Safety risk early warning system and method for workshop production

Abstract

The invention relates to the technical field of workshop safety monitoring, in particular to a safety risk early warning system and method for workshop production, and the system comprises a data sensor unit which is used for collecting and uploading the real-time operation data of workshop production equipment; the database is used for acquiring historical operation data of workshop production equipment; the data acquisition unit is used for acquiring real-time operation data and historical fault data and then sending the data to the risk assessment unit; the risk assessment unit is used for performing equipment fault judgment and safety risk assessment on the corresponding workshop production equipment in combination with the real-time operation data and the historical fault data; and the safety early warning unit is used for implementing fault alarm or safety early warning according to the equipment fault judgment result or the safety risk assessment result. Based on the technical scheme, the attention degree of the equipment prone to faults can be improved, faults of the equipment can be found in time, the fault equipment can be checked and maintained, and the production efficiency is prevented from being affected by the equipment faults.

Description

Technical Field

[0001] The present invention relates to the technical field of workshop safety monitoring, and in particular to a safety risk early warning system and method for workshop production. Background Art

[0002] The workshop is the core place for product manufacturing. Through precise equipment and processes, raw materials are processed into products that meet design requirements. The workshop production safety risk warning can help enterprises timely discover potential safety hazards and risks, take timely measures to prevent and manage them, and ensure the health and safety of employees. Through the workshop production safety warning, factors that may lead to accidents can be discovered and predicted in advance, and corresponding safety measures can be taken to avoid accidents, ensure the safety and stability of the production process, and enhance the company's reputation and image. The workshop production safety risk warning can help enterprises timely discover, analyze and solve possible problems and hidden dangers in the production process, effectively manage and control risks, and improve production efficiency.

[0003] The Chinese invention patent document with the prior art application number 2023107466764 discloses a cement clinker production safety intelligent management and control system based on data analysis, which includes an intelligent management and control platform, which is communicatively connected to an explosion monitoring module, a hidden danger analysis module, a decision analysis module, and a storage module; the explosion monitoring module is used to perform explosion monitoring and analysis on the cement clinker production workshop; the cement clinker production workshop is divided into several monitoring areas and numbers are assigned to the monitoring areas; the cement clinker production workshop can be monitored and analyzed, and the explosion coefficient is obtained by analyzing and calculating the explosion-related parameters of each monitoring area in the cement clinker production workshop, and a warning is issued in time when there is an explosion risk in the monitoring area. However, in this prior art, the explosion risk is only warned by the explosion coefficient of the monitoring area, and the safety risk assessment of the equipment in the production workshop is not performed, which may affect the workshop production efficiency due to equipment failure. Summary of the invention

[0004] The purpose of the present invention is to address the above-mentioned problems and to propose a safety risk warning system and method for workshop production, which is used to solve the technical problem that the prior art only warns of explosion risks by monitoring the explosion coefficient in the area, but does not conduct safety risk assessment on the equipment in the production workshop, which may affect the production efficiency of the workshop due to equipment failure.

[0005] The technical solutions adopted to achieve the above purpose are as follows:

[0006] A safety risk early warning system for workshop production includes a database, a data acquisition unit, a data sensor unit, a risk assessment unit and a safety early warning unit. The data sensor unit is communicatively connected to the data acquisition unit, and is used to collect and upload real-time operation data of workshop production equipment. The database is communicatively connected to the data acquisition unit, and is used for historical operation data of workshop production equipment, including historical fault data. The data acquisition unit is communicatively connected to the risk assessment unit, and is used to obtain real-time operation data and historical fault data from the database and the data sensor unit, respectively, and send the real-time operation data and historical fault data to the risk assessment unit. The risk assessment unit is used to perform equipment fault judgment and safety risk assessment on the corresponding workshop production equipment in combination with the real-time operation data and the historical fault data. The safety early warning unit is communicatively connected to the risk assessment unit, and is used to implement fault alarm or safety early warning according to the equipment fault judgment result or the safety risk assessment result.

[0007] A safety risk early warning method for workshop production, using the above-mentioned safety risk early warning system for workshop production, comprises the following steps:

[0008] S1, using the historical operation data of the workshop production equipment in the database, including historical fault data, the historical fault data includes the number of equipment failures, fault types and fault handling methods;

[0009] S2, using the data acquisition unit to obtain historical fault data in the database, and uploading the historical fault data to the risk assessment unit;

[0010] S3, using the risk assessment unit to classify the corresponding workshop production equipment based on the historical fault data to obtain an equipment classification table; according to the equipment classification table, the collection frequency of the real-time operation data of the workshop production equipment is obtained;

[0011] S4, the risk assessment unit sends a real-time data collection instruction to the data collection unit based on the current collection frequency;

[0012] S5, after receiving the real-time data collection instruction, the data collection unit cooperates with the data sensor unit to collect and upload the real-time operation data of the workshop production equipment according to the corresponding collection frequency, including real-time temperature, real-time pressure and real-time current;

[0013] S6, using the risk assessment unit to determine whether the corresponding workshop production equipment has a fault based on the real-time operation data; if so, an alarm signal is generated and sent to the safety warning unit, and then the process goes to step S8; if not, the risk level of the corresponding workshop production equipment is assessed, and then the process goes to step S7;

[0014] S7, judging whether there is a safety risk for the corresponding workshop production equipment according to the risk level assessment result; if so, generating an early warning signal and sending it to the safety early warning unit, and then proceeding to step S8; if not, updating the collection frequency of the real-time operation data of the workshop production equipment based on the risk level assessment result, and then returning to step S4;

[0015] S8, implement countermeasures according to the type of signal obtained by the safety warning unit, namely: when the safety warning unit receives an alarm signal, it issues a fault alarm, and the equipment maintenance personnel inspect the faulty equipment according to the alarm signal, determine the fault type and fault handling method, and update the historical fault data in the database; when the safety warning unit receives a warning signal, it issues a safety warning, and the equipment maintenance personnel inspect and maintain the corresponding workshop production equipment based on the warning signal.

[0016] Preferably, in step S3, classifying the corresponding workshop production equipment includes the following steps:

[0017] Set the equipment classification threshold range based on equipment maintenance experience;

[0018] Obtain the number of failures of workshop production equipment based on historical failure data;

[0019] Compare the number of failures with the equipment classification threshold range; when the number of failures is less than the lower limit of the equipment classification threshold range, the corresponding workshop production equipment will be included in the category of equipment that is not prone to failure; when the number of failures is within the equipment classification threshold range, the corresponding workshop production equipment will be included in the category of ordinary equipment; when the number of failures is greater than the upper limit of the equipment classification threshold range, the corresponding workshop production equipment will be included in the category of equipment that is prone to failure.

[0020] Preferably, in step S3, obtaining the collection frequency of real-time operation data of workshop production equipment includes: calling up the equipment classification table, setting the collection frequency of equipment prone to failure to high frequency, setting the collection frequency of ordinary equipment to medium frequency, and setting the collection frequency of equipment not prone to failure to low frequency.

[0021] Preferably, in step S6, determining whether a corresponding workshop production equipment fails includes:

[0022] Split the real-time operation data according to the data type to obtain corresponding sub-data;

[0023] In the risk assessment unit, a standard threshold value of each sub-data is preset as a basis for fault judgment;

[0024] Each sub-data of each single workshop production equipment is compared with the corresponding standard threshold; if all sub-data meet the standard threshold requirements, it is determined that the workshop production equipment has no fault; if there is sub-data that does not meet the standard threshold requirements, it is determined that the workshop production equipment has a fault.

[0025] Preferably, in step S6, evaluating the risk level of the corresponding workshop production equipment includes:

[0026] Calculate the difference between each standard threshold and the corresponding sub-data, including: real-time temperature difference SWC, real-time pressure difference SYC and real-time current difference SIC;

[0027] By formula FD = a × (SWC + SYC + SIC) 2 +b calculates the risk level FD of the corresponding equipment; where a represents a proportional coefficient less than 0, and b represents an integer greater than 0 and is the maximum value of the risk level.

[0028] Preferably, in step S7, determining whether there is a safety risk in the corresponding workshop production equipment includes:

[0029] Set risk level thresholds, including primary and secondary thresholds;

[0030] Retrieve the risk level FD and determine whether the risk level FD is greater than the first-level threshold; if so, determine that the corresponding workshop production equipment has a safety risk; if not, determine that the equipment does not have a safety risk.

[0031] Preferably, in step S7, updating the collection frequency of real-time operation data of workshop production equipment includes: determining whether the risk level FD is greater than the secondary threshold; if so, increasing the collection frequency of the corresponding workshop production equipment; if not, maintaining the current collection frequency.

[0032] Beneficial effects of the present invention:

[0033] 1. This technical solution classifies workshop production equipment according to historical fault data to obtain an equipment classification table, and then sets the collection frequency of workshop production equipment according to the equipment classification table, which can increase the attention to equipment that is prone to failure; based on each sub-data in the real-time operation data of the workshop production equipment, it is judged whether the workshop production equipment has a fault. When the equipment fails, an alarm signal is generated, and the faulty equipment is inspected according to the alarm signal to obtain the fault type and fault handling method. When a equipment failure is found, an alarm can be issued in time and the faulty equipment can be inspected and repaired to avoid affecting production efficiency due to equipment failure.

[0034] 2. This technical solution calculates the risk level of the equipment based on the difference between the sub-data in the real-time operation data and the standard threshold, and compares the risk level with the set first-level threshold and second-level threshold. When the risk level of the workshop production equipment is greater than the first-level threshold, the corresponding equipment has a safety risk, and an early warning signal is generated, which can promptly remind the staff in the workshop to inspect and maintain the workshop production equipment, avoid repairing the equipment only when the workshop production equipment fails, and extend the service life of the equipment. When the risk level is less than the first-level threshold and greater than the second-level threshold, the collection frequency of the corresponding workshop production equipment will be increased by one level, which can avoid the equipment failure before the next data collection due to low collection frequency, affecting the efficiency of workshop production. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 This is a block diagram of the safety risk early warning system;

[0036] Figure 2 This is a basic implementation flow chart of the safety risk early warning method. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solution and advantages of the invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings in the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments.

[0038] Therefore, the following detailed description of the invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the invention. 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.

[0039] Example 1

[0040] This embodiment discloses a safety risk early warning system and method for workshop production. As a preferred implementation scheme of this technical solution, the safety risk early warning system is as follows: Figure 1As shown, it includes a database, a data acquisition unit, a data sensor unit, a risk assessment unit and a safety warning unit. Among them: the data sensor unit is communicatively connected to the data acquisition unit, and is used to collect and upload the real-time operation data of the workshop production equipment. The database is communicatively connected to the data acquisition unit, and is used for the historical operation data of the workshop production equipment, including the historical fault data. The data acquisition unit is communicatively connected to the risk assessment unit, and is used to obtain the real-time operation data and the historical fault data from the database and the data sensor unit respectively, and send the real-time operation data and the historical fault data to the risk assessment unit. The risk assessment unit is used to perform equipment fault judgment and safety risk assessment on the corresponding workshop production equipment in combination with the real-time operation data and the historical fault data. The safety warning unit is communicatively connected to the risk assessment unit, and is used to implement fault alarm or safety warning according to the equipment fault judgment result or the safety risk assessment result.

[0041] Based on the above security risk warning system, the corresponding security risk warning method is as follows: Figure 2 As shown, the following steps are included:

[0042] S1, using the historical operation data of the workshop production equipment in the database, including historical fault data, the historical fault data includes the number of equipment failures, fault types and fault handling methods.

[0043] S2, using the data acquisition unit to obtain historical fault data in the database, and uploading the historical fault data to the risk assessment unit.

[0044] S3, using the risk assessment unit to classify the corresponding workshop production equipment based on the historical fault data to obtain an equipment classification table; and obtaining the collection frequency of the real-time operation data of the workshop production equipment according to the equipment classification table.

[0045] S4, the risk assessment unit sends a real-time data collection instruction to the data collection unit based on the current collection frequency.

[0046] S5, after receiving the real-time data collection instruction, the data collection unit cooperates with the data sensor unit to collect and upload the real-time operation data of the workshop production equipment according to the corresponding collection frequency, including real-time temperature, real-time pressure and real-time current.

[0047] S6, using the risk assessment unit to determine whether the corresponding workshop production equipment has a fault based on real-time operation data; if so, an alarm signal is generated and sent to the safety warning unit, and then the process goes to step S8; if not, the risk level of the corresponding workshop production equipment is assessed, and then the process goes to step S7.

[0048] S7, determine whether there is a safety risk for the corresponding workshop production equipment based on the risk level assessment results; if so, generate an early warning signal and send it to the safety early warning unit, and then enter step S8; if not, update the collection frequency of the real-time operation data of the workshop production equipment based on the risk level assessment results, and return to step S4.

[0049] S8, implement countermeasures according to the type of signal obtained by the safety warning unit, namely: when the safety warning unit receives an alarm signal, it issues a fault alarm, and the equipment maintenance personnel inspect the faulty equipment according to the alarm signal, determine the fault type and fault handling method, and update the historical fault data in the database; when the safety warning unit receives a warning signal, it issues a safety warning, and the equipment maintenance personnel inspect and maintain the corresponding workshop production equipment based on the warning signal.

[0050] Example 2

[0051] This embodiment discloses a safety risk early warning method for workshop production, which, as a preferred implementation scheme of this technical solution, includes the following steps:

[0052] S1, using the historical operation data of the workshop production equipment in the database, including historical fault data, the historical fault data includes the number of equipment failures, fault types and fault handling methods.

[0053] S2, using the data acquisition unit to obtain historical fault data in the database, and uploading the historical fault data to the risk assessment unit.

[0054] S3, using the risk assessment unit to classify the corresponding workshop production equipment based on the historical fault data to obtain an equipment classification table; and obtaining the collection frequency of the real-time operation data of the workshop production equipment according to the equipment classification table.

[0055] Furthermore, classifying the corresponding workshop production equipment includes the following steps:

[0056] Set the equipment classification threshold range based on equipment maintenance experience;

[0057] Obtain the number of failures of workshop production equipment based on historical failure data;

[0058] Compare the number of failures with the equipment classification threshold range; when the number of failures is less than the lower limit of the equipment classification threshold range, the corresponding workshop production equipment will be included in the category of equipment that is not prone to failure; when the number of failures is within the equipment classification threshold range, the corresponding workshop production equipment will be included in the category of ordinary equipment; when the number of failures is greater than the upper limit of the equipment classification threshold range, the corresponding workshop production equipment will be included in the category of equipment that is prone to failure.

[0059] Furthermore, the acquisition frequency of real-time operation data of workshop production equipment includes: calling up the equipment classification table, setting the acquisition frequency of equipment prone to failure to high frequency, setting the acquisition frequency of ordinary equipment to medium frequency, and setting the acquisition frequency of equipment not prone to failure to low frequency.

[0060] S4, the risk assessment unit sends a real-time data collection instruction to the data collection unit based on the current collection frequency.

[0061] S5, after receiving the real-time data collection instruction, the data collection unit cooperates with the data sensor unit to collect and upload the real-time operation data of the workshop production equipment according to the corresponding collection frequency, including real-time temperature, real-time pressure and real-time current.

[0062] S6, using the risk assessment unit to determine whether the corresponding workshop production equipment has a fault based on real-time operation data; if so, an alarm signal is generated and sent to the safety warning unit, and then the process goes to step S8; if not, the risk level of the corresponding workshop production equipment is assessed, and then the process goes to step S7.

[0063] S7, determine whether there is a safety risk for the corresponding workshop production equipment based on the risk level assessment results; if so, generate an early warning signal and send it to the safety early warning unit, and then enter step S8; if not, update the collection frequency of the real-time operation data of the workshop production equipment based on the risk level assessment results, and return to step S4.

[0064] S8, implement countermeasures according to the type of signal obtained by the safety warning unit, namely: when the safety warning unit receives an alarm signal, it issues a fault alarm, and the equipment maintenance personnel inspect the faulty equipment according to the alarm signal, determine the fault type and fault handling method, and update the historical fault data in the database; when the safety warning unit receives a warning signal, it issues a safety warning, and the equipment maintenance personnel inspect and maintain the corresponding workshop production equipment based on the warning signal.

[0065] Example 3

[0066] This embodiment discloses a safety risk early warning method for workshop production, which, as a preferred implementation scheme of this technical solution, includes the following steps:

[0067] S1, using the historical operation data of the workshop production equipment in the database, including historical fault data, the historical fault data includes the number of equipment failures, fault types and fault handling methods.

[0068] S2, using the data acquisition unit to obtain historical fault data in the database, and uploading the historical fault data to the risk assessment unit.

[0069] S3, using the risk assessment unit to classify the corresponding workshop production equipment based on the historical fault data to obtain an equipment classification table; and obtaining the collection frequency of the real-time operation data of the workshop production equipment according to the equipment classification table.

[0070] Furthermore, classifying the corresponding workshop production equipment includes the following steps:

[0071] Set the equipment classification threshold range based on equipment maintenance experience;

[0072] Obtain the number of failures of workshop production equipment based on historical failure data;

[0073] Compare the number of failures with the equipment classification threshold range; when the number of failures is less than the lower limit of the equipment classification threshold range, the corresponding workshop production equipment will be included in the category of equipment that is not prone to failure; when the number of failures is within the equipment classification threshold range, the corresponding workshop production equipment will be included in the category of ordinary equipment; when the number of failures is greater than the upper limit of the equipment classification threshold range, the corresponding workshop production equipment will be included in the category of equipment that is prone to failure.

[0074] Furthermore, the acquisition frequency of real-time operation data of workshop production equipment includes: calling up the equipment classification table, setting the acquisition frequency of equipment prone to failure to high frequency, setting the acquisition frequency of ordinary equipment to medium frequency, and setting the acquisition frequency of equipment not prone to failure to low frequency.

[0075] The equipment classification threshold range and collection frequency are set based on experience. For example, if the number of failures of production equipment in a workshop ranges from 0 to 10, the threshold range is set between 3 and 7. Based on this, the high-frequency collection frequency is set to once a day, the medium-frequency collection frequency is set to once every three days, and the low-frequency collection frequency is set to once every five days.

[0076] S4, the risk assessment unit sends a real-time data collection instruction to the data collection unit based on the current collection frequency.

[0077] S5, after receiving the real-time data collection instruction, the data collection unit cooperates with the data sensor unit to collect and upload the real-time operation data of the workshop production equipment according to the corresponding collection frequency, including real-time temperature, real-time pressure and real-time current.

[0078] S6, using the risk assessment unit to determine whether the corresponding workshop production equipment has a fault based on real-time operation data; if so, an alarm signal is generated and sent to the safety warning unit, and then the process goes to step S8; if not, the risk level of the corresponding workshop production equipment is assessed, and then the process goes to step S7.

[0079] Furthermore, judging whether the corresponding workshop production equipment has a fault includes:

[0080] Split the real-time operation data according to the data type to obtain corresponding sub-data;

[0081] In the risk assessment unit, a standard threshold value of each sub-data is preset as a basis for fault judgment;

[0082] Each sub-data of each single workshop production equipment is compared with the corresponding standard threshold; if all sub-data meet the standard threshold requirements, it is determined that the workshop production equipment has no fault; if there is sub-data that does not meet the standard threshold requirements, it is determined that the workshop production equipment has a fault.

[0083] Furthermore, the risk level of the corresponding workshop production equipment is assessed including:

[0084] Calculate the difference between each standard threshold and the corresponding sub-data, including: real-time temperature difference SWC, real-time pressure difference SYC and real-time current difference SIC;

[0085] By formula FD = a × (SWC + SYC + SIC) 2 +b calculates the risk level FD of the corresponding equipment; wherein z represents a proportional coefficient less than 0, and b represents an integer greater than 0 and is the maximum value of the risk level.

[0086] S7, determine whether there is a safety risk for the corresponding workshop production equipment based on the risk level assessment results; if so, generate an early warning signal and send it to the safety early warning unit, and then enter step S8; if not, update the collection frequency of the real-time operation data of the workshop production equipment based on the risk level assessment results, and return to step S4.

[0087] Furthermore, judging whether there are safety risks in the corresponding workshop production equipment includes:

[0088] Set risk level thresholds, including primary and secondary thresholds;

[0089] Retrieve the risk level FD and determine whether the risk level FD is greater than the first-level threshold; if so, determine that the corresponding workshop production equipment has a safety risk; if not, determine that the equipment does not have a safety risk.

[0090] Furthermore, updating the collection frequency of real-time operation data of workshop production equipment includes: judging whether the risk level FD is greater than the secondary threshold; if so, increasing the collection frequency of the corresponding workshop production equipment; if not, maintaining the current collection frequency.

[0091] S8, implement countermeasures according to the type of signal obtained by the safety warning unit, namely: when the safety warning unit receives an alarm signal, it issues a fault alarm, and the equipment maintenance personnel inspect the faulty equipment according to the alarm signal, determine the fault type and fault handling method, and update the historical fault data in the database; when the safety warning unit receives a warning signal, it issues a safety warning, and the equipment maintenance personnel inspect and maintain the corresponding workshop production equipment based on the warning signal.

[0092] Example 4

[0093] This embodiment discloses a safety risk early warning system and method for workshop production, as a preferred implementation scheme of this technical solution, the safety risk early warning system is as follows: Figure 1 As shown, it includes a database, a data acquisition unit, a data sensor unit, a risk assessment unit and a safety warning unit. Among them: the data sensor unit is communicatively connected to the data acquisition unit, and is used to collect and upload the real-time operation data of the workshop production equipment. The database is communicatively connected to the data acquisition unit, and is used for the historical operation data of the workshop production equipment, including the historical fault data. The data acquisition unit is communicatively connected to the risk assessment unit, and is used to obtain the real-time operation data and the historical fault data from the database and the data sensor unit respectively, and send the real-time operation data and the historical fault data to the risk assessment unit. The risk assessment unit is used to perform equipment fault judgment and safety risk assessment on the corresponding workshop production equipment in combination with the real-time operation data and the historical fault data. The safety warning unit is communicatively connected to the risk assessment unit, and is used to implement fault alarm or safety warning according to the equipment fault judgment result or the safety risk assessment result.

[0094] In actual application, based on the above security risk early warning system, the specific use is as follows:

[0095] Set the equipment classification threshold range based on equipment maintenance experience. Obtain historical fault data of multiple workshop production equipment in the database through the data acquisition unit, and obtain the number of faults of each workshop production equipment from the historical fault data. When the number of faults is less than the lower limit of the equipment classification threshold range, the corresponding workshop production equipment is included in the category of equipment that is not prone to failure; when the number of faults is within the equipment classification threshold range, the corresponding workshop production equipment is included in the category of ordinary equipment; when the number of faults is greater than the upper limit of the equipment classification threshold range, the corresponding workshop production equipment is included in the category of equipment that is prone to failure. In this way, an equipment classification table is generated.

[0096] Furthermore, the acquisition frequency of the equipment that is prone to failure is set to high frequency, the acquisition frequency of the common equipment is set to medium frequency, and the acquisition frequency of the equipment that is not prone to failure is set to low frequency. The specific ranges of high frequency, medium frequency and low frequency are set based on experience. The risk assessment unit sends a real-time data acquisition instruction to the data acquisition unit based on the current acquisition frequency. After receiving the real-time data acquisition instruction, the data acquisition unit cooperates with several data sensors in the data sensor unit to collect and upload the real-time operation data of the workshop production equipment according to the corresponding acquisition frequency.

[0097] It should be noted that the database is used to store the historical fault data of several workshop production equipment, including the number of equipment failures, fault types, and fault handling methods. The equipment classification threshold range and collection frequency are set based on experience. For example, the threshold range of existing workshop production equipment is [5,10]; the collection frequency is set to collect once every hour for high frequency, once every 2 hours for medium frequency, and once every 4 hours for low frequency; the workshop production equipment includes equipment A, equipment B, and equipment C. The data is as follows: Equipment A, the number of failures is 7 times, then equipment A is included in the category of ordinary equipment, and the real-time operation data of equipment A is collected every 2 hours. Equipment B, the number of failures is 3 times, then equipment B is included in the category of equipment that is not prone to failure, and the real-time operation data of equipment B is collected every 4 hours. Equipment C, the number of failures is 14 times, then equipment C is included in the category of equipment that is prone to failure, and the real-time operation data of equipment C is collected every 1 hour.

[0098] The real-time operation data is split according to the data type to obtain the corresponding sub-data, including real-time temperature, real-time pressure and real-time current. The standard threshold of each sub-data is preset in the risk assessment unit as the basis for fault judgment. The sub-data of each single workshop production equipment is compared with the corresponding standard threshold; if all sub-data meet the standard threshold requirements, it is determined that the workshop production equipment has no fault; if there is sub-data that does not meet the standard threshold requirements, it is determined that the workshop production equipment has a fault. Among them, the standard threshold of each sub-data is set according to the equipment type and / or equipment model, and the standard threshold of each sub-data can be found in the user guide or manual of the corresponding workshop production equipment.

[0099] For example, the standard thresholds for workshop equipment are temperature threshold 45 degrees Celsius, pressure threshold 10MPa, and current threshold 750A. The latest real-time operation data collected by equipment A, equipment B, and equipment C are as follows:

[0100] Device A, real-time temperature is 36 degrees Celsius, real-time pressure is 2MPa, real-time current is 743A, and the sub-data in the real-time operation data of device A are all less than the standard thresholds, so device A has no fault.

[0101] Device B, real-time temperature 35 degrees Celsius, real-time pressure 3MPa, real-time current 732A, the sub-data in the real-time operation data of device B are all less than the standard thresholds, then device B has no fault.

[0102] Device C, real-time temperature 43 degrees Celsius, real-time pressure 8MPa, real-time current 765A, the real-time current of device C is greater than the current threshold, and device C has a fault. The subsequent sequence needs to check and analyze the fault type and fault handling method of device C, and update the historical fault data in the database.

[0103] Evaluate the risk level of the corresponding workshop production equipment. That is, calculate the difference between each standard threshold and the corresponding sub-data, including the real-time temperature difference SWC, the real-time pressure difference SYC and the real-time current difference SIC. Then use the formula FD = a × (SWC + SYC + SIC) 2 +b calculates the risk level FD of the corresponding equipment; where a represents a proportional coefficient less than 0, and b represents an integer greater than 0 and is the maximum value of the risk level.

[0104] Set the risk level threshold, including the first-level threshold and the second-level threshold. Retrieve the risk level FD and determine whether the risk level FD is greater than the first-level threshold; if so, determine that the corresponding workshop production equipment has a safety risk; if not, determine that the corresponding workshop production equipment does not have a safety risk. Determine whether the risk level FD is greater than the second-level threshold; if so, increase the collection frequency of the corresponding workshop production equipment by one level; if not, maintain the current collection frequency.

[0105] It should be noted that the difference between the standard threshold and the sub-data is calculated only when the sub-data in the real-time operation data of the workshop production equipment are all less than the standard threshold, and the real-time temperature difference, real-time pressure difference and real-time current difference are obtained by subtracting the sub-data from the standard threshold. Therefore, the values ​​of each difference cannot be negative. The first-level threshold and the second-level threshold are set based on experience, and the first-level threshold is greater than the second-level threshold. For example, if the first-level threshold is set to 80 based on experience, the second-level threshold is set to 60. For example, for equipment A and equipment B that have no faults, the risk level of equipment A and equipment B is evaluated, and the corresponding first-level threshold of the risk level is 80, the second-level threshold is 60, a=-1, and b=100. The evaluation results of equipment A and equipment B are as follows:

[0106] For device A, the real-time temperature difference SWC = 4, the real-time pressure difference SYC = 8, and the real-time current difference SIC = 7. The risk level of device A is FD = 81, which is greater than the first-level threshold. A warning signal needs to be generated in the subsequent sequence to inspect and maintain device A.

[0107] For device B, the real-time temperature difference SWC = 10, the real-time pressure difference SYC = 7, and the real-time current difference SIC = 18. The risk level of device B is FD = 65, which is less than the first-level threshold and greater than the second-level threshold. The collection frequency of device B is updated from low frequency to medium frequency, and the real-time operation data of device B is collected every 2 hours.

[0108] Implement countermeasures based on the type of signal obtained by the safety early warning unit, namely: when the safety early warning unit receives an alarm signal, it issues a fault alarm, and the equipment maintenance personnel inspect the faulty equipment based on the alarm signal, determine the fault type and fault handling method, and update the historical fault data in the database; when the safety early warning unit receives a warning signal, it issues a safety warning, and the equipment maintenance personnel inspect and maintain the corresponding workshop production equipment based on the warning signal.

[0109] Part of the data in the above formula is calculated by removing the dimension and taking its numerical value. The formula is a formula closest to the actual situation obtained by software simulation of a large amount of collected data; the preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained through simulation of a large amount of data.

[0110] Working principle of the present invention: The present invention collects historical fault data of several devices through a database, and divides several devices into fault-prone devices, common devices and non-fault-prone devices according to the number of faults in the historical fault data, thereby generating an equipment classification table; sets a collection frequency according to the equipment type in the equipment classification table; collects real-time operation data of several devices through several data sensors according to the collection frequency, and determines whether the sub-data in the real-time operation data are all less than a set standard threshold; if yes, analyzes the risk level of several devices; if not, generates an alarm signal, checks the equipment to obtain the fault type, processes the faulty equipment based on the database, and updates the number of failures of the corresponding equipment in the database.

[0111] The present invention retrieves sub-data in the real-time operation data of the equipment, calculates the difference between each standard threshold and the sub-data, and obtains the real-time temperature difference, the real-time pressure difference and the real-time current difference; calculates the risk level of the equipment according to each difference; when the risk level is greater than the first-level threshold, determines that the corresponding equipment has a safety risk, generates an early warning signal, and inspects and maintains the equipment according to the early warning signal; when the risk level is less than the first-level threshold and greater than the second-level threshold, updates the collection frequency of the corresponding equipment.

[0112] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. 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 safety risk early warning system for workshop production, characterized by: It includes a database, a data acquisition unit, a data sensor unit, a risk assessment unit and a safety warning unit; The data sensor unit is in communication with the data acquisition unit and is used to collect and upload real-time operation data of workshop production equipment; The database is in communication with the data acquisition unit and is used for historical operation data of workshop production equipment, including historical fault data; The data acquisition unit is in communication connection with the risk assessment unit, and is used to obtain real-time operation data and historical fault data from the database and the data sensor unit respectively, and send the real-time operation data and historical fault data to the risk assessment unit; The risk assessment unit is used to combine real-time operation data and historical fault data to perform equipment fault judgment and safety risk assessment on corresponding workshop production equipment; The safety warning unit is in communication connection with the risk assessment unit, and is used to implement a fault alarm or a safety warning according to the equipment fault judgment result or the safety risk assessment result.

2. A safety risk early warning method for workshop production, using a safety risk early warning system for workshop production as claimed in claim 1, characterized in that: The following steps are involved: S1, using the historical operation data of the workshop production equipment in the database, including historical fault data, the historical fault data includes the number of equipment failures, fault types and fault handling methods; S2, using the data acquisition unit to obtain historical fault data in the database, and uploading the historical fault data to the risk assessment unit; S3, using the risk assessment unit to classify the corresponding workshop production equipment based on the historical fault data to obtain an equipment classification table; according to the equipment classification table, the collection frequency of the real-time operation data of the workshop production equipment is obtained; S4, the risk assessment unit sends a real-time data collection instruction to the data collection unit based on the current collection frequency; S5, after receiving the real-time data collection instruction, the data collection unit cooperates with the data sensor unit to collect and upload the real-time operation data of the workshop production equipment according to the corresponding collection frequency, including real-time temperature, real-time pressure and real-time current; S6, using the risk assessment unit to determine whether the corresponding workshop production equipment has a fault based on the real-time operation data; if so, an alarm signal is generated and sent to the safety warning unit, and then the process goes to step S8; if not, the risk level of the corresponding workshop production equipment is assessed, and then the process goes to step S7; S7, judging whether there is a safety risk for the corresponding workshop production equipment according to the risk level assessment result; if so, generating an early warning signal and sending it to the safety early warning unit, and then proceeding to step S8; if not, updating the collection frequency of the real-time operation data of the workshop production equipment based on the risk level assessment result, and then returning to step S4; S8, implement countermeasures according to the type of signal obtained by the safety warning unit, namely: when the safety warning unit receives an alarm signal, it issues a fault alarm, and the equipment maintenance personnel inspect the faulty equipment according to the alarm signal, determine the fault type and fault handling method, and update the historical fault data in the database; when the safety warning unit receives a warning signal, it issues a safety warning, and the equipment maintenance personnel inspect and maintain the corresponding workshop production equipment based on the warning signal.

3. A safety risk early warning method for workshop production as claimed in claim 2, characterized in that: In step S3, classifying the corresponding workshop production equipment includes the following steps: Set the equipment classification threshold range based on equipment maintenance experience; Obtain the number of failures of workshop production equipment based on historical failure data; Compare the number of failures with the equipment classification threshold range; when the number of failures is less than the lower limit of the equipment classification threshold range, the corresponding workshop production equipment will be included in the category of equipment that is not prone to failure; when the number of failures is within the equipment classification threshold range, the corresponding workshop production equipment will be included in the category of ordinary equipment; when the number of failures is greater than the upper limit of the equipment classification threshold range, the corresponding workshop production equipment will be included in the category of equipment that is prone to failure.

4. A safety risk early warning method for workshop production as claimed in claim 3, characterized in that: In step S3, obtaining the collection frequency of real-time operation data of workshop production equipment includes: calling the equipment classification table, setting the collection frequency of fault-prone equipment to high frequency, setting the collection frequency of ordinary equipment to medium frequency, and setting the collection frequency of non-fault-prone equipment to low frequency.

5. A safety risk early warning method for workshop production as claimed in claim 3, characterized in that: In step S6, determining whether a corresponding workshop production equipment fails includes: Split the real-time operation data according to the data type to obtain corresponding sub-data; In the risk assessment unit, a standard threshold value of each sub-data is preset as a basis for fault judgment; Each sub-data of each single workshop production equipment is compared with the corresponding standard threshold; if all sub-data meet the standard threshold requirements, it is determined that the workshop production equipment has no fault; if there is sub-data that does not meet the standard threshold requirements, it is determined that the workshop production equipment has a fault.

6. A safety risk early warning method for workshop production as claimed in claim 5, characterized in that: In step S6, evaluating the risk level of the corresponding workshop production equipment includes: Calculate the difference between each standard threshold and the corresponding sub-data, including: real-time temperature difference SWC, real-time pressure difference SYC and real-time current difference SIC; By formula FD = a × (SWC + SYC + SIC) 2 +b calculates the risk level FD of the corresponding equipment; where a represents a proportional coefficient less than 0, and b represents an integer greater than 0 and is the maximum value of the risk level.

7. A safety risk early warning method for workshop production as claimed in claim 6, characterized in that: In step S7, determining whether there is a safety risk in the corresponding workshop production equipment includes: Set risk level thresholds, including primary and secondary thresholds; Retrieve the risk level FD and determine whether the risk level FD is greater than the first-level threshold; if so, determine that the corresponding workshop production equipment has a safety risk; if not, determine that the equipment does not have a safety risk.

8. A safety risk early warning method for workshop production according to claim 7, characterized in that: In step S7, updating the collection frequency of real-time operation data of workshop production equipment includes: judging whether the risk level FD is greater than the secondary threshold; if so, increasing the collection frequency of the corresponding workshop production equipment; if not, maintaining the current collection frequency.

Images