Fault self-checking and error-reporting system for robot

Abstract

The invention discloses a fault self-checking and error-reporting system for a robot, and relates to the technical field of computer software, and the fault self-checking and error-reporting system comprises a power electrical detection module, a physical mechanical detection module, a software detection module, an ethical detection module and a fault feedback module. The power electrical detection module is used for detecting short circuit and overload fault conditions in a robot power electrical system; the physical mechanical detection module is used for detecting the fault condition of physical hardware, and the physical hardware comprises but is not limited to a motor, a sensor and electronic skin. According to the fault self-checking and error-reporting system for the robot, a plurality of modules are integrated, so that the operation condition of each component of the robot can be comprehensively and quickly detected and reflected, the fault detection and diagnosis efficiency is remarkably improved, maintenance personnel can quickly position and solve the fault problem, and the fault detection and diagnosis efficiency is improved. The maintenance cost and the maintenance difficulty are reduced, and the running state of the robot can be monitored in real time.

Description

Technical Field

[0001] The present invention relates to the technical field of computer software, and in particular to a fault self-checking and error reporting system for a robot. Background Art

[0002] With the advancement of science and technology and the development of intelligence, robots are increasingly used in homes and factories. These robots can not only perform various complex tasks, such as housework cleaning, child care, industrial production assistance, etc., but also greatly improve life and work efficiency. However, robots also face a series of challenges in actual use, the most prominent of which is the difficulty in carrying due to their heavy weight.

[0003] In a home environment, due to space limitations and the limited strength of the residents, when a robot breaks down, it is particularly inconvenient to move it to a professional repair shop for repair. This not only increases the burden on users, but may also cause the robot to be unable to resume normal operation in time due to delayed repairs, thereby affecting the user's daily life or production efficiency. Therefore, repairing the robot at the place where the failure occurred, that is, the user's home or factory site, has become a key means to solve this problem. However, as a highly integrated intelligent device, the robot has a complex internal structure and contains numerous sensors, actuators, controllers and complex software systems. This makes maintenance personnel face huge challenges when performing on-site maintenance, especially when professional testing instruments and spare parts are needed for troubleshooting and repair. Since carrying and preparing all possible testing instruments and spare parts is neither realistic nor economical, maintenance personnel often find it difficult to quickly and accurately locate and solve all possible fault problems on site. In this regard, we propose a fault self-detection and error reporting system for robots. Summary of the invention

[0004] In order to solve the above technical problems, a fault self-detection and error reporting system for a robot is provided. This technical solution solves the above problems.

[0005] In order to achieve the above purpose, the technical solution adopted by the present invention is:

[0006] A fault self-checking and error reporting system for a robot, the fault self-checking and error reporting system comprising: an electric power detection module, a physical mechanical detection module, a software detection module, an ethics detection module and a fault feedback module;

[0007] The power and electrical detection module is used to detect short circuit and overload faults in the robot's power and electrical system;

[0008] The physical mechanical detection module is used to detect the fault condition of the physical hardware, and the physical hardware includes: a motor, a sensor and an electronic skin;

[0009] The software detection module is used to detect the failures of each independent software and integrate them into one module for unified management;

[0010] The ethics detection module is used to generate commands for AI chips and conduct ethical reviews, as well as conduct ethical and virus reviews for each system software upgrade, and improve its own functions with social ethics research;

[0011] The fault feedback module is used to integrate the fault reports of each individual component, differentiate the faults according to their severity, take corresponding measures according to the severity, and provide feedback on the maintenance status, upkeep and functional status of each component of the robot to the manufacturer and the cloud and terminal of the maintenance point through local voice and display information.

[0012] Preferably, the power electrical detection module includes: a current detection unit, a voltage detection unit, an insulation detection unit and a power supply detection unit;

[0013] The current detection unit is used to monitor the current size in the robot's power and electrical system in real time and capture current abnormalities;

[0014] The voltage detection unit is used to detect the voltage of each part of the power electrical system and capture voltage anomalies;

[0015] The insulation test unit is used to check the insulation performance of wires and electronic components in the power and electrical system;

[0016] The power detection unit is used to measure the output power of the power supply, detect whether the power supply meets the requirements of the robot operation, and detect overload faults in time.

[0017] Preferably, the method for the current detection unit, the voltage detection unit, the insulation detection unit and the power detection unit to identify abnormalities and faults is:

[0018] The current detection unit installs current sensors at key locations of the power and electrical system. Based on the current sensors, current data is collected in real time and transmitted to the current detection unit for analysis. The collected current data is compared with the preset normal current range. If the current exceeds the normal range, it is judged as an abnormal current situation. The normal current range is obtained based on the factory information of the robot.

[0019] The voltage detection unit installs voltage sensors at different nodes of the power and electrical system to detect the voltage of each part, and transmits the data to the current detection unit to analyze the collected voltage data and compare it with the preset normal voltage range. If the voltage exceeds the normal range, it is judged as an abnormal voltage situation. The normal voltage range is obtained according to the factory information of the robot;

[0020] The insulation detection unit uses an insulation resistance tester connected to the electronic components in the power electrical system. The tester applies a certain voltage, measures the current passing through the object under test, and calculates the insulation resistance value. The calculation formula for the insulation resistance value is:

[0021] R=U / I

[0022] In the formula, R represents the insulation resistance value, U represents the applied voltage value, and I represents the measured current value;

[0023] The calculated insulation resistance value is compared with the preset insulation resistance standard. If the insulation resistance value is lower than the standard value, it is judged that the insulation performance is poor;

[0024] The power detection unit calculates power by measuring voltage and current. The power sensor collects power data in real time and transmits it to the power detection unit. The power detection unit compares the detected power value with the power requirement of the robot under different working conditions. If the power is insufficient or overloaded, it is judged as an abnormal power situation.

[0025] Preferably, the physical mechanical detection module includes: a motor detection unit, a sensor detection unit, an electronic skin detection unit and an electronic circuit and chip detection unit;

[0026] The motor detection unit is used to detect the running state of the motor, which includes: speed, torque and temperature, and to determine whether the motor has a fault by monitoring the running state;

[0027] The sensor detection unit is used to detect various sensors used by the robot;

[0028] The electronic skin detection unit is used to detect whether the electronic skin is damaged, short-circuited, or has abnormal signals;

[0029] The electronic circuit and chip detection unit is used to detect the connectivity of the robot's electronic circuit, parameter stability, functional integrity of the chip, operating temperature and communication function, and to determine whether there are any faults in the electronic circuit and chip.

[0030] Preferably, the software detection module includes: a code integrity detection unit, a function test unit, an interface detection unit, a memory management detection unit and an error log recording unit;

[0031] The code integrity detection unit is used to check the integrity of the software code by scanning each code file of the software to verify whether there is any missing, damaged or tampered part of the code;

[0032] The functional testing unit is used to test various functions of the software and verify whether the functions of the software are running normally according to the design requirements by simulating various input conditions and scenarios;

[0033] The interface detection unit is used to detect the stability and compatibility of the interface between the software and other software or hardware. It ensures that data can be correctly transmitted and received when the software interacts with external systems;

[0034] The memory management detection unit is used to monitor the memory usage during software operation and detect memory leaks and memory overflow problems;

[0035] The error log recording unit is used to record error information that occurs during software operation. The error information includes: the time when the failure occurs, the specific location in the code, and the error type.

[0036] Preferably, checking the integrity of the software code specifically includes:

[0037] For software with a version control system, obtain the file tree structure from the version library and record the name, path and version information of all code files. For software without a version control system, traverse the software installation directory and its subdirectories, identify files that match the code file extension, and generate a file list.

[0038] Calculate a hash value for each code file and compare it with the known correct hash value, which comes from the official release notes of the software;

[0039] Get the size of each code file and compare the file size with the expected size obtained from the official software documentation and history;

[0040] According to the code file type, select the corresponding tool for format verification. The selection of the corresponding tool for format verification includes: using the Java compiler to check the syntax format of the Java code file, and using the XML parser to verify whether the XML configuration file complies with the syntax rules. If the code file is encrypted or specially encoded, it needs to be decrypted or decoded before format verification;

[0041] For object-oriented programming languages, the dependencies between files are determined by analyzing class references and interface implementations;

[0042] During the inspection process, the inspection results of each file are recorded, and an integrity report is generated based on the inspection results, including the file name, path, hash value comparison results, whether the file size matches, format verification results, and code dependency inspection results.

[0043] Preferably, the ethics detection module includes: a command ethics review unit, a software upgrade ethics review unit, a virus review unit, and an ethics standard update unit;

[0044] The command ethics review unit is used to conduct ethical evaluations on the commands generated by the AI ​​chip to ensure that the instructions issued by the robot comply with ethical standards when performing tasks;

[0045] The software upgrade ethics review unit is used to conduct ethical review of the upgrade content when the system software is upgraded to check whether the new software functions will cause ethical issues;

[0046] The virus review unit is used to detect whether the system software upgrade package and the running software contain malware and viruses;

[0047] The ethics standards update unit is used to continuously pay attention to the latest developments in social ethics research and update the robot's ethical testing guidelines according to new ethical standards.

[0048] Preferably, ethical assessments are conducted on commands generated by AI chips, and ethical reviews are conducted on upgrade contents, specifically including:

[0049] Refer to internationally accepted ethical codes, industry standards, and relevant laws and regulations to clarify the ethical principles applicable to robots, including: not harming humans, protecting privacy, and being fair and just;

[0050] Design an evaluation framework, translate ethical principles into specific evaluation indicators, and determine the weight of each indicator;

[0051] When the AI ​​chip generates a command, it parses the command in detail to analyze the command's goal, execution method, and objects involved;

[0052] For each evaluation indicator, evaluation is performed based on the results of command parsing;

[0053] Based on the evaluation results and weights of each indicator, a comprehensive evaluation is conducted using the weighted average method. If the score is lower than the threshold set by the experts, the order is considered to be inconsistent with ethical requirements and needs to be adjusted and refused to be executed. The order is regenerated and ethical evaluation is conducted again until it meets the requirements.

[0054] When the system software is upgraded, all contents in the upgrade package are obtained, including new function codes, configuration files, and data;

[0055] A detailed analysis is conducted on the new functions in the upgrade content, and an assessment is made on the ethical risks that the new functions may bring. If the score is lower than the threshold set by the experts, the upgrade is considered to be unethical and the upgrade instruction is rejected.

[0056] Preferably, the fault feedback module includes: a severity assessment unit, a measure execution unit, a maintenance situation feedback unit, a maintenance situation feedback unit and a functional status feedback unit;

[0057] The severity assessment unit is used to comprehensively assess the severity of the fault based on the detection results of each module, and classify the fault into different severity levels by analyzing the impact of the fault on the operation of the robot and the potential risks;

[0058] The measure execution unit is used to execute corresponding measures according to the severity of the fault. For minor faults, a warning prompt is issued to draw the attention of users and maintenance personnel; for medium faults, some functions of the robot are restricted, and users and maintenance personnel are notified for repair; for serious faults, the robot is stopped immediately to ensure safety;

[0059] The maintenance feedback unit is used to provide feedback on the maintenance status of each component of the robot to the manufacturer and the cloud and terminal of the maintenance point. The maintenance status includes: recording the robot's operating time, maintenance history and wear degree information of the components;

[0060] The maintenance feedback unit is used to feedback the maintenance status of the robot, and the maintenance status includes: the time of the most recent maintenance, the content of the maintenance, and the operating status of the robot after the maintenance;

[0061] The functional status feedback unit is used to provide real-time feedback on the functional status of each component of the robot, including whether the motor, sensor and software are working normally and whether there is any performance degradation.

[0062] Preferably, the severity of the fault is comprehensively evaluated, and the fault is classified into different severity levels by analyzing the impact of the fault on the operation of the robot and the potential risks, including:

[0063] Based on the fault data collected and fed back by the power and electrical detection module, physical and mechanical detection module, software detection module and ethical detection module, the fault severity, impact and potential risks are scored;

[0064] Among them, the expression of fault severity score is:

[0065] S=α×I+β×R

[0066] In the formula, S represents the fault severity score, α represents the impact weight, β represents the potential risk weight, and the fault severity level is divided according to the value of S, I represents the impact score, and R represents the potential risk score;

[0067] The expression of impact score is:

[0068] I=w1×F key +w2×T impact +w3×S impact

[0069] In the formula, F key represents the key function impact factor, w1 represents the key function impact weight, T impact represents the task execution impact factor, w2 represents the task execution impact weight, S impactrepresents the system association impact factor, w3 represents the system association impact weight;

[0070] Among them, the expression of potential risk score is:

[0071] R=w4×S risk +w5×D risk

[0072] In the formula, S risk represents the safety risk factor, w4 represents the safety risk weight, D risk represents the equipment damage risk factor, and w5 represents the equipment damage risk weight.

[0073] Compared with the prior art, the present invention has the following beneficial effects:

[0074] The fault self-detection and error reporting system for the robot proposed in the present invention can comprehensively and quickly detect the fault conditions of various components of the robot by integrating multiple modules, significantly improving the efficiency of fault detection and diagnosis, enabling maintenance personnel to quickly locate and solve fault problems, and can perform preliminary detection and diagnosis of the robot at the place where the fault occurs, i.e., the user's home or factory site, reducing dependence on professional testing instruments and spare parts, thereby reducing maintenance costs and maintenance difficulties, and can monitor the operating status of the robot in real time, and take timely measures when a fault is detected, effectively avoiding robot operation safety issues caused by failure to discover and handle the fault in time, improving the reliability of the robot, and being able to perform ethical reviews on commands generated by the AI ​​chip, and perform ethical and virus reviews on system software upgrades, so that the robot can comply with ethical and moral standards when performing tasks, and continuously improve its own functions with the progress of social ethics research. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] Figure 1 This is a module framework diagram of the robot's fault self-detection and error reporting system. DETAILED DESCRIPTION

[0076] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think of other obvious variations.

[0077] Reference Figure 1 As shown, a fault self-checking and error reporting system for a robot, the fault self-checking and error reporting system comprises: an electric power detection module, a physical mechanical detection module, a software detection module, an ethical detection module and a fault feedback module;

[0078] 1. Power electrical detection module

[0079] The power and electrical detection module is used to comprehensively detect short circuits, overloads and other faults in the robot's power and electrical system to ensure that the robot's power supply is stable and reliable. The module mainly includes a current detection unit, a voltage detection unit, an insulation detection unit and a power detection unit.

[0080] Current detection unit: The current detection unit can monitor the current in the robot's power and electrical system in real time. Through high-precision current sensors, it can accurately capture subtle changes in current and detect abnormal current conditions in a timely manner. For example, when the current suddenly increases or decreases beyond the normal range, it may mean that there is a short circuit, overload or other electrical fault in the system. The current detection unit can not only respond quickly to current changes, but also analyze long-term current trends to detect potential fault hazards in advance.

[0081] Voltage detection unit: The voltage detection unit is responsible for detecting the voltage of each part of the power electrical system. It can accurately measure the voltage value of different circuit nodes and capture voltage anomalies. Voltage that is too high or too low may damage the electronic components of the robot and affect the normal operation of the robot. By continuously monitoring voltage changes, the voltage detection unit can promptly detect voltage fluctuations, voltage sags or surges, and issue an alarm so that maintenance personnel can take appropriate measures.

[0082] Insulation detection unit: The insulation detection unit is used to check the insulation performance of wires and electronic components in the power and electrical system. Good insulation performance is the key to ensure the safe operation of the power system. The insulation detection unit can detect the insulation resistance, capacitance and other parameters of the wires to determine whether the insulation is damaged, aged or damp. If it is found that the insulation performance has deteriorated, it will issue a warning in time to remind maintenance personnel to carry out maintenance to prevent electrical accidents.

[0083] Power supply power detection unit: The power supply power detection unit is used to measure the output power of the power supply and detect whether the power supply meets the requirements of the robot operation. During the operation of the robot, different tasks and operations may require different power outputs. The power supply power detection unit can monitor the output power of the power supply in real time and compare it with the power requirements of the robot. If the power supply is found to be insufficient, it may cause the robot's performance to deteriorate or fail to operate normally. At this time, the unit will issue an overload alarm to remind maintenance personnel to check the power supply or adjust the robot's task load.

[0084] 2. Physical and mechanical testing module

[0085] The physical mechanical detection module is used to detect the physical hardware failure of the robot and ensure the normal operation of the robot's mechanical parts and sensors. This module mainly includes the motor detection unit, the sensor detection unit and the electronic skin detection unit.

[0086] Motor detection unit: The motor detection unit is used to detect the operating status of the motor, including parameters such as speed, torque and temperature. Through the sensors installed on the motor, it can monitor the operation of the motor in real time and determine whether the motor has any faults. For example, when the motor speed is abnormal, the torque fluctuates greatly, or the temperature is too high, it may mean that the motor has mechanical failure, electrical failure or overload problems. The motor detection unit can detect these problems in time and issue an alarm so that maintenance personnel can carry out maintenance.

[0087] Sensor detection unit: The sensor detection unit is used to detect various sensors used by the robot. Robots are usually equipped with a variety of sensors, such as position sensors, force sensors, temperature sensors, etc. These sensors are essential for the perception and control of the robot. The sensor detection unit can check whether the output signal of the sensor is normal and determine whether the sensor is faulty or damaged. If the sensor is found to be abnormal, it will promptly issue an alarm to remind maintenance personnel to repair or replace the sensor.

[0088] Electronic skin detection unit: The electronic skin detection unit is used to detect whether the electronic skin is damaged, short-circuited, or has abnormal signals. Electronic skin is a new type of sensor technology that can provide robots with more sensitive tactile perception. The electronic skin detection unit can determine whether the electronic skin is damaged, short-circuited, or has other problems by detecting parameters such as the resistance and capacitance of the electronic skin. At the same time, it can also monitor the signal output of the electronic skin to determine whether the signal is normal. If an abnormality is found in the electronic skin, it will promptly issue an alarm to remind maintenance personnel to inspect or replace the electronic skin.

[0089] 3. Software Detection Module

[0090] The software detection module is used to detect the failure of each independent software of the robot and integrate them into one module for unified management to ensure the stability and reliability of the robot's software system. This module mainly includes code integrity detection unit, function test unit, interface detection unit, memory management detection unit and error log recording unit.

[0091] Code integrity detection unit: The code integrity detection unit is used to check the integrity of the software code. By scanning the various code files of the software, it can verify whether there are any missing, damaged or tampered parts of the code. Code integrity is the basis for the normal operation of the software. If the code is incomplete, it may cause various errors and failures in the software. The code integrity detection unit can scan the software code regularly to ensure the integrity and security of the code.

[0092] Functional testing unit: The functional testing unit is used to test various functions of the software. By simulating various input conditions and scenarios, it can verify whether the functions of the software are running normally according to the design requirements. Functional testing is an important part of software quality assurance. Through functional testing, functional defects and errors in the software can be discovered so that they can be repaired in time. The functional testing unit can develop detailed test plans and test cases based on the functional requirements and design documents of the software to ensure comprehensive coverage of the functional testing of the software.

[0093] Interface detection unit: The interface detection unit is used to detect the stability and compatibility of the interface between the software and other software or hardware. In the robot system, different software and hardware need to transmit and interact with each other through the interface. The stability and compatibility of the interface are crucial to the normal operation of the robot. The interface detection unit can check the interface's protocol, data format, transmission rate and other parameters to ensure that the data can be correctly transmitted and received when the software interacts with the external system. If a problem is found in the interface, it will issue an alarm in time to remind the maintenance personnel to perform maintenance or adjust the interface parameters.

[0094] Memory management detection unit: The memory management detection unit is used to monitor the memory usage during the software operation. During the software operation, the memory usage directly affects the performance and stability of the software. The memory management detection unit can detect memory leaks, memory overflows and other problems, and promptly discover abnormal memory usage. If a memory leak or memory overflow is found, it will promptly issue an alarm to remind maintenance personnel to repair it to prevent software crashes or system failures.

[0095] Error log recording unit: The error log recording unit is used to record error information that occurs during the operation of the software. When an error occurs in the software, the error log recording unit can record information such as the time when the error occurred, the specific location in the code, and the type of error. This error information is very important for software fault diagnosis and repair. Maintenance personnel can quickly locate errors in the software by analyzing the error log and take appropriate measures to repair them. The error log recording unit can store error information locally or upload it to the cloud so that maintenance personnel can view and analyze it at any time.

[0096] 4. Ethics Testing Module

[0097] The ethics detection module is used to conduct ethical review of commands generated by AI chips, as well as ethical and virus review of system software upgrades, and continuously improves its own functions with the progress of social ethics research. This module mainly includes command ethics review unit, software upgrade ethics review unit, virus review unit and ethics standard update unit.

[0098] Command Ethics Review Unit: The command ethics review unit is used to conduct ethical evaluations on the commands generated by the AI ​​chip. With the development of artificial intelligence technology, the autonomy and intelligence of robots are constantly improving, and they may issue various commands when performing tasks. Whether these commands comply with ethical norms is directly related to whether the robot's behavior is legal, reasonable and safe. The command ethics review unit can evaluate the commands generated by the AI ​​chip according to preset ethical guidelines and moral standards to ensure that the instructions issued by the robot comply with ethical norms when performing tasks. If an ethical problem is found in the command, it will issue an alarm in time to remind maintenance personnel to make adjustments or interventions.

[0099] Software Upgrade Ethics Review Unit: The software upgrade ethics review unit is used to conduct ethical reviews of the upgrade content when the system software is upgraded. With the continuous advancement of technology, the robot's software system needs to be continuously upgraded and improved. However, new software functions may raise ethical issues, such as privacy protection, data security, and human dignity. The software upgrade ethics review unit can conduct an ethical review of the upgrade content before the software is upgraded to check whether the new software functions will cause ethical issues. If it is found that there is an ethical risk in the upgrade content, it will issue an alarm in time to remind the maintenance personnel to evaluate and adjust.

[0100] Virus inspection unit: The virus inspection unit is used to detect whether there are malware and viruses in the system software upgrade package and the running software. In the robot's software system, malware and viruses may undermine the stability and security of the system, and even cause the robot to lose control or be attacked. The virus inspection unit can detect whether there are malware and viruses by scanning the software upgrade package and the running software. If malware or viruses are found, it will issue an alarm in time to remind maintenance personnel to remove and repair them.

[0101] Ethical Standards Update Unit: The Ethical Standards Update Unit is used to continuously follow the latest progress in social ethics research and update the ethical testing criteria for robots according to new ethical standards. With the development and progress of society, ethical standards are also constantly changing and improving. The Ethical Standards Update Unit can regularly collect the latest results of social ethics research, analyze their impact on robot ethics testing, and update the ethical testing criteria for robots in a timely manner. This can ensure that the ethical testing of robots always meets the ethical requirements of society and ensure that the behavior of robots is legal, reasonable and safe.

[0102] On the one hand, ethical testing regulates the behavioral boundaries of robots and prevents robots from disrupting the human social order due to unconstrained actions. For example, in the medical field, robots that have passed ethical review can assist in treatment more safely and improve the quality of medical care. On the other hand, it helps to enhance the collaboration between robots and humans. When the behavior of robots meets ethical requirements, people will be more willing to accept them, thus achieving more efficient human-machine cooperation. In addition, ethical review also promotes the sustainable development of robotics technology, enabling it to continue to innovate and progress within the framework of ethical standards.

[0103] 5. Fault feedback module

[0104] The fault feedback module is used to distinguish the severity of the fault, take corresponding measures according to the severity, and feedback the maintenance status, maintenance status and functional status of each component of the robot to the manufacturer and the cloud and terminal of the maintenance point so as to carry out repair and maintenance in time. This module mainly includes severity assessment unit, measure execution unit, maintenance status feedback unit, maintenance status feedback unit and functional status feedback unit.

[0105] Severity Assessment Unit: The severity assessment unit is used to comprehensively assess the severity of a fault based on the detection results of each module. It classifies faults into different severity levels by analyzing the impact of the fault on the robot's operation and the potential risks. For example, a minor fault may only affect part of the robot's functions, while a serious fault may cause the robot to stop operating completely. The severity assessment unit can develop detailed assessment criteria and methods based on the characteristics and impact of the fault to ensure that the severity assessment of the fault is accurate and reliable.

[0106] Measures execution unit: The measures execution unit is used to execute corresponding measures according to the severity of the fault. For minor faults, it will issue a warning prompt to draw the attention of users and maintenance personnel; for moderate faults, it will limit some functions of the robot and notify users and maintenance personnel for repairs; for serious faults, it will immediately stop the robot from running to ensure safety. The measures execution unit can formulate corresponding emergency measures and maintenance plans according to the severity and type of the fault to ensure that the robot can be handled in time when a fault occurs.

[0107] Maintenance feedback unit: The maintenance feedback unit is used to provide feedback on the maintenance status of each component of the robot to the cloud and terminal of the manufacturer and maintenance point. It can record information such as the robot's operating time, maintenance history, and the degree of wear of parts. This information is very important for the maintenance and repair of the robot, and can help maintenance personnel formulate reasonable maintenance plans and repair plans. The maintenance feedback unit can regularly upload this information to the cloud so that manufacturers and maintenance personnel can view and analyze it at any time.

[0108] Maintenance feedback unit: The maintenance feedback unit is used to provide feedback on the robot's maintenance status. It can record the time of the most recent maintenance, the content of the maintenance, the robot's operating status after maintenance, and other information. This information can help maintenance personnel understand the robot's maintenance history and effects, so that they can adjust maintenance plans and methods in a timely manner. The maintenance feedback unit can upload the maintenance status to the cloud after each maintenance for reference by manufacturers and other maintenance personnel.

[0109] Functional Status Feedback Unit: The functional status feedback unit is used to provide real-time feedback on the functional status of each component of the robot. It can monitor whether the working status of parts such as motors, sensors and software is normal, and whether there are problems such as performance degradation. The functional status feedback unit can upload this information to the cloud in real time so that users and maintenance personnel can understand the operating status of the robot at any time. If an abnormal functional status is found, it will issue an alarm in time to remind maintenance personnel to conduct inspections and maintenance.

[0110] The method for the current detection unit, the voltage detection unit, the insulation detection unit and the power detection unit to identify abnormalities and faults is:

[0111] For the current detection unit, current sensors are first installed at key locations in the power and electrical system. These current sensors play a vital role. They can collect current data in real time based on their own functional characteristics. The collected current data will be transmitted to the current detection unit, which will conduct in-depth analysis of these data. During the analysis process, the collected current data will be compared with the preset normal current range. This preset normal current range is obtained based on the factory information of the robot and has high accuracy and reliability. If the current exceeds the normal range, it will be judged as a current abnormality. In this way, the current detection unit can detect current anomalies in the power and electrical system in a timely and accurate manner, providing an important basis for subsequent troubleshooting and processing.

[0112] The working method of the voltage detection unit is also unique. Voltage sensors are installed at different nodes of the power and electrical system, and these voltage sensors can detect the voltage of each part. The detected voltage data will be transmitted to the current detection unit, which also plays an important role in analyzing the voltage data. When analyzing the collected voltage data, it will be compared with the preset normal voltage range. Like the current detection unit, this normal voltage range is also obtained based on the factory information of the robot. If the voltage exceeds the normal range, it will be judged as an abnormal voltage. In this way, the voltage detection unit can comprehensively and accurately monitor the voltage conditions of each part of the power and electrical system, ensure that the voltage fluctuates within the normal range, and ensure the stable operation of the robot.

[0113] The insulation test unit takes a more professional approach when identifying anomalies and faults. Use an insulation resistance tester connected to the electronic components in the power electrical system. The insulation resistance tester applies a certain voltage and measures the current passing through the object being tested. The insulation resistance value can be calculated from the measured current and the applied voltage. The insulation resistance value is calculated using the formula:

[0114] R=U / I

[0115] In the formula, R represents the insulation resistance value, U represents the applied voltage value, and I represents the measured current value;

[0116] The calculated insulation resistance value will be compared with the preset insulation resistance standard. If the insulation resistance value is lower than the standard value, it will be judged as poor insulation performance. This method can accurately detect the insulation performance of electronic components in the power and electrical system, detect poor insulation in time, and avoid safety accidents caused by insulation problems;

[0117] When identifying anomalies and faults, the power detection unit calculates the power by measuring voltage and current. The power sensor collects power data in real time and transmits it to the power detection unit. The power detection unit compares the detected power value with the power requirements of the robot under different working conditions. If the power is insufficient or overloaded, it will be judged as an abnormal power supply. This method can effectively monitor the output power of the power supply, ensure that the power supply can meet the power requirements of the robot under different working conditions, and ensure the normal operation of the robot.

[0118] Checking the integrity of software code specifically includes:

[0119] For software with a version control system, first obtain the file tree structure from the version library. In this process, the name, path and version information of all code files will be recorded in detail. This makes it easy to track the change history of the code and ensure the traceability of the code. For software without a version control system, it is necessary to traverse the software installation directory and its subdirectories. By identifying files that match the code file extension, a file list is generated. This list will serve as the basis for subsequent inspections.

[0120] For each code file, a hash value is calculated. The hash value is a unique digital fingerprint that can be used to verify the integrity of the file. The calculated hash value is compared with the known correct hash value. These correct hash values ​​come from the official version notes released by the software, which are authoritative and reliable. If the hash values ​​do not match, it means that the file may have been tampered with or damaged.

[0121] Get the size of each code file. File size is also an important indicator for verifying file integrity. Compare the file size with the expected size, which can be obtained from the official software documentation and history. If the file size does not match the expected size, it may mean that there is a problem with the file.

[0122] According to the type of code file, select the corresponding tool for format verification. For example, for Java code files, you can use the Java compiler to check the syntax format; for XML configuration files, you can use the XML parser to verify whether it complies with the syntax rules. If the code file is encrypted or specially encoded, it needs to be decrypted or decoded before format verification. This ensures that the format of the code file is correct and avoids software failures caused by format problems.

[0123] For object-oriented programming languages, the dependencies between files are determined by analyzing class references and interface implementations. This helps to understand the structure and functionality of the software and discover potential dependency issues. During the inspection process, the inspection results of each file are recorded. Based on these inspection results, an integrity report is generated, which includes the file name, path, hash value comparison results, whether the file size matches, format verification results, and code dependency inspection results. This report can provide detailed information for software developers and maintainers to help them quickly locate and solve problems.

[0124] Conduct ethical assessments on commands generated by AI chips and ethical reviews on upgrade content, including:

[0125] Refer to internationally accepted ethical codes, industry standards, and relevant laws and regulations. Through the study of these norms, clarify the ethical principles applicable to robots. These ethical principles include not harming humans, protecting privacy, and fairness. These principles are the basic norms of robot behavior, ensuring that the behavior of robots will not cause harm to humans, while protecting human privacy and rights.

[0126] Design an evaluation framework, transform ethical principles into specific evaluation indicators, and determine the weight of each indicator. Evaluation indicators are a specific refinement of ethical principles and can more accurately evaluate the ethical compliance of commands and upgrades. The determination of weights can reflect the importance of different indicators and play a key role in comprehensive evaluation.

[0127] When the AI ​​chip generates a command, it will parse the command in detail, analyzing the command's goal, execution method, and objects involved. By gaining a deeper understanding of the specific content of the command, its ethical compliance can be more accurately assessed.

[0128] For each evaluation indicator, an evaluation is conducted based on the results of command analysis. During the evaluation process, it is necessary to consider the impact of the command on humans, the degree of privacy protection, and whether it is fair and just. If ethical issues are found in the command, it needs to be adjusted in a timely manner.

[0129] According to the evaluation results and weights of each indicator, a comprehensive evaluation is conducted using the weighted average method. If the score is lower than the threshold set by the expert, the order is considered to be unethical and needs to be adjusted and refused to be executed. After the order is regenerated, the ethical evaluation is conducted again until it meets the requirements.

[0130] When the system software is upgraded, all contents in the upgrade package are obtained, including new function codes, configuration files, and data. The new functions in the upgrade content are analyzed in detail, and the ethical risks that the new functions may bring are evaluated. If the score is lower than the threshold set by the experts, it is considered that the upgrade does not meet the ethical requirements and the upgrade instruction is rejected. This ensures that the system software upgrade will not introduce new ethical issues and ensure the ethical compliance of the robot.

[0131] Comprehensively evaluate the severity of the fault, and by analyzing the impact of the fault on the operation of the robot and the potential risks, classify the fault into different severity levels, including:

[0132] Based on the fault data collected and fed back by the power and electrical detection module, physical and mechanical detection module, software detection module and ethical detection module, the fault severity, impact and potential risks are scored;

[0133] Among them, the expression of fault severity score is:

[0134] S=α×I+β×R

[0135] In the formula, S represents the fault severity score, α represents the impact weight, β represents the potential risk weight, and the fault severity level is divided according to the value of S, I represents the impact score, and R represents the potential risk score;

[0136] The expression of impact score is:

[0137] I=w1×F key +w2×T impact +w3×S impact

[0138] In the formula, F key represents the key function impact factor, w1 represents the key function impact weight, T impact represents the task execution impact factor, w2 represents the task execution impact weight, S impact represents the system association impact factor, w3 represents the system association impact weight;

[0139] Among them, the expression of potential risk score is:

[0140] R=w4×S risk +w5×D risk

[0141] In the formula, S risk represents the safety risk factor, w4 represents the safety risk weight, D risk represents the equipment damage risk factor, and w5 represents the equipment damage risk weight.

[0142] Potential risk scoring can more objectively and accurately evaluate faults and avoid subjective judgment bias. By quantifying the severity, impact and potential risks, we can clearly understand the hazard level of the fault and provide a clear basis for taking corresponding measures. Secondly, it helps to reasonably allocate maintenance resources, give priority to high-scoring faults, and improve maintenance efficiency. At the same time, it is also convenient to compare and analyze different faults, provide data support for subsequent improved design and preventive maintenance, and improve the overall reliability and safety of the robot.

[0143] The usage process of the present invention is: the system starts each detection module; the power and electrical detection module detects power failure; the physical and mechanical module detects hardware failure; the software detection module detects software failure; the ethics detection module reviews AI commands and upgrades; the fault feedback module evaluates the fault and executes measures; and feedbacks maintenance, maintenance and functional status to the cloud / terminal.

[0144] To sum up, the advantages of the present invention are: it can comprehensively and quickly detect faults, improve diagnostic efficiency, and facilitate maintenance personnel to locate and solve problems. It can perform preliminary detection and diagnosis at the user's home or factory site, reduce dependence on professional instruments and spare parts, reduce costs and difficulty, monitor operating status in real time, handle faults in a timely manner, and improve reliability. It can also perform ethical and virus reviews on AI chip commands and system software upgrades to ensure compliance with ethical norms and improve functions as social ethics progress.

[0145] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.

Claims

1. A fault self-checking and error reporting system for a robot, characterized in that: The fault self-checking and error reporting system includes: power and electrical detection module, physical and mechanical detection module, software detection module, ethics detection module and fault feedback module; The power and electrical detection module is used to detect short circuit and overload faults in the robot's power and electrical system; The physical mechanical detection module is used to detect the fault condition of the physical hardware, and the physical hardware includes: a motor, a sensor and an electronic skin; The software detection module is used to detect the failures of each independent software and integrate them into one module for unified management; The ethics detection module is used to generate commands for AI chips and conduct ethical reviews, as well as conduct ethical and virus reviews for each system software upgrade, and improve its own functions with social ethics research; The fault feedback module is used to integrate the fault reports of each individual component, differentiate the faults according to their severity, take corresponding measures according to the severity, and provide feedback on the maintenance status, upkeep and functional status of each component of the robot to the manufacturer and the cloud and terminal of the maintenance point through local voice and display information.

2. A fault self-checking and error reporting system for a robot according to claim 1, characterized in that: The power electrical detection module includes: a current detection unit, a voltage detection unit, an insulation detection unit and a power supply detection unit; The current detection unit is used to monitor the current size in the robot's power and electrical system in real time and capture current abnormalities; The voltage detection unit is used to detect the voltage of each part of the power electrical system and capture voltage anomalies; The insulation test unit is used to check the insulation performance of wires and electronic components in the power and electrical system; The power detection unit is used to measure the output power of the power supply, detect whether the power supply meets the requirements of the robot operation, and detect overload faults in time.

3. A fault self-checking and error reporting system for a robot according to claim 2, characterized in that: The method for the current detection unit, the voltage detection unit, the insulation detection unit and the power detection unit to identify abnormalities and faults is: The current detection unit installs current sensors at key locations of the power and electrical system. Based on the current sensors, current data is collected in real time and transmitted to the current detection unit for analysis. The collected current data is compared with the preset normal current range. If the current exceeds the normal range, it is judged as an abnormal current situation. The normal current range is obtained based on the factory information of the robot. The voltage detection unit installs voltage sensors at different nodes of the power and electrical system to detect the voltage of each part, and transmits the data to the current detection unit to analyze the collected voltage data and compare it with the preset normal voltage range. If the voltage exceeds the normal range, it is judged as an abnormal voltage situation. The normal voltage range is obtained according to the factory information of the robot; The insulation detection unit uses an insulation resistance tester connected to the electronic components in the power electrical system. The tester applies a certain voltage, measures the current passing through the object under test, and calculates the insulation resistance value. The calculation formula for the insulation resistance value is: R=U / I In the formula, R represents the insulation resistance value, U represents the applied voltage value, and I represents the measured current value; The calculated insulation resistance value is compared with the preset insulation resistance standard. If the insulation resistance value is lower than the standard value, it is judged that the insulation performance is poor; The power detection unit calculates power by measuring voltage and current. The power sensor collects power data in real time and transmits it to the power detection unit. The power detection unit compares the detected power value with the power requirement of the robot under different working conditions. If the power is insufficient or overloaded, it is judged as an abnormal power situation.

4. A fault self-checking and error reporting system for a robot according to claim 1, characterized in that: The physical mechanical detection module includes: a motor detection unit, a sensor detection unit, an electronic skin detection unit, and an electronic circuit and chip detection unit; The motor detection unit is used to detect the running state of the motor, which includes: speed, torque and temperature, and to determine whether the motor has a fault by monitoring the running state; The sensor detection unit is used to detect various sensors used by the robot; The electronic skin detection unit is used to detect whether the electronic skin is damaged, short-circuited, or has abnormal signals; The electronic circuit and chip detection unit is used to detect the connectivity of the robot's electronic circuit, parameter stability, functional integrity of the chip, operating temperature and communication function, and to determine whether there are any faults in the electronic circuit and chip.

5. A fault self-checking and error reporting system for a robot according to claim 1, characterized in that: The software detection module includes: a code integrity detection unit, a functional testing unit, an interface detection unit, a memory management detection unit and an error log recording unit; The code integrity detection unit is used to check the integrity of the software code by scanning each code file of the software to verify whether there is any missing, damaged or tampered part of the code; The functional testing unit is used to test various functions of the software and verify whether the functions of the software are running normally according to the design requirements by simulating various input conditions and scenarios; The interface detection unit is used to detect the stability and compatibility of the interface between the software and other software or hardware. It ensures that data can be correctly transmitted and received when the software interacts with external systems; The memory management detection unit is used to monitor the memory usage during software operation and detect memory leaks and memory overflow problems; The error log recording unit is used to record error information that occurs during software operation. The error information includes: the time when the failure occurs, the specific location in the code, and the error type.

6. A fault self-checking and error reporting system for a robot according to claim 5, characterized in that: Checking the integrity of software code specifically includes: For software with a version control system, obtain the file tree structure from the version library and record the name, path and version information of all code files. For software without a version control system, traverse the software installation directory and its subdirectories, identify files that match the code file extension, and generate a file list. Calculate a hash value for each code file and compare it with the known correct hash value, which comes from the official release notes of the software; Get the size of each code file and compare the file size with the expected size obtained from the official software documentation and history; According to the code file type, select the corresponding tool for format verification. The selection of the corresponding tool for format verification includes: using the Java compiler to check the syntax format of the Java code file, and using the XML parser to verify whether the XML configuration file complies with the syntax rules. If the code file is encrypted or specially encoded, it needs to be decrypted or decoded before format verification; For object-oriented programming languages, the dependencies between files are determined by analyzing class references and interface implementations; During the inspection process, the inspection results of each file are recorded, and an integrity report is generated based on the inspection results, including the file name, path, hash value comparison results, whether the file size matches, format verification results, and code dependency inspection results.

7. A fault self-checking and error reporting system for a robot according to claim 1, characterized in that: The ethics detection module includes: command ethics review unit, software upgrade ethics review, virus review unit and ethics standard update unit; The command ethics review unit is used to conduct ethical evaluations on the commands generated by the AI ​​chip to ensure that the instructions issued by the robot comply with ethical standards when performing tasks; The software upgrade ethics review unit is used to conduct ethical review of the upgrade content when the system software is upgraded to check whether the new software functions will cause ethical issues; The virus review unit is used to detect whether the system software upgrade package and the running software contain malware and viruses; The ethics standards update unit is used to continuously pay attention to the latest developments in social ethics research and update the robot's ethical testing guidelines according to new ethical standards.

8. A fault self-checking and error reporting system for a robot according to claim 1, characterized in that: Conduct ethical assessments on commands generated by AI chips and ethical reviews on upgrade content, including: Refer to internationally accepted ethical codes, industry standards, and relevant laws and regulations to clarify the ethical principles applicable to robots, including: not harming humans, protecting privacy, and being fair and just; Design an evaluation framework, translate ethical principles into specific evaluation indicators, and determine the weight of each indicator; When the AI ​​chip generates a command, it parses the command in detail to analyze the command's goal, execution method, and objects involved; For each evaluation indicator, evaluation is performed based on the results of command parsing; Based on the evaluation results and weights of each indicator, a comprehensive evaluation is conducted using the weighted average method. If the score is lower than the threshold set by the experts, the order is considered to be inconsistent with ethical requirements and needs to be adjusted and refused to be executed. The order is regenerated and ethical evaluation is conducted again until it meets the requirements. When the system software is upgraded, all contents in the upgrade package are obtained, including new function codes, configuration files, and data; A detailed analysis is conducted on the new functions in the upgrade content, and an assessment is made on the ethical risks that the new functions may bring. If the score is lower than the threshold set by the experts, the upgrade is considered to be unethical and the upgrade instruction is rejected.

9. A fault self-checking and error reporting system for a robot according to claim 1, characterized in that: The fault feedback module includes: severity assessment unit, measure execution unit, maintenance situation feedback unit, maintenance situation feedback unit and function status feedback unit; The severity assessment unit is used to comprehensively assess the severity of the fault based on the detection results of each module, and classify the fault into different severity levels by analyzing the impact of the fault on the operation of the robot and the potential risks; The measure execution unit is used to execute corresponding measures according to the severity of the fault. For minor faults, a warning prompt is issued to draw the attention of users and maintenance personnel; for medium faults, some functions of the robot are restricted, and users and maintenance personnel are notified for repair; for serious faults, the robot is stopped immediately to ensure safety; The maintenance feedback unit is used to provide feedback on the maintenance status of each component of the robot to the manufacturer and the cloud and terminal of the maintenance point. The maintenance status includes: recording the robot's operating time, maintenance history and wear degree information of the components; The maintenance feedback unit is used to feedback the maintenance status of the robot, and the maintenance status includes: the time of the most recent maintenance, the content of the maintenance, and the operating status of the robot after the maintenance; The functional status feedback unit is used to provide real-time feedback on the functional status of each component of the robot, including whether the motor, sensor and software are working normally and whether there is any performance degradation.

10. A fault self-checking and error reporting system for a robot according to claim 1, characterized in that: Comprehensively evaluate the severity of the fault, and by analyzing the impact of the fault on the operation of the robot and the potential risks, classify the fault into different severity levels, including: Based on the fault data collected and fed back by the power and electrical detection module, physical and mechanical detection module, software detection module and ethical detection module, the fault severity, impact and potential risks are scored; Among them, the expression of fault severity score is: S=α×I+β×R In the formula, S represents the fault severity score, α represents the impact weight, β represents the potential risk weight, and the fault severity level is divided according to the value of S, I represents the impact score, and R represents the potential risk score; The expression of impact score is: I=w1×F key +w2×T impact +w3×S impact In the formula, F key represents the key function impact factor, w1 represents the key function impact weight, T impact represents the task execution impact factor, w2 represents the task execution impact weight, S impact represents the system association impact factor, w3 represents the system association impact weight; Among them, the expression of potential risk score is: R=w4×S risk +w5×D risk In the formula, S risk represents the safety risk factor, w4 represents the safety risk weight, D risk represents the equipment damage risk factor, and w5 represents the equipment damage risk weight.

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