Heading machine remote control safety detection system based on big data

Abstract

The invention discloses a heading machine remote control safety detection system based on big data, relates to the technical field of heading machine safety detection, and solves the problems that instruction mapping errors, signal interference and the like cannot be effectively recognized, and the technical problem that an effective mechanism is lacked for synergism and priority judgment of multi-instruction fusion execution. By establishing an instruction and action bidirectional mapping table and a finite-state machine model, deep verification of action execution correctness is realized, forward instruction mapping errors can be detected, uniqueness of instructions corresponding to actions can be reversely checked, the risk of instruction mistaken execution is reduced, a moving average algorithm is introduced to establish a response time baseline model, and the accuracy of action execution is improved. The multi-instruction fusion analysis module can identify trend delay and enhance the operation stability of the system, the multi-instruction fusion analysis module ensures the accuracy and high efficiency of multi-instruction execution through instruction priority ranking, mutual exclusion instruction detection, action collaboration analysis and other mechanisms, and equipment faults and safety accidents caused by instruction conflicts or execution deviations are avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of roadheader safety detection technology, and in particular to a roadheader remote control safety detection system based on big data. Background Art

[0002] With the development of intelligent tunneling, more and more tunnel boring machines are equipped with remote control functions. In underground engineering fields such as mining and tunnel excavation, tunnel boring machines are core operating equipment, and the safety and reliability of their remote control operation are of vital importance.

[0003] Traditional tunnel boring machine remote control systems often rely on a single functional module for command transmission and equipment control, and have significant deficiencies in command analysis and anomaly detection. For example, some systems determine equipment status solely through simple signal feedback, lacking in-depth analysis of complex scenarios such as command mapping logic, signal interference, and the fusion execution of multiple commands. In response time monitoring, fixed thresholds are often used, making it difficult to adapt to dynamic changes under different operating conditions. Furthermore, existing systems often rely on manual experience to locate the cause of anomalies, lacking a systematic, automated analysis process. This results in low fault diagnosis efficiency and a high rate of misjudgment. As the complexity of underground engineering operating environments increases, traditional remote control detection technology can no longer meet the demands of safe and efficient operations. Summary of the Invention

[0004] In response to the shortcomings of the existing technology, the present invention provides a tunnel boring machine remote control safety detection system based on big data, which solves the problems of being unable to effectively identify instruction mapping errors, signal interference, etc., and the lack of an effective mechanism for the coordination and priority judgment of multi-instruction fusion execution.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: A roadheader remote control safety detection system based on big data, comprising:

[0006] The remote control status analysis module is used to judge the execution action transmitted by the information acquisition module. By comprehensively judging the correctness of the execution action and the response time, if both are normal, a normal status signal is generated and transmitted to the multi-instruction fusion analysis module. On the contrary, if any group is abnormal, an abnormal status signal is generated and transmitted to the instruction abnormality analysis module.

[0007] The instruction exception analysis module is used to analyze the abnormal status signal and the correctness of the execution action. By analyzing the instruction mapping logic, it determines the abnormality and generates the corresponding logic mapping correct or error signal;

[0008] Analyze the response time of the action execution, determine the abnormality by comparing the signal strength with the threshold, and generate the corresponding signal interference or normal signal, and transmit it to the safety detection information output module;

[0009] The multi-instruction fusion analysis module is used to analyze the normal state signal, obtain the fusion instruction and the corresponding execution action, determine whether there is an abnormality, and generate a normal or abnormal signal for the fusion instruction;

[0010] Analyze the abnormal signal of the fusion instruction to determine the specific abnormal situation of the execution action, and analyze the three abnormal phenomena of no execution, partial execution of instructions, and abnormal action respectively to determine the specific cause and transmit it to the safety detection information output module.

[0011] As a further solution of the present invention, it also includes an information acquisition module and a safety detection information output module;

[0012] An information collection module is used to collect execution actions obtained according to remote control instructions and transmit them to the remote control status analysis module;

[0013] The safety detection information output module is used to display the correct or incorrect signals of logical mapping, signal interference or normal signals and the specific reasons to the corresponding management personnel.

[0014] As a further solution of the present invention, the specific manner in which the remote control status analysis module judges the execution action transmitted by the information acquisition module is:

[0015] Establish a bidirectional mapping table between commands and actions, obtain a response time threshold, match the execution action corresponding to the remote control command with the bidirectional mapping table, and compare the response time corresponding to the remote control command with the response time threshold;

[0016] If any of the two is abnormal, an abnormal state signal is generated; otherwise, if both are normal, a normal state signal is generated.

[0017] As a further solution of the present invention, the specific method in which the instruction exception analysis module analyzes the correctness of the execution action is:

[0018] Obtain and analyze the command mapping logic of the tunnel boring machine, check the firmware code or configuration file of the remote control terminal, and confirm whether the mapping relationship between the command code and the equipment action is correct. If correct, generate a mapping logic correct signal; otherwise, generate a mapping logic error signal.

[0019] As a further solution of the present invention, the specific method of analyzing the execution action response time by the instruction abnormality analysis module is as follows:

[0020] Use a spectrum analyzer or the terminal's built-in signal monitoring function to check the signal-to-noise ratio (SNR) of the communication frequency band and compare the obtained SNR with the threshold.

[0021] If the signal strength is lower than the threshold, it indicates that there is signal interference and a signal interference signal is generated. Conversely, if the signal strength is greater than the threshold, it indicates that there is no signal interference and a signal normal signal is generated.

[0022] As a further solution of the present invention, the specific manner in which the multi-instruction fusion analysis module generates a normal or abnormal signal of a fusion instruction is as follows:

[0023] Acquire multiple fusion instructions and corresponding execution actions, sort the acquired multiple fusion instructions and their corresponding execution actions according to timestamps and instruction priorities, establish a one-to-one mapping relationship table, and at the same time establish a mutually exclusive instruction rule library to check whether there are contradictory instruction combinations in the fusion instructions. If there is an abnormality in the execution action, a fusion instruction abnormal signal is generated. Conversely, if there is no abnormality in the execution action, a fusion instruction normal signal is generated.

[0024] As a further solution of the present invention, the specific method of the multi-instruction fusion analysis module to analyze the abnormal phenomenon of no execution is as follows:

[0025] Determine whether the antenna is detached. If so, generate the hardware communication link abnormality reason;

[0026] If the cause is abnormal power supply to the remote control terminal or the device main control, the hardware module fault abnormality reason is generated;

[0027] If the instruction filter misjudges a normal instruction as an illegal operation, a software logic blocking exception reason is generated;

[0028] If the error is caused by the format of the multi-command combination data packet, the command format error exception reason is generated.

[0029] As a further solution of the present invention, the specific method of analyzing the abnormality of executing some instructions by the multi-instruction fusion analysis module is as follows:

[0030] If the instruction is discarded due to insufficient CPU or memory, a hardware resource contention exception is generated;

[0031] If the priority configuration is wrong, low-priority instructions are preempted by high-priority instructions, the instruction queue processing order is disordered, and the software segmented execution causes subsequent instructions to be interrupted, then the instruction processing defect exception reason is generated;

[0032] If the cause is a malfunction of the remote control terminal buttons or sensors, an input device failure exception reason is generated.

[0033] As a further solution of the present invention, the specific method of the multi-instruction fusion analysis module to analyze the abnormal phenomenon of abnormal action is:

[0034] If the instruction field is misread due to a software protocol vulnerability, an instruction parsing error exception will be generated;

[0035] If the cause is the sticking of hardware contacts such as relays, or inconsistency between instructions and actions, then a hardware signal interference anomaly is generated;

[0036] If the mutually exclusive logic fails and contradictory instructions are executed at the same time, a logical and mechanical problem abnormality will be generated.

[0037] The present invention provides a remote control safety detection system for roadheaders based on big data. Compared with the existing technology, it has the following advantages:

[0038] The present invention achieves in-depth verification of the correctness of action execution by establishing a bidirectional mapping table of instructions and actions and a finite state machine model. It can not only detect forward instruction mapping errors, but also reversely verify the uniqueness of the instructions corresponding to the actions, reducing the risk of incorrect instruction execution. The moving average algorithm is introduced to establish a response time baseline model, which can identify trend delays and enhance the stability of system operation compared to traditional fixed threshold judgment.

[0039] The multi-instruction fusion analysis module of the present invention ensures the accuracy and efficiency of multi-instruction execution through mechanisms such as instruction priority sorting, mutually exclusive instruction detection, and action coordination analysis, thereby avoiding equipment failures and safety accidents caused by instruction conflicts or execution deviations. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 This is a block diagram of the system principle of the present invention. DETAILED DESCRIPTION

[0041] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0042] See also Figure 1 This application provides a roadheader remote control safety detection system based on big data, including: information acquisition module, remote control status analysis module, instruction abnormality analysis module, multi-instruction fusion analysis module and safety detection information output module, combined with Figure 1 It can be known that the functional modules are electrically connected in a unidirectional manner.

[0043] At the same time, the tunnel boring machine equipment in this application has a general emergency stop button, a cutting emergency stop button, a motor start warning, a travel alarm light, an electrical interlock between the oil pump motor and the cutting motor, a high and low speed interlock between the cutting speed, a host remote control and a host manual interlock, an anchor function and a cutting motor interlock, a mechanical interlock between the electric control box switch and the door, and a protection against the electric control box door not being tightly closed. It must also have a remote control button / lever detection function. Each time the equipment is started (when the start button on the operating console is pressed), the system automatically detects, and then the remote control performs a self-reset. The specific reset means that the machine starts, and first detects whether the remote control is reset and whether its own hydraulic reversing valve is reset. If these two tests are in the reset state, the machine can start normally. Otherwise, an alarm will be sounded, and the user will be prompted to check.

[0044] The information acquisition module is used to obtain the remote control instructions of the tunnel boring machine and the execution actions obtained based on the remote control instructions, and transmit the two to the remote control status analysis module.

[0045] The remote control status analysis module is used to judge and analyze the obtained execution actions. It makes a comprehensive judgment on the correctness of the execution actions and the response time of the execution actions. Specifically, based on the correctness of the execution actions, a two-way mapping table between instructions and actions is established to verify whether the actual actions fully match the expected instructions. At the same time, based on the finite state machine (FSM) model, it checks whether the action sequence conforms to the state transition rules. For the response time of the execution actions, a fixed response time threshold (such as 200ms) is set. A moving average algorithm is used to establish a response time baseline model to identify trend delays. If any of the two groups is abnormal, it indicates that the remote control status of the tunnel boring machine is abnormal, and an abnormal status signal is generated. Conversely, if both are normal, it indicates that the remote control status of the tunnel boring machine is normal, and a normal status signal is generated.

[0046] For example, when analyzing the response time, the total time from pressing the "forward" button on the remote control terminal to the actual movement of the device needs to be broken down into:

[0047] Terminal processing delay: the time from key scanning to command encoding (e.g. 50ms);

[0048] Communication delay: wireless transmission time (e.g. Wi-Fi signal transmission time is 20ms);

[0049] Device-side delay: the time from receiving module decoding → controller calculation → driver output (e.g. 100ms);

[0050] Mechanical delay: The physical time taken for the motor to start and the mechanical parts to move (e.g. the track rotation lags by 80ms).

[0051] The total response time obtained by summing the above times is 250ms, while the response time threshold is 200ms. After comparing the two, it is found that the total response time is greater than the response time threshold, indicating that the response time is abnormal.

[0052] The generated abnormal status signal is transmitted to the instruction abnormality analysis module, and the normal status signal is transmitted to the multi-instruction fusion analysis module.

[0053] The instruction exception analysis module is used to analyze the acquired abnormal status signals and perform separate analysis based on the correctness of the execution action and the response time;

[0054] For the analysis of the instruction mapping logic, the configuration file of the remote control terminal is read first. If the configuration file is missing or abnormal, the firmware code is analyzed in depth. For the configuration file, structured formats such as JSON and YAML are used to clarify the correspondence between the instruction code and the device action. When parsing the firmware code, static code analysis tools are used to accurately locate the code fragments of the instruction code and action mapping. At the same time, not only the forward mapping from the instruction code to the device action is verified, but also the reverse verification is required to see whether the device action can accurately correspond to the unique instruction code to avoid many-to-one or one-to-many erroneous mapping situations. If a mapping error is found, the error location (such as the specific line of the configuration file, the function name and line number of the firmware code) and the error type (such as duplicate instruction mapping, missing mapping of key instructions) are recorded in detail, and a mapping logic error signal is generated. Conversely, if the mapping is correct, a mapping logic correct signal is generated.

[0055] Suppose the remote control terminal configuration file originally defined command code "0x03" as corresponding to the device's "up" action, but due to human error, it was modified to correspond to the "down" action. When the "up" command was executed, the roadheader instead executed the "down" action. Through the optimized analysis process, the system reads the configuration file and discovers the incorrect mapping, recording the error location as line 5 of the configuration file, the error type as a command mapping error, and simultaneously generates a mapping logic error signal.

[0056] In addition to monitoring the signal-to-noise ratio (SNR) and signal strength, response time analysis also includes testing for signal frequency stability and waveform integrity. Use a spectrum analyzer's real-time spectrum analysis function to observe whether the signal frequency drifts. Use an oscilloscope to monitor the signal waveform for distortion or aberration.

[0057] Based on historical signal data and different operating environments (such as bends in tunnels and equipment-intensive areas), the thresholds of signal strength and signal-to-noise ratio are dynamically adjusted. If the signal strength is lower than the threshold, a signal interference signal is generated. Conversely, if the signal strength is greater than the threshold, a normal signal is generated.

[0058] For example, in a coal mine tunnel operation scenario, the tunnel boring machine remote control system uses the 2.4GHz Wi-Fi frequency band for communication. During the operation, there were sudden delays and confusion in the execution of actions. The optimized analysis system monitored through a spectrum analyzer and found that the signal-to-noise ratio of the 2.4GHz frequency band dropped to -85dBm (below the threshold of -80dBm), and the signal waveform showed obvious distortion, and the frequency stability decreased. The system further analyzed the spectrum graph and found that the interference signal was concentrated in the 2.412-2.422GHz frequency band. Combined with the on-site equipment, it was located that the newly put into use wireless sensor network nearby was causing co-frequency interference with the remote control system. The system generates a signal interference signal and prompts "Co-frequency interference exists in the 2.4GHz frequency band.

[0059] Multi-instruction fusion analysis module, which is used to analyze the acquired normal state signals and the generated fusion instruction abnormal signals;

[0060] The multiple fusion instructions and their corresponding execution actions are sorted by timestamp and instruction priority, and a one-to-one mapping table is established. Key parameters such as action speed, displacement distance, and running time are extracted from the execution action data to provide a quantitative basis for subsequent analysis.

[0061] Establish a mutually exclusive instruction rule base to check whether there are contradictory instruction combinations in the fusion instructions. For example, when instructions such as "forward" and "backward", "up" and "down" appear at the same time, it is determined to be a logical conflict. According to the preset instruction priority rules, verify whether the execution action complies with the priority order. For example, the "emergency stop" instruction has the highest priority. When the "emergency stop" is fused with other instructions, the equipment should give priority to the emergency stop action. For fusion instructions that require the collaboration of multiple components, analyze the time synchronization and parameter matching between the execution actions. For example, in the "turn + move" fusion instruction, check whether the steering angle and movement speed match to avoid action disconnection or interference;

[0062] Based on the above instruction rule library, judgment and analysis are performed. If there is an abnormality in the execution action, a fusion instruction abnormal signal is generated. If there is no abnormality in the execution action, a fusion instruction normal signal is generated.

[0063] Obtain the execution action and identify the specific abnormal situation of the execution action in combination with the fusion instruction. Three abnormal phenomena are obtained: no execution at all, partial execution of instructions, and abnormal action. All three are analyzed separately.

[0064] Analyze the situation where instructions are not executed at all, and the specific phenomenon is: after multiple instructions are input, the device does not respond at all and no error prompts are given. Then analyze separately from the hardware communication link, hardware module failure, software logic blockage, and instruction format errors;

[0065] The analysis of hardware communication link interruption is as follows:

[0066] Wireless communication: The signal between the remote control terminal and the device is completely lost (for example, the antenna is detached or the channel is blocked by strong interference), resulting in the command not being delivered to the main control system.

[0067] Example: In a metal mine environment, radio frequency signals are shielded and remote control commands cannot be transmitted to the roadheader.

[0068] Wired communication: A broken cable, loose connector, or physical layer failure (such as a damaged CAN bus terminal resistor) may cause the command data packet to fail to transmit.

[0069] The analysis of power supply or hardware module failure is as follows:

[0070] The power supply of the remote control terminal or the device main control module is abnormal (such as battery exhaustion or power adapter failure), causing the circuit to fail to work.

[0071] Key hardware damage: such as microcontroller (MCU) crash, communication chip (such as SPI / UART module) burnt out, unable to receive or process instructions.

[0072] The analysis of software logic blocking is as follows:

[0073] Instruction filtering mechanism is falsely triggered: the system misjudges normal multi-instruction combinations as "illegal operations" (such as undefined instruction combinations), directly intercepts and discards them.

[0074] Example: When "Up" and "Down" commands are sent simultaneously, the system does not perform any action by default due to the mutual exclusion logic.

[0075] State machine locked: The device is in a "safety locked state" (e.g. not reset after an emergency stop) and refuses to receive any control instructions.

[0076] Regarding the analysis of instruction format errors, when multiple instructions are combined, the data packet format is incorrect (such as check bit error, length field abnormality) and is directly discarded by the system verification mechanism.

[0077] Example: The concatenation of the byte streams of two instructions causes the CRC check to fail, and the system determines that the instruction is invalid.

[0078] Regarding the analysis of partial command execution, the specific phenomenon is that after multiple commands are input, the device only executes some of them, and the rest are ignored or not effective. The following reasons are analyzed respectively:

[0079] Hardware resource competition

[0080] CPU / memory bottleneck: The main control chip has insufficient computing power and cannot process multiple instructions simultaneously (such as multi-threaded scheduling failure), resulting in some instructions being discarded.

[0081] Example: When the "move + turn + laser ranging" commands are sent simultaneously, the ranging command is not executed due to excessive CPU load.

[0082] Peripheral port conflict: Multiple instructions call the same hardware resource (such as a GPIO port or motor driver), causing the later instruction to be blocked by the previous instruction.

[0083] Example: Simultaneously control two actions that require the same motor (such as extension and rotation of a robotic arm). Only the extension action with a higher priority is executed.

[0084] Defects in the instruction priority mechanism: The system does not correctly define instruction priorities, or the priority configuration is incorrect: low-priority instructions are preempted by high-priority instructions for processing resources.

[0085] Example: The "Emergency Stop" command has a higher priority than the "Speed ​​Adjustment" command. If they are input at the same time, only the emergency stop will take effect.

[0086] Queue processing logic exception: The instruction queue is not processed according to the "first in, first out" or "priority first" principle, resulting in some instructions being skipped.

[0087] Software logic segmented execution: The program uses a segmented processing mechanism. When multiple instructions are executed across cycles, subsequent instructions are interrupted due to state changes:

[0088] For example, if you send "move 10 meters" first and then "turn 90 degrees," the device will not turn until it has completed moving forward. If the operator mistakenly believes that the turn has not been executed, they may mistakenly determine that some commands have failed.

[0089] Input device failure: Some buttons / sensors on the remote control terminal malfunction, causing the corresponding commands to not be triggered correctly:

[0090] Example: The left joystick of the controller is faulty, resulting in the "left turn" command not being sent, and only the "forward" command being executed.

[0091] Analysis of abnormal actions: After multiple instructions are input, the device performs abnormal actions unrelated to the instructions (such as motor reversal and robot arm loss of control). Analysis is conducted from the following aspects:

[0092] Instruction parsing error

[0093] Software protocol vulnerability: When multiple instructions are combined, the parser misreads the instruction fields (such as address bit confusion and data bit misalignment), resulting in erroneous actions.

[0094] Example: The low bytes of the "forward" command (0x01) and the "backward" command (0x02) are concatenated and interpreted as "turn right" (0x12).

[0095] Data type overflow: When multiple instruction parameters are superimposed, they exceed the register storage range (for example, an 8-bit register receives 16-bit data), resulting in a value truncation error.

[0096] Example: When the speed command (0x80, decimal 128) is combined with the direction command (0x01), it becomes -128 due to register overflow, and the device runs in reverse at full speed.

[0097] Hardware signal interference

[0098] Electromagnetic compatibility (EMC) issues: Strong electromagnetic interference (such as inverters and motor startup) causes communication signal distortion and instruction data tampering.

[0099] Example: When the wireless signal is interfered with, the "Stop" command (0x00) is incorrectly transmitted as "Start" (0x0F), causing the device to operate abnormally.

[0100] Hardware contact adhesion: Actuators such as relays and contactors may become stuck due to arcing, resulting in inconsistencies between instructions and actual actions (e.g., the instructions require power off, but the contacts remain closed).

[0101] Logical mutex failure

[0102] The system does not correctly implement mutual exclusion logic, allowing conflicting instructions to execute simultaneously:

[0103] Example: "Motor forward" and "motor reverse" instructions take effect at the same time, causing the motor to stall or trip due to overload.

[0104] State machine jump error: Multiple instructions trigger illegal state machine jumps (such as jumping directly from "Standby" to "Running" without going through "Initialization"), causing abnormal actions.

[0105] Actuator mechanical failure

[0106] Mechanical component jamming, loose couplings, or sensor feedback errors can cause the device's actions to differ from instructions. For example, after a steering command is sent, the actual steering angle may not match the command due to jamming in the robotic arm joints, triggering the limit switch to malfunction.

[0107] Software bug or version defect

[0108] In a multithreaded environment, shared variables are not locked, causing confusion in instruction processing logic. For example, if two threads modify motor speed parameters simultaneously, the final value is random, causing the device to accelerate or decelerate abnormally.

[0109] Old versions of the software have unfixed multi-instruction processing bugs, such as recursive call stack overflows that cause the program to run away.

[0110] Based on the above analysis, the abnormality cause information is generated and transmitted to the safety detection information output module.

[0111] The safety detection information output module is used to display the acquired abnormality cause information to the corresponding operator.

[0112] Some of the data in the above formulas are calculated based on their numerical values ​​and are not substituted into parameter units for calculation. At the same time, the contents not described in detail in this specification belong to the existing technology known to those skilled in the art.

[0113] The above embodiments are only used to illustrate the technical method of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A roadheader remote control safety detection system based on big data, characterized in that: include: The remote control status analysis module is used to judge the execution action transmitted by the information acquisition module. By comprehensively judging the correctness of the execution action and the response time, if both are normal, a normal status signal is generated and transmitted to the multi-instruction fusion analysis module. On the contrary, if any group is abnormal, an abnormal status signal is generated and transmitted to the instruction abnormality analysis module. The instruction exception analysis module is used to analyze the abnormal status signal and the correctness of the execution action. By analyzing the instruction mapping logic, it determines the abnormality and generates the corresponding logic mapping correct or error signal; Analyze the response time of the action execution, determine the abnormality by comparing the signal strength with the threshold, and generate the corresponding signal interference or normal signal, and transmit it to the safety detection information output module; The multi-instruction fusion analysis module is used to analyze the normal state signal, obtain the fusion instruction and the corresponding execution action, determine whether there is an abnormality, and generate a normal or abnormal signal for the fusion instruction; Analyze the abnormal signal of the fusion instruction to determine the specific abnormal situation of the execution action, and analyze the three abnormal phenomena of no execution, partial execution of instructions, and abnormal action respectively to determine the specific cause and transmit it to the safety detection information output module.

2. The remote control safety detection system for a roadheader based on big data according to claim 1 is characterized in that: It also includes an information collection module and a safety detection information output module; An information collection module is used to collect execution actions obtained according to remote control instructions and transmit them to the remote control status analysis module; The safety detection information output module is used to display the correct or incorrect signals of logical mapping, signal interference or normal signals and the specific reasons to the corresponding management personnel.

3. The remote control safety detection system for a roadheader based on big data according to claim 1 is characterized in that: The specific method in which the remote control status analysis module judges the execution action transmitted by the information acquisition module is: Establish a bidirectional mapping table between commands and actions, obtain a response time threshold, match the execution action corresponding to the remote control command with the bidirectional mapping table, and compare the response time corresponding to the remote control command with the response time threshold; If any of the two is abnormal, an abnormal state signal is generated; otherwise, if both are normal, a normal state signal is generated.

4. The remote control safety detection system for a roadheader based on big data according to claim 1 is characterized in that: The specific method by which the instruction exception analysis module analyzes the correctness of the execution action is as follows: Obtain and analyze the command mapping logic of the tunnel boring machine, check the firmware code or configuration file of the remote control terminal, and confirm whether the mapping relationship between the command code and the equipment action is correct. If correct, generate a mapping logic correct signal; otherwise, generate a mapping logic error signal.

5. The remote control safety detection system for a roadheader based on big data according to claim 1 is characterized in that: The specific method in which the instruction abnormality analysis module analyzes the execution action response time is as follows: Use a spectrum analyzer or the terminal's built-in signal monitoring function to check the signal-to-noise ratio (SNR) of the communication frequency band and compare the obtained SNR with the threshold. If the signal strength is lower than the threshold, it indicates that there is signal interference and a signal interference signal is generated. Conversely, if the signal strength is greater than the threshold, it indicates that there is no signal interference and a signal normal signal is generated.

6. The remote control safety detection system for a roadheader based on big data according to claim 1 is characterized in that: The specific method for the multi-instruction fusion analysis module to generate a normal or abnormal signal of the fusion instruction is: Acquire multiple fusion instructions and corresponding execution actions, sort the acquired multiple fusion instructions and their corresponding execution actions according to timestamps and instruction priorities, establish a one-to-one mapping relationship table, and at the same time establish a mutually exclusive instruction rule library to check whether there are contradictory instruction combinations in the fusion instructions. If there is an abnormality in the execution action, a fusion instruction abnormal signal is generated. Conversely, if there is no abnormality in the execution action, a fusion instruction normal signal is generated.

7. The remote control safety detection system for a roadheader based on big data according to claim 1 is characterized in that: The specific method for the multi-instruction fusion analysis module to analyze the abnormal phenomenon of no execution is as follows: Determine whether the antenna is detached. If so, generate the hardware communication link abnormality reason; If the power supply of the remote control terminal or the main control of the device is abnormal, the hardware module fault abnormality reason is generated; If the instruction filter misjudges a normal instruction as an illegal operation, a software logic blocking exception reason is generated; If the format of the multi-command combination data packet is incorrect, a command format error exception reason is generated.

8. The remote control safety detection system for a roadheader based on big data according to claim 1 is characterized in that: The specific method for the multi-instruction fusion analysis module to analyze abnormal phenomena in executing some instructions is as follows: If the instruction is discarded due to insufficient CPU or memory, a hardware resource contention exception is generated; If the priority configuration is wrong, low-priority instructions are preempted by high-priority instructions, the instruction queue processing order is disordered, and the software segmented execution causes subsequent instructions to be interrupted, then the instruction processing defect exception reason is generated; If the cause is a malfunction of the remote control terminal buttons or sensors, an input device failure exception reason is generated.

9. The remote control safety detection system for a roadheader based on big data according to claim 1 is characterized in that: The specific method for the multi-instruction fusion analysis module to analyze abnormal phenomena that produce abnormal actions is as follows: If the instruction field is misread due to a software protocol vulnerability, an instruction parsing error exception will be generated; If the cause is the sticking of hardware contacts such as relays, or inconsistency between instructions and actions, then a hardware signal interference anomaly is generated; If the mutually exclusive logic fails and contradictory instructions are executed at the same time, a logical and mechanical problem abnormality will be generated.

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