Method for managing operation data of electric field intensity monitoring equipment

Abstract

The invention relates to the technical field of equipment monitoring, in particular to an electric field intensity monitoring equipment operation data management method, which comprises the steps of S1, acquiring equipment operation information, sensor information and environment information; s2, judging the running state of the equipment; s3, analyzing the abnormality of the environmental magnetic field intensity, and adjusting the judgment process of the equipment operation state; s4, evaluating the performance of the magnetic field sensor, and adjusting the analysis process of the environmental magnetic field intensity abnormality; s5, analyzing the validity of the equipment operation state according to the analysis result of the equipment operation state, and analyzing the management scheme of the equipment in the next monitoring period; and step S6, optimizing the analysis process of the validity of the operation state of the equipment, analyzing the fluctuation of the load of the equipment, and optimizing the analysis process of the abnormality of the load of the equipment according to the fluctuation of the load so as to optimize the management scheme of the equipment. The equipment operation monitoring efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of equipment monitoring, and in particular to a method for managing operation data of electric field strength monitoring equipment. Background Art

[0002] The electric field strength monitoring sensor is an auxiliary sensor device that is mounted on the monitored device. It monitors the device's power on / off, standby, and working status by monitoring the magnetic field generated by the monitored device when it is running. Because it is an external device, in a complex multi-device environment, it will be affected by the magnetic field generated by other nearby devices when they are working, resulting in erroneous magnetic field monitoring values, short-term power on / off, standby, and working records, affecting the accuracy of monitoring.

[0003] Chinese patent publication number CN110764474A discloses a method and system for monitoring the operating status of equipment, wherein the method includes: selecting several operating parameters of the equipment as parameters to be monitored; collecting multiple groups of historical data of several parameters to be monitored; constructing target data according to each group of historical data; using a non-parametric method to train the distribution model of the target parameter using the target data set; setting a safe distribution interval according to the preset confidence of the distribution model; collecting a set of current data of several parameters to be monitored; constructing current target data according to the current data of several parameters to be monitored; judging whether the current target data is within the safe distribution interval; if not, determining that the equipment is operating abnormally. The present invention constructs the target parameter data of the equipment based on the monitored operating parameter data, and uses a non-parametric method to characterize the distribution model of the target parameter data to obtain the safe distribution interval of the target data. When the current target data exceeds the safe distribution interval, it can be determined that the equipment is operating abnormally; it can be seen that when monitoring the equipment, this scheme only analyzes the equipment operating data, and there are problems of low equipment monitoring efficiency and low equipment management efficiency. Summary of the invention

[0004] The object of the present invention is to provide a method for managing operation data of electric field strength monitoring equipment to solve at least one of the problems existing in the prior art.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] Step S1, obtaining equipment operation information, sensor information and environmental information;

[0007] Step S2, judging the operating state of the device according to the acquired electric field strength and magnetic field strength of the device;

[0008] Step S3, analyzing the abnormality of the ambient magnetic field strength according to the acquired ambient magnetic field strength, and adjusting the judgment process of the equipment operation state according to the analysis result;

[0009] Step S4, evaluating the performance of the magnetic field sensor according to the acquired relative magnetic permeability of the magnetic field sensor shielding material and the thickness of the shielding layer, and adjusting the analysis process of the abnormality of the environmental magnetic field intensity according to the evaluation result;

[0010] Step S5, analyzing the effectiveness of the equipment operation status according to the analysis result of the equipment operation status, and analyzing the management plan of the equipment in the next monitoring period according to the analysis result of the effectiveness of the equipment operation status in the monitoring period;

[0011] Step S6, analyzing the abnormality of the equipment load according to the acquired equipment load, and optimizing the analysis process of the effectiveness of the equipment operating status according to the analysis results of the abnormality of the equipment load, analyzing the volatility of the equipment load, and optimizing the analysis process of the abnormality of the equipment load according to the volatility of the load, so as to optimize the management plan of the equipment.

[0012] Furthermore, the step S2 determines the operating state of the device according to the acquired device electric field strength E and device magnetic field strength B, wherein:

[0013] When E<E1 and B<B1, the running state of the device is determined to be the shutdown state;

[0014] When (E1≤E<E2 and B1≤B<B2) or (E1≤E<E2 and B<B1) or (E<E1 and B1≤B<B2), the operation state of the device is determined to be the standby state;

[0015] When E≥E2 or B≥B2, the equipment is judged to be in working state;

[0016] When (E≥E2 and B<B1) or (E<E1 and B≥B2) or (E1≤E<E2 and B≥B2) or (E≥E2 and B1≤B<B2), the operation state of the equipment is determined to be an abnormal state;

[0017] Among them, E1 is the first preset electric field strength threshold, E2 is the second preset electric field strength threshold, B1 is the first preset magnetic field strength threshold, and B2 is the second preset magnetic field strength threshold.

[0018] Furthermore, the step S3 compares the acquired ambient magnetic field strength HB with the preset ambient magnetic field strength HB0, and analyzes the abnormality of the ambient magnetic field strength according to the comparison result, wherein:

[0019] When HB≤HB0, the environmental magnetic field strength is judged to be normal;

[0020] When HB>HB0, the environmental magnetic field strength is judged to be abnormal;

[0021] When adjusting the judgment process of the equipment operation status, if the ambient magnetic field strength is normal, no adjustment is performed; if the ambient magnetic field strength is abnormal, the judgment process of the equipment operation status is adjusted, and the adjusted preset magnetic field strength threshold is set to Bb', and Bb'=Bb-α×(HB-HB0);

[0022] Wherein, Bb is the preset magnetic field strength threshold, b=1,2, and α is the preset adjustment coefficient.

[0023] Furthermore, in step S4, the magnetic field sensor performance evaluation method includes:

[0024] Step S41, calculating the magnetic permeability performance index according to the acquired relative magnetic permeability of the magnetic field sensor shielding material;

[0025] Step S42, calculating a thickness performance index according to the acquired thickness of the magnetic field sensor shielding layer;

[0026] Step S43, calculating the magnetic field sensor performance index according to the magnetic permeability performance index and the thickness performance index;

[0027] Step S44, adjusting the analysis process of the abnormality of the environmental magnetic field intensity according to the magnetic field sensor performance index;

[0028] The step S41 compares the acquired relative magnetic permeability c0 of the magnetic field sensor shielding material with the preset magnetic permeability c1, and calculates the magnetic permeability performance index according to the comparison result, wherein:

[0029] When c0≤c1, the relative magnetic permeability of the magnetic field sensor shielding material is determined to be abnormal, and the magnetic permeability performance index is set to N1, and N1 is set to 1-sin[arctan(c1-c0)×(π / 4) / c1];

[0030] When c0>c1, it is determined that the relative magnetic permeability of the magnetic field sensor shielding material is normal, and the magnetic permeability performance index is set to N2, and N2=1;

[0031] In the step S42, the obtained magnetic field sensor shielding layer thickness s0 is compared with the preset thickness s1, and the thickness performance index is calculated according to the comparison result, wherein:

[0032] When s0≤s1, it is determined that the thickness of the thick shielding layer of the magnetic field sensor is abnormal, and the thickness performance index is set to Q1, and Q1=1-exp{lg[(s1-s0) / s1]};

[0033] When s0>s1, it is determined that the thickness of the magnetic field sensor shielding layer is normal, and the thickness performance index is set to Q2, and Q2=1.

[0034] Further, the step S43 calculates the magnetic field sensor performance index XN according to the magnetic permeability performance index and the thickness performance index, and sets XN=w1×Nn+w2×Qq, wherein Nn is the magnetic permeability performance index, n=1,2; Qq is the thickness performance index, q=1,2; w1 is the magnetic permeability weight, and w2 is the thickness weight;

[0035] The step S44 adjusts the analysis process of the abnormality of the environmental magnetic field intensity according to the magnetic field sensor performance index, wherein:

[0036] When XN≤XN0, the performance of the magnetic field sensor is determined to be abnormal, and the analysis process of the abnormality of the ambient magnetic field strength is adjusted, and the adjusted preset ambient magnetic field strength is set to HB0', and HB0'=HB0×exp[-(XN0-XN)];

[0037] When XN>XN0, the performance of the magnetic field sensor is judged to be normal and no adjustment is performed;

[0038] Wherein, XN0 is the preset performance coefficient.

[0039] Furthermore, in step S5, the method for analyzing the management scheme of the equipment includes:

[0040] Step S51, analyzing the effectiveness of the equipment operation status according to the analysis result of the equipment operation status;

[0041] Step S52, analyzing the device standby time in the next monitoring cycle according to the judgment result of the device operation status effectiveness;

[0042] Step S53, prompting the user of abnormal equipment operation status according to the judgment result of the effectiveness of the equipment operation status within the monitoring period;

[0043] In step S51, the validity of the equipment operation status analysis is judged according to the analysis result of the equipment operation status, wherein:

[0044] When t0 i≤T, the duration of the i-th device state is determined to be abnormal, and the i-th device state corresponding to t0 i is regarded as an invalid state of the i-th device state;

[0045] When t0 i>T, it is determined that the duration of the i-th device state is normal, and the i-th device state corresponding to t0 i is taken as the valid state of the i-th device state;

[0046] Wherein, t0i is the duration of the i-th device state in the monitoring period, and T is the preset state judgment threshold.

[0047] Furthermore, the step S52 analyzes the device standby time in the next monitoring cycle according to the judgment result of the effectiveness of the device operation status, wherein:

[0048] When TC / T0≤u1, the device standby duration of the current monitoring cycle is determined to be normal, and the device standby duration of the next monitoring cycle is set to k0; when TC / T0≥u1, the device standby duration of the current monitoring cycle is determined to be abnormal, if k0≤k1, the device standby duration of the next monitoring cycle is set to k0, if k0>k1, the device standby duration of the next monitoring cycle is set to k2, and when k2≤k1, the value of k2 is k1;

[0049] Among them, u1 is the first preset proportion, k0 is the standby time of the device in the current monitoring period, and k1 is the preset standby time threshold.

[0050] Furthermore, the step S53 provides the user with an abnormal device operation status prompt according to the result of the judgment of the validity of the device operation status, wherein:

[0051] When TY / T0≤u2, the abnormal state duration of the equipment in the current monitoring period is determined to be normal, and the user is not prompted for abnormal equipment operation status;

[0052] When TY / T0>u2, it is determined that the duration of the abnormal state of the equipment in the current monitoring period is abnormal, and the user is prompted with the abnormal operation state of the equipment.

[0053] Furthermore, in step S6, the method for analyzing abnormality of equipment load includes:

[0054] Step S61, analyzing the abnormality of the equipment load according to the acquired equipment load, and optimizing the analysis process of the effectiveness of the equipment operation status according to the analysis result;

[0055] Step S62, analyzing the volatility of the equipment load according to the acquired equipment load, and optimizing the analysis process of the equipment load abnormality according to the analysis result;

[0056] In step S61, the abnormality of the equipment load is analyzed according to the acquired equipment load, and the analysis process of the effectiveness of the equipment operation status is optimized according to the analysis result, wherein:

[0057] When F i≤F0, the equipment load level corresponding to t0 i is determined to be normal and no optimization is performed;

[0058] When F i>F0, the equipment load level corresponding to t0 i is determined to be abnormal, and the judgment process of the effectiveness of the equipment operation status is optimized, and the optimized preset status judgment threshold is set to T', setting: T'=T×{1+ln[(F i-F0) / (F i+F0)+1]×cos{arctan[(F i-F0) / (F i+F0)]}};

[0059] Among them, F0 is the preset load level, Fi is the average value of the equipment load data corresponding to t0 i, J is the number of device load data corresponding to t0i, and fj is the j-th device load data corresponding to t0i.

[0060] Furthermore, in step S62, the fluctuation of the equipment load is analyzed according to the acquired equipment load, and the analysis process of the abnormality of the equipment load is optimized according to the analysis result, wherein:

[0061] when When t0i is reached, it is determined that the fluctuation of the equipment load data corresponding to t0i is normal and no optimization is performed;

[0062] when When t0i is reached, the fluctuation of the equipment load data corresponding to t0i is determined to be abnormal, and the analysis process of the equipment load abnormality is optimized, and the optimized preset load level is set to F0', and the setting is:

[0063] Among them, γ is the preset volatility coefficient.

[0064] The beneficial effects of the present invention are as follows: by judging the operating status of the equipment and adjusting the judgment process in combination with the environmental magnetic field, the adjustment process is optimized through sensor performance evaluation, the effective operating status of the equipment is obtained through short-time filtering, and the process is optimized, thereby improving the monitoring efficiency of the equipment and at the same time improving the management efficiency of the equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0066] Figure 1 It is a flowchart of the method for managing the operation data of the electric field strength monitoring equipment in this embodiment.

[0067] Figure 2 Schematic diagram of the flow of the magnetic field sensor performance evaluation method of this embodiment.

[0068] Figure 3 This is a flow chart of the management solution analysis of the equipment in this embodiment.

[0069] Figure 4 The figure is a flow chart of abnormality analysis of equipment load in this embodiment. DETAILED DESCRIPTION

[0070] In order to more clearly illustrate the present invention, the present invention is further described below in conjunction with preferred embodiments and accompanying drawings. Similar components in the accompanying drawings are represented by the same reference numerals. It should be understood by those skilled in the art that the content specifically described below is illustrative rather than restrictive, and should not be used to limit the scope of protection of the present invention.

[0071] It should be noted that, although the terms first, second, third, etc. may be used to describe in the embodiments of the present application, these descriptions should not be limited to these terms. These terms are only used to distinguish the descriptions. For example, without departing from the scope of the embodiments of the present application, the first may also be referred to as the second, and similarly, the second may also be referred to as the first.

[0072] See also Figure 1 As shown, it is a flow chart of the method for managing the operation data of the electric field strength monitoring device of this embodiment, including:

[0073] Step S1, obtaining equipment operation information, sensor information and environmental information; the equipment operation information includes equipment electric field strength, equipment magnetic field strength and equipment load, the sensor information includes relative magnetic permeability of magnetic field sensor shielding material and shielding layer thickness, and the environmental information includes environmental magnetic field strength; in this embodiment, no specific limitation is made on the acquisition method of equipment operation information, sensor information and environmental information, and those skilled in the art can freely set it, as long as the acquisition requirements of equipment operation information, sensor information and environmental information are met, wherein the equipment electric field strength can be obtained by an electric field strength sensor installed on the monitored equipment, the equipment magnetic field strength can be obtained by a magnetic field strength sensor installed on the monitored equipment, the equipment load is the power load of the equipment, the power load is the ratio of the current power to the maximum power, and can be obtained through the built-in power monitoring system of the equipment, the relative magnetic permeability of the magnetic field sensor shielding material and the shielding layer thickness can be obtained through interaction, and the environmental magnetic field strength can be obtained by evenly arranging at least three magnetic field sensors at a distance of 1m-2m from the monitored equipment, and the average value thereof is used as the environmental magnetic field strength. In this embodiment, no specific limitation is made on the distance from the monitored equipment, and those skilled in the art can freely set it, as long as the setting requirements of the distance are met;

[0074] Step S2, judging the operating state of the device according to the acquired electric field strength and magnetic field strength of the device;

[0075] Step S3, analyzing the abnormality of the ambient magnetic field strength according to the acquired ambient magnetic field strength, and adjusting the judgment process of the equipment operation state according to the analysis result;

[0076] Step S4, evaluating the performance of the magnetic field sensor according to the acquired relative magnetic permeability of the magnetic field sensor shielding material and the thickness of the shielding layer, and adjusting the analysis process of the abnormality of the environmental magnetic field intensity according to the evaluation result;

[0077] Step S5, analyzing the effectiveness of the equipment operation status according to the analysis result of the equipment operation status, and analyzing the management plan of the equipment in the next monitoring period according to the analysis result of the effectiveness of the equipment operation status in the monitoring period; in this embodiment, no specific limitation is made to the setting of the monitoring period, and those skilled in the art can freely set it, as long as the setting requirements of the monitoring period are met, wherein the monitoring period can be set to 24h, 36h, etc.;

[0078] Step S6, analyzing the abnormality of the equipment load according to the acquired equipment load, and optimizing the analysis process of the effectiveness of the equipment operating status according to the analysis results, analyzing the volatility of the equipment load, and optimizing the analysis process of the abnormality of the equipment load according to the volatility of the load, so as to optimize the management plan of the equipment.

[0079] Specifically, the electric field strength monitoring device operation data management method described in this embodiment is applied to the monitoring of the operating status of medical equipment in the presence of environmental magnetic field interference. The operating status of the equipment is judged and the judgment process is adjusted in combination with the environmental magnetic field. The adjustment process is optimized through sensor performance evaluation. The effective operating status of the equipment is obtained through short-time filtering, and the process is optimized. This improves the monitoring efficiency of the equipment and at the same time improves the management efficiency of the equipment.

[0080] Specifically, in step S2 of this embodiment, the operating state of the device is judged according to the acquired device electric field strength E and device magnetic field strength B, wherein:

[0081] When E<E1 and B<B1, the running state of the device is determined to be the shutdown state;

[0082] When (E1≤E<E2 and B1≤B<B2) or (E1≤E<E2 and B<B1) or (E<E1 and B1≤B<B2), the operation state of the device is determined to be the standby state;

[0083] When E≥E2 or B≥B2, the equipment is judged to be in working state;

[0084] When (E≥E2 and B<B1) or (E<E1 and B≥B2) or (E1≤E<E2 and B≥B2) or (E≥E2 and B1≤B<B2), the operation state of the equipment is determined to be an abnormal state;

[0085] Among them, E1 is the first preset electric field strength threshold, E2 is the second preset electric field strength threshold, B1 is the first preset magnetic field strength threshold, and B2 is the second preset magnetic field strength threshold.

[0086] Specifically, step S2 sets various preset thresholds to determine different operating states of the device, thereby improving the accuracy of the analysis of the effectiveness of the device operating state, thereby improving the accuracy of the analysis of the device management plan, and ultimately improving the monitoring efficiency of the device, while improving the management efficiency of the device; in this embodiment, the setting of the first preset electric field strength threshold, the second preset electric field strength threshold, the first preset magnetic field strength threshold and the second preset magnetic field strength threshold is not specifically limited, and those skilled in the art can set them freely, as long as the setting requirements of the first preset electric field strength threshold, the second preset electric field strength threshold, the first preset magnetic field strength threshold and the second preset magnetic field strength threshold are met, wherein, when the device type is a medical device, the optimal value range of E1 is 1-5V / m, the optimal value range of E2 is 10-50V / m, the optimal value range of B1 is 0.1-0.5μT, and the optimal value of B2 is 1-5μT.

[0087] Specifically, in step S3 of this embodiment, when analyzing the abnormality of the ambient magnetic field strength, the acquired ambient magnetic field strength HB is compared with the preset ambient magnetic field strength HB0, and the abnormality of the ambient magnetic field strength is analyzed according to the comparison result, wherein:

[0088] When HB≤HB0, the environmental magnetic field strength is judged to be normal;

[0089] When HB>HB0, the environmental magnetic field strength is judged to be abnormal;

[0090] When adjusting the judgment process of the equipment operation status, if the ambient magnetic field strength is normal, no adjustment is performed; if the ambient magnetic field strength is abnormal, the judgment process of the equipment operation status is adjusted, and the adjusted preset magnetic field strength threshold is set to Bb', and Bb'=Bb-α×(HB-HB0);

[0091] Wherein, Bb is the preset magnetic field strength threshold, b=1,2, and α is the preset adjustment coefficient.

[0092] Specifically, step S3 improves the accuracy of the abnormality analysis of the environmental magnetic field strength by setting the preset environmental magnetic field strength and the preset adjustment coefficient, thereby reducing the impact of the environmental magnetic field on the magnetic field strength of the equipment, thereby improving the accuracy of the analysis of the effectiveness of the equipment operation status, and then improving the accuracy of the equipment management plan analysis, and ultimately improving the monitoring efficiency of the equipment, while also improving the management efficiency of the equipment; in this embodiment, there is no specific limitation on the setting of the preset environmental magnetic field strength and the preset adjustment coefficient, and technical personnel in this field can set them freely, as long as the setting requirements of the preset environmental magnetic field strength and the preset adjustment coefficient are met, where the optimal value of HB0 is 0.1μT, and the optimal value of α is 0.68.

[0093] See also Figure 2 As shown, in step S4 of this embodiment, the magnetic field sensor performance evaluation method includes:

[0094] Step S41, calculating the magnetic permeability performance index according to the acquired relative magnetic permeability of the magnetic field sensor shielding material;

[0095] Step S42, calculating a thickness performance index according to the acquired thickness of the magnetic field sensor shielding layer;

[0096] Step S43, calculating the magnetic field sensor performance index according to the magnetic permeability performance index and the thickness performance index;

[0097] Step S44, adjusting the analysis process of the abnormality of the environmental magnetic field intensity according to the magnetic field sensor performance index.

[0098] Specifically, in step S41 of this embodiment, the acquired relative magnetic permeability c0 of the magnetic field sensor shielding material is compared with the preset magnetic permeability c1, and the magnetic permeability performance index is calculated according to the comparison result, wherein:

[0099] When c0≤c1, the relative magnetic permeability of the magnetic field sensor shielding material is determined to be abnormal, and the magnetic permeability performance index is set to N1, and N1 is set to 1-sin[arctan(c1-c0)×(π / 4) / c1];

[0100] When c0>c1, it is determined that the relative magnetic permeability of the magnetic field sensor shielding material is normal, and the magnetic permeability performance index is set to N2, and N2=1 is set.

[0101] Specifically, step S41 analyzes the magnetic permeability performance index of the magnetic field sensor to improve the accuracy of the magnetic field sensor performance evaluation, thereby improving the accuracy of the environmental magnetic field strength abnormality analysis, thereby improving the accuracy of the equipment operation status effectiveness analysis, thereby improving the accuracy of the equipment management plan analysis, and ultimately improving the equipment monitoring efficiency, while also improving the equipment management efficiency; in this embodiment, there is no specific limitation on the setting of the preset magnetic permeability, and technical personnel in this field can set it freely, as long as the setting requirements of the preset magnetic permeability are met, where the optimal value of c1 is 50000.

[0102] Specifically, in step S42 of this embodiment, the obtained thickness s0 of the magnetic field sensor shielding layer is compared with the preset thickness s1, and the thickness performance index is calculated according to the comparison result, wherein:

[0103] When s0≤s1, it is determined that the thickness of the thick shielding layer of the magnetic field sensor is abnormal, and the thickness performance index is set to Q1, and Q1=1-exp{lg[(s1-s0) / s1]};

[0104] When s0>s1, it is determined that the thickness of the magnetic field sensor shielding layer is normal, and the thickness performance index is set to Q2, and Q2=1.

[0105] Specifically, the step S42 analyzes the thickness performance index of the magnetic field sensor to improve the accuracy of the magnetic field sensor performance evaluation, thereby improving the accuracy of the environmental magnetic field strength abnormality analysis, thereby improving the accuracy of the equipment operation status effectiveness analysis, thereby improving the accuracy of the equipment management plan analysis, and ultimately improving the equipment monitoring efficiency, while also improving the equipment management efficiency; in this embodiment, there is no specific limitation on the setting of the preset thickness, and technical personnel in this field can set it freely, as long as the setting requirements of the preset thickness are met, where the optimal value of s1 is 0.1mm.

[0106] Specifically, in step S43 described in this embodiment, the magnetic field sensor performance index XN is calculated according to the magnetic permeability performance index and the thickness performance index, and XN=w1×Nn+w2×Qq is set, wherein Nn is the magnetic permeability performance index, n=1,2; Qq is the thickness performance index, q=1,2; w1 is the magnetic permeability weight, w2 is the thickness weight, w1+w2=1, w1>w2.

[0107] Specifically, step S43 improves the accuracy of the magnetic field sensor performance evaluation by setting various weights, thereby improving the accuracy of the environmental magnetic field strength abnormality analysis, thereby improving the accuracy of the equipment operation status effectiveness analysis, and then improving the accuracy of the equipment management plan analysis, and ultimately improving the equipment monitoring efficiency, while improving the equipment management efficiency; in this embodiment, there is no specific limitation on the setting of each weight, and technical personnel in this field can set it freely, as long as the setting requirements of each weight are met, where the optimal value of w1 is 0.63, and the optimal value of w2 is 0.37.

[0108] Specifically, in step S44 of this embodiment, the analysis process of the abnormality of the environmental magnetic field strength is adjusted according to the magnetic field sensor performance index, wherein:

[0109] When XN≤XN0, the performance of the magnetic field sensor is determined to be abnormal, and the analysis process of the abnormality of the ambient magnetic field strength is adjusted, and the adjusted preset ambient magnetic field strength is set to HB0', and HB0'=HB0×exp[-(XN0-XN)];

[0110] When XN>XN0, the performance of the magnetic field sensor is judged to be normal and no adjustment is performed;

[0111] Wherein, XN0 is the preset performance coefficient.

[0112] Specifically, step S44 improves the accuracy of the magnetic field sensor performance evaluation by setting a preset performance coefficient, thereby improving the accuracy of the environmental magnetic field strength abnormality analysis, thereby improving the accuracy of the equipment operation status effectiveness analysis, and then improving the accuracy of the equipment management plan analysis, and ultimately improving the equipment monitoring efficiency, while also improving the equipment management efficiency; in this embodiment, there is no specific limitation on the setting of the preset performance coefficient, and technical personnel in this field can set it freely, as long as the setting requirements of the preset performance coefficient are met, where the optimal value of XN0 is 0.8.

[0113] See also Figure 3 As shown, it is a method for analyzing the management scheme of the equipment in step S5 of this embodiment, including:

[0114] Step S51, analyzing the effectiveness of the equipment operation status according to the analysis result of the equipment operation status;

[0115] Step S52, analyzing the device standby time in the next monitoring cycle according to the judgment result of the device operation status effectiveness;

[0116] Step S53, prompting the user of abnormal equipment operation status according to the judgment result of the effectiveness of the equipment operation status within the monitoring period;

[0117] Step S54, using the analysis result of the device standby time in the next monitoring cycle and the result of the abnormal device operation status prompt as a management plan, and outputting it to the user.

[0118] Specifically, in step S51 of this embodiment, the validity of the equipment operation status analysis is judged according to the analysis result of the equipment operation status, wherein:

[0119] When t0 i≤T, the duration of the i-th device state is determined to be abnormal, and the i-th device state corresponding to t0 i is regarded as an invalid state of the i-th device state;

[0120] When t0 i>T, it is determined that the duration of the i-th device state is normal, and the i-th device state corresponding to t0 i is taken as the valid state of the i-th device state;

[0121] Wherein, t0i is the duration of the i-th device state in the monitoring period, and T is the preset state judgment threshold.

[0122] Specifically, t0 i in the step S51 is the duration from the start of the i-th device state to the end of the i-th device state within the monitoring period. This is an analysis of the device operating states of the shutdown state, the standby state and the working state, and does not include abnormal states. When the device operating state is an abnormal state, it is regarded as a valid state; the step S51 sets a preset state judgment threshold to improve the accuracy of the device operating state validity analysis, thereby improving the accuracy of the device management plan analysis, and ultimately improving the monitoring efficiency of the device, while also improving the management efficiency of the device; in this embodiment, the setting of the preset state judgment threshold is not specifically limited, and technicians in this field can set it freely, as long as the setting requirements of the preset state threshold are met, wherein the optimal value of T is 2 seconds.

[0123] Specifically, in step S52 of this embodiment, the device standby time in the next monitoring cycle is analyzed according to the judgment result of the validity of the device operation status, wherein:

[0124] When TC / T0≤u1, the standby time of the device in the current monitoring cycle is determined to be normal, and the standby time of the device in the next monitoring cycle is set to k0; when TC / T0≥u1, the standby time of the device in the current monitoring cycle is determined to be abnormal. If k0≤k1, the standby time of the device in the next monitoring cycle is set to k0. If k0>k1, the standby time of the device in the next monitoring cycle is set to k2, k2=k0×{2-exp[arctan(TC / T0-u1)×(π / 4)]}, when k2≤k1, the value of k2 is k1;

[0125] Among them, TC is the total duration of the effective standby state of the device during the monitoring period, T0 is the duration of the monitoring period, u1 is the first preset proportion, k0 is the standby duration of the device in the current monitoring period, and k1 is the preset standby duration threshold.

[0126] Specifically, the step S52 sets the first preset proportion and the preset standby time threshold to improve the accuracy of the standby time analysis of the equipment in the next monitoring cycle, thereby improving the accuracy of the equipment management plan analysis, and ultimately improving the monitoring efficiency of the equipment, while also improving the management efficiency of the equipment; in this embodiment, there is no specific limitation on the setting of the first preset proportion and the preset standby time threshold, and technical personnel in this field can set them freely, as long as the setting requirements of the first preset proportion and the preset standby time threshold are met, where the optimal value of u1 is 0.3, and when the equipment type is medical equipment, the optimal value of k1 is 15 minutes, and the standby time of the equipment in the current monitoring cycle described in this embodiment can be obtained through interaction.

[0127] Specifically, in step S53 of this embodiment, a prompt of abnormal device operation status is given to the user according to the result of judging the validity of the device operation status, wherein:

[0128] When TY / T0≤u2, the abnormal state duration of the equipment in the current monitoring period is determined to be normal, and the user is not prompted for abnormal equipment operation status;

[0129] When TY / T0>u2, the abnormal state duration of the equipment in the current monitoring period is determined to be abnormal, and the user is prompted with the abnormal equipment operation status;

[0130] Among them, TY is the total duration of the abnormal state of the equipment during the monitoring period, and u2 is the second preset abnormality ratio.

[0131] Specifically, step S53 improves the accuracy of abnormal prompts of equipment operating status by setting a second preset ratio, thereby improving the accuracy of equipment management solution analysis, and ultimately improving the monitoring efficiency of the equipment, while also improving the management efficiency of the equipment; in this embodiment, the setting of the second preset ratio is not specifically limited, and technicians in this field can set it freely, as long as the setting requirements of the second preset ratio are met, where the optimal value of u2 is 0.05.

[0132] See also Figure 4 As shown, in step S6 of this embodiment, the method for analyzing abnormality of equipment load includes:

[0133] Step S61, analyzing the abnormality of the equipment load according to the acquired equipment load, and optimizing the analysis process of the effectiveness of the equipment operation status according to the analysis result;

[0134] Step S62, analyzing the fluctuation of the equipment load according to the acquired equipment load and optimizing the analysis process of the equipment load abnormality according to the analysis result.

[0135] Specifically, in step S61 of this embodiment, the abnormality of the equipment load is analyzed according to the acquired equipment load, and the analysis process of the effectiveness of the equipment operation status is optimized according to the analysis result, wherein:

[0136] When F i≤F0, the equipment load level corresponding to t0 i is determined to be normal and no optimization is performed;

[0137] When Fi>F0, the equipment load level corresponding to t0i is determined to be abnormal, and the judgment process of the effectiveness of the equipment operation status is optimized. The optimized preset status judgment threshold is set to T', and the setting is: T'=T×{1+ln[(Fi-F0) / (Fi+F0)+1]×cos{arctan[(Fi-F0) / (Fi+F0)]}}

[0138] Among them, F0 is the preset load level, Fi is the average value of the equipment load data corresponding to t0 i, J is the number of device load data corresponding to t0i, and fj is the j-th device load data corresponding to t0i.

[0139] Specifically, step S61 improves the accuracy of equipment load abnormality analysis by setting a preset load level, thereby improving the accuracy of equipment operation status effectiveness analysis, thereby improving the accuracy of equipment management solution analysis, and ultimately improving equipment monitoring efficiency while improving equipment management efficiency. In this embodiment, the setting of the preset load level is not specifically limited, and technicians in this field can set it freely as long as the setting requirements of the preset load level are met. The optimal value of F0 is 0.7.

[0140] Specifically, in step S62 of this embodiment, the fluctuation of the equipment load is analyzed according to the acquired equipment load, and the analysis process of the abnormality of the equipment load is optimized according to the analysis result, wherein:

[0141] when When t0i is reached, it is determined that the fluctuation of the equipment load data corresponding to t0i is normal and no optimization is performed;

[0142] when When t0i is reached, the fluctuation of the equipment load data corresponding to t0i is determined to be abnormal, and the analysis process of the equipment load abnormality is optimized, and the optimized preset load level is set to F0', and the setting is:

[0143] Among them, γ is the preset volatility coefficient.

[0144] Specifically, step S62 reduces the accuracy of equipment load abnormality analysis due to load fluctuation anomalies by setting a preset fluctuation coefficient, thereby improving the accuracy of equipment load abnormality analysis, and further improving the accuracy of equipment operation status effectiveness analysis, thereby improving the accuracy of equipment management scheme analysis, and ultimately improving equipment monitoring efficiency, while also improving equipment management efficiency; in this embodiment, no specific limitation is made to the setting of the preset fluctuation coefficient, and technical personnel in this field can set it freely, as long as the setting requirements of the preset fluctuation coefficient are met, wherein the optimal value of γ is 0.15.

[0145] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not limitations on the embodiments of the present invention. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is impossible to list all the embodiments here. All obvious changes or modifications derived from the technical solution of the present invention are still within the protection scope of the present invention.

Claims

1. A method for managing operation data of electric field strength monitoring equipment, characterized in that: include, Step S1, obtaining equipment operation information, sensor information and environmental information; Step S2, judging the operating state of the device according to the acquired electric field strength and magnetic field strength of the device; Step S3, analyzing the abnormality of the ambient magnetic field strength according to the acquired ambient magnetic field strength, and adjusting the judgment process of the equipment operation state according to the analysis result; Step S4, evaluating the performance of the magnetic field sensor according to the acquired relative magnetic permeability of the magnetic field sensor shielding material and the thickness of the shielding layer, and adjusting the analysis process of the abnormality of the environmental magnetic field intensity according to the evaluation result; Step S5, analyzing the effectiveness of the equipment operation status according to the analysis result of the equipment operation status, and analyzing the management plan of the equipment in the next monitoring period according to the analysis result of the effectiveness of the equipment operation status in the monitoring period; Step S6, analyzing the abnormality of the equipment load according to the acquired equipment load, and optimizing the analysis process of the effectiveness of the equipment operating status according to the analysis results of the abnormality of the equipment load, analyzing the volatility of the equipment load, and optimizing the analysis process of the abnormality of the equipment load according to the volatility of the load, so as to optimize the management plan of the equipment.

2. The method for managing operation data of electric field strength monitoring equipment according to claim 1, characterized in that: The step S2 determines the operating state of the device according to the acquired device electric field strength E and device magnetic field strength B, wherein: When E<E1 and B<B1, the running state of the device is determined to be the shutdown state; When (E1≤E<E2 and B1≤B<B2) or (E1≤E<E2 and B<B1) or (E<E1 and B1≤B<B2), the operation state of the device is determined to be the standby state; When E≥E2 or B≥B2, the equipment is judged to be in working state; When (E≥E2 and B<B1) or (E<E1 and B≥B2) or (E1≤E<E2 and B≥B2) or (E≥E2 and B1≤B<B2), the operation state of the equipment is determined to be an abnormal state; Among them, E1 is the first preset electric field strength threshold, E2 is the second preset electric field strength threshold, B1 is the first preset magnetic field strength threshold, and B2 is the second preset magnetic field strength threshold.

3. The method for managing operation data of electric field strength monitoring equipment according to claim 2, characterized in that: The step S3 compares the acquired ambient magnetic field strength HB with the preset ambient magnetic field strength HB0, and analyzes the abnormality of the ambient magnetic field strength according to the comparison result, wherein: When HB≤HB0, the environmental magnetic field strength is judged to be normal; When HB>HB0, the environmental magnetic field strength is judged to be abnormal; When adjusting the judgment process of the equipment operation status, if the ambient magnetic field strength is normal, no adjustment is performed; if the ambient magnetic field strength is abnormal, the judgment process of the equipment operation status is adjusted, and the adjusted preset magnetic field strength threshold is set to Bb', and Bb'=Bb-α×(HB-HB0); Wherein, Bb is the preset magnetic field strength threshold, b=1,2, and α is the preset adjustment coefficient.

4. The method for managing operation data of electric field strength monitoring equipment according to claim 3, characterized in that: In step S4, the magnetic field sensor performance evaluation method includes: Step S41, calculating the magnetic permeability performance index according to the acquired relative magnetic permeability of the magnetic field sensor shielding material; Step S42, calculating a thickness performance index according to the acquired thickness of the magnetic field sensor shielding layer; Step S43, calculating the magnetic field sensor performance index according to the magnetic permeability performance index and the thickness performance index; Step S44, adjusting the analysis process of the abnormality of the environmental magnetic field intensity according to the magnetic field sensor performance index; The step S41 compares the acquired relative magnetic permeability c0 of the magnetic field sensor shielding material with the preset magnetic permeability c1, and calculates the magnetic permeability performance index according to the comparison result, wherein: When c0≤c1, the relative magnetic permeability of the magnetic field sensor shielding material is determined to be abnormal, and the magnetic permeability performance index is set to N1, and N1 is set to 1-sin[arctan(c1-c0)×(π / 4) / c1]; When c0>c1, it is determined that the relative magnetic permeability of the magnetic field sensor shielding material is normal, and the magnetic permeability performance index is set to N2, and N2=1; In the step S42, the obtained magnetic field sensor shielding layer thickness s0 is compared with the preset thickness s1, and the thickness performance index is calculated according to the comparison result, wherein: When s0≤s1, it is determined that the thickness of the thick shielding layer of the magnetic field sensor is abnormal, and the thickness performance index is set to Q1, and Q1=1-exp{lg[(s1-s0) / s1]}; When s0>s1, it is determined that the thickness of the magnetic field sensor shielding layer is normal, and the thickness performance index is set to Q2, and Q2=1.

5. The method for managing operation data of electric field strength monitoring equipment according to claim 4, characterized in that: The step S43 calculates the magnetic field sensor performance index XN according to the magnetic permeability performance index and the thickness performance index, and sets XN=w1×Nn+w2×Qq, wherein Nn is the magnetic permeability performance index, n=1,2; Qq is the thickness performance index, q=1,2; w1 is the magnetic permeability weight, and w2 is the thickness weight; The step S44 adjusts the analysis process of the abnormality of the environmental magnetic field intensity according to the magnetic field sensor performance index, wherein: When XN≤XN0, the performance of the magnetic field sensor is determined to be abnormal, and the analysis process of the abnormality of the ambient magnetic field strength is adjusted, and the adjusted preset ambient magnetic field strength is set to HB0', and HB0'=HB0×exp[-(XN0-XN)]; When XN>XN0, the performance of the magnetic field sensor is judged to be normal and no adjustment is performed; Wherein, XN0 is the preset performance coefficient.

6. The method for managing operation data of electric field strength monitoring equipment according to claim 5, characterized in that: In step S5, the method for analyzing the management scheme of the equipment includes: Step S51, analyzing the effectiveness of the equipment operation status according to the analysis result of the equipment operation status; Step S52, analyzing the device standby time in the next monitoring cycle according to the judgment result of the device operation status effectiveness; Step S53, prompting the user of abnormal equipment operation status according to the judgment result of the effectiveness of the equipment operation status within the monitoring period; In step S51, the validity of the equipment operation status analysis is judged according to the analysis result of the equipment operation status, wherein: When t0 i≤T, the duration of the i-th device state is determined to be abnormal, and the i-th device state corresponding to t0 i is regarded as an invalid state of the i-th device state; When t0 i>T, it is determined that the duration of the i-th device state is normal, and the i-th device state corresponding to t0 i is taken as the valid state of the i-th device state; Wherein, t0i is the duration of the i-th device state in the monitoring period, and T is the preset state judgment threshold.

7. The method for managing operation data of electric field strength monitoring equipment according to claim 6, characterized in that: The step S52 analyzes the device standby time in the next monitoring cycle according to the judgment result of the device operation status validity, wherein: When TC / T0≤u1, the device standby duration of the current monitoring cycle is determined to be normal, and the device standby duration of the next monitoring cycle is set to k0; when TC / T0≥u1, the device standby duration of the current monitoring cycle is determined to be abnormal, if k0≤k1, the device standby duration of the next monitoring cycle is set to k0, if k0>k1, the device standby duration of the next monitoring cycle is set to k2, and when k2≤k1, the value of k2 is k1; Among them, u1 is the first preset proportion, k0 is the standby time of the device in the current monitoring period, and k1 is the preset standby time threshold.

8. The method for managing operation data of electric field strength monitoring equipment according to claim 7, characterized in that: The step S53 provides the user with an abnormal device operation status prompt according to the result of judging the validity of the device operation status, wherein: When TY / T0≤u2, the abnormal state duration of the equipment in the current monitoring period is determined to be normal, and the user is not prompted for abnormal equipment operation status; When TY / T0>u2, it is determined that the duration of the abnormal state of the equipment in the current monitoring period is abnormal, and the user is prompted with the abnormal operation state of the equipment.

9. The method for managing operation data of electric field strength monitoring equipment according to claim 8, characterized in that: In step S6, the method for analyzing the abnormality of the equipment load includes: Step S61, analyzing the abnormality of the equipment load according to the acquired equipment load, and optimizing the analysis process of the effectiveness of the equipment operation status according to the analysis result; Step S62, analyzing the volatility of the equipment load according to the acquired equipment load, and optimizing the analysis process of the equipment load abnormality according to the analysis result; In step S61, the abnormality of the equipment load is analyzed according to the acquired equipment load, and the analysis process of the effectiveness of the equipment operation status is optimized according to the analysis result, wherein: When Fi≤F0, the equipment load level corresponding to t0 i is determined to be normal and no optimization is performed; When Fi>F0, the equipment load level corresponding to t0i is determined to be abnormal, and the judgment process of the effectiveness of the equipment operation status is optimized, and the optimized preset status judgment threshold is set to T', setting: T'=T×{1+ln[(Fi-F0) / (Fi+F0)+1]×cos{arctan[(Fi-F0) / (Fi+F0)]}}; Among them, F0 is the preset load level, Fi is the average value of the equipment load data corresponding to t0 i, J is the number of device load data corresponding to t0i, and fj is the j-th device load data corresponding to t0i.

10. The method for managing operation data of electric field strength monitoring equipment according to claim 9, characterized in that: In step S62, the fluctuation of the equipment load is analyzed according to the acquired equipment load, and the analysis process of the equipment load abnormality is optimized according to the analysis result, wherein: when When t0i is reached, it is determined that the fluctuation of the equipment load data corresponding to t0i is normal and no optimization is performed; when When t0i is reached, the fluctuation of the equipment load data corresponding to t0i is determined to be abnormal, and the analysis process of the equipment load abnormality is optimized, and the optimized preset load level is set to F0', and the setting is: Among them, γ is the preset volatility coefficient.

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