Chain store equipment operation inspection system based on data analysis

Abstract

The invention relates to the field of chain store equipment management, in particular to a chain store equipment operation inspection system based on data analysis, and is used for solving the problems that an existing chain store equipment operation inspection mode is long in response time, low in inspection efficiency and accuracy and inaccurate in maintenance personnel matching. The system comprises the following modules: an equipment monitoring module, an equipment analysis module, an operation evaluation module, an abnormity notification module, a personnel analysis module and a personnel management module. The system accurately monitors the operation fault of the store equipment in real time, improves the timeliness and accuracy of fault discovery, selects the most suitable maintenance personnel for the fault equipment, improves the maintenance efficiency and quality, optimizes the inspection flow through an intelligent means, shortens the inspection period, improves the inspection efficiency, accuracy and timeliness, and improves the maintenance efficiency and quality. The system improves the overall operation efficiency and service quality of chain stores, and has wide application prospects and market values.

Description

Technical Field

[0001] The present invention relates to the field of chain store equipment management, and in particular to a chain store equipment operation inspection system based on data analysis. Background Art

[0002] In recent years, the business scale of chain stores has continued to expand, and the number of store equipment has also shown an upward trend. However, operational failures of store equipment occur from time to time, which not only affects the normal operation of the store, but also causes economic losses and a decline in customer experience. Traditional equipment maintenance methods often rely on manual inspections and telephone repairs, which have problems such as long response time, low inspection efficiency and accuracy, and inaccurate matching of maintenance personnel. It is impossible to accurately grasp the equipment failure situation, and the selection of maintenance personnel is also unscientific, resulting in poor maintenance results and affecting the normal operation of the store.

[0003] Therefore, there is an urgent need for a chain store equipment operation inspection system that can effectively monitor the operating status of store equipment, intelligently warn of faults, and accurately dispatch maintenance personnel. This can not only shorten the fault handling time and improve the repair efficiency, but also improve the work efficiency and satisfaction of maintenance personnel. Summary of the invention

[0004] In order to overcome the above-mentioned technical problems, the purpose of the present invention is to provide a chain store equipment operation inspection system based on data analysis, which solves the problems of long response time, low inspection efficiency and accuracy, and inaccurate matching of maintenance personnel in the existing chain store equipment operation inspection method.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] A chain store equipment operation inspection system based on data analysis, including:

[0007] The equipment monitoring module is used to obtain the equipment monitoring parameters of the monitoring equipment i and send the equipment monitoring parameters to the equipment analysis module; wherein the equipment monitoring parameters include temperature and humidity information WS, voltage information DY, current information DL and vibration and sound information ZY;

[0008] The equipment analysis module is used to obtain the equipment monitoring coefficient SBi according to the equipment monitoring parameters, and send the equipment monitoring coefficient SBi to the operation evaluation module;

[0009] The specific process of the equipment analysis module obtaining the equipment monitoring coefficient SBi is as follows:

[0010] Normalize the temperature and humidity information WS, voltage information DY, current information DL and vibration and sound information ZY, and quantize the values ​​of the temperature and humidity information WS, voltage information DY, current information DL and vibration and sound information ZY according to a preset equipment monitoring model to obtain an equipment monitoring coefficient SBi;

[0011] Among them, the equipment monitoring model is as follows:

[0012]

[0013] Where:

[0014] ε is the preset error adjustment factor, and ε=1.113;

[0015] Both e and π are mathematical constants;

[0016] α1, α2, α3 and α4 are preset weight factors corresponding to the set temperature and humidity information WS, voltage information DY, current information DL and vibration and sound information ZY respectively, α1, α2, α3 and α4 satisfy α1>α2>α3>α4>1.125, and α1=2.91, α2=2.27, α3=1.88, α4=1.39;

[0017] Send the equipment monitoring coefficient SBi to the operation evaluation module;

[0018] The operation evaluation module is used to obtain abnormal store equipment according to the equipment monitoring coefficient SBi, and send the abnormal store equipment to the abnormal notification module;

[0019] The abnormal notification module is used to obtain abnormal stores based on abnormal store equipment and notify the store managers of the abnormal stores.

[0020] As a further solution of the present invention: the specific process of the device monitoring module obtaining the device monitoring parameters is as follows:

[0021] Obtain all running store devices in the chain store and mark them as monitoring devices i, i = 1, ..., v, v is a positive integer, i is the number of any monitoring device, and v is the total number of monitoring devices;

[0022] Obtain the temperature at the preset collection point inside the monitoring device i and the preset standard temperature, obtain the difference between the two, and mark it as the temperature difference value CW, obtain the humidity at the preset collection point inside the monitoring device i and the preset standard humidity, obtain the difference between the two, and mark it as the humidity difference value CS, quantify the temperature difference value CW and the humidity difference value CS, extract the values ​​of the temperature difference value CW and the humidity difference value CS, and substitute them into the formula for calculation, and obtain the temperature and humidity information WS according to the formula WS=c1×CW+c2×CS; wherein c1 and c2 are the preset proportional coefficients corresponding to the set temperature difference value CW and humidity difference value CS, respectively, c1 and c2 satisfy c1+c2=1, 0<c2<c1<1, and c1=0.58 and c2=0.42;

[0023] Obtain several real-time voltages of monitoring device i within a unit time, obtain the average value of all real-time voltages, and mark it as the average voltage value, obtain the difference between the average voltage value and the preset rated voltage, and mark it as the average pressure difference CJy, obtain the maximum real-time voltage and the minimum real-time voltage, obtain the difference between the two, and mark it as the maximum pressure difference CZy, quantify the average pressure difference CJy and the maximum pressure difference CZy, extract the values ​​of the average pressure difference CJy and the maximum pressure difference CZy, and substitute them into the formula for calculation. According to the formula The voltage information DY is obtained; wherein y1 and y2 are preset proportional coefficients corresponding to the set voltage difference mean value CJy and the voltage difference maximum value CZy, respectively, y1 and y2 satisfy y1+y2=1, 0<y2<y1<1, and y1=0.78, y2=0.22;

[0024] Obtain several real-time currents of monitoring device i within a unit time, obtain the average value of all real-time currents, and mark it as the average current value, obtain the difference between the average current value and the preset rated current, and mark it as the average current difference CJ l, obtain the maximum real-time current and the minimum real-time current, obtain the difference between the two, and mark it as the maximum current difference CZ l, quantify the average current difference CJ l and the maximum current difference CZ l, extract the values ​​of the average current difference CJ l and the maximum current difference CZ l, and substitute them into the formula for calculation. According to the formula The current information DL is obtained; wherein l1 and l2 are preset proportional coefficients corresponding to the set current difference mean value CJl and the current difference maximum value CZl, respectively; l1 and l2 satisfy l1+l2=1, 0<l2<l1<1, and l1=0.66 and l2=0.34;

[0025] Obtain the total number of vibrations and the maximum real-time sound intensity of the monitoring device i per unit time, and mark them as the vibration frequency value ZC and the sound intensity value SQ respectively, obtain the product of the vibration frequency value ZC and the sound intensity value SQ, and mark it as vibration sound information ZY;

[0026] The temperature and humidity information WS, voltage information DY, current information DL and vibration and sound information ZY are sent to the equipment analysis module.

[0027] As a further solution of the present invention: the specific process of the operation evaluation module obtaining abnormal store equipment is as follows:

[0028] The equipment monitoring coefficient SBi is compared with the preset equipment monitoring threshold SBz. The comparison results are as follows:

[0029] If the equipment monitoring coefficient SBi≥equipment monitoring threshold SBz, the monitoring device i corresponding to the equipment monitoring coefficient SBi is marked as an abnormal store device, and the abnormal store device is sent to the abnormal notification module.

[0030] As a further solution of the present invention: the specific process of the abnormal notification module notifying the store manager of the abnormal store is as follows:

[0031] Get the chain store to which the abnormal store device belongs, mark it as an abnormal store, and send the abnormal store device to the mobile terminal of the store manager of the abnormal store;

[0032] The store manager checks the abnormal store equipment. If the abnormality is confirmed, he clicks the "Confirm" button through the mobile terminal, generates a personnel analysis instruction, and sends the personnel analysis instruction to the personnel analysis module.

[0033] As a further solution of the present invention: the chain store equipment operation inspection system based on data analysis also includes:

[0034] The personnel analysis module is used to obtain the personnel analysis parameters of abnormal stores after receiving the personnel analysis instructions, and obtain the personnel analysis coefficient RYo based on the personnel analysis parameters, and send the personnel analysis coefficient RYo to the personnel management module; wherein the personnel analysis parameters include distance information LJ, experience information JY and scoring information PF.

[0035] As a further solution of the present invention: the specific process of the personnel analysis module obtaining the personnel analysis parameters is as follows:

[0036] After receiving the personnel analysis instruction, the location of the abnormal store is obtained and marked as the reference center, and a circular area is drawn with the reference center as the center and the preset length as the radius, and the circular area is marked as the reference area;

[0037] Obtain all idle maintenance personnel in the reference area, and mark them as analysis objects o in sequence, where o=1, ..., u, where u is a positive integer, o is the number of any analysis object, and u is the total number of analysis objects;

[0038] Obtain the length of the travel road between the position of the analysis object o and the reference center, and mark it as the road distance information LJ;

[0039] Obtain the total working time of the analysis object o and the total number of times the abnormal store equipment is repaired, and mark them as the working time value GS and the inspection value JC respectively. Draw an ellipse with the working time value GS and the inspection value JC as the major axis and minor axis of the ellipse respectively, obtain the area of ​​the ellipse, and mark it as the experience information JY;

[0040] Obtain the scores of the store managers of the abnormal stores after the abnormal store equipment of the analysis object o is repaired, obtain the average of all scores, and mark it as the score information PF.

[0041] As a further solution of the present invention: the specific process of the personnel analysis module obtaining the personnel analysis coefficient RYo is as follows:

[0042] The road distance information LJ, the experience information JY and the scoring information PF are normalized, and the values ​​of the road distance information LJ, the experience information JY and the scoring information PF are quantified according to a preset personnel analysis model to obtain a personnel analysis coefficient RYo;

[0043] Among them, the personnel analysis model is as follows:

[0044]

[0045] Where:

[0046] λ is the preset error adjustment factor, and λ=0.964;

[0047] Both e and π are mathematical constants;

[0048] β1, β2 and β3 are respectively the preset weight factors corresponding to the set road distance information LJ, the experience information JY and the score information PF, β1, β2 and β3 satisfy β2>β1>β3>2.018, and β1=2.88, β2=3.35, β3=2.27;

[0049] The personnel analysis coefficient RYo is sent to the personnel management module.

[0050] As a further solution of the present invention: the chain store equipment operation inspection system based on data analysis also includes:

[0051] The personnel management module is used to obtain the selected maintenance personnel according to the personnel analysis coefficient RYo, and send the location of the abnormal store and the abnormal store equipment to the mobile terminal of the selected maintenance personnel.

[0052] As a further solution of the present invention: the specific process of the personnel management module obtaining the selected maintenance personnel is as follows:

[0053] Sort all analysis objects o according to the personnel analysis coefficient RYo from large to small, and mark the first analysis object o as the selected maintenance personnel;

[0054] The location of the abnormal store and the abnormal store equipment are sent to the mobile terminal of the selected maintenance personnel.

[0055] As a further solution of the present invention: the working method of the chain store equipment operation inspection system based on data analysis includes the following steps:

[0056] Step 1: The device monitoring module obtains the device monitoring parameters of the monitoring device i, wherein the device monitoring parameters include temperature and humidity information WS, voltage information DY, current information DL and vibration and sound information ZY, and sends the device monitoring parameters to the device analysis module;

[0057] Step 2: The equipment analysis module obtains the equipment monitoring coefficient SBi according to the equipment monitoring parameters, and sends the equipment monitoring coefficient SB i to the operation evaluation module;

[0058] Step 3: The operation evaluation module obtains abnormal store equipment according to the equipment monitoring coefficient SBi, and sends the abnormal store equipment to the abnormal notification module;

[0059] Step 4: The abnormal notification module obtains the abnormal store according to the abnormal store equipment and notifies the store manager of the abnormal store;

[0060] Step 5: After receiving the personnel analysis instruction, the personnel analysis module obtains the personnel analysis parameters of the abnormal store, wherein the personnel analysis parameters include the distance information LJ, the experience information JY and the scoring information PF, obtains the personnel analysis coefficient RYo according to the personnel analysis parameters, and sends the personnel analysis coefficient RYo to the personnel management module;

[0061] Step 6: The personnel management module obtains the selected maintenance personnel according to the personnel analysis coefficient RYo, and sends the location of the abnormal store and the abnormal store equipment to the mobile terminal of the selected maintenance personnel.

[0062] Beneficial effects of the present invention:

[0063] A chain store equipment operation inspection system based on data analysis of the present invention first collects data from monitoring equipment to obtain equipment monitoring parameters, then uses data analysis technology to obtain equipment monitoring coefficients based on equipment monitoring parameters to comprehensively measure the degree of abnormal operation of the monitoring equipment, and the larger the equipment monitoring coefficient, the higher the degree of abnormal operation. When the degree of abnormal operation is high, an abnormal notification is made, then data is collected from maintenance personnel to obtain personnel analysis parameters, then uses data analysis technology to obtain personnel analysis coefficients based on personnel analysis parameters to comprehensively measure the quality of maintenance personnel, and the larger the personnel analysis coefficient, the higher the quality of maintenance personnel. Finally, excellent maintenance personnel are selected for maintenance dispatch;

[0064] The chain store equipment operation inspection system based on data analysis of the present invention can monitor the operation failure of store equipment in real time and accurately, improve the timeliness and accuracy of fault discovery, select the most suitable maintenance personnel for the faulty equipment, improve the maintenance efficiency and quality, optimize the inspection process through intelligent means, shorten the inspection cycle, improve the inspection efficiency, accuracy and timeliness, and improve the overall operating efficiency and service quality of the chain store. It has broad application prospects and market value. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] The present invention will be further described below in conjunction with the accompanying drawings.

[0066] Figure 1 It is a principle block diagram of a chain store equipment operation inspection system based on data analysis in the present invention;

[0067] Figure 2 It is a flow chart of a working method of a chain store equipment operation inspection system based on data analysis in the present invention. DETAILED DESCRIPTION

[0068] The following will be combined with 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.

[0069] Embodiment 1:

[0070] See also Figure 1 As shown, this embodiment is a chain store equipment operation inspection system based on data analysis, including the following modules: equipment monitoring module, equipment analysis module, operation evaluation module, abnormal notification module, personnel analysis module and personnel management module;

[0071] The device monitoring module is used to obtain the device monitoring parameters of the monitoring device i and send the device monitoring parameters to the device analysis module; wherein the device monitoring parameters include temperature and humidity information WS, voltage information DY, current information DL and vibration and sound information ZY;

[0072] The equipment analysis module is used to obtain the equipment monitoring coefficient SBi according to the equipment monitoring parameters, and send the equipment monitoring coefficient SB i to the operation evaluation module;

[0073] The operation evaluation module is used to obtain abnormal store equipment according to the equipment monitoring coefficient SBi, and send the abnormal store equipment to the abnormal notification module;

[0074] The abnormal notification module is used to obtain abnormal stores according to abnormal store equipment and notify the store manager of the abnormal store;

[0075] The personnel analysis module is used to obtain the personnel analysis parameters of the abnormal store after receiving the personnel analysis instruction, obtain the personnel analysis coefficient RYo according to the personnel analysis parameters, and send the personnel analysis coefficient RYo to the personnel management module; wherein the personnel analysis parameters include the distance information LJ, the experience information JY and the scoring information PF;

[0076] Among them, the personnel management module is used to obtain the selected maintenance personnel according to the personnel analysis coefficient RYo, and send the location of the abnormal store and the abnormal store equipment to the mobile terminal of the selected maintenance personnel.

[0077] Embodiment 2:

[0078] See also Figure 2 As shown, this embodiment is a working method of a chain store equipment operation inspection system based on data analysis, comprising the following steps:

[0079] Step 1: The device monitoring module obtains the device monitoring parameters of the monitoring device i, wherein the device monitoring parameters include temperature and humidity information WS, voltage information DY, current information DL and vibration and sound information ZY, and sends the device monitoring parameters to the device analysis module;

[0080] Step 2: The equipment analysis module obtains the equipment monitoring coefficient SBi according to the equipment monitoring parameters, and sends the equipment monitoring coefficient SB i to the operation evaluation module;

[0081] Step 3: The operation evaluation module obtains abnormal store equipment according to the equipment monitoring coefficient SBi, and sends the abnormal store equipment to the abnormal notification module;

[0082] Step 4: The abnormal notification module obtains the abnormal store according to the abnormal store equipment and notifies the store manager of the abnormal store;

[0083] Step 5: After receiving the personnel analysis instruction, the personnel analysis module obtains the personnel analysis parameters of the abnormal store, wherein the personnel analysis parameters include the distance information LJ, the experience information JY and the scoring information PF, obtains the personnel analysis coefficient RYo according to the personnel analysis parameters, and sends the personnel analysis coefficient RYo to the personnel management module;

[0084] Step 6: The personnel management module obtains the selected maintenance personnel according to the personnel analysis coefficient RYo, and sends the location of the abnormal store and the abnormal store equipment to the mobile terminal of the selected maintenance personnel.

[0085] Embodiment 3:

[0086] Based on any of the above embodiments, Embodiment 3 of the present invention is a device monitoring module. The function of the device monitoring module is to obtain device monitoring parameters, wherein the device monitoring parameters include temperature and humidity information WS, voltage information DY, current information DL and vibration information ZY. The specific process is as follows:

[0087] The equipment monitoring module obtains all the running store equipment in the chain store and marks them as monitoring equipment i in sequence, i=1, ..., v, v is a positive integer, i is the number of any monitoring equipment, and v is the total number of monitoring equipment;

[0088] The equipment monitoring module obtains the temperature at the preset collection point inside the monitoring device i and the preset standard temperature, obtains the difference between the two, and marks it as the temperature difference value CW, obtains the humidity at the preset collection point inside the monitoring device i and the preset standard humidity, obtains the difference between the two, and marks it as the humidity difference value CS, quantifies the temperature difference value CW and the humidity difference value CS, extracts the values ​​of the temperature difference value CW and the humidity difference value CS, and substitutes them into the formula for calculation, and obtains the temperature and humidity information WS according to the formula WS=c1×CW+c2×CS; wherein c1 and c2 are the preset proportional coefficients corresponding to the set temperature difference value CW and humidity difference value CS, respectively, and c1 and c2 satisfy c1+c2=1, 0<c2<c1<1, and c1=0.58 and c2=0.42;

[0089] The equipment monitoring module obtains several real-time voltages of the monitoring equipment i within a unit time, obtains the average value of all real-time voltages, and marks it as the average voltage value, obtains the difference between the average voltage value and the preset rated voltage, and marks it as the average pressure difference CJy, obtains the maximum real-time voltage and the minimum real-time voltage, obtains the difference between the two, and marks it as the maximum pressure difference CZy, quantifies the average pressure difference CJy and the maximum pressure difference CZy, extracts the values ​​of the average pressure difference CJy and the maximum pressure difference CZy, and substitutes them into the formula for calculation. According to the formula The voltage information DY is obtained; wherein y1 and y2 are preset proportional coefficients corresponding to the set voltage difference mean value CJy and the voltage difference maximum value CZy, respectively, y1 and y2 satisfy y1+y2=1, 0<y2<y1<1, and y1=0.78, y2=0.22;

[0090] The equipment monitoring module obtains several real-time currents of the monitoring equipment i within a unit time, obtains the average value of all real-time currents, and marks it as the average current value, obtains the difference between the average current value and the preset rated current, and marks it as the average current difference CJ l, obtains the maximum real-time current and the minimum real-time current, obtains the difference between the two, and marks it as the maximum current difference CZ l, quantifies the average current difference CJ l and the maximum current difference CZ l, extracts the values ​​of the average current difference CJl and the maximum current difference CZ l, and substitutes them into the formula for calculation. According to the formula The current information DL is obtained; wherein l 1 and l 2 are respectively the preset proportional coefficients corresponding to the set current difference mean value CJ l and the current difference maximum value CZ l, l 1,

[0091] l 2 satisfies l 1+l 2=1, 0<l 2<l 1<1, so l 1=0.66, l 2=0.34;

[0092] The equipment monitoring module obtains the total number of vibrations and the maximum real-time sound intensity of the monitoring equipment i per unit time, and marks them as the vibration value ZC and the sound intensity value SQ respectively, obtains the product of the vibration value ZC and the sound intensity value SQ, and marks it as vibration and sound information ZY;

[0093] The equipment monitoring module sends the temperature and humidity information WS, voltage information DY, current information DL and vibration and sound information ZY to the equipment analysis module.

[0094] Embodiment 4:

[0095] Based on any of the above embodiments, Embodiment 4 of the present invention is a device analysis module. The function of the device analysis module is to obtain the device monitoring coefficient SB i. The specific process is as follows:

[0096] The equipment analysis module normalizes the temperature and humidity information WS, voltage information DY, current information DL and vibration and sound information ZY, and quantifies the values ​​of the temperature and humidity information WS, voltage information DY, current information DL and vibration and sound information ZY according to the preset equipment monitoring model to obtain the equipment monitoring coefficient SBi;

[0097] Among them, the equipment monitoring model is as follows:

[0098]

[0099] Where:

[0100] ε is the preset error adjustment factor, and ε=1.113;

[0101] Both e and π are mathematical constants;

[0102] α1, α2, α3 and α4 are preset weight factors corresponding to the set temperature and humidity information WS, voltage information DY, current information DL and vibration and sound information ZY respectively, α1, α2, α3 and α4 satisfy α1>α2>α3>α4>1.125, and α1=2.91, α2=2.27, α3=1.88, α4=1.39;

[0103] The equipment analysis module sends the equipment monitoring coefficient SBi to the operation evaluation module.

[0104] Embodiment 5:

[0105] Based on any of the above embodiments, Embodiment 5 of the present invention is an operation evaluation module. The function of the operation evaluation module is to obtain abnormal store equipment. The specific process is as follows:

[0106] The operation evaluation module compares the equipment monitoring coefficient SB i with the preset equipment monitoring threshold SBz. The comparison results are as follows:

[0107] If the equipment monitoring coefficient SBi≥equipment monitoring threshold SBz, the monitoring device i corresponding to the equipment monitoring coefficient SBi is marked as an abnormal store device, and the abnormal store device is sent to the abnormal notification module.

[0108] Embodiment 6:

[0109] Based on any of the above embodiments, Embodiment 6 of the present invention is an abnormal notification module. The function of the abnormal notification module is to notify the store manager of the abnormal store. The specific process is as follows:

[0110] The abnormal notification module obtains the chain store to which the abnormal store equipment belongs, marks it as an abnormal store, and sends the abnormal store equipment to the mobile terminal of the store manager of the abnormal store;

[0111] The store manager checks the abnormal store equipment. If the abnormality is confirmed, he clicks the "Confirm" button through the mobile terminal, generates a personnel analysis instruction, and sends the personnel analysis instruction to the personnel analysis module.

[0112] Embodiment 7:

[0113] Based on any of the above embodiments, Embodiment 7 of the present invention is a personnel analysis module. The function of the personnel analysis module is to obtain the personnel analysis coefficient RYo. The specific process is as follows:

[0114] After receiving the personnel analysis instruction, the personnel analysis module obtains the location of the abnormal store and marks it as the reference center, draws a circular area with the reference center as the center and a preset length as the radius, and marks the circular area as the reference area;

[0115] The personnel analysis module obtains all idle maintenance personnel in the reference area and marks them as analysis objects o, o=1, ..., u, where u is a positive integer, o is the number of any analysis object, and u is the total number of analysis objects;

[0116] The personnel analysis module obtains the length of the travel road between the position of the analysis object o and the reference center, and marks it as the road distance information LJ;

[0117] The personnel analysis module obtains the total working hours of the analysis object o and the total number of times the abnormal store equipment is repaired, and marks them as the working time value GS and the inspection value JC respectively. The ellipse is drawn with the values ​​of the working time value GS and the inspection value JC as the major axis and minor axis of the ellipse, and the area of ​​the ellipse is obtained, which is marked as the experience information JY;

[0118] The personnel analysis module obtains the scores of the store managers of the abnormal stores after the analysis object o is repaired, obtains the average of all scores, and marks it as the score information PF;

[0119] The personnel analysis module normalizes the road distance information LJ, the experience information JY and the scoring information PF, and quantifies the values ​​of the road distance information LJ, the experience information JY and the scoring information PF according to the preset personnel analysis model to obtain the personnel analysis coefficient RYo;

[0120] Among them, the personnel analysis model is as follows:

[0121]

[0122] Where:

[0123] λ is the preset error adjustment factor, and λ=0.964;

[0124] Both e and π are mathematical constants;

[0125] β1, β2 and β3 are respectively the preset weight factors corresponding to the set road distance information LJ, the experience information JY and the score information PF, β1, β2 and β3 satisfy β2>β1>β3>2.018, and β1=2.88, β2=3.35, β3=2.27;

[0126] The personnel analysis module sends the personnel analysis coefficient RYo to the personnel management module.

[0127] Embodiment 8:

[0128] Based on any of the above embodiments, Embodiment 8 of the present invention is a personnel management module. The function of the personnel management module is to obtain selected maintenance personnel. The specific process is as follows:

[0129] The personnel management module sorts all analysis objects o according to the personnel analysis coefficient RYo from large to small, and marks the analysis object o at the first place as the selected maintenance personnel;

[0130] The personnel management module sends the location of the abnormal store and the abnormal store equipment to the mobile terminal of the selected maintenance personnel.

[0131] Based on the above embodiments 1-8, the working principle of the present invention is as follows:

[0132] The present invention discloses a chain store equipment operation inspection system based on data analysis, which obtains equipment monitoring parameters of monitoring equipment through an equipment monitoring module, wherein the equipment monitoring parameters include temperature and humidity information, voltage information, current information and vibration and sound information, obtains equipment monitoring coefficients according to equipment monitoring parameters through an equipment analysis module, obtains abnormal store equipment according to the equipment monitoring coefficients through an operation evaluation module, obtains abnormal stores according to abnormal store equipment through an abnormal notification module, and notifies the store manager of the abnormal store, obtains personnel analysis parameters of abnormal stores after receiving personnel analysis instructions through a personnel analysis module, wherein the personnel analysis parameters include road distance information, experience information and scoring information, obtains personnel analysis coefficients according to personnel analysis parameters, obtains selected maintenance personnel according to the personnel analysis coefficients through a personnel management module, and sends the location of the abnormal store and the abnormal store equipment to the mobile phone terminal of the selected maintenance personnel; the system first collects data from the monitoring equipment, obtains equipment monitoring parameters, obtains equipment monitoring parameters, and sends the location of the abnormal store and the abnormal store equipment to the mobile phone terminal of the selected maintenance personnel; Control parameters, and then use data analysis technology to obtain the equipment monitoring coefficient based on the equipment monitoring parameters to comprehensively measure the degree of abnormal operation of the monitoring equipment, and the larger the equipment monitoring coefficient, the higher the degree of abnormal operation. When the degree of abnormal operation is high, an abnormal notification is made, and then data is collected on the maintenance personnel to obtain personnel analysis parameters. Then, the personnel analysis coefficient obtained based on the personnel analysis parameters using data analysis technology can comprehensively measure the quality of the maintenance personnel, and the larger the personnel analysis coefficient, the higher the quality of the maintenance personnel. Finally, excellent maintenance personnel are selected for maintenance dispatch; the system monitors the operating failures of store equipment in real time and accurately, improves the timeliness and accuracy of fault detection, and selects the most suitable maintenance personnel for faulty equipment, improves maintenance efficiency and quality, optimizes the inspection process through intelligent means, shortens the inspection cycle, improves inspection efficiency, accuracy and timeliness, and improves the overall operating efficiency and service quality of the chain store, and has broad application prospects and market value.

[0133] It should be further explained that the above formulas are obtained by collecting a large amount of data and performing software simulation, and a formula close to the actual value is selected. The coefficients in the formula are set by technical personnel in this field according to actual conditions.

[0134] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0135] The above contents are merely examples and explanations of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the invention or exceed the scope defined in this application, they shall all fall within the protection scope of the present invention.

Claims

1. A chain store equipment operation inspection system based on data analysis, characterized in that: include: The equipment monitoring module is used to obtain the equipment monitoring parameters of the monitoring equipment i and send the equipment monitoring parameters to the equipment analysis module; wherein the equipment monitoring parameters include temperature and humidity information WS, voltage information DY, current information DL and vibration and sound information ZY; The equipment analysis module is used to obtain the equipment monitoring coefficient SBi according to the equipment monitoring parameters, and send the equipment monitoring coefficient SBi to the operation evaluation module; The specific process of the equipment analysis module obtaining the equipment monitoring coefficient SBi is as follows: The values ​​of the temperature and humidity information WS, the voltage information DY, the current information DL and the vibration and sound information ZY are quantified and calculated according to the preset equipment monitoring model to obtain the equipment monitoring coefficient SBi; Among them, the equipment monitoring model is as follows: Where: ε is the preset error adjustment factor; Both e and π are mathematical constants; α1, α2, α3 and α4 are preset weight factors corresponding to the set temperature and humidity information WS, voltage information DY, current information DL and vibration and sound information ZY respectively; Send the equipment monitoring coefficient SBi to the operation evaluation module; The operation evaluation module is used to obtain abnormal store equipment according to the equipment monitoring coefficient SBi, and send the abnormal store equipment to the abnormal notification module; The abnormal notification module is used to obtain abnormal stores based on abnormal store equipment and notify the store managers of the abnormal stores.

2. According to the data analysis-based chain store equipment operation inspection system of claim 1, it is characterized in that: The specific process of the device monitoring module obtaining device monitoring parameters is as follows: Obtain all running store devices in the chain store and mark them as monitoring devices i in turn; The temperature at the preset collection point inside the monitoring device i and the preset standard temperature are obtained, the difference between the two is obtained, and it is marked as the temperature difference value CW; the humidity at the preset collection point inside the monitoring device i and the preset standard humidity are obtained, the difference between the two is obtained, and it is marked as the humidity difference value CS; the temperature difference value CW and the humidity difference value CS are quantified to obtain the temperature and humidity information WS; Obtain several real-time voltages of monitoring device i within a unit time, obtain the average value of all real-time voltages, and mark it as an average voltage value, obtain the difference between the average voltage value and the preset rated voltage, and mark it as a pressure difference average value CJy, obtain the maximum real-time voltage and the minimum real-time voltage, obtain the difference between the two, and mark it as a pressure difference maximum value CZy, quantize the pressure difference average value CJy and the pressure difference maximum value CZy, and obtain voltage information DY; Obtain several real-time currents of monitoring device i within a unit time, obtain the average value of all real-time currents, and mark it as the average current value, obtain the difference between the average current value and the preset rated current, and mark it as the current difference average value CJ1, obtain the maximum real-time current and the minimum real-time current, obtain the difference between the two, and mark it as the current difference maximum value CZ1, quantize the current difference average value CJ1 and the current difference maximum value CZ1, and obtain the current information DL; Obtain the total number of vibrations and the maximum real-time sound intensity of the monitoring device i per unit time, and mark them as the vibration frequency value ZC and the sound intensity value SQ respectively, obtain the product of the vibration frequency value ZC and the sound intensity value SQ, and mark it as vibration sound information ZY; The temperature and humidity information WS, voltage information DY, current information DL and vibration and sound information ZY are sent to the equipment analysis module.

3. The chain store equipment operation inspection system based on data analysis according to claim 1 is characterized in that: The specific process of the operation evaluation module obtaining abnormal store equipment is as follows: The equipment monitoring coefficient SBi is compared with the preset equipment monitoring threshold SBz. The comparison results are as follows: If the equipment monitoring coefficient SBi≥equipment monitoring threshold SBz, the monitoring device i corresponding to the equipment monitoring coefficient SBi is marked as an abnormal store device, and the abnormal store device is sent to the abnormal notification module.

4. The chain store equipment operation inspection system based on data analysis according to claim 1 is characterized in that: The specific process of the abnormal notification module notifying the store manager of the abnormal store is as follows: Get the chain store to which the abnormal store device belongs, mark it as an abnormal store, and send the abnormal store device to the mobile terminal of the store manager of the abnormal store; The store manager checks the abnormal store equipment. If the abnormality is confirmed, he clicks the "Confirm" button through the mobile terminal, generates a personnel analysis instruction, and sends the personnel analysis instruction to the personnel analysis module.

5. The chain store equipment operation inspection system based on data analysis according to claim 1 is characterized in that: Also includes: The personnel analysis module is used to obtain the personnel analysis parameters of abnormal stores after receiving the personnel analysis instructions, and obtain the personnel analysis coefficient RYo based on the personnel analysis parameters, and send the personnel analysis coefficient RYo to the personnel management module; wherein the personnel analysis parameters include distance information LJ, experience information JY and scoring information PF.

6. A chain store equipment operation inspection system based on data analysis according to claim 5, characterized in that: The specific process of the personnel analysis module obtaining personnel analysis parameters is as follows: After receiving the personnel analysis instruction, the location of the abnormal store is obtained and marked as the reference center, and a circular area is drawn with the reference center as the center and the preset length as the radius, and the circular area is marked as the reference area; Obtain all idle maintenance personnel in the reference area and mark them as analysis objects o in turn; Obtain the length of the travel road between the position of the analysis object o and the reference center, and mark it as the road distance information LJ; Obtain the total working time of the analysis object o and the total number of times the abnormal store equipment is repaired, and mark them as the working time value GS and the inspection value JC respectively. Draw an ellipse with the working time value GS and the inspection value JC as the major axis and minor axis of the ellipse respectively, obtain the area of ​​the ellipse, and mark it as the experience information JY; Obtain the scores of the store managers of the abnormal stores after the abnormal store equipment of the analysis object o is repaired, obtain the average of all scores, and mark it as the score information PF.

7. The chain store equipment operation inspection system based on data analysis according to claim 5 is characterized in that: The specific process of the personnel analysis module obtaining the personnel analysis coefficient RYo is as follows: The values ​​of the road distance information LJ, the experience information JY and the scoring information PF are quantified according to the preset personnel analysis model to obtain the personnel analysis coefficient RYo; Among them, the personnel analysis model is as follows: Where: λ is the preset error adjustment factor; Both e and π are mathematical constants; β1, β2 and β3 are preset weight factors corresponding to the set road distance information LJ, experience information JY and score information PF respectively; The personnel analysis coefficient RYo is sent to the personnel management module.

8. The chain store equipment operation inspection system based on data analysis according to claim 1 is characterized in that: Also includes: The personnel management module is used to obtain the selected maintenance personnel according to the personnel analysis coefficient RYo, and send the location of the abnormal store and the abnormal store equipment to the mobile terminal of the selected maintenance personnel.

9. The chain store equipment operation inspection system based on data analysis according to claim 8 is characterized in that: The specific process of the personnel management module obtaining the selected maintenance personnel is as follows: Sort all analysis objects o according to the personnel analysis coefficient RYo from large to small, and mark the first analysis object o as the selected maintenance personnel; The location of the abnormal store and the abnormal store equipment are sent to the mobile terminal of the selected maintenance personnel.

10. The chain store equipment operation inspection system based on data analysis according to claim 1 is characterized in that: The working method of the chain store equipment operation inspection system based on data analysis includes the following steps: Step 1: The device monitoring module obtains the device monitoring parameters of the monitoring device i, wherein the device monitoring parameters include temperature and humidity information WS, voltage information DY, current information DL and vibration and sound information ZY, and sends the device monitoring parameters to the device analysis module; Step 2: The equipment analysis module obtains the equipment monitoring coefficient SBi according to the equipment monitoring parameters, and sends the equipment monitoring coefficient SBi to the operation evaluation module; Step 3: The operation evaluation module obtains abnormal store equipment according to the equipment monitoring coefficient SBi, and sends the abnormal store equipment to the abnormal notification module; Step 4: The abnormal notification module obtains the abnormal store according to the abnormal store equipment and notifies the store manager of the abnormal store; Step 5: After receiving the personnel analysis instruction, the personnel analysis module obtains the personnel analysis parameters of the abnormal store, wherein the personnel analysis parameters include the distance information LJ, the experience information JY and the scoring information PF, obtains the personnel analysis coefficient RYo according to the personnel analysis parameters, and sends the personnel analysis coefficient RYo to the personnel management module; Step 6: The personnel management module obtains the selected maintenance personnel according to the personnel analysis coefficient RYo, and sends the location of the abnormal store and the abnormal store equipment to the mobile terminal of the selected maintenance personnel.

Images