Explosion-proof electrical control system and method for underground explosion-proof electric vehicles for mines

Abstract

The present invention relates to the field of mining equipment control technology, and in particular to an explosion-proof electrical control system and method for underground explosion-proof electric vehicles for mining, including a control management platform, a data acquisition unit, an energy supervision unit, a drive evaluation unit, a practical operation supervision unit, a fusion control unit and a management response unit; the present invention analyzes the target explosion-proof electric vehicle from the two perspectives of energy supply and drive to understand the control interference risk of the target explosion-proof electric vehicle, and supervises the control response of the target explosion-proof electric vehicle by means of information feedback, so as to optimize and adjust the control of the target explosion-proof electric vehicle to improve the response timeliness of the target explosion-proof electric vehicle, and performs control performance integration evaluation and analysis on the target explosion-proof electric vehicle by means of information feedback and information fusion to understand the overall control effect of the target explosion-proof electric vehicle, thereby helping to improve the control stability of the target explosion-proof electric vehicle.

Description

Technical Field

[0001] The present invention relates to the technical field of mining equipment control, and in particular to an explosion-proof electrical control system and method for underground mining explosion-proof electric vehicles. Background Art

[0002] The design and development of underground explosion-proof electric vehicles for mines need to meet strict safety technical requirements, including explosion-proof performance, electrical safety, mechanical safety, fire protection and other aspects to ensure safe operation in the special environment of coal mines. The electric control system technology of underground explosion-proof electric vehicles for mines can ensure that underground explosion-proof electric vehicles for mines can provide reliable performance and good operating experience while meeting the explosion-proof safety requirements.

[0003] However, in the existing electronic control system, it is impossible to monitor and analyze the electronic control stability performance of explosion-proof electric vehicles, which leads to an increase in the risk of abnormal electronic control stability of explosion-proof electric vehicles, which is not conducive to the stable control of explosion-proof electric vehicles, and it is impossible to monitor the energy and drive of explosion-proof electric vehicles, and thus it is impossible to adjust the control in time, which leads to an increase in the influence of energy and drive on the control of explosion-proof electric vehicles;

[0004] In view of the above technical defects, a solution is now proposed. Summary of the invention

[0005] The purpose of the present invention is to provide an explosion-proof electrical control system and method for underground explosion-proof electric vehicles for mining, so as to solve the technical defects mentioned above. The present invention analyzes the target explosion-proof electric vehicle from the two perspectives of energy supply and drive to understand the control interference risk of the target explosion-proof electric vehicle, that is, to understand the control stability from the perspective of energy supply, so as to reduce the influence of energy storage batteries on the control stability of the target explosion-proof electric vehicle, and analyzes from the perspective of the drive of the target explosion-proof electric vehicle to ensure the driving safety and stability of the target explosion-proof electric vehicle, and supervises the control response of the target explosion-proof electric vehicle by means of information feedback, so as to optimize and adjust the control of the target explosion-proof electric vehicle to improve the response timeliness of the target explosion-proof electric vehicle, and performs control performance integration evaluation and analysis of the target explosion-proof electric vehicle by means of information feedback and information fusion to understand the overall control effect of the target explosion-proof electric vehicle, thereby helping to improve the control stability of the target explosion-proof electric vehicle.

[0006] The purpose of the present invention can be achieved by the following technical solutions: An explosion-proof electrical control system for underground explosion-proof electric vehicles for mining, including a control management platform, a data acquisition unit, an energy supervision unit, a drive evaluation unit, a practical operation supervision unit, a fusion control unit and a management response unit;

[0007] The data acquisition unit is used to collect energy supply risk data and driving status data of the target explosion-proof electric vehicle, and send the energy supply risk data and driving status data to the energy supervision unit and the driving evaluation unit respectively;

[0008] After receiving the energy supply risk data, the energy supervision unit immediately performs energy supply safety supervision assessment and analysis on the energy supply risk data, sends the obtained normal signal to the practical supervision unit, and sends the obtained risk signal to the management response unit;

[0009] After receiving the driving state data, the driving evaluation unit immediately performs driving safety supervision feedback analysis on the driving state data, sends the obtained stability signal to the practical operation supervision unit, and sends the obtained alarm signal to the management response unit;

[0010] The practical operation supervision unit is used to collect the target explosion-proof electric vehicle control risk data, and perform operation control supervision evaluation and analysis on the control risk data, and compare and analyze the obtained control deviation value and control trend risk value to obtain an optimization signal;

[0011] The fusion control unit is used to perform integrated evaluation and analysis of the control performance of the target explosion-proof electric vehicle, and send the obtained qualified signals and unqualified signals to the management response unit.

[0012] Preferably, the energy supply safety supervision assessment and analysis process of the energy supervision unit is as follows:

[0013] S1: Collect the working time period corresponding to the explosion-proof electric vehicle and set it as the time threshold. At the same time, set the explosion-proof electric vehicle as the target explosion-proof electric vehicle, divide the time threshold into i sub-time periods, i is a natural number greater than zero, and obtain the energy supply risk data of the target explosion-proof electric vehicle in each sub-time period. The energy supply risk data includes the actual energy supply value and the energy evaluation value, and compare and analyze the actual energy supply value and the energy evaluation value with the stored preset actual energy supply value and energy evaluation value threshold. If the actual energy supply value is less than the preset actual energy supply value threshold, and the energy evaluation value is less than the preset energy evaluation value threshold, then the corresponding sub-time period is determined to be a normal time period. If the actual energy supply value is greater than or equal to the preset actual energy supply value threshold, or the energy evaluation value is greater than or equal to the preset energy evaluation value threshold, then the corresponding sub-time period is determined to be a risk time period, and the ratio between the number corresponding to the risk time period and the number corresponding to the normal time period is set as the time period evaluation coefficient;

[0014] S2: Obtain the state risk value of the target explosion-proof electric vehicle energy storage battery within the time threshold, where the state risk value represents the sum of the number of overcharges and overdischarges during the historical use of the energy storage battery;

[0015] S3: The time period assessment coefficient and the state risk value are labeled SP and ZF respectively, and the time period assessment coefficient SP and the state risk value ZF are substituted into the formula to obtain the control interference assessment coefficient N, and the control interference assessment coefficient N is compared and analyzed with the preset control interference assessment coefficient threshold value stored in the internal input:

[0016] If the ratio between the control disturbance evaluation coefficient N and the preset control disturbance evaluation coefficient threshold is less than 1, a normal signal is generated;

[0017] If the ratio between the control disturbance assessment coefficient N and the preset control disturbance assessment coefficient threshold is greater than or equal to 1, a risk signal is generated.

[0018] Preferably, the actual energy supply value represents the overlapping time length between the time length corresponding to the average temperature rise rate of the energy storage battery exceeding the preset temperature rise rate average threshold and the time length corresponding to the average discharge rate exceeding the preset discharge rate average threshold; the energy evaluation value represents the sum of the values ​​corresponding to the bulge area and the line port oxidation area in the appearance feature image of the energy storage battery.

[0019] Preferably, the driving safety supervision feedback analysis process of the driving evaluation unit is as follows:

[0020] The driving state data of the target explosion-proof electric vehicle within the time threshold is obtained. The driving state data includes an operation evaluation value and a cooling evaluation value. The operation evaluation value and the cooling evaluation value are compared and analyzed with the preset operation evaluation value threshold and the preset cooling evaluation value threshold stored in the internal input:

[0021] If the operation evaluation value is less than the preset operation evaluation value threshold, and the cooling evaluation value is less than the preset cooling evaluation value threshold, a stable signal is generated;

[0022] If the operation evaluation value is greater than or equal to the preset operation evaluation value threshold, or the cooling evaluation value is greater than or equal to the preset cooling evaluation value threshold, an alarm signal is generated;

[0023] The operation evaluation value indicates the duration of the overlap of the value corresponding to the operation performance parameter of the explosion-proof motor of the target explosion-proof electric vehicle exceeding the preset threshold, and the operation performance parameter indicates the average value of the vibration amplitude and the average value of the abnormal sound;

[0024] The cooling evaluation value indicates the duration corresponding to the average heat dissipation rate of the explosion-proof motor of the target explosion-proof electric vehicle being lower than the preset heat dissipation rate average threshold.

[0025] Preferably, the operation control supervision evaluation and analysis process of the practical supervision unit is as follows:

[0026] T1: Obtain the control risk data of the target explosion-proof electric vehicle within the time threshold. The control risk data includes the control deviation value and the total number of historical controls. Obtain the control response time corresponding to a single control. Establish a rectangular coordinate system with the number as the X-axis and the control response time as the Y-axis. Draw the control response time curve by plotting points. Then, obtain the proportion of the number corresponding to the rising segment from the control response time curve and set it as the control trend risk value.

[0027] T2: The control deviation value indicates the part where the actual control response time of the target explosion-proof electric vehicle is greater than the set control response time. The actual control response time indicates the time between the time when the control command is sent and the time when the target explosion-proof electric vehicle executes the control command.

[0028] T3: Compare and analyze the control deviation value and control trend risk value with the preset control deviation value and control trend risk value thresholds stored in the internal storage:

[0029] If the control deviation value is less than the preset control deviation value threshold, and the control trend risk value is less than the preset control trend risk value threshold, no signal is generated;

[0030] If the control deviation value is greater than or equal to the preset control deviation value threshold, or the control trend risk value is greater than or equal to the preset control trend risk value threshold, an optimization signal is generated.

[0031] Preferably, the control performance integration evaluation and analysis process of the fusion control unit is as follows:

[0032] Obtain the control interference evaluation coefficient N corresponding to the normal signal within the time threshold, and at the same time obtain the operation evaluation value and cooling evaluation value corresponding to the stable signal within the time threshold, as well as obtain the control deviation value and control trend risk value within the time threshold, and label the operation evaluation value, cooling evaluation value, control deviation value and control trend risk value as YP, LQ, TP and TQ respectively;

[0033] The control performance evaluation coefficient R is obtained according to the formula, and the control performance evaluation coefficient R is compared and analyzed with the preset control performance evaluation coefficient threshold value stored in the internal input:

[0034] If the ratio between the control performance evaluation coefficient R and the preset control performance evaluation coefficient threshold is less than 1, a qualified signal is generated;

[0035] If the ratio between the control performance evaluation coefficient R and the preset control performance evaluation coefficient threshold is greater than or equal to 1, a failure signal is generated.

[0036] The beneficial effects of the present invention are as follows:

[0037] (1) The present invention analyzes the target explosion-proof electric vehicle from two perspectives: energy supply and drive, so as to understand the control interference risk of the target explosion-proof electric vehicle, that is, to perform energy supply safety supervision assessment analysis on energy supply risk data, so as to understand the control stability from the perspective of energy supply, so as to reduce the influence of energy storage batteries on the control stability of the target explosion-proof electric vehicle, thereby helping to improve the control reliability of the target explosion-proof electric vehicle, and to perform drive safety supervision feedback analysis on drive status data, so as to analyze from the perspective of the drive of the target explosion-proof electric vehicle, so as to ensure the drive safety and stability of the target explosion-proof electric vehicle, thereby helping to accurately control the target explosion-proof electric vehicle;

[0038] (2) The present invention monitors the control response of the target explosion-proof electric vehicle by means of information feedback, so as to optimize and adjust the control of the target explosion-proof electric vehicle to improve the timeliness of the response of the target explosion-proof electric vehicle, and performs integrated evaluation and analysis of the control performance of the target explosion-proof electric vehicle by means of information feedback and information fusion to understand the overall control effect of the target explosion-proof electric vehicle, thereby helping to improve the control stability of the target explosion-proof electric vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The present invention will be further described below in conjunction with the accompanying drawings;

[0040] Figure 1 It is a flowchart of the system of the present invention;

[0041] Figure 2 It is a reference diagram for analysis of the method of the present invention. DETAILED DESCRIPTION

[0042] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0043] Embodiment 1:

[0044] See also Figure 1 to Figure 2As shown, the present invention is an explosion-proof electrical control system for underground explosion-proof electric vehicles for mining, including a control management platform, a data acquisition unit, an energy supervision unit, a drive evaluation unit, a practical operation supervision unit, a fusion control unit and a management response unit. The control management platform is connected to the data acquisition unit in a one-way communication manner, the data acquisition unit is connected to the energy supervision unit and the drive evaluation unit in a one-way communication manner, the energy supervision unit and the drive evaluation unit are connected to the practical operation supervision unit, the fusion control unit and the management response unit in a one-way communication manner, the practical operation supervision unit is connected to the fusion control unit in a one-way communication manner, and the fusion control unit is connected to the management response unit in a one-way communication manner;

[0045] When the control management platform detects that any explosion-proof electric vehicle is working, an operation management instruction is generated and sent to the data acquisition unit. The data acquisition unit immediately collects the energy supply risk data and driving status data of the explosion-proof electric vehicle, and sends the energy supply risk data and driving status data to the energy supervision unit and the driving evaluation unit respectively. After receiving the energy supply risk data, the energy supervision unit immediately performs energy supply safety supervision evaluation and analysis on the energy supply risk data, so as to understand the control stability from the perspective of energy supply, so as to rationally manage the energy storage battery, so as to reduce the influence of the energy storage battery on the control stability of the explosion-proof electric vehicle, thereby helping to improve the control reliability of the explosion-proof electric vehicle. The specific energy supply safety supervision evaluation and analysis process is as follows:

[0046] Collect the working time period corresponding to the explosion-proof electric vehicle, and set it as the time threshold, and set the explosion-proof electric vehicle as the target explosion-proof electric vehicle, divide the time threshold into i sub-time periods, i is a natural number greater than zero, and obtain the energy supply risk data of the target explosion-proof electric vehicle in each sub-time period, the energy supply risk data includes the actual energy supply value and the energy evaluation value, and compare and analyze the actual energy supply value and the energy evaluation value with the stored preset actual energy supply value and energy evaluation value threshold. If the actual energy supply value is less than the preset actual energy supply value threshold, and the energy evaluation value is less than the preset energy evaluation value threshold, then the corresponding sub-time period is determined to be a normal time period. If the actual energy supply value is greater than or equal to the preset actual energy supply value threshold, or the energy evaluation value is greater than or equal to the preset energy evaluation value threshold, then the corresponding sub-time period is determined to be a risk time period, and the ratio between the number corresponding to the risk time period and the number corresponding to the normal time period is set as the time period evaluation coefficient. It should be noted that the larger the value of the time period evaluation coefficient, the greater the risk of the target explosion-proof electric vehicle energy storage battery, and the greater the risk of control disturbance of the target explosion-proof electric vehicle;

[0047] The state risk value of the target explosion-proof electric vehicle energy storage battery within the time threshold is obtained. The state risk value represents the sum of the number of overcharges and the number of over-discharges during the historical use of the energy storage battery. It should be noted that the larger the value of the state risk value, the greater the risk of damage to the energy storage battery and the greater the interference to the control;

[0048] The period assessment coefficient and the state risk value are labeled SP and ZF respectively. Substitute the period assessment coefficient SP and the state risk value ZF into the formula The control interference assessment coefficient is obtained, where a1 and a2 are the preset proportional factor coefficients of the time period assessment coefficient SP and the state risk value ZF respectively. The proportional factor coefficient is used to correct the deviation of various parameters in the formula calculation process, so as to make the calculation result more accurate. a3 is the preset correction factor coefficient. a1, a2 and a3 are all greater than zero. N is the control interference assessment coefficient. The control interference assessment coefficient N is compared and analyzed with the preset control interference assessment coefficient threshold value stored in the internal input:

[0049] If the ratio between the control interference assessment coefficient N and the preset control interference assessment coefficient threshold is less than 1, a normal signal is generated and sent to the practical operation supervision unit;

[0050] If the ratio between the control interference assessment coefficient N and the preset control interference assessment coefficient threshold is greater than or equal to 1, a risk signal is generated and sent to the management response unit. After receiving the risk signal, the management response unit immediately performs a preset warning operation corresponding to the risk signal, that is, the preset warning operation corresponding to the risk signal is "the target explosion-proof electric vehicle is marked as red", so as to manage and maintain the internal energy storage battery of the target explosion-proof electric vehicle according to the information feedback, so as to ensure the energy supply stability of the energy storage battery, thereby helping to improve the control stability of the target explosion-proof electric vehicle;

[0051] In the embodiment of the present invention, the actual energy supply value indicates the overlap time between the time corresponding to the average value of the temperature rise rate of the energy storage battery exceeding the preset temperature rise rate average threshold and the time corresponding to the average value of the discharge rate exceeding the preset discharge rate average threshold. It should be noted that the actual energy supply value is a quantitative value obtained by comprehensive quantitative evaluation from the perspective of energy supply performance. The actual energy supply value is an influencing parameter reflecting the energy supply performance of the energy storage battery. The larger the value of the actual energy supply value, the greater the risk of abnormal energy supply stability of the energy storage battery.

[0052] In the embodiment of the present invention, the energy evaluation value represents the sum of the values ​​corresponding to the bulge area and the line port oxidation area in the appearance feature image of the energy storage battery. It should be noted that the energy evaluation value is a quantitative value obtained by comprehensive quantitative evaluation from the perspective of appearance performance. The larger the value of the energy evaluation value, the greater the risk of energy storage battery failure, and the greater the control impact on the target explosion-proof electric vehicle;

[0053] After receiving the driving status data, the driving evaluation unit immediately performs driving safety supervision feedback analysis on the driving status data, so as to analyze from the perspective of the target explosion-proof electric vehicle drive to understand the operation of the target explosion-proof electric vehicle explosion-proof motor. The specific driving safety supervision feedback analysis process is as follows:

[0054] Acquire driving state data of the target explosion-proof electric vehicle within a time threshold, the driving state data including an operation evaluation value and a cooling evaluation value;

[0055] In the embodiment of the present invention, the operation evaluation value indicates the duration of the overlap of the numerical value corresponding to the operation performance parameter of the explosion-proof motor of the target explosion-proof electric vehicle exceeding the preset threshold value, and the operation performance parameter indicates the average value of the vibration amplitude, the average value of the abnormal sound, etc. It should be noted that the operation evaluation value is an influencing parameter reflecting the operation state of the explosion-proof motor;

[0056] In the embodiment of the present invention, the cooling evaluation value indicates the duration corresponding to the average heat dissipation rate of the explosion-proof motor of the target explosion-proof electric vehicle being lower than the preset heat dissipation rate average threshold. It should be noted that the cooling evaluation value is an influencing parameter reflecting the operating state of the explosion-proof motor;

[0057] Compare and analyze the operation evaluation value and cooling evaluation value with the preset operation evaluation value threshold and preset cooling evaluation value threshold that are stored internally:

[0058] If the operation evaluation value is less than the preset operation evaluation value threshold, and the cooling evaluation value is less than the preset cooling evaluation value threshold, a stabilization signal is generated and sent to the practical operation supervision unit;

[0059] If the operation evaluation value is greater than or equal to the preset operation evaluation value threshold, or the cooling evaluation value is greater than or equal to the preset cooling evaluation value threshold, an alarm signal is generated and sent to the management response unit. After receiving the alarm signal, the management response unit immediately performs the preset warning operation corresponding to the alarm signal, that is, the preset warning operation corresponding to the alarm signal is "the target explosion-proof electric vehicle is marked as yellow", so as to manage and maintain the explosion-proof motor according to the information feedback, so as to ensure the driving safety and stability of the target explosion-proof electric vehicle, thereby helping to accurately control the target explosion-proof electric vehicle and improve the control efficiency of the target explosion-proof electric vehicle.

[0060] Embodiment 2:

[0061] When normal signals and stable signals are generated, the practical supervision unit collects the control risk data of the target explosion-proof electric vehicle, and performs operation control supervision evaluation and analysis on the control risk data to understand the control response of the target explosion-proof electric vehicle, so as to optimize and adjust the control of the target explosion-proof electric vehicle to improve the timeliness of the response of the target explosion-proof electric vehicle. The specific operation control supervision evaluation and analysis process is as follows:

[0062] The control risk data of the target explosion-proof electric vehicle within the time threshold is obtained. The control risk data includes the control deviation value and the total number of historical controls. The control response time corresponding to a single control is obtained. A rectangular coordinate system is established with the number of times as the X-axis and the control response time as the Y-axis. The control response time curve is drawn by plotting points. Then, the proportion value of the number corresponding to the rising segment is obtained from the control response time curve, and it is set as the control trend risk value. It should be noted that the larger the value of the control trend risk value, the greater the risk of abnormal control of the target explosion-proof electric vehicle and the greater the risk of response delay;

[0063] In the embodiment of the present invention, the control deviation value indicates the portion where the actual control response time of the target explosion-proof electric vehicle is greater than the set control response time, and the actual control response time indicates the time between the time when the control instruction is sent and the time when the target explosion-proof electric vehicle executes the control instruction. It should be noted that the analysis is performed from the perspective of the control response of the target explosion-proof electric vehicle to understand the control performance of the target explosion-proof electric vehicle, so as to ensure the control effect of the entire target explosion-proof electric vehicle;

[0064] Compare and analyze the control deviation value and control trend risk value with the preset control deviation value and control trend risk value thresholds stored in the internal entry:

[0065] If the control deviation value is less than the preset control deviation value threshold, and the control trend risk value is less than the preset control trend risk value threshold, no signal is generated;

[0066] If the control deviation value is greater than or equal to the preset control deviation value threshold, or the control trend risk value is greater than or equal to the preset control trend risk value threshold, an optimization signal is generated, and the optimization signal is sent to the management response unit via the fusion control unit. After receiving the optimization signal, the management response unit immediately displays the preset warning text corresponding to the optimization signal, that is, the preset warning text corresponding to the optimization signal is "control optimization", so as to optimize and adjust the explosion-proof motor control network according to the information feedback, so as to improve the control efficiency of the target explosion-proof electric vehicle;

[0067] When normal signals and stable signals are generated, the fusion control unit performs control performance integration evaluation and analysis on the target explosion-proof electric vehicle from the perspective of information feedback and information fusion to understand the overall control effect of the target explosion-proof electric vehicle. The specific control performance integration evaluation and analysis process is as follows:

[0068] Obtain the control interference evaluation coefficient N corresponding to the normal signal within the time threshold, and at the same time obtain the operation evaluation value and cooling evaluation value corresponding to the stable signal within the time threshold, as well as obtain the control deviation value and control trend risk value within the time threshold, and label the operation evaluation value, cooling evaluation value, control deviation value and control trend risk value as YP, LQ, TP and TQ respectively;

[0069] According to the formula The control performance evaluation coefficient is obtained, where f1, f2, f3, f4 and f5 are respectively the preset weight factor coefficients of the operation evaluation value, the cooling evaluation value, the control deviation value, the control interference evaluation coefficient and the control trend risk value, f1, f2, f3, f4 and f5 are all greater than zero, and R is the control performance evaluation coefficient. The control performance evaluation coefficient R is compared and analyzed with the preset control performance evaluation coefficient threshold value stored in the internal input:

[0070] If the ratio between the control performance evaluation coefficient R and the preset control performance evaluation coefficient threshold is less than 1, a qualified signal is generated;

[0071] If the ratio between the control performance evaluation coefficient R and the preset control performance evaluation coefficient threshold is greater than or equal to 1, an unqualified signal is generated, and the qualified signal and the unqualified signal are sent to the management response unit. After receiving the qualified signal and the unqualified signal, the management response unit immediately displays the preset warning texts corresponding to the qualified signal and the unqualified signal, that is, the preset warning text corresponding to the qualified signal is "stability performance qualified", and the preset warning text corresponding to the unqualified signal is "stability performance unqualified", so as to adjust the overall control of the target explosion-proof electric vehicle according to the information feedback to ensure the overall control effect of the target explosion-proof electric vehicle.

[0072] Embodiment three:

[0073] The explosion-proof electrical control method of underground explosion-proof electric vehicle for mining includes the following steps:

[0074] Step 1: Collect the energy supply risk data and driving status data of the target explosion-proof electric vehicle and transmit them to step 2 and step 3;

[0075] Step 2: It is used to conduct energy supply safety supervision assessment and analysis on energy supply risk data, and compare and analyze the obtained control interference assessment coefficient N. If a normal signal is obtained, it proceeds to step 4. If a risk signal is obtained, it feeds back an early warning.

[0076] Step 3: It is used to conduct drive safety supervision feedback analysis on the drive status data, and to judge and process the obtained operation evaluation value and cooling evaluation value. If a stable signal is obtained, it proceeds to step 4. If an alarm signal is obtained, it feeds back an early warning.

[0077] Step 4: Collect the target explosion-proof electric vehicle control risk data through information feedback, and conduct operation control supervision evaluation and analysis on the control risk data. If an optimization signal is obtained, feedback warning is given;

[0078] Step 5: Conduct control performance integration evaluation and analysis through information feedback and fusion, and conduct judgment and analysis on the control performance evaluation coefficient R, and feedback processing on the qualified and unqualified signals obtained;

[0079] In summary, the present invention analyzes the target explosion-proof electric vehicle from the two perspectives of energy supply and drive to understand the control interference risk of the target explosion-proof electric vehicle, that is, performs energy supply safety supervision evaluation analysis on the energy supply risk data, so as to understand the control stability from the perspective of energy supply, so as to rationally manage the energy storage battery, so as to reduce the influence of the energy storage battery on the control stability of the target explosion-proof electric vehicle, thereby helping to improve the control reliability of the target explosion-proof electric vehicle, and performs drive safety supervision feedback analysis on the drive state data, so as to analyze from the perspective of the drive of the target explosion-proof electric vehicle, so as to understand the operation of the explosion-proof motor of the target explosion-proof electric vehicle, so as to ensure the driving safety and stability of the target explosion-proof electric vehicle, thereby helping to accurately control the target explosion-proof electric vehicle, and supervise the control response of the target explosion-proof electric vehicle by means of information feedback, so as to optimize and adjust the control of the target explosion-proof electric vehicle, so as to improve the response timeliness of the target explosion-proof electric vehicle, and perform control performance integration evaluation analysis on the target explosion-proof electric vehicle by means of information feedback and information fusion, so as to understand the overall control effect of the target explosion-proof electric vehicle, thereby helping to improve the control stability of the target explosion-proof electric vehicle.

[0080] The threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by technicians in this field for each group of sample data; as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0081] The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula that is close to the actual value. The coefficients in the formula are set by technical personnel in this field according to actual conditions. The above is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited to this. Any technical personnel familiar with the technical field within the technical scope disclosed by the present invention, according to the technical solution and the inventive concept of the present invention, make equivalent replacement or change, which should be covered within the protection scope of the present invention.

Claims

1. Explosion-proof electrical control system for underground explosion-proof electric vehicles for mines, characterized in that: It includes control management platform, data acquisition unit, energy supervision unit, drive evaluation unit, practical operation supervision unit, fusion control unit and management response unit; The data acquisition unit is used to collect energy supply risk data and driving status data of the target explosion-proof electric vehicle, and send the energy supply risk data and driving status data to the energy supervision unit and the driving evaluation unit respectively; After receiving the energy supply risk data, the energy supervision unit immediately performs energy supply safety supervision assessment and analysis on the energy supply risk data, sends the obtained normal signal to the practical supervision unit, and sends the obtained risk signal to the management response unit; After receiving the driving state data, the driving evaluation unit immediately performs driving safety supervision feedback analysis on the driving state data, sends the obtained stability signal to the practical operation supervision unit, and sends the obtained alarm signal to the management response unit; The practical operation supervision unit is used to collect the target explosion-proof electric vehicle control risk data, and perform operation control supervision evaluation and analysis on the control risk data, and compare and analyze the obtained control deviation value and control trend risk value to obtain an optimization signal; The fusion control unit is used to perform integrated evaluation and analysis of the control performance of the target explosion-proof electric vehicle, and send the obtained qualified signals and unqualified signals to the management response unit.

2. The explosion-proof electrical control system for underground explosion-proof electric vehicles for mines according to claim 1 is characterized in that: The energy supply safety supervision assessment and analysis process of the energy supervision unit is as follows: S1: Collect the working time period corresponding to the explosion-proof electric vehicle and set it as the time threshold. At the same time, set the explosion-proof electric vehicle as the target explosion-proof electric vehicle, divide the time threshold into i sub-time periods, i is a natural number greater than zero, and obtain the energy supply risk data of the target explosion-proof electric vehicle in each sub-time period. The energy supply risk data includes the actual energy supply value and the energy evaluation value, and compare and analyze the actual energy supply value and the energy evaluation value with the stored preset actual energy supply value and energy evaluation value threshold. If the actual energy supply value is less than the preset actual energy supply value threshold, and the energy evaluation value is less than the preset energy evaluation value threshold, then the corresponding sub-time period is determined to be a normal time period. If the actual energy supply value is greater than or equal to the preset actual energy supply value threshold, or the energy evaluation value is greater than or equal to the preset energy evaluation value threshold, then the corresponding sub-time period is determined to be a risk time period, and the ratio between the number corresponding to the risk time period and the number corresponding to the normal time period is set as the time period evaluation coefficient; S2: Obtain the state risk value of the target explosion-proof electric vehicle energy storage battery within the time threshold, where the state risk value represents the sum of the number of overcharges and overdischarges during the historical use of the energy storage battery; S3: Label the period assessment coefficient and state risk value as SP and ZF respectively, and substitute the period assessment coefficient SP and state risk value ZF into the formula The control interference assessment coefficient N is obtained, a1 and a2 are respectively the preset proportional factor coefficients of the time period assessment coefficient SP and the state risk value ZF, a3 is the preset correction factor coefficient, a1, a2 and a3 are all greater than zero, and the control interference assessment coefficient N is compared and analyzed with the preset control interference assessment coefficient threshold value stored in the internal entry: If the ratio between the control disturbance evaluation coefficient N and the preset control disturbance evaluation coefficient threshold is less than 1, a normal signal is generated; If the ratio between the control disturbance assessment coefficient N and the preset control disturbance assessment coefficient threshold is greater than or equal to 1, a risk signal is generated.

3. The explosion-proof electrical control system for underground explosion-proof electric vehicles for mines according to claim 2 is characterized in that: The actual energy supply value represents the overlapping time length between the time length corresponding to the average temperature rise rate of the energy storage battery exceeding the preset temperature rise rate average threshold and the time length corresponding to the average discharge rate exceeding the preset discharge rate average threshold; the energy evaluation value represents the sum of the values ​​corresponding to the bulge area and the line port oxidation area in the appearance feature image of the energy storage battery.

4. The explosion-proof electrical control system for underground explosion-proof electric vehicles for mines according to claim 1 is characterized in that: The driving safety supervision feedback analysis process of the driving evaluation unit is as follows: The driving state data of the target explosion-proof electric vehicle within the time threshold is obtained. The driving state data includes an operation evaluation value and a cooling evaluation value. The operation evaluation value and the cooling evaluation value are compared and analyzed with the preset operation evaluation value threshold and the preset cooling evaluation value threshold stored in the internal input: If the operation evaluation value is less than the preset operation evaluation value threshold, and the cooling evaluation value is less than the preset cooling evaluation value threshold, a stable signal is generated; If the operation evaluation value is greater than or equal to the preset operation evaluation value threshold, or the cooling evaluation value is greater than or equal to the preset cooling evaluation value threshold, an alarm signal is generated; The operation evaluation value indicates the duration of the overlap of the value corresponding to the operation performance parameter of the explosion-proof motor of the target explosion-proof electric vehicle exceeding the preset threshold, and the operation performance parameter indicates the average value of the vibration amplitude and the average value of the abnormal sound; The cooling evaluation value indicates the duration corresponding to the average heat dissipation rate of the explosion-proof motor of the target explosion-proof electric vehicle being lower than the preset heat dissipation rate average threshold.

5. The explosion-proof electrical control system for underground explosion-proof electric vehicles for mines according to claim 1 is characterized in that: The operation control supervision assessment and analysis process of the practical supervision unit is as follows: T1: Obtain the control risk data of the target explosion-proof electric vehicle within the time threshold. The control risk data includes the control deviation value and the total number of historical controls. Obtain the control response time corresponding to a single control. Establish a rectangular coordinate system with the number as the X-axis and the control response time as the Y-axis. Draw the control response time curve by plotting points. Then, obtain the proportion of the number corresponding to the rising segment from the control response time curve and set it as the control trend risk value. T2: The control deviation value indicates the part where the actual control response time of the target explosion-proof electric vehicle is greater than the set control response time. The actual control response time indicates the time between the time when the control command is sent and the time when the target explosion-proof electric vehicle executes the control command. T3: Compare and analyze the control deviation value and control trend risk value with the preset control deviation value and control trend risk value thresholds stored in the internal storage: If the control deviation value is less than the preset control deviation value threshold, and the control trend risk value is less than the preset control trend risk value threshold, no signal is generated; If the control deviation value is greater than or equal to the preset control deviation value threshold, or the control trend risk value is greater than or equal to the preset control trend risk value threshold, an optimization signal is generated.

6. The explosion-proof electrical control system for underground explosion-proof electric vehicles for mines according to claim 1 is characterized in that: The control performance integration evaluation and analysis process of the fusion control unit is as follows: Obtain the control interference evaluation coefficient N corresponding to the normal signal within the time threshold, and at the same time obtain the operation evaluation value and cooling evaluation value corresponding to the stable signal within the time threshold, as well as obtain the control deviation value and control trend risk value within the time threshold, and label the operation evaluation value, cooling evaluation value, control deviation value and control trend risk value as YP, LQ, TP and TQ respectively; According to the formula The control performance evaluation coefficient R is obtained, where f1, f2, f3, f4 and f5 are respectively the preset weight factor coefficients of the operation evaluation value, the cooling evaluation value, the control deviation value, the control interference evaluation coefficient and the control trend risk value, and f1, f2, f3, f4 and f5 are all greater than zero. The control performance evaluation coefficient R is compared and analyzed with the preset control performance evaluation coefficient threshold value stored in the internal input: If the ratio between the control performance evaluation coefficient R and the preset control performance evaluation coefficient threshold is less than 1, a qualified signal is generated; If the ratio between the control performance evaluation coefficient R and the preset control performance evaluation coefficient threshold is greater than or equal to 1, a failure signal is generated.

7. An explosion-proof electrical control method for underground explosion-proof electric vehicles for mines, the method being applied to an explosion-proof electrical control system for underground explosion-proof electric vehicles for mines as described in any one of items 3-6, characterized in that: The following steps are involved: Step 1: Collect the energy supply risk data and driving status data of the target explosion-proof electric vehicle and transmit them to step 2 and step 3; Step 2: It is used to conduct energy supply safety supervision assessment and analysis on energy supply risk data, and compare and analyze the obtained control interference assessment coefficient N. If a normal signal is obtained, it proceeds to step 4. If a risk signal is obtained, it feeds back an early warning. Step 3: It is used to conduct drive safety supervision feedback analysis on the drive status data, and to judge and process the obtained operation evaluation value and cooling evaluation value. If a stable signal is obtained, it proceeds to step 4. If an alarm signal is obtained, it feeds back an early warning. Step 4: Collect the target explosion-proof electric vehicle control risk data through information feedback, and conduct operation control supervision evaluation and analysis on the control risk data. If an optimization signal is obtained, feedback warning is given; Step 5: Conduct integrated evaluation and analysis of control performance through information feedback and fusion, and conduct judgment and analysis on the control performance evaluation coefficient R, and perform feedback processing on the qualified and unqualified signals obtained.

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