting operation or a blade assembly hoisting operation. As shown in Figure 3 The step B1 includes the following steps S303-S308:

[0114] S301, obtaining work data of a hoisting device.

[0115] S302, extracting a work feature in the work data, wherein the work feature is determined according to an action performed in a working process of the hoisting device.

[0116] The steps S301 and S302 correspond to the steps S201 and S202 in the foregoing embodiment respectively, and the specific content of the steps S301 and S302 can be referred to the content in the foregoing embodiment, which will not be described here.

[0117] S303, compare the job characteristics with the job flow of hoisting the tower section in the target working condition.

[0118] The job characteristics obtained in step S302 are compared with the first job characteristics of the job data generated when the hoisting device hoists the tower section in the standard working state and with the standard action flow.

[0119] The job characteristics include but are not limited to the change process of hoisting weight, etc.

[0120] S304, determine whether the job characteristics match the job flow of hoisting the tower section in the target working condition.

[0121] If the comparison result obtained in step S303 meets the preset requirement, it is determined that the job characteristics match the job flow of hoisting the tower section in the target working condition, and step S305 is performed; otherwise, it is determined that the job characteristics do not match the job flow of hoisting the tower section in the target working condition, i.e., it is determined that the job characteristics do not match the job flow of the target working condition, and step S3011 is performed to end the process.

[0122] S305, compare the job characteristics with the job flow of hoisting the nacelle in the target working condition.

[0123] For specific contents, reference can be made to the contents of step S303, which will not be repeated here.

[0124] S306, determine whether the job characteristics match the job flow of hoisting the nacelle in the target working condition.

[0125] If the comparison result obtained in step S305 meets the preset requirement, it is determined that the job characteristics match the job flow of hoisting the nacelle in the target working condition, and step S307 is performed; otherwise, it is determined that the job characteristics do not match the job flow of the target working condition, and step S3011 is performed to end the process.

[0126] S307, compare the job characteristics with the job flow of hoisting the blade or hoisting the blade assembly in the target working condition.

[0127] For specific contents, reference can be made to the contents of step S303, which will not be repeated here.

[0128] S308, determine whether the job characteristics match the job flow of hoisting the blade or hoisting the blade assembly in the target working condition.

[0129] If the comparison result obtained in step S307 meets the preset requirement, it is determined that the job characteristics match the job flow of hoisting the blade or hoisting the blade assembly in the target working condition, and step S309 is performed; otherwise, it is determined that the job characteristics do not match the job flow of the target working condition, and step S3011 is performed to end the process.

[0130] S309, determine whether the operation feature matches the operation flow of the target working condition according to the order of each target data segment in the operation data respectively matched with the tower hoisting operation, the machine cabin hoisting operation, and the blade hoisting operation or the blade assembly hoisting operation in the target working condition, and the order of each working stage of the target working condition.

[0131] The specific processing process of step S309 can refer to the content of step B2.

[0132] S3010, in the case that the operation feature matches the operation flow of the target working condition, count the operation data as target operation data matched with the target working condition.

[0133] S3011, end the process.

[0134] In Figure 3 In the embodiment shown, in each working stage of the wind turbine hoisting operation, the operation feature is preferentially compared with the operation flow of the tower hoisting operation in the target working condition, and the reason for determining whether the operation feature matches the operation flow of the tower hoisting operation in the target working condition is that the tower hoisting operation has the data feature of hoisting and overturning point compared with other hoisting operations in the working stage, which is easier to be identified. Preferentially determining whether the operation feature matches the operation flow of the tower hoisting operation in the target working condition can further improve the identification efficiency of the wind turbine hoisting operation and reduce the calculation amount.

[0135] For example, comparing the operation feature with the operation flow of the tower hoisting operation in the target working condition to determine whether the operation feature matches the operation flow of the tower hoisting operation in the target working condition can include the following steps D1-D6:

[0136] D1, clear the abnormal data in the operation data, the abnormal data refers to the data containing null value, large mutation value and other obvious abnormal value.

[0137] D2, compare the torque percentage and hoisting height in the operation data with the corresponding torque percentage and hoisting height in the hoisting operation data of the hoisting tower, and determine whether the comparison result meets the preset requirement, that is, whether the torque percentage and the hoisting height are within the preset range. If yes, execute step D3, if not, determine that the operation feature does not match the operation flow of the tower hoisting operation in the target working condition, and end the process.

[0138] D3, smooth the hoisting weight data in the operation data.

[0139] D4, calculate the hoisting weight change and average hoisting weight of each time window of the hoisting weight data in the processed job data of step D3 by using a time sliding window, and compare the hoisting weight data features corresponding to the tower overturning points in the hoisting tower data with the hoisting weight data features corresponding to the tower overturning points in the hoisting tower data, if the comparison result of a certain time window meets the preset requirement, that is, the hoisting weight change and average hoisting weight of a certain time window of the hoisting weight data in the processed job data of step D3 are within the preset range, record the time window as a suspected tower overturning point. Determine whether the job data block contains a suspected tower overturning point. If yes, execute step D5, if not, determine that the job feature does not match the hoisting tower operation process in the target working condition, and end the process.

[0140] D5, divide the time window corresponding to the suspected hoisting tower operation before and after the suspected tower overturning point by using the hoisting weight, amplitude and rotation angle.

[0141] D6, compare the hoisting time, peak hoisting weight, valley hoisting weight, and the proportion of the overturning point hoisting weight to the peak hoisting weight in the time window corresponding to the suspected hoisting tower operation in the job data with the hoisting time, peak hoisting weight, valley hoisting weight, and the proportion of the overturning point hoisting weight to the peak hoisting weight in the hoisting tower data, and determine whether the comparison result meets the preset requirement. If yes, determine that the job feature matches the hoisting tower operation process in the target working condition, if not, determine that the job feature does not match the hoisting tower operation process in the target working condition.

[0142] Optionally, the job data of the mechanical equipment obtained by the server in step S201 includes job position information, and the job position information is information capable of representing the position of the job site of the mechanical equipment. In this case, as an optional implementation manner, another job recognition method is provided by the embodiments of the present application, Figure 4 A third job recognition method provided by the embodiments of the present application is shown in Figure 4 The method includes steps S401-S404:

[0143] S401, obtain the job data of the mechanical equipment.

[0144] Step S401 corresponds to step S201 in the foregoing embodiments, and the specific content can be referred to the content of step S201 in the foregoing embodiments, which will not be described here.

[0145] S402, divide the job data into at least one working condition data block according to the job position information of the job data, wherein each working condition data block includes the job data of the mechanical equipment at one job site.

[0146] The job position information is information capable of representing the position of the job site of the mechanical equipment.

[0147] Optionally, when the mechanical equipment does not move or the moving distance is less than a preset distance threshold in a specified time interval, the position of the mechanical equipment is the work site of the mechanical equipment.

[0148] The work site can be determined according to the work position information in the work data of the mechanical equipment. For example, the work data of the mechanical equipment includes longitude and latitude data of the mechanical equipment. Whether the difference between the longitude and latitude data of the mechanical equipment before and after a preset time range in each window is less than a preset distance threshold is calculated by using a time sliding window. If the difference between the longitude and latitude data of the mechanical equipment before and after the preset time range is less than the preset distance threshold, the position of the mechanical equipment in the time window is the work site of the mechanical equipment.

[0149] In the embodiments of the present application, the work data of the mechanical equipment at the same work site constitutes a working condition data block, and the work data of the same mechanical equipment at different work sites belongs to different working condition data blocks.

[0150] Specifically, after obtaining the work position information of the mechanical equipment, at least one work site of the mechanical equipment can be determined according to the work position information of the mechanical equipment, and then the work data of the mechanical equipment can be further divided according to the work site of the mechanical equipment, so as to divide the work data of the mechanical equipment into at least one working condition data block, wherein the work data of the mechanical equipment at the same work site constitutes the same working condition data block.

[0151] S403, respectively extracting the work features of each working condition data block, wherein the work features are determined according to the actions performed by the mechanical equipment during the working process.

[0152] The work features of the working condition data block can be understood as the work features of the work data in the working condition data block. Therefore, respectively extracting the work features of each working condition data block can be understood as respectively extracting the work features of the work data in each working condition data block.

[0153] S404, in the case that the work features of the working condition data block match the work flow of the target working condition, the working condition data block is counted as a target working condition data block matching the target working condition.

[0154] After respectively extracting the work features of each working condition data block, the extracted work features of each working condition data block are matched with the work flow of the target working condition respectively. The working condition data block whose work features match the work flow of the target working condition is counted as a target working condition data block matching the target working condition. The remaining specific contents correspond to the content of step S203, and the content of step S203 in the foregoing embodiments can be referred to.

[0155] Optionally, when the work data of the mechanical equipment obtained by the server in step S201 includes work position information, as an optional implementation manner, the embodiment of the present application provides another work recognition method, Figure 5 A fourth work recognition method provided by the embodiment of the present application is shown in FIG. 5. Figure 5 The method includes steps S501-S505.

[0156] S501, obtaining work data of a mechanical equipment.

[0157] S502, extracting work features in the work data, wherein the work features are determined according to actions performed in a working process of the mechanical equipment.

[0158] S503, in a case where the work features match a work flow of a target working condition, counting the work data as target work data matching the target working condition.

[0159] S504, counting work position information of multiple groups of target work data matching the target working condition.

[0160] After step S503 determines that the work features match the work flow of the target working condition and counts the work data as the target work data matching the target working condition, work position information in the target work data is recorded, and work position information in multiple groups of target work data is counted.

[0161] S505, generating work region distribution data corresponding to the target working condition according to the counted work position information.

[0162] The work region distribution data corresponding to the target working condition can be understood as distribution data of work sites performing target work. The distribution data can be data representing work site distribution, and can also be data representing work site cluster distribution.

[0163] Specifically, according to the counted work position information of multiple groups of target work data, multiple work sites performing target work can be determined, positions of the multiple work sites performing target work are analyzed, and distribution data representing work site distribution, i.e., work region distribution data corresponding to the target working condition, is obtained.

[0164] Further, analyzing positions of the multiple work sites performing target work can be clustering analysis on positions of the multiple work sites performing target work, so as to determine position information of at least one cluster of the multiple work sites performing target work, and further obtain distribution data representing work site cluster distribution of the work sites performing target work.

[0165] Optionally, the clustering analysis on the positions of the multiple work sites performing the target job can be implemented by a clustering algorithm, which can be a density-based spatial clustering of applications with noise (DBSCAN) or other clustering algorithms capable of determining the cluster points of the work sites performing the target job, which are not limited in the present application.

[0166] Specifically, when the target job is the fan hoisting job, the work site performing the target job can be understood as the site where the hoisting equipment performs the fan hoisting job, and the cluster point of the multiple work sites performing the target job is the cluster point of the fan hoisting job site, i.e., the position of the wind farm.

[0167] Optionally, after recording the position of the wind farm and forming the wind farm position distribution data, the time when the hoisting equipment performs the fan hoisting job, i.e., the time when the fan is installed, can also be recorded to form a wind farm database, which helps to develop the fan maintenance market.

[0168] Figure 5 The steps S501-S503 in the embodiment shown correspond to the steps S201-S203 in the embodiment shown, and the specific content of the steps S501-S503 can be referred to the content of the steps S201-S203 in the embodiment shown, which will not be described here again. Figure 2 The steps S501-S503 in the embodiment shown correspond to the steps S201-S203 in the embodiment shown, and the specific content of the steps S501-S503 can be referred to the content of the steps S201-S203 in the embodiment shown, which will not be described here again. Figure 2 The steps S501-S503 in the embodiment shown correspond to the steps S201-S203 in the embodiment shown, and the specific content of the steps S501-S503 can be referred to the content of the steps S201-S203 in the embodiment shown, which will not be described here again.

[0169] As an optional implementation manner, the present embodiment provides another job recognition method, Figure 6 The fifth job recognition method provided by the present embodiment is shown in the following table: Figure 6 As shown in the table, the method comprises steps S601-S605:

[0170] S601, obtaining job data of a mechanical equipment.

[0171] S602, extracting a job feature in the job data, wherein the job feature is determined according to an action performed in a working process of the mechanical equipment.

[0172] S603, in the case that the job feature matches a job flow of a target working condition, counting the job data as target job data matching the target working condition.

[0173] S604, collecting multiple groups of target job data matching the target working condition.

[0174] S604, collecting multiple groups of target job data matching the target working condition.

[0175] S605, analyze the multiple sets of target operation data to generate an optimization result of the operation parameter of the target working condition.

[0176] Optionally, the operation data comprises an operation time, which refers to a time for completing the target operation. Analyzing the multiple sets of target operation data collected according to the target working condition can be understood as analyzing the operation time of the multiple sets of target operation data, determining a set of target operation data with the shortest operation time from the multiple sets of target operation data, and analyzing the set of target operation data to generate an optimization result of the operation parameter of the target working condition according to the analysis result, and optimizing the operation parameter of the target working condition.

[0177] Optionally, the operation data comprises an operation time, which refers to a time for completing the target operation. Analyzing the multiple sets of target operation data collected according to the target working condition can be understood as analyzing the operation time of the multiple sets of target operation data, determining a set of target operation data with the shortest operation time from the multiple sets of target operation data, and analyzing the set of target operation data to generate an optimization result of the operation parameter of the target working condition according to the analysis result, and optimizing the operation parameter of the target working condition.

[0178] Optionally, the operation data comprises an operation time, which refers to a time for completing the target operation. Analyzing the multiple sets of target operation data collected according to the target working condition can be understood as analyzing the operation time of the multiple sets of target operation data, determining a set of target operation data with the shortest operation time from the multiple sets of target operation data, and analyzing the set of target operation data to generate an optimization result of the operation parameter of the target working condition according to the analysis result, and optimizing the operation parameter of the target working condition.

[0179] It should be noted that, in addition to analyzing the operation time of the multiple sets of target operation data, other data contents in the multiple sets of target operation data can also be analyzed, which is not limited in the present application.

[0180] Optionally, analyzing the multiple sets of target operation data to generate an optimization result of the operation parameter of the target working condition can also be analyzing the multiple sets of target operation data to determine an average value of the multiple sets of target operation data, and generating an optimization result of the operation parameter of the target working condition according to the average value, and optimizing the operation parameter of the target working condition.

[0181] Figure 6 The steps S601-S603 in the embodiment correspond to the steps S201-S203 in the embodiment shown in Figure 2 The steps S601-S603 in the embodiment correspond to the steps S201-S203 in the embodiment shown in Figure 2 The steps S601-S603 in the embodiment correspond to the steps S201-S203 in the embodiment shown in

[0182] Corresponding to the above-mentioned work identification method, the embodiment of the present application further provides a work identification device, Figure 7 is a structural schematic diagram of a work identification device provided by the embodiment of the present application, as Figure 7 indicated, the work identification device can include:

[0183] a data acquisition unit 701 configured to acquire work data of a mechanical device;

[0184] a feature extraction unit 702 configured to extract work features in the work data, wherein the work features are determined according to actions performed in a work process of the mechanical device;

[0185] an identification unit 703 configured to, in a case where the work features match a work flow of a target working condition, count the work data as target work data matching the target working condition.

[0186] The work identification device provided by the embodiment of the present application can acquire work data of a mechanical device through the data acquisition unit 701; then extract work features in the work data through the feature extraction unit 702, wherein the work features are determined according to actions performed in a work process of the mechanical device; finally, in a case where the work features match a work flow of a target working condition, count the work data as target work data matching the target working condition through the identification unit 703. By using the technical solution of the present application, the target working condition can be identified according to the work data of the mechanical device, so that the work data of the mechanical device related to the target working condition is effectively developed and utilized, and the data value of the work data of the mechanical device is fully tapped.

[0187] Optionally, the work identification device further includes a first unit, which can be specifically configured to:

[0188] acquire a plurality of groups of target work data matching the target working condition;

[0189] analyze the plurality of groups of target work data to generate an optimization result of work parameters of the target working condition.

[0190] Optionally, the work data includes work position information, and the work identification device further includes a second unit, which can be specifically configured to:

[0191] count work position information of a plurality of groups of target work data matching the target working condition;

[0192] Generate the work area distribution data corresponding to the target work condition according to the statistical work position information.

[0193] Optionally, the work data includes work position information, and the work recognition device further includes a third unit, which can be specifically used for:

[0194] Divide the work data into at least one work condition data block according to the work position information of the work data, wherein each work condition data block includes work data of the mechanical equipment at one work site;

[0195] The feature extraction unit 702 can be specifically used for:

[0196] Respectively extract the work features of each work condition data block.

[0197] Optionally, the work recognition device further includes a fourth unit, which can be specifically used for:

[0198] Obtain historical work data of the mechanical equipment performing the target work condition;

[0199] Generate historical work features of the target work condition according to the historical work data;

[0200] Determine the work flow of the target work condition according to the arrangement order of the historical work features.

[0201] Optionally, the work flow of the target work condition includes the work flow of each work stage of the target work condition, and the recognition unit 703 can be specifically used for:

[0202] Compare the work features with the work flow of each work stage of the target work condition to determine whether the work features match the work flow of each work stage of the target work condition;

[0203] In the case that the work features match the work flow of each work stage of the target work condition, determine whether the work features match the work flow of the target work condition according to the order of each target data segment in the work data and the order of each work stage of the target work condition, wherein each target data segment is a work data segment matching each work stage of the target work condition;

[0204] In the case that the work features match the work flow of the target work condition, count the work data as target work data matching the target work condition.

[0205] Optionally, the recognition unit 703 can be specifically used for:

[0206] comparing the job feature with the job flow of the first working stage of the target working condition, to determine whether the job feature matches the job flow of the first working stage of the target working condition;

[0207] when the job feature matches the job flow of the first working stage of the target working condition, comparing the job feature with the job flow of the second working stage of the target working condition, to determine whether the job feature matches the job flow of the second working stage of the target working condition;

[0208] repeating the above processing until it is determined whether the job feature matches the job flow of each working stage of the target working condition.

[0209] Optionally, the mechanical equipment is a hoisting equipment, and the job data includes one or more of hoisting weight, hoisting height, hoisting posture and hoisting time.

[0210] The job recognition device provided by the embodiment belongs to the same application concept as the job recognition method provided by the above-mentioned embodiments of the application, can execute the job recognition method provided by any of the above-mentioned embodiments of the application, and has the corresponding function modules and beneficial effects of executing the job recognition method. Technical details not described in detail in the embodiment can be referred to the specific processing content of the job recognition method provided by the above-mentioned embodiments of the application, which will not be described here.

[0211] Another embodiment of the application further provides a job recognition device, which is shown in Figure 8 The device includes:

[0212] a memory 200 and a processor 210;

[0213] The memory 200 is connected with the processor 210, and is configured to store a program.

[0214] The processor 210 is configured to realize the job recognition method disclosed in any of the above-mentioned embodiments by running the program stored in the memory 200.

[0215] Specifically, the job recognition device can further include a bus, a communication interface 220, an input device 230 and an output device 240.

[0216] The processor 210, the memory 200, the communication interface 220, the input device 230 and the output device 240 are connected with each other through the bus. Among them:

[0217] The bus can include a channel for transmitting information between various components of a computer system.

[0218] The processor 210 can be a general processor, such as a general central processing unit (CPU), a microprocessor, or the like, or can be an application-specific integrated circuit (ASIC), or one or more integrated circuits for controlling the execution of programs of the present application. It can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a ready-to-use programmable gate array (FPGA), or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component.

[0219] The processor 210 can include a main processor and can also include a baseband chip, a modem, and the like.

[0220] The memory 200 stores programs for implementing the technical solutions of the present application, and can also store operating systems and other key services. Specifically, the programs can include program codes, and the program codes include computer operation instructions. More specifically, the memory 200 can include a read-only memory (ROM), other types of static storage devices that can store static information and instructions, a random access memory (RAM), other types of dynamic storage devices that can store information and instructions, a disk memory, a flash, and the like.

[0221] The input device 230 can include a device that receives data and information input by a user, such as a keyboard, a mouse, a camera, a scanner, a light pen, a voice input device, a touch screen, a pedometer, or a gravity sensor, and the like.

[0222] The output device 240 can include a device that allows information to be output to a user, such as a display screen, a printer, a speaker, and the like.

[0223] The communication interface 220 can include a device using any transceiver to communicate with other devices or communication networks, such as an Ethernet, a radio access network (RAN), a wireless local area network (WLAN), and the like.

[0224] The processor 210 executes the programs stored in the memory 200 and calls other devices, which can be used to implement each step of any one of the job recognition methods provided by the above-mentioned embodiments of the present application.

[0225] Another embodiment of the present application also provides a crane, which comprises the work recognition device in the above-mentioned embodiments. In this embodiment, the crane refers to a multi-action hoisting machine that vertically lifts and horizontally carries heavy objects within a certain range. For example, a crown block, a crane, a flight crane, etc. The work recognition device in the crane can obtain work data of the crane; then extract work features in the work data, wherein the work features are determined according to actions performed in the work process of the crane; and finally, in the case that the work features match the work flow of a target working condition, the work data is counted as target work data matching the target working condition. The crane provided in this embodiment can identify a target working condition according to work data of the crane, so that work data of the crane related to the target working condition is effectively developed and utilized, and the data value of the work data of the crane is fully tapped.

[0226] In addition to the above method and device, the embodiments of the present application can also be a computer program product, which includes computer program instructions that, when executed by a processor, cause the processor to perform the steps in the work recognition method according to various embodiments of the present application described in the above “Exemplary Method” section of the present specification.

[0227] The computer program product can be written in any combination of one or more programming languages to perform the operations of the embodiments of the present application, including an object-oriented programming language, such as Java, C++, etc., and a conventional procedural programming language, such as “C” language or similar programming languages. The program code can be executed entirely on a user computing device, partially on a user device, as an independent software package, partially on a user computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0228] In addition, the embodiments of the present application can also be a storage medium having a computer program stored thereon, and the computer program is executed by a processor to perform the steps in the work recognition method according to various embodiments of the present application described in the above “Exemplary Method” section of the present specification. Specifically, the following steps can be implemented:

[0229] Step S201, obtaining work data of a mechanical device.

[0230] Step S202, extracting work features in the work data, wherein the work features are determined according to actions performed in the work process of the mechanical device.

[0231] Step S203, in the case that the work features match the work flow of a target working condition, counting the work data as target work data matching the target working condition.

[0232] For each method embodiment described above, for the sake of simplicity, the method embodiments are described as a series of acts. But those skilled in the art will appreciate that the method embodiments are not limited by the order of acts, as some steps could occur in other orders or concurrently with each other. Moreover, those skilled in the art will appreciate that described acts could be implemented other ways, such as at least partially in hardware, and that the disclosure is not limited to the described or illustrated order or grouping of acts.

[0233] It is noted that each of the above-described examples of the present disclosure is described in a progressive manner, and each example focuses on the differences from other examples. Therefore, the same or similar parts among the examples can be mutually referred to. For the device examples, since they are basically similar to the method examples, the description is relatively simple, and the relevant parts can be referred to the description of the method examples.

[0234] The steps in the method embodiments of the present disclosure can be adjusted in order, combined, and reduced according to actual needs. The technical features recorded in each embodiment can be replaced or combined.

[0235] The modules and sub-modules in the devices and terminals in the embodiments of the present disclosure can be combined, divided, and reduced according to actual needs.

[0236] In several embodiments of the present disclosure, it should be understood that the disclosed terminals, devices, and methods can be implemented in other ways. For example, the terminal embodiments described above are only schematic. For example, the division of modules or sub-modules is only a logical function division. In actual implementation, another division mode can be used, for example, a plurality of sub-modules or modules can be combined or integrated into another module, or some features can be omitted or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed each other can be indirect coupling or communication connection through some interfaces, devices or modules, which can be electrical, mechanical or other forms.

[0237] The modules or sub-modules described as separate components can or can not be physically separated, and the components of the modules or sub-modules can or can not be physical modules or sub-modules, that is, they can be located in one place or distributed on a plurality of network modules or sub-modules. According to actual needs, some or all of the modules or sub-modules can be selected to achieve the purpose of the embodiment.

[0238] In addition, each functional module or sub-module in each embodiment of the present application can be integrated in one processing module, or each module or sub-module can exist physically alone, or two or more modules or sub-modules can be integrated in one module. The integrated module or sub-module can be realized in the form of hardware or in the form of a software functional module or sub-module.

[0239] Those skilled in the art will further appreciate that the functions or steps of the examples described herein can be implemented using electronic hardware, computer software, or any combination of the two. To clearly illustrate this interchangeability of hardware and software, various examples have been described herein in terms of their functional generalities. Whether such functions are implemented as hardware or software depends on the particular application and design constraints imposed on the overall system. Skilled artisans can implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

[0240] The steps of a method or algorithm described in connection with the embodiments disclosed herein can be embodied directly in hardware, in a software executed by a processor, or in a combination of the two. A software unit can reside in random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM (EPROM), an electrically erasable programmable ROM (EEPROM), a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0241] Finally, it needs to be pointed out that, in this document, the relationship terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or sequence between the entities or operations. Moreover, the terms "include", "contain" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or device. Without more limitations, the element defined by the statement "including a" does not exclude the presence of another identical element in the process, method, article or device including the element.

[0242] The above description of disclosed embodiments enables one of ordinary skill in the art to make and use the application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein can be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A work recognition method characterized by comprising: The method comprises: acquiring work data of a mechanical device; wherein the mechanical device is a hoisting device; extracting work features from the work data, wherein the work data comprises one or more of hoisting weight, hoisting height, hoisting posture and hoisting time, and the work features are determined according to actions performed during work of the mechanical device; comparing the work features with a work flow of a first working stage of a target working condition to determine whether the work features match the work flow of the first working stage of the target working condition; when the work features match the work flow of the first working stage of the target working condition, comparing the work features with a work flow of a second working stage of the target working condition to determine whether the work features match the work flow of the second working stage of the target working condition; repeating the above processes until it is determined whether the work features match the work flows of all working stages of the target working condition; when the work features match the work flows of all working stages of the target working condition, determining whether the work features match a work flow of the target working condition according to an order of each target data segment in the work data and an order of each working stage of the target working condition; each target data segment is a work data segment that matches each working stage of the target working condition; when the work features match the work flow of the target working condition, counting the work data as target work data that matches the target working condition.

2. The method of claim 1, wherein, After the work data is counted as the target work data that matches the target working condition, the method further comprises: collecting multiple sets of target work data that match the target working condition; analyzing the multiple sets of target work data to generate an optimization result of work parameters of the target working condition.

3. The method of claim 1, wherein, The work data comprises work location information, and after the work data is counted as the target work data that matches the target working condition, the method further comprises: counting work location information of the multiple sets of target work data that match the target working condition; generating work region distribution data corresponding to the target working condition according to the counted work location information.

4. The method of claim 1, wherein, The work data comprises work location information, and after the work data is counted as the target work data that matches the target working condition, the method further comprises: dividing the work data into at least one working condition data block according to work location information of the work data, wherein each working condition data block comprises work data of the mechanical device at one work site; The method further comprises: extracting work features of each working condition data block.

5. The method of claim 1, wherein, Before the work data is counted as the target work data that matches the target working condition, the method further comprises: acquiring historical work data of the mechanical device performing the target working condition; generating historical work features of the target working condition according to the historical work data; determining a work flow of the target working condition according to an arrangement order of the historical work features; wherein the work flow of the target working condition comprises work flows of each working stage of the target working condition.

6. A work recognition device characterized by comprising: The method comprises: A data acquisition unit is configured to acquire operation data of a mechanical device, wherein the mechanical device is a hoisting device. A feature extraction unit is configured to extract an operation feature from the operation data, wherein the operation data comprises one or more of a hoisted load, a hoisting height, a hoisting posture, and a hoisting time, and the operation feature is determined according to an action performed in a working process of the mechanical device. An identification unit is configured to compare the operation feature with an operation procedure of a first working stage of a target working condition, to determine whether the operation feature matches the operation procedure of the first working stage of the target working condition; when the operation feature matches the operation procedure of the first working stage of the target working condition, the identification unit compares the operation feature with an operation procedure of a second working stage of the target working condition, to determine whether the operation feature matches the operation procedure of the second working stage of the target working condition; the above process is repeatedly performed until it is determined whether the operation feature matches the operation procedures of all working stages of the target working condition; when the operation feature matches the operation procedures of all working stages of the target working condition, the identification unit determines whether the operation feature matches an operation procedure of the target working condition according to an order of each target data segment in the operation data and an order of each working stage of the target working condition, wherein each target data segment is a data segment that matches each working stage of the target working condition; when the operation feature matches the operation procedure of the target working condition, the operation data is counted as target operation data that matches the target working condition.

7. A work recognition apparatus characterized by comprising: Comprise: A processor, and a memory connected to the processor; The memory is configured to store a computer program; The processor is configured to call and execute the computer program in the memory to execute the operation identification method in any one of claims 1-5.

8. A crane, characterized in that Comprise: The operation identification device in claim 7.

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