Operation abnormity monitoring method and system for circuit board controller

Abstract

The invention discloses an operation abnormity monitoring method and system for a circuit board controller, and relates to the technical field of circuit board controller monitoring, and the method comprises the steps: S1, collecting operation parameters of an automatic robot circuit board controller; s2, operating parameters of the automatic robot circuit board controller are evaluated; s3, responding to abnormal operation parameters of a circuit board controller of the automatic robot; s4, acquiring predicted operation parameters of the circuit board controller of the automatic robot; s5, evaluating predicted operation parameters of the circuit board controller of the automatic robot; and S6, responding to the predicted risk operation parameters of the automatic robot circuit board controller. A data analysis technology is applied, the system not only can detect current abnormity, but also can predict possible problems in the future based on historical data, the prospective maintenance strategy can remarkably reduce the occurrence rate of sudden faults, and the maintenance cost and the system downtime are effectively reduced.

Description

Technical Field

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

[0002] With the development of technologies such as artificial intelligence and machine learning, automated robots are able to work in more complex and changing environments, greatly improving the production efficiency of intelligent manufacturing production lines while ensuring high standards of product quality. It is particularly important for automated robot circuit board controllers to maintain their stable operation. Any abnormal situation in automated robot circuit board controllers may trigger overall system failures and may cause serious financial damage and safety hazards. Therefore, the development of efficient operation anomaly detection methods and systems has become an urgent problem in the industry.

[0003] The existing technology for monitoring the 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 method of the circuit board controller of the automated robot relies on periodic inspections or repairs after a fault occurs, and relies on regular maintenance inspections rather than continuous monitoring, resulting in the early stages of fault development being missed and the optimal maintenance time being unable to be achieved, causing the automated robot circuit board controller to be more seriously damaged and the repair cost to be higher.

[0004] Second, the existing monitoring method of the automated robot circuit board controller ignores the various operating parameters of historical monitoring, fails to fully utilize the collected data for in-depth analysis, and lacks data analysis capabilities, resulting in the inability to obtain the predicted operating parameters in advance based on the historical operating parameters to conduct evaluations to avoid future problems. It cannot effectively ensure that the automated robot circuit board controller maintains stable operation, posing certain safety hazards to the industry's production.

[0005] Third, the existing technology ignores the factors that affect the normal operation of the automated robot circuit board controller, including internal working parameters and external environmental parameters. As a result, when the automated robot circuit board controller operates abnormally, it is impossible to immediately determine the cause of the abnormal operation of the automated robot circuit board controller, resulting in the inability to perform timely and targeted repairs, reducing maintenance efficiency and the stability of corporate production. Summary of the invention

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

[0007] According to a first aspect of the present invention, a method for monitoring the operation abnormality of a circuit board controller is provided, the method comprising: S1. collecting the operation parameters of an 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.

[0008] S2. Evaluate the operating parameters of the automated robot circuit board controller: evaluate whether the various working parameters of the automated robot circuit board controller are abnormal, obtain the various abnormal working parameters of the automated robot circuit board controller, evaluate whether the various environmental parameters of the automated robot circuit board controller are abnormal, obtain the various 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.

[0009] S3. Respond 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.

[0010] S4. Obtain the predicted operating parameters of the automated robot circuit board controller: obtain the historical working parameters of the automated robot circuit board controller, obtain the predicted working parameters of the automated robot circuit board controller, construct a predicted working parameter data set of the automated robot circuit board controller, obtain the historical environmental parameters of the automated robot circuit board controller, 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.

[0011] S5. Predict 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, obtain the predicted risk working parameters of the automated robot circuit board controller; based on the predicted environmental parameter data set of the automated robot circuit board controller, obtain the predicted risk environmental parameters of the automated robot circuit board controller, and construct a predicted risk operating parameter data set of the automated robot circuit board controller.

[0012] S6. Respond 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, implement corresponding response measures.

[0013] In a second aspect of the present invention, a system is provided for executing an operation abnormality monitoring method of a circuit board controller, comprising: an operation parameter acquisition 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 collect various working parameters and environmental parameters of the automated robot circuit board controller.

[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 working parameters of the automated robot circuit board controller are abnormal.

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

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

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

[0020] The predicted operation 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 predicted working parameters of the automated robot circuit board controller are abnormal.

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

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

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

[0025] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: 1. The present invention adopts 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 internal working parameters and external environmental parameters. It can promptly detect any minor abnormal changes and reflect whether the factors affecting the abnormal operation of the automated robot circuit board controller are internal working parameters or external environmental parameters, so as to facilitate timely and targeted response measures and improve the maintenance efficiency of the automated robot circuit board controller.

[0026] 2. The present invention makes efficient response measures for various abnormal operating parameters of the automated robot circuit board controller, can timely eliminate the causes of various abnormal operating parameters of the automated robot circuit board controller, and can ensure the stability of automated robot production.

[0027] 3. The present invention applies data analysis technology. The system can not only detect current anomalies, but also predict possible problems in the future 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 embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. 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 paying creative work.

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

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

[0031] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions 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.

[0032] For better understanding, the terms involved in the present invention are explained below.

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

[0034] The onboard temperature refers to the temperature of the automated robot circuit board controller in the running state. The onboard temperature of the automated robot circuit board controller reflects whether the controller is working normally. If the onboard temperature of the automated robot circuit board controller is too high, it means that there is an abnormality in the operation of the automated robot circuit board controller.

[0035] Onboard voltage refers to the working voltage of the automated robot circuit board controller when it is running. If the onboard voltage of the automated robot circuit board controller is too high, it will cause logic errors, affect the correct processing of signals and the reliability of data, and thus affect the running state of the automated robot circuit board controller.

[0036] Onboard current refers to the working current of the automated robot circuit board controller in operation. If the onboard current of the automated robot circuit board controller is too high, it will cause resistors, transistors and other components in the circuit to overheat, and then be damaged and fail permanently, thus affecting the operation of the automated robot circuit board controller.

[0037] Environmental magnetic field strength refers to the situation where the magnetic field strength in the environment is too high during operation, which will cause the electronic components of the automated robot circuit board controller to work unstably, resulting in excessive signal noise, signal distortion, data transmission errors or abnormal processor behavior.

[0038] Ambient temperature refers to the temperature of the environment in which the automated robot circuit board controller operates. The increase in ambient temperature will directly affect the thermal decay of semiconductor components, capacitors and other components on the automated robot circuit board controller, shortening its life and efficiency.

[0039] Ambient humidity refers to the humidity of the environment in which the automated robot circuit board controller operates. Increased ambient humidity causes corrosion and oxidation of metal parts on the automated robot circuit board controller, destroying the metal's conductive properties and causing poor circuit connections or short circuits.

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

[0041] Appearance damage refers to mechanical damage and component damage of the automated robot circuit board controller. Mechanical damage specifically refers to cracks in the automated robot circuit board controller, which can cause it to not work properly. Component damage specifically refers to damage and desoldering of components in the automated robot circuit board controller, which can cause it to not work properly.

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

[0043] Welding solder joints refer to the soldering positions of components on the automated robot circuit board controller. Checking whether the soldering solder joints are consistent refers to checking whether the soldering positions of components on the automated robot circuit board controller are detached from the soldering pad or offset.

[0044] Embodiment 1

[0045] Reference Figure 1 As shown, the first aspect of the present invention provides a method for monitoring the operation abnormality of a circuit board controller, the method comprising: S1. Collecting the operation 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.

[0046] S2. Evaluate the operating parameters of the automated robot circuit board controller: evaluate whether the various working parameters of the automated robot circuit board controller are abnormal, obtain the various abnormal working parameters of the automated robot circuit board controller, evaluate whether the various environmental parameters of the automated robot circuit board controller are abnormal, obtain the various 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.

[0047] S3. Respond 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.

[0048] S4. Obtain the predicted operating parameters of the automated robot circuit board controller: obtain the historical working parameters of the automated robot circuit board controller, obtain the predicted working parameters of the automated robot circuit board controller, construct a predicted working parameter data set of the automated robot circuit board controller, obtain the historical environmental parameters of the automated robot circuit board controller, 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.

[0049] S5. Predict 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, obtain the predicted risk working parameters of the automated robot circuit board controller; based on the predicted environmental parameter data set of the automated robot circuit board controller, obtain the predicted risk environmental parameters of the automated robot circuit board controller, and construct a predicted risk operating parameter data set 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 data set of the automated robot circuit board controller, implement corresponding response measures.

[0051] In a specific embodiment of the present invention, the operating parameters of the automated robot circuit board controller are collected by a specific method as follows: obtaining the onboard temperature of the automated robot circuit board controller through a temperature sensor integrated in the automated robot circuit board controller, which is recorded as T.

[0052] 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.

[0053] 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.

[0054] Based on the working parameters of the automated robot circuit board controller, a working parameter data set D of the automated robot circuit board controller is constructed.

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

[0056] Similarly, by collecting sensors in various environments around the automated robot circuit board controller, the environmental magnetic field strength H, ambient temperature W, ambient humidity S, and ambient dust concentration C of the automated robot circuit board controller are obtained.

[0057] 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.

[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 millitesla, W = 33 degrees Celsius, S = 70%, C = 5 micrograms per cubic meter, and an environmental parameter data set E = [H = 2, W = 33, S = 70, C = 5] for the automated robot circuit board controller is constructed.

[0059] The present invention adopts 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 internal working parameters and external environmental parameters. It can promptly detect any slight abnormal changes and reflect whether the factors affecting the abnormal operation of the automated robot circuit board controller are internal working parameters or external environmental parameters, so as to facilitate timely and targeted response measures and improve the maintenance efficiency of the automated robot circuit board controller.

[0060] In a specific embodiment of the present invention, the specific method for evaluating the operating parameters of the automated robot circuit board controller is: based on the working parameter data set D of the automated robot circuit board controller, by formula: Get the abnormal judgment value QD(k) of the kth working parameter of the automatic robot circuit board controller, It represents the allowable interval of the kth working parameter of the automatic robot circuit board controller extracted from the database, k=1,2,3, and k represents the number of the parameter in the working parameter data set of the automatic robot circuit board controller.

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

[0062] If QD(k)=1, it is determined that the kth working parameter of the automatic robot circuit board controller is abnormal, and the working parameter of the automatic robot circuit board controller is recorded as an abnormal working parameter.

[0063] 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.

[0064] It should be noted that, in a specific embodiment, for example, the allowable range of each working parameter of the automatic robot circuit board controller is extracted from the database as follows: 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, and the onboard temperature and onboard voltage of the automatic robot circuit board controller are recorded as abnormal working parameters, and the abnormal working parameters of the automatic robot circuit board controller are obtained.

[0065] 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.

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

[0067] In a specific embodiment of the present invention, the abnormal operating parameter data set of the automated robot circuit board controller is constructed, which is specifically: based on the abnormal operating parameter data set of the 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.

[0068] It should be noted that, in a specific embodiment, for example, various abnormal operating parameters of the circuit board controller of the automated robot Abnormal environmental parameters of automated robot circuit board controller Constructing a dataset of abnormal operating parameters of an automated robot circuit board controller

[0069] In a specific embodiment of the present invention, the abnormal operation parameter data set based on the circuit board controller of the automated robot is used to implement corresponding response measures, and the specific method is as follows: the automated robot stops working, and the abnormal operation parameters are extracted from the abnormal operation parameter data set of the circuit board controller of the automated robot. If Then, measures are taken to deal with the abnormal working parameters of the automated robot circuit board controller. First, a maintenance work order for the abnormal working parameters of the automated robot circuit board controller is generated and submitted to the corresponding maintenance personnel.

[0070] 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 there is any surface damage on the automated robot circuit board controller.

[0071] If the automated robot circuit board controller is found to have external damage, replace the automated robot circuit board controller in time to resume production.

[0072] If no external damage is found on the automated robot circuit board controller, a maintenance technician will inspect and repair the electrical system of the automated robot circuit board controller.

[0073] It should be noted that, in a specific embodiment, a surface image of the automated robot circuit board controller is first captured and sent to a computer image recognition system, and then the surface image of the automated robot circuit board controller is segmented to obtain multiple surface image slices, which are compared with the crack features stored in the system. If one or more surface image slices of the automated robot circuit board controller are found to have crack features, then it is determined that the automated robot circuit board controller has external damage, otherwise the process proceeds to the next step.

[0074] Based on the multiple surface image slices of the automated robot circuit board controller obtained, they are compared with the characteristic surface image slices of the automated robot circuit board controller of the same model stored in the system to 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 welding solder joint positions are inconsistent, it is determined that the automated robot circuit board controller has external damage. Otherwise, the electrical system of the automated robot circuit board controller will be inspected and repaired by maintenance technicians.

[0075] like Then take measures to deal with abnormal environmental parameters of the automated robot circuit board controller.

[0076] when This means that the environmental magnetic field strength of the automation robot circuit board controller is abnormal. External magnetic field interference can be blocked by using a shielding cover around the automation robot circuit board controller.

[0077] when This means that the ambient temperature of the automated robot circuit board controller is abnormal, and the temperature can be lowered by strengthening the heat dissipation system around the automated robot circuit board controller.

[0078] when This means that the ambient humidity of the automated robot circuit board controller is abnormal, and the humidity can be reduced by strengthening the exhaust system around the automated robot circuit board controller.

[0079] when This means that the environmental dust concentration of the automated robot circuit board controller is abnormal. The impact 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.

[0080] 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.

[0081] The present invention makes efficient response measures for various abnormal operating parameters of the automated robot circuit board controller, can timely eliminate the causes of various abnormal operating parameters 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 operating parameters of the automated robot circuit board controller is: extracting the historical working parameters of the automated robot circuit board controller and the historical environmental parameters of the automated robot circuit board controller from a database, and respectively constructing an LSTM long short-term memory network model of the working parameters of the automated robot circuit board controller and an LSTM long short-term memory network model of the environmental parameters 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, 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.

[0084] It should be noted that, in a specific embodiment, for example, the predicted operating parameters of the automated robot circuit board controller are obtained as follows: Celsius, volt, Ampere, building a dataset of predictive operating parameters for automated robot circuit board controllers

[0085] 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.

[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, Celsius, Micrograms per cubic meter, building a dataset of predicted environmental parameters for automated circuit board controllers

[0087] In a specific embodiment of the present invention, the method for constructing a predicted risk operating parameter data set of an automated robot circuit board controller is as follows: based on a predicted operating parameter data set of an 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

[0088] It should be noted that, in a specific embodiment, as above, for example, the allowable range of each working parameter of the automated robot circuit board controller is extracted from the database, based on the predicted working parameter data set of the automated robot circuit board controller Obtain the predicted risk working parameter dataset of the automated robot circuit board controller

[0089] Similarly, the predicted risk environment parameter data set of the automated robot circuit board controller is obtained

[0090] It should also be noted that in a specific embodiment, as above, the predicted environmental parameter data set based on the automated robot circuit board controller Get the predicted risk parameter dataset of the automated robot circuit board controller

[0091] 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 dataset B of predicted risk operating parameters for automated robot circuit board controllers.

[0092] In a specific embodiment of the present invention, 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 predicted risk working parameter abnormality response measures of the automated robot circuit board controller.

[0093] It should be noted that, in a specific embodiment, the countermeasures for the predicted risk abnormal working parameters of the automated robot circuit board controller are to capture the surface image of the automated robot circuit board controller by means of a camera equipment, and to focus on checking whether the automated robot circuit board controller has any external damage through computer image recognition and machine learning technology.

[0094] like This triggers the abnormal response measures of the predicted risk environment parameters of the automated robot circuit board controller.

[0095] It should be noted that, in a specific embodiment, the abnormal response measures for the predicted risk environment parameters of the automated robot circuit board controller are: This means that the environmental magnetic field strength of the automated robot circuit board controller is a predicted risk parameter. By installing a shielding cover, the influence of the environmental magnetic field strength on the automated robot circuit board controller can be eliminated.

[0096] when This means that the ambient 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 ambient temperature on the automated robot circuit board controller can be eliminated.

[0097] when This means that the ambient 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 ambient humidity on the automated robot circuit board controller can be eliminated.

[0098] when This means 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 can be eliminated.

[0099] The present invention applies data analysis technology, and the system can not only detect current anomalies, but also predict possible problems in the future 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] Reference Figure 2 As shown, the second aspect of the present invention provides a system for an operation abnormality monitoring method of a circuit board controller, comprising: an operation parameter acquisition 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.

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

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

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

[0107] The operating parameter prediction unit is used to predict various operating parameters and environmental parameters of the automated robot circuit board controller.

[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 the predicted working parameters of the automated robot circuit board controller are abnormal.

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

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

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

[0113] It should be noted that, in a specific embodiment, the operating parameter acquisition unit is connected to the operating parameter evaluation unit, in the operating parameter evaluation unit, the working parameter evaluation module is connected to the environmental parameter evaluation module, the operating parameter evaluation unit is connected to the abnormal operating parameter response unit, the operating parameter prediction unit is connected to the unit for predicting operating parameter evaluation, in the predictive operating parameter evaluation unit, the predictive working parameter evaluation module is connected to the predictive environmental parameter evaluation module, the predictive operating parameter evaluation unit is connected to the predictive risk operating parameter response unit, and the database is connected to the operating parameter evaluation unit and the predictive operating parameter evaluation unit.

[0114] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they shall all 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. Respond 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.

2. The method for monitoring abnormal operation of a circuit board controller according to claim 1, characterized in that: The method further comprises: 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. Respond 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, implement corresponding response measures.

3. 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.

4. The method for monitoring abnormal operation of a circuit board controller according to claim 3, 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.

5. The method for monitoring abnormal operation of a circuit board controller according to claim 4, 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.

6. The method for monitoring abnormal operation of a circuit board controller according to claim 5, 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.

7. The method for monitoring abnormal operation of a circuit board controller according to claim 2, characterized in that: The specific method of predicting the risk operating parameters of the automated robot circuit board controller is as follows: Extract historical working parameters and environmental parameters of the automated robot circuit board controller from the database, and construct an LSTM long short-term memory network model of working parameters 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.

8. The method for monitoring abnormal operation of a circuit board controller according to claim 7, characterized in that: The specific method of constructing the predicted risk operation parameter data set of the automated robot circuit board controller is as follows: Predictive operating parameter dataset for 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 dataset B of predicted risk operating parameters for automated robot circuit board controllers.

9. The method for monitoring abnormal operation of a circuit board controller according to claim 8, characterized in that: The specific method of implementing corresponding response measures based on the predicted risk operation parameter data set of the automated robot circuit board controller is as follows: Extract the predicted risk operation parameters from the predicted risk operation parameter dataset of the automated robot circuit board controller. 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.

10. A system for executing the circuit board controller operation abnormality monitoring method according to claims 1-9, 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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