November 18, 2024
A complete thermal imaging inspection workflow includes six steps. The first step is inspection preparation: confirm the thermal camera has sufficient battery power, the infrared lens is clean, and parameters are correctly set (emissivity, reflected temperature, distance, etc.).
A complete thermal imaging inspection workflow includes six steps. The first step is inspection preparation: confirm the thermal camera has sufficient battery power, the infrared lens is clean, and parameters are correctly set (emissivity, reflected temperature, distance, etc.). The second step is equipment identification: number and mark the equipment to be inspected, ensuring consistency of equipment and location across inspections. The third step is data collection: scan according to a predetermined path and sequence, ensuring all critical measurement points are covered. The fourth step is data analysis: compare inspection data with historical data, identifying equipment with abnormal temperatures. The fifth step is report generation: organize inspection results into a report, listing all equipment with abnormal temperatures and recommended maintenance measures. The sixth step is data archiving: file inspection data and reports into the maintenance management system as part of the equipment health record.
Among these six steps, the first and sixth are most easily overlooked. Preparation before inspection directly affects accuracy — if emissivity is set incorrectly, temperature readings will be inaccurate. Data archiving after inspection determines the long-term value of inspection data — if data is not correctly archived, future analysis is impossible.
Equipment temperature baseline is the starting point of thermal imaging inspection. When equipment is first put into operation, conduct a thermal imaging inspection and record the temperature distribution under normal operating conditions. This temperature distribution is the equipment's health baseline — future inspection results can be compared against this baseline.
Several details must be noted when establishing temperature baselines. First, record ambient temperature. The same equipment operates at different normal temperatures under different ambient conditions — if ambient temperature varies significantly, inspection results need temperature correction. Second, record equipment load. Equipment temperature is directly related to load — temperature at full load is significantly higher than at no load. When establishing the baseline, record the load conditions at that time, so future inspections can be conducted under the same or comparable load conditions. Third, record infrared parameters. Infrared parameters such as emissivity, reflected temperature, and inspection distance should be clearly noted in the baseline record, ensuring parameter consistency across inspections.
After the temperature baseline is established, compare current temperature with baseline temperature during each inspection. If temperature deviation exceeds a preset threshold (typically 10°C to 15°C, depending on equipment type), mark it as abnormal and conduct further analysis.
After detecting temperature anomalies, systematic analysis and handling are required. The first step is confirming the authenticity of the anomaly. Exclude external factors such as ambient temperature changes, load variations, and incorrect infrared parameter settings, confirming the temperature anomaly is indeed caused by an equipment issue.
The second step is assessing anomaly severity. Based on temperature deviation magnitude, criticality of the abnormal equipment, and the development trend of the temperature anomaly, classify anomalies into three levels. Level 1 (WARNING): temperature deviation of 10°C to 20°C; equipment can continue operating, but inspection should be arranged during the next maintenance window. Level 2 (ATTENTION): temperature deviation of 20°C to 40°C; inspection frequency should be shortened, with close monitoring of temperature change trends. Level 3 (URGENT): temperature deviation exceeding 40°C, or rapid temperature anomaly development; arrange for immediate shutdown inspection.
The third step is analyzing the cause of the anomaly. Possible causes of temperature anomalies include: loose or corroded electrical connections, increased mechanical friction (such as bearing wear), cooling system failure (such as fan stoppage), insulation aging, and abnormal load. Based on the location, shape, and development trend of the temperature anomaly, the cause can be preliminarily determined.
The fourth step is developing a treatment plan. Based on the cause and severity of the anomaly, develop corresponding treatment measures. For loose electrical connections, the treatment is typically tightening or replacing the connection components. For increased mechanical friction, the treatment is typically lubrication or bearing replacement. For cooling system failure, the treatment is typically cleaning the heat sink or replacing the fan.
The fifth step is verifying treatment effectiveness. After treatment, use the thermal camera to re-inspect, confirming temperature has returned to normal. If temperature has not returned to normal, further troubleshooting is needed.
The value of thermal imaging inspection data lies not only in detecting current temperature anomalies, but more importantly in the analysis and utilization of long-term data. Through analysis of historical inspection data, equipment temperature change trends can be discovered, equipment remaining life can be predicted, and maintenance plans can be optimized.
Trend analysis is the most basic data analysis method. By comparing temperature data of the same equipment at different time points, a temperature change curve can be plotted. If the curve shows an upward trend, it indicates the equipment is aging and maintenance should be scheduled in advance. If the curve suddenly rises in a short period, it may indicate sudden equipment failure, requiring immediate investigation.
Predictive analysis is a more advanced data analysis method. Through statistical analysis of temperature data from a large equipment fleet, a relationship model between temperature and equipment failure rates can be established. Based on this model, the failure probability of equipment under its current temperature state can be predicted, thereby optimizing maintenance prioritization. Data sharing is an important means of increasing data value. Inspection data from different teams can be shared and compared — for example, thermal imaging data from the electrical team can be combined with vibration analysis data from the mechanical team, achieving multi-parameter comprehensive diagnosis.
For maintenance teams, integrate thermal imaging inspections into routine maintenance procedures. Conduct a thermal imaging inspection when new equipment is put into operation, establishing a temperature baseline. During service, determine inspection frequency based on equipment criticality (critical equipment monthly, general equipment quarterly). After each inspection, record temperature data and establish equipment health records. Generate a quarterly temperature report listing all equipment with abnormal temperatures.
For purchasers, when selecting thermal imaging equipment, do not compare initial procurement price alone. Also consider long-term usage costs — including calibration service fees, infrared lens replacement costs, battery life and longevity, and software upgrade policies. A thermal camera that is 20% cheaper but has easily damaged lenses requiring imported replacements may cost more in total ownership.
Finally, the ultimate goal of thermal imaging inspection is not to measure equipment temperature — it is to prevent equipment failure at the wrong moment. To achieve this, inspection data must translate into maintenance action, and maintenance action must have clear owners and deadlines. Only then does thermal imaging inspection truly deliver value. View the Thermal Imaging Detection Instruments Collection
Tell us your project scenario and requirements, and we will match the right solution and provide a quote within 24 hours.
Get a Free QuotePK57 and PK58 fixed industrial thermal imagers, PK61 pocket thermal camera, PK62 infrared thermometer, PK63 handheld high-resolution thermal imager — five series covering the complete needs from online monitoring to rapid field screening. High-precision temperature measurement, multi-scenario compatibility — designed for electrical maintenance, building inspection, industrial R&D, and predictive maintenance.
Explore the Thermal Imaging Detection Instruments →