In industrial conveyor Wireless Sensor Networks (WSNs), ensuring reliable data transmission is crucial for effectively monitoring and controlling industrial processes. However, these networks are vulnerable to various security threats including black hole attacks, where compromised nodes absorb and discard transmitted data, disrupting network integrity and reliability. This paper presents a novel approach for detecting black hole attacks in WSNs using bond graph theory. By representing the WSN as a bond graph, the approach captures the system’s exchanges of data flows, enabling the identification of anomalies indicative of a black hole attack. Through bond graph analysis, the path of the attack is traced to pinpoint the compromised node. Additionally, latency and energy consumption metrics for each node are analyzed to assess the impact of compromised nodes on network performance and overall efficiency.