A method and system for monitoring abnormal operation of a circuit board controller

Abstract

The present invention discloses a method and system for monitoring abnormal operation of a circuit board controller, relating to the technical field of circuit board controller monitoring. The method includes: S1. Collecting the operation parameters of the circuit board controller of an automated robot; S2. Evaluating the operation parameters of the circuit board controller of the automated robot; S3. Responding to the abnormal operation parameters of the circuit board controller of the automated robot; S4. Obtaining the predicted operation parameters of the circuit board controller of the automated robot; S5. Evaluating the predicted operation parameters of the circuit board controller of the automated robot; S6. Responding to the predicted risk operation parameters of the circuit board controller of the automated robot. By applying data analysis technology, the system can not only detect current abnormalities but also predict future possible problems based on historical data. This proactive maintenance strategy can significantly reduce the incidence of sudden failures and effectively reduce maintenance costs and system downtime.

Description

Technical Field

[0001] The present invention relates to the technical field of circuit board controller monitoring, and particularly to a method and system for monitoring abnormal operation of a circuit board controller. Background Art

[0002] With the development of technologies such as artificial intelligence and machine learning, automated robots can work in more complex and changing environments, greatly improving the production efficiency of intelligent manufacturing production lines and ensuring high standards of product quality. It has become particularly crucial for the circuit board controller of an automated robot to maintain its stable operation. Any abnormal situation in the circuit board controller of an automated robot may trigger a failure of the overall system and may cause serious financial damage and safety hazards. Therefore, developing an efficient method and system for detecting abnormal operation has become an urgent problem in the industry.

[0003] In the prior art, the monitoring of abnormal operation of circuit board controllers can meet basic requirements, but there are also some potential problems, which are specifically reflected in the following aspects: First, the existing monitoring methods for circuit board controllers of automated robots rely on periodic inspections or repairs after a failure occurs, depending on regular maintenance inspections rather than continuous monitoring, resulting in the situation of missing the early stage of fault development, being unable to achieve the optimal maintenance timing, causing more serious damage to the circuit board controller of the automated robot and higher repair costs.

[0004] Second, the existing monitoring methods for circuit board controllers of automated robots ignore the operating parameters of historical monitoring, fail to make full use of the collected data for in-depth analysis, lack data analysis capabilities, resulting in the inability to obtain predicted operating parameters in advance based on historical operating parameters for evaluation to avoid future problems, and being unable to effectively ensure the stable operation of the circuit board controller of the automated robot, posing a certain safety hazard to the production of the industry.

[0005] Third, the prior art ignores the factors affecting the normal operation of the circuit board controller of the automated robot, including internal operating parameters and external environmental parameters. When an abnormal operation occurs in the circuit board controller of the automated robot, it is impossible to determine the cause of the abnormal operation of the circuit board controller of the automated robot immediately, resulting in the inability to perform targeted repairs in a timely manner, reducing the repair efficiency and the stability of enterprise production. Summary of the Invention

[0006] The purpose of the present invention is to provide a method and system for monitoring abnormal operation of a circuit board controller to solve the problems existing in the background art.

[0007] In the first aspect of the present invention, a method for monitoring abnormal operation of a circuit board controller is provided. The method includes: S1. Collecting operation parameters of the circuit board controller of the automated robot: Collecting various working parameters of the circuit board controller of the automated robot, constructing a working parameter data set of the circuit board controller of the automated robot, collecting various environmental parameters of the circuit board controller of the automated robot, and constructing an environmental parameter data set of the circuit board controller of the automated robot.

[0008] S2. Evaluating the operation parameters of the circuit board controller of the automated robot: Evaluating whether each working parameter of the circuit board controller of the automated robot is abnormal to obtain each abnormal working parameter of the circuit board controller of the automated robot, evaluating whether each environmental parameter of the circuit board controller of the automated robot is abnormal to obtain each abnormal environmental parameter of the circuit board controller of the automated robot, and constructing an abnormal operation parameter data set of the circuit board controller of the automated robot.

[0009] S3. Responding to the abnormal operation parameters of the circuit board controller of the automated robot: Implementing corresponding response measures based on the abnormal operation parameter data set of the circuit board controller of the automated robot.

[0010] S4. Obtaining the predicted operation parameters of the circuit board controller of the automated robot: Obtaining the historical working parameters of the circuit board controller of the automated robot to obtain each predicted working parameter of the circuit board controller of the automated robot, constructing a predicted working parameter data set of the circuit board controller of the automated robot, obtaining the historical environmental parameters of the circuit board controller of the automated robot to obtain each predicted environmental parameter of the circuit board controller of the automated robot, and constructing a predicted environmental parameter data set of the circuit board controller of the automated robot.

[0011] S5. Predicting the risk operation parameters of the circuit board controller of the automated robot: Obtaining each predicted risk working parameter of the circuit board controller of the automated robot based on the predicted working parameter data set of the circuit board controller of the automated robot, obtaining each predicted risk environmental parameter of the circuit board controller of the automated robot based on the predicted environmental parameter data set of the circuit board controller of the automated robot, and constructing a predicted risk operation parameter data set of the circuit board controller of the automated robot.

[0012] S6. Responding to the predicted risk operation parameters of the circuit board controller of the automated robot: Implementing corresponding response measures based on the predicted risk operation parameter data set of the circuit board controller of the automated robot.

[0013] In the second aspect of the present invention, a system for executing the method for monitoring abnormal operation of a circuit board controller is provided, including: an operation parameter collection unit, an operation parameter evaluation unit, an abnormal operation parameter response unit, an operation parameter prediction unit, a predicted operation parameter evaluation unit, a predicted risk operation parameter response unit, and a database.

[0014] The operating parameter acquisition unit is used to acquire various working parameters and various environmental parameters of the controller of the automated robot circuit board.

[0015] The operating parameter evaluation unit includes a working parameter evaluation module and an environmental parameter evaluation module.

[0016] The working parameter evaluation module is used to evaluate whether the various working parameters of the controller of the automated robot circuit board are abnormal.

[0017] The environmental parameter evaluation module is used to evaluate whether the various environmental parameters of the controller of the automated robot circuit board are abnormal.

[0018] The abnormal operating parameter response unit is used to process the various abnormal operating parameters of the controller of the automated robot circuit board.

[0019] The operating parameter prediction unit is used to predict the various working parameters and various environmental parameters of the controller of the automated robot circuit board.

[0020] The predicted operating parameter evaluation unit includes a predicted working parameter evaluation module and a predicted environmental parameter evaluation module.

[0021] The predicted working parameter evaluation module is used to evaluate whether the various predicted working parameters of the controller of the automated robot circuit board are abnormal.

[0022] The predicted environmental parameter evaluation module is used to evaluate whether the various predicted environmental parameters of the controller of the automated robot circuit board are abnormal.

[0023] The predicted risk operating parameter response unit is used to process the various predicted risk operating parameters of the controller of the automated robot circuit board.

[0024] The database is used to store the allowable ranges of the various working parameters of the controller of the automated robot circuit board and the allowable ranges of the various environmental parameters of the controller of the automated robot circuit board, and is used to store the historical various working parameters and the historical various environmental parameters of the controller of the automated robot circuit board.

[0025] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: First, the present invention uses a variety of high-precision sensors integrated on the circuit board. By utilizing real-time data acquisition and transmission technology, it can continuously monitor the operating parameters of the circuit board controller of the automated robot, including various internal operating parameters and external environment parameters. It can promptly detect any tiny abnormal changes and identify whether the factors affecting the abnormal operation of the circuit board controller of the automated robot are internal operating parameters or external environment parameters, facilitating the timely implementation of targeted response measures and improving the maintenance efficiency of the circuit board controller of the automated robot.

[0026] Second, the present invention makes efficient response measures for each abnormal operating parameter of the circuit board controller of the automated robot, can promptly eliminate the causes of each abnormal operating parameter of the circuit board controller of the automated robot, and can ensure the stability of automated robot production.

[0027] Third, the present invention applies data analysis technology. The system can not only detect current abnormalities but also predict future possible problems based on historical data. This forward-looking maintenance strategy can significantly reduce the incidence of sudden failures and effectively reduce maintenance costs and system downtime. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0029] Figure 1 It is a schematic flowchart of the method of the present invention.

[0030] Figure 2 It is a connection diagram of the system structure of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0031] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0032] For better understanding, the following explains the terms related to the present invention.

[0033] Operating parameters refer to the various operating parameters of the circuit board controller of the automated robot and the various environment parameters of the circuit board controller of the automated robot.

[0034] On-board temperature refers to the temperature of the circuit board controller of the automated robot in the operating state. The on-board temperature of the circuit board controller of the automated robot reflects whether the controller is working properly. If the on-board temperature of the circuit board controller of the automated robot is too high, it indicates that there is an abnormality in the operation of the circuit board controller of the automated robot.

[0035] On-board voltage refers to the operating voltage of the circuit board controller of the automated robot in the operating state. If the on-board voltage of the circuit board controller of the automated robot is too high, it will cause logic errors, affect the correct processing of signals and the reliability of data, and thus affect the operating state of the circuit board controller of the automated robot.

[0036] On-board current refers to the operating current of the circuit board controller of the automated robot in the operating state. If the on-board current of the circuit board controller of the automated robot is too high, it will cause components such as resistors and transistors in the circuit to overheat, and then be damaged and permanently fail, thus affecting the operating state of the circuit board controller of the automated robot.

[0037] Environmental magnetic field intensity refers to the magnetic field intensity in the environment in the operating state. When the environmental magnetic field intensity is too high, it will cause the electronic components of the circuit board controller of the automated robot to work unstably, resulting in excessive signal noise, signal distortion, data transmission errors, or abnormal processor behavior.

[0038] Environmental temperature refers to the temperature of the environment where the circuit board controller of the automated robot operates. An increase in environmental temperature will directly affect the thermal degradation of semiconductor components, capacitors, and other components on the circuit board controller of the automated robot, and will affect its service life and efficiency.

[0039] Environmental humidity refers to the humidity of the environment where the circuit board controller of the automated robot operates. An increase in environmental humidity will cause corrosion and oxidation of the metal components on the circuit board controller of the automated robot, damage the electrical conductivity of the metal, and cause poor circuit connection or short circuit.

[0040] Environmental dust concentration refers to the dust concentration in the environment where the circuit board controller of the automated robot operates. An excessively high dust concentration will reduce the heat dissipation efficiency of the circuit board controller of the automated robot, affect the normal operation and service life of the components. If the dust particles are conductive, it will cause a conductive path to form between different parts of the circuit board controller of the automated robot, resulting in abnormal current.

[0041] External damage refers to mechanical damage and component damage of the circuit board controller of the automated robot. Mechanical damage specifically refers to the situation where there are cracks in the circuit board controller of the automated robot, which will cause it to malfunction. Component damage specifically refers to the situation where the components of the circuit board controller of the automated robot are damaged or de-soldered, resulting in malfunction.

[0042] The LSTM long short-term memory network model refers to a special recurrent neural network (RNN) structure, mainly used to process and predict sequence data problems. In the present invention, it is used to predict the operating parameters and environmental parameters of the automated robot circuit board controller.

[0043] The welding solder joint refers to the component welding position of the automated robot circuit board controller. Checking whether the welding solder joints are consistent means checking whether the component welding positions of the automated robot circuit board controller are detached from the welding pads or shifted.

[0044] Embodiment 1

[0045] Refer to Figure 1 As shown, the first aspect of the present invention provides a method for monitoring abnormal operation of a circuit board controller. The method includes: S1. Collect the operating parameters of the automated robot circuit board controller: collect the operating parameters of the automated robot circuit board controller, construct a dataset of the operating parameters of the automated robot circuit board controller, collect the environmental parameters of the automated robot circuit board controller, and construct a dataset of the environmental parameters of the automated robot circuit board controller.

[0046] S2. Evaluate the operating parameters of the automated robot circuit board controller: evaluate whether the operating parameters of the automated robot circuit board controller are abnormal to obtain the abnormal operating parameters of the automated robot circuit board controller, evaluate whether the environmental parameters of the automated robot circuit board controller are abnormal to obtain the abnormal environmental parameters of the automated robot circuit board controller, and construct a dataset of abnormal operating parameters of the automated robot circuit board controller.

[0047] S3. Respond to the abnormal operating parameters of the automated robot circuit board controller: Based on the dataset of abnormal operating parameters of the automated robot circuit board controller, implement corresponding response measures.

[0048] S4. Obtain the predicted operating parameters of the automated robot circuit board controller: obtain the historical operating parameters of the automated robot circuit board controller to obtain the predicted operating parameters of the automated robot circuit board controller, construct a dataset of predicted operating parameters of the automated robot circuit board controller, obtain the historical environmental parameters of the automated robot circuit board controller to obtain the predicted environmental parameters of the automated robot circuit board controller, and construct a dataset of predicted environmental parameters of the automated robot circuit board controller.

[0049] S5. Predict the risk operating parameters of the automated robot circuit board controller: Based on the predicted working parameter dataset of the automated robot circuit board controller, obtain each predicted risk working parameter of the automated robot circuit board controller. Based on the predicted environmental parameter dataset of the automated robot circuit board controller, obtain each predicted risk environmental parameter of the automated robot circuit board controller, and construct a predicted risk operating parameter dataset of the automated robot circuit board controller.

[0050] S6. Respond to the predicted risk operating parameters of the automated robot circuit board controller: Based on the predicted risk operating parameter dataset of the automated robot circuit board controller, implement corresponding response measures.

[0051] In a specific embodiment of the present invention, the method for collecting the operating parameters of the automated robot circuit board controller is as follows: Through the temperature sensor integrated in the automated robot circuit board controller, obtain the on-board temperature of the automated robot circuit board controller, denoted as T.

[0052] Similarly, through the voltage sensor and Hall effect sensor integrated in the automated robot circuit board controller, obtain the on-board voltage U and on-board current I of the circuit board controller of the automated robot.

[0053] Through the above analysis, obtain the on-board temperature, on-board voltage, and on-board current of the automated robot circuit board controller, and obtain each working parameter of the automated robot circuit board controller.

[0054] Based on each working parameter of the automated robot circuit board controller, construct a working parameter dataset D of the automated robot circuit board controller.

[0055] It should be noted that in a specific embodiment, for example, each working parameter of the collected automated robot circuit board controller is T = 46 degrees Celsius, U = 6 volts, I = 1 ampere, and construct a working parameter dataset D of the circuit board controller = [T = 46, U = 6, I = 1].

[0056] Similarly, through each environmental acquisition sensor around the automated robot circuit board controller, obtain the environmental magnetic field intensity H, environmental temperature W, environmental humidity S, and environmental dust concentration C of the automated robot circuit board controller.

[0057] Through the above analysis, obtain each environmental parameter of the automated robot circuit board controller, and construct an environmental parameter dataset E of the automated robot circuit board controller.

[0058] It should be noted that in a specific embodiment, for example, the environmental parameters of the automated robot circuit board controller collected are H = 2 mT, W = 33 °C, S = 70%, C = 5 μg / m³, and an environmental parameter dataset E = [H = 2, W = 33, S = 70, C = 5] of the automated robot circuit board controller is constructed.

[0059] The present invention uses a variety of high-precision sensors integrated on the circuit board and utilizes real-time data acquisition and transmission technology to continuously monitor the operating parameters of the automated robot circuit board controller, including various internal operating parameters and external environmental parameters. It can promptly detect any tiny abnormal changes and identify whether the factors affecting the abnormal operation of the automated robot circuit board controller are internal operating parameters or external environmental parameters, facilitating the timely adoption of targeted response measures and improving the maintenance efficiency of the automated robot circuit board controller.

[0060] In a specific embodiment of the present invention, the method for evaluating the operating parameters of the automated robot circuit board controller is as follows: Based on the operating parameter dataset D of the automated robot circuit board controller, through the formula: The abnormal judgment value QD(k) of the k-th operating parameter of the automated robot circuit board controller is obtained. represents the allowable range of the k-th operating parameter of the automated robot circuit board controller extracted from the database, where k = 1, 2, 3, and k represents the serial number of the parameter in the operating parameter dataset of the automated robot circuit board controller.

[0061] If QD(k) = 0, it is determined that the k-th operating parameter of the automated robot circuit board controller is normal.

[0062] If QD(k) = 1, it is determined that the k-th operating parameter of the automated robot circuit board controller is abnormal, and this operating parameter of the automated robot circuit board controller is recorded as an abnormal operating parameter.

[0063] Through the above analysis method, the abnormal operating parameters of the automated robot circuit board controller are obtained, and an abnormal operating parameter dataset of the automated robot circuit board controller is constructed.

[0064] It should be noted that in a specific embodiment, for example, the allowable ranges of the operating parameters of the automated robot circuit board controller extracted from the database are Based on D = [T = 46, U = 6, I = 1], according to the formula It is calculated that QD(1) = 1, QD(2) = 1, QD(3) = 0. The on-board temperature and on-board voltage of the automated robot circuit board controller are recorded as abnormal operating parameters, and each abnormal operating parameter of the automated robot circuit board controller is obtained.

[0065] Similarly, based on the environmental parameter dataset E of the automated robot circuit board controller, each abnormal environmental parameter dataset of the automated robot circuit board controller is obtained.

[0066] It should be noted that in a specific embodiment, for example, the allowable ranges of each environmental parameter of the automated robot circuit board controller extracted from the database are Based on E = [H = 2, W = 33, S = 70, C = 5], similarly, each abnormal environmental parameter dataset of the automated robot circuit board controller is obtained.

[0067] In a specific embodiment of the present invention, the construction of the abnormal operation parameter dataset of the automated robot circuit board controller is specifically as follows: based on the abnormal operating parameter dataset of the automated robot circuit board controller The abnormal environmental parameter dataset of the automated robot circuit board controller Construct the abnormal operation parameter dataset A of the automated robot circuit board controller.

[0068] It should be noted that in a specific embodiment, for example, based on each abnormal operating parameter of the automated robot circuit board controller Each abnormal environmental parameter of the automated robot circuit board controller Construct the abnormal operation parameter dataset of the automated robot circuit board controller

[0069] In a specific embodiment of the present invention, for the implementation of corresponding response measures based on the abnormal operation parameter dataset of the automated robot circuit board controller, the specific method is as follows: the automated robot stops working, and abnormal operation parameters are extracted from the abnormal operation parameter dataset of the automated robot circuit board controller. If Then take the countermeasures for the abnormal working parameters of the automated robot circuit board controller. First, generate a maintenance work order for the abnormal working parameters of the automated robot circuit board controller and submit it to the corresponding maintenance personnel.

[0070] Extract the surface image of the automated robot circuit board controller through the imaging equipment, and check whether there is any appearance damage on the automated robot circuit board controller through computer image recognition and machine learning techniques.

[0071] If it is found that the surface of the automated robot circuit board controller is damaged, replace the automated robot circuit board controller in a timely manner and resume production.

[0072] If it is not found that the surface of the automated robot circuit board controller is damaged, the maintenance technician shall check and repair the electrical part of the automated robot circuit board controller.

[0073] It should be noted that in a specific embodiment, first, take the surface image of the automated robot circuit board controller and send it to the computer image recognition system. Then, segment the surface image of the automated robot circuit board controller to obtain multiple surface image slices, and compare them with the crack features stored in the system. If it is found that there are crack features in one or more surface image slices of the automated robot circuit board controller, it is determined that the surface of the automated robot circuit board controller is damaged; otherwise, proceed to the next step.

[0074] Based on the multiple surface image slices of the automated robot circuit board controller obtained, compare them with the characteristic surface image slices of the same model of automated robot circuit board controller stored in the system, and detect whether the component models at the corresponding surface image slice positions are the same and whether the welding solder joints are consistent. If it is found that the components of one or more surface image slices of the automated robot circuit board controller are different from the characteristic surface image slices and the positions of the welding solder joints are inconsistent, it is determined that the surface of the automated robot circuit board controller is damaged; otherwise, the maintenance technician shall check and repair the electrical part of the automated robot circuit board controller.

[0075] If Then take countermeasures for abnormal environmental parameters of the automated robot circuit board controller.

[0076] When It indicates that the environmental magnetic field intensity of the automated robot circuit board controller is abnormal, and a shielding cover is used around the automated robot circuit board controller to block external magnetic field interference.

[0077] When It indicates that the environmental temperature of the automated robot circuit board controller is abnormal, and the temperature is reduced by strengthening the heat dissipation system around the automated robot circuit board controller.

[0078] When It indicates that the environmental humidity of the automated robot circuit board controller is abnormal, and the humidity is reduced by strengthening the exhaust system around the automated robot circuit board controller.

[0079] When It indicates that the environmental dust concentration of the automated robot circuit board controller is abnormal. By strengthening the exhaust system around the automated robot circuit board controller and installing a dust-proof cover, the impact of dust concentration on the automated robot circuit board controller can be reduced.

[0080] Through the above method, corresponding processing is carried out for each abnormal parameter in the abnormal operation parameter data set of the automated robot circuit board controller.

[0081] The present invention makes efficient countermeasures for each abnormal operation parameter of the automated robot circuit board controller, can timely eliminate the causes of each abnormal operation parameter of the automated robot circuit board controller, and can ensure the stability of automated robot production.

[0082] In a specific embodiment of the present invention, the specific method for predicting the risk operation parameters of the automated robot circuit board controller is as follows: Extract the historical working parameters of the automated robot circuit board controller and the historical environmental parameters of the automated robot circuit board controller from the database, and respectively construct a working parameter LSTM long short-term memory network model of the automated robot circuit board controller and an environmental parameter LSTM long short-term memory network model of the automated robot circuit board controller.

[0083] Based on the working parameter LSTM long short-term memory network model of the automated robot circuit board controller, obtain the predicted working parameters of the automated robot circuit board controller, and construct a predicted working parameter data set of the automated robot circuit board controller.

[0084] It should be noted that in a specific embodiment, for example, the predicted working parameters of the automated robot circuit board controller are degrees Celsius, volts, amperes, and construct a predicted working parameter data set of the automated robot circuit board controller.

[0085] Similarly, obtain the predicted environmental parameters of the automated robot circuit board controller, and construct a predicted environmental parameter data set of the automated robot circuit board controller.

[0086] It should be noted that in a specific embodiment, for example, the predicted environmental parameters of the automated robot circuit board controller collected are millitesla, degrees Celsius, micrograms per cubic meter, and construct a predicted environmental parameter data set of the automated circuit board controller.

[0087] In a specific embodiment of the present invention, the method for constructing a prediction risk operation parameter dataset of an automated robot circuit board controller is as follows: Based on the prediction working parameter dataset of the automated robot circuit board controller Compare with the allowable range of the corresponding working parameters of the automated robot circuit board controller in the database to obtain the prediction risk working parameter dataset of the automated robot circuit board controller

[0088] It should be noted that in a specific embodiment, similarly, for example, extract the allowable range of each working parameter of the automated robot circuit board controller from the database, and based on the prediction working parameter dataset of the automated robot circuit board controller Obtain the prediction risk working parameter dataset of the automated robot circuit board controller

[0089] Similarly, obtain the prediction risk environment parameter dataset of the automated robot circuit board controller

[0090] It should also be noted that in a specific embodiment, similarly, based on the prediction environment parameter dataset of the automated robot circuit board controller Obtain the prediction risk parameter dataset of the automated robot circuit board controller

[0091] Based on the prediction risk working parameter dataset of the automated robot circuit board controller The prediction risk environment parameter dataset of the automated robot circuit board controller Construct the prediction risk operation parameter dataset B of the automated robot circuit board controller.

[0092] In a specific embodiment of the present invention, the method for implementing corresponding response measures based on the prediction risk operation parameter dataset of the automated robot circuit board controller is as follows: Extract the prediction risk operation parameters from the prediction risk operation parameter dataset of the automated robot circuit board controller. If Then trigger the abnormal response measures for the prediction risk working parameters of the automated robot circuit board controller.

[0093] It should be noted that in a specific embodiment, the abnormal response measures for the prediction risk working parameters of the automated robot circuit board controller are to collect the surface image of the automated robot circuit board controller through a camera device, and through computer image recognition and machine learning technologies, focus on checking whether there is any damage on the surface of the automated robot circuit board controller.

[0094] If Then, it triggers the countermeasures for abnormal predicted risk environment parameters of the automated robot circuit board controller.

[0095] It should be noted that, in a specific embodiment, the countermeasures for abnormal predicted risk environment parameters of the automated robot circuit board controller are as follows. When it indicates that the environmental magnetic field intensity of the automated robot circuit board controller is a predicted risk parameter. By installing a shielding cover, the influence of the environmental magnetic field intensity on the automated robot circuit board controller is eliminated.

[0096] When it indicates that the environmental temperature of the automated robot circuit board controller is a predicted risk parameter. By strengthening the heat dissipation system around the automated robot circuit board controller, the influence of the environmental temperature on the automated robot circuit board controller is eliminated.

[0097] When it indicates that the environmental humidity of the automated robot circuit board controller is a predicted risk parameter. By strengthening the exhaust system around the automated robot circuit board controller, the influence of the environmental humidity on the automated robot circuit board controller is eliminated.

[0098] When it indicates that the environmental dust concentration of the automated robot circuit board controller is a predicted risk parameter. By strengthening the exhaust system around the automated robot circuit board controller, the influence of the environmental dust concentration on the automated robot circuit board controller is eliminated.

[0099] The present invention applies data analysis technology. The system can not only detect current abnormalities but also predict future possible problems based on historical data. This forward-looking maintenance strategy can significantly reduce the incidence of sudden failures and effectively reduce maintenance costs and system downtime.

[0100] Embodiment 2

[0101] Referring to Figure 2 as shown, the second aspect of the present invention provides a system for a method of monitoring abnormal operation of a circuit board controller, including: an operating parameter acquisition unit, an operating parameter evaluation unit, an abnormal operating parameter response unit, an operating parameter prediction unit, a predicted operating parameter evaluation unit, a predicted risk operating parameter response unit, and a database.

[0102] The operating parameter acquisition unit is used to acquire various working parameters and various environmental parameters of the automated robot circuit board controller.

[0103] The operating parameter evaluation unit includes a working parameter evaluation module and an environmental parameter evaluation module.

[0104] The working parameter evaluation module is used to evaluate whether each working parameter of the circuit board controller of the automated robot is abnormal.

[0105] The environmental parameter evaluation module is used to evaluate whether each environmental parameter of the circuit board controller of the automated robot is abnormal.

[0106] The abnormal operation parameter response unit is used to process each abnormal operation parameter of the circuit board controller of the automated robot.

[0107] The operation parameter prediction unit is used to predict each working parameter and each environmental parameter of the circuit board controller of the automated robot.

[0108] The predicted operation parameter evaluation unit includes a predicted working parameter evaluation module and a predicted environmental parameter evaluation module.

[0109] The predicted working parameter evaluation module is used to evaluate whether each predicted working parameter of the circuit board controller of the automated robot is abnormal.

[0110] The predicted environmental parameter evaluation module is used to evaluate whether each predicted environmental parameter of the circuit board controller of the automated robot is abnormal.

[0111] The predicted risk operation parameter response unit is used to process each predicted risk operation parameter of the circuit board controller of the automated robot.

[0112] The database is used to store the allowable ranges of each working parameter of the circuit board controller of the automated robot and the allowable ranges of each environmental parameter of the circuit board controller of the automated robot, and is used to store the historical working parameters and historical environmental parameters of the circuit board controller of the automated robot.

[0113] It should be noted that in a specific embodiment, the operation parameter acquisition unit is connected to the operation parameter evaluation unit. In the operation parameter evaluation unit, the working parameter evaluation module is connected to the environmental parameter evaluation module. The operation parameter evaluation unit is connected to the abnormal operation parameter response unit. The operation parameter prediction unit is connected to the predicted operation parameter evaluation unit. In the predicted operation parameter evaluation unit, the predicted working parameter evaluation module is connected to the predicted environmental parameter evaluation module. The predicted operation parameter evaluation unit is connected to the predicted risk operation parameter response unit. The database is connected to the operation parameter evaluation unit and the predicted operation parameter evaluation unit.

[0114] The above content is only an example and explanation of the concept of the present invention. Those skilled in the art of this technology can make various modifications or supplements to the described specific embodiments or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they should fall within the protection scope of the present invention.

Claims

1. A method for monitoring abnormal operation of a circuit board controller, characterized in that: The method comprises: S1. Collecting operating parameters of the automated robot circuit board controller: Collecting various working parameters of the automated robot circuit board controller, constructing a working parameter data set of the automated robot circuit board controller, collecting various environmental parameters of the automated robot circuit board controller, and constructing an environmental parameter data set of the automated robot circuit board controller; S2. Evaluate the operating parameters of the automated robot circuit board controller: evaluate whether the operating parameters of the automated robot circuit board controller are abnormal, obtain the abnormal operating parameters of the automated robot circuit board controller, evaluate whether the environmental parameters of the automated robot circuit board controller are abnormal, obtain the abnormal environmental parameters of the automated robot circuit board controller, and construct an abnormal operating parameter data set of the automated robot circuit board controller; S3. Response to abnormal operating parameters of the automated robot circuit board controller: Based on the abnormal operating parameter data set of the automated robot circuit board controller, implement corresponding response measures; S4. Obtaining predicted operating parameters of the automated robot circuit board controller: obtaining historical operating parameters of the automated robot circuit board controller, obtaining predicted operating parameters of the automated robot circuit board controller, constructing a predicted operating parameter data set of the automated robot circuit board controller, obtaining historical environmental parameters of the automated robot circuit board controller, obtaining predicted environmental parameters of the automated robot circuit board controller, and constructing a predicted environmental parameter data set of the automated robot circuit board controller; S5. Predicting the risk operating parameters of the automated robot circuit board controller: based on the predicted working parameter data set of the automated robot circuit board controller, obtaining each predicted risk working parameter of the automated robot circuit board controller, based on the predicted environmental parameter data set of the automated robot circuit board controller, obtaining each predicted risk environmental parameter of the automated robot circuit board controller, and constructing a predicted risk operating parameter data set of the automated robot circuit board controller; S6. Responding to the predicted risk operating parameters of the automated robot circuit board controller: Based on the predicted risk operating parameter data set of the automated robot circuit board controller, implementing corresponding response measures; The specific method for predicting the risk operation parameters of the automated robot circuit board controller is as follows: extracting historical working parameters of the automated robot circuit board controller and historical environmental parameters of the automated robot circuit board controller from a database, and constructing an LSTM long short-term memory network model of working parameters of the automated robot circuit board controller and an LSTM long short-term memory network model of environmental parameters of the automated robot circuit board controller respectively; Based on the working parameter LSTM long short-term memory network model of the automated robot circuit board controller, the predicted working parameters of the automated robot circuit board controller are obtained, and the predicted working parameter dataset of the automated robot circuit board controller is constructed. Similarly, the predicted environmental parameters of the automated robot circuit board controller are obtained, and the predicted environmental parameter data set of the automated robot circuit board controller is constructed. The specific method of constructing the predicted risk operation parameter data set of the automated robot circuit board controller is as follows: based on the predicted working parameter data set of the automated robot circuit board controller Compare with the allowable interval of the corresponding working parameters of the automated robot circuit board controller in the database to obtain the predicted risk working parameter data set of the automated robot circuit board controller Similarly, the predicted risk environment parameter data set of the automated robot circuit board controller is obtained A dataset of predicted risky work parameters for automated robot circuit board controllers Predictive Risk Environment Parameters Dataset for Automated Robot Circuit Board Controllers Construct a predicted risk operating parameter dataset B of the automated robot circuit board controller; The corresponding response measures are implemented based on the predicted risk operation parameter data set of the automated robot circuit board controller, and the specific method is: extracting the predicted risk operation parameters from the predicted risk operation parameter data set of the automated robot circuit board controller, if This triggers the abnormal response measures for the predicted risk working parameters of the automated robot circuit board controller; like This triggers the abnormal response measures of the predicted risk environment parameters of the automated robot circuit board controller.

2. The method for monitoring abnormal operation of a circuit board controller according to claim 1, characterized in that: The specific method of collecting the operating parameters of the automatic robot circuit board controller is as follows: The temperature of the circuit board controller of the automated robot is obtained by using a temperature sensor integrated in the circuit board controller of the automated robot, which is recorded as T. Similarly, the onboard voltage U and onboard current I of the circuit board controller of the automated robot are obtained through the voltage sensor and the Hall effect sensor integrated in the circuit board controller of the automated robot; Through the above analysis, the onboard temperature, onboard voltage, and onboard current of the automated robot circuit board controller are obtained, and the various working parameters of the automated robot circuit board controller are obtained; Based on the working parameters of the automatic robot circuit board controller, a working parameter data set D of the automatic robot circuit board controller is constructed; Similarly, by collecting sensors in various environments around the automated robot circuit board controller, the environmental magnetic field intensity H, environmental temperature W, environmental humidity S, and environmental dust concentration C of the automated robot circuit board controller are obtained; Through the above analysis, the environmental parameters of the automated robot circuit board controller are obtained, and an environmental parameter data set E of the automated robot circuit board controller is constructed.

3. The method for monitoring abnormal operation of a circuit board controller according to claim 2, characterized in that: The specific method for evaluating the operating parameters of the automated robot circuit board controller is as follows: Based on the working parameter data set D of the automated robot circuit board controller, the formula is: Get the abnormal judgment value QD(k) of the kth working parameter of the automatic robot circuit board controller, [D(k) - ,D(k) + ] represents the allowable interval of the kth working parameter of the automatic robot circuit board controller extracted from the database, k=1,2,3, k represents the number of the parameter in the working parameter data set of the automatic robot circuit board controller; If QD(k)=0, it is determined that the kth working parameter of the automated robot circuit board controller is normal; If QD(k)=1, it is determined that the kth operating parameter of the automatic robot circuit board controller is abnormal, and the operating parameter of the automatic robot circuit board controller is recorded as an abnormal operating parameter; Through the above analysis method, the abnormal working parameters of the automated robot circuit board controller are obtained, and the abnormal working parameter data set of the automated robot circuit board controller is constructed. Similarly, based on the environmental parameter dataset E of the automated robot circuit board controller, the abnormal environmental parameter datasets of the automated robot circuit board controller are obtained.

4. The method for monitoring abnormal operation of a circuit board controller according to claim 3, characterized in that: The abnormal operation parameter data set of the automated robot circuit board controller is constructed as follows: Abnormal working parameter dataset based on automated robot circuit board controller Abnormal environmental parameter dataset for automated robot circuit board controller Construct abnormal operating parameter dataset A of the automated robot circuit board controller.

5. The method for monitoring abnormal operation of a circuit board controller according to claim 4, characterized in that: The specific method of implementing corresponding response measures based on the abnormal operation parameter data set of the automated robot circuit board controller is as follows: The automated robot stops working, and the abnormal operation parameters are extracted from the abnormal operation parameter data set of the automated robot circuit board controller. Then, measures to deal with abnormal working parameters of the automated robot circuit board controller are taken, and first, a maintenance work order for abnormal working parameters of the automated robot circuit board controller is generated and submitted to the corresponding maintenance personnel; The surface image of the automated robot circuit board controller is extracted through camera equipment, and computer image recognition and machine learning technology are used to check whether the automated robot circuit board controller has surface damage; If the circuit board controller of the automated robot is found to be damaged on the outside, replace the circuit board controller of the automated robot in time and resume production; If no external damage is found on the circuit board controller of the automated robot, a maintenance technician will inspect and repair the electrical system of the circuit board controller of the automated robot; like Then take measures to deal with abnormal environmental parameters of the automated robot circuit board controller; when This means that the environmental magnetic field strength of the automated robot circuit board controller is abnormal. External magnetic field interference can be blocked by using a shielding cover around the automated robot circuit board controller. when This means that the ambient temperature of the automated robot circuit board controller is abnormal. The temperature can be lowered by strengthening the heat dissipation system around the automated robot circuit board controller. when This means that the ambient humidity of the automated robot circuit board controller is abnormal. The humidity can be reduced by strengthening the exhaust system around the automated robot circuit board controller. when This means that the ambient dust concentration of the automated robot circuit board controller is abnormal. The effect of dust concentration on the automated robot circuit board controller can be reduced by strengthening the exhaust system around the automated robot circuit board controller and installing a dust cover. Through the above method, corresponding processing is achieved for each abnormal parameter in the abnormal operation parameter data set of the automated robot circuit board controller.

6. A system for executing the circuit board controller operation abnormality monitoring method according to claim 5, characterized in that: include: An operating parameter acquisition unit is used to collect various operating parameters and environmental parameters of the circuit board controller of the automated robot; An operation parameter evaluation unit, including a working parameter evaluation module and an environmental parameter evaluation module; A working parameter evaluation module is used to evaluate whether the working parameters of the circuit board controller of the automated robot are abnormal; An environmental parameter evaluation module is used to evaluate whether the environmental parameters of the automated robot circuit board controller are abnormal; An abnormal operation parameter response unit, used for processing various abnormal operation parameters of the circuit board controller of the automated robot; An operating parameter prediction unit is used to predict various operating parameters and environmental parameters of the circuit board controller of the automated robot; A prediction operation parameter evaluation unit, including a prediction work parameter evaluation module and a prediction environment parameter evaluation module; A predicted working parameter evaluation module is used to evaluate whether each predicted working parameter of the automated robot circuit board controller is abnormal; A predicted environmental parameter evaluation module is used to evaluate whether each predicted environmental parameter of the automated robot circuit board controller is abnormal; The predicted risk operation parameter response unit is used to process various predicted risk operation parameters of the automated robot circuit board controller.

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