Abnormality detection method and device for target device

Abstract

The present invention discloses a method and device for detecting abnormality of a target device, the method comprising: collecting component information of a target component on a target device through a target sensor, wherein the target sensor comprises an angle recognition sensor and / or a fracture recognition sensor; determining the component state of the target component according to the component information, and determining the device state information of the target device according to the component state of the target component; determining the device abnormality information in the device state information, and determining the abnormality detection result of the target device according to the device abnormality information. It can be seen that the implementation of the present invention can determine the device state information and then determine the abnormality detection result of the target device by determining the state of the target component on the target device, can specifically determine the component information and the abnormality information of the target device, can accurately detect the abnormality of the target device, and is conducive to improving the safety and reliability of the operation of the target device.

Description

Technical Field

[0001] The present invention relates to the field of intelligent detection technology, and in particular to a method and device for detecting abnormalities of a target device. Background Art

[0002] With the continuous development of science and technology, the number of equipment such as wind turbines has increased significantly in recent years, and more and more equipment has been put into practical use. Such equipment needs to operate continuously for a long time, and with the expansion of the scale of equipment use and the increase in operating time, abnormal detection and fault diagnosis of equipment has become a problem of great concern in the industry.

[0003] At present, most of the abnormality detection methods for such equipment are to have inspectors conduct regular inspections of the equipment, but the inspection time interval is long, and all rely on manual marking and manual identification by inspectors, which requires a lot of manpower and time costs, resulting in errors or mistakes in the abnormality detection of the equipment, and even causing safety hazards in the operation of the equipment. It can be seen that it is particularly important to provide a new abnormality detection method to improve the efficiency and accuracy of abnormality detection of equipment and thus improve the safety of equipment operation. Summary of the invention

[0004] The present invention provides a method and device for detecting anomalies of a target device, which can accurately detect the abnormal conditions of the target device and help improve the safety and reliability of the operation of the target device.

[0005] In order to solve the above technical problems, the first aspect of the present invention discloses a method for detecting anomalies of a target device, wherein the method is applied to an anomaly detection system, wherein the anomaly detection system includes a target sensor and a data processor, wherein the data processor includes a data collector, and the method includes:

[0006] Collecting component information of a target component on the target device by means of the target sensor, wherein the target sensor comprises an angle recognition sensor and / or a fracture recognition sensor;

[0007] Determining, by the data processor, the component status of the target component according to the component information and a predetermined status analysis model, and determining the device status information of the target device according to the component status of the target component;

[0008] Device abnormality information is determined from the device status information, and an abnormality detection result of the target device is generated according to the device abnormality information.

[0009] A second aspect of the present invention discloses a device for detecting anomalies of a target device, the device comprising:

[0010] A collection module, used for collecting component information of a target component on the target device through a target sensor, wherein the target sensor includes an angle recognition sensor and / or a fracture recognition sensor;

[0011] A determination module, configured to determine a component state of the target component according to the component information, and determine device state information of the target device according to the component state of the target component;

[0012] The generating module is used to determine the device abnormality information in the device status information, and generate the abnormality detection result of the target device according to the device abnormality information.

[0013] As an optional implementation, in the second aspect of the present invention, the determination module is further used to determine component abnormality information of the target device according to the abnormality detection result, wherein the component abnormality information includes one or more of component abnormality quantity information and component abnormality degree information;

[0014] The device also includes:

[0015] An acquisition module, used to acquire original component information of the target device;

[0016] A comparison module, used to perform a comparison operation on the original component information and the component abnormality information to obtain an information comparison result;

[0017] A judgment module, used to judge whether the target device meets the preset device operation conditions based on the information comparison result;

[0018] The determination module is further configured to determine, when the determination module determines that the target device does not meet the preset device operating condition, a cause of abnormal detection corresponding to the information comparison result according to the information comparison result and the preset device operating condition;

[0019] An execution module, configured to execute an exception handling operation on the target device based on the exception detection cause;

[0020] The specific manner in which the judgment module judges whether the target device meets the preset device operating conditions based on the information comparison result includes:

[0021] Based on the information comparison result, determine the component abnormality ratio of the target device, and judge whether the component abnormality ratio is greater than or equal to a preset abnormality ratio threshold;

[0022] When it is determined that the component abnormality ratio is greater than or equal to the preset abnormality ratio threshold, it is determined that the target device meets the preset device operating conditions; when it is determined that the component abnormality ratio is less than the preset abnormality ratio threshold, it is determined that the target device does not meet the preset device operating conditions.

[0023] As an optional implementation, in the second aspect of the present invention, when the target sensor includes the angle recognition sensor, the specific manner in which the acquisition module acquires component information of the target component on the target device through the target sensor includes:

[0024] Acquiring component angle parameters of the target component by means of the angle recognition sensor, wherein the component angle parameters include current angle parameters of the target component and / or angle difference parameters between the current angle parameters of the target component and a preset reference angle parameter;

[0025] Performing an angle calibration operation on the component angle parameter to obtain an angle calibration parameter, and determining component information of the target component on the target device based on the angle calibration parameter;

[0026] Furthermore, when the target sensor includes the fracture identification sensor, the specific manner in which the acquisition module acquires component information of the target component on the target device through the target sensor includes:

[0027] Collecting component position parameters of the target component by means of the fracture identification sensor, wherein the component position parameters include current position parameters of the target component and / or displacement difference parameters between the current position parameters of the target component and preset reference position parameters;

[0028] A displacement check operation is performed on the component position parameters to obtain displacement check parameters, and component information of the target component on the target device is determined based on the displacement check parameters.

[0029] As an optional implementation, in the second aspect of the present invention, the specific manner in which the determination module determines the component status of the target component according to the component information, and determines the device status information of the target device according to the component status of the target component includes:

[0030] Determining a loose parameter of the target component according to the component information, determining a parameter difference relationship between the loose parameter of the target component and a preset target parameter, and determining a component state of the target component based on the parameter difference relationship;

[0031] Determining, according to the component state of the target component, operation impact information of the component state of the target component on the target device, wherein the operation impact information includes state impact information of the target component on the target device;

[0032] An information fitting operation is performed on the operation impact information and the component status of the target component to obtain an information fitting result, and the device status information of the target device is determined based on the information fitting result; wherein the information fitting result is at least used to represent the current operation impact information of the component status of the target component on the target device.

[0033] As an optional implementation, in the second aspect of the present invention, the specific manner in which the generating module generates the abnormality detection result of the target device according to the device abnormality information includes:

[0034] Determining the abnormality degree of the fan of the target device according to the device abnormality information, wherein the abnormality degree of the fan at least includes abnormality degree information of the target component included in the target device;

[0035] Determining a degree difference relationship between the abnormality degree of the fan and a preset target abnormality degree, wherein the degree difference relationship at least includes a degree difference value between the abnormality degree of the fan and the target abnormality degree;

[0036] Determining whether the degree difference relationship satisfies a preset degree difference condition, obtaining a degree determination result, and generating an abnormality detection result of the target device according to the degree determination result;

[0037] The specific manner in which the generating module generates the abnormality detection result of the target device according to the degree judgment result includes:

[0038] When the degree judgment result is used to indicate that the degree difference relationship satisfies the preset degree difference condition, generating an abnormality detection result of the target device according to the degree judgment result, wherein the abnormality detection result is used to indicate that the target device is in a normal operating state;

[0039] When the degree judgment result is used to indicate that the degree difference relationship does not satisfy the preset degree difference condition, the component maintenance parameters of the target device are predicted based on the degree difference relationship, and the abnormality detection result of the target device is generated based on the component maintenance parameters and the degree difference relationship, wherein the abnormality detection result is used to indicate that the target device is in an abnormal operating state.

[0040] As an optional implementation, in the second aspect of the present invention, the acquisition module performs an angle verification operation on the component angle parameter to obtain the angle verification parameter, and determines the component information of the target component on the target device based on the angle verification parameter. The specific manner includes:

[0041] Based on the component angle parameter, an angle rotation signal of the target component is determined, and based on the angle rotation signal and a preset reference angle signal, a verification operation is performed on the angle rotation signal of the target component to obtain an angle difference value between the angle rotation signal of the target component and the reference angle signal, and an angle verification parameter is determined based on the angle difference value, and an angle loosening parameter of the target component is determined according to the angle verification parameter, and a preload force parameter of the target component is determined according to the angle loosening parameter, a component attribute parameter of the target component and a predetermined target calculation formula, and component information of the target component is determined based on the preload force parameter of the target component, wherein the component attribute parameter includes a material elastic modulus parameter of the target component, a radial equivalent cross-sectional area parameter of the target component, a clamping length parameter of the target component, and a pitch parameter of the target component, and the angle loosening parameter includes a loosening change amount of the target component, an angular displacement change amount of the target component, and an angular change amount of the target component;

[0042] And, the acquisition module performs a displacement verification operation on the component position parameter to obtain a displacement verification parameter, and determines the component information of the target component on the target device based on the displacement verification parameter in a specific manner including:

[0043] Determine the current position signal of the target component based on the component position parameter, and perform a displacement verification operation on the current position signal of the target component based on the current position signal and a preset reference distance signal to obtain a displacement verification parameter, and determine component information of the target component on the target device based on the displacement verification parameter, wherein the displacement verification parameter includes a displacement distance parameter between the current position signal and the preset reference distance signal;

[0044] And, the predetermined target calculation formula includes:

[0045] F = E × S × △ L / L;

[0046] △L=△T×а;

[0047] △T=P / 360°;

[0048] Among them, F is the preload force of the target component, E is the material elastic modulus of the target component, S is the radial equivalent cross-sectional area of ​​the target component, △L is the looseness change of the target component, L is the clamping length of the target component, P is the pitch of the target component, а is the angular change of the target component, and △T is the angular displacement change of the target component.

[0049] As an optional implementation, in the second aspect of the present invention, the specific manner in which the execution module performs the exception handling operation on the target device based on the exception detection cause includes:

[0050] Based on the abnormality detection cause and the abnormality information of the component of the target device, generating an abnormality prediction trend of the target device, wherein the abnormality prediction trend includes one or more of the predicted abnormal time, predicted abnormal duration, and predicted abnormal component of the target device;

[0051] Obtaining the operation requirement information of the target equipment in a preset future time period, and determining the maintenance requirement information of the target equipment based on the abnormal prediction trend and the operation requirement information, wherein the maintenance requirement information includes one or more of maintenance time requirement, maintenance method requirement, and maintenance time requirement;

[0052] Based on the maintenance requirement information, maintenance parameters matching the maintenance requirement information are determined from a predetermined processing parameter library, and target processing parameters are generated based on all the maintenance parameters, and an exception processing operation is performed on the target device based on the target processing parameters.

[0053] As an optional implementation, in the second aspect of the present invention, the data processor further includes an abnormality detection platform; wherein the specific manner in which the determination module determines the component status of the target component according to the component information through the data processor, and determines the device status information of the target device according to the component status of the target component includes:

[0054] The data collector determines the component status of the target component based on the component information, in combination with a predetermined status analysis model and the abnormality detection platform, and determines the device status information of the target device based on the component status of the target component.

[0055] The third aspect of the present invention discloses another device for detecting abnormalities of a target device, the device comprising:

[0056] A memory storing executable program code;

[0057] a processor coupled to the memory;

[0058] The processor calls the executable program code stored in the memory to execute the method for detecting anomalies of a target device disclosed in the first aspect of the present invention.

[0059] A fourth aspect of the present invention discloses a computer storage medium, wherein the computer storage medium stores computer instructions, and when the computer instructions are called, they are used to execute the method for detecting anomalies in a target device disclosed in the first aspect of the present invention.

[0060] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0061] In an embodiment of the present invention, component information of a target component on a target device is collected through a target sensor, wherein the target sensor includes an angle recognition sensor and / or a fracture recognition sensor; the component state of the target component is determined according to the component information, and the device state information of the target device is determined according to the component state of the target component; device abnormality information is determined in the device state information, and the abnormality detection result of the target device is determined according to the device abnormality information. It can be seen that the implementation of the present invention can determine the device state information and then determine the abnormality detection result of the target device by determining the state of the target component on the target device, can specifically determine the component information and the abnormality information of the target device, can accurately detect the abnormality of the target device, and is conducive to improving the safety and reliability of the operation of the target device. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0063] Figure 1 It is a flow chart of a method for detecting anomalies of a target device disclosed in an embodiment of the present invention;

[0064] Figure 2 It is a flowchart of another method for detecting anomalies of a target device disclosed in an embodiment of the present invention;

[0065] Figure 3 It is a structural schematic diagram of a device for detecting abnormalities of a target device disclosed in an embodiment of the present invention;

[0066] Figure 4 It is a structural schematic diagram of another device for detecting abnormalities of a target device disclosed in an embodiment of the present invention;

[0067] Figure 5It is a structural schematic diagram of another device for detecting anomalies of a target device disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0068] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0069] The terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish different objects rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, device, product or end including a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units inherent to these processes, methods, products or ends.

[0070] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0071] The present invention discloses a method and device for detecting abnormality of a target device, which can determine the state of a target component on the target device to determine the device state information and then determine the abnormality detection result of the target device, can specifically determine the component information and the abnormal information of the target device, can accurately detect the abnormal situation of the target device, and is conducive to improving the safety and reliability of the operation of the target device. The following are detailed descriptions.

[0072] Embodiment 1

[0073] See also Figure 1 , Figure 1 : is a flow chart of a method for detecting abnormalities of a target device disclosed in an embodiment of the present invention. Figure 1The method for detecting anomalies in a target device described above can be applied to an anomaly detection system for a target device, wherein the anomaly detection system includes a target sensor and a data processor, wherein the data processor includes a data collector. Furthermore, the method can also be applied to the target device itself, wherein the anomaly detection device applied to the target device can be integrated in a cloud server or a local server, and the target device can be one or more of a wind turbine and a large machine, which is not limited in the embodiments of the present invention. Figure 1 As shown, the method for detecting anomalies of a target device may include the following operations:

[0074] 101. Collect component information of a target component on a target device through a target sensor.

[0075] In the embodiment of the present invention, the target sensor includes an angle recognition sensor and / or a fracture recognition sensor.

[0076] In the embodiment of the present invention, optionally, the number of target sensors may be one or more, which is not specifically limited in the embodiment of the present invention; further optionally, one target sensor may correspond to one target component, or one target sensor may correspond to multiple target components, so as to collect component information of multiple target components through one target sensor, which is not specifically limited in the embodiment of the present invention.

[0077] In the embodiment of the present invention, optionally, the number of the target components may be one or more, which is not specifically limited in the embodiment of the present invention. Further optionally, the target component may include a bolt.

[0078] In the embodiment of the present invention, optionally, the component information of the target component includes one or more of installation position information, installation angle information, and installation method information of the target component.

[0079] In the embodiment of the present invention, the angle recognition sensor can be used to collect the angle rotation information of the target component, and the fracture recognition sensor can be used to collect the component fracture information of the target component. The angle rotation information includes the rotation angle information between the current angle of the target component and the preset reference angle.

[0080] 102. Determine, by a data processor, a component state of a target component based on the component information and a predetermined state analysis model, and determine device state information of a target device based on the component state of the target component.

[0081] In the embodiment of the present invention, optionally, the component state of the target component may include one of a normal operation state, a component loosening warning state, a component loosening alarm state, a component fracture warning state, and a component fracture alarm state. The target component may include a bolt.

[0082] In the embodiment of the present invention, optionally, the number of the target components can be one or more, which is not specifically limited in the embodiment of the present invention. Further optionally, each target component has a component state corresponding thereto.

[0083] In the embodiment of the present invention, further optionally, when there are multiple target components, the device status information of the target device is determined jointly according to the component status of all the target components.

[0084] In the embodiment of the present invention, optionally, the device status information of the target device includes operation status information of the target device.

[0085] 103. Determine device abnormality information in the device status information, and generate an abnormality detection result of the target device based on the device abnormality information.

[0086] In the embodiment of the present invention, the device abnormality information includes one or more of device abnormality data information, device abnormality duration information, device abnormality frequency information, and device abnormality number information of the target device.

[0087] In the embodiment of the present invention, the abnormality detection result of the target device optionally includes one or more of abnormality type information and abnormality degree information of the target device. Further, the abnormality type information of the target device includes one or more of temperature abnormality information, vibration abnormality information, and electrical abnormality information; the abnormality degree information of the target device includes target device performance abnormality degree information.

[0088] It can be seen that implementation Figure 1The described method for detecting abnormalities in a target device can collect component information of a target component on a target device through a target sensor, and determine the component status of the target component through a data processor according to the component information, determine the device status information of the target device according to the component status of the target component and further determine the device abnormality information, and determine the abnormality detection result according to the device abnormality information. The target sensor can collect information of the target component and determine the status of the target component, and can specifically collect component information of each target component and determine the component status, which is beneficial to improving the accuracy and reliability of determining the component status of each target component, as well as the intelligence and efficiency of determining the component status of each target component, and can determine the device status information of the target device according to the component status of the target component, which is beneficial to improving the accuracy and intelligence of determining the device status information, thereby facilitating the determination of device abnormality information and abnormality detection results based on the device status information, and can timely discover abnormal problems existing in the target device by monitoring the status of the target component and performing abnormality detection, thereby facilitating the generation of the accuracy and reliability of the abnormality detection results of the target device, thereby achieving accurate detection of abnormal conditions of the target device, and facilitating the improvement of the reliability and safety of the operation of the target device.

[0089] Embodiment 2

[0090] See also Figure 2 , Figure 2 is a flow chart of another method for detecting abnormalities of a target device disclosed in an embodiment of the present invention. Figure 2 The described method for detecting abnormalities in a target device can be applied to an abnormality detection system for a target device, wherein the abnormality detection system includes a target sensor and a data processor, wherein the data processor includes a data collector. Furthermore, the method can also be applied to the target device itself, wherein the abnormality detection system for the target device can be integrated in a cloud server or a local server, and the target device can be one or more of a wind turbine and a large machine, which is not limited in the embodiments of the present invention. Figure 2 As shown, the method for detecting anomalies of a target device may include the following operations:

[0091] 201. Collect component information of a target component on a target device through a target sensor.

[0092] 202. Determine the component state of the target component by a data processor according to the component information and a predetermined state analysis model, and determine the device state information of the target device according to the component state of the target component.

[0093] 203. Determine device abnormality information in the device status information, and determine an abnormality detection result of the target device based on the device abnormality information.

[0094] In the embodiment of the present invention, for the detailed description of steps 201 to 203, please refer to the other descriptions of steps 101 to 103 in the first embodiment, and the embodiment of the present invention will not be repeated.

[0095] 204. Determine component abnormality information of the target device according to the abnormality detection result.

[0096] In the embodiment of the present invention, the component abnormality information includes one or more of component abnormality quantity information and component abnormality degree information.

[0097] In the embodiment of the present invention, optionally, the component abnormality quantity information includes the quantity of target components in abnormal state included in the target device; the component abnormality degree information includes the abnormality degree of each target component in abnormal state included in the target device.

[0098] In the embodiment of the present invention, optionally, determining the component abnormality information of the target device according to the abnormality detection result may include:

[0099] The abnormality detection result is input into a predetermined abnormality information analysis model to obtain an analysis model output result, and the component abnormality information of the target device is determined according to the analysis model output result.

[0100] 205. Obtain original component information of the target device, perform a comparison operation on the original component information and the component abnormality information, and obtain an information comparison result.

[0101] In the embodiment of the present invention, optionally, the original component information of the target device includes one or more of initial component installation position information, initial component installation angle information, and initial component installation mode information of each target component included in the target device.

[0102] In the embodiment of the present invention, optionally, the information comparison result includes one or more of angle difference information and position difference information between the original component information and the component abnormality information.

[0103] 206. Based on the information comparison result, determine whether the target device meets the preset device operating conditions.

[0104] In the embodiment of the present invention, judging whether the target device meets the preset device operating conditions based on the information comparison result includes:

[0105] Based on the information comparison result, determine the abnormal proportion of components of the target device, and judge whether the abnormal proportion of components is greater than or equal to a preset abnormal proportion threshold;

[0106] When it is determined that the component abnormality ratio is greater than or equal to the preset abnormality ratio threshold, it is determined that the target device meets the preset device operating conditions; when it is determined that the component abnormality ratio is less than the preset abnormality ratio threshold, it is determined that the target device does not meet the preset device operating conditions.

[0107] In the embodiment of the present invention, optionally, the component abnormality ratio information of the target device includes the ratio between the target components in the abnormal state and the target components in the normal state in the target device.

[0108] In the embodiment of the present invention, optionally, for example, the preset abnormal proportion threshold may be 15% or 10%, which is not specifically limited in the embodiment of the present invention.

[0109] 207. When it is determined that the target device does not meet the preset device operating conditions, determine the abnormality detection cause corresponding to the information comparison result according to the information comparison result and the preset device operating conditions, and perform an abnormality handling operation on the target device based on the abnormality detection cause.

[0110] In the embodiment of the present invention, further optionally, the above method may also include:

[0111] When it is determined that the target device meets the preset device operating conditions, the device operating trend of the target device in the preset future time period is generated according to the abnormality detection result of the target device and the preset device operating conditions, and according to the device operating trend, it is determined whether the target device has a target abnormal moment in the preset future time period, wherein the target abnormal moment includes the moment corresponding to the target device not meeting the preset device operating conditions;

[0112] When it is determined that the target device has a target abnormal moment within a preset future time period, the abnormality detection cause is determined according to the target abnormal moment and the information comparison result, and an abnormality handling operation is performed on the target device at the target abnormal moment based on the abnormality detection cause;

[0113] When it is determined that the target device does not have a target abnormal moment within a preset future time period, this process can be terminated.

[0114] It can be seen that implementation Figure 2The described method for detecting abnormalities in a target device can determine the abnormal component information of the target device based on the abnormal detection results, obtain the original component information of the target device and perform a comparison operation to obtain the information comparison results to further determine whether the target device meets the preset device operating conditions. If not, the corresponding abnormal detection cause is determined based on the information comparison results and the device operating conditions, and then the abnormal handling operation is performed. It can timely detect and diagnose abnormal problems of the target device, reduce the risk of damage to the target device, and thus help improve the reliability and safety of the target device. It can also timely discover abnormal problems of the target device and perform predictive maintenance on the target device, avoid failure of the target device or danger during use due to unexpected failures, and further improve the efficiency and performance of the target device by analyzing abnormal data and identifying potential improvement points of the target device based on the information comparison results, thereby improving the utilization rate of the target device through automated intelligent abnormality detection, thereby achieving accurate detection of abnormal conditions of the target device, and helping to improve the reliability and safety of the target device operation.

[0115] In an optional embodiment, when the target sensor includes an angle recognition sensor, collecting component information of a target component on a target device through the target sensor includes:

[0116] Acquiring component angle parameters of the target component by an angle recognition sensor, wherein the component angle parameters include current angle parameters of the target component and / or angle difference parameters between the current angle parameters of the target component and a preset reference angle parameter;

[0117] Performing an angle calibration operation on the component angle parameter to obtain the angle calibration parameter, and determining component information of the target component on the target device based on the angle calibration parameter;

[0118] And, when the target sensor includes a fracture recognition sensor, collecting component information of the target component on the target device through the target sensor includes:

[0119] Collecting component position parameters of the target component by means of a fracture identification sensor, wherein the component position parameters include current position parameters of the target component and / or displacement difference parameters between the current position parameters of the target component and preset reference position parameters;

[0120] A displacement check operation is performed on the component position parameters to obtain displacement check parameters, and component information of a target component on a target device is determined based on the displacement check parameters.

[0121] In this optional embodiment, optionally, the current angle parameter of the target component may include the current installation angle of the target component; the angle difference parameter between the current angle parameter of the target component and the preset reference angle parameter includes the angle difference between the current angle of the target component and the reference angle.

[0122] In this optional embodiment, optionally, the angle verification parameters include rotation angle parameters of the target component; further, the above-mentioned determination of component information of the target component on the target device based on the angle verification parameters may include: determining the loosening angle of the target component on the target device based on the angle verification parameters, and determining the component information according to the loosening angle of the target component; wherein the component information includes component looseness degree information.

[0123] In this optional embodiment, optionally, the current position parameter of the target component may include the current installation position of the target component; the displacement difference parameter between the current position parameter of the target component and the preset reference position parameter includes the distance value between the current position of the target component and the reference position.

[0124] In this optional embodiment, optionally, for example, when the displacement check parameter is used to represent a sudden displacement change of a target component on a target device within a preset time period, determining the component information of the target component may include information on a break of the target component.

[0125] It can be seen that the implementation of this optional embodiment can collect the component angle information of the target component through the angle recognition sensor and perform an angle verification operation to obtain angle verification parameters, and determine the component information of the target component on the target device based on the angle verification parameters, or collect the component position parameters of the target component through the fracture recognition sensor and perform a displacement verification operation to obtain displacement verification parameters, and determine the component information of the target component on the target device based on the displacement verification parameters. The component angle parameters or component position parameters corresponding to the target component can be collected respectively by two sensors, which is conducive to improving the accuracy and reliability of obtaining the angle verification parameters and the displacement verification parameters, thereby facilitating improving the accuracy and reliability of the angle verification parameters and the displacement verification parameters based on the angle verification parameters. The parameter and displacement calibration parameters determine the accuracy and reliability of the component information of the target component, and the component information collected by the angle recognition sensor and the fracture recognition sensor can provide a more comprehensive understanding of the state of the target component, including its position, angle and other parameters. Through calibration operations and comparative analysis, the collected information can be ensured to be accurate and reliable, thereby providing more reliable data support for the state monitoring and anomaly detection of the target equipment, helping to improve the stability and performance of the system, which can be beneficial to improving the accuracy and reliability of the anomaly detection results generated for the target equipment, thereby achieving accurate detection of abnormal conditions of the target equipment, and is beneficial to improving the reliability and safety of the target equipment operation.

[0126] In another optional embodiment, determining the component state of the target component according to the component information, and determining the device state information of the target device according to the component state of the target component includes:

[0127] Determine the looseness parameter of the target component according to the component information, determine the parameter difference relationship between the looseness parameter of the target component and the preset target parameter, and determine the component state of the target component based on the parameter difference relationship;

[0128] Determining, according to the component state of the target component, operation impact information of the component state of the target component on the target device, wherein the operation impact information includes state impact information of the target component on the target device;

[0129] An information fitting operation is performed on the operation impact information and the component state of the target component to obtain an information fitting result, and the device state information of the target device is determined based on the information fitting result; wherein the information fitting result is at least used to represent the current operation impact information of the component state of the target component on the target device.

[0130] In this optional embodiment, optionally, the looseness parameter of the target component includes a degree of looseness of the target component.

[0131] In this optional embodiment, optionally, the parameter difference relationship between the loose parameter of the target component and the preset target parameter includes a loose degree difference relationship between the loose degree of the target component and the loose degree corresponding to the preset target parameter.

[0132] In this optional embodiment, optionally, the above-mentioned determination of the component state of the target component based on the parameter difference relationship may include: determining the looseness difference degree of the target component based on the parameter difference relationship, determining the looseness degree range corresponding to the looseness difference degree of the target component based on the looseness difference degree of the target component, and determining the component state of the target component according to the looseness degree range. For example, when the looseness difference degree is used to indicate that the target component is slightly loose, it is determined that the component state of the target component includes a looseness warning state; when the looseness difference degree is used to indicate that the target component is moderately loose, it is determined that the component state of the target component includes a looseness alarm state.

[0133] In this optional embodiment, optionally, determining the information on the impact of the component state of the target component on the operation of the target device according to the component state of the target component may include:

[0134] Determining, according to the component state of the target component, an influence factor of the component state of the target component on the target device, wherein the influence factor includes an internal influence factor and / or an external influence factor;

[0135] Based on the influence factor of the component state of the target component on the target device, the operation influence information of the component state of the target component on the target device is generated.

[0136] In this optional embodiment, optionally, performing the information fitting operation on the operation impact information and the component state of the target component to obtain the information fitting result, and determining the device state information of the target device based on the information fitting result may include:

[0137] Performing an information fitting operation on the operation influencing information and the component state of the target component to generate an influence association relationship between the operation influencing information and the component state of the target component, and generating an information fitting result according to the influence association relationship; wherein the influence association relationship between the operation influencing information and the component state of the target component includes a mutual influence relationship between the operation influencing information and the component state of the target component;

[0138] A state keyword is extracted from the information fitting result, and an operation impact state of the target device is determined according to the state keyword, and device state information of the target device is determined according to the operation impact state of the target device.

[0139] In this optional embodiment, the current operation impact information may include the current operation internal impact information and / or the current operation external impact information. For example, the current operation internal impact information may include one or more of internal vibration information, internal noise information, etc.; the current operation external impact information may include one or more of wind impact information, wind direction impact information, and impact impact information.

[0140] It can be seen that the implementation of this optional embodiment can determine the loosening parameters of the target component according to the component information and determine the parameter difference relationship between the loosening parameters and the target parameters to determine the component state of the target component, and determine the operation impact information according to the component state of the target component, perform an information fitting operation based on the operation impact information and the component state of the target component to obtain an information fitting result, and determine the device state information of the target device according to the information fitting result, and can monitor and diagnose the loosening parameters of the target component in real time, so as to timely discover potential problems and take corresponding measures to ensure the safe and reliable operation of the target device, and can determine the parameter difference between the loosening parameters of the target component and the preset target parameters. The abnormal relationship and the impact information of component status on the operation of the target equipment can realize predictive maintenance of the equipment. Furthermore, through information fitting operations, the operation impact information and component status can be fitted to obtain more accurate equipment status information, which is conducive to optimizing the performance of the equipment, improving its efficiency and stability, and through timely monitoring and diagnosis, as well as predictive maintenance measures, it can reduce equipment wear and damage, extend its service life, and reduce replacement and repair costs, which can help improve the accuracy and reliability of generating abnormal detection results for the target equipment, thereby realizing accurate detection of abnormal conditions of the target equipment, and is conducive to improving the reliability and safety of the target equipment operation.

[0141] In yet another optional embodiment, generating an abnormality detection result of a target device according to the device abnormality information includes:

[0142] Determine the abnormality degree of the fan of the target device according to the device abnormality information, wherein the abnormality degree of the fan at least includes abnormality degree information of the target component included in the target device;

[0143] Determine a degree difference relationship between the abnormality degree of the fan and a preset target abnormality degree, wherein the degree difference relationship includes at least a degree difference value between the abnormality degree of the fan and the target abnormality degree;

[0144] Determine whether the degree difference relationship satisfies a preset degree difference condition, obtain a degree determination result, and generate an abnormality detection result of the target device according to the degree determination result;

[0145] Among them, the abnormal detection result of the target device is generated according to the degree judgment result, including:

[0146] When the degree judgment result is used to indicate that the degree difference relationship satisfies a preset degree difference condition, an abnormality detection result of the target device is generated according to the degree judgment result, wherein the abnormality detection result is used to indicate that the target device is in a normal operating state;

[0147] When the degree judgment result is used to indicate that the degree difference relationship does not satisfy the preset degree difference condition, the component maintenance parameters of the target device are predicted based on the degree difference relationship, and the abnormality detection result of the target device is generated based on the component maintenance parameters and the degree difference relationship, wherein the abnormality detection result is used to indicate that the target device is in an abnormal operating state.

[0148] In this optional embodiment, optionally, the abnormality degree information of the target component at least includes looseness degree information and / or fracture degree information of the target component.

[0149] In this optional embodiment, optionally, the abnormality degree of the fan of the target device includes abnormality degree information of all target components and current abnormality degree information of the target device; wherein, the abnormality degree information of the fan of the target device is determined based on the abnormality degree information of all target components.

[0150] In this optional embodiment, optionally, when the degree judgment result is used to indicate that the degree difference relationship satisfies a preset degree difference condition, the degree difference value corresponding to the degree difference relationship is less than the degree difference threshold corresponding to the preset degree difference condition; when the degree judgment result is used to indicate that the degree difference relationship does not satisfy the preset degree difference condition, the degree difference value corresponding to the degree difference relationship is greater than or equal to the degree difference threshold corresponding to the preset degree difference condition.

[0151] In this optional embodiment, optionally, predicting the component maintenance parameters of the target device according to the degree difference relationship may include:

[0152] The degree difference value is determined according to the degree difference relationship, and the abnormal cause of the target equipment is determined based on the degree difference value and the equipment abnormality information, and the component maintenance parameters matching the abnormal cause are determined in a predetermined maintenance parameter set according to the abnormal cause.

[0153] It can be seen that the implementation of this optional embodiment can determine the degree of abnormality of the fan of the target device according to the equipment abnormality information, and determine the degree difference relationship between the degree of abnormality of the fan and the target abnormality degree and judge whether the degree difference condition is met to obtain the degree judgment result and then generate the abnormality detection result of the target device, wherein, when the degree judgment result is used to indicate that the degree difference relationship satisfies the degree difference condition, the abnormality detection result of the target device is generated according to the degree judgment result, and when the degree judgment result is used to indicate that the degree difference relationship does not satisfy the degree difference condition, the component maintenance parameters of the target device are predicted, and the abnormality detection result of the target device is generated according to the component maintenance parameters and the degree difference relationship. By monitoring various parameters of the target device and comparing them with the preset target abnormality degree, real-time abnormality detection can be realized, and abnormal conditions that may exist in the target device can be discovered in time, so that corresponding measures can be taken. Measures are taken to ensure the safe operation of the equipment, and by analyzing the degree difference relationship between the degree of abnormality of the fan and the preset target degree of abnormality, the degree of abnormality of the target equipment can be accurately judged, which is conducive to determining the severity of the abnormal situation and providing guidance for subsequent maintenance and repair work. When the degree difference relationship does not meet the preset conditions, according to the predicted component maintenance parameters and degree difference relationship, possible failures can be predicted in advance, and maintenance plans can be formulated accordingly. Predictive maintenance helps to avoid sudden failures and reduce downtime, which is conducive to improving the availability and reliability of the target equipment. Being able to detect and repair problems in a timely manner can reduce the losses caused by failures and avoid production losses caused by downtime, thereby reducing the overall maintenance cost, which is conducive to improving the safety, reliability and efficiency of the target equipment, reducing maintenance costs, and also improving the life and utilization of equipment.

[0154] In yet another optional embodiment, performing an angle calibration operation on a component angle parameter to obtain an angle calibration parameter, and determining component information of a target component on a target device based on the angle calibration parameter includes:

[0155] Based on the component angle parameter, an angle rotation signal of the target component is determined, and based on the angle rotation signal and a preset reference angle signal, a verification operation is performed on the angle rotation signal of the target component to obtain an angle difference value between the angle rotation signal of the target component and the reference angle signal, and an angle verification parameter is determined based on the angle difference value, and an angle loosening parameter of the target component is determined according to the angle verification parameter, and a preload force parameter of the target component is determined according to the angle loosening parameter, a component attribute parameter of the target component and a predetermined target calculation formula, and component information of the target component is determined based on the preload force parameter of the target component, the component attribute parameter includes a material elastic modulus parameter of the target component, a radial equivalent cross-sectional area parameter of the target component, a clamping length parameter of the target component, and a pitch parameter of the target component, and the angle loosening parameter includes a loosening change amount of the target component, an angular displacement change amount of the target component, and an angular change amount of the target component;

[0156] And, performing a displacement check operation on the component position parameter to obtain the displacement check parameter, and determining component information of the target component on the target device based on the displacement check parameter, including:

[0157] Determine a current position signal of a target component based on the component position parameter, and perform a displacement verification operation on the current position signal of the target component based on the current position signal and a preset reference distance signal to obtain a displacement verification parameter, and determine component information of the target component on the target device based on the displacement verification parameter, wherein the displacement verification parameter includes a displacement distance parameter between the current position signal and the preset reference distance signal;

[0158] And, the predetermined target calculation formula includes:

[0159] F = E × S × △ L / L;

[0160] △L=△T×а;

[0161] △T=P / 360°;

[0162] Among them, F is the preload force of the target component, E is the material elastic modulus of the target component, S is the radial equivalent cross-sectional area of ​​the target component, △L is the looseness change of the target component, L is the clamping length of the target component, P is the pitch of the target component, а is the angular change of the target component, and △T is the angular displacement change of the target component.

[0163] In this optional embodiment, optionally, the target component can be a bolt; wherein F is the bolt preload, E is the elastic modulus of the bolt body material, S is the radial equivalent cross-sectional area of ​​the bolt body, △L is the bolt loosening change, L is the clamping length of the measured portion of the bolt body, P is the pitch, △T is the angular displacement change, and а is the angle change; further, E, S, L, P, and △T can all be predetermined fixed constants.

[0164] In this optional embodiment, the angle rotation signal of the target component may optionally include the rotation angle value of the target component. Further optionally, the angle difference value between the angle rotation signal of the target component and the reference angle signal includes the angle difference value between the rotation angle value corresponding to the angle rotation signal and the reference angle value corresponding to the reference angle signal.

[0165] In this optional embodiment, optionally, the above-mentioned determining the angle verification parameter based on the angle difference value, and determining the angle looseness parameter of the target component according to the angle verification parameter may include:

[0166] generating an angle calibration parameter based on the angle difference value, wherein the angle calibration parameter at least includes an angle difference value between the angle rotation signal of the target component and the reference angle signal, and the angle calibration parameter also includes an angle difference value between the angle rotation signal of the target component and the initial angle signal of the target component;

[0167] According to the angle verification parameters, the degree of angular looseness of the target component is determined, and according to the degree of angular looseness and the angle verification parameters, the angular looseness parameters of the target component are determined.

[0168] In this optional embodiment, optionally, the current position signal of the target component includes the current position of the target component in the target device.

[0169] In this optional embodiment, optionally, the component angle parameter can be composed of an angle displacement identification sensor and an angle compass and information is collected through the angle displacement identification sensor and the angle compass, wherein the functions of the two angle displacement identification sensors are respectively a bolt angle loosening warning and verification sensor and a bolt angle loosening counting sensor, wherein both sensors are provided with triggers and are fixed on the bolt; and the angle compass is fixed on the nut, when the bolt and the nut produce a relative angle displacement a, when the angle a value reaches a loosening warning level such as 2°, the trigger of the bolt angle loosening warning and verification sensor is triggered to produce a reverse jump , the data collector collects the digital coding signal specially numbered for the corresponding position. At this time, the system bolt status monitoring data platform will display the loosening warning status of the specific bolt of the specific fan. When the bolt continues to loosen a certain angle such as 1~2°, the trigger of the bolt angle loosening warning and verification sensor is triggered to produce a positive jump, and the trigger of the bolt angle loosening counting sensor is triggered to produce a reverse jump, and will be superimposed on the basis of the warning angle by 1°. Similarly, the trigger of the bolt angle loosening counting sensor is triggered to produce a positive jump and will be superimposed by 1°. The angle displacement a is counted continuously according to the specific changes. According to the change in the angle displacement, the bolt preload can be calculated through the preset target calculation formula.

[0170] In this optional embodiment, optionally, performing a displacement verification operation on the current position signal of the target component based on the current position signal and a preset reference distance signal to obtain a displacement verification parameter may include:

[0171] Based on the current position signal and a preset reference distance signal, the distance value between the current position signal of the target component and the reference position signal corresponding to the reference distance signal is determined, and a unique calibration parameter is generated according to the distance value between the current position signal of the target component and the reference position signal corresponding to the reference distance signal.

[0172] In this optional embodiment, optionally, determining the component information of the target component on the target device based on the displacement verification parameter may include:

[0173] Based on the displacement check parameter, a fracture detection parameter of the target component is determined, wherein when the displacement check parameter is used to indicate that the target component has a displacement jump within a preset time period, the fracture detection parameter of the target component is determined to include a parameter corresponding to a fracture state of the target component, and when the displacement check parameter is used to indicate that the target component has no displacement jump within the preset time period, the fracture detection parameter of the target component is determined to include a parameter corresponding to a normal state of the target component;

[0174] Component information of the target component on the target device is determined based on the fracture detection parameter of the target component.

[0175] It can be seen that the implementation of this optional embodiment can determine the angle rotation signal of the target component based on the component angle parameter and perform a calibration operation to obtain the angle difference value and then obtain the angle calibration parameter, determine the angle looseness parameter of the target component according to the angle calibration parameter and then determine the component information of the target component, and determine the current position signal of the target component based on the component position parameter and perform a displacement calibration operation to obtain the displacement calibration parameter and determine the component information of the target component on the target device based on the displacement calibration parameter. By performing a calibration operation on the angle parameter and position parameter of the component, the actual angle and position information of the component can be accurately obtained and compared with the preset reference signal, so as to obtain accurate angle difference value and displacement distance parameter. It is beneficial to avoid the accumulation of errors, improve the accuracy of the target equipment component information, and according to the angle verification parameters and displacement verification parameters, the angle looseness parameters and other relevant information of the target component can be further determined, and the potential failure or abnormality of the target equipment component can be discovered in time, so as to take corresponding maintenance measures, avoid the expansion of failures, and improve the operating stability and reliability of the target equipment. Based on accurate component information, the maintenance plan of the target equipment can be formulated more scientifically, the maintenance time and resources can be arranged reasonably, and unnecessary downtime and maintenance costs can be reduced. It can also help to improve its overall performance and life, thereby helping to improve the safety, reliability and efficiency of the target equipment, reduce maintenance costs, and also improve the life and utilization of the equipment.

[0176] In yet another optional embodiment, based on the abnormality detection reason, performing an abnormality handling operation on the target device includes:

[0177] Based on the abnormality detection cause and the abnormality information of the component of the target device, an abnormality prediction trend of the target device is generated, wherein the abnormality prediction trend includes one or more of the predicted abnormal time, predicted abnormal duration, and predicted abnormal component of the target device;

[0178] Obtaining the operation demand information of the target equipment in a preset future time period, and determining the maintenance demand information of the target equipment based on the abnormal prediction trend and the operation demand information, wherein the maintenance demand information includes one or more of the maintenance time requirement, maintenance method requirement, and maintenance time requirement;

[0179] Based on the maintenance requirement information, maintenance parameters matching the maintenance requirement information are determined from a predetermined processing parameter library, and target processing parameters are generated based on all maintenance parameters, and an abnormality processing operation is performed on the target device based on the target processing parameters.

[0180] In this optional embodiment, optionally, the generating of the abnormality prediction trend of the target device based on the abnormality detection cause and the abnormality information of the components of the target device may include:

[0181] A first keyword for extracting an abnormality detection cause and a second keyword for extracting component abnormality information of a target device are extracted, abnormality key information of the target device is generated based on the first keyword and the second keyword, and an abnormality prediction trend of the target device is generated based on the abnormality key information of the target device.

[0182] In this optional embodiment, optionally, the operation requirement information of the target device within a preset future time period may be obtained in real time or periodically according to a preset time period, which is not specifically limited in the embodiment of the present invention.

[0183] In this optional embodiment, optionally, the maintenance parameters that match the maintenance requirement information may include a maintenance operation corresponding to a maintenance operation performed on a target component on a target device; for example, the maintenance parameters may include one or more of maintenance parameters for tightening a bolt, maintenance parameters for replacing a bolt, and maintenance parameters for resetting a bolt.

[0184] It can be seen that the implementation of this optional embodiment can generate an abnormality prediction trend based on the abnormality detection cause and the abnormality information of the components of the target device, obtain the operation requirement information of the target device, and determine the maintenance requirement information of the target device based on the abnormality prediction trend and the operation requirement information, determine the maintenance parameters based on the maintenance requirement information and the processing parameter library to generate the target processing parameters and then perform the abnormal processing operation on the target device, and can generate the abnormality prediction trend by analyzing the abnormality detection cause and the abnormality information of the components of the target device, and can predict the potential abnormal time, abnormal duration and abnormal components that may be involved of the target device in advance, so as to ensure that the target device can be promptly and effectively processed before or when the abnormality occurs, and obtain the target device. The operation demand information of the equipment in the preset future time period, combined with the abnormal prediction trend, can determine the maintenance demand information that is more in line with the actual operation status, which can avoid unnecessary shutdown and maintenance, and ensure that the target equipment can be properly maintained while meeting the operation requirements. By screening out matching maintenance parameters from a predetermined processing parameter library based on the maintenance demand information, and generating target processing parameters, accurate abnormal handling of the target equipment can be achieved, which is beneficial to improving the efficiency and accuracy of abnormal handling. Therefore, through timely and effective abnormal handling and preventive maintenance, the service life of the target equipment can be extended, the frequency and severity of failures can be reduced, and the reliability and stability of the target equipment can be improved.

[0185] In yet another optional embodiment, the data processor further includes an anomaly detection platform; wherein determining the component status of the target component according to the component information by the data processor, and determining the device status information of the target device according to the component status of the target component, includes:

[0186] The data collector determines the component status of the target component based on the component information, combined with a predetermined status analysis model and an anomaly detection platform, and determines the device status information of the target device based on the component status of the target component.

[0187] In this optional embodiment, optionally, the predetermined state analysis model may be a state analysis model that is pre-trained to convergence, and the state analysis model can analyze the state of the target component based on the component information.

[0188] In this optional embodiment, optionally, the component state of the target component can be comprehensively determined by a comprehensive data processor, a state analysis model, and an anomaly detection platform.

[0189] In this optional embodiment, further optionally, the device status information of the target device may be jointly determined by the anomaly detection platform and the data collector.

[0190] It can be seen that the implementation of this optional embodiment can determine the component state of the target component through the data collector according to the component information and in combination with the state analysis model and the anomaly detection platform, and determine the device state information of the target device according to the component state of the target component. The data collector can collect various parameter data from the target component with high precision to ensure the accuracy and reliability of the data. The data collector can collect data in real time and analyze it in real time through the anomaly detection platform to make the monitoring of the device state more timely and improve the accuracy and reliability of the component state of the target component. Real-time monitoring and predictive maintenance of the device state help to maintain the stable operation of the equipment and reduce production delays and interruptions caused by equipment failures, thereby improving production efficiency. It can also promptly discover and deal with safety hazards of the equipment, effectively prevent the occurrence of equipment accidents, and improve the safety and reliability of the operation of the target component and the target device, thereby improving the accuracy and reliability of determining the component state of the target component and determining the device state information of the target device.

[0191] Embodiment 3

[0192] See also Figure 3 , Figure 3 is a schematic diagram of a structure of a target device anomaly detection device disclosed in an embodiment of the present invention. The device is applied to an anomaly detection system, wherein the anomaly detection system includes a target sensor and a data processor, wherein the data processor includes a data collector, such as Figure 3 As shown, the abnormality detection device applied to the target device may include:

[0193] A collection module 301 is used to collect component information of a target component on a target device through a target sensor, wherein the target sensor includes an angle recognition sensor and / or a fracture recognition sensor;

[0194] The determination module 302 is used to determine the component state of the target component according to the component information and the predetermined state analysis model through the data processor, and determine the device state information of the target device according to the component state of the target component;

[0195] The generating module 303 is used to determine the device abnormality information in the device status information, and generate the abnormality detection result of the target device according to the device abnormality information.

[0196] It can be seen that implementation Figure 3 The described device can collect component information of a target component on a target device through a target sensor, and determine the component status of the target component through a data processor according to the component information, determine the device status information of the target device according to the component status of the target component and further determine the device abnormality information, and determine the abnormality detection result according to the device abnormality information. It can collect the information of the target component and determine the status of the target component through the target sensor, and can specifically collect the component information of each target component and determine the component status, which is conducive to improving the accuracy and reliability of determining the component status of each target component, and is conducive to improving the intelligence and efficiency of determining the component status of each target component, and can determine the device status information of the target device according to the component status of the target component, which is conducive to improving the accuracy and intelligence of determining the device status information, thereby facilitating improving the determination of device abnormality information and abnormality detection results based on the device status information, and can timely discover abnormal problems existing in the target device by monitoring the status of the target component and performing abnormality detection, thereby facilitating improving the accuracy and reliability of generating abnormality detection results for the target device, thereby realizing accurate detection of abnormal conditions of the target device, and is conducive to improving the reliability and safety of the operation of the target device.

[0197] In an optional embodiment, if Figure 4 As shown, the determination module 302 is further used to determine component abnormality information of the target device according to the abnormality detection result, wherein the component abnormality information includes one or more of component abnormality quantity information and component abnormality degree information;

[0198] The device also includes:

[0199] The acquisition module 304 is used to acquire the original component information of the target device;

[0200] A comparison module 305 is used to perform a comparison operation on the original component information and the component abnormality information to obtain an information comparison result;

[0201] A judgment module 306 is used to judge whether the target device meets the preset device operation conditions based on the information comparison result;

[0202] The determination module 302 is further configured to determine the abnormality detection cause corresponding to the information comparison result according to the information comparison result and the preset device operating condition when the determination module 306 determines that the target device does not meet the preset device operating condition;

[0203] An execution module 307 is used to perform an exception handling operation on the target device based on the cause of the exception detection;

[0204] The specific manner in which the judgment module 306 judges whether the target device meets the preset device operating conditions based on the information comparison result includes:

[0205] Based on the information comparison result, determine the abnormal proportion of components of the target device, and judge whether the abnormal proportion of components is greater than or equal to a preset abnormal proportion threshold;

[0206] When it is determined that the component abnormality ratio is greater than or equal to the preset abnormality ratio threshold, it is determined that the target device meets the preset device operating conditions; when it is determined that the component abnormality ratio is less than the preset abnormality ratio threshold, it is determined that the target device does not meet the preset device operating conditions.

[0207] It can be seen that implementation Figure 4 The described device can determine the component abnormality information of the target equipment according to the abnormality detection result, obtain the original component information of the target equipment and perform a comparison operation to obtain the information comparison result, and further judge whether the target equipment meets the preset equipment operating conditions. If not, the corresponding abnormality detection cause is determined according to the information comparison result and the equipment operating conditions, and then the abnormality handling operation is performed. It can timely detect and diagnose abnormal problems of the target equipment, reduce the risk of equipment damage to the target equipment, thereby helping to improve the reliability and safety of the target equipment, and can timely discover abnormal problems of the target equipment and perform predictive maintenance on the target equipment, and avoid failure of the target equipment or danger during use due to unexpected failures. It can also analyze abnormal data and identify potential improvement points of the target equipment based on the information comparison results, so as to further improve the efficiency and performance of the target equipment, thereby improving the utilization rate of the target equipment through automated intelligent abnormality detection, thereby achieving accurate detection of abnormal conditions of the target equipment, and helping to improve the reliability and safety of the target equipment operation.

[0208] In another optional embodiment, Figure 4 As shown, when the target sensor includes an angle recognition sensor, the specific manner in which the acquisition module 301 acquires component information of the target component on the target device through the target sensor includes:

[0209] Acquiring component angle parameters of the target component by an angle recognition sensor, wherein the component angle parameters include current angle parameters of the target component and / or angle difference parameters between the current angle parameters of the target component and a preset reference angle parameter;

[0210] Performing an angle calibration operation on the component angle parameter to obtain the angle calibration parameter, and determining component information of the target component on the target device based on the angle calibration parameter;

[0211] Furthermore, when the target sensor includes a fracture recognition sensor, the specific manner in which the acquisition module 301 acquires component information of the target component on the target device through the target sensor includes:

[0212] Collecting component position parameters of the target component by means of a fracture identification sensor, wherein the component position parameters include current position parameters of the target component and / or displacement difference parameters between the current position parameters of the target component and preset reference position parameters;

[0213] A displacement check operation is performed on the component position parameters to obtain displacement check parameters, and component information of a target component on a target device is determined based on the displacement check parameters.

[0214] It can be seen that implementation Figure 4 The described device can collect component angle information of the target component through an angle recognition sensor and perform an angle calibration operation to obtain angle calibration parameters, and determine component information of the target component on the target device based on the angle calibration parameters, or collect component position parameters of the target component through a fracture recognition sensor and perform a displacement calibration operation to obtain displacement calibration parameters, and determine component information of the target component on the target device based on the displacement calibration parameters. The component angle parameters or component position parameters corresponding to the target component can be collected by two sensors respectively, which is conducive to improving the accuracy and reliability of obtaining the angle calibration parameters and obtaining the displacement calibration parameters, thereby facilitating improving the accuracy and reliability of determining the component information of the target component based on the angle calibration parameters and the displacement calibration parameters, and the component information collected by the angle recognition sensor and the fracture recognition sensor can more comprehensively understand the state of the target component, including parameters such as its position and angle. Through the calibration operation and comparative analysis, it can ensure that the collected information is accurate and reliable, thereby providing more reliable data support for state monitoring and abnormality detection of the target device, helping to improve the stability and performance of the system, thereby being conducive to improving the accuracy and reliability of generating abnormality detection results of the target device, thereby achieving accurate detection of abnormal conditions of the target device, and being conducive to improving the reliability and safety of the operation of the target device.

[0215] In yet another optional embodiment, Figure 4As shown, the specific manner in which the determination module 302 determines the component status of the target component according to the component information, and determines the device status information of the target device according to the component status of the target component includes:

[0216] Determine the looseness parameter of the target component according to the component information, determine the parameter difference relationship between the looseness parameter of the target component and the preset target parameter, and determine the component state of the target component based on the parameter difference relationship;

[0217] Determining, according to the component state of the target component, operation impact information of the component state of the target component on the target device, wherein the operation impact information includes state impact information of the target component on the target device;

[0218] An information fitting operation is performed on the operation impact information and the component state of the target component to obtain an information fitting result, and the device state information of the target device is determined based on the information fitting result; wherein the information fitting result is at least used to represent the current operation impact information of the component state of the target component on the target device.

[0219] It can be seen that implementation Figure 4 The described device can determine the loosening parameters of the target component according to the component information and determine the parameter difference relationship between the loosening parameters and the target parameters to determine the component state of the target component, and determine the operation impact information according to the component state of the target component, perform information fitting operations based on the operation impact information and the component state of the target component to obtain information fitting results, and determine the equipment state information of the target device according to the information fitting results, and can monitor and diagnose the loosening parameters of the target component in real time, can timely discover potential problems and take corresponding measures to ensure the safe and reliable operation of the target device, and can determine the parameter difference relationship between the loosening parameters of the target component and the preset target parameters. , as well as the impact information of component status on the operation of the target equipment, can realize predictive maintenance of the equipment. Furthermore, through information fitting operations, the operation impact information and component status can be fitted to obtain more accurate equipment status information, which is conducive to optimizing the performance of the equipment, improving its efficiency and stability, and through timely monitoring and diagnosis, as well as predictive maintenance measures, it can reduce equipment wear and damage, extend its service life, and reduce replacement and repair costs, which can be conducive to improving the accuracy and reliability of generating abnormal detection results for the target equipment, thereby realizing accurate detection of abnormal conditions of the target equipment, and is conducive to improving the reliability and safety of the target equipment operation.

[0220] In yet another optional embodiment, Figure 4 As shown, the specific manner in which the generating module 303 generates the abnormality detection result of the target device according to the device abnormality information includes:

[0221] Determine the abnormality degree of the fan of the target device according to the device abnormality information, wherein the abnormality degree of the fan at least includes abnormality degree information of the target component included in the target device;

[0222] Determine a degree difference relationship between the abnormality degree of the fan and a preset target abnormality degree, wherein the degree difference relationship includes at least a degree difference value between the abnormality degree of the fan and the target abnormality degree;

[0223] Determine whether the degree difference relationship satisfies a preset degree difference condition, obtain a degree determination result, and generate an abnormality detection result of the target device according to the degree determination result;

[0224] The specific manner in which the generating module 303 generates the abnormality detection result of the target device according to the degree judgment result includes:

[0225] When the degree judgment result is used to indicate that the degree difference relationship satisfies a preset degree difference condition, an abnormality detection result of the target device is generated according to the degree judgment result, wherein the abnormality detection result is used to indicate that the target device is in a normal operating state;

[0226] When the degree judgment result is used to indicate that the degree difference relationship does not satisfy the preset degree difference condition, the component maintenance parameters of the target device are predicted based on the degree difference relationship, and the abnormality detection result of the target device is generated based on the component maintenance parameters and the degree difference relationship, wherein the abnormality detection result is used to indicate that the target device is in an abnormal operating state.

[0227] It can be seen that implementation Figure 4The described device can determine the degree of abnormality of the fan of the target device according to the equipment abnormality information, and determine the degree difference relationship between the degree of abnormality of the fan and the target abnormality degree and judge whether the degree difference condition is met to obtain the degree judgment result and then generate the abnormality detection result of the target device, wherein, when the degree judgment result is used to indicate that the degree difference relationship satisfies the degree difference condition, the abnormality detection result of the target device is generated according to the degree judgment result, and when the degree judgment result is used to indicate that the degree difference relationship does not satisfy the degree difference condition, the component maintenance parameters of the target device are predicted, and the abnormality detection result of the target device is generated according to the component maintenance parameters and the degree difference relationship. By monitoring various parameters of the target device and comparing them with the preset target abnormality degree, real-time abnormality detection can be realized, and abnormal conditions that may exist in the target device can be discovered in time, so that corresponding measures can be taken. Ensure the safe operation of the equipment, and by analyzing the degree difference relationship between the degree of fan abnormality and the preset target abnormality, the degree of abnormality of the target equipment can be accurately judged, which is conducive to determining the severity of the abnormal situation and providing guidance for subsequent maintenance and repair work. When the degree difference relationship does not meet the preset conditions, based on the predicted component maintenance parameters and degree difference relationship, possible failures can be predicted in advance and maintenance plans can be formulated accordingly. Predictive maintenance helps to avoid sudden failures and reduce downtime, which is conducive to improving the availability and reliability of the target equipment. Being able to detect and repair problems in a timely manner can reduce losses caused by failures and avoid production losses caused by downtime, thereby reducing overall maintenance costs, which is conducive to improving the safety, reliability and efficiency of the target equipment, reducing maintenance costs, and also improving the life and utilization of equipment.

[0228] In yet another optional embodiment, Figure 4 As shown, the acquisition module 301 performs an angle calibration operation on the component angle parameter to obtain the angle calibration parameter, and determines the component information of the target component on the target device based on the angle calibration parameter. The specific method includes:

[0229] Based on the component angle parameter, an angle rotation signal of the target component is determined, and based on the angle rotation signal and a preset reference angle signal, a verification operation is performed on the angle rotation signal of the target component to obtain an angle difference value between the angle rotation signal of the target component and the reference angle signal, and an angle verification parameter is determined based on the angle difference value, and an angle loosening parameter of the target component is determined according to the angle verification parameter, and a preload force parameter of the target component is determined according to the angle loosening parameter, a component attribute parameter of the target component and a predetermined target calculation formula, and component information of the target component is determined based on the preload force parameter of the target component, the component attribute parameter includes a material elastic modulus parameter of the target component, a radial equivalent cross-sectional area parameter of the target component, a clamping length parameter of the target component, and a pitch parameter of the target component, and the angle loosening parameter includes a loosening change amount of the target component, an angular displacement change amount of the target component, and an angular change amount of the target component;

[0230] Furthermore, the acquisition module 301 performs a displacement verification operation on the component position parameter to obtain the displacement verification parameter, and determines the component information of the target component on the target device based on the displacement verification parameter. The specific method includes:

[0231] Determine a current position signal of a target component based on the component position parameter, and perform a displacement verification operation on the current position signal of the target component based on the current position signal and a preset reference distance signal to obtain a displacement verification parameter, and determine component information of the target component on the target device based on the displacement verification parameter, wherein the displacement verification parameter includes a displacement distance parameter between the current position signal and the preset reference distance signal;

[0232] And, the predetermined target calculation formula includes:

[0233] F = E × S × △ L / L;

[0234] △L=△T×а;

[0235] △T=P / 360°;

[0236] Among them, F is the preload force of the target component, E is the material elastic modulus of the target component, S is the radial equivalent cross-sectional area of ​​the target component, △L is the looseness change of the target component, L is the clamping length of the target component, P is the pitch of the target component, а is the angular change of the target component, and △T is the angular displacement change of the target component.

[0237] It can be seen that implementation Figure 4The described device can determine the angle rotation signal of the target component based on the component angle parameter and perform a calibration operation to obtain the angle difference value and then obtain the angle calibration parameter, determine the angle looseness parameter of the target component according to the angle calibration parameter and then determine the component information of the target component, and determine the current position signal of the target component based on the component position parameter and perform a displacement calibration operation to obtain the displacement calibration parameter and determine the component information of the target component on the target device based on the displacement calibration parameter. By performing a calibration operation on the angle parameter and position parameter of the component, the actual angle and position information of the component can be accurately obtained and compared with the preset reference signal, thereby obtaining accurate angle difference value and displacement distance parameter. It is beneficial to avoid the accumulation of errors, improve the accuracy of the target equipment component information, and according to the angle verification parameters and displacement verification parameters, the angle looseness parameters and other relevant information of the target component can be further determined, and the potential failure or abnormality of the target equipment component can be discovered in time, so as to take corresponding maintenance measures, avoid the expansion of failures, and improve the operating stability and reliability of the target equipment. Based on accurate component information, the maintenance plan of the target equipment can be formulated more scientifically, the maintenance time and resources can be arranged reasonably, and unnecessary downtime and maintenance costs can be reduced. It can also help to improve its overall performance and life, thereby helping to improve the safety, reliability and efficiency of the target equipment, reduce maintenance costs, and also improve the life and utilization of the equipment.

[0238] In yet another optional embodiment, Figure 4 As shown, the specific manner in which the execution module 307 performs the exception handling operation on the target device based on the exception detection cause includes:

[0239] Based on the abnormality detection cause and the abnormality information of the component of the target device, an abnormality prediction trend of the target device is generated, wherein the abnormality prediction trend includes one or more of the predicted abnormal time, predicted abnormal duration, and predicted abnormal component of the target device;

[0240] Obtaining the operation demand information of the target equipment in a preset future time period, and determining the maintenance demand information of the target equipment based on the abnormal prediction trend and the operation demand information, wherein the maintenance demand information includes one or more of the maintenance time requirement, maintenance method requirement, and maintenance time requirement;

[0241] Based on the maintenance requirement information, maintenance parameters matching the maintenance requirement information are determined from a predetermined processing parameter library, and target processing parameters are generated based on all maintenance parameters, and an abnormality processing operation is performed on the target device based on the target processing parameters.

[0242] It can be seen that implementation Figure 4The described device can generate an abnormality prediction trend based on the abnormality detection cause and the abnormality information of the components of the target equipment, obtain the operation requirement information of the target equipment, and determine the maintenance requirement information of the target equipment based on the abnormality prediction trend and the operation requirement information, determine the maintenance parameters based on the maintenance requirement information and the processing parameter library to generate the target processing parameters and then perform the abnormality processing operation on the target equipment, and can generate the abnormality prediction trend by analyzing the abnormality detection cause and the abnormality information of the components of the target equipment, and can predict the potential abnormal moment, abnormal duration and abnormal components that may be involved of the target equipment in advance, so as to ensure that the target equipment can be promptly and effectively processed before or when the abnormality occurs, and obtain the target equipment at The operation demand information in the preset future time period, combined with the abnormal prediction trend, can determine the maintenance demand information that is more in line with the actual operation status, which can avoid unnecessary shutdown and maintenance, and ensure that the target equipment can be properly maintained while meeting the operation requirements. By screening out matching maintenance parameters from a predetermined processing parameter library based on the maintenance demand information, and generating target processing parameters, accurate abnormal handling of the target equipment can be achieved, which is beneficial to improving the efficiency and accuracy of abnormal handling. Therefore, through timely and effective abnormal handling and preventive maintenance, the service life of the target equipment can be extended, the frequency and severity of failures can be reduced, and the reliability and stability of the target equipment can be improved.

[0243] In yet another optional embodiment, Figure 4 As shown, the data processor also includes an abnormality detection platform; wherein the determination module determines the component status of the target component according to the component information through the data processor, and determines the device status information of the target device according to the component status of the target component. The specific method includes:

[0244] The data collector determines the component status of the target component based on the component information, combined with a predetermined status analysis model and an anomaly detection platform, and determines the device status information of the target device based on the component status of the target component.

[0245] It can be seen that the implementation of this optional embodiment can determine the component state of the target component through the data collector according to the component information and in combination with the state analysis model and the anomaly detection platform, and determine the device state information of the target device according to the component state of the target component. The data collector can collect various parameter data from the target component with high precision to ensure the accuracy and reliability of the data. The data collector can collect data in real time and analyze it in real time through the anomaly detection platform to make the monitoring of the device state more timely and improve the accuracy and reliability of the component state of the target component. Real-time monitoring and predictive maintenance of the device state help to maintain the stable operation of the equipment and reduce production delays and interruptions caused by equipment failures, thereby improving production efficiency. It can also promptly discover and deal with safety hazards of the equipment, effectively prevent the occurrence of equipment accidents, and improve the safety and reliability of the operation of the target component and the target device, thereby improving the accuracy and reliability of determining the component state of the target component and determining the device state information of the target device.

[0246] Embodiment 4

[0247] See also Figure 5 , Figure 5 FIG. 1 is a schematic diagram of another structure of a target device abnormality detection device disclosed in an embodiment of the present invention. Figure 5 As shown, the abnormality detection device applied to the target device may include:

[0248] A memory 401 storing executable program codes;

[0249] a processor 402 coupled to the memory 401;

[0250] The processor 402 calls the executable program code stored in the memory 401 to execute the steps of the target device abnormality detection method described in the first embodiment of the present invention or the second embodiment of the present invention.

[0251] Embodiment 5

[0252] An embodiment of the present invention discloses a computer storage medium, which stores computer instructions. When the computer instructions are called, they are used to execute the steps of the target device anomaly detection method described in Embodiment 1 or Embodiment 2 of the present invention.

[0253] Embodiment 6

[0254] An embodiment of the present invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to enable a computer to execute the steps of the target device anomaly detection method described in Embodiment 1 or Embodiment 2.

[0255] The device embodiments described above are only illustrative, wherein the modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical modules, i.e., they may be located in one place, or they may be distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Those of ordinary skill in the art may understand and implement it without creative work.

[0256] Through the specific description of the above embodiments, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on such an understanding, the above technical solution can be essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, and the storage medium includes a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable rewritable read-only memory (EEPROM), a compact disc (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0257] Finally, it should be noted that the method and device for detecting anomalies in a target device disclosed in the embodiments of the present invention are only preferred embodiments of the present invention, and are only used to illustrate the technical solution of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for detecting anomalies of a target device, characterized in that: The method is applied to an anomaly detection system, wherein the anomaly detection system includes a target sensor and a data processor, wherein the data processor includes a data collector, and the method includes: Collecting component information of a target component on the target device by means of the target sensor, wherein the target sensor comprises an angle recognition sensor and / or a fracture recognition sensor; Determining, by the data processor, the component status of the target component according to the component information and a predetermined status analysis model, and determining the device status information of the target device according to the component status of the target component; Determining device abnormality information in the device status information, and generating an abnormality detection result of the target device according to the device abnormality information; The method further comprises: Determine component abnormality information of the target device according to the abnormality detection result, wherein the component abnormality information includes one or more of component abnormality quantity information and component abnormality degree information; Acquire original component information of the target device, perform a comparison operation on the original component information and the component abnormality information, and obtain an information comparison result; Based on the information comparison result, determining whether the target device meets the preset device operating conditions; When it is determined that the target device does not meet the preset device operating condition, determining the abnormality detection reason corresponding to the information comparison result according to the information comparison result and the preset device operating condition, and performing an abnormality handling operation on the target device based on the abnormality detection reason; Wherein, judging whether the target device meets a preset device operating condition based on the information comparison result includes: Based on the information comparison result, determine the component abnormality ratio of the target device, and judge whether the component abnormality ratio is greater than or equal to a preset abnormality ratio threshold; When it is determined that the component abnormality ratio is greater than or equal to the preset abnormality ratio threshold, it is determined that the target device meets the preset device operating condition; when it is determined that the component abnormality ratio is less than the preset abnormality ratio threshold, it is determined that the target device does not meet the preset device operating condition; When the target sensor includes the angle recognition sensor, collecting component information of the target component on the target device through the target sensor includes: Acquiring component angle parameters of the target component by means of the angle recognition sensor, wherein the component angle parameters include current angle parameters of the target component and / or angle difference parameters between the current angle parameters of the target component and a preset reference angle parameter; Performing an angle calibration operation on the component angle parameter to obtain an angle calibration parameter, and determining component information of the target component on the target device based on the angle calibration parameter; And, when the target sensor includes the fracture identification sensor, collecting component information of the target component on the target device through the target sensor includes: Collecting component position parameters of the target component by means of the fracture identification sensor, wherein the component position parameters include current position parameters of the target component and / or displacement difference parameters between the current position parameters of the target component and preset reference position parameters; Performing a displacement check operation on the component position parameter to obtain a displacement check parameter, and determining component information of the target component on the target device based on the displacement check parameter; The performing an angle calibration operation on the component angle parameter to obtain the angle calibration parameter, and determining the component information of the target component on the target device based on the angle calibration parameter, includes: Based on the component angle parameter, an angle rotation signal of the target component is determined, and based on the angle rotation signal and a preset reference angle signal, a verification operation is performed on the angle rotation signal of the target component to obtain an angle difference value between the angle rotation signal of the target component and the reference angle signal, and an angle verification parameter is determined based on the angle difference value, and an angle loosening parameter of the target component is determined according to the angle verification parameter, and a preload force parameter of the target component is determined according to the angle loosening parameter, a component attribute parameter of the target component and a predetermined target calculation formula, and component information of the target component is determined based on the preload force parameter of the target component, wherein the component attribute parameter includes a material elastic modulus parameter of the target component, a radial equivalent cross-sectional area parameter of the target component, a clamping length parameter of the target component, and a pitch parameter of the target component, and the angle loosening parameter includes a loosening change amount of the target component, an angular displacement change amount of the target component, and an angular change amount of the target component; And, performing a displacement check operation on the component position parameter to obtain a displacement check parameter, and determining component information of the target component on the target device based on the displacement check parameter, includes: Determine the current position signal of the target component based on the component position parameter, and perform a displacement verification operation on the current position signal of the target component based on the current position signal and a preset reference distance signal to obtain a displacement verification parameter, and determine component information of the target component on the target device based on the displacement verification parameter, wherein the displacement verification parameter includes a displacement distance parameter between the current position signal and the preset reference distance signal; And, the predetermined target calculation formula includes: F = E × S × △ L / L; △L=△T×а; △T=P / 360°; Wherein, F is the preload force of the target component, E is the material elastic modulus of the target component, S is the radial equivalent cross-sectional area of ​​the target component, ΔL is the looseness change of the target component, L is the clamping length of the target component, P is the pitch of the target component, а is the angular change of the target component, and ΔT is the angular displacement change of the target component; The performing an exception handling operation on the target device based on the exception detection cause includes: Based on the abnormality detection cause and the abnormality information of the component of the target device, generating an abnormality prediction trend of the target device, wherein the abnormality prediction trend includes one or more of the predicted abnormal time, predicted abnormal duration, and predicted abnormal component of the target device; Obtaining the operation requirement information of the target equipment in a preset future time period, and determining the maintenance requirement information of the target equipment based on the abnormal prediction trend and the operation requirement information, wherein the maintenance requirement information includes one or more of maintenance time requirement, maintenance method requirement, and maintenance time requirement; Based on the maintenance requirement information, maintenance parameters matching the maintenance requirement information are determined from a predetermined processing parameter library, and target processing parameters are generated based on all the maintenance parameters, and an exception processing operation is performed on the target device based on the target processing parameters.

2. The method for detecting anomalies of a target device according to claim 1, characterized in that: Determining a component state of the target component according to the component information, and determining device state information of the target device according to the component state of the target component, including: Determining a loose parameter of the target component according to the component information, determining a parameter difference relationship between the loose parameter of the target component and a preset target parameter, and determining a component state of the target component based on the parameter difference relationship; Determining, according to the component state of the target component, operation impact information of the component state of the target component on the target device, wherein the operation impact information includes state impact information of the target component on the target device; An information fitting operation is performed on the operation impact information and the component status of the target component to obtain an information fitting result, and the device status information of the target device is determined based on the information fitting result; wherein the information fitting result is at least used to represent the current operation impact information of the component status of the target component on the target device.

3. The method for detecting anomalies of a target device according to claim 1, characterized in that: The generating, according to the device abnormality information, an abnormality detection result of the target device includes: Determining the abnormality degree of the fan of the target device according to the device abnormality information, wherein the abnormality degree of the fan at least includes abnormality degree information of the target component included in the target device; Determining a degree difference relationship between the abnormality degree of the fan and a preset target abnormality degree, wherein the degree difference relationship at least includes a degree difference value between the abnormality degree of the fan and the target abnormality degree; Determining whether the degree difference relationship satisfies a preset degree difference condition, obtaining a degree determination result, and generating an abnormality detection result of the target device according to the degree determination result; The step of generating the abnormality detection result of the target device according to the degree judgment result includes: When the degree judgment result is used to indicate that the degree difference relationship satisfies the preset degree difference condition, generating an abnormality detection result of the target device according to the degree judgment result, wherein the abnormality detection result is used to indicate that the target device is in a normal operating state; When the degree judgment result is used to indicate that the degree difference relationship does not satisfy the preset degree difference condition, the component maintenance parameters of the target device are predicted based on the degree difference relationship, and the abnormality detection result of the target device is generated based on the component maintenance parameters and the degree difference relationship, wherein the abnormality detection result is used to indicate that the target device is in an abnormal operating state.

4. The method for detecting anomalies of a target device according to claim 1, characterized in that: The data processor also includes an abnormality detection platform; wherein, determining the component status of the target component according to the component information by the data processor, and determining the device status information of the target device according to the component status of the target component, includes: The data collector determines the component status of the target component based on the component information, in combination with a predetermined status analysis model and the abnormality detection platform, and determines the device status information of the target device based on the component status of the target component.

5. A device for detecting abnormality of a target device, characterized in that: The device is applied to the anomaly detection method according to any one of claims 1 to 4 and to an anomaly detection system, wherein the anomaly detection system comprises a target sensor and a data processor, wherein the data processor comprises a data collector, and the device comprises: A collection module, used for collecting component information of a target component on the target device through the target sensor, wherein the target sensor includes an angle recognition sensor and / or a fracture recognition sensor; a determination module, configured to determine the component state of the target component through the data processor according to the component information and in combination with a predetermined state analysis model, and determine the device state information of the target device according to the component state of the target component; A generating module, configured to determine device abnormality information in the device status information, and generate an abnormality detection result of the target device according to the device abnormality information; The determination module is further configured to determine component abnormality information of the target device according to the abnormality detection result, wherein the component abnormality information includes one or more of component abnormality quantity information and component abnormality degree information; The device also includes: An acquisition module, used to acquire original component information of the target device; A comparison module, used to perform a comparison operation on the original component information and the component abnormality information to obtain an information comparison result; A judgment module, used to judge whether the target device meets the preset device operation conditions based on the information comparison result; The determination module is further configured to determine, when the determination module determines that the target device does not meet the preset device operating condition, a cause of abnormal detection corresponding to the information comparison result according to the information comparison result and the preset device operating condition; An execution module, configured to execute an exception handling operation on the target device based on the exception detection cause; The specific manner in which the judgment module judges whether the target device meets the preset device operating conditions based on the information comparison result includes: Based on the information comparison result, determine the component abnormality ratio of the target device, and judge whether the component abnormality ratio is greater than or equal to a preset abnormality ratio threshold; When it is determined that the component abnormality ratio is greater than or equal to the preset abnormality ratio threshold, it is determined that the target device meets the preset device operating condition; when it is determined that the component abnormality ratio is less than the preset abnormality ratio threshold, it is determined that the target device does not meet the preset device operating condition; When the target sensor includes the angle recognition sensor, the specific manner in which the acquisition module acquires the component information of the target component on the target device through the target sensor includes: Acquiring component angle parameters of the target component by means of the angle recognition sensor, wherein the component angle parameters include current angle parameters of the target component and / or angle difference parameters between the current angle parameters of the target component and a preset reference angle parameter; Performing an angle calibration operation on the component angle parameter to obtain an angle calibration parameter, and determining component information of the target component on the target device based on the angle calibration parameter; Furthermore, when the target sensor includes the fracture identification sensor, the specific manner in which the acquisition module acquires component information of the target component on the target device through the target sensor includes: Collecting component position parameters of the target component by means of the fracture identification sensor, wherein the component position parameters include current position parameters of the target component and / or displacement difference parameters between the current position parameters of the target component and preset reference position parameters; Performing a displacement check operation on the component position parameter to obtain a displacement check parameter, and determining component information of the target component on the target device based on the displacement check parameter; The specific manner in which the acquisition module performs an angle calibration operation on the component angle parameter to obtain the angle calibration parameter, and determines the component information of the target component on the target device based on the angle calibration parameter includes: Based on the component angle parameter, an angle rotation signal of the target component is determined, and based on the angle rotation signal and a preset reference angle signal, a verification operation is performed on the angle rotation signal of the target component to obtain an angle difference value between the angle rotation signal of the target component and the reference angle signal, and an angle verification parameter is determined based on the angle difference value, and an angle loosening parameter of the target component is determined according to the angle verification parameter, and a preload force parameter of the target component is determined according to the angle loosening parameter, a component attribute parameter of the target component and a predetermined target calculation formula, and component information of the target component is determined based on the preload force parameter of the target component, wherein the component attribute parameter includes a material elastic modulus parameter of the target component, a radial equivalent cross-sectional area parameter of the target component, a clamping length parameter of the target component, and a pitch parameter of the target component, and the angle loosening parameter includes a loosening change amount of the target component, an angular displacement change amount of the target component, and an angular change amount of the target component; And, the acquisition module performs a displacement verification operation on the component position parameter to obtain a displacement verification parameter, and determines the component information of the target component on the target device based on the displacement verification parameter in a specific manner including: Determine the current position signal of the target component based on the component position parameter, and perform a displacement verification operation on the current position signal of the target component based on the current position signal and a preset reference distance signal to obtain a displacement verification parameter, and determine component information of the target component on the target device based on the displacement verification parameter, wherein the displacement verification parameter includes a displacement distance parameter between the current position signal and the preset reference distance signal; And, the predetermined target calculation formula includes: F = E × S × △ L / L; △L=△T×а; △T=P / 360°; Wherein, F is the preload force of the target component, E is the material elastic modulus of the target component, S is the radial equivalent cross-sectional area of ​​the target component, ΔL is the looseness change of the target component, L is the clamping length of the target component, P is the pitch of the target component, а is the angular change of the target component, and ΔT is the angular displacement change of the target component; The specific manner in which the execution module performs the exception handling operation on the target device based on the exception detection cause includes: Based on the abnormality detection cause and the abnormality information of the component of the target device, generating an abnormality prediction trend of the target device, wherein the abnormality prediction trend includes one or more of the predicted abnormal time, predicted abnormal duration, and predicted abnormal component of the target device; Obtaining the operation requirement information of the target equipment in a preset future time period, and determining the maintenance requirement information of the target equipment based on the abnormal prediction trend and the operation requirement information, wherein the maintenance requirement information includes one or more of maintenance time requirement, maintenance method requirement, and maintenance time requirement; Based on the maintenance requirement information, maintenance parameters matching the maintenance requirement information are determined from a predetermined processing parameter library, and target processing parameters are generated based on all the maintenance parameters, and an exception processing operation is performed on the target device based on the target processing parameters.

6. A device for detecting abnormality of a target device, characterized in that: The device comprises: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the abnormality detection method applied to the target device as described in any one of claims 1-4.

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