Intelligent temperature monitoring system applied to silent generator set

Abstract

The application discloses an intelligent temperature monitoring system applied to a silent generator set, and the system is characterized in that: after an operation abnormality occurs, data before the operation abnormality is backtracked and analyzed, temperature sensors are arranged at key positions of the silent generator set, temperature changes and temperature states of each point are acquired, ambient temperatures of the silent generator set are read and analyzed at the same time, the influence of environmental changes is considered, a warning model of the silent generator set in a set time period before the operation abnormality occurs is constructed, a warning threshold range of the operation abnormality of the silent generator set is obtained based on the warning model, the analysis of the abnormality precursor temperature change before the abnormality occurs is realized, and if the analysis result in a set time period in the future matches the warning threshold range, the corresponding warning model is directly output, future faults are predicted, and the number of faults is reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of generator set monitoring, in particular to an intelligent temperature monitoring system applied to a silent generator set. BACKGROUND

[0002] The silent generator set is widely used in various occasions due to its low noise characteristics, especially in environments with strict noise level requirements.

[0003] In the application process, the temperature of the silent generator set during operation needs to be monitored, and the temperature monitoring system in the prior art still has the following deficiencies:

[0004] Mostly rely on simple threshold setting, trigger an alarm and perform maintenance and adjustment when the set threshold is reached, but at this time the silent generator set has already run abnormally, lack of in-depth analysis of temperature changes before the abnormal precursor, so as to establish a relevant early warning mechanism to predict and prevent future operation abnormalities, reduce the number of failures, and the degree of intelligence is low.

[0005] Therefore, an intelligent temperature monitoring system applied to a silent generator set is proposed. SUMMARY

[0006] Therefore, the present application provides an intelligent temperature monitoring system applied to a silent generator set to solve the problems raised in the background art.

[0007] The purpose of the present application can be achieved by the following technical scheme: an intelligent temperature monitoring system applied to a silent generator set, comprising:

[0008] The fault analysis module: after the silent generator set runs abnormally, the running temperature change of the silent generator set in the set time period before the abnormal running is analyzed, and the early warning model of the silent generator set in the current set time period is constructed based on the result of the analysis.

[0009] The model establishment module: receives the early warning model of the silent generator set in the current set time period, obtains the early warning threshold range of the silent generator set for this time based on the early warning model, and integrates it into the constructed database.

[0010] The fault processing module: after each operation exception of the silent generator set occurs, the adjustment processing result of the silent generator set when each operation exception occurs is collected, and if the silent generator set matches the corresponding early warning model within a set time period, the corresponding adjustment processing result corresponding to the corresponding early warning model is directly executed, and after the corresponding adjustment processing result is executed, the operation temperature parameter of the silent generator set within a set time period after the adjustment processing is monitored and analyzed in real time, and if the analysis result still matches the corresponding early warning model in the database, the maintenance signaling is triggered and the corresponding steps are executed, and the process of triggering the maintenance signaling this time is recorded as the candidate adjustment processing result of the corresponding early warning model.

[0011] In some embodiments, the operation parameters of the silent generator set within a set time period before the operation exception occurs are analyzed, specifically:

[0012] S1: Extract the temperature values of each arrangement point of the silent generator set at each time point within a set time period, and analyze to obtain the change index, state index and abnormal index of each arrangement point of the silent generator set within a set time period; wherein i represents the number of the corresponding arrangement point, i=1, 2, …, g, g represents the total number of arrangement points;

[0013] S2: Read the ambient temperature values of the surrounding environment of the silent generator set at each time point within a set time period, and take the maximum value of the ambient temperature values at each time point as the peak temperature value of the silent generator set within a set time period;

[0014] Each group of temperature value ranges of the preset peak temperature value is set, and each group of temperature value ranges is set to the highest allowable value of each arrangement point change index, state index and abnormal index, respectively; the peak temperature value is matched with the preset each group of temperature value ranges to obtain the highest allowable change index, the highest allowable state index and the highest allowable abnormal index of each arrangement point of the silent generator set within a set time period;

[0015] S3: Extract the change index and the highest allowable change index of each arrangement point of the silent generator set within a set time period, calculate the ratio between the change index and the highest allowable change index of each arrangement point, and then sum each group of ratios to obtain a first construction value of the silent generator set within a set time period;

[0016] Extract the state index and the highest allowable state index of each arrangement point of the silent generator set within a set time period, calculate the ratio between the state index and the highest allowable state index of each arrangement point, and then sum each group of ratios to obtain a second construction value of the silent generator set within a set time period;

[0017] Extracting the abnormality index and the highest allowable abnormality index of each arrangement point of the silent generator set in the set time period, respectively calculating the ratio between the abnormality index and the highest allowable abnormality index of each arrangement point, and then summing up each group of ratios to obtain the constructed ternary of the silent generator set in the set time period.

[0018] In some embodiments, the change index, the state index and the abnormality index of each arrangement point of the silent generator set in the set time period are obtained, specifically:

[0019] Obtaining the temperature value of each time point of the corresponding arrangement point in the set time period, and constructing a temperature change broken line graph of the corresponding arrangement point in the set time period from the temperature value, drawing the numerical point of the temperature value of each time point in the broken line graph, connecting adjacent numerical points to obtain a line segment, which is called a trend line; calculating the slope of each trend line and the included angle with the horizontal line, if the included angle is obtuse, the slope of the trend line is marked as an upward value, if the included angle is acute, the slope of the trend line is marked as a downward value, summing up all the upward values to obtain a first total value, summing up all the downward values to obtain a second total value; calculating through the first total value / (second total value+k) to obtain the total ratio of the corresponding arrangement point in the set time period; wherein k is a preset natural constant;

[0020] Marking the highest numerical point and the lowest numerical point in the broken line graph, and constructing a vertical line between the two groups of marked points, calculating the length of the vertical line as the total difference value of the corresponding arrangement point in the set time period;

[0021] Extracting the weight coefficient of the total ratio and the total difference value of the corresponding arrangement point, multiplying the total ratio and the total difference value of the corresponding arrangement point by the corresponding weight coefficient respectively, and then summing up to obtain the change index of the corresponding arrangement point in the set time period;

[0022] Obtaining the temperature value of each time point of the corresponding arrangement point in the set time period, and taking the mean value of the temperature value of each time point as the state index of the corresponding arrangement point in the set time period;

[0023] From the temperature value of each time point of the corresponding arrangement point in the set time period, extracting the highest temperature value as the abnormality index of the corresponding arrangement point in the set time period.

[0024] In some embodiments, a warning model of the silent generator set in the current set time period is constructed, specifically:

[0025] The build binary value and the build ternary value of the silent generator set in a set time period are extracted, and the build binary value and the build ternary value are summed, and the summed value is taken as the bottom diameter of a cylinder, the build unary value of the silent generator set in the set time period is extracted as the height of the cylinder, and the cylinder model of the silent generator set in the set time period is constructed based on the bottom diameter and the height, and the constructed cylinder model is taken as the early warning model of the silent generator set in the current set time period.

[0026] In some embodiments, the early warning threshold range of the abnormal operation of the silent generator set is obtained based on the early warning model, and specifically:

[0027] The surface area of the early warning model of the silent generator set in the current set time period is calculated, the calculated surface area is taken as the middle value of the early warning threshold range corresponding to the abnormal operation, and the early warning threshold range of the abnormal operation of the silent generator set is obtained by integrating the preset upper and lower fluctuation ranges and the obtained middle value.

[0028] In some embodiments, the maintenance signaling is triggered and the corresponding steps are performed, and specifically:

[0029] M1: Taking the current position of the silent generator set as the center and setting the distance as the radius to make a circle; screening the maintenance personnel within the range of the circle at this time as the to-be-processed personnel triggering the maintenance signaling this time;

[0030] M2: The number of the to-be-processed personnel is marked as m, m=1, 2,..., v, and v represents the total number of the to-be-processed personnel within the current circle range;

[0031] M3: The work logs of each to-be-processed personnel are extracted from the database and analyzed to obtain the route distance Em, the processing performance value Ym and the work experience value Pm of each to-be-processed personnel; the above parameters are substituted into the formula to obtain the optimal allocation value Um of each to-be-processed personnel by weighted calculation; wherein , and are the influence weight factors of the route distance Em, the processing performance value Ym and the work experience value Pm respectively; is a preset correction factor;

[0032] M4: The to-be-processed personnel with the maximum optimal allocation value Um is taken as the solution personnel triggering the maintenance signaling this time, and the location and the unit picture of the silent generator set are sent to the mobile terminal of the solution personnel, the solution personnel arrives at the location of the silent generator set, and then the problems existing in the silent generator set are investigated and adjusted, and the investigation and adjustment process is fed back to the fault processing module; at the same time, the total processing times of the personnel in the month is increased by one.

[0033] In some embodiments, the route distance Em of each to-be-processed person, the processing performance value Ym and the work experience value Pm are obtained, specifically as follows:

[0034] The position feedback signaling is sent to the mobile terminal of the corresponding to-be-processed person, so that the location of the corresponding to-be-processed person at the current time point is obtained; and the route distance Em of the corresponding to-be-processed person is obtained according to the location of the corresponding to-be-processed person and the location of the mute generator set;

[0035] The historical total selection times and the monthly selected times of the corresponding to-be-processed person are obtained from the work log of the corresponding to-be-processed person; further, the used maintenance time of each time is obtained from the historical total selection times of the corresponding to-be-processed person; the mean value of the used maintenance time of each group is taken as the maintenance mean time of the corresponding to-be-processed person; the monthly selected times, the historical total selection times and the maintenance mean time of the corresponding to-be-processed person are extracted and transformed, each group of value ranges of the monthly selected times, the historical total selection times and the maintenance mean time are preset, the monthly selected times, the historical total selection times and the maintenance mean time of the corresponding to-be-processed person are matched with the corresponding preset each group of value ranges respectively, the monthly selection score, the total selection score and the mean time score of the corresponding to-be-processed person are obtained; each group of value ranges of the monthly selected times, the historical total selection times and the maintenance mean time is set to correspond to a monthly selection score, a total selection score and a mean time score respectively, the monthly selection score, the total selection score and the mean time score of the corresponding to-be-processed person are accumulated, and the processing performance value Ym of the to-be-processed person is obtained.

[0036] The work time of the corresponding to-be-processed person is obtained from the work log of the corresponding to-be-processed person, and the time difference between the work time and the current time point is calculated, so that the work time of the corresponding to-be-processed person is obtained; each group of time length value ranges of the work time is preset, and each group of time length value ranges is set to correspond to a work experience score; the work time of the corresponding to-be-processed person is matched with the preset each group of time length value ranges, so that the work experience score of the corresponding to-be-processed person is obtained, and the work experience score is taken as the work experience value Pm of the corresponding to-be-processed person.

[0037] Compared with the prior art, the beneficial effects of the present application are:

[0038] The application considers the influence of environmental changes by backtracking the data before the operation abnormality occurs, arranging temperature sensors at key positions of the silent generator set, obtaining temperature changes and temperature states of each point, simultaneously reading and analyzing the ambient temperature of the silent generator set, constructing an early warning model of the silent generator set within a set time period before the operation abnormality occurs, and obtaining the early warning threshold range of the silent generator set this time based on the early warning model, thereby realizing the analysis of the abnormal precursor temperature change, and if the analysis result within a certain set time period in the future matches the early warning threshold range, the corresponding early warning model is directly output, the future fault is predicted, and the fault frequency is reduced.

[0039] The application collects the adjustment processing result of the silent generator set when the operation abnormality occurs each time, and if the silent generator set matches the corresponding early warning model within a set time period, the corresponding adjustment processing result corresponding to the early warning model is directly executed, and after the corresponding adjustment processing result is executed, the operation parameters of the silent generator set within a set time period after the adjustment processing are monitored and analyzed in real time, if the analysis result still matches the corresponding early warning model in the database, maintenance signaling is triggered and processed, and the process of triggering the maintenance signaling this time is recorded as the candidate adjustment processing result of the corresponding early warning model, thereby improving the operation and maintenance efficiency and quality of the silent generator set, reducing the abnormal time, and providing data support for continuous improvement. BRIEF DESCRIPTION OF DRAWINGS

[0040] In the following description of exemplary embodiments in conjunction with the accompanying drawings, more details, features and advantages of the application are disclosed, in which:

[0041] Figure 1 The figure is a schematic diagram of the principle of the application. DETAILED DESCRIPTION

[0042] Several embodiments of the application will be described in detail below with reference to the accompanying drawings, so as to enable those skilled in the art to implement the application. The application can be embodied in many different forms and purposes and should not be limited to the embodiments described herein. These embodiments are provided to make the application comprehensive and complete, and fully convey the scope of the application to those skilled in the art. The embodiments do not limit the application.

[0043] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and the present disclosure and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.

[0044] Referring to Figure 1 As shown in the drawings, an intelligent temperature monitoring system applied to a silent generator set comprises a fault analysis module, a model establishment module and a fault processing module.

[0045] The fault analysis module is configured to, after an operation abnormality occurs in the silent generator set, perform backtracking analysis on the operation temperature variation of the silent generator set in a set time period before the operation abnormality occurs, and construct a warning model of the silent generator set in the current set time period based on the result of the backtracking analysis.

[0046] The backtracking analysis on the operation parameters of the silent generator set in the set time period before the operation abnormality occurs is specifically as follows:

[0047] S1: Extract the temperature values of each arrangement point of the silent generator set at each time point in the set time period, and analyze to obtain the variation index, state index and abnormality index of each arrangement point of the silent generator set in the set time period; wherein i represents the number of the corresponding arrangement point, i = 1, 2 or g, g represents the total number of the arrangement points; the arrangement points include but are not limited to the temperature sensors arranged at key positions such as the air inlet, air outlet and cylinder body of the silent generator set, and the specific arrangement points are arranged by technical personnel.

[0048] S1-101: Obtain the temperature values of the corresponding arrangement point at each time point in the set time period, and construct a temperature variation broken line graph of the corresponding arrangement point in the set time period therefrom, draw the numerical points corresponding to the temperature values of each time point in the broken line graph, and connect adjacent numerical points to obtain a line segment, which is denoted as a trend line; calculate the slope of each trend line and the included angle with the horizontal line, if the included angle is obtuse, mark the slope of the trend line as an upward value, if the included angle is acute, mark the slope of the trend line as a downward value, sum all the upward values to obtain a first total value, sum all the downward values to obtain a second total value; calculate through the first total value / (the second total value+k) to obtain the total ratio of the corresponding arrangement point in the set time period; wherein k is a preset natural constant, and the value is >1, which is set by technical personnel to avoid the calculation process being invalid due to the second total value being 0;

[0049] Mark the highest and lowest value points in the line graph, and construct a vertical line between the two sets of marked points. Calculate the length of the vertical line as the total difference value of the corresponding layout point in the set time period;

[0050] Extract the weight coefficient of the total ratio and total difference value of the corresponding layout point; it is set by the technical personnel based on the specific location of the layout point, and can be adjusted according to the actual application situation; multiply the total ratio and total difference value of the corresponding layout point by the corresponding weight coefficient, and then sum to obtain the change index of the corresponding layout point in the set time period;

[0051] S2-102: Obtain the temperature value of the corresponding layout point at each time point in the set time period, and take the average of the temperature values at each time point as the state index of the corresponding layout point in the set time period;

[0052] S2-103: Extract the highest temperature value from the temperature values of the corresponding layout point at each time point in the set time period as the abnormal index of the corresponding layout point in the set time period;

[0053] S2: Read the ambient temperature value of the surrounding environment of the silent generator set at each time point in the set time period, and take the maximum value of the ambient temperature values at each time point as the peak temperature value of the silent generator set in the set time period;

[0054] Pre-set each group of temperature value range of the peak temperature value, set the highest allowable value of each layout point change index, state index and abnormal index respectively for each group of temperature value range; match the peak temperature value with the pre-set each group of temperature value range, to obtain the highest allowable change index, the highest allowable state index and the highest allowable abnormal index of each layout point of the silent generator set in the set time period;

[0055] S3: Extract the change index and the highest allowable change index of each layout point of the silent generator set in the set time period, calculate the ratio between the change index and the highest allowable change index of each layout point respectively, and then sum each group of ratios to obtain the construction one value of the silent generator set in the set time period;

[0056] Extract the state index and the highest allowable state index of each layout point of the silent generator set in the set time period, calculate the ratio between the state index and the highest allowable state index of each layout point respectively, and then sum each group of ratios to obtain the construction two value of the silent generator set in the set time period;

[0057] Extract the abnormal index and the highest allowable abnormal index of each layout point of the silent generator set in the set time period, calculate the ratio between the abnormal index and the highest allowable abnormal index of each layout point respectively, and then sum each group of ratios to obtain the construction three value of the silent generator set in the set time period;

[0058] It should be noted that by arranging temperature sensors at key positions of the silent generator set, the temperature changes and temperature states of each point can be accurately monitored, the ambient temperature of the silent generator set is read and analyzed, the influence of environmental changes is considered, and the accuracy of data analysis is improved.

[0059] The warning model of the silent generator set in the current setting time period is constructed, specifically:

[0060] The construction binary and construction ternary of the silent generator set in the setting time period are extracted, and the construction binary and construction ternary are summed. The summed value is used as the diameter of the bottom surface of the cylinder. The construction one value of the silent generator set in the setting time period is extracted as the height of the cylinder. Based on the diameter of the bottom surface and the height, the cylinder model of the silent generator set in the setting time period is constructed, and the constructed cylinder model is used as the warning model of the silent generator set in the current setting time period.

[0061] The model integration module is used to receive the warning model of the silent generator set in the current setting time period, obtain the warning threshold range of the abnormal operation of the silent generator set this time based on the warning model, and integrate it into the constructed database.

[0062] The warning threshold range of the abnormal operation of the silent generator set this time is obtained based on the warning model, specifically:

[0063] The surface area of the warning model of the silent generator set in the current setting time period is calculated. The calculated surface area is used as the middle value of the corresponding warning threshold range of the abnormal operation this time. According to the preset upper and lower fluctuation range, which is set by the technician and can be adjusted according to the actual application situation. The obtained middle value is integrated as the warning threshold range of the abnormal operation of the silent generator set this time. If the surface area of the warning model in a certain setting time period is within the integrated warning threshold range this time, it matches the corresponding warning model of the abnormal operation this time.

[0064] The fault processing module is used to collect the adjustment processing results of the silent generator set when the abnormal operation occurs each time after the abnormal operation of the silent generator set occurs each time. The adjustment processing results include but are not limited to heat dissipation adjustment, load adjustment, voltage and frequency adjustment, and mechanical fault processing. If the silent generator set matches the corresponding warning model in the setting time period, the corresponding adjustment processing result corresponding to the corresponding warning model is directly executed, and the running temperature parameters of the silent generator set in the setting time period after the adjustment processing are monitored and analyzed in real time. If the analysis result still matches the corresponding warning model in the database, the maintenance signaling is triggered and the corresponding steps are executed, and the process of triggering the maintenance signaling this time is recorded as the candidate adjustment processing result of the corresponding warning model.

[0065] Triggering maintenance signaling and performing corresponding steps, specifically:

[0066] M1: Taking the current location of the silent generator set as the center of a circle, a circle is set with the distance as the radius; for example, the distance is set to 1 kilometer, which is specifically set and adjusted by the technical personnel; screening the maintenance personnel within the range of the circle at this time as the to-be-processed personnel of this triggered maintenance signaling; if there is no maintenance personnel within the range of the circle, multiply the set distance by an integer two as the new set distance to make a circle;

[0067] M2: Mark the number of the to-be-processed personnel as m, m=1, 2 or v, v represents the total number of to-be-processed personnel within the current circle range;

[0068] M3: Extract the work log of each to-be-processed personnel from the database and analyze it to obtain the route distance Em, the processing performance value Ym and the work experience value Pm of each to-be-processed personnel; Substitute the above parameters into the formula , and perform weighted calculation to obtain the optimal matching value Um of each to-be-processed personnel; wherein , and are the influence weight factors of the route distance Em, the processing performance value Ym and the work experience value Pm respectively, and the values are set to 1.578, 1.627 and 1.593 respectively; is a preset correction factor, and the value is set to 0.853;

[0069] M3-301: Send a position feedback signaling to the mobile terminal of the corresponding to-be-processed personnel, thereby obtaining the location of the corresponding to-be-processed personnel at the current time point; according to the location of the corresponding to-be-processed personnel and the location of the silent generator set, the route distance Em of the corresponding to-be-processed personnel is obtained;

[0070] M3-302: obtain the historical total selection times and the month selected times of the corresponding to-be-handled personnel from the work log corresponding to the to-be-handled personnel; further obtain the used maintenance time of each time from the historical total selection times of the corresponding to-be-handled personnel; the used maintenance time starts to be counted from the time when the to-be-handled personnel arrives at the location of the silent generator set, and ends to be counted after the process of checking and adjusting is fed back to the fault handling module, and the time length of the segment is taken as the used maintenance time of the to-be-handled personnel; take the mean value of the used maintenance time of each group as the maintenance mean time of the corresponding to-be-handled personnel; extract the month selected times, the historical total selection times and the maintenance mean time of the corresponding to-be-handled personnel, and transform them; preset the value range of each group of the month selected times, the historical total selection times and the maintenance mean time, match the month selected times, the historical total selection times and the maintenance mean time of the corresponding to-be-handled personnel with the preset value range of each group respectively, and obtain the month selection score, the total selection score and the mean time score of the corresponding to-be-handled personnel; set that each group of the value range of the month selected times, the historical total selection times and the maintenance mean time corresponds to a month selection score, a total selection score and a mean time score respectively; the score range of the month selection score, the total selection score and the mean time score is set to be 1-10, and the positive integer, the more the month selected times, the lower the month selection score matched, the longer the maintenance mean time, the lower the month selection score matched, and the more the historical total selection times, the higher the total selection score matched; add the month selection score, the total selection score and the mean time score of the corresponding to-be-handled personnel to obtain the handling performance value Ym of the to-be-handled personnel;

[0071] It should be noted that the more the month selected times of the to-be-handled personnel, the higher the work load of the employee in the month, and the lower the matched month selection score; the more the historical total selection times of the to-be-handled personnel, the higher the processing experience of the employee, and the higher the matched total selection score; the shorter the maintenance mean time of the to-be-handled personnel, the faster the processing efficiency of the personnel, and the higher the matched mean time score, thereby providing a method for quantitatively evaluating the performance of maintenance personnel.

[0072] M3-303: obtain the employment time of the corresponding to-be-handled personnel from the work log corresponding to the to-be-handled personnel, and calculate the time difference between the employment time and the current time point to obtain the working time length of the corresponding to-be-handled personnel; preset the time length value range of each group of the working time length, and set that each group of the time length value range corresponds to a work experience score; match the working time length of the corresponding to-be-handled personnel with the preset time length value range of each group to obtain the work experience score of the corresponding to-be-handled personnel; the work experience score range is set to be 1-10, and the positive integer, the longer the working time length, the higher the work experience score matched; take the work experience score as the work experience value Pm of the corresponding to-be-handled personnel;

[0073] M4: the person to be processed with the largest optimal matching value Um is taken as the solving person of the triggered maintenance signaling, and the location of the silent generator set and the picture of the generator set are sent to the mobile terminal of the solving person, the solving person arrives at the location of the silent generator set, and then the existing problems of the silent generator set are investigated and adjusted, and the investigation and adjustment process is fed back to the fault processing module; meanwhile, the total processing times of the person in the month is added by one;

[0074] It should be noted that the operation and maintenance efficiency and quality of the silent generator set are improved by intelligent and automatic means, the abnormal time is reduced, and data support is provided for continuous improvement.

[0075] The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula close to the true value, and the influence weight factor and specific coefficient value in the formula are set by the person skilled in the art according to the actual situation, which can be adjusted and modified later.

[0076] The preferred embodiments disclosed above are only used to help explain the present application. The preferred embodiments do not describe all the details and limit the present application to the specific embodiments. Obviously, many modifications and changes can be made according to the content of the present application. The present application is selected and described in detail in order to better explain the principles and practical application of the present application, so that the person skilled in the art can well understand and utilize the present application. The present application is limited by the claims and the entire scope and equivalents thereof.

Claims

1. An intelligent temperature monitoring system applied to a silent generator set, characterized in that, The method comprises the following steps: a fault analysis module: after the operation of the silent generator set is abnormal, the temperature change of the silent generator set within a set time period before the operation is abnormal is analyzed, and a warning model of the silent generator set within the set time period is constructed based on the analysis result; constructing a warning model of the silent generator set within the set time period, specifically: extracting the temperature values of each arrangement point of the silent generator set at each time point within the set time period, and analyzing to obtain the change index, state index and abnormal index of each arrangement point of the silent generator set within the set time period; According to the change index, state index and abnormal index within the set time period, the construction one value, construction two value and construction three value are calculated respectively; extracting the construction two value and construction three value of the silent generator set within the set time period, and summing the construction two value and construction three value, taking the summed value as the diameter of the bottom surface of the cylinder, extracting the construction one value of the silent generator set within the set time period as the height of the cylinder, and constructing a cylinder model of the silent generator set within the set time period based on the diameter of the bottom surface and the height, and taking the constructed cylinder model as the warning model of the silent generator set within the set time period; a model establishment module: receiving the warning model of the silent generator set within the set time period, obtaining the warning threshold range of the silent generator set for this operation based on the warning model, and integrating into the constructed database; obtaining the warning threshold range of the silent generator set for this operation based on the warning model, specifically: calculating the surface area of the warning model of the silent generator set within the set time period, taking the calculated surface area as the middle value of the corresponding warning threshold range of this operation, and integrating according to the preset upper and lower fluctuation range and the obtained middle value as the warning threshold range of the silent generator set for this operation; a fault processing module: after the operation of the silent generator set is abnormal each time, the adjustment processing result of the silent generator set when the operation is abnormal each time is collected, and if the silent generator set matches the corresponding warning model within the set time period, the corresponding adjustment processing result corresponding to the corresponding warning model is directly executed, and after the corresponding adjustment processing result is executed, the operation temperature parameter of the silent generator set within the set time period after the adjustment processing is monitored and analyzed in real time, if the analysis result still matches the corresponding warning model in the database, a maintenance signaling is triggered and the corresponding steps are executed, and the process of triggering the maintenance signaling this time is recorded as the candidate adjustment processing result of the corresponding warning model.

2. The intelligent temperature monitoring system applied to the silent generator set according to claim 1, characterized in that, backtracking analysis is performed on the operation parameters of the silent generator set within a set time period before the operation is abnormal, specifically: S1: extracting the temperature values of each arrangement point of the silent generator set at each time point within the set time period, and analyzing to obtain the change index, state index and abnormal index of each arrangement point of the silent generator set within the set time period; wherein i represents the number of the corresponding arrangement point, i=1,2,......,g, g represents the total number of arrangement points; S2: reading the ambient temperature values of the ambient environment of the silent generator set at each time point in the set time period, and taking the maximum value of the ambient temperature values at each time point as the peak temperature value of the silent generator set in the set time period; presetting a temperature value range for each group of peak temperature values, setting the highest allowable value of each change index, state index and abnormal index for each arrangement point respectively in each temperature value range, matching the peak temperature value with each preset temperature value range to obtain the highest allowable change index, highest allowable state index and highest allowable abnormal index of each arrangement point of the silent generator set in the set time period; S3: extracting the change index and the highest allowable change index of each arrangement point of the silent generator set in the set time period, calculating the ratio between the change index and the highest allowable change index of each arrangement point respectively, and then summing each group of ratios to obtain a first value of the silent generator set in the set time period; extracting the state index and the highest allowable state index of each arrangement point of the silent generator set in the set time period, calculating the ratio between the state index and the highest allowable state index of each arrangement point respectively, and then summing each group of ratios to obtain a second value of the silent generator set in the set time period; extracting the abnormal index and the highest allowable abnormal index of each arrangement point of the silent generator set in the set time period, calculating the ratio between the abnormal index and the highest allowable abnormal index of each arrangement point respectively, and then summing each group of ratios to obtain a third value of the silent generator set in the set time period.

3. The intelligent temperature monitoring system applied to the silent generator set according to claim 2, characterized in that, obtaining the change index, state index and abnormal index of each arrangement point of the silent generator set in the set time period, specifically: obtaining the temperature values of each time point in the set time period for the corresponding arrangement point, and constructing a temperature change broken line graph for the corresponding arrangement point in the set time period, drawing the numerical points of the temperature values of each time point in the broken line graph, connecting adjacent numerical points to obtain a line segment, and marking the line segment as a trend line; calculating the slope of each trend line and the included angle with the horizontal line, if the included angle is obtuse, marking the slope of the trend line as an upward value, if the included angle is acute, marking the slope of the trend line as a downward value, summing all upward values to obtain a first total value, and summing all downward values to obtain a second total value; calculating the first total value / (second total value+k) to obtain the total ratio of the corresponding arrangement point in the set time period; wherein k is a preset natural constant, and the value is >1; marking the highest numerical point and the lowest numerical point in the broken line graph, and constructing a vertical line between the two groups of marked points, calculating the length of the vertical line as the total difference value of the corresponding arrangement point in the set time period; extracting the weight coefficients of the total ratio and the total difference value of the corresponding arrangement point, multiplying the total ratio and the total difference value of the corresponding arrangement point by the corresponding weight coefficients respectively, and then summing to obtain the change index of the corresponding arrangement point in the set time period; obtaining the temperature values of each time point in the set time period for the corresponding arrangement point, and taking the mean value of the temperature values at each time point as the state index of the corresponding arrangement point in the set time period; Extract the highest temperature value from the temperature values of the corresponding layout point at each time point within the set time period as the abnormal index of the corresponding layout point within the set time period.

4. The intelligent temperature monitoring system for a silent generator set according to claim 1, wherein, Trigger maintenance signaling and perform corresponding steps, specifically: M1: Set the current position of the silent generator set as the center and a distance as the radius to make a circle; select the maintenance personnel within the range of the circle as the to-be-processed personnel for this triggered maintenance signaling; M2: Mark the number of the to-be-processed personnel as m, m = 1, 2, …, v, v represents the total number of to-be-processed personnel within the current circle range; M3: Extracts the work log of each to-be-processed person from the database and analyzes to obtain the route distance Em, the processing performance value Ym and the work experience value Pm of each to-be-processed person; substitutes the above parameters into the formula , performs weighted calculation to obtain the optimal matching value Um of each to-be-processed person; wherein , and are the influence weight factors of the route distance Em, the processing performance value Ym and the work experience value Pm respectively; is a preset correction factor; M4: Take the to-be-processed personnel with the maximum optimal allocation value Um as the solution personnel for this triggered maintenance signaling, and send the location and unit picture of the silent generator set to the mobile terminal of the solution personnel; after the solution personnel arrives at the location of the silent generator set, the solution personnel checks and adjusts the problems of the silent generator set, and feeds back the checking and adjusting process to the fault processing module; at the same time, the total processing times of the personnel in the current month is increased by one.

5. The intelligent temperature monitoring system for a silent generator set according to claim 4, wherein, Obtain the route distance Em, processing performance value Ym and work experience value Pm of each to-be-processed personnel, specifically: Send the location feedback signaling to the mobile terminal of the corresponding to-be-processed personnel, thereby obtaining the location of the corresponding to-be-processed personnel at the current time point; obtain the route distance Em of the corresponding to-be-processed personnel according to the location of the corresponding to-be-processed personnel and the location of the silent generator set; Obtain the historical total selection times and the monthly selected times of the corresponding to-be-processed personnel from the work log of the corresponding to-be-processed personnel; further obtain the maintenance time of each time from the historical total selection times of the corresponding to-be-processed personnel; take the average of each group of maintenance time as the maintenance average time of the corresponding to-be-processed personnel; Extract the monthly selected times, historical total selection times and maintenance average time of the corresponding to-be-processed personnel, and perform conversion; preset each group of value range of the monthly selected times, historical total selection times and maintenance average time, set each group of value range of the monthly selected times, historical total selection times and maintenance average time to correspond to a monthly selection score, a total selection score and an average time score respectively, match the monthly selected times, historical total selection times and maintenance average time of the corresponding to-be-processed personnel with the preset each group of value range respectively, and obtain the monthly selection score, the total selection score and the average time score of the corresponding to-be-processed personnel; Add the monthly selection score, the total selection score and the average time score of the corresponding to-be-processed personnel to obtain the processing performance value Ym of the to-be-processed personnel; Obtain the employment time of the corresponding to-be-processed personnel from the work log of the corresponding to-be-processed personnel, and perform time difference calculation on the employment time and the current time point to obtain the work time of the corresponding to-be-processed personnel; preset each group of time length value range of the work time, set each group of time length value range to correspond to a work experience score respectively; match the work time of the corresponding to-be-processed personnel with the preset each group of time length value range to obtain the work experience score of the corresponding to-be-processed personnel, and take the work experience score as the work experience value Pm of the corresponding to-be-processed personnel.

Images