Workshop intelligent inspection management method and system

Abstract

The invention discloses an intelligent workshop inspection management method and system, and particularly relates to the technical field of artificial intelligence, and the method comprises a workshop information acquisition step, a text preprocessing step, a text data selection step, a workshop information analysis step, a comprehensive analysis step, a comprehensive judgment step and a man-machine interaction step. The method comprises the steps of obtaining a first workshop text of a target workshop and performing preprocessing operation to obtain a first feature data text corresponding to the first workshop text; performing data selection on the first feature data text; calculating and analyzing the first feature data text to obtain a reasonable value corresponding to the first feature data text; obtaining an intelligent inspection model, importing the first feature data text reasonable value into the intelligent inspection model to obtain a comprehensive text reasonable value, and improving the accuracy and comprehensiveness of workshop intelligent inspection management through the comprehensive text reasonable value of the target workshop.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and more specifically, to a workshop intelligent inspection management method and system. Background Art

[0002] Artificial intelligence technology is booming in today's era, and it is supported by a deep technical background; the advancement of data acquisition technology has also brought new opportunities for artificial intelligence. The widespread use of various high-precision sensors, such as temperature sensors and pressure sensors, can collect multimodal data from different fields in real time. These data cover a variety of information such as images, sounds, temperature, pressure, etc., providing rich input for artificial intelligence models. In addition, the continuous development of professional data annotation and cleaning technologies has significantly improved data quality, providing a guarantee for training accurate and reliable artificial intelligence models.

[0003] The existing workshop intelligent inspection management method includes three steps: data collection, data analysis and problem assessment. Data collection uses intelligent sensors to obtain workshop-related data, such as equipment operating parameters, environmental indicators, etc. Data analysis converts complex data into intuitive results to clearly present the workshop operation status, including analysis of equipment operation, environmental impact and production efficiency. Problem assessment evaluates existing analysis results by comparing historical data to determine potential workshop problem risks, such as equipment performance decline trends, environmental impact on product quality, and reasons for production efficiency fluctuations.

[0004] However, it still has some shortcomings in actual use. In the workshop intelligent inspection management method, the data collection step uses various intelligent sensors to collect workshop data, which is easily disturbed by workshop environmental factors, resulting in inaccurate collected data. For example, mechanical vibration may affect the accuracy of the sensor, causing deviations in the collected equipment operating parameters, environmental indicators and other data; in the data analysis step, the collected data is processed, but when the existing technology analyzes complex workshop data, there will be deviations in the analysis results and omissions of data, resulting in data gaps, which reduces the reference value of workshop data; the existing system lacks comprehensive data to measure the key indicators of workshop operation, making the evaluation not comprehensive and objective, increasing the difficulty and risk of decision-making, and bringing great troubles to workshop inspection management. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a workshop intelligent inspection management method and system, which solves the problems raised in the above-mentioned background technology through the field of artificial intelligence technology.

[0006] To achieve the above-mentioned purpose, the present invention provides the following technical solution: a workshop intelligent inspection management method, including S1-S7:

[0007] S1: Workshop information acquisition: in response to the inspection intelligent operation of the target workshop, a first workshop text corresponding to the target workshop is acquired;

[0008] S2: Text preprocessing: preprocessing the first workshop text of the target workshop, obtaining the first characteristic data text corresponding to the first workshop text, determining the first characteristic data text as the target text, filtering the target text into sub-texts, and numbering the sub-texts in sequence as i=1, 2, ..., n;

[0009] S3: text data selection: performing a preprocessing operation on the first power text of the target enterprise to obtain a first characteristic data text, and performing data selection on the first characteristic data text;

[0010] S4: Workshop information analysis: according to the first feature data text, a reasonable value corresponding to the first feature data text is obtained by calculation and analysis; including an equipment operation calculation unit, a workshop environment calculation unit, an equipment performance calculation unit and an equipment mechanical calculation unit;

[0011] S5: Comprehensive analysis: obtaining an intelligent inspection model, importing the reasonable value of the first feature data text into the intelligent inspection model to obtain a comprehensive reasonable value of the text; including an intelligent inspection unit;

[0012] S6: Comprehensive judgment: obtaining a preset comprehensive text threshold, comparing the comprehensive text reasonable value with the preset comprehensive text threshold and transmitting the judged digital signal to the human-computer interaction step;

[0013] S7: Human-computer interaction step: According to the digital signal, a preset intelligent reply method is sent to the corresponding manager of the target workshop.

[0014] Preferably, the first characteristic data text for data selection specifically includes: equipment vibration amplitude recorded as yz, equipment current fluctuation value recorded as yd, equipment surface temperature change rate recorded as yw, water molecule concentration recorded as hs, noise intensity recorded as hz, electromagnetic radiation intensity recorded as hd, equipment production capacity fluctuation rate recorded as xb, equipment output power recorded as xc, equipment precision tolerance recorded as xg, equipment lubricating oil impurity content recorded as jr, equipment wear depression volume recorded as jm and equipment rotating parts imbalance recorded as jx.

[0015] Preferably, the equipment operation calculation unit is used to establish a mathematical model of equipment operation coefficient values, select and import the data of the first characteristic data text into the mathematical model of equipment operation coefficient values, and calculate the equipment operation coefficient value of each sub-text, which is specifically expressed as:

[0016]

[0017] YA iIndicates the equipment operation coefficient value of the i-th subtext, yz i Indicates the vibration amplitude of the device for the i-th subtext, yd i represents the device current fluctuation value of the i-th subtext, yw i Indicates the rate of change of the device surface temperature of the i-th subtext, and n indicates the number of subtexts.

[0018] Preferably, the workshop environment calculation unit is used to establish a mathematical model of the workshop environment coefficient value, select and import the data of the first characteristic data text into the mathematical model of the workshop environment coefficient value, and calculate the workshop environment coefficient value of each sub-text, which is specifically expressed as:

[0019]

[0020] HA i Indicates the workshop environment coefficient value of the i-th subtext, hs i Indicates the water molecule concentration of the i-th subtext, hz i represents the noise intensity of the ith subtext, hd i Represents the electromagnetic radiation intensity of the i-th subtext.

[0021] Preferably, the equipment performance calculation unit is used to establish a mathematical model of equipment performance coefficient values, select and import the data of the first characteristic data text into the mathematical model of equipment performance coefficient values, and calculate the equipment performance coefficient values ​​of each sub-text, which is specifically expressed as:

[0022]

[0023] XA i Indicates the equipment performance coefficient value of the i-th subtext, xb i represents the fluctuation rate of equipment capacity of the ith subtext, xc i represents the device output power of the ith subtext, xg i represents the device precision tolerance of the ith subtext, and n represents the number of subtexts.

[0024] Preferably, the equipment mechanical calculation unit is used to establish a mathematical model of the equipment mechanical coefficient value, select and import the data of the first characteristic data text into the mathematical model of the equipment mechanical coefficient value, and calculate the equipment mechanical coefficient value of each sub-text, which is specifically expressed as:

[0025]

[0026] J A i Indicates the mechanical coefficient value of the equipment in the i-th subtext, jr i Indicates the impurity content of the equipment lubricating oil in the i-th subtext, jm i represents the wear depression volume of the device of the i-th subtext, jxi Indicates the unbalance amount of the rotating part of the equipment in the i-th subtext.

[0027] Preferably, the intelligent inspection unit is used to establish an intelligent inspection model, import the reasonable value of the first feature data text into the intelligent inspection model, and calculate the reasonable value of the comprehensive text, which is specifically expressed as:

[0028]

[0029] [η i =α1×YA i +α2×HA i +α3×XA i +α4×JA i ], where P represents the reasonable value of the comprehensive text, η i represents the reasonable value of the first feature data text of the i-th subtext, η def Indicates the mean of the reasonable values ​​of the key texts in the previous years’ data statistics of the target text, YA i Indicates the equipment operation coefficient value of the i-th subtext, HA i Indicates the workshop environment coefficient value of the i-th subtext, XA i Indicates the equipment performance coefficient value of the i-th subtext, JA i represents the equipment mechanical coefficient value of the i-th subtext, α1, α2, α3, α4 represent weight coefficients and are all greater than zero, and λ represents other influencing factors of the comprehensive text safety value.

[0030] Preferably, the preset comprehensive text threshold is a value reasonably evaluated based on statistics of previous years; the specific determination is as follows:

[0031] B1: If the reasonable value of the comprehensive text is greater than the preset comprehensive text threshold, a danger signal is issued;

[0032] B2: If the comprehensive text reasonable value is less than the preset comprehensive text threshold, a safety signal is issued.

[0033] To achieve the above object, the present invention provides the following technical solution: a workshop intelligent inspection management system, comprising the following modules:

[0034] A workshop information acquisition module, in response to the inspection intelligent operation of the target workshop, acquires the first workshop text corresponding to the target workshop;

[0035] Text preprocessing module: preprocessing the first workshop text of the target workshop, obtaining the first characteristic data text corresponding to the first workshop text, determining the first characteristic data text as the target text, filtering the target text into sub-texts, and numbering the sub-texts in sequence as i=1, 2, ..., n;

[0036] Text data selection module: performs preprocessing operations on the first power text of the target enterprise to obtain a first characteristic data text, and performs data selection on the first characteristic data text;

[0037] Workshop information analysis module: calculates and analyzes the first feature data text to obtain a reasonable value corresponding to the first feature data text; includes an equipment operation calculation unit, a workshop environment calculation unit, an equipment performance calculation unit, and an equipment mechanical calculation unit;

[0038] Comprehensive analysis module: obtains an intelligent inspection model, imports the reasonable value of the first feature data text into the intelligent inspection model to obtain a comprehensive text reasonable value; includes an intelligent inspection unit;

[0039] Comprehensive judgment module: obtains a preset comprehensive text threshold, compares the comprehensive text reasonable value with the preset comprehensive text threshold, and transmits the judged digital signal to the human-computer interaction module;

[0040] Human-computer interaction module: Based on the digital signal, a preset intelligent reply method is sent to the corresponding manager of the target workshop.

[0041] Technical effects and advantages of the present invention:

[0042] 1. The present invention obtains the first workshop text corresponding to the target workshop through the intelligent inspection operation of the target workshop, and determines it as the target text. The first workshop text of the target workshop is preprocessed to obtain the first feature data text corresponding to the first workshop text, and the first feature data text is determined to be the target text. The target text is filtered into various sub-texts, which is helpful to improve the comprehensiveness of the workshop inspection in the future, and at the same time, improve the data accuracy of the target workshop inspection;

[0043] 2. The present invention selects data for the first feature data text, and then calculates and analyzes the first feature data text to obtain the corresponding reasonable value of the first feature data text, thereby discovering problems in the intelligent inspection management of the target workshop, which helps to provide a guarantee for the subsequent analysis of the workshop inspection and helps to improve the stability of the workshop inspection management; the intelligent inspection model is obtained, and the reasonable value of the first feature data text is imported into the intelligent inspection model to obtain the reasonable value of the comprehensive text, which helps to present a more intuitive and accurate inspection to the management personnel;

[0044] 3. The present invention compares the reasonable value of the comprehensive text with the preset comprehensive text threshold and transmits the judged digital signal to the human-computer interaction step, which helps to improve the accuracy of the judgment of the target workshop inspection; the digital signal sent by the system can be discovered in real time through the reply method. Once a dangerous signal is received, the system will feed back the processing result to the management personnel, who will perform intelligent optimization and adjustment on the target workshop; it helps to improve the comprehensiveness and integrity of the inspection management of the target workshop; BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 It is a schematic diagram of the structure of the method of the present invention.

[0046] Figure 2 It is a schematic diagram of the system structure of the present invention. DETAILED DESCRIPTION

[0047] 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.

[0048] As attached Figure 1 A workshop intelligent inspection management method is shown in the figure, including steps S1-S7.

[0049] S1: Workshop information acquisition: in response to the inspection intelligent operation of the target workshop, a first workshop text corresponding to the target workshop is acquired.

[0050] In this embodiment, it should be specifically explained that the manager of the target workshop can perform intelligent inspection operations on the corresponding information terminal equipment. The types of information terminal equipment mainly include: smart phone terminals, tablet terminals, PC terminals, etc.; there are many ways for managers to inspect the target workshop data, including but not limited to: text, tables, images, etc. The manager obtains the corresponding workshop text through the corresponding information terminal equipment. The method performs intelligent inspection analysis on the target workshop through the intelligent inspection operation of the target workshop and obtains the first workshop text of the target workshop. This embodiment does not limit the information terminal equipment and the workshop data method.

[0051] S2: Text preprocessing: perform preprocessing operations on the first workshop text of the target workshop, obtain the first characteristic data text corresponding to the first workshop text, determine that the first characteristic data text is the target text, filter the target text into sub-texts, and number each sub-text in sequence as i=1, 2,..., n.

[0052] In this embodiment, it should be specifically explained that the specific steps of preprocessing the first workshop text of the target workshop are as follows:

[0053] A1: Text cleaning: Remove special characters, punctuation marks, and numbers from the first workshop text, convert the case, and unify them into uppercase or lowercase;

[0054] A2: Stop word removal: Remove common words that contribute little to the analysis of the text from the first workshop, such as "de", "di", "shi", "zai", etc.

[0055] A3: Standardize the data of the text from the first workshop to obtain the first feature data text.

[0056] S3: Text data selection: After preprocessing the first power text of the target enterprise to obtain the first feature data text, perform data selection on the first feature data text.

[0057] In this embodiment, specifically, the data selection for the first feature data text specifically includes: the vibration amplitude of the equipment is denoted as yz, the current fluctuation value of the equipment is denoted as yd, the surface temperature change rate of the equipment is denoted as yw, the water molecule concentration is denoted as hs, the noise intensity is denoted as hz, the electromagnetic radiation intensity is denoted as hd, the production capacity volatility of the equipment is denoted as xb, the output power of the equipment is denoted as xc, the precision tolerance of the equipment is denoted as xg, the impurity content of the equipment lubricating oil is denoted as jr, the worn and sunken volume of the equipment is denoted as jm, and the unbalance amount of the rotating parts of the equipment is denoted as jx.

[0058] In this embodiment, specifically, for the vibration amplitude of the equipment, a vibration sensor can be used to collect data by installing it at key parts of the equipment; the current fluctuation value of the equipment is collected through a current transformer installed on the equipment power supply line; the surface temperature change rate of the equipment is collected with the help of a temperature sensor installed at the easily heated parts of the equipment; the water molecule concentration is collected by using a humidity sensor installed at the air circulation area of the workshop; the noise intensity is collected with a noise sensor installed at a certain distance from the equipment; the electromagnetic radiation intensity is collected through an electromagnetic radiation detector installed around the equipment; the production capacity volatility of the equipment is collected by a production counting sensor combined with a data recording device installed at key positions on the production line; the output power of the equipment is collected by using a power sensor installed on the power supply line; the precision tolerance of the equipment is collected by using a measuring tool combined with a data recording device at the product; the impurity content of the equipment lubricating oil is collected by using an oil fluid analyzer to extract oil samples from the lubrication system; the worn and sunken volume of the equipment is collected by using a 3D scanner or a precision measuring tool at the easily worn parts; the unbalance amount of the rotating parts of the equipment is collected through a dynamic balance detector installed on the rotating parts.

[0059] S4: Workshop information analysis: Calculate and analyze the corresponding reasonable values of the first feature data text based on the first feature data text; including an equipment operation calculation unit, a workshop environment calculation unit, an equipment performance calculation unit, and an equipment machinery calculation unit.

[0060] In this embodiment, specifically, the reasonable values of the first feature data text include the equipment operation coefficient values of each sub - text, the workshop environment coefficient values of each sub - text, the equipment performance coefficient values of each sub - text, and the equipment machinery coefficient values of each sub - text.

[0061] In this embodiment, it should be specifically explained that the equipment operation calculation unit is used to establish a mathematical model of the equipment operation coefficient value, select the data of the first characteristic data text and import it into the mathematical model of the equipment operation coefficient value, and calculate the equipment operation coefficient value of each sub-text, which is specifically expressed as:

[0062]

[0063] YA i Indicates the equipment operation coefficient value of the i-th subtext, yz i Indicates the vibration amplitude of the device for the i-th subtext, yd i represents the device current fluctuation value of the i-th subtext, yw i Indicates the rate of change of the device surface temperature of the i-th subtext, and n indicates the number of subtexts.

[0064] In this embodiment, it should be specifically explained that the workshop environment calculation unit is used to establish a mathematical model of the workshop environment coefficient value, select and import the data of the first characteristic data text into the mathematical model of the workshop environment coefficient value, and calculate the workshop environment coefficient value of each sub-text, which is specifically expressed as:

[0065]

[0066] HA i Indicates the workshop environment coefficient value of the i-th subtext, hs i Indicates the water molecule concentration of the i-th subtext, hz i represents the noise intensity of the ith subtext, hd i Represents the electromagnetic radiation intensity of the i-th subtext.

[0067] In this embodiment, it should be specifically explained that the device performance calculation unit is used to establish a mathematical model of the device performance coefficient value, select the data of the first characteristic data text and import it into the mathematical model of the device performance coefficient value, and calculate the device performance coefficient value of each sub-text, which is specifically expressed as:

[0068]

[0069] XA i Indicates the equipment performance coefficient value of the i-th subtext, xb i represents the fluctuation rate of equipment capacity of the ith subtext, xc i Indicates the device output power of the ith subtext, xg i represents the device precision tolerance of the ith subtext, and n represents the number of subtexts.

[0070] In this embodiment, it should be specifically explained that the equipment mechanical calculation unit is used to establish a mathematical model of the equipment mechanical coefficient value, select the data of the first characteristic data text and import it into the mathematical model of the equipment mechanical coefficient value, and calculate the equipment mechanical coefficient value of each sub-text, which is specifically expressed as:

[0071]

[0072] J A i Indicates the mechanical coefficient value of the equipment in the i-th subtext, jr i Indicates the impurity content of the equipment lubricating oil in the i-th subtext, jm i represents the wear depression volume of the device of the i-th subtext, jx i Indicates the unbalance amount of the rotating part of the equipment in the i-th subtext.

[0073] S5: Comprehensive analysis: obtaining an intelligent inspection model, importing the reasonable value of the first feature data text into the intelligent inspection model to obtain a comprehensive reasonable value of the text; including an intelligent inspection unit.

[0074] In this embodiment, it should be specifically explained that the intelligent inspection unit is used to establish an intelligent inspection model, import the reasonable value of the first feature data text into the intelligent inspection model, and calculate the reasonable value of the comprehensive text, which is specifically expressed as:

[0075]

[0076] [η i =α1×YA i +α2×HA i +α3×XA i +α4×JA i ], where P represents the reasonable value of the comprehensive text, η i represents the reasonable value of the first feature data text of the i-th subtext, η def Indicates the mean of the reasonable values ​​of the key texts in the previous years’ data statistics of the target text, YA i Indicates the equipment operation coefficient value of the i-th subtext, HA i Indicates the workshop environment coefficient value of the i-th subtext, XA i Indicates the equipment performance coefficient value of the i-th subtext, JA i represents the equipment mechanical coefficient value of the i-th subtext, α1, α2, α3, α4 represent weight coefficients and are all greater than zero, and λ represents other influencing factors of the comprehensive text safety value.

[0077] S6: Comprehensive judgment: obtain a preset comprehensive text threshold, compare the comprehensive text reasonable value with the preset comprehensive text threshold, and transmit the judged digital signal to the human-computer interaction step.

[0078] In this embodiment, it should be specifically noted that the preset comprehensive text threshold is a value reasonably evaluated based on statistics of previous years; the specific determination is as follows:

[0079] B1: If the reasonable value of the comprehensive text is greater than the preset comprehensive text threshold, a danger signal is issued;

[0080] B2: If the comprehensive text reasonable value is less than the preset comprehensive text threshold, a safety signal is issued.

[0081] S7: Human-computer interaction step: According to the digital signal, a preset intelligent reply method is sent to the corresponding manager of the target workshop.

[0082] In this embodiment, it is specifically necessary to explain that the preset smart reply modes are: text smart reply, image smart reply and audio smart reply.

[0083] As attached Figure 2 As shown, this embodiment provides a workshop intelligent inspection management system, including the following modules:

[0084] A workshop information acquisition module, in response to the inspection intelligent operation of the target workshop, acquires the first workshop text corresponding to the target workshop;

[0085] Text preprocessing module: preprocessing the first workshop text of the target workshop, obtaining the first characteristic data text corresponding to the first workshop text, determining the first characteristic data text as the target text, filtering the target text into sub-texts, and numbering the sub-texts in sequence as i=1, 2, ..., n;

[0086] Text data selection module: performs preprocessing operations on the first power text of the target enterprise to obtain a first characteristic data text, and performs data selection on the first characteristic data text;

[0087] Workshop information analysis module: calculates and analyzes the first feature data text to obtain a reasonable value corresponding to the first feature data text; includes an equipment operation calculation unit, a workshop environment calculation unit, an equipment performance calculation unit, and an equipment mechanical calculation unit;

[0088] Comprehensive analysis module: obtains an intelligent inspection model, imports the reasonable value of the first feature data text into the intelligent inspection model to obtain a comprehensive text reasonable value; includes an intelligent inspection unit;

[0089] Comprehensive judgment module: obtains a preset comprehensive text threshold, compares the comprehensive text reasonable value with the preset comprehensive text threshold, and transmits the judged digital signal to the human-computer interaction module;

[0090] Human-computer interaction module: Based on the digital signal, a preset intelligent reply method is sent to the corresponding manager of the target workshop.

[0091] The present invention obtains the first workshop text corresponding to the target workshop through the intelligent operation of the inspection of the target workshop, and determines it as the target text. The first workshop text of the target workshop is preprocessed to obtain the first feature data text corresponding to the first workshop text, and the first feature data text is determined to be the target text. The target text is filtered into various sub-texts, which is helpful to subsequently improve the comprehensiveness of the workshop inspection, and at the same time, improve the accuracy and reliability of the data of the target workshop inspection; thereafter, the first feature data text is selected, and then the reasonable value of the corresponding first feature data text is obtained according to the calculation and analysis of the first feature data text, so as to find problems in the intelligent inspection management of the target workshop, which is helpful for subsequent workshop inspection. The analysis provides a guarantee, which helps to improve the stability of workshop inspection management; obtain the intelligent inspection model, and import the reasonable value of the first feature data text into the intelligent inspection model to obtain the reasonable value of the comprehensive text, which helps to present a more intuitive and accurate inspection to the management personnel; compare the reasonable value of the comprehensive text with the preset comprehensive text threshold and transmit the judged digital signal to the human-computer interaction step, which helps to improve the accuracy of the judgment of the target workshop inspection; the digital signal sent by the system can be discovered in real time through the reply method. Once a dangerous signal is received, the system will feed back the processing results to the management personnel, and the management personnel will perform intelligent optimization and adjustment of the target workshop; it helps to improve the comprehensiveness and integrity of the inspection management of the target workshop.

[0092] Secondly, in the drawings of the embodiments disclosed in the present invention, only the structures related to the embodiments disclosed in the present invention are involved, and other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of the present invention can be combined with each other;

[0093] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A workshop intelligent inspection management method, characterized in that: include: S1: Workshop information acquisition: in response to the inspection intelligent operation of the target workshop, a first workshop text corresponding to the target workshop is acquired; S2: Text preprocessing: preprocessing the first workshop text corresponding to the target workshop, obtaining the first characteristic data text corresponding to the first workshop text, determining the first characteristic data text as the target text, filtering the target text into sub-texts, and numbering the sub-texts in sequence as i=1, 2, ..., n; S3: text data selection: performing a preprocessing operation on the first power text of the target enterprise to obtain a first characteristic data text, and performing data selection on the first characteristic data text; S4: Workshop information analysis: according to the first feature data text, a reasonable value corresponding to the first feature data text is obtained by calculation and analysis; including an equipment operation calculation unit, a workshop environment calculation unit, an equipment performance calculation unit and an equipment mechanical calculation unit; S5: Comprehensive analysis: obtaining an intelligent inspection model, importing the reasonable value of the first feature data text into the intelligent inspection model to obtain a comprehensive reasonable value of the text; including an intelligent inspection unit; S6: Comprehensive judgment: obtaining a preset comprehensive text threshold, comparing the comprehensive text reasonable value with the preset comprehensive text threshold and transmitting the judged digital signal to the human-computer interaction step; S7: Human-computer interaction step: According to the digital signal, a preset intelligent reply method is sent to the corresponding manager of the target workshop.

2. A workshop intelligent inspection management method according to claim 1, characterized in that: The data selection of the first characteristic data text specifically includes: equipment vibration amplitude is recorded as yz, equipment current fluctuation value is recorded as yd, equipment surface temperature change rate is recorded as yw, water molecule concentration is recorded as hs, noise intensity is recorded as hz, electromagnetic radiation intensity is recorded as hd, equipment production capacity fluctuation rate is recorded as xb, equipment output power is recorded as xc, equipment accuracy tolerance is recorded as xg, equipment lubricating oil impurity content is recorded as jr, equipment wear depression volume is recorded as jm and equipment rotating parts imbalance is recorded as jx.

3. A workshop intelligent inspection management method according to claim 1, characterized in that: The equipment operation calculation unit is used to establish a mathematical model of equipment operation coefficient values, select and import the data of the first characteristic data text into the mathematical model of equipment operation coefficient values, and calculate the equipment operation coefficient values ​​of each sub-text, which is specifically expressed as: YA i Indicates the equipment operation coefficient value of the i-th subtext, yz i Indicates the vibration amplitude of the device for the i-th subtext, yd i represents the device current fluctuation value of the i-th subtext, yw i Indicates the rate of change of the device surface temperature of the i-th subtext, and n indicates the number of subtexts.

4. A workshop intelligent inspection management method according to claim 1, characterized in that: The workshop environment calculation unit is used to establish a mathematical model of the workshop environment coefficient value, select and import the data of the first characteristic data text into the mathematical model of the workshop environment coefficient value, and calculate the workshop environment coefficient value of each sub-text, which is specifically expressed as: HA i Indicates the workshop environment coefficient value of the i-th subtext, hs i Indicates the water molecule concentration of the i-th subtext, hz i represents the noise intensity of the ith subtext, hd i Represents the electromagnetic radiation intensity of the i-th subtext.

5. The method for intelligent inspection management of a workshop according to claim 1, characterized in that: The device performance calculation unit is used to establish a mathematical model of the device performance coefficient value, select the data of the first characteristic data text and import it into the mathematical model of the device performance coefficient value, and calculate the device performance coefficient value of each sub-text, which is specifically expressed as: XA i Indicates the equipment performance coefficient value of the i-th subtext, xb i represents the fluctuation rate of equipment capacity of the ith subtext, xc i represents the device output power of the ith subtext, xg i represents the device precision tolerance of the ith subtext, and n represents the number of subtexts.

6. A workshop intelligent inspection management method according to claim 1, characterized in that: The equipment mechanical calculation unit is used to establish a mathematical model of the equipment mechanical coefficient value, select the data of the first characteristic data text and import it into the mathematical model of the equipment mechanical coefficient value, and calculate the equipment mechanical coefficient value of each sub-text, which is specifically expressed as: J A i Indicates the mechanical coefficient value of the equipment in the i-th subtext, jr i Indicates the impurity content of the equipment lubricating oil in the i-th subtext, jm i represents the wear depression volume of the device of the i-th subtext, jx i Indicates the unbalance amount of the rotating part of the equipment in the i-th subtext.

7. A workshop intelligent inspection management method according to claim 1, characterized in that: The intelligent inspection unit is used to establish an intelligent inspection model, import the reasonable value of the first feature data text into the intelligent inspection model, and calculate the reasonable value of the comprehensive text, which is specifically expressed as: [or i =α1×YA i +α2×HA i +α3×XA i +α4×JA i ], Where P represents the reasonable value of comprehensive text, η i represents the reasonable value of the first feature data text of the i-th subtext, η def Indicates the mean of the reasonable values ​​of the key texts in the previous years’ data statistics of the target text, YA i Indicates the equipment operation coefficient value of the i-th subtext, HA i Indicates the workshop environment coefficient value of the i-th subtext, XA i Indicates the equipment performance coefficient value of the i-th subtext, JA i represents the equipment mechanical coefficient value of the i-th subtext, α1, α2, α3, α4 represent weight coefficients and are all greater than zero, and λ represents other influencing factors of the comprehensive text safety value.

8. A workshop intelligent inspection management method according to claim 1, characterized in that: The preset comprehensive text threshold is a value reasonably evaluated based on statistics from previous years; the specific determination is as follows: B1: If the reasonable value of the comprehensive text is greater than the preset comprehensive text threshold, a danger signal is issued; B2: If the comprehensive text reasonable value is less than the preset comprehensive text threshold, a safety signal is issued.

9. A workshop intelligent inspection management system, characterized by: A workshop intelligent inspection management method for implementing any one of claims 1 to 8 above comprises the following modules: A workshop information acquisition module, in response to the inspection intelligent operation of the target workshop, acquires the first workshop text corresponding to the target workshop; Text preprocessing module: preprocessing the first workshop text of the target workshop, obtaining the first characteristic data text corresponding to the first workshop text, determining the first characteristic data text as the target text, filtering the target text into sub-texts, and numbering the sub-texts in sequence as i=1, 2, ..., n; Text data selection module: performs preprocessing operations on the first power text of the target enterprise to obtain a first characteristic data text, and performs data selection on the first characteristic data text; Workshop information analysis module: calculates and analyzes the first feature data text to obtain a reasonable value corresponding to the first feature data text; includes an equipment operation calculation unit, a workshop environment calculation unit, an equipment performance calculation unit, and an equipment mechanical calculation unit; Comprehensive analysis module: obtains an intelligent inspection model, imports the reasonable value of the first feature data text into the intelligent inspection model to obtain a comprehensive text reasonable value; Including intelligent inspection unit; Comprehensive judgment module: obtains a preset comprehensive text threshold, compares the comprehensive text reasonable value with the preset comprehensive text threshold, and transmits the judged digital signal to the human-computer interaction module; Human-computer interaction module: Based on the digital signal, a preset intelligent reply method is sent to the corresponding manager of the target workshop.

Images